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Instantaneous movement-unrelated midbrain activity modifies ongoing eye movements

  1. Antimo Buonocore  Is a corresponding author
  2. Xiaoguang Tian
  3. Fatemeh Khademi
  4. Ziad M Hafed
  1. Werner Reichardt Centre for Integrative Neuroscience, Tübingen University, Germany
  2. Hertie Institute for Clinical Brain Research, Tübingen University, Germany
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Cite this article as: eLife 2021;10:e64150 doi: 10.7554/eLife.64150

Abstract

At any moment in time, new information is sampled from the environment and interacts with ongoing brain state. Often, such interaction takes place within individual circuits that are capable of both mediating the internally ongoing plan as well as representing exogenous sensory events. Here, we investigated how sensory-driven neural activity can be integrated, very often in the same neuron types, into ongoing saccade motor commands. Despite the ballistic nature of saccades, visually induced action potentials in the rhesus macaque superior colliculus (SC), a structure known to drive eye movements, not only occurred intra-saccadically, but they were also associated with highly predictable modifications of ongoing eye movements. Such predictable modifications reflected a simultaneity of movement-related discharge at one SC site and visually induced activity at another. Our results suggest instantaneous readout of the SC during movement generation, irrespective of activity source, and they explain a significant component of kinematic variability of motor outputs.

Introduction

A hallmark of the central nervous system is its ability to process an incredibly complex amount of incoming information from the environment in parallel. This is achieved through multiplexing of functions, either at the level of individual brain areas or even at the level of individual neurons themselves. For example, in different motor modalities like arm (Alexander and Crutcher, 1990; Shen and Alexander, 1997; Breveglieri et al., 2016) or eye (Goldberg and Wurtz, 1972b; Goldberg and Wurtz, 1972a; Wurtz and Goldberg, 1972; Mohler and Wurtz, 1976; Bruce and Goldberg, 1985; Jagadisan and Gandhi, 2019) movements, a large fraction of the neurons contributing to the motor command are also intrinsically sensory in nature, hence being described as sensory-motor neurons. In this study, we aimed to investigate the implications of such sensory and motor multiplexing using vision and the oculomotor system as our model of choice.

A number of brain areas implicated in eye movement control, such as the midbrain superior colliculus (SC) (Wurtz and Albano, 1980; Munoz and Wurtz, 1995), frontal eye fields (FEF) (Bruce and Goldberg, 1985; Schall and Hanes, 1993; Schall et al., 1995; Tehovnik et al., 2000), and lateral intra-parietal area (LIP) (Mazzoni et al., 1996), contain many so-called visual-motor neurons. These neurons burst both in reaction to visual stimuli entering into their response fields (RF’s) as well as in association with triggering eye movements towards these RF’s. In some neurons, for example in the SC (Mohler and Wurtz, 1976; Mays and Sparks, 1980; Edelman and Goldberg, 2001; Willeke et al., 2019), even the motor bursts themselves are contingent on the presence of a visual target at the movement endpoint. In the laboratory, the properties of visual and motor bursts are frequently studied in isolation, by dissociating the time of visual onsets (evoking ‘visual’ bursts) from the time of saccade triggering (evoking ‘motor’ bursts). However, in real life, exogenous sensory events can happen at any time in relation to our own ongoing internal state. Thus, ‘visual’ spikes at one visual field location may, in principle, be present at the same time as ‘motor’ spikes for a saccade to another location. What are the implications of such simultaneity? Answering this question is important to clarify mechanisms of readout from circuits in which functional multiplexing is prevalent.

In the SC, our focus here, there have been many debates about how this structure contributes to saccade control (Waitzman et al., 1991; Smalianchuk et al., 2018). In recent proposals (Goossens and Van Opstal, 2006; van Opstal and Goossens, 2008; Goossens and van Opstal, 2012), it was suggested that every spike emitted by SC neurons during their ‘motor’ bursts contributes a mini-vector of movement tendency, such that the aggregate sum of all output spikes is read out by downstream structures to result in a given movement trajectory. However, implicit in these models is the assumption that only action potentials within a narrow time window around movement triggering (the ‘motor’ burst) matter. Any other spiking, by the same or other neurons, before or after the eye movement is irrelevant. This causes a significant readout problem, since downstream neurons do not necessarily have the privilege of knowing which spikes should now count for a given eye movement implementation and which not (Jagadisan and Gandhi, 2019).

Indeed, from an ecological perspective, an important reason for multiplexing could be exactly to maintain flexibility to rapidly react to the outside world, even in a late motor control structure, and there is rich behavioral evidence for this (Miles et al., 1986; Gellman et al., 1990; Masson and Perrinet, 2012; Buonocore et al., 2016; Buonocore et al., 2019). In that sense, rather than invoking mechanisms that allow actively ignoring ‘other spiking’ activity outside of the currently triggered eye movement (whether spatially or temporally), one would predict that SC readout, at any one moment, should be quite sensitive to any spiking activity regardless of its source.

We experimentally tested this hypothesis. We ‘injected’ SC spiking activity around the time of saccade generation, but at a spatially dissociated location, similar in principle to dual-site suprathreshold SC microstimulation to alter saccade metrics (Katnani and Gandhi, 2011; Katnani et al., 2012). We found that the entire landscape of SC activity, not just at the movement burst site, can instantaneously contribute to individual saccade metrics, and in a lawful manner, thus explaining a component of behavioral variability previously unaccounted for. Interestingly, the detailed properties of such contribution depend on the location of the movement-unrelated activity on the SC topographic map relative to the movement burst location. This places important constraints on existing models of saccade generation by the SC, and also allows generating new testable hypotheses about the functional role of SC motor bursts in general.

Results

Stimulus-driven SC ‘visual’ bursts can occur intra-saccadically

We first tested the hypothesis that visually-induced action potentials can occur in the SC intra-saccadically; that is, putatively simultaneously with motor-related bursts. We exploited the topographic nature of the SC in representing visual and motor space (Cynader and Berman, 1972; Robinson, 1972; Chen et al., 2019). We asked two monkeys to maintain steady fixation on a central spot. Prior work has shown that this condition gives rise to frequent microsaccades, which are associated with movement-related bursts in the rostral region of the SC representing small visual eccentricities and movement vectors (Hafed et al., 2009; Hafed and Krauzlis, 2012; Chen et al., 2019; Willeke et al., 2019). In experiments 1 and 2, we then presented a visual stimulus at a more eccentric location, and we recorded neural activity from SC sites representing this location (Figure 1). For experiment 1, the stimulus consisted of a vertical sine wave grating of 2.2 cycles/deg spatial frequency and variable contrast (Chen et al., 2015; Materials and methods). For experiment 2, the stimulus consisted of a high contrast vertical gabor grating of variable spatial frequency and constant contrast (Khademi et al., 2020; Materials and methods). Depending on the timing of the visual burst relative to a given microsaccade, we could measure visual burst strength (in both visual and visual-motor neurons; Materials and methods) either in isolation of microsaccades or when a microsaccade was in-flight. If SC visual bursts could still occur intra-saccadically, then one would expect that visual burst strength should be generally similar whether the burst timing happened when a microsaccade was being triggered or not. We ensured that all sites did not simultaneously burst for microsaccade generation (Figure 1C; Figure 1—figure supplement 1), to ensure that we were only measuring visual bursts and not concurrent movement-related activity. Such movement-related activity was expectedly in more rostral SC sites, representing foveal visual eccentricities (Chen et al., 2019), as we also explicitly demonstrate in our experiment three described later.

Figure 1 with 1 supplement see all
Injecting arbitrary, movement-unrelated spiking activity into the SC map around the time of saccade generation.

(A) A monkey steadily fixated while we presented an eccentric stimulus in a recorded neuron’s RF (red). In experiment 1, the stimulus consisted of a vertical grating of 2.2 cycles/deg spatial frequency, and the stimulus contrast was varied across trials (Chen et al., 2015). In experiment 2, the stimulus consisted of a high contrast vertical grating having either 0.56, 2.2, or 4.4 cycles/deg spatial frequency (Khademi et al., 2020). The stimulus location was spatially dissociated from the motor range of microsaccades being generated (blue). This allowed us to experimentally inject movement-unrelated ‘visual’ spikes into the SC map around the time of microsaccade generation. (B) We injected ‘visual’ spikes at eccentric retinotopic locations (red) distinct from the neurons that would normally exhibit motor bursts for microsaccades (blue). The shown SC topographic map is based on our earlier dense mappings revealing both foveal and upper visual field tissue area magnification (Hafed et al., 2021). (C) Across experiments 1 and 2, we measured ‘visual’ spikes from a total of 128 neurons with RF hotspots indicated by the symbols. The blue line and shaded area denote the mean and 95% confidence interval, respectively, of all microsaccade amplitudes that we observed. The neurons in which we injected ‘visual’ spikes (symbols) were not involved in generating these microsaccades (Figure 1—figure supplement 1; also see Khademi et al., 2020). The origin of the shown log-polar plot corresponds to 0.03 deg eccentricity (Hafed and Krauzlis, 2012). Across experiments 1 and 2, 11 neurons were run on both experiments, 73 neurons were run on only experiment 1, and 44 neurons were run on only experiment 2.

Figure 1—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig1-data1-v2.xlsx

Regardless of microsaccade direction, ‘visual’ bursts could still occur in the SC even if there was an ongoing eye movement. To illustrate this, Figure 2A shows the stimulus-driven visual burst of an example neuron from experiment one with and without concurrent microsaccades. The neuron had a preferred eccentricity of 3.4 deg, and the stimulus in this case consisted of a vertical sine wave grating of 40% or 80% contrast (Materials and methods). The spike rasters in the figure are color-coded depending on whether there were no microsaccades around the visual stimulus onset (gray) or whether there were movements in the same session that temporally overlapped (even partially) with the interval of visual burst occurrence (red); we defined this visual burst interval (for the current study) to be 30–100 ms, and this was chosen based on the firing rate curves also shown in the same figure (bottom). The gray firing rate curve shows average firing rate when there were no microsaccades from −100 ms to +150 ms relative to stimulus onset, and the red curve shows average firing rate when the visual burst (shaded interval) coincided with at least a part of an ongoing microsaccade. As can be seen, intra-saccadic ‘visual’ bursts could still occur, and they were similar in strength to saccade-free visual bursts (t(92) = −0.43, p=0.67 for a t-test on peak firing rate after stimulus onset with and without microsaccades). This was also true regardless of microsaccade direction relative to the RF location (indicated in the figure by the color-coded horizontal lines in the rasters, which highlight movements either towards or away from the RF location). Therefore, intra-saccadic ‘visual’ bursts are possible.

Figure 2 with 1 supplement see all
SC visual bursts still occurred intra-saccadically.

(A) We measured the firing rate of an example neuron (from experiment 1) when a stimulus appeared inside its RF without any nearby microsaccades (gray firing rate curve and spike rasters) or when the same stimulus appeared while microsaccades were being executed around the time of visual burst occurrence (red firing rate curve and spike rasters). The stimulus eccentricity was 3.4 deg. For the red rasters, each trial also has associated with it an indication of microsaccade onset and end times relative to the visual burst (horizontal lines; colors indicate whether the microsaccade was towards the RF or opposite it as per the legend). For all of the movements, the visual burst overlapped with at least parts of the movements. Error bars denote 95% confidence intervals, and the shaded region between 30 and 100 ms denotes our estimate of visual burst interval. There was no statistically significant difference between peak firing rate with and without microsaccades (p=0.67, t-test). The numbers of trials and microsaccades can be inferred from the rasters. (B) For the same example session in A, we plotted the mean radial amplitude (left) and mean radial eye velocity (right) for the microsaccades towards or opposite the RF in A. The black curves show baseline microsaccade amplitude and peak velocity (for movements occurring within 100 ms before stimulus onset). Movements towards the RF were increased in size when they coincided with a peripheral visual burst; our subsequent analyses provide a mechanism for this increase. Opposite microsaccades are also shown, and they were slightly truncated. Error bars denote s.e.m. (C) At the population level, we plotted peak firing rate with saccades detected during a visual burst (y-axis) or without saccades around the visual burst (x-axis). The different symbols show firing rate measurements in either experiment 1 (contrast task) or experiment 2 (spatial frequency task); all neurons from each experiment are shown. Note that some neurons were run on both tasks sequentially in the same session (Figure 1), resulting in a larger number of symbols than total number of neurons.

Figure 2—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig2-data1-v2.xlsx

Interestingly, the microsaccades temporally coinciding with visual burst occurrence in this example session had clearly different metrics from baseline microsaccades, and in a manner that depended on their direction relative to the RF location (Figure 2B). Movements toward the RF location were increased in size (but they were still an order of magnitude smaller than stimulus eccentricity); movements opposite the RF location appeared truncated (they were slightly reduced in size despite a smaller reduction in their peak velocity) (Buonocore et al., 2016; Buonocore et al., 2017). These behavioral observations are consistent with earlier reports (Hafed and Ignashchenkova, 2013; Buonocore et al., 2016; Buonocore et al., 2017; Tian et al., 2018), and the remainder of the current study provides a detailed mechanistic account for them. These observations also occurred for for peripheral stimuli more eccentric than 3.4 deg, as we elaborate shortly.

Across the entire population of neurons recorded from both experiments 1 and 2, we found that ‘visual’ bursts in the SC could occur intra-saccadically. For each neuron, we plotted in Figure 2C peak firing rate after stimulus onset when there was a concurrent microsaccade being generated as a function of peak firing rate when there was no concurrent microsaccade. For this analysis, we pooled trials from the highest three contrasts (20%, 40%, and 80%) in experiment one for simplicity (Materials and methods), but similar conclusions could also be reached for individual stimulus contrasts. Similarly, for the neurons in experiment 2, we also pooled trials from all spatial frequencies (Materials and methods). Note that some neurons were collected in both experiments (Materials and methods), meaning that there are more data points in Figure 2C than actual neurons (as indicated in the figure legend). As can be seen, intra-saccadic ‘visual’ bursts in the SC could still clearly occur. Statistically, we compared all points in Figure 2C and found mild, but significant, modulations of visual burst strength (t(137) = 2.842, p=0.005). Moreover, SC visual bursts could still occur intra-saccadically whether the stimulus was activating the same SC side generating a given movement or the opposite SC side (Figure 2—figure supplement 1). However, expectedly (Chen et al., 2015), there were modulations in visual burst strength that depended on microsaccade direction relative to the RF location. This is consistent with (Chen et al., 2015), although that study aligned microsaccades to stimulus, rather than burst, onset (meaning that it studied slightly earlier microsaccades than the ones that we were interested in here).

Therefore, at the time of movement execution (that is, at the time of a movement-related burst in one part of the SC map; here, the foveal representation associated with microsaccades), it is possible to have spatially dissociated visual bursts in another part of the map. We next investigated how such additional ‘visual’ spikes (at an unrelated spatial location relative to the movements) affected the eye movements that they were coincident with (similar to the example situation that happened in Figure 2B). We also studied whether there was an impact of spatial disparity between the locus of the additional spikes and the movement endpoints.

Peri-saccadic stimulus-driven ‘visual’ bursts systematically influence eye movement metrics

If ‘visual’ bursts can be present somewhere on the SC map at a time when ‘motor’ bursts elsewhere on the map are to be read out by downstream neurons, then one might expect that each additional ‘visual’ spike on the map should contribute to the executed movement metrics and cause a change in saccades. This would suggest a highly lawful relationship between the strength of the peri-saccadic ‘visual’ burst and the amount of eye movement alteration that is observed. We explored this by relating the behavioral properties of the saccades in our task to the temporal relationship between their onset and the presence of ‘visual’ spikes in the SC map caused by an unrelated stimulus onset.

We first confirmed a clear general relationship between microsaccade amplitudes and eccentric stimulus onsets, like shown in the example session of Figure 2B (Hafed and Ignashchenkova, 2013; Buonocore et al., 2017; Tian et al., 2018; Malevich et al., 2020b). Our stimuli in experiment 1 consisted of vertical sine wave gratings having different luminance contrasts (Materials and methods). We plotted the time course of microsaccade amplitudes relative to grating onset for microsaccades that were spatially congruent with grating location (that is, having directions towards grating location; Materials and methods). For the present analysis, we only focused on stimulus eccentricities of ≤4.5 deg because these had the strongest effects on microsaccades (Figure 3); in later analyses, we also explicitly explored the farther eccentricities in more detail, and we found similar results that we describe shortly. As expected (Hafed and Ignashchenkova, 2013; Buonocore et al., 2017; Tian et al., 2018; Malevich et al., 2020b), there was a transient increase in microsaccade amplitude approximately 80–90 ms after grating onset (Figure 3A). Critically, the increase reflected the stimulus properties, because it was stronger with higher stimulus contrast (main effect of contrast: F(2,713) = 81.55, p<1.27427*10−32), and there were also different temporal dynamics: amplitude increases occurred earlier for higher (~75 ms) than lower (~85 ms) contrasts. The increases also occurred, but to a lesser extent, for more eccentric peripheral stimuli (Figure 3—figure supplement 1).

Figure 3 with 3 supplements see all
Microsaccade metrics were altered when the movements coincided with SC visual bursts, and the alteration was related to SC visual burst strength.

(A) Time course of microsaccade amplitude in the contrast task (experiment 1) relative to stimulus onset (for neurons with eccentricities ≤ 4.5 deg). The data were subdivided according to stimulus contrast (three different colors representing the three highest contrasts in our task). Movement amplitudes were small (microsaccades) in the baseline pre-stimulus interval, but they sharply increased after stimulus onset, reaching a peak at around 70–80 ms. Moreover, the metric alteration clearly depended on stimulus contrast. N = 288, 206, and 222 microsaccades for the highest, second highest, and lowest contrast, respectively. (B) Normalized firing rates relative to stimulus onset for the extra-foveal neurons (≤4.5 deg preferred eccentricity) that we recorded simultaneously in experiment one with the eye movement data in A. The alterations in movement metrics in A were strongly related, in both time and amplitude, with the properties of the SC visual bursts. Figure 3—figure supplement 1 shows the results obtained from more eccentric neurons and stimuli (>4.5 deg), and Figure 3—figure supplement 2 shows similar observations from the spatial frequency task (experiment 2). A subsequent figure (Figure 4—figure supplement 3) described the full dependence on eccentricity in our data. Error bars denote 95% confidence intervals.

Figure 3—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig3-data1-v2.xlsx

Because we had simultaneously recorded neural data, we then analyzed, for the same trials, the SC visual bursts that were associated with the appearing gratings in these sessions (Figure 3B). For simplicity, we included all trials (regardless of eye movements) in the illustration of Figure 3B, especially since the visual bursts were largely unaffected whether they occurred intra-saccadically or without any saccadic movements (Figure 2C). The visual bursts started earlier, and were stronger, for higher stimulus contrasts (Figure 3B; Li and Basso, 2008; Marino et al., 2012; Chen et al., 2015), similar to the amplitude changes in the microsaccades (Figure 3A). Moreover, the timing of the microsaccadic effects (Figure 3A) was similar to the timing of the SC visual bursts (Figure 3B), showing a short lag of ~20 ms relative to the bursts that is consistent with an efferent processing delay from SC neurons to the final extraocular muscle drive (Miyashita and Hikosaka, 1996; Jagadisan and Gandhi, 2017; Smalianchuk et al., 2018).

Interestingly, when we experimentally altered the properties of the SC visual bursts by using different stimulus properties, namely spatial frequencies in experiment 2, similar analyses to Figure 3 on microsaccade amplitudes also revealed altered influences on the movements themselves. Specifically, different spatial frequencies are known to give rise to different response strengths and response latencies in SC visual bursts (Chen et al., 2018; Khademi et al., 2020). Consistent with this, the time courses of microsaccade amplitudes reflected clear dependencies on spatial frequency (Figure 3—figure supplement 2A,C). Moreover, there was again a dependence of effects on the eccentricity of the visual bursts (Figure 3—figure supplement 2B,D).

Therefore, as we hypothesized in previous reports (Hafed and Ignashchenkova, 2013; Buonocore et al., 2017; Malevich et al., 2020b), not only is it possible for SC visual bursts to occur intra-saccadically (Figure 2), but such bursts are temporally aligned with concurrent changes in microsaccade amplitudes (Figure 3). We next uncovered a highly lawful impact of each injected extra ‘spike’ per recorded neuron on saccade metrics.

There is a linear relationship between intra-saccadic ‘visual’ spikes and eye movement amplitude increases

The number of extra ‘visual’ spikes per recorded neuron occurring intra-saccadically was linearly related to metric alterations in microsaccades. For each eye movement toward the recently appearing stimulus (that is, congruent with stimulus location), we counted how many ‘visual’ spikes by the concurrently recorded neuron occurred in the interval 0–20 ms after movement onset. That is, we tested for the impact of the number of extra ‘visual’ spikes by a given recorded neuron as the SC population was being read out, intra-saccadically, by downstream pre-motor and motor structures to execute the currently triggered movement. This per-neuron spike count was a proxy for how adding additional ‘visual’ spikes in the SC population at a site unrelated to the movement vector can ‘leak’ downstream when the saccade gate is opened; this is, in fact, the reason why we picked such a strict intra-saccadic period of 0–20 ms after movement onset (subsequent analyses explored the full time course of impacts expected from movement-unrelated SC activity on the eye movement metrics). Moreover, since the extra spikes were more eccentric than the sizes of the congruent microsaccades (Figure 1), we expected that the contribution would act to increase microsaccade amplitudes (as in Figure 3A). We focused, for now, on neurons at eccentricities ≤ 4.5 deg (but still more eccentric than microsaccade amplitude; Figure 1B,C) because our earlier analyses showed that the clearest metric changes to tiny microsaccades occurred under these circumstances (Figure 3, Figure 3—figure supplements 13).

We found a clear, lawful relationship between the amount of ‘extra’ spikes that occurred intra-saccadically and movement metrics. These spikes were unrelated to the originally planned ‘motor’ burst; they were spatially dissociated but temporally coincident with saccade triggering, and they were also driven by an exogenous visual stimulus onset. To demonstrate this observation, we plotted in Figure 4A the average microsaccadic eye movement trajectory in the absence of any additional SC ‘visual’ bursts during experiment 1 (dark red; the curve labeled 0 spikes; Methods). These ‘0 spike’ microsaccades were, like all other movements in Figure 4A, movements that occurred shortly after stimulus onset (Materials and methods); they just happened to not have any ‘visual’ spikes occurring during the first 20 ms of their execution. These microsaccades were also all towards the eccentric RF location. We then plotted average microsaccade size whenever any given recorded eccentric neuron had a visual burst such that 1 spike of this visual burst happened to occur in the interval 0–20 ms after movement onset (red; 1 spike). The amplitude of the microsaccade was significantly larger than with 0 spikes. We then progressively looked for movements with 2, 3, 4, or 5 ‘visual’ spikes per recorded neuron; there were progressively larger and larger microsaccades (Figure 4A). Therefore, for microsaccades towards the eccentric RF location, there was a lawful relationship between intra-saccadic ‘visual’ spikes and movement amplitude.

Figure 4 with 4 supplements see all
The number of exogenous, movement-unrelated ‘visual’ spikes to occur intra-saccadically linearly added to the executed movement’s amplitude.

(A) For every recorded neuron from experiment 1 (Figure 3A,B) and every microsaccade to occur near the visual burst interval (Figure 2), we counted the number of spikes recorded from the neuron that occurred intra-saccadically (0–20 ms after movement onset). We did this for movements directed towards the RF location (Figure 1C; Materials and methods). We then plotted radial eye position (aligned to zero in both the x- and y-axes) relative to saccade onset after categorizing the movements by the number of intra-saccadic spikes. When no spikes were recorded during the eye movement, saccade amplitudes were small (darkest curve). Adding ‘visual’ spikes into the SC map during the ongoing movements systematically increased movement amplitudes. Error bars denote s.e.m. (B) To summarize the results in A, we plotted mean saccade amplitude against the number of intra-saccadic ‘visual’ spikes for movements directed towards the RF locations (faint red dots). There was a linear increase in amplitude with each additional spike per recorded neuron (orange line representing the best linear fit of the underlying raw data). Even intra-saccadic spikes from visual neurons (more dissociated from the motor output of the SC than visual-motor neurons) were still associated with increased amplitudes (Figure 4—figure supplement 1). For movements opposite the RF locations (faint green dots and green line), there was no impact of intra-saccadic ‘visual’ spikes on movement amplitudes. The numbers of movements contributing to each x-axis value are 1772, 383, 237, 145, 113, and 78 (towards) or 1549, 238, 104, 63, 36, 23 (opposite) for 0, 1, 2, 3, 4, and 5 spikes, respectively. (C) For the movements towards the RF locations (A), peak radial eye velocities also increased, as expected (Buonocore et al., 2017). Error bars denote one standard error of the mean (A, C) and 95% confidence intervals (B). Figure 4—figure supplement 2 shows results for intra-saccadic spikes from more eccentric neurons (>4.5 deg), and Figure 4—figure supplement 3 shows the full dependence on neuronal preferred eccentricity. Finally, Figure 4—figure supplement 4 shows the same analyses of B but for the data from experiment 2.

Figure 4—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig4-data1-v2.xlsx

Across all data from experiment 1, the number of ‘visual’ spikes (per recorded neuron) that occurred intra-saccadically was monotonically and linearly driving the amplitude increase of the (smaller) saccades (Figure 4B) (Towards condition, F-statistic vs. constant model: F = 426, p<0.0001; estimated coefficients: intercept = 0.14253, t = 28.989, p<0.0001; slope = 0.066294, t = 20.644, p<0.0001); this relationship also held when we excluded the ‘0 spike’ movements from the analysis. Incidentally, the peak velocities of the movements also increased systematically (Figure 4C), consistent with previous behavioral observations (Buonocore et al., 2017). On the other hand, microsaccades directed opposite to the RF (Figure 4B) did not show a similar large positive slope; and a trend for a negative slope was not statistically significant (Opposite condition, F-statistic vs. constant model: F = 2.22, p=0.137; estimated coefficients: intercept = 0.1185, t = 56.261, p<0.0001; slope = −0.0028872, t = −1.488, p=0.137). This suggests that it is difficult to reduce microsaccade size below the already small amplitude of these tiny eye movements (Hafed, 2011).

These results suggest that there is an instantaneous specification of saccade metrics described by the overall activity present on the SC map, and they provide a much more nuanced view of the correlations between SC visual bursts and microsaccade amplitudes shown in Figures 2B and 3. Every SC spike matters: all activity happening intra-saccadically and at locations of the SC map different from the saccade endpoint goal is interpreted as part of the motor command by downstream neurons. Most interestingly, visual spiking activity in even purely visual neurons was still positively correlated with increased microsaccade amplitudes, although the effect was weaker than that of visual spiking activity in the deeper visual-motor neurons of the SC (Figure 4—figure supplement 1). This difference between visual and visual-motor neurons makes sense in hindsight: the visual-motor neurons are presumed to be much closer to the output of the SC than the visual neurons (Mohler and Wurtz, 1976).

We also considered the same analyses as in Figure 4 (that is, with congruent movements, and also including the ‘0 spike’ trials) but for more eccentric SC ‘visual’ bursts (Figure 4—figure supplement 2). The effects were still present but with a notably smaller slope than in Figure 4, suggesting that the distance of the ‘extra’ spiking activity on the SC map from the planned movement vector matters (Towards condition, F-statistic vs. constant model: F = 45.1, p<2.03*10−11; estimated coefficients: intercept = 0.12368, t = 57.252, p<0.0001; slope = 0.0098876, t = 6.7195, p<2.024*10−11). This observation, while still showing that every spike matters, is not predicted by recent models of saccade generation by the SC (Goossens and Van Opstal, 2006; van Opstal and Goossens, 2008; Goossens and van Opstal, 2012), which do not necessarily implement any kind of local versus remote interactions in how the SC influences saccade trajectories through individual spike effects.

In fact, we found an almost sudden change in local versus remote interactions in terms of readout. Specifically, for all microsaccades towards the RF location from experiment 1, we repeated analyses similar to Figure 4B, but now taking neuronal preferred eccentricity into account. We added eccentricity to our generalized linear model analysis, and there was a significant interaction between eccentricity and the number of injected spikes (slope = −0.0080709, t = −14.585, p<0.0001): the slope of the relationship between the number of ‘injected’ visual spikes and microsaccade amplitude decreased as a function of increasing eccentricity. To visualize this, we created a running average of neuronal preferred eccentricity. For each eccentricity range, we then re-analyzed the data as we did for Figure 4B. In all cases, there was a linear relationship between each additional ‘injected’ visual spike and microsaccade amplitude (Figure 4—figure supplement 3A), consistent with Figure 4B. However, the slope of the relationship decreased with increasing eccentricity. This is better demonstrated in Figure 4—figure supplement 3B, in which we plotted the slope parameter of the generalized linear model as a function of eccentricity. For eccentricities larger than approximately 4–5 deg, there was a weaker impact of additional ‘injected’ visual spikes on microsaccade amplitudes than for smaller eccentricities (which justifies our choice in other figures to focus on neurons with preferred eccentricities ≤ 4.5 deg). However, and most critically, the slope always remained positive. This means that there was never a negative impact of ‘injected’ visual spikes on microsaccade amplitudes. The readout always involved ‘adding’ to the movement amplitude. We also confirmed this conclusion with yet more data from experiment three having eccentric stimuli, as we discuss shortly when describing the results from that experiment (e.g. Figures 8–12), and also with additional analyses of experiments 1 and 2 (e.g. see Figure 6 below).

As stated above, the observations of Figure 4—figure supplement 3 are not easy to reconcile with recent models of SC readout for saccadic eye movements (Goossens and Van Opstal, 2006; van Opstal and Goossens, 2008; Goossens and van Opstal, 2012). They are also not easily reconcilable with classic vector averaging models as well (Lee et al., 1988; Brecht et al., 2004; Walton et al., 2005; Katnani et al., 2012). However, we think that these observations are rendered plausible with newer ideas (Jagadisan and Gandhi, 2019) on temporal alignment of population activity in the SC at the time of saccade triggering, as we explain in Discussion.

Finally, and for completeness, we repeated the same analyses of Figure 4, but this time for the neurons collected during experiment 2. The results are shown in Figure 4—figure supplement 4, and they are all consistent with the results that we obtained from Figure 4. Therefore, there was a clear and lawful relationship between the number of ‘injected’ visual spikes injected into the SC map by each active neuron and the executed movement amplitude.

Tight temporal alignment between ‘visual’ spikes and movement onsets is needed for the spikes to alter eye movements

To further investigate the results of Figure 4 and its related figure supplements, we next explored more detailed temporal interactions between SC visual bursts and saccade metric changes. Across all trials from all neurons analyzed in Figure 4 (i.e. ≤4.5 deg eccentricity and in experiment 1), we measured the time of any given trial’s visual burst peak relative to either microsaccade onset (Figure 5A), microsaccade peak velocity (Figure 5B), or microsaccade end (Figure 5C), and we sorted the trials based on burst peak time relative to microsaccade onset (i.e. the trial sorting in all panels in Figure 5 was always based on the data from panel A). We then plotted individual trial spike rasters with the bottom set of rasters representing trials with the SC ‘visual’ burst happening much earlier than microsaccade onset and the top set being trials with the SC ‘visual’ burst occurring after microsaccade end. The rasters were plotted in gray in Figure 5, except that during a putative visual burst interval (30–100 ms from stimulus onset), we color-coded the rasters by the microsaccade amplitude observed in the same trials (same color coding scheme as in Figure 4A; note that if there was no spike in the measurement interval for a given trial, then there was no coloring made in the figure). The marginal plot in Figure 5D shows microsaccade amplitudes for the sorted trials (Materials and methods). We used this marginal plot as a basis for estimating which sorted trials were associated with the beginning of microsaccade amplitude increases (from the bottom of the raster and moving upward) and which trials were associated with the end of the microsaccade amplitude increases (horizontal blue lines; Materials and methods). As can be seen, whenever SC ‘visual’ bursts occurred pre- and intra-saccadically, microsaccade amplitudes were dramatically increased by two- to three-fold relative to baseline microsaccade amplitudes (blue horizontal lines). For visual bursts after peak velocity (Figure 5C), the effect was diminished, consistent with efferent delays from SC activity to extraocular muscle activation (Miyashita and Hikosaka, 1996; Munoz et al., 1996; Stanford et al., 1996; Gandhi and Keller, 1999b; Katnani and Gandhi, 2012; Jagadisan and Gandhi, 2017; Smalianchuk et al., 2018). The same results were obtained when we repeated the same analyses for the neurons collected during experiment 2 (Figure 5—figure supplement 1).

Figure 5 with 2 supplements see all
Exogenous, movement-unrelated SC spikes had the greatest impact on movement metrics when they occurred peri-saccadically.

(A) Individual trial spike rasters across all neurons ≤ 4.5 deg in eccentricity and all movements towards RF locations from experiment 1. The spike rasters are sorted based on the time of the visual burst (peak firing rate after stimulus onset) relative to saccade onset (bottom left: trials with visual bursts earlier than microsaccades; top right: trials with visual bursts later than microsaccades). The spike rasters are plotted in gray except during the interval 30–100 ms after stimulus onset (our visual burst interval; Figure 2) to highlight the relative timing of the visual burst to movement onset. Spikes in the visual burst interval are color-coded according to the observed movement amplitude on a given trial (legend on the left). As can be seen, microsaccades were enlarged when extra-foveal SC spiking (stimulus-driven visual bursts) occurred right before and during the microsaccades (see marginal plot of movement amplitudes in D). (B) Same as A, and with the same trial sorting, but with burst timing now aligned to movement peak velocity. (C) Same as A, B, and with the same trial sorting, but with burst timing now aligned to movement end. The biggest amplitude effects occurred when the exogenous ‘visual’ spikes occurred pre- and intra-saccadically, but not post-saccadically. (D) Microsaccade amplitudes (20-trial moving average) on all sorted trials in A–C. Blue horizontal lines denote the range of trials for which there was a significant increase in movement amplitudes (Materials and methods). Note that the numbers of trials are evident in figure. Figure 5—figure supplement 1 shows similar results from experiment 2, and Figure 5—figure supplement 2 shows similar results from the far neurons of experiment 1.

Figure 5—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig5-data1-v2.xlsx

Importantly, in our earlier analyses (Figure 3—figure supplement 1; Figure 4—figure supplements 2 and 3), we had observed that the effects with more eccentric visual bursts on microsaccade amplitudes were still present, albeit with a significantly weaker magnitude. This would suggest that the same temporal relationship between the injected spikes and the movement amplitudes should still exist for the far neurons. This was indeed the case, as demonstrate in Figure 5—figure supplement 2. In this figure, we repeated the same analyses of Figure 5 but only for neurons with eccentricities > 4.5 deg. We still found that it was the pre- and intra-saccadic injected ‘visual’ spikes that were associated with the increased microsaccade amplitudes. The tight temporal relationship did not depend on the eccentricity of the injected ‘visual’ spikes.

Therefore, our results so far suggest that at the time at which SC activity is to be read out by downstream neurons to implement a saccadic eye movement (right before movement onset to right before movement end, e.g. Miyashita and Hikosaka, 1996; Munoz et al., 1996; Stanford et al., 1996; Gandhi and Keller, 1999b; Katnani and Gandhi, 2012; Jagadisan and Gandhi, 2017; Smalianchuk et al., 2018), additional movement-unrelated SC spiking activity is also read out and has a direct impact on eye movement metrics.

Having said that, one problem with the analysis of Figure 5 is that our ‘visual burst interval’ was still arbitrarily defined as a period 30–100 ms after stimulus onset (Figure 2). In reality, spiking activity could vary with different stimulus parameters like stimulus contrast or spatial frequency (e.g. Figure 3 and its associated figure supplements). Therefore, to obtain even more precise knowledge of the time needed for any injected ‘visual’ spikes to start influencing microsaccade metrics, we next selected all individual trial spike rasters from Figure 5A (i.e. experiment 1), and we counted the number of spikes occurring within any given 5 ms time bin relative to eye movement onset. We did this for all time bins between −100 ms and +100 ms from movement onset, and we also binned the movements by their amplitude ranges (Figure 6A). The two smallest microsaccade amplitude bins reflected baseline movement amplitudes (see Figure 3A), and they expectedly occurred when there was no ‘extra’ spiking activity in the SC around their onset (Figure 6A, two darkest reds). For all other amplitude bins, the larger movements were always associated with the presence of extra ‘visual’ spikes on the SC map (more eccentric than the normal microsaccade amplitudes) occurring between −30 ms and +30 ms from saccade onset (Figure 6A). Note how the timing of the effect was constant across amplitude bins, suggesting that it was the relative timing of extra ‘visual’ spikes and movement onset that mattered; the amplitude effect (that is, the different colored curves) simply reflected the total number of spikes that occurred during the critical time window of movement triggering. This is consistent with Figure 4 and also with new ideas related to population temporal alignment in the SC (Jagadisan and Gandhi, 2019). Therefore, additional ‘visual’ spikes in the SC at a time consistent with saccade-related readout by downstream neurons essentially ‘leak’ into the saccade being generated.

Figure 6 with 2 supplements see all
Exogenous, movement-unrelated ‘visual’ spikes affected movement metrics when they occurred within approximately ±30 ms from movement onset.

(A) For the different microsaccade amplitude ranges from Figure 5 (color-coded curves), we counted the number of exogenous spikes occurring from a recorded extra-foveal SC neuron (≤4.5 deg) within any given 5 ms time bin around movement onset (range of times tested: −100 ms to +100 ms from movement onset). The lowest two microsaccade amplitude ranges (0.1–0.2 and 0.2–0.3 deg) reflected baseline amplitudes during steady-state fixation (e.g. Figure 3), and they were not correlated with additional extra-foveal spiking activity around their onset (two darkest red curves). For all other larger microsaccades, they were clearly associated with precise timing of extra-foveal ‘visual’ spikes occurring within approximately ±30 ms from movement onset, regardless of movement size. The data shown are from experiment 1; similar observations were made from experiment 2 (Figure 6—figure supplement 1). The number of movements contributing to this figure is the same as in Figure 5. (B) Same as A but for movements opposite the recorded neuron’s RF locations. There were fewer spikes during the peri-saccadic interval, suggesting that it was easier to trigger eye movements when there was no activity present in the opposite SC. Figure 6—figure supplement 2 shows similar results from the far neurons (>4.5 deg eccentricity) of the same experiment (experiment 1).

Figure 6—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig6-data1-v2.xlsx

On the other hand, the pattern of Figure 6A was not present for movements going opposite to the recorded neuron’s RF’s, for which, if anything, there was a lower number of spikes happening during the peri-saccadic interval (Figure 6B). This suggests that it was easier to trigger microsaccades in one direction when no activity was present in the opposite SC. Moreover, all these effects were directly replicated with the spatial frequency task as well (experiment 2; Figure 6—figure supplement 1).

Once again, when we repeated the analyses of Figure 6 but now for only the far neurons from the same experiment, we got a qualitatively and quantitatively similar result (Figure 6—figure supplement 2). This is an important finding because it suggests that once a movement-unrelated spike is properly temporally aligned with the motor burst, it can still have a similar behavioral impact on movement amplitudes whether the spike was far or near in eccentricity. This suggests that the global reduction of behavioral effects that we saw with more eccentric stimuli (e.g. Figure 3—figure supplement 1) could reflect a reduced likelihood of temporal alignment between the ‘visual’ spikes and the population of neurons bursting as part of the movement command. As stated above, this idea of temporal alignment is consistent with recent novel hypotheses about the role of SC population temporal alignment in enabling the triggering of saccades (Jagadisan and Gandhi, 2019; see Discussion).

Any peri-saccadic ‘visual’ spikes, even outside of ‘visual’ bursts, influence ongoing eye movements

The strongest evidence that any ‘extra’ spiking activity present on the SC map can systematically alter the amplitude of the eye movements, irrespective of our experimental manipulation of visual bursts, can be seen from the analyses of Figure 7. Here, we exploited an important property of experiment 2: the presented stimulus remained on the display inside a neuron’s RF for a substantial period of time of up to 1300 ms (sometimes up to 3000 ms) (Khademi et al., 2020). This meant that after the initial visual bursts had subsided, SC neurons maintained a lower level of ‘sustained’ discharge for a prolonged period of time, a discharge that was often absent in the absence of stimuli since some SC neurons do not exhibit any baseline discharge. This meant that we could now ask whether SC activity long after the visual bursts was still read out at the time of movement triggering (i.e. whether the previous results in Figures 26 were contingent on ‘bursting’ activity in the SC, or whether any spiking could still matter).

Figure 7 with 1 supplement see all
Exogenous, movement-unrelated spikes influenced eye movement metrics even when they did not occur within stimulus-driven ‘visual’ bursts.

(A) In experiment 2, we had a prolonged period of fixation after stimulus onset. This meant that there was low-level discharge present in the SC long after the end of the initial ‘visual’ burst, as shown in this example neuron (spike raster and average firing rate across trials with the preferred spatial frequency in the RF; error bars denote s.e.m.). This allowed us to select all microsaccades occurring >550 ms after stimulus onset, and to ask whether movement-unrelated SC spiking activity that was coincident with these movements still influenced their metrics. (B) For the example neuron in A and for microsaccades > 550 ms after stimulus onset and towards the RF, we performed an analysis like that of Figure 4B. There was a positive correlation between the number of intra-saccadic spikes and movement amplitude. Note that we combined trials with the lowest two spatial frequencies to increase the numbers of observations in this analysis. The numbers of movements contributing to each x-axis point are 62, 10, and 4 microsaccades for 0, 1, and 2 spikes, respectively. (C) Same as B but for movements opposite the RF from the same session. The numbers of movements contributing to each x-axis point are 77, 20, and 1 microsaccades for 0, 1, and 2 spikes, respectively. (D) Relationship between the number of intra-saccadic SC ‘sustained’ spikes (i.e. not part of ‘visual’ bursts) and microsaccade amplitudes for eye movements triggered >550 ms after grating onset from all sessions of experiment 2. We included trials from all spatial frequencies. For each microsaccade towards the RF location, we counted how many ‘sustained’ spikes were emitted by a given recorded neuron in the interval 0–20 ms after microsaccade onset. We then plotted microsaccade amplitude as a function of intra-saccadic ‘sustained’ spikes. Even when the spikes occurred outside of ‘visual’ bursts, they still had an influence on movement metrics. The numbers of movements contributing to each x-axis point are 4009, 747, 226, 62, and 26 microsaccades for 0, 1, 2, 3, and 4 spikes, respectively. (E) Same as D but for movements opposite the RF location. There was no increase in microsaccade amplitude. The numbers of movements contributing to each x-axis point are 4114, 721, 157, 45, and 16 microsaccades for 0, 1, 2, 3, and 4 spikes, respectively. Error bars in B–D denote 95% confidence intervals.

Figure 7—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig7-data1-v2.xlsx

Consider, for example, the neuron in Figure 7A, which showed robust sustained activity for its preferred spatial frequency. We selected all microsaccades occurring >550 ms after stimulus onset in this neuron. We then asked whether we could replicate results similar to those in Figure 4B, but only for these movements occurring outside of the early ‘visual’ bursts. In Figure 7B, we plotted results for movements towards the RF location (this time, combining the lowest two spatial frequencies to increase our data availability, especially because sustained discharge is significantly lower in firing rate than burst discharge). And, in Figure 7C, we plotted movements opposite the RF location. The ‘towards movements’ were increased in amplitude with every injected extra spike from the ‘sustained’ discharge of the recorded neuron (F-statistic vs. constant model: F = 383, p=0.0325; estimated coefficients: intercept = 0.1105, t = 17.67, p=0.0360; slope = 0.0948, t = 19.57, p=0.0324), whereas opposite movements were not (F-statistic vs. constant model: F = 6.15, p=0.2440; estimated coefficients: intercept = 0.1348, t = 24.49, p=0.0250; slope = −0.0101, t = −2.47, p=0.2440). Another example neuron’s results are shown in Figure 7—figure supplement 1, and both neurons were consistent with each other. Therefore, there was actually no need for a stimulus-driven visual burst to be present in the SC for us to observe effects of extraneous spiking activity on triggered eye movements. Even when the spikes were no longer strongly associated with the stimulus-induced visual burst (i.e. with stimulus onset), their presence on the SC map at a site more eccentric than microsaccade amplitudes was enough to modulate eye movement amplitudes in a systematic manner, increasing the amplitude above baseline levels when more spikes were present.

Across all neurons collected from experiment 2, in which we had the opportunity to look for spiking outside of the ‘burst’ intervals due to the longer trial durations, we found robust effects of individual neuronal spiking and microsaccade amplitudes (Figure 7D,E). These results were also statistically validated. For movements towards the RF, every additional ‘sustained’ spike linearly increased microsaccade amplitude with a slope of 0.0126 deg/spike (F-statistic vs. constant model: F = 13.1, p=0.0364; estimated coefficients: intercept = 0.1098, t = 12.87, p=0.0010; slope = 0.0126, t = 3.61, p=0.0363). Such modulation was again not visible for movements going in the opposite direction from the recorded neuron’s RF’s (Figure 7E), again suggesting that there is a lower limit to how small microsaccades can become with opposite drive from the other SC (F-statistic vs. constant model: F = 5, p=0.1110; estimated coefficients: intercept = 0.1169, t = 13.31, p=0.0009; slope = −0.0080, t = −2.23, p=0.1112).

Of course, quantitatively, the impact of each spike in Figure 7D (for ‘towards’ movements) was smaller in magnitude than the impact of each spike in Figure 4B (for similar ‘towards’ movements). In other words, a single spike during the ‘sustained’ discharge caused a smaller microsaccade amplitude increase than a single spike during ‘burst’ discharge. However, this is fully expected: during the visual bursts, a large population of SC neurons are expected to be bursting simultaneously (Lee et al., 1988); on the other hand, during ‘sustained’ discharge, different individual neurons may or may not be simultaneously active depending on a variety of factors related to their individual spatio-temporal RF properties (Churan et al., 2012). Thus, a smaller population of simultaneously spiking neurons is expected. In that regard, the results of Figure 7D,E provide the most compelling evidence in our experiments so far that every additional SC spike that is available at movement triggering can alter movement metrics.

To summarize the overall results so far, we found that there is a tight time window around saccade onset (Figures 57) in which any movement-unrelated spikes in sites other than the saccade goal representation can induce a systematic variation in the motor program.

Saccade-related movement bursts occur simultaneously with stimulus-driven ‘visual’ bursts at separate SC sites

Our results demonstrate that as little as one single extra action potential by each visually activated neuron was sufficient, within a specific time window, to alter ongoing microsaccades (Figures 47). However, it still remains unclear whether the movement bursts for these microsaccades did indeed occur in the SC or not. In other words, in all of the above experiments, our primary hypothesis was that the visual bursts ‘added’ to movement-related bursts elsewhere on the SC map (in our case, in the rostral SC) in order to alter the movement metrics. We believe that this is a reasonable hypothesis. However, past work might predict otherwise: that visual bursts in the caudal SC, representing the eccentric stimulus locations (e.g. Figures 1 and 2), should actually reduce activity in other distant SC sites associated with the movement plans (Dorris et al., 2007). From the perspective of microsaccades, this alternative mechanism would mean a reduction of rostral SC activity rather than an increase, since microsaccade-related discharge occurs in the rostral SC (Hafed et al., 2009; Hafed and Krauzlis, 2012; Willeke et al., 2019). Indeed, in the absence of any microsaccades, a peripheral stimulus onset is known to be associated with both a visual burst in the caudal SC as well as a reduction in firing activity in the rostral SC (Munoz and Istvan, 1998; Hafed and Krauzlis, 2008). Moreover, slice work in rodents suggests the existence of potential lateral inhibition mechanisms in at least some SC layers, consistent with this prior evidence (Isa and Hall, 2009; Kasai and Isa, 2016). Might it then be the case that our hypothesis of ‘added’ spikes to the readout is invalid, and that rostral SC activity actually did not burst for our microsaccades?

To directly test this, in experiment 3, we conducted additional recordings using multielectrode arrays inserted into either the rostral SC (representing microsaccade amplitude ranges), the caudal SC (representing eccentric locations associated with ‘visual’ bursts), or both simultaneously (Figure 8). In this case, we presented a white disc of radius 0.5 deg peripherally during maintained fixation (Materials and methods). During rostral SC recordings, we placed the peripheral stimulus at 10 deg eccentricity either to the right or left of fixation across the different trials (i.e. very far in eccentricity from the movement endpoints). During caudal SC and simultaneous rostral and caudal SC recordings, we placed the peripheral stimulus either at the visual field location represented by the caudal SC site (i.e. inside the visual RF’s) or at the diametrically opposite location.

Exploring both movement-related and stimulus-driven SC discharge at the time of microsaccade triggering.

(A) We inserted microelectrode arrays into either the rostral SC (example shown in the right rostral SC) or the caudal SC. We then ran a behavioral fixation task in which the monkey fixated and a peripheral stimulus appeared on either side of fixation (Materials and methods). This meant that we injected ‘visual’ bursts in either the right or left caudal SC across trials (red), allowing us to measure either rostral SC or caudal SC activity when the injected ‘visual’ spikes occurred coincidentally with triggered microsaccades (same logic as in Figure 1). The caudal SC recordings were meant to support the earlier figures by demonstrating that intra-saccadic visual bursts could still occur in the SC; the rostral SC recordings were meant to investigate what happens to movement-related bursts at the time of the peripheral visual bursts. (B) In yet another set of experiments, and using the same behavioral task, we inserted two sets of microelectrode arrays simultaneously into both the rostral and caudal SC together. This allowed us to confirm the results from A using simultaneous rostral and caudal recordings. The shown topographic map of the SC is based on our earlier dense mappings, demonstrating both foveal (Chen et al., 2019) and upper visual field (Hafed and Chen, 2016) tissue area magnification.

We confirmed that movement-related discharge still occurred simultaneously with peripheral ‘visual’ bursts in the SC. For example, Figure 9 shows two example neurons recorded from the rostral SC. In Figure 9A, we show the movement-related RF of the neuron, which was recorded from the right SC. The neuron preferred primarily horizontal leftward microsaccades. For these microsaccades, the neuron exhibited expected peri-microsaccadic elevations in activity (Hafed et al., 2009; Hafed and Krauzlis, 2012; Willeke et al., 2019) in a standard RF mapping task (Methods; Figure 9B). We then asked what happened to this neuron’s activity in the main task of experiment three when peripheral stimuli were presented in the absence of any microsaccades during a peri-stimulus interval (−50–200 ms). Consistent with prior observations (Munoz and Istvan, 1998; Dorris et al., 2007; Hafed and Krauzlis, 2008) the neuron indeed decreased its activity (Figure 9C). However, and most critically, on the rare occasions in which microsaccades towards the movement RF occurred 30–100 ms after stimulus onset (i.e. coincident with peripheral visual bursts; Figures 26), the neuron actually still burst and did not decrease its activity (Figure 9D). This means that when we aligned these same trials’ activity profiles to stimulus onset rather than to microsaccade onset (Figure 9E), we found that the neuron actually increased, rather than decreased, its activity at the same time as the presumptive caudal SC visual burst. In other words, there were two ‘bursts’ in the SC: one in the rostral SC and one in the caudal SC. Naturally, because microsaccades happened at variable times relative to stimulus onset in Figure 9E (also see Figure 2A), the activity increase was temporally smeared (giving rise to what appeared like transient modulations) when aligned to stimulus, rather than to microsaccade, onset.

Rostral SC activity still exhibited bursts for microsaccades at the same time as caudal SC visual bursts.

(A) Example movement-related RF of a rostral SC neuron in the right SC (obtained from an RF mapping task; Materials and methods). Peak peri-microsaccadic firing rate is shown as a function of microsaccade radial amplitude and direction. Movement dimensions are plotted on log-polar axes (Hafed and Krauzlis, 2012), and the origin represents 0.03 deg radial amplitude. The neuron preferred leftward horizontal microsaccades. (B) After obtaining a movement RF like in A, we fitted the RF with a two-dimensional gaussian function (Materials and methods), and we then selected all microsaccades to a region within 2 s.d. of the fitted gaussian’s peak. We then plotted firing rates as a function of time from microsaccade onset, confirming movement-related discharge (Hafed et al., 2009; Willeke et al., 2019). (C) When a peripheral stimulus appeared in the main task of experiment three and no microsaccades occurred within −50–200 ms from stimulus onset, the neuron reduced its activity, consistent with earlier reports (Munoz and Istvan, 1998; Dorris et al., 2007; Hafed and Krauzlis, 2008). (D) However, the same neuron still exhibited a movement-related burst if the microsaccades towards its movement RF occurred within the visual burst interval associated with stimulus onset. (E) Thus, when aligned to peripheral stimulus onset, the neuron could either reduce its activity if microsaccades did not occur (blue curves), or it could increase its activity if microsaccades to the movement RF occurred (red). (F–J) Similar observations for a second example rostral SC neuron, this time in the left rostral SC. Note that for this particular example neuron, the visual burst interval that we picked was slightly modified because of a rarity of microsaccades of appropriate direction, but the same conclusions were reached as in the first example neuron (also see Figure 11). Error bars denote s.e.m.

Figure 9—source data 1

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Almost identical observations were made for a second example rostral SC neuron, now from the left SC (Figure 9F–J). Therefore, at the time of peripheral visual bursts, it is still possible to observe movement-related bursts in another location in the SC map. This is consistent with the idea that local excitation dominates lateral connectivity patterns in the deeper motor-related layers of the SC (Phongphanphanee et al., 2014), which seems particularly useful (at the expense of long-range inhibition) for rapid burst generation.

To even further support the above conclusion, we recorded from both the caudal and rostral SC simultaneously in some sessions (in addition to other sessions in which we only recorded the caudal SC, in order to confirm our earlier observations in Figure 2 that peripheral visual bursts could still occur simultaneously with triggered microsaccades). Figure 10 shows an example pair of neurons that were recorded simultaneously from the same task of Figures 8 and 9. The caudal neuron is shown in the top row of the figure (Figure 10A–C), and the rostral neuron is shown in the bottom row (Figure 10D–F). Based on the visual RF of the caudal neuron (Figure 10A), which was at an eccentricity of approximately 6 deg, we placed the stimulus inside this RF, and we measured the response when there were microsaccades being triggered towards the movement field of the rostral neuron (shown in Figure 10D from the RF mapping task). In other words, in Figure 10B, a peripheral stimulus appeared inside the visual RF of the caudal neuron, while leftward microsaccades were occurring simultaneously towards the movement RF of the rostral neuron. As can be seen from Figure 10B, the visual burst still occurred in the caudal neuron, consistent with Figure 2. At the simultaneously recorded rostral SC site, the rostral neuron also exhibited a peri-microsaccadic movement burst (Figure 10E). Therefore, there were two simultaneous SC bursts (Figure 10B,E). This observation is rendered clearer when we aligned the activity in Figure 10E to peripheral stimulus onset rather than to microsaccade onset (Figure 10F, red; again the firing rate was distorted by the variable microsaccade onset times). In this case, Figure 10C (red) showed a visual burst, and Figure 10F (red) showed a rostral movement burst, simultaneously. Incidentally, and consistent with Figure 9 and prior reports (Dorris et al., 2007; Hafed and Krauzlis, 2008), in the absence of any microsaccades, the peripheral visual burst (Figure 10C, blue) was indeed accompanied by reduced activity in the rostral neuron (Figure 10F, blue), but this was only the case in the absence of microsaccades.

Simultaneous rostral and caudal.

SC recordings confirmed the simultaneity of peripheral visual bursts and foveal movement-related bursts when microsaccades were triggered around the time of peripheral visual bursts. (A) Visual RF of an example neuron from an experiment with both caudal and rostral microelectrode arrays inserted into the SC. This example neuron was recorded from the caudal array inserted into the left SC. The RF mapping task revealed a preferred eccentricity of ~6 deg. (B) The neuron still exhibited a robust visual response for a stimulus appearing inside its visual RF (at an eccentricity of ~6 deg) even when there were simultaneous microsaccades (towards the movement RF) occurring 30–100 ms after stimulus onset (i.e. coincident with the time of the visual burst). (C) For the same neuron, the visual burst was similar with and without microsaccades occurring within the visual burst interval. (D) A foveal movement-related RF of a simultaneously recorded neuron, this time from the second microelectrode array inserted into the right rostral SC. The shown map was obtained from the RF mapping task (Methods). (E) In the main task of experiment 3, for microsaccades towards the movement RF occurring within the visual burst interval (i.e. coincident with the visual burst in B), the neuron still exhibited a robust microsaccade-related discharge. (F) This means that relative to peripheral stimulus onset, this neuron actually had a burst (red) rather than a decrease (blue) in firing rate at the same time as the peripheral visual burst in the caudal SC (C). The blue firing rate curves show the same neuron’s response when the peripheral stimulus onset occurred in the absence of any microsaccades (same conventions as in Figure 9). Therefore, microsaccades occurring at the time of peripheral visual bursts were associated with readout of two burst loci: one in the rostral SC associated with the triggered movement and one in the caudal SC associated with visual stimulus onset. Error bars denote s.e.m.

Figure 10—source data 1

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Across the population of rostral and caudal SC neurons recorded during this additional experiment, we observed consistent results with the above examples in Figures 810. Specifically, we normalized each neuron’s activity (either the microsaccade-related response for rostral neurons or the stimulus-induced visual response for caudal neurons) to its peak response in baseline (Materials and methods). We then averaged across neurons to obtain a population summary. For the rostral neurons, when microsaccades were triggered 30–100 ms after peripheral stimulus onset and they were towards the movement RF’s of these neurons (Materials and methods), the neurons still exhibited classic microsaccade-related discharge (Figure 11A, left panel). Because the microsaccades happened right after peripheral stimulus onset, aligning this same discharge to the stimulus onset (Figure 11A, right panel, red) revealed a clear burst, which was absent (and replaced by a decrease in activity) when no microsaccades occurred near stimulus onset (Figure 11A, right panel, blue). For the peripheral neurons, stimulus onsets inside their RF’s elicited robust visual bursts, both without microsaccades (Figure 11B, blue) and with microsaccades (Figure 11B, red). The visual burst with microsaccades was slightly suppressed (see Figure 2—figure supplement 1), but this was expected: most of our rostral sites were opposite the caudal sites (Figure 11C). Therefore, microsaccades towards the movement RF’s of rostral neurons were opposite the direction of the peripheral stimulus, a condition that suppresses visual bursts (Chen et al., 2015).

Population summary of the experiments in Figures 810.

(A) Left panel: movement-related firing rate for all rostral SC neurons when microsaccades towards the movement RF occurred 30–100 ms after peripheral stimulus onset (i.e. coincident with peripheral visual burst occurrence). For each neuron, we first calculated the microsaccade-related discharge for the preferred microsaccades in the RF mapping task and then divided by this maximum firing rate to normalize the activity of individual trials from the main task. We then averaged across all average normalized firing rates of individual neurons to obtain a population response (error bars denote s.e.m.). Right panel: When the same data were aligned to stimulus onset (as opposed to microsaccade onset), we could see that the rostral SC clearly exhibited bursts at the same time as peripheral visual bursts when microsaccades occurred (red). Figure 12 shows paired measurements of raw firing rates of all rostral neurons at the time of microsaccade onset, with or without peripheral visual bursts; it confirms that the rostral SC movement-related bursts were similar whether there was a peripheral visual burst or not. When microsaccades did not occur, peripheral stimulus onsets in either direction suppressed rostral SC activity (blue curves). (B) For all caudal SC neurons, we first averaged the firing rate across trials after a stimulus appeared inside the RF (again from the RF mapping task). We then normalized all trial firing rates by this measurement, and we then pooled neurons by averaging their individual normalized firing rate curves in the main task of experiment 3 (to obtain a population average response; error bars denote s.e.m.). Consistent with all of our earlier results, peripheral visual bursts still occurred even when coincident microsaccades occurred (red). Note that the red curve was slightly suppressed. This is because in most of our experiments (see C), the microsaccade site was opposite in direction from the caudal SC site. This is a condition known to be associated with suppressed visual bursts (Chen et al., 2015); also see Figure 2—figure supplement 1. (C) RF hotspot locations from all recording sites in these experiments (top: individual microelectrode array in either the caudal or rostral SC; bottom: simultaneous caudal and rostral SC recording arrays). The numbers of neurons are described in Materials and methods.

Figure 11—source data 1

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Importantly, for each recorded rostral SC neuron, we also performed a paired comparison between the neuron’s unnormalized raw microsaccade-related movement bursts with and without peripheral visual bursts. Specifically, we picked microsaccades directed towards each neuron’s movement RF hotspot location (Methods), and we did this both when the movements occurred in a baseline pre-stimulus interval (500–1500 ms before peripheral stimulus onset in the main task) or in the interval 30–100 ms after peripheral stimulus onset. We then measured average firing rate within ±15 ms from microsaccade onset. Across the population, there was no significant alteration of the rostral motor bursts by the presence of a peripheral visual burst (Figure 12A; p=0.12539, paired ranksum test, N = 42 neurons). The example rostral SC neurons from Figures 9 and 10 are all explicitly highlighted in the summary plot of Figure 12A.

Similarity of microsaccade-related motor bursts at the time of peripheral visual bursts.

(A) For each rostral SC neuron from Figures 811, we measured the average firing rate in the interval within ±15 ms from microsaccade onset. We did this for microsaccades directed towards the rostral RF hotspot (Materials and methods). We then plotted this firing rate for the movements with which there was no peripheral stimulus onset (baseline microsaccades 500–1500 ms before stimulus onset; x-axis; Materials and methods) and also when the microsaccades occurred 30–100 ms after peripheral stimulus onset (that is, coincident with the peripheral visual bursts; y-axis). There was no statistically significant difference between the two measurements (p=0.12539; paired ranksum test; N = 42 neurons). The example rostral SC neurons from Figures 9 and 10 are highlighted with black arrows, and the inset shows the peri-movement population firing rates from all within-neuron paired measurements: red replicates the plot of Figure 11A, and blue shows the activity for baseline pre-stimulus microsaccades (error bars denote 95% confidence intervals). (B) For all of the sessions of experiment 3, we measured baseline microsaccade amplitudes and the amplitudes of microsaccades that were coincident with the peripheral visual bursts (occurring 30–100 ms after stimulus onset). In both cases, we picked microsaccades with directions towards the peripheral stimulus locations, because it is these microsaccades that are enlarged in size (e.g. Figures 2 and 3). Microsaccade amplitudes were significantly larger for the movements coincident with the peripheral visual bursts (p=7.9073×10−27; t-test; N = 650 microsaccades with peripheral stimulus onset, and N = 1956 baseline microsaccades). This occurred even though the peripheral stimuli were more eccentric than 4.5 deg, consistent with our earlier results (e.g. Figure 3—figure supplement 1 and Figure 6—figure supplement 2). Error bars denote s.e.m.

Figure 12—source data 1

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In contrast, from the perspective of behavioral results in the same experiment, we still found that the stimulus-congruent microsaccades occurring simultaneously with the peripheral visual bursts were enlarged in size when compared to baseline microsaccades (Figure 12B), just like with all of our earlier analyses in experiments 1 and 2. This was the case in experiment three despite the fact that this experiment had peripheral stimuli at eccentricities > 5 deg.

Therefore, the results of Figures 27 demonstrate that intra-saccadic visual bursts (and intra-saccadic visual discharge in general, even outside of visual bursts) lawfully ‘add’ to the metric computation of the executed microsaccades. Moreover, Figures 812 confirm that such visual bursts (and visual discharge in general) are indeed ‘additions’ to the originally existing movement-related bursts being emitted by the SC for downstream readout, and that the movement-related bursts themselves are minimally affected.

Discussion

We experimentally injected movement-unrelated spikes into the SC map at the time of saccade generation. We found that such spikes significantly altered the metrics of the generated saccadic eye movement, suggesting an instantaneous readout of the entire SC map for implementing any individual movement.

The SC and behavioral variability

Our results reveal a component of motor variability that we believe has been previously unaccounted for, namely, the fact that ever-present spiking activity in the entire SC map (whether due to sustained firing rates for a stimulus presented in the RF, like in Figure 7, or otherwise) can ‘leak’ into the readout performed by downstream motor structures when executing a movement. In fact, our results from Figure 7 showed that any intra-saccadic spikes on the SC map (far from the location of the motor burst) were sufficient to modulate microsaccade metrics, meaning that there was no need for a stimulus onset or even a stimulus-driven visual burst, like in Figures 26. Indeed, saccades during natural viewing show an immense amount of kinematic variability when compared to simplified laboratory tasks with only a single saccade target (Berg et al., 2009). In such natural viewing, natural images with plenty of low spatial frequency image power are expected to strongly activate a large number of SC neurons, which prefer low spatial frequencies, around the time of saccades (Chen et al., 2018; Khademi et al., 2020).

From an ecological perspective, our results demonstrate a remarkable flexibility of the oculomotor system during eye movement generation. Historically, saccades were thought to be controlled by an open-loop control system due to their apparent ballistic nature. However, other evidence, including our current results, clearly showed that individual saccades are actually malleable brain processes. In our case, we experimentally tried to generate a movement-unrelated ‘visual’ burst of activity that precisely coincided with the time of saccade triggering. We uncovered an instantaneous readout of the entire SC map that includes all the activity related to the ongoing motor program as well as the ‘extra’ activity. In real life, this extra activity might happen due to external sensory stimulation, such as the presence of a new object in the visual scene. In the laboratory, this extra activity can also be completely artificial, as is the case with electrical microstimulation (Katnani and Gandhi, 2011; Katnani et al., 2012); for example, dual-site suprathreshold simultaneous SC microstimulation results in saccades to neither ‘burst’ location, consistent with the deviations that we observed for our microsaccades.

Sensory signals in motor structures

The integration that we observed of sensory signals into the motor plan was not merely a ‘loose’ leakage phenomenon; rather, it exhibited a lawful additive process between the ‘visual’ spikes injected into the SC population and the altered microsaccade amplitudes (Figures 47). The more ‘visual’ spikes that occurred intra-saccadically, the larger the microsaccades became, following a linear relationship. Once again, this was even more remarkable for ‘sustained’ discharge, in which only few SC neurons might be expected to be active at the very same time (Figure 7). We discount the possibility that this effect was due to movement-related bursts per se, because we ensured that the neurons were not exhibiting movement bursts for the ranges of eye movements that we analyzed (Figure 1—figure supplement 1).

We suggest that this additive mechanism might underlie many of the effects commonly seen in experimental psychophysics, in which saccade kinematics are systematically altered by the presence of sudden irrelevant visual information available as close as 40 ms to movement onset (Edelman and Xu, 2009; Buonocore and McIntosh, 2012; Guillaume, 2012; Buonocore et al., 2016; Buonocore et al., 2017; Malevich et al., 2020b). Our hypothesis is that these modulations are a behavioral manifestation of the instantaneous readout of the activity on the SC map, as we also previously hypothesized (Hafed and Ignashchenkova, 2013; Buonocore et al., 2017).

Moreover, similar specification mechanisms can be seen in the instantaneous alteration of eye velocity during smooth pursuit when small flashes are presented (Buonocore et al., 2019), and even with ocular position drift during fixation (Malevich et al., 2020a). These observations extend the mechanisms uncovered in our study to the pursuit system and beyond, and they also relate to sequential activation of SC neurons during curved saccades associated with planning sequences of movements (Port and Wurtz, 2003). These observations are also consistent with experimental manipulations in which the oculomotor ‘gate’ in the brainstem is ‘opened’ by blinks (Jagadisan and Gandhi, 2017). In such manipulations, the authors exploited the fact that blinks are associated with pauses in brainstem omnipause neuron activity, and they revealed that blinks during saccade planning revealed that preparatory spikes in the SC before saccade onset contain a kind of ‘movement potential’ (Jagadisan and Gandhi, 2017). This is a clear analogous situation to our results.

Our investigations, which were driven by behavioral modulations observed in psychophysical experiments as alluded to above, therefore now provide a means to precisely quantify such behavioral modulations when sensory stimuli arrive in close temporal proximity to saccade generation. They also extend to early microstimulation experiments (Glimcher and Sparks, 1993), and to situations in which concurrent saccade motor plans can give rise to vector averaging (Robinson, 1972; Schiller et al., 1979; Schiller and Sandell, 1983; Sparks and Mays, 1983; Edelman and Keller, 1998; Katnani and Gandhi, 2011; Katnani et al., 2012) or curved (McPeek et al., 2003) saccades to ones in which a sensory burst itself is what is concurrently present with the saccade motor program. In that sense, the sensory burst may act as a motor program itself, as with express saccades having ultra-short latencies that appear to merge SC visual and motor bursts (Edelman and Keller, 1996; Sparks et al., 2000). In these saccades, it could be that the triggering for the saccades happens exactly at the time of the visual bursts, therefore ‘pulling’ the saccades to the locations of the bursts. This is not unlike our observations (Figures 36).

Most intriguingly, our results motivate similar neurophysiological studies on sensory-motor integration in other oculomotor structures. For example, our own ongoing experiments in the lower oculomotor brainstem, at the very final stage for saccade control (Keller, 1974; Büttner-Ennever et al., 1988; Gandhi and Keller, 1999a; Missal and Keller, 2002), are revealing highly thought provoking visual pattern analysis capabilities of intrinsically motor neurons (Buonocore et al., 2020). These and other experiments will, in the future, clarify the mechanisms behind multiplexing of visual and motor processing in general, across other subcortical areas, like pulvinar, and also cortical areas, like FEF and LIP. Moreover, these sensory-motor integration processes can have direct repercussions on commonly used behavioral paradigms in which microsaccades and saccades happen around the time of attentional cues/probes and can alter performance (Hafed, 2013; Hafed et al., 2015; Tian et al., 2016; Buonocore et al., 2017).

The SC and saccade generation

Consistent with the above sentiment, our study illuminates emerging and classic models of the role of the SC in saccade control. In a recent model by Goossens and Van Opstal, 2006, it was suggested that every SC spike during a motor burst contributes a mini-vector of eye movement tendency, such that the aggregate sum of movement tendencies comprises the overall trajectory. Our results are consistent with this model, and related ones also invoking a role of SC activity levels in instantaneous trajectory control (Waitzman et al., 1991; Smalianchuk et al., 2018), in the sense that we did observe linear contributions of additional SC spikes on eye movement metrics (Figures 4, 6 and 7). However, our results add to this model the notion that there need not be a ‘classifier’ identifying particular SC spikes as being the movement-related spikes of the current movement and other spikes as being irrelevant. More importantly, we found diminishing returns of relative eccentricity between the ‘extra’ spikes and the current motor burst (e.g. Figure 4—figure supplement 3). According to their model, the more eccentric spikes that we introduced from more eccentric neurons should have each contributed ‘mini-vectors’ that were actually larger than the ‘mini-vectors’ contributed by the less eccentric spikes from the less eccentric neurons. So, if anything, we should have expected larger effects for the more eccentric neurons. This was clearly not the case. Therefore, this model needs to consider local and remote interactions more explicitly. The model also needs to consider other factors like input from other areas. Indeed, Peel et al., 2020 reported that the SC generates fewer saccade-related spikes during FEF inactivation, even for matched saccade amplitudes. Thus, the link between SC motor burst spiking and saccade kinematics is more loose than suggested by the model.

Similarly, we recently found that microsaccades without visual guidance can be associated with substantially fewer active SC neurons than similarly-sized microsaccades with visual guidance, because of so-called visually-dependent saccade-related neurons (Willeke et al., 2019). Finally, SC motor bursts themselves are different for saccades directed to upper versus lower visual field locations (Hafed and Chen, 2016). All these observations suggest that further research on the functional roles of SC motor bursts is strongly needed.

What other model, then, is more suitable than the mini-vector model and its variants? Classic vector averaging could be appealing. Indeed, dual-site SC microstimulation (Katnani et al., 2012) supports vector averaging models, and it is also conceptually similar to our approach. However, in its purest form, vector averaging still cannot account for our behavioral observations with far stimuli and neurons (e.g, Figure 3—figure supplement 1). Specifically, like with mini-vectors, vector averaging still predicts larger microsaccades with more eccentric stimuli, but this was not the case.

We are thus left with neither model fully accounting for our observations. However, newer ideas in the literature would be useful here. In recent work, Jagadisan and Gandhi, 2019 suggested that saccades are not triggered except if there was substantial population temporal alignment among active neurons. Their motivation was to ask why strong SC visual bursts do not automatically trigger saccades, even when they reach similar peak firing rates as motor bursts. They found that motor bursts have stronger temporal alignment between active neurons than visual bursts. This idea is appealing to us because it provides a plausible explanation for why we found the strongest impact of ‘visual’ spikes on movement metrics in a very specific time window around movement onset (Figure 6). In our view, this idea can also account for our weaker behavioral effects with increasing eccentricity. Specifically, because peripheral SC neurons prefer lower spatial frequencies than central SC neurons (Chen et al., 2018), the visual bursts of far neurons (for similar stimuli) could be more variable than the bursts of near neurons. This decreases the likelihood of temporal alignment in Figure 6, and therefore reduces the behavioral impact of the peripheral spikes. Future work comparing temporal population alignment at different eccentricities, and with and without microsaccade-related motor bursts, would provide experimental support for such a view, and it would extend the Jagadisan and Gandhi, 2019 hypothesis from one of ‘why’ a movement is triggered to also one of ‘how’ the movement specifications are read out by downstream structures.

Another important area that our results can illuminate is related to the question of lateral interactions. In experiment 3 (Figures 812), we explicitly recorded activity from rostral SC neurons while presenting peripheral visual stimuli. On the one hand, we confirmed that peripheral visual bursts may be associated with reductions in rostral SC activity, as we and others had also previously observed (Munoz and Istvan, 1998; Hafed and Krauzlis, 2008). This may be consistent with theories of lateral inhibition across the SC map (Dorris et al., 2007; Isa and Hall, 2009; Kasai and Isa, 2016). However, rostral SC inhibition only occurred in the complete absence of microsaccades (Figures 912). On the contrary, when microsaccades were triggered simultaneously with peripheral visual bursts, the rostral SC neurons actually exhibited activity bursts (Figures 912). Therefore, lateral interactions do not necessarily mean that a visual burst at one SC map location automatically implies a pausing of activity at distant locations. Rather, bursts happen in both the rostral and caudal SC, with the caudal ‘bursts’ kinematically adding to the generated saccades.

‘Choice probability’ in the oculomotor realm

Finally, our analyses in Figures 4 and 7 are analogous to ‘choice probability’ analyses in other fields (Britten et al., 1996; Nienborg and Cumming, 2006). In such analyses, one uncovers a relationship between a single neuron’s activity and the global output of the whole brain. In our case, we found that individual ‘injected’ spikes in the SC correlated remarkably well with saccade metric changes. From this perspective, our observation of differential effects between visual spikes of visual neurons versus visual spikes of visual-motor neurons (Figure 4—figure supplement 1) is particularly informative: both visual and visual-motor neurons were linearly related to the saccade amplitudes. However, the impact of a single extra visual spike from a visual-motor neuron was stronger than that of a single extra spike from a visual neuron. This is consistent with suggestions that visual-motor neurons are the SC output neurons (Mohler and Wurtz, 1976), and it is also consistent with our earlier observations that under specific conditions, visual-motor neurons are what might dictate saccadic behavior (Chen and Hafed, 2017). Revealing functional differences between visual responses of visual versus visual-motor neurons remains to be an interesting open question.

Conclusion

Our results expose highly plausible neural mechanisms associated with robust behavioral effects on saccades accompanied by nearby visual flashes in a variety of paradigms, and they also motivate revisiting a classic neurophysiological problem, the role of the SC in saccade control, from the perspective of visual-motor multiplexing within individual brain circuits, and even individual neurons themselves.

Materials and methods

Animal preparation

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We collected data from two adult, male rhesus monkeys (Macaca mulatta) that were 6–8 years of age and weighed 6–8 kg. The experiments were approved (licenses: CIN3/13; CIN4/19G) by ethics committees at the regional governmental offices of the city of Tuebingen and were in accordance with European Union guidelines on animal research and the associated implementations of these guidelines in German law. The monkeys were prepared using standard surgical procedures necessary for behavioral training and intracranial recordings. In short, monkeys N and P had a chamber centered on the midline and aiming at the superior colliculus (SC) with an angle of 35 and 38 degrees posterior of vertical in the sagittal plane, respectively. The details of the surgical procedures were described in previous reports (Chen and Hafed, 2013; Chen et al., 2015). To record eye movements with high temporal and spatial precision, the monkeys were also implanted with a scleral search coil. This allowed eye tracking using the magnetic induction technique (Fuchs and Robinson, 1966; Judge et al., 1980). Monkeys N and P were each implanted in the right and left eye, respectively.

Experimental control system and monkey setup

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We used a custom-built real-time experimental control system that drove stimulus presentation and ensured monkey behavioral monitoring and reward delivery. The details of the system are reported in recent publications (Chen and Hafed, 2013; Tian et al., 2016).

During the testing sessions, the animals were head fixed and seated in a standard primate chair placed at a distance of 74 cm from a CRT monitor. The eye height was aligned with the center of the screen. The room was completely dark with the only light source being the monitor. All stimuli were presented over a uniform gray background (21 Cd/m2). In all the experiments, the fixation spot consisted of a small square made of 3 by three pixels (about 8.5 by 8.5 min arc) colored in white (72 Cd/m2). The central pixel had the same color as the background.

Behavioral tasks and electrophysiology

Experiment 1: injecting visual spikes at the time of saccade generation (contrast task)

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We performed a novel analysis of SC data reported on earlier; our behavioral task is therefore described in detail in Chen et al., 2015. Briefly, we used a fixation paradigm during which we introduced a peripheral transient visual event at random intervals (see Figure 1A). Each trial started with a white fixation spot presented at the center of the display over a uniform gray background. The monkey was required to align its gaze with the fixation spot. Because fixation is an active process, this steady-state fixation paradigm allowed us to have a scenario in which microsaccades were periodically generated (Hafed and Ignashchenkova, 2013). After a random interval, we presented a stimulus consisting of a vertical sine wave grating of 2.2 cycles/deg spatial frequency and filling the visual response field (RF) of the recorded neuron. The stimulus onset allowed experimentally injecting visual spikes into the SC at retinotopic locations dissociated from the neurons involved in microsaccade generation (Hafed et al., 2009; Willeke et al., 2019). Therefore, we could investigate the influence of such injected spiking activity if it happened to occur in the middle of an ongoing microsaccade (see Results). We varied the contrast of the grating across trials in order to vary the amount of injected SC spiking activity around the time of microsaccade generation. Specifically, grating contrast could be one of 5%, 10%, 20%, 40%, or 80% (Chen et al., 2015). For the current study, we only analyzed trials with the highest three contrasts. We related microsaccade kinematics to injected ‘visual’ spiking activity. Overall, we analyzed 84 SC visual (44) and visual-motor (40) neurons in two monkeys. Out of these, 11 neurons (2 visual and nine visual-motor) were also tested on the behavioral task of experiment two below (i.e. within the same sessions). The remaining ones were collected on their own, in separate sessions, and one of them was tested at two stimulus locations in the RF in two successive runs. Across neurons, we analyzed a total of 1150 ± 379 s.d. trials per neuron. These were equally divided across the different stimulus contrasts.

Experiment 2: injecting visual spikes at the time of saccade generation (spatial frequency task)

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We performed a novel analysis of SC data reported on earlier in a different, unrelated study (Khademi et al., 2020). The behavioral task was similar to the stimulus contrast task above, but it had two key differences that were particularly useful for the current study. First, the task involved gratings of different spatial frequencies as opposed to different stimulus contrasts. The specific spatial frequencies used were 0.56, 2.2, and 4.4 cycles/deg. This allowed us to demonstrate that any kind of SC visual spiking activity at the time of saccade triggering, irrespective of which source it came from (whether visual contrast or spatial frequency), can be read out in a way to alter ongoing eye movements. Second, and most importantly, this task involved a prolonged fixation period after stimulus onset (up to 1300–3000 ms) (Khademi et al., 2020). This allowed us to ask whether our effects were restricted to visual ‘bursts’ or whether any kind of ongoing SC activity (e.g. during sustained stimulus presentation long after the ends of ‘visual’ bursts) can be read out to alter ongoing eye movements. We analyzed the activity of 55 neurons from this task (31 visual and 24 visual motor); 11 of these neurons were also tested with the contrast task described above within the same sessions. The remaining neurons were collected in separate sessions. In all cases, the stimulus was placed within the visual RF of a given recorded neuron (Figure 1). Across neurons, we analyzed a total of 266 ± 169 s.d. trials per neuron. These trials were equally divided among the three different spatial frequencies presented.

Experiment 3: microelectrode array recordings in either the rostral SC, the caudal SC, or both simultaneously

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In monkey N, we performed new recording experiments to explore modulations in the rostral SC (where movement bursts are expected to occur for microsaccades) at the time of peripheral ‘visual’ bursts. The monkey maintained fixation on a similar fixation spot to that we used in experiments 1 and 2 above, and we presented a white disc of 0.5 deg radius at an eccentric location. When we recorded from the rostral SC (representing foveal eccentricities), the eccentric location (i.e. the potential location of the white disc) was chosen to be at 10 deg either to the right or left of fixation (i.e. well away from the microsaccade endpoints). That is, across trials, we sampled visual stimuli activating the caudal portion of either the same or opposite SC as the recorded rostral SC site. When we recorded from the caudal SC (representing more eccentric visual field locations), the white disc appeared either within the visual RF of the caudal SC neurons being recorded at the site or in a diametrically opposite location. The monkey simply maintained fixation. The exact trial sequence in the experiment was similar to our earlier instantiation of the cueing task in Tian et al., 2018. That is, the white disc first appeared for approximately 32 ms, and then after a random time of up to 1 s, the disc appeared again at either the same or opposite location. Unlike in Tian et al., 2018, the monkey did not generate a saccade; rather, the monkey just maintained fixation and touched a bar after the second stimulus onset. We collected a total of 799 ± 272 s.d. trials per session. We counterbalanced first and second disc appearance location per trial (e.g. first at 10 deg right and second at 10 deg left, or first at 10 deg right and second at 10 deg right, and so on) across all trials. Since we were primarily interested in demonstrating that there is a visual burst no matter whether there are coincident microsaccades being triggered or not, we combined measurements of visual bursts for both the first and second disc appearance. Similarly, for the rostral SC, we were primarily interested in demonstrating that there is a motor microsaccade-related burst whether or not there is a peripheral visual burst; we therefore again combined first and second disc appearances per trial in analyses.

We inserted 16-channel linear microelectrode arrays (V Probes; Plexon, Inc) into either the rostral or caudal SC (23 and 17 sessions, respectively). In yet an additional set of sessions (13 sessions), we inserted two arrays simultaneously, one in the rostral SC and one in the caudal SC. To aid in the technical insertion of the two arrays, we inserted them into separate SC’s (e.g. right rostral SC and left caudal SC) because this gave us slightly more lateral separation between the microelectrode arrays for simultaneous insertion. Across all sessions, we isolated offline (see below) 42 rostral SC neurons and 54 caudal SC neurons for further analysis in the current study. Out of these, 15 rostral and 19 caudal neurons were recorded during the simultaneous recording sessions. To identify the sites that we were recording from, the monkey was also engaged in standard eye movement tasks similar to those described using similar experiments recently (Willeke et al., 2019). These tasks allowed us to map the visual and movement-related RF’s of the recorded neurons.

Data analysis

Experiment one data analysis

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All analyses were performed with Matlab (MathWorks, Inc). Most of the analyses involved grouping the eye movement data into groups of movements going either towards or opposite a recorded neuron’s RF. To make this classification, we first calculated the angle of the RF relative to the fixation spot. Then, all eye movements with an angle ±90 degrees around the RF direction were classified as being ‘towards’ the RF. All remaining eye movements were classified as being directed ‘opposite’ to the RF. Movement angles were defined as the arctangent subtended by the horizontal and vertical component between movement onset and end. RF angles were defined as the arctangent subtended by the horizontal and vertical coordinates of the RF locations relative to the fixation spot.

To confirm that none of our neurons exhibited movement-related discharge for the saccades that we studied (Figure 1—figure supplement 1), we searched for all microsaccades occurring in a pre-stimulus baseline interval of 25–100 ms before stimulus onset (i.e. in the absence of any eccentric visual stimuli). We then aligned all neural discharge to all microsaccades, and we confirmed that there was no activity elevation either towards or away from the recorded neuron’s RF. We also did this analysis separately for visual and visual-motor neurons. The former were expected not to show any movement-related discharge, by definition. The latter were only expected to exhibit discharge for much larger saccades than the ones we studied, and this analysis confirmed this. This means that our modulated microsaccade amplitudes in Results (e.g. Figure 4) were unlikely to be simply explained by the idea that the spikes that we measured were ‘motor’ bursts for microsaccades (e.g. see Discussion).

To analyze peak firing rates ‘without saccades’ (e.g. Figures 2 and 3B, Figure 2—figure supplement 1, Figure 3—figure supplement 1B), we selected all trials in which there were no microsaccades btween −100 ms and 200 ms relative to stimulus onset. We then averaged all the firing rates across trials, and we determined the peak firing rate for each neuron from the across-trial average curve. For the peak firing rate ‘with saccades’, we took all the trials in which a microsaccade was either starting or ending during the so-called visual burst interval, which we defined to be the interval 30–100 ms after stimulus onset. Paired-sample t-tests were performed to test the influence of saccades on the peak visual burst with an α level of 0.05 unless otherwise stated (e.g. Figure 2, Figure 2—figure supplement 1).

To summarize the time courses of microsaccade amplitudes after stimulus onset (e.g. Figure 3A, Figure 3—figure supplement 1A), we selected the first saccade of each trial that was triggered within the interval from −100 ms to +150 ms relative to stimulus onset. All the microsaccade amplitudes were then pooled together across monkeys and sessions. The microsaccade amplitude time course was obtained by filtering the data with a running average window of 50 ms with a step size of 10 ms. To statistically test the effect of grating contrasts on these time courses, we performed a one-way ANOVA on saccade amplitudes for all saccades occurring between 50 ms and 100 ms after stimulus onset. To compare the effect of grating contrast on SC visual bursts (e.g. Figure 3B, Figure 3—figure supplement 1B), for each neuron, we normalized the firing rate based on the maximum firing rate elicited by the strongest contrast. Subsequently, we calculated the mean firing rate of the population and the 95% confidence interval for the different contrast levels. Both the amplitude and the firing rate analyses focused on the three highest contrasts because the first two contrast levels did not have a visible impact on eye movement behavior.

For some analyses (Figures 47 and their supplements), we explored the relationship between the number of ‘visual’ spikes emitted by a recorded neuron and saccade amplitude. This allowed us to directly investigate the effect of each single additional spike per recorded neuron in the SC map on an ongoing saccade, irrespective of other variables. We selected all the trials in which an eye movement was performed in the direction of the grating soon after its presentation (0–200 ms from stimulus onset). The analysis was restricted to the three highest contrasts, since they had a clear effect on the eye movement behavior and also had a clear visual burst (e.g. Figure 3A). For each selected saccade, we counted the number of spikes happening from a given recorded neuron during the interval 0–20 ms after movement onset. This interval was constant, irrespective of saccade size, and it was early enough to be read out and influence the eye movement. Note that if there was no spike in this interval, then this meant that the microsaccade was classified as having ‘0 spikes’ (e.g. in Figure 4); therefore, the microsaccade was still occurring soon after stimulus onset but without a coincidence of peripheral spiking at its onset. For Figure 4A, Figure 4—figure supplement 2A, we calculated the ‘radial eye position’ from saccade start as the Euclidian distance of any eye position sample (i.e. at any millisecond) recorded during an eye movement relative to the eye position at movement onset (see for similar procedures: Hafed et al., 2009; Buonocore et al., 2017). We also plotted radial eye velocity for the same movements (e.g. Figure 4C). To make statistical inferences on the effects of the number of spikes on saccade amplitude (e.g. Figure 4B, Figure 4—figure supplement 2B), we proceeded by fitting a generalized linear model to the raw data with equation: y = β0 + β1*x where ‘x’ was our predictor variable, the number of spikes, and ‘y’ was the predicted amplitude. The parameters fitted were: β0 the intercept, β1 the slope. We imposed a cutoff of at least 15 trials for each level of the predictor, leading to exclusion of spike counts bigger than five. In a different variant of this analysis, we repeated it for only either visual or visual-motor neurons (e.g. Figure 4—figure supplement 1). Note that in all other analyses in this study, we decided to combine visual and visual-motor neurons for purposes of clarity. This was not problematic; if anything, it only muted our results slightly (rather than amplified them) since visual-motor neurons showed even stronger effects in general than visual neurons (see Results).

Also note that our choice of 0–20 ms from movement onset in the above analyses was to strictly enforce that the ‘visual’ spikes associated with bigger movements were intra-saccadic. Our other analyses (e.g. Figure 6) showed that we would have obtained even bigger effects had we include ‘visual’ spikes also right before movement onset. Either way, 0–20 ms was still early enough within the eye movements to cause measurable impacts (e.g. Figure 4).

To explore the impact of neuronal preferred eccentricity on the relationship between the number of spikes emitted by a given eccentric neuron and movement amplitude, we repeated the above generalized linear model analysis approach, but this time for specific eccentricity ranges of neurons. Specifically, we used a sliding window on neuronal preferred eccentricity. Starting with a preferred eccentricity of 1 deg, we defined a window centered on this and having 2 deg width. We then slid this 2 deg window in steps of 1 deg eccentricity. For each sliding window eccentricity center, we estimated the slope of the linear model described above, but this time from only neurons having a preferred eccentricity within the current sliding window location. We then plotted the slope of the relationship (i.e. the slope of the line relating saccade amplitude and the number of spikes) as a function of neuronal preferred eccentricity. This allowed us to confirm that our choice to focus on eccentricities less than or equal to 4.5 deg in most of our analyses in this study was a valid approach (Figure 4—figure supplement 3). It also allowed us to investigate whether the slope ever turned negative for the most eccentric neurons, which was not the case (see Results). For Figure 4—figure supplement 3B, we used the estimates of s.e.m. obtained from the generalized linear model fits to visually present the s.e.m. ranges of the shown slopes.

In all the above generalized linear model analyses, we included the 0 spike movements in the data fits. However, it turned out that we could have also excluded these movements, and the same results would have been obtained (and this was also true in the eccentricity effects of Figure 4—figure supplement 3). For simplicity, in Results, we showed only the analyses with the ‘0 spike’ movements included as parts of the generalized linear model fits.

To study the time window of influence of each added spike on saccade amplitudes (Figure 5), we generated raster plots from all trials of all sessions by aligning each spike raster trace to the saccade occurring on the same trial (either saccade start, peak velocity, or end). The saccades were chosen as those that happened after stimulus onset and being directed towards the RF locations, and the alignment was based on the time of peak visual burst after stimulus onset on a given trial relative to the time of the movement. We selected data from the three highest stimulus contrasts and also with eye movements directed towards the RF, since the modulation in behavior was most pronounced in these cases (e.g. Figure 4). We also focused on neurons with preferred eccentricities ≤ 4.5 deg. To identify the point at which the amplitude diverged from a baseline level in Figure 5D, we first sorted all the amplitudes based on burst time relative to saccade onset (Figure 5A). Then, we made bins of 30 trials each from which we derived the mean amplitude values (Figure 5D shows something similar but with a moving average of 20 trials, in steps of 1 trial, just for visualization purposes). We also tested the amplitudes of each 30-trial bin against the first one (baseline amplitude) to determine when the amplitude increase was significant. To do so, we performed two-sample independent t-tests between each pair (i.e. the current time bin and the first baseline time bin), and we adjusted the alpha level with Bonferroni correction. We chose as an index for a significant increase in amplitude the point at which three consecutive bins were significantly different from the baseline (first horizontal blue line in the trial sorting of Figure 5D). The next three consecutive bins that did not differ anymore from the baseline indicated that the amplitude increase was not significant anymore (second horizontal blue line in the trial sorting of Figure 5D).

We also repeated the analyses of Figure 5 but for the far neurons having preferred eccentricities > 4.5 deg (Figure 5—figure supplement 2). We used the same procedures as described above. However, since there was a significantly larger number of trials, we used 100-trial bins rather than 30-trial bins for the running statistical tests used to assess the locations of the horizontal blue lines in Figure 5—figure supplement 2. For the visualization of the microsaccade amplitudes in panel D of the same figure, we also used a moving average of 50 trials (in steps of 10 trial) instead of a moving average of 20 trials as in Figure 5. Again, this was done only to result in smoother looking curves in panel D; the conclusions based on the running statistical tests did not depend on the visualization binning. We also did not use Bonferroni correction in the running tests, just for simplicity. This was fine, especially because, in any case, we quantitatively assessed the time window of maximal impact by peripheral spiking on microsaccade amplitudes in Figure 6—figure supplement 2 for the same data set; therefore, in this sense, Figure 5—figure supplement 2 was more suitable as a visualization of the impact of spike timing relative to movement onset, whereas Figure 6—figure supplement 2 provided a more quantitative estimate of the relative timing relationship between the far spiking and the movements that were altered by such far spiking.

For Figure 6, for each movement amplitude range from the data in Figure 5, we identified ‘how many’ and ‘when’ visual spikes in an eccentric neuron occurred in association with this amplitude range. This allowed us to identify a window of time in which injected ‘visual’ spikes had the most effect on saccade amplitudes. For each movement, we estimated the average number of spikes to occur within a given 5 ms time window around saccade onset. We also repeated this same analysis for the far neurons of the same experiment, which had preferred eccentricities > 4.5 deg (Figure 6—figure supplement 2).

Experiment two data analysis

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We repeated all the visual burst analyses described above for experiment 1 (the contrast task). This allowed us to confirm the robustness of all results from experiment 1. We pooled across spatial frequencies when investigating the impact of a given number of spikes on movement amplitude (e.g. Figure 4—figure supplement 4 or Figure 6—figure supplement 1).

For Figure 5—figure supplement 1, we repeated the same analysis steps of Figure 5. Here, we used 20-trial moving average bins (in panel D of the figure), and also 20-trial bins for the Bonferroni corrected running statistical tests used to obtain the horizontal blue lines in the figure. Similarly, we also assessed the specific time window for maximal impact of visual spiking on microsaccades in Figure 6—figure supplement 1.

To demonstrate that even spiking activity long after visual bursts could still influence movement amplitudes (Figure 7), we collected all microsaccades occurring >550 ms after stimulus onset. We then analyzed the relationship between spiking activity and movement metrics exactly like we did for the analyses with spikes coming during the ‘visual burst interval’. The results are shown in Figure 7 and Figure 7—figure supplement 1. For the summary plots of amplitude as a function of number of intra-saccadic spikes, we included trials from all spatial frequencies.

Experiment three data analysis

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Neurons in experiments 1 and 2 were sorted online for their respective previous studies (Chen et al., 2015; Khademi et al., 2020). For experiment 3, we sorted the neurons offline using the Kilosort toolbox (Pachitariu et al., 2016). Briefly, after a semi-automated spike detection and classification step, we manually inspected all isolated units based on auto- and cross-correlograms, as well as waveform shapes. Any atypical sorting results (such as irregular waveforms, no clear characteristic auto-correlograms, or violations of refractory periods) were excluded from our analyzed database. Besides these strict mathematical sorting quantifications, we also verified the sorting results based on RF and neuronal properties in the classic delayed visually guided and memory-guided saccade tasks. All isolated units within a simultaneously recorded session (e.g. across the 16 channels of a single microelectrode array) had high similarity in their movement RF locations (quantified by Pearson’s correlations: average correlation value 0.875 ± 0.002 s.e.m., p<0.0001).

Visual and movement RF’s in these new recordings were assessed using our standard delayed visually guided and memory-guided saccade tasks (Munoz and Wurtz, 1995; Li and Basso, 2008; Chen et al., 2015; Willeke et al., 2019). For plotting microsaccade-related movement RF’s of the rostral neurons, we plotted the raw peak firing rate as a function of microsaccade amplitude and direction (the illustrations of rostral RF’s in Results are based on the memory-guided saccade mapping task). We then fitted the resulting data with a two-dimensional gaussian function. This allowed us to estimate a region of interest (e.g. movements within 2 s.d. radii from the peaks) for plotting firing rates as a function of time from microsaccade onset (e.g. Figure 9B,G). For visual and movement RF plots, we also used log-polar axes to cover the large range of eccentricities used (Hafed and Krauzlis, 2012; Willeke et al., 2019).

Our comparison of interest for caudal visual burst analyses in this experiment was firing rates with no microsaccades occurring −50–200 ms relative to peripheral stimulus onset or firing rates with microsaccades occurring towards the rostral movement RF direction during a visual burst interval (e.g. 30–100 ms). We therefore split trials based on whether microsaccades happened or not. For rostral SC neurons, in Figure 12, our comparison of interest was microsaccade-related bursts in baseline (pre-stimulus interval) or when microsaccades occurred during the visual burst interval (e.g. 30–100 ms after peripheral stimulus onset), with the microsaccades being directed towards the RF hotspot location in both cases. The baseline microsaccades were defined as those occurring 500–1500 ms before peripheral stimulus onset.

To summarize results across neurons, we obtained average population firing rates by first normalizing each neuron’s response to its maximum and then averaging across neurons. For rostral neurons, we identified the ‘preferred’ microsaccades (i.e. those resulting in the highest peri-microsaccadic firing rates; our region of interest in the RF). We then normalized each neuron’s activity by the peak microsaccade-related activity for the preferred microsaccades from the RF mapping tasks. We then averaged across neurons in the main task. The average could be either for baseline microsaccades in the absence of a peripheral visual stimulus (for microsaccades occurring 500–1500 ms before stimulus onset), or it could be for microsaccades towards the movement RF starting 30–100 ms after stimulus onset (i.e. during the peripheral visual burst); see for example Figure 12 with the raw measurements. When we did show normalized firing rates (e.g. Figure 11A), the normalization factor for both conditions was the same (the peak firing of the neuron in baseline, based on the region of interest in the RF mapping tasks). For caudal neurons, the stimulus in the visual RF was always at a fixed location across trials in the main task. We therefore took all trials in which no microsaccades occurred −50–150 ms from stimulus onset in the main task. We then averaged the firing rate for these trials, and we then used this as the normalization factor. We normalized all trial firing rates by this normalization factor (again, dividing the individual trial firing rates by this normalization factor), including the trials in which microsaccades happened during the visual burst interval (30–100 ms after stimulus onset). We then averaged the neurons’ normalized firing rates to obtain a population average response.

For the behavioral analyses in Figure 12B, we measured microsaccade amplitudes from all of the sessions of experiment 3, but for either pre-stimulus microsaccades (500–1500 ms before peripheral stimulus onset) or for microsaccades occurring 30–100 ms after peripheral stimulus onset. In both cases, we picked microsaccades with angular directions within ±25 deg from peripheral stimulus direction. This was so because amplitude increases for the microsaccades are expected to happen for movements towards the recently appearing peripheral stimuli (e.g. Figure 3).

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for all figures.

References

  1. Conference
    1. Buonocore A
    2. Baumann MP
    3. Hafed ZM
    (2020)
    Visual pattern analysis by motor neurons (Abstract)
    Computational and Systems Neuroscience.
  2. Conference
    1. Pachitariu M
    2. Steinmetz NA
    3. Kadir SN
    4. Carandini M
    5. Harris KD
    (2016)
    Fast and accurate spike sorting of high-channel count probes with KiloSort
    NIPS'16: Proceedings of the 30th International Conference on Neural Information Processing Systems.

Decision letter

  1. Martin Vinck
    Reviewing Editor; Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Germany
  2. Richard B Ivry
    Senior Editor; University of California, Berkeley, United States
  3. Terrence R Stanford
    Reviewer; Wake Forest School of Medicine, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

The brain can rapidly adjust its actions on the fly when new sensory information becomes available. This study addresses how microsaccadic eye movements are influenced by a suddenly presented visual stimulus in the periphery, and how this depends on interactions within the superior colliculus. Whenever visually evoked activity occurs in a small temporal window around microsaccade execution, the visual spikes modify the amplitude of the microsaccade. These visual spikes influence the motor command in a lawful manner such that each extra spike from the same SC increases systematically the amplitude of the microsaccade. These findings shed new light on how visual information is integrated into ongoing saccadic motor commands.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "Instantaneous movement-unrelated midbrain activity modifies ongoing eye movements" for consideration by eLife. Your article has been reviewed by 4 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Terrence R Stanford (Reviewer #3).

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife. As you will see from the reviews, the reviewers expressed general interests and made many positive remarks. However, they also agreed on major issues that would require a substantial amount of additional experimentation and analysis. Some of the major issues include (1) There were major concerns about the relationship and consistency between experiment 1 and 2, and the interpretation of the microstimulation experiment. (2) The results of Experiment 1 might have several other interpretations including visual enhancement and competitive interactions, and could be influenced by several confounds. Within the domain on mechanisms of saccade generation, the analyses are not detailed enough to test competing models and provide conclusive mechanistic insight.

We would welcome submission of a new manuscript if it is possible to address these issues, but we judged them to be sufficiently significant that we thought it better to reject at this stage. Should you go this route, we would likely go to the same reviewers.

Reviewer #1:

This study investigates the influence of visual stimuli and spiking activity in distant SC (superior colliculus) locations on small microsaccadic movements during fixation. The authors show that visual stimuli and activity in these distant locations modulates the ongoing microsaccadic movements. The authors find however that nearby locations have more powerful effects than distant locations, which challenges existing models based on vector-averaging (as one would expect distant locations to exert more powerful effects). Overall these findings provide a very interesting addition to the literature. My main critique is the possibility of lateral interactions or influence on the activity of more foveal neurons.

1. If I understand correctly, the authors suppose that the effects on the saccade trajectory are mediated by the projections of neurons in distal locations to other brain areas. However there are lateral inhibitory interactions within the superior colliculus and the effects reported here could potentially be mediated by these lateral interactions that modulate the activity of neurons driving the microsaccadese.

2. A related point is that the visual stimulus might exert some effects directly on the neurons driving the microsaccades, either through lateral mechanisms within the retina or within the superior colliculus.

The best control would be to analyze directly the neurons in foveal regions. What happens there? Is their firing rate affected or not? It appears that the authors have this data but they do not report this.

3. The authors should provide more raster plots of activity of neurons and describe more clearly how many neurons were recorded/analyzed throughout the legends and results text.

4. What functional cell types are recorded by the authors? This should be described.

Reviewer #2:

The superior colliculus (SC) is recognized for its role in sensorimotor transformations. A vast number of SC neurons discharge both when a stimulus is presented in their response fields and also when a saccade is directed to that location. Mechanisms have been proposed for differentiating 'sensory' from 'motor' activity across the SC population and, furthermore, computing the metrics and/or kinematics of the observed saccade. This study shows that if additional spikes, whether evoked by a visual stimulus or through electrical stimulation, are introduced at a SC location away from the active 'motor' population and around the time of saccade, then these spikes contribute to the size of the saccade. Amazingly, effects of adding single spikes per neuron (but from many neurons) are noticeable in the analyses. It is a thought-provoking finding and, provided several serious concerns are mitigated satisfactorily, has implications on multiple facets of SC role in saccade generation.

1. The data shown in Figure 2 do not align with the working model of the SC. A fairly well-known study by Dorris, Olivier, and Munoz (https://doi.org/10.1523/JNEUROSCI.4212-06.2007), which surprisingly is not cited here, showed that a visual stimulus (distractor) interferes with motor preparatory activity elsewhere in the SC. The preparatory activity is enhanced if the target and distractor populations are in close proximity but suppressed if the distractor is far way, including in the opposite hemifield. This finding – complemented by slice studies by Isa, Hall, and others -

has established a framework for local excitation and mutual distal inhibition in the SC. What is shown in Figure 2 does not conform to this framework and, if true, it is too important a result to be overlooked.

a. I realize that the activity recorded in this study is from neurons at the "visual", rather than the "motor", site. However, if interactions between the two populations are mutual, then the effect should arguably be observed in both populations. Should we be rethinking this conclusion – are the competitive interactions not mutually effective?

b. The motor activity relevant here is in the rostral SC and associated with microsaccades, while the Dorris study focused on more caudal regions that encode larger amplitude movements. However, an underlying theme of a large body of Hafed's studies is that our knowledge of large amplitude saccades and their neural control extend to microsaccades also. In fact, this is the justification used for the microstimulation experiments reported in the manuscript. Should we be second guessing this conclusion – perhaps there is something unique about microsaccade control?

c. The relative timing of activity in the 'visual' and 'motor' populations are different in the two studies. I believe Dorris et al. only focused on trials when distractor-driven activity occurred during saccade preparation rather than during execution. In contrast, this Buonocore et al. manuscript draws our attention to when the two bursts are effectively coincident. But it is not clear why competitive interaction effect should disappear during a saccade.

d. These results are also inconsistent with the large body of literature on saccadic or visual suppression in the SC (e.g., D.L. Robinson and Wurtz).

e. It would be tremendously valuable if the authors also show what happens to the motor burst when visual spikes are added elsewhere in the SC, not just during the execution phase of a microsaccade but also in the preparatory period preceding it. Given that the Hafed lab does a lot of neural recordings in the rostral SC during microsaccades, the data may already be available or easily collectable. Without this data, it is difficult to offer full support of the results presented in this manuscript.

2. The data in Figures 4 and 5 are rather remarkable. They make a compelling case for systematic increase in saccade amplitude as additional spikes/neuron are coincident with the motor burst. A few points of clarification:

a. Please also include velocity profiles in Figure 4A. Are they bell-shaped or like control movements? Or do the velocity profiles exhibit an inflection point or multiple peaks (like that observed for the microstimulation experiments reported later in the manuscript)?

b. As best as I can tell, the data are pooled across all trials and all neurons (like in Figure 5). If true, please make this (more) explicit in the text and figure caption. It also raises the concern that the effect may be weighted more by the subset of neurons that have substantially more trials than other neurons. Please provide summary of number of trials per neuron. Importantly, provide insights into how many neurons' data conform to the results shown in Figure 4.

c. If I am mistaken and the analysis is performed one neuron at a time, then please underlay in Figure 4B the distribution of all points for each x-axis value (as in Figure S4).

3. Several aspects of Figure 6 are bothersome and require clarity. Frankly, it is not clear that the effect the authors want to emphasize is actually present in the data.

a. In Figure 6C, there aren't enough points for 3 and 4 intra-saccadic spikes to justify using mean as the average measure. Median is a better choice and, in this case, the suggested effect will likely not exist. This will likely change the text on Lines 374-378, which incidentally deserves to be backed with a statistical test.

b. In Figure 6C and 6D, color the dots according to the histograms in Figure 6A and 6B, respectively. Basically, the color of dots should change from dark red (green) to light orange (yellow) as y-axis value increases.

c. Data in Figure 6A and 6C suggest some discrepancy. Figure 6A indicates that microsaccades larger than 1 deg were observed, but Figure 6C does not show any saccades greater than one degree. Same concern for Figures 6B and 6D.

4. I am less excited about the experiments using microstimulation during visually-guided saccades.

a. The authors want us to accept that the relationship between the sensory and motor populations of neurons remains the same in the two experimental paradigms (L424-430). I would've accepted this premise prior to reading this manuscript, but the lack of competitive interactions makes me question this assumption, particularly as the electrode placement moves away from the rostral SC.

b. Example velocity traces are not unimodal. Perhaps this is due to stimulation occurring late within a saccade, but it looks more like the ongoing saccades is truncated and potentially replaced by another movement command. These results are indicative of competitive interactions.

5. Data in Figure 8 are difficult to interpret.

a. Normalized amplitude increases earlier for 1 electrical spike compared to 2 and 3 spikes. Is this significant and how can this be? We can't interpret this result until we have a sense of variability in normalized saccadic amplitude in the absence of stimulation.

b. Given the arguments raised above about Figure 7, this analysis should arguably not include displacement associated with the second bell-shape in the velocity profile.

c. Saccade amplitude peaks when microstimulation and saccade onsets are coincidental, but according to Figure 7, the effect is observed as a second peak in velocity, which occurs 40-50 ms later, and this is substantially longer than the efferent delay. So, pieces are not adding up.

Reviewer #3:

Overall, this is a strong manuscript that considers a topic of significant interest to those interested in visuomotor control and attention. Main strengths: 1) It provides important insight for understanding the kinematics of saccades that would be made under natural viewing circumstances and 2) good experimental design and analysis have yielded a compelling dataset that speaks to the main conclusion that currently executed SC motor commands are influenced by the instantaneous readout of any concurrent visually-evoked activity within the SC map. Weakness: Although the study provides an important additional piece to the SC readout puzzle, it does seem to strongly constrain possible mechanistic frameworks.

Specific comments:

The experiment in which visually evoked activity is "injected" and alters the metrics of microsaccades is elegant and compelling. To me this is what makes the manuscript worthy of publication as it shows quite definitely that such activity is read-out as part of the ongoing motor command. This has important implications for understanding the execution of saccades during natural scanning when the perception/action sequence is considerably more fluid than for a typical laboratory task. With respect to this main strength, the results are clearly presented and interpreted.

The results of Experiment 2 are also well presented, but, in my view, there are some issues with interpretation that might be remedied with further discussion.

The microstimulation results are interesting but think there are some issues that limit the conclusions that one might draw regarding the SC readout mechanism.

1. The injection of microstimulation pulses is suggested as an analog of "injecting" visual activity. But not all SC saccade-related neurons are visually responsive, and the electrical stimulation is certain to impact visual-motor and motor cells alike. Thus, microstimulation does not so cleanly tap visually driven activity as does the visual stimulus employed in the first experiment. That microstimulation alone does not trigger saccades does not mitigate this concern since 1-3 stimulus pulses would not be expected to trigger a saccade in any case. Some consideration of this distinction seems warranted.

2. There have been many variants of SC readout models that are or are not consistent with producing the form of input required of brainstem local feedback circuit models as originally proposed by David Robinson and others (e.g., Jurgens et al., 1981) and which likewise either support or supplant the vector averaging scheme proposed by Sparks and colleagues (Lee et al., 1988). It is not entirely clear how the present microstimulation data inform or distinguish between traditional or later developed frameworks. For example, given the spatial configuration employed here (i.e., in line, stim always more eccentric), I could imagine how a simple vector averaging scheme could yield the linear increase in amplitude with additional pulses if one assumes the pulses produce a transient modification of the SC's desired displacement signal. But then, I think more recent schemes (e.g., that of vector summation) could work equally well. More discussion of how these data constrain current models would be welcome.

3. Related to the above, the microstimulation results are not unexpected based on how one would expect it to interact with an ongoing movement. This we could intuit from extant literature (as properly cited by the authors). The weakening of the effect with eccentricity is new and interesting, but I wonder if it is specific to eccentricity or if it generalizes in some way to distance in an SC spatial coordinate frame.

4. I understand that microsaccades, provide only the option of a more eccentric stimulus or stimulation, however, it seems like an experimental variant in which the "ectopic" stimulus was less eccentric might have been of use in distinguishing between readout mechanisms. I'm not suggesting this as a necessary addition, but some discussion might be valuable.

5. There is a recent paper by Gandhi and colleagues (Smalianchuk et al., 2018) that seems quite relevant as it relates to instantaneous SC readout mechanisms. Although it does not deal with "visual" activity, there is enough conceptual overlap that it should be referenced and/or discussed at the authors' discretion.

Reviewer #4:

In this study, Buonocore and colleagues investigate the influence of visual neural activity in the superior colliculus (SC) on eye-movements. In the first experiment, they show that visual activity in the SC – induced by a peripheral grating – was unaffected by concurrent microsaccades. Interestingly, the size of microsaccades was biased by the visual stimulation, and the higher the number of spikes around the its onset, the larger the amplitude of the eye-movement. In a second experiment, using electrical microstimulation of the SC during a saccade task, they show that even a small number of induced spikes (3) was enough to bias the animal's eye-movement response towards the stimulated site. Overall, this is an interesting study, with significant implications for saccade generation models in the SC.

The authors often use selection criteria for their data analysis that is not clearly justified. One criterion that might be particularly problematic is to focus most of their analysis on eccentricities <= 4.5 deg. Their justification for this is that "these had the strongest effects on microsaccades" (line 189). Analyses for values > 4.5 deg, showing usually just weaker effects, are presented in the supplementary materials. My main concern is that this approach might be hiding an underlying interaction between eccentricity, SC firing rate, and microsaccade amplitude, which could contradict the other findings presented. The firing rate values in Figure S4 suggest that there might be a positive correlation between eccentricity and SC firing rate (higher firing for more eccentric RFs). While microsaccade amplitudes seem negatively correlated with eccentricity. If this is true, the analysis pooling together all data would suggest that higher firing would be associated with smaller amplitudes (the opposite of what is shown here). Of course, that eccentricity could be considered a confounding variable. So, one possible way to deal with this problem would be to perform a regression analysis to predict microsaccade amplitudes using both eccentricity and SC activity as independent variables.

The analysis presented in Figure 4 shows a clear relationship between the number of spikes in SC and microsaccade amplitude. This is a very interesting finding. However, I see two potential problems here. One, that by sorting their data on 'number of spikes', they might inadvertently be also splitting their data by contrast (a result already shown in Figure 3). Second, they count the number of spikes from saccade onset to peak velocity as a criterion. The problem is that, because of the ballistic nature of saccades, this interval would linearly increase with saccade amplitude. Given the result presented in Figure 6A, I would not expect that this would compromise their main finding, but the authors should nonetheless correct for this by using a fixed time-window across all saccade amplitude conditions.

The statistical inferences from experiment 2 are mostly done one "saccadic displacement", calculated as the "radial position of the eyes from saccade start to 100 ms thereafter" (line 814). I might be missing something, but I don't understand why they use this criterion instead of, for example, the normalized distance of the saccade offset to the target. It seems to me that they might yield similar results, but since most saccades are finished by 60-80ms (Figure 7CD), the 100ms zone might be contaminated by corrective eye-movements.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "Instantaneous movement-unrelated midbrain activity modifies ongoing eye movements" for consideration by eLife. Your article has been reviewed by 4 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Richard Ivry as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Terrence R Stanford (Reviewer #4).

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Summary:

This manuscript explores how microsaccades produced during active fixation are altered when a visual stimulus is flashed at parafoveal and more eccentric locations in the visual world. Focusing on neural activity in the superior colliculus (SC), the authors show that whenever visually evoked activity occurs in a small temporal window around microsaccade execution, the "visual" spikes modify the amplitude of the microsaccade. More specifically, they propose the additional spikes "leak" into the motor command in a lawful manner such that each extra spike from the same SC increases systematically the amplitude of the microsaccade.

Essential revisions:

Overall several concerns remain about the data analysis and interpretation of the findings of the authors, especially concerning the mechanistic interpretation of the findings. These mechanistic interpretations require additional analysis and further discussion or modification.

1. Rostral SC and intracollicular interactions: Concerns related to intracollicular interactions were salient in the initial round of reviews. These concerns still remain to some extent. It remains unclear whether the authors have convincingly determined that every additional spike contributes to the movement metrics. Much of the document is written like the microsaccade-related activity in the rostral SC is unaltered by a visual burst produced elsewhere in the SC. In the new figures added in this version, the focus is on proving that there exists a burst in the rostral SC while a visual burst occurs elsewhere in the SC. They do not test whether this burst is attenuated or statistically similar. The authors are aware of this possibility because they mention it several times in the response document, but the realization is scant in the manuscript.

If the change in microsaccade amplitude is entirely due to leakage of the visual activity, the activity in the rostral SC should be the same in the presence and absence of a visual burst. That is, the number of spikes in a window around the saccade duration should be unaltered. It is unclear whether this will be the case because, as the authors stated, the velocity profiles do not show double-peaks or inflection points to represent a separate addition of spikes from a different source. Two alternatives might be more likely and should be considered by the authors. One, the rostral SC neuron fires MORE spikes when the microsaccade is larger, which confounds the importance of the lawful relationship between additional the number of intrasaccadic visual spikes and microsaccade amplitude. Two, the rostral SC neuron fires FEWER spikes during the visual burst. Both alternatives suggest that intracollicular interactions may play a far more important role than additional intrasaccadic spikes from other parts of the SC.

The authors should analyze the activity of rostral SC neurons during microsaccades with and without a visual burst. If neural activity (either burst profiles or the number of spikes 15 ms before saccade onset to 15 ms before saccade end) is not altered, this would indicate that their lawful relationship is robust. In contrast, any alteration in rostral SC activity would support intracollicular interactions. At this point, one cannot exclude that the observed saccades is due to a newly organized population response and, crucially, one cannot differentiate between vector averaging and vector summation mechanisms; the authors favor the latter mechanism. Consequently, the lawful linear relationship might be merely an observation; it is no longer informative of any mechanism.

Even given intracollicular effects, it is possible that most of the results could be reconciled with a vector averaging scheme while also considering that averaging becomes less likely with spatial disparity. The authors should consider this possibility in their revision.

2. Eccentricity of stimulus. The dichotomy of the lawful relationship for stimulus presentation closer than or further than 4.5 deg is crucial to how the data should be interpreted. For eccentric stimulus locations (beyond 4.5 deg), there is clear evidence of bursts in both rostral and caudal SC. However, the visual spikes of caudal SC have minimal impact on microsaccade amplitude. This does not align with any reasonable model of saccade generation. If SC output, defined as number of active neurons or total number of output spikes, is relatively invariant across all saccade vectors and if visual spikes are the same as motor spikes, as the current paper asserts, then microsaccade amplitude must increase at a higher rate as the target is placed at increasingly eccentric locations. Not observing this effect implies that there may in fact be something different about "visual" and "motor" spikes, especially when the two bursts do not merge, such that visual spikes do not contribute to saccade amplitude. Concepts of motor-potent and motor-null subspaces borrowed from skeletomotor research or differences in the temporal properties of the two active populations offer viable alternatives (https://www.biorxiv.org/content/10.1101/132514v3.full). For parafoveal stimulus presentation (inside 4.5 deg), the active populations of neurons representing visual and motor bursts interact in an excitatory manner. They may effectively merge into one larger population with two local peaks, not unlike SC activity during averaging saccades of ultrashort latencies. Moreover, the combined population may take on the properties of the motor burst, which accounts for an increase in saccade amplitude with additional spike. The point is that the spatial distribution of the active population in the rostral SC is now altered, and one cannot convincingly conclude that the increase in microsaccade amplitude is merely due to more spikes added elsewhere. Given the arguments in the paragraph, it may be incorrect to state that "instantaneous readout of the SC map during movement generation, irrespective of activity source…explains a significant component of kinematic variability of motor outputs" (lines 40-42) and "the entire landscape of SC activity, not just at the movement burst site, can instantaneously contribute to individual saccade metrics" (lines 90-92).

To summarize, if visual spikes add to microsaccade amplitude "regardless of activity source"…"across the entire landscape of SC", then spikes beyond the 4.5 deg eccentricity must add more to saccade vector than spikes induced at more rostral sites. Lack of this effect might refute the authors' hypothesis.

3. Choice of saccade analysis window. It is unclear what precisely motivates the choice of window (0-20 ms after saccade onset) to assess the impact of visual spikes. Given the brief duration of microsaccades and after accounting for transduction time, the movement is nearly over by the time these spikes can impact the amplitude. Wouldn't a rigorous choice be to use the 20 to 25 ms window before saccade onset? This could maximize the impact of the visual spikes, as Figure 6 suggests.

4. Regression analysis. Readers will have difficulty with the linear regression analyses of Figure 4B and related figures. Specific comments: (a) It is questionable whether the linear regression is convincing for data beyond 4.5 deg eccentricity given the distribution of the data. The accompanying figure is an image of Figure 4 – —figure supplement 3, with the dark blue points circled in red. The linear fit does reflect the trend in the plotted points. Thus, either the regression analysis is incorrect or the illustration is inappropriate for the analysis. (b) The number of data points for 0 intrasaccadic spikes is about 5 times greater than for 1 and 2 spikes. Does this have an impact on the regression analysis output? Should another strategy be used? (c) It appears that the data for 0 intrasaccadic spikes are largely obtained from a baseline period. It is possible that the neural state during baseline could be different than around the time visual processing occurs. Thus, a stricter criterion for selection of microsaccades with 0 intrasaccadic visual spikes might be warranted.

https://doi.org/10.7554/eLife.64150.sa1

Author response

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

As you will see from the reviews, the reviewers expressed general interests and made many positive remarks. However, they also agreed on major issues that would require a substantial amount of additional experimentation and analysis. Some of the major issues include (1) There were major concerns about the relationship and consistency between experiment 1 and 2, and the interpretation of the microstimulation experiment. (2) The results of Experiment 1 might have several other interpretations including visual enhancement and competitive interactions, and could be influenced by several confounds. Within the domain on mechanisms of saccade generation, the analyses are not detailed enough to test competing models and provide conclusive mechanistic insight.

We would welcome submission of a new manuscript if it is possible to address these issues, but we judged them to be sufficiently significant that we thought it better to reject at this stage. Should you go this route, we would likely go to the same reviewers.

Thank you very much for the opportunity to resubmit our work. We have now introduced major edits to the manuscript, including the addition of extensive new experiments and new analyses that directly address all of the reviewer comments.

Below is an executive summary of our changes to the manuscript (detailed explanations are provided below in the specific responses to individual reviewers, and also in the actual revised manuscript):

1. We have now conducted substantial new experiments using linear microelectrode arrays inserted into the rostral SC (where movement bursts for microsaccades occur), the caudal SC (where visual bursts for the appearing stimuli occur), or simultaneously in both the rostral and caudal SC together. Please see the new Figures 8-11 of the revised manuscript. These experiments have allowed us to:

a. Confirm previous observations that a visual stimulus onset somewhere on the SC map is associated with reduced activity elsewhere in the map as long as there are no saccades directed towards that second SC location (e.g. Dorris et al., 2007; also see Hafed and Krauzlis, 2008)

b. Convincingly demonstrate that if the visual bursts in the SC come simultaneously with the triggering of a saccade to another site (in our case, a rostral site because of the small size of microsaccades), then the reduced activity alluded to above is actually replaced by movement bursts, confirming our presumption in the original version of the manuscript that there were two sites of elevated SC activity in our experiments. We believe that this is a very important addition to our manuscript, and to the literature as a whole (as we describe in more detail below)

c. Support our original experiments with recordings in single SC sites, because we still found that visual bursts occurred peripherally at the time of microsaccade triggering

2. We have now also added new experiments for our original visual burst analyses. This time, the stimuli used had other visual features (spatial frequency gratings versus stimulus contrast manipulations), and, more critically, there was a prolonged period of fixation after stimulus onset. Please see the new Figure 7 and Figure 7 —figure supplement 1 of the manuscript. These additional experiments were critical for the manuscript because:

a. They have allowed us to confirm that our original results simply depend on the presence of movement-unrelated spiking activity on the SC map, irrespective of the source of activity

b. They have allowed us to substantially strengthen our interpretations by looking at spiking activity long after any visual bursts (up to >1 second later). Long after visual bursts, the SC might maintain low level discharge (that can sometimes be completely absent before stimulus onset in many neurons). This has allowed us to ask whether any spiking activity during such low-level discharge would still be read out and influence movement metrics if such spiking occurred simultaneously with movement triggering. Remarkably, this was indeed the case (please see Figure 7 and Figure 7 —figure supplement 1). Therefore, one does not even need visual “bursts” to see modification of movement metrics. We consider this new analysis critical for supporting our study

c. They had sufficiently long fixation periods to allow us to demonstrate that our effects are robust enough to also be observed on a single neuron basis (please see Figure 7 and Figure 7 —figure supplement 1)

3. In the original visual burst analyses, we have now compared the relative relationship between either visual or visual-motor neurons and the final behavioral outcomes (saccade amplitudes). This was important because it allowed constraining the mechanisms of SC readout during saccades even further, and to clarify potential functional differences between visual responses in visual neurons versus visual responses in visual-motor neurons (a topic that remains wide open in the SC field)

4. Because the above experiments and analyses were extensive (they have added 5 new figures and 9 new or modified figure supplements), we have decided to defer publication of our microstimulation experiments to a later subsequent study. Otherwise, allocating sufficient space for the microstimulation experiments (in addition to the new data) would have resulted in an unnecessarily large and unwieldy paper. The additional new experiments described above are much more valuable than the microstimulation component for the current manuscript, as also suggested by the reviewers

Please note that our omission of the Dorris et al., 2007 citation in the original version was purely erroneous due to a mistake in our citation manager. We sincerely apologize for missing this error during proofreading. In fact, in our original submission, we wanted to suggest Michael Dorris as a reviewer for this manuscript, and we were only prevented from doing so because we could not find his new affiliation on the internet for inclusion in the online submission system.

In any case, we believe that all of the reviewers will be happy to see that our new microelectrode array experiments (Figures 8-11) both confirm and add to his (and others’) earlier experiments. Specifically, if no microsaccades occur at the time of peripheral visual bursts, then we do indeed observe a reduction in SC activity at the rostral sites (“lateral interaction”). However, if the peripheral visual bursts occur simultaneously with the triggering of microsaccades, then there are actually two sites of SC activity bursts: the rostral SC site for the movement bursts, and the caudal SC site for the visual bursts. We strongly believe that this is a very important addition to the literature.

Reviewer #1:

This study investigates the influence of visual stimuli and spiking activity in distant SC (superior colliculus) locations on small microsaccadic movements during fixation. The authors show that visual stimuli and activity in these distant locations modulates the ongoing microsaccadic movements. The authors find however that nearby locations have more powerful effects than distant locations, which challenges existing models based on vector-averaging (as one would expect distant locations to exert more powerful effects). Overall these findings provide a very interesting addition to the literature. My main critique is the possibility of lateral interactions or influence on the activity of more foveal neurons.

Thank you very much for bringing up both of these interesting points. We have now added new experiments directly addressing both of them. Specifically, please see Figures 8-11 of the revised manuscript. We have now recorded from foveal sites, eccentric sites, and simultaneously from both foveal and eccentric sites. The new recordings in the eccentric sites confirmed all of our other analyses in the original manuscript (i.e. that visual bursts still happen intrasaccadically). The new recordings at the foveal sites confirmed that movement bursts still happen when the movement triggering coincides with the presence of eccentric spikes (this was an important addition, and we thank you for bringing it up). And, most importantly, the new simultaneous recordings confirmed that at the time of movement triggering, it is still possible to have simultaneous peripheral spikes. This means that at the time of the readout of the SC population to implement the actual saccade, additional spikes from the peripheral visual burst are present on the SC map. Our other analyses (e.g. Figures 4-6 and the new Figure 7, and their associated figure supplements) clearly demonstrate that such additional “visual” spikes do indeed matter at the time of readout (because they systematically add to saccade amplitude).

Most interestingly, the new additional experiments do not deny that there can be lateral interactions. In fact, we confirmed that if no microsaccades are triggered, then peripheral visual bursts are indeed associated with reduced rostral SC activity (please see Figures 8-11). This is consistent with prior work (e.g. Dorris et al., 2007; also see Hafed and Krauzlis, 2008, and others). However, the key difference is that our study was not focusing on the case of “no movement triggering” at the time of visual bursts (i.e. the interaction between visual bursts and “movement preparation”); rather, we were interested in what happens if there are both visual bursts and simultaneous movement triggering. In that case, one expects (and we confirmed) that the movement bursts will still happen.

1. If I understand correctly, the authors suppose that the effects on the saccade trajectory are mediated by the projections of neurons in distal locations to other brain areas. However there are lateral inhibitory interactions within the superior colliculus and the effects reported here could potentially be mediated by these lateral interactions that modulate the activity of neurons driving the microsaccadese.

The most classic and accepted view of lateral interactions would suggest that peripheral visual bursts are associated with decreased rostral SC activity. For example, in Hafed and Krauzlis, 2008, we recorded rostral SC activity at the time of a peripheral visual stimulus onset. This rostral SC activity (in the absence of microsaccades) was indeed reduced, and this is also consistent with Dorris et al., 2007 as well as other work by Munoz and colleagues (also see our confirmation of this in the current manuscript – in the absence of microsaccades – in Figures 8-11). However, a reduction of rostral SC activity would mean smaller microsaccades at the time of the flashes, not larger microsaccades like we saw.

In fact, one can modify the location of the visual flash and change the likelihood of whether to get an increase or a decrease in microsaccade amplitudes: decrease for foveal flashes (Rolfs et al., 2008) and increase for eccentric flashes (Hafed and Ignashchenkova, 2013; Buonocore et al., 2017; also confirmed in our current study). Indeed, even with foveal flashes, one can get increased microsaccade amplitudes under specific conditions related to the relative position of the movement goal and the visual flash location (Buonocore et al., 2017). All of these very disparate behavioral effects on microsaccade amplitudes (increases versus decreases) cannot be parsimoniously explained by inhibition of the rostral SC by peripheral visual bursts. Instead, they can best be explained by the readout idea that we put forward in our current study. Indeed, our new experiments (Figures 8-11) confirm that if visual bursts occur peripherally at the same time as microsaccade triggering, then rostral SC activity still exhibits movement-related bursts (and not decreases as predicted by lateral inhibition).

Therefore, when the SC map is being read out to implement the current saccade, there are two loci of elevated activity (Figure 11). Moreover, analyses like in Figures 47 demonstrate that such readout is systematically dependent on every spike emitted by every active neuron during movement execution.

In addition to the above figures (4, 7-11, and the associated figure supplements), please also see the associated text edits documenting the above ideas (e.g. lines 441-538).

To summarize, we believe that the key issue here is the idea of temporal coincidence. All we say is that if there happens to be peripheral spiking activity at the time of movement triggering (i.e. if there is a temporal coincidence of spiking), then the readout will take all simultaneous spikes into account. The individual visual bursts or movement bursts may be slightly modulated due to lateral interaction (e.g. visual enhancement and visual suppression around the time of microsaccades/saccades), but the key point is that they still happen.

2. A related point is that the visual stimulus might exert some effects directly on the neurons driving the microsaccades, either through lateral mechanisms within the retina or within the superior colliculus.

The best control would be to analyze directly the neurons in foveal regions. What happens there? Is their firing rate affected or not? It appears that the authors have this data but they do not report this.

Thank you for this very important suggestion. As stated above, we have now added new experiments directly recording rostral SC activity at the time of peripheral visual bursts (please see Figures 8-11, and the associated text edits). We have now confirmed that rostral SC activity indeed still bursts for microsaccades that are temporally coincident with peripheral visual bursts in the SC.

Once again, we do not deny that there may be modulatory influences of visual stimuli on the rostral SC or vice versa. For example, we do see evidence for visual burst modulation (Figure 2 —figure supplement 1). Moreover, microsaccade motor bursts might be slightly modulated relative to when microsaccades happen in the absence of any visual transients (such slight modulation would actually be conceptually similar to modulation of saccade motor bursts when making saccades towards moving targets in the work of Goffart, Gandhi, and Keller). However, our point is simply that at the time of movement triggering, there are two loci of activity elevation on the SC map, and the locus of activity in the periphery seems to matter significantly because each additional spike by each active neuron in the periphery matters (e.g. Figures 4-7). As stated above, lateral interaction alone cannot explain the large diversity of possible behavioral effects of visual flashes on saccade metrics.

3. The authors should provide more raster plots of activity of neurons and describe more clearly how many neurons were recorded/analyzed throughout the legends and results text.

We have now gone through the entire text to clarify all of this information. We have also added raster plots in Figure 2, as also suggested by Reviewer 2. Please also note that Figure 5 and the new Figure 5 —figure supplement 1 show all spiking activity from all of our trials in the first two experiments (contrast task and spatial frequency task). These figures show spikes from each individual trial in our database used in the analysis. Finally, in Figure 7, we showed an example neuron (with raster plots) in panel A, and we also showed that our results could be observed on an individual neuron basis in panels B, C (a second example neuron is also shown in Figure 7 —figure supplement 1). Moreover, Figures 9 and 10 show 4 different example neuron results.

4. What functional cell types are recorded by the authors? This should be described.

This information was presented in Methods (line 762-765; 784-785), but we have now also added it to Results and Discussion (please see lines 267-273; 682-692).

Please note that we have now also added an interesting new analysis comparing the relationship between spiking and microsaccade amplitudes in visual versus visual-motor neurons (Figure 4 —figure supplement 1). This turned out to be very informative because it demonstrated that similar visual bursts in visual and visual-motor neurons have different correlations with saccade amplitudes. Visual responses in visual-motor neurons seem to be more relevant for saccade amplitude metric changes than visual responses in visual neurons, which is (in retrospect) consistent with several other findings in the literature (a recent example from our lab would be Chen and Hafed, 2017).

Reviewer #2:

The superior colliculus (SC) is recognized for its role in sensorimotor transformations. A vast number of SC neurons discharge both when a stimulus is presented in their response fields and also when a saccade is directed to that location. Mechanisms have been proposed for differentiating 'sensory' from 'motor' activity across the SC population and, furthermore, computing the metrics and/or kinematics of the observed saccade. This study shows that if additional spikes, whether evoked by a visual stimulus or through electrical stimulation, are introduced at a SC location away from the active 'motor' population and around the time of saccade, then these spikes contribute to the size of the saccade. Amazingly, effects of adding single spikes per neuron (but from many neurons) are noticeable in the analyses. It is a thought-provoking finding and, provided several serious concerns are mitigated satisfactorily, has implications on multiple facets of SC role in saccade generation.

Thank you very much for such encouragement. We have made a faithful effort to address all of the comments, and we have added extensive new data that we believe strongly supports our original findings.

1. The data shown in Figure 2 do not align with the working model of the SC. A fairly well-known study by Dorris, Olivier, and Munoz (https://doi.org/10.1523/JNEUROSCI.4212-06.2007), which surprisingly is not cited here, showed that a visual stimulus (distractor) interferes with motor preparatory activity elsewhere in the SC. The preparatory activity is enhanced if the target and distractor populations are in close proximity but suppressed if the distractor is far way, including in the opposite hemifield. This finding – complemented by slice studies by Isa, Hall, and others -has established a framework for local excitation and mutual distal inhibition in the SC. What is shown in Figure 2 does not conform to this framework and, if true, it is too important a result to be overlooked.

We sincerely apologize for the error in citation with respect to Dorris et al., 2007. As stated above, this was a mistake in our citation manager, and we apologize once again for not catching this mistake during proofreading. We have now included citations to Dorris et al., 2007 and also Isa et al.

More importantly, we have also added new experiments in which we explicitly recorded at the movement generation sites (rostral SC) at the same time as peripheral visual bursts (please see Figures 8-11). Briefly, in the absence of microsaccades, we indeed replicated Dorris et al., 2007. That is, there was a reduction in rostral SC activity at the same time as there was a peripheral visual burst. However, critically, if a microsaccade were to be triggered at the same time as the peripheral visual burst, then the movement burst still actually happened. Therefore, our results clearly show that there are two loci of “bursts” on the SC map when microsaccades occur simultaneously with perhipheral visual bursts (please see Figures 8-11). This is, in our opinion, an important addition to the literature, as you also agree.

Please note that the keyword here is your mention of “preparatory”. We do not deny that in the absence of microsaccades, rostral SC activity would be reduced simultaneously with peripheral visual bursts (please see Figures 8-11 and our earlier work: Hafed and Krauzlis, 2008). However, if a microsaccade were to be triggered simultaneously with the visual bursts, then there will still be a motor burst instead of activity reduction. Even in Dorris et al., 2007, when an early saccade was erroneously generated by the monkeys, there was still a burst of activity instead of activity reduction. Our focus in the current study was exactly on the simultaneity of movement triggering and movement-unrelated activity.

a. I realize that the activity recorded in this study is from neurons at the "visual", rather than the "motor", site. However, if interactions between the two populations are mutual, then the effect should arguably be observed in both populations. Should we be rethinking this conclusion – are the competitive interactions not mutually effective?

b. The motor activity relevant here is in the rostral SC and associated with microsaccades, while the Dorris study focused on more caudal regions that encode larger amplitude movements. However, an underlying theme of a large body of Hafed's studies is that our knowledge of large amplitude saccades and their neural control extend to microsaccades also. In fact, this is the justification used for the microstimulation experiments reported in the manuscript. Should we be second guessing this conclusion – perhaps there is something unique about microsaccade control?

c. The relative timing of activity in the 'visual' and 'motor' populations are different in the two studies. I believe Dorris et al. only focused on trials when distractor-driven activity occurred during saccade preparation rather than during execution. In contrast, this Buonocore et al. manuscript draws our attention to when the two bursts are effectively coincident. But it is not clear why competitive interaction effect should disappear during a saccade.

We lump our responses here to a, b, and c above exactly because these points (a, b, c) all progressed in a logic that ultimately reached a conclusion (in c) that is directly consistent with our message: we fully agree that our focus here is on the coincidence of bursts. In our new experiments of Figures 8-11, we found that if the visual burst happens in the absence of microsaccades, rostral SC activity is indeed reduced, consistent with Dorris et al., 2007. However, when the microsaccades are triggered at the time of the visual bursts, there is still a rostral microsaccade-related burst. As a result, there are two loci of elevated activity at the time of movement triggering (i.e. at the time of readout). The most intriguing finding in this regard, as all reviewers agree, is that the elevated activity at the visual burst site clearly matters for behavioral readout, because there is a systematic relationship between the addition of individual spikes by individual active neurons and the movement metrics (e.g. Figures 4-7 and their associated figure supplements).

So, we believe that there is no contradiction with the prior literature. Rather, we believe that we add interesting new observations that extend such prior literature.

There is also no contradiction with the idea that microsaccades are similar to larger saccades. In fact, even in Dorris et al., 2007, when the monkeys erroneously triggered the saccades at the time of the “distractor”, there was a burst rather than a reduction in activity, similar to what we show here in Figures 811.

Concerning the idea that competitive interaction might disappear entirely during a saccade, this need not be the case. Motor bursts are known to be modulated by several factors. For example, when making saccades to moving targets (the work of Goffart, Gandhi, and Keller), SC motor bursts can be modulated (i.e. the burst of the intended movement still occurs but the actual movement might be modified by the moving stimulus, which can give the impression that the movement field was modified or modulated). So, it is very conceivable that both the visual and motor bursts may appear to be somewhat “modulated” at the time of movement triggering. However, the key is that they still occur and will therefore matter for readout. In fact, we know from our prior work that peripheral visual bursts can be modulated if stimulus onset comes within a specific time window from microsaccade onset (e.g. Chen et al., 2015). The difference in the current study is that we focused on rare microsaccades that are triggered right at the time of the visual bursts (i.e. slightly later than those in Chen et al., 2015). For these “rare” microsaccades, the visual bursts were still modulated by microsaccade direction in a manner consistent with Chen et al., 2015 (see Figure 2 —figure supplement 1), but the key message, once again, is that these bursts still occurred. Moreover, their occurrence systematically mattered for behavioral readout (Figures 4-7).

In other words, at the time of “gate opening” to implement a current movement, there are two bursts that are both read out by downstream populations. Competitive interactions might slightly modify both of these bursts, but they do not suddenly eliminate one of them for readout. This is exactly our message.

d. These results are also inconsistent with the large body of literature on saccadic or visual suppression in the SC (e.g., D.L. Robinson and Wurtz).

We now do a better job of clarifying that there is no inconsistency. In Figure 2, microsaccade directions were pooled together. When we separated movements according to their direction (towards versus opposite the RF location), we did, in fact, see evidence consistent with visual burst modulation as a function of microsaccade direction in our data (e.g. Figure 2 —figure supplement 1; also please see Figure 11 where the visual burst was suppressed because most microsaccade sessions were in the opposite direction from the peripheral stimulus location). Such evidence is directly consistent with Chen et al., 2015, which itself was the microsaccade variant of the early pioneering work by Robinson and Wurtz and colleagues.

So, there is no contradiction. The key point to keep in mind here is that our alignment in this study was between microsaccade triggering and visual burst onset (and, more generally, spike occurrence) and not stimulus onset. Aligning microsaccade onset to visual burst onset (as opposed to stimulus onset) allowed us to focus on a few rare movements that are triggered right at the time of SC visual burst spiking (the idea of simultaneity between two separate bursts). Such alignment was highly informative with respect to the mechanisms of SC readout for saccades.

Please also note that we added new experiments on sustained activity in the complete absence of visual bursts (Figure 7 and Figure 7 —figure supplement 1, as well as their associated text edits). We found a very similar impact of peripheral spiking activity on movement metrics. In other words, there is not even a need for a visual burst to occur in order for us to make our point. In our mind, Figure 7 is one of the most important analyses of the current manuscript, because it demonstrates that any spiking activity, irrespective of its source, can be read out if it simply happens to occur simultaneously with saccade execution.

e. It would be tremendously valuable if the authors also show what happens to the motor burst when visual spikes are added elsewhere in the SC, not just during the execution phase of a microsaccade but also in the preparatory period preceding it. Given that the Hafed lab does a lot of neural recordings in the rostral SC during microsaccades, the data may already be available or easily collectable. Without this data, it is difficult to offer full support of the results presented in this manuscript.

Thank you very much for this suggestion, which echoes suggestions by Reviewer 1. We have now explicitly added exactly these data. We have recorded, using linear microelectrode arrays, in both the rostral and caudal SC while presenting visual stimuli peripherally. Please see Figures 8-11 and their associated text descriptions. As stated above, these data were very important because:

– They confirmed that in the absence of microsaccades, peripheral visual bursts are associated with reductions in rostral SC activity (consistent with Dorris et al., 2007 and others; this also confirms our earlier observations of reductions in rostral SC activity at the onset of peripheral stimulus onsets in Hafed and Krauzlis, 2008).

– They demonstrated that with coincident triggering, there are two loci of bursts in the SC (one caudally and one rostrally).

– They also confirmed (Figure 11) that there can still be modulatory effects on the visual bursts themselves – for example, most of our sites were associated with microsaccade movement fields opposite to the peripheral visual burst location. As a result, visual bursts were suppressed (directly consistent with Chen et al., 2015; please also see Figure 2 —figure supplement 1).

2. The data in Figures 4 and 5 are rather remarkable. They make a compelling case for systematic increase in saccade amplitude as additional spikes/neuron are coincident with the motor burst. A few points of clarification:

a. Please also include velocity profiles in Figure 4A. Are they bell-shaped or like control movements? Or do the velocity profiles exhibit an inflection point or multiple peaks (like that observed for the microstimulation experiments reported later in the manuscript)?

We have now added these velocity plots. Please see the new Figure 4. We have also added example eye position and velocity plots to Figure 2. Please also note that we have previously analyzed microsaccadic kinematic alterations at the time of visual flashes at length in Buonocore et al., 2017. In fact, that earlier study directly motivated our current experiments.

To directly answer your question here, the velocity curves did not exhibit multiple peaks like observed with microstimulation, so this is an important difference between the effects of visual flashes and the effects of electrical microstimulation (please see below for further thoughts concerning microstimulation).

b. As best as I can tell, the data are pooled across all trials and all neurons (like in Figure 5). If true, please make this (more) explicit in the text and figure caption. It also raises the concern that the effect may be weighted more by the subset of neurons that have substantially more trials than other neurons. Please provide summary of number of trials per neuron. Importantly, provide insights into how many neurons' data conform to the results shown in Figure 4.

We have now gone through the entire manuscript to clarify details about neuron counts, numbers of trials per neuron, and other variables (e.g. lines 763-768; 784-789; 811; 820-828).

We have also added a whole new set of experiments related to Figure 4. Specifically, in a new experiment, we have now used visual onsets consisting of different spatial frequencies rather than stimulus contrasts (the new experiment 2). The key here was to add even more neurons to our database, and to also demonstrate that the effects do not depend on a specific visual stimulus type. The results of Figure 4 held up even though not all neurons in this new experiment were shared with the original experiments (please see the new Figure 4 —figure supplement 4).

Most importantly, these new recordings in the new experiment 2 also had a prolonged fixation interval to allow us to do a much better job on the original Figure 6C, D, which was indeed based on very sparse data. The prolonged fixation interval had an important added advantage: we now had many more microsaccades during sustained fixation per individual neuron. Therefore, we could pick example neurons and replicate the new Figure 7 analysis on them. Indeed, the example neuron in Figure 7 showed results consistent with our population analyses. Figure 7 —figure supplement 1 also shows a second example neuron. We are therefore very confident that our results are consistent across the SC population, and even robust on a per-neuron basis (see Figure 2A, B). Please also see Figure 7 and its supplement.

Finally, please note that metric effects on microsaccades by visual onsets are very robust, in both humans and monkeys, as we mentioned above (e.g. Rolfs et al., 2008; Hafed and Ignashchenkova, 2013; Buonocore et al., 2017). This increases our confidence in the robustness of our results.

c. If I am mistaken and the analysis is performed one neuron at a time, then please underlay in Figure 4B the distribution of all points for each x-axis value (as in Figure S4).

No, you are correct. The variable of interest for us was the behavior (i.e. the individual microsaccade). We have clarified this throughout the manuscript (e.g. lines 220-224; 389-390; 410-412). Also, we have added a whole new experiment with additional neurons and additional analyses beyond the visual burst interval (e.g. Figure 7). This new experiment has even allowed us to demonstrate individual neuron results more convincingly (Figure 7 and Figure 7 —figure supplement 1). Finally, Figures 9, 10 show 4 different example neurons from the new experiment 3 as well.

3. Several aspects of Figure 6 are bothersome and require clarity. Frankly, it is not clear that the effect the authors want to emphasize is actually present in the data.

We have now split the figure into two separate figures: Figure 6 containing the original A, B panels, and a new Figure 7 containing completely new experiments. For Figure 6 (i.e. the original A, B panels), this figure was important to add in the study because in Figure 5, we had just arbitrarily picked a “visual burst interval” (30-100 ms after stimulus onset). This is arbitrary and does not describe the temporal relationship between individual spiking activity and amplitude changes in a more assumption-free manner. As a result, Figure 6 (i.e. the original A, B panels) became absolutely necessary in our mind, and the data in it are robust (we even added new experiments with spatial frequency gratings to support our findings; please see Figure 6 —figure supplement 1).

For Figure 7 (i.e. the original Figure 6C, D), we fully agree that the original results were too sparse. The problem was that the original experiments had too brief a fixation interval. We therefore did not have much data long after the visual bursts to analyze the potential influence of “spontaneous” spiking activity outside of the realm of visual bursts. As a result, we have now decided to add a whole new set of experiments (the “spatial frequency task”). In these experiments, the monkeys were presented with gratings of different spatial frequencies (as opposed to stimulus contrasts), and, critically, the stimulus in the RF was maintained for >1 second in every trial. As a result, we could now ask the important question of whether any spiking activity (well after the end of the visual burst) can have similar effects on movement amplitudes. This was indeed the case, as we show in Figure 7. As stated above, this effect was robust in individual neurons as well (Figure 7 and Figure 7 —figure supplement 1). Therefore, with the addition of these new data, we are quite confident that the new figure shows robust results, which we view as being perhaps the most important confirmation of our hypothesis.

a. In Figure 6C, there aren't enough points for 3 and 4 intra-saccadic spikes to justify using mean as the average measure. Median is a better choice and, in this case, the suggested effect will likely not exist. This will likely change the text on Lines 374-378, which incidentally deserves to be backed with a statistical test.

b. In Figure 6C and 6D, color the dots according to the histograms in Figure 6A and 6B, respectively. Basically, the color of dots should change from dark red (green) to light orange (yellow) as y-axis value increases.

c. Data in Figure 6A and 6C suggest some discrepancy. Figure 6A indicates that microsaccades larger than 1 deg were observed, but Figure 6C does not show any saccades greater than one degree. Same concern for Figures 6B and 6D.

As stated above, we fully agree that Figure 6C, D in the original manuscript had data that were too sparse, for reasons explained above. As a result, we have now added completely new data with prolonged fixation intervals. The results are now relegated to their own figures (Figure 7 and Figure 7 —figure supplement 1). We believe that there is now no inconsistency.

4. I am less excited about the experiments using microstimulation during visually-guided saccades.

a. The authors want us to accept that the relationship between the sensory and motor populations of neurons remains the same in the two experimental paradigms (L424-430). I would've accepted this premise prior to reading this manuscript, but the lack of competitive interactions makes me question this assumption, particularly as the electrode placement moves away from the rostral SC.

Because we have added extensive new data (5 new figures and 9 new or modified figure supplements), we have now decided to defer our microstimulation results to a later follow-up manuscript. We sincerely hope that you agree with our choice.

Just to clarify, concerning your statement on competitive interactions, please see our detailed responses above. We do not think that there is a contradiction.

b. Example velocity traces are not unimodal. Perhaps this is due to stimulation occurring late within a saccade, but it looks more like the ongoing saccades is truncated and potentially replaced by another movement command. These results are indicative of competitive interactions.

As stated above, we have decided to defer publication of our microstimulation results to a follow-up study since the new recording experiments were extensive and added many figures (and much more support to our hypotheses). Just to clarify, we do not believe that the saccades were truncated; they reached similar peak velocity to the baseline saccades in their “first” velocity pulse. Instead, we believe that an additional velocity pulse was added by microstimulation. In any case, this is no longer being discussed in the current manuscript for the reasons described above.

5. Data in Figure 8 are difficult to interpret.

a. Normalized amplitude increases earlier for 1 electrical spike compared to 2 and 3 spikes. Is this significant and how can this be? We can't interpret this result until we have a sense of variability in normalized saccadic amplitude in the absence of stimulation.

b. Given the arguments raised above about Figure 7, this analysis should arguably not include displacement associated with the second bell-shape in the velocity profile.

c. Saccade amplitude peaks when microstimulation and saccade onsets are coincidental, but according to Figure 7, the effect is observed as a second peak in velocity, which occurs 40-50 ms later, and this is substantially longer than the efferent delay. So, pieces are not adding up.

As stated above, we have decided to defer publication of our microstimulation results to a later manuscript, since the current one grew substantially in size with the extensive new recording data that were added. We hope that our follow-up study will provide a nice culmination of our current one and the recent Buonocore et al., 2016, 2017, which also discussed behavioral analyses of saccade kinematic alterations with visual flashes.

Reviewer #3:

Overall, this is a strong manuscript that considers a topic of significant interest to those interested in visuomotor control and attention. Main strengths: 1) It provides important insight for understanding the kinematics of saccades that would be made under natural viewing circumstances and 2) good experimental design and analysis have yielded a compelling dataset that speaks to the main conclusion that currently executed SC motor commands are influenced by the instantaneous readout of any concurrent visually-evoked activity within the SC map. Weakness: Although the study provides an important additional piece to the SC readout puzzle, it does seem to strongly constrain possible mechanistic frameworks.

Thank you very much for this assessment. We have added extensive new analyses and experiments that we believe strongly constrain readout mechanisms for the SC:

1. In the new Figure 7, we have added new data with substantial periods of prolonged fixation. This has allowed us to demonstrate that any kind of spiking activity, not just within a visual “burst”, can be read out in a manner that influences saccade size if it occurs simultaneously with saccade triggering

2. In Figure 4 —figure supplement 1, we have compared the relationship between “injected” visual spikes and microsaccade amplitude for visual versus visual-motor neurons. This has implications for the functional role of otherwise very similar visual bursts in these two types of SC neurons

3. In Figure 4 —figure supplements 2 and 3, we have demonstrated that eccentricity matters for the impact of visual spikes on microsaccade amplitudes. This directly constrains the current mini-vector models (e.g. van Opstal and colleagues), because our experimental measurements show opposite effects from what would be predicted by these models

4. Most importantly, we have performed additional recordings in the rostral and caudal SC to demonstrate that there will still be rostral SC activity bursts at the time of peripheral visual bursts. This is fundamentally important to document, especially given the apparent perception by all reviewers that lateral inhibition should mean no rostral bursts at the time of the caudal visual bursts. We show that there can be lateral competition in the absence of saccade triggering, but that there are simultaneous motor and visual bursts when a saccade is triggered. This is fundamental, because it demonstrates that lateral interaction is not always sufficient to completely eliminate any spiking activity at the non-visual-burst sites.

Specific comments:

The experiment in which visually evoked activity is "injected" and alters the metrics of microsaccades is elegant and compelling. To me this is what makes the manuscript worthy of publication as it shows quite definitely that such activity is read-out as part of the ongoing motor command. This has important implications for understanding the execution of saccades during natural scanning when the perception/action sequence is considerably more fluid than for a typical laboratory task. With respect to this main strength, the results are clearly presented and interpreted.

The results of Experiment 2 are also well presented, but, in my view, there are some issues with interpretation that might be remedied with further discussion.

The microstimulation results are interesting but think there are some issues that limit the conclusions that one might draw regarding the SC readout mechanism.

1. The injection of microstimulation pulses is suggested as an analog of "injecting" visual activity. But not all SC saccade-related neurons are visually responsive, and the electrical stimulation is certain to impact visual-motor and motor cells alike. Thus, microstimulation does not so cleanly tap visually driven activity as does the visual stimulus employed in the first experiment. That microstimulation alone does not trigger saccades does not mitigate this concern since 1-3 stimulus pulses would not be expected to trigger a saccade in any case. Some consideration of this distinction seems warranted.

As mentioned above to the editors and to the other two reviewers, the addition of extensive new data and experiments (5 new figures and 9 new or modified figure supplements) has made us decide to defer publication of the microstimulation results to a later paper. This would allow us to present a much more complete microstimulation study (without compromising the current study because the new data that we have now added richly clarifies our mechanisms).

2. There have been many variants of SC readout models that are or are not consistent with producing the form of input required of brainstem local feedback circuit models as originally proposed by David Robinson and others (e.g., Jurgens et al., 1981) and which likewise either support or supplant the vector averaging scheme proposed by Sparks and colleagues (Lee et al., 1988). It is not entirely clear how the present microstimulation data inform or distinguish between traditional or later developed frameworks. For example, given the spatial configuration employed here (i.e., in line, stim always more eccentric), I could imagine how a simple vector averaging scheme could yield the linear increase in amplitude with additional pulses if one assumes the pulses produce a transient modification of the SC's desired displacement signal. But then, I think more recent schemes (e.g., that of vector summation) could work equally well. More discussion of how these data constrain current models would be welcome.

Yes, this is one more reason why it made sense for us to defer the microstimulation results to a later study, especially given the large amount of additional recording data that we have added.

Having said that, we do believe that our recording data (especially the new results in Figures 8-11 and the eccentricity analyses in Figure 4 —figure supplement 3) can be quite informative with respect to the different models. Specifically, we fully agree that the role of SC motor bursts in controlling saccades remains to be open, and we believe that our current manuscript helps to clarify some sticking points. For example, the mini-vector model (e.g. van Opstal and colleagues) would predict that more eccentric visual bursts would cause even larger effects on microsaccades than less eccentric visual bursts (i.e. 1 spike from a more eccentric neuron should contribute a larger “mini-vector” than 1 spike from a less eccentric neuron). However, this is clearly not the case in our data, so this is already a very important constraint on models (please see the new Figure 4 —figure supplement 3 explicitly parameterizing the impact of eccentricity). Similarly, our new experiments (Figures 8-11) constrain the role of lateral interaction interpretations, as discussed at length with the other two reviewers above. Briefly, it is not necessarily true that if there is a visual burst somewhere, then there can be no other burst elsewhere. Our Discussion section mentions these and other constraints at length (lines 654-677).

3. Related to the above, the microstimulation results are not unexpected based on how one would expect it to interact with an ongoing movement. This we could intuit from extant literature (as properly cited by the authors). The weakening of the effect with eccentricity is new and interesting, but I wonder if it is specific to eccentricity or if it generalizes in some way to distance in an SC spatial coordinate frame.

We are glad that you think that the microstimulation results are consistent with the literature. Our original intent was to support the recording data by injecting single, double, or triple pulse microstimulation. However, as stated above, it makes sense to defer such data to a later study. We have therefore removed the microstimulation results from the current manuscript. We believe that the new recording additions throughout the manuscript (e.g. the new Figure 7 and several analyses related to Figures 4-6) now do a better job in supporting the original recording data.

4. I understand that microsaccades, provide only the option of a more eccentric stimulus or stimulation, however, it seems like an experimental variant in which the "ectopic" stimulus was less eccentric might have been of use in distinguishing between readout mechanisms. I'm not suggesting this as a necessary addition, but some discussion might be valuable.

We have now added additional mention of this issue, as suggested. Please see, for example, lines 137-145 and 578-596. Please also note that we had previously discussed the different variants of saccadic alterations from the perspective of SC readout in our earlier work. For example, Buonocore et al., 2016 showed that saccade amplitude can be decreased with less eccentric flashes, and Buonocore et al., 2017 showed that saccade amplitude can be increased with more eccentric flashes. These two previous studies directly motivated our current manuscript, and they are now mentioned early on (e.g. near Figure 2), as well as in Discussion.

5. There is a recent paper by Gandhi and colleagues (Smalianchuk et al., 2018) that seems quite relevant as it relates to instantaneous SC readout mechanisms. Although it does not deal with "visual" activity, there is enough conceptual overlap that it should be referenced and/or discussed at the authors' discretion.

Yes, we now realize that we cited the paper erroneously as Ivan et al., 2018. This was due to an error with our citation manager, as we also explained above concerning the missing Dorris et al., 2007 citation. We apologize for that. We have now proofread all citations more carefully.

Reviewer #4:

In this study, Buonocore and colleagues investigate the influence of visual neural activity in the superior colliculus (SC) on eye-movements. In the first experiment, they show that visual activity in the SC – induced by a peripheral grating – was unaffected by concurrent microsaccades. Interestingly, the size of microsaccades was biased by the visual stimulation, and the higher the number of spikes around the its onset, the larger the amplitude of the eye-movement. In a second experiment, using electrical microstimulation of the SC during a saccade task, they show that even a small number of induced spikes (3) was enough to bias the animal's eye-movement response towards the stimulated site. Overall, this is an interesting study, with significant implications for saccade generation models in the SC.

The authors often use selection criteria for their data analysis that is not clearly justified. One criterion that might be particularly problematic is to focus most of their analysis on eccentricities <= 4.5 deg. Their justification for this is that "these had the strongest effects on microsaccades" (line 189). Analyses for values > 4.5 deg, showing usually just weaker effects, are presented in the supplementary materials. My main concern is that this approach might be hiding an underlying interaction between eccentricity, SC firing rate, and microsaccade amplitude, which could contradict the other findings presented. The firing rate values in Figure S4 suggest that there might be a positive correlation between eccentricity and SC firing rate (higher firing for more eccentric RFs). While microsaccade amplitudes seem negatively correlated with eccentricity. If this is true, the analysis pooling together all data would suggest that higher firing would be associated with smaller amplitudes (the opposite of what is shown here). Of course, that eccentricity could be considered a confounding variable. So, one possible way to deal with this problem would be to perform a regression analysis to predict microsaccade amplitudes using both eccentricity and SC activity as independent variables.

Thank you for this very helpful comment.

First, just to clarify, the slope of the relationship between the number of spikes and saccade amplitude was still positive at the more eccentric sites. That is, the dependence of saccade amplitude on the number of injected visual spikes was similar (more intra-saccadic spikes mean more microsaccadic amplitude), but with a weaker effect overall. So, it is not the case that our effect reverses with higher eccentricity. It is just weaker. This is an important observation to make especially because a class of current models in which each spike contributes a mini-vector (e.g. van Opstal and colleagues) would predict the opposite: they would predict that a mini-vector from a more eccentric site is larger, meaning that the same number of injected spikes should lead to a larger amplitude change.

Concerning eccentricity analyses, we fully agree, and we have now directly followed your advice. We have repeated the analysis of Figure 4B (i.e. amplitude as a function of number of injected spikes) for different eccentricity ranges across our population. The results are shown in Figure 4 —figure supplement 3. These results support our choice of 4.5 deg eccentricity as the threshold in our main analyses, and they critically demonstrate that the slope of the relationship always remains positive even at the most eccentric sites. This is important because, once again, it demonstrates that injected spikes still “add” to individual saccade amplitudes; it’s just that with more eccentric injected spikes, the addition is smaller (i.e. less effective).

The analysis presented in Figure 4 shows a clear relationship between the number of spikes in SC and microsaccade amplitude. This is a very interesting finding. However, I see two potential problems here. One, that by sorting their data on 'number of spikes', they might inadvertently be also splitting their data by contrast (a result already shown in Figure 3). Second, they count the number of spikes from saccade onset to peak velocity as a criterion. The problem is that, because of the ballistic nature of saccades, this interval would linearly increase with saccade amplitude. Given the result presented in Figure 6A, I would not expect that this would compromise their main finding, but the authors should nonetheless correct for this by using a fixed time-window across all saccade amplitude conditions.

Thank you. These are valid points. We have now addressed them using multiple ways. First, we have replaced all similar analyses with ones that count spikes in the interval of 0-20 ms after microsaccade onset (regardless of microsaccade size) as opposed to 0 to peak velocity time. Second, we have added new experiments with different visual stimuli (spatial frequency) to show that the results were not specific to the stimulus type (and therefore not specific to stimulus contrast). Third, we extended the old Figure 6C, D to look at new data with much longer sustained fixation intervals. This has allowed us to explore spiking activity completely independently of visual bursts (and therefore independently of stimulus contrast). Please see the new Figure 7. In all cases, we counted spikes in a fixed interval (0-20 ms) rather than relative to peak velocity time, as you suggested. Our choice of 20 ms was that we wanted to ensure that our measurement interval remained early within even the smallest microsaccades, especially because Figure 6A demonstrates that this is when the readout of SC spiking activity seems to take place.

The statistical inferences from experiment 2 are mostly done one "saccadic displacement", calculated as the "radial position of the eyes from saccade start to 100 ms thereafter" (line 814). I might be missing something, but I don't understand why they use this criterion instead of, for example, the normalized distance of the saccade offset to the target. It seems to me that they might yield similar results, but since most saccades are finished by 60-80ms (Figure 7CD), the 100ms zone might be contaminated by corrective eye-movements.

As stated above to the editors and to the other reviewers, we have now decided to defer the microstimulation results to a later study. Our reasoning is that the new recording data that we have added (5 new figures and 9 new or modified figure supplements) are extensive and provide better insight for the current study than that provided by the brief microstimulation results as they were originally presented. A follow up study will hopefully delve into our microstimulation results/analyses in much more detail.

[Editors’ note: what follows is the authors’ response to the second round of review.]

Essential revisions:

Overall several concerns remain about the data analysis and interpretation of the findings of the authors, especially concerning the mechanistic interpretation of the findings. These mechanistic interpretations require additional analysis and further discussion or modification.

We have now added new analyses of the rostral neurons that directly address the most major comment of the reviewers (please see Figure 11 —figure supplement 1).

We have also modified the Introduction, Discussion, and other parts of the text with respect to our interpretations (e.g. please see lines 93-104, 407-417, 454-465, 595-598, 642-658, 695-699, 801-827).

We have also added several other minor analyses and figures recommended by the reviewers (copies of which are included in this document for easier parsing).

All details are provided in the responses below.

We are strongly convinced that our results and analyses represent an important contribution to the literature, and we sincerely hope that you will agree with us.

1. Rostral SC and intracollicular interactions: Concerns related to intracollicular interactions were salient in the initial round of reviews. These concerns still remain to some extent. It remains unclear whether the authors have convincingly determined that every additional spike contributes to the movement metrics. Much of the document is written like the microsaccade-related activity in the rostral SC is unaltered by a visual burst produced elsewhere in the SC. In the new figures added in this version, the focus is on proving that there exists a burst in the rostral SC while a visual burst occurs elsewhere in the SC. They do not test whether this burst is attenuated or statistically similar. The authors are aware of this possibility because they mention it several times in the response document, but the realization is scant in the manuscript.

We have now added a new figure directly comparing the rostral SC microsaccade bursts with and without the peripheral visual bursts, exactly as suggested by the reviewers. Please see the new Figure 11—figure supplement 1A. As can be seen, there was no statistically significant change in the motor bursts in the presence of the peripheral bursts. Note how panel B shows that there was still a behavioral effect of increased microsaccade size in the same experiment (despite the more eccentric stimuli than in most of our main figures from experiments 1 and 2). Please see lines 642-658.

If the change in microsaccade amplitude is entirely due to leakage of the visual activity, the activity in the rostral SC should be the same in the presence and absence of a visual burst. That is, the number of spikes in a window around the saccade duration should be unaltered. It is unclear whether this will be the case because, as the authors stated, the velocity profiles do not show double-peaks or inflection points to represent a separate addition of spikes from a different source. Two alternatives might be more likely and should be considered by the authors. One, the rostral SC neuron fires MORE spikes when the microsaccade is larger, which confounds the importance of the lawful relationship between additional the number of intrasaccadic visual spikes and microsaccade amplitude. Two, the rostral SC neuron fires FEWER spikes during the visual burst. Both alternatives suggest that intracollicular interactions may play a far more important role than additional intrasaccadic spikes from other parts of the SC.

As described above, the microsaccade bursts were not significantly altered.

We also strongly disagree with the statement that a “normal” velocity profile (no double-peaks) means that there cannot be multiple loci of activity on the SC map. The well-known global effect (Findlay, 1982), in which a saccade lands in between two simultaneously appearing targets, results in normal-looking saccades, and this effect is believed to be mediated by multiple loci of activity on the SC map (e.g. Glimcher and Sparks, 1993; Katnani et al., 2012; Vokoun et al., 2014). Even microsaccades show a version of the global effect, and the movements look normal (Hafed and Ignashchenkova, 2013). More importantly, with suprathreshold dual microstimulation of the SC at two different sites, the evoked saccades are largely normal (Katnani and Gandhi, 2011; Katnani et al., 2012). This is despite the fact that the microstimulation pulses are highly unnatural (uniform pulse trains) when compared to physiological bursts. Even when a physiological burst at one site (i.e. normal visually-guided saccade) is paired with electrical microstimulation at another site, the evoked saccades are normal (Katnani et al., 2012), but they are deviated in trajectory (from either burst location) exactly like our microsaccades are deviated in trajectory. Naturally, the saccades can be slightly off the main sequence relationship of peak velocity versus amplitude (as seen in Katnani et al., 2012), but our microsaccades also deviate from the main sequence relationship (Buonocore et al., 2017).

The example of Katnani et al., 2012 is particularly relevant here. In that study, the authors used exactly the idea of simultaneous activity on the SC map to test for predictions of SC read-out (they injected simultaneous activity to modify saccades). This is the same logic that we are invoking in our study.

Finally, please also keep in mind our results from Figure 7 and its supplement. Here, there was no peripheral burst at all. There were simply “spontaneous” spikes in the peripheral SC, and we related them to microsaccade amplitudes and still found a systematic relationship. As we stated previously, this is, in our view, perhaps the most important aspect of our study: there is no need for a visual burst at all to see our effects (Figure 7).

We have now further clarified the points above in the revised manuscript (e.g. please see lines 359-366, 695-699, 801-827).

The authors should analyze the activity of rostral SC neurons during microsaccades with and without a visual burst. If neural activity (either burst profiles or the number of spikes 15 ms before saccade onset to 15 ms before saccade end) is not altered, this would indicate that their lawful relationship is robust. In contrast, any alteration in rostral SC activity would support intracollicular interactions. At this point, one cannot exclude that the observed saccades is due to a newly organized population response and, crucially, one cannot differentiate between vector averaging and vector summation mechanisms; the authors favor the latter mechanism. Consequently, the lawful linear relationship might be merely an observation; it is no longer informative of any mechanism.

As stated above, we have now checked the rostral SC bursts with and without the peripheral bursts, exactly as suggested by the reviewers, and there was no significant alteration. Please see Figure 11—figure supplement 1A.

Please also note that the visual bursts (that are simultaneous with the motor bursts) do indeed create an altered “population response”. Specifically, read-out of the SC map by downstream structures cannot know whether a spike in one part of the map is “visual” or “motor” in label. Therefore, if there is a peripheral visual spike at the same time of SC read-out (which we show to be clearly the case; e.g. Figures 8-11), then it is indeed part of the entire population response being implemented for the saccade. This is exactly our message, and it is exactly the logic that was used in previous studies (e.g. dual microstimulation at two different sites; Katnani and Gandhi, 2011; Katnani et al., 2012). In a later comment below, we also clarify how the new ideas of Jagadisan and Gandhi, 2019 on the population temporal structure at read-out are also consistent with our interpretations.

Put another way, our results show the existence of two bursts at the time of “gate opening” to trigger a saccade (one rostral and one peripheral; e.g. Figures 8-11). Even if both bursts were to be slightly modified by each other due to intra-collicular lateral interactions (which we do not deny could happen; see Figures 8-11), it is inevitable that the visual bursts should have at least some impact at read-out. Our contribution is to show that this inevitable impact is not just to cause random variability in the saccades, but it is highly systematic and lawful (e.g. see Figure 6). Please also again remember the results of Figure 7, in which there was no peripheral visual burst at all. Here, the monkeys were simply fixating, and there was low-level discharge in the periphery. At the time of read-out at saccade triggering, whatever “spontaneous” activity that was present still had a measurable and systematic impact on the movements. This is, in our view, very striking.

Finally, we would like to clarify that we do not favor vector summation. In fact, we clearly stated that it is not entirely sufficient to understand SC read-out (please see lines 359-366, 775-793). We have now further clarified this point to avoid confusion (please see lines 801-827).

As for vector averaging, it also cannot fully account for our results. For example, at the behavioral level, even before considering any neural activity, it is clear that vector averaging should result in bigger microsaccades for the farther visual stimuli; this is not the case (e.g. Figure 3—figure supplement 1). Therefore, we do not wish to take sides between two models that both cannot fully account for our observations. Rather, our results will motivate many new interesting future research directions. For one, we are now completely revisiting the role of saccade-related bursts in the SC as a result of our observations in this manuscript, as well as others mentioned in the Discussion section. In our view, the present manuscript has opened our eyes to amazing possibilities on the mechanistic role of SC saccade bursts that we will hopefully publish soon.

So, we respectfully disagree that our results are “merely an observation”.

Even given intracollicular effects, it is possible that most of the results could be reconciled with a vector averaging scheme while also considering that averaging becomes less likely with spatial disparity. The authors should consider this possibility in their revision.

Vector averaging is definitely less likely with spatial disparity, as can be clearly seen from the behavioral data (e.g. Figure 3 —figure supplement 1).

In any case, we do agree that vector averaging is worthwhile to mention, and we did indeed discuss it in the previous versions of the manuscript. We have now done so more explicitly in the revised manuscript (e.g. please see lines 801-827).

However, as stated above, we do not wish to pick sides between vector summation and vector averaging, which both are not fully sufficient to account for our observations (or the observations of other studies, as we described in the manuscript). We also do not wish to try to add constraints to an existing model (e.g. by saying: vector averaging but with a distance constraint) just to keep the model name. We would much rather stick to our point that read-out at the time of “gate opening” for saccades is lawfully sensitive to spiking elsewhere on the SC map, regardless of the source of such spiking. As we discuss below, and in the revised manuscript (e.g. please see lines 363-366, 454-464, 809-827), we also think that the new hypotheses of Jagadisan and Gandhi, 2019 can be reconciled very well with this interpretation.

2. Eccentricity of stimulus. The dichotomy of the lawful relationship for stimulus presentation closer than or further than 4.5 deg is crucial to how the data should be interpreted. For eccentric stimulus locations (beyond 4.5 deg), there is clear evidence of bursts in both rostral and caudal SC. However, the visual spikes of caudal SC have minimal impact on microsaccade amplitude. This does not align with any reasonable model of saccade generation. If SC output, defined as number of active neurons or total number of output spikes, is relatively invariant across all saccade vectors and if visual spikes are the same as motor spikes, as the current paper asserts, then microsaccade amplitude must increase at a higher rate as the target is placed at increasingly eccentric locations. Not observing this effect implies that there may in fact be something different about "visual" and "motor" spikes, especially when the two bursts do not merge, such that visual spikes do not contribute to saccade amplitude. Concepts of motor-potent and motor-null subspaces borrowed from skeletomotor research or differences in the temporal properties of the two active populations offer viable alternatives (https://www.biorxiv.org/content/10.1101/132514v3.full). For parafoveal stimulus presentation (inside 4.5 deg), the active populations of neurons representing visual and motor bursts interact in an excitatory manner. They may effectively merge into one larger population with two local peaks, not unlike SC activity during averaging saccades of ultrashort latencies. Moreover, the combined population may take on the properties of the motor burst, which accounts for an increase in saccade amplitude with additional spike. The point is that the spatial distribution of the active population in the rostral SC is now altered, and one cannot convincingly conclude that the increase in microsaccade amplitude is merely due to more spikes added elsewhere. Given the arguments in the paragraph, it may be incorrect to state that "instantaneous readout of the SC map during movement generation, irrespective of activity source…explains a significant component of kinematic variability of motor outputs" (lines 40-42) and "the entire landscape of SC activity, not just at the movement burst site, can instantaneously contribute to individual saccade metrics" (lines 90-92).

To summarize, if visual spikes add to microsaccade amplitude "regardless of activity source"…"across the entire landscape of SC", then spikes beyond the 4.5 deg eccentricity must add more to saccade vector than spikes induced at more rostral sites. Lack of this effect might refute the authors' hypothesis.

Once again, to be absolutely clear, there was no lack of effect with the more eccentric spikes; it was merely weaker. Please see, for example, Figure 3 —figure supplement 1: the microsaccades were almost doubled in size at the time of the (far) peripheral visual bursts. Similarly, Figure 4 —figure supplements 2 and 3 show that the effect was still clearly present for far visual bursts.

To further support this idea, we have now also analyzed the behavioral data from the experiments of Figures 8-11, in which the visual bursts were more eccentric than 4.5 deg. Again, with these eccentric visual stimuli, the behavioral effect was still clearly present (i.e. the microsaccades got larger in size when they occurred at the same time as the peripheral visual bursts). Please see Figure 11—figure supplement 1B.

In addition, we have now replicated Figures 5 and 6 for the far neurons (as suggested by the reviewers in later comments below), and we have found that there was still a precise temporal window of impact of the peripheral spikes, just like with the nearer neurons (please see Figure 5 —figure supplement 2 and Figure 6 —figure supplement 2).

In our opinion, the fact that our results “do not align” with existing models of saccade generation is no reason to consider them non-important. Rather, we believe that it is exactly this difference that makes our results very intriguing.

Concerning the Jagadisan and Gandhi study, thank you for pointing it out. We do like this study, and we have now discussed it in more detail because it is indeed an important and relevant study. Please see, for example, lines 363-366, 454-464, 809-827 of the revised manuscript. In fact, this study can provide a plausible explanation for the diminishing peripheral burst effects that we see with increasing eccentricity. Specifically, if peripheral visual bursts are more variable for farther eccentric neurons, which is entirely plausible given the predominantly low spatial frequency tuning of the peripheral SC neurons (Chen et al., 2018), then the likelihood of disparity between their “population temporal alignment” and the “population temporal alignment” of the motor bursts would be larger than for nearer visual bursts. This would result in weaker behavioral effects. In other words, it could be less likely that the injected peripheral visual spikes are temporally aligned with the motor spikes at read-out, and this gives these visual spikes a weaker impact on the read-out according to the Jagadisan and Gandhi hypothesis.

This idea fits very well with our observations, and we have clarified this in the text (e.g. please see lines 809-827). In fact, the new analysis of Figure 6 with our far neurons (Figure 6 —figure supplement 2) shows a very similar quantitative influence of peri-saccadic spikes to that with the near neurons. This means that once the visual spikes are properly temporally aligned with the population motor burst, an impact on read-out is inevitable (and also quantitatively similar for near and far visual bursts; please see the y-axis values in Figure 6A and Figure 6 —figure supplement 2A).

Please also note that the Jagadisan and Gandhi hypothesis primarily asks the question of why saccades are triggered at all by a neural burst. Their hypothesis is, therefore, relatively ambivalent of the implementation of the saccade itself (i.e. the question of read-out that we focus on here). So, we view our results from Figure 6 and Figure 6 —figure supplement 2 as not only supporting the temporal alignment hypothesis of Jagadisan and Gandhi, 2019, but also generalizing it to the problem of read-out and not just triggering.

In our view, our interpretation of our results vis-à-vis Jagadisan and Gandhi is a more plausible mechanism than suggesting that near visual bursts simply get merged with microsaccade bursts into one large motor burst. This merging is inconsistent with all of our studies of the foveal and peri-foveal SC. For example, in Chen et al., 2015, 2019, we deliberately checked whether “motor bursts” for microsaccades “leak” into the peri-foveal visual burst representation (as might be predicted from a merged motor burst); please also see Figure 1 —figure supplement 1. Similarly, in Buonocore et al., 2017 (please see Figures 5-8 of that particular study), we observed the very same microsaccade amplitude effects as we described in the present study even when the microsaccades and visual flashes were virtually-colocalized (the flash was literally a transient alteration in fixation spot luminance, and the microsaccades were directed towards the fixation spot). All of this evidence makes sense in retrospect: if there was a merging of population activity in the central 5 deg of the SC, then small saccades during high acuity visual behavior would not be possible. This is the opposite of the remarkable behavioral precision of microsaccades (e.g. Ko et al., 2010). In fact, the majority of saccades during natural scene viewing are smaller than 5 deg; if the central 5 deg of the SC map were all “one hill” even with distractor onsets, then the high precision of scanning saccades would not be possible.

3. Choice of saccade analysis window. It is unclear what precisely motivates the choice of window (0-20 ms after saccade onset) to assess the impact of visual spikes. Given the brief duration of microsaccades and after accounting for transduction time, the movement is nearly over by the time these spikes can impact the amplitude. Wouldn't a rigorous choice be to use the 20 to 25 ms window before saccade onset? This could maximize the impact of the visual spikes, as Figure 6 suggests.

We have now further clarified why we chose this window for some of our analyses. Please see, for example, lines 263-265, 1097-1102 in the revised manuscript.

Briefly, we fully agree that our results would look even more compelling if we had included a slightly earlier time window (e.g. please see Figure 6). However, we wanted to demonstrate, at least in some figures, that even a very strict enforcement of “simultaneity” of visual spikes with movement bursts would still result in movement modification. Therefore, by way of example in Figure 4 (and related figures), we took a very strict criterion of “intra-saccadic” spikes; however, in subsequent figures (e.g. Figures 5 and 6), we additionally showed the full time course of effects. We have also now repeated Figures 5 and 6 for the far neurons, for completeness (please see Figure 5 —figure supplement 2 and Figure 6 —figure supplement 2).

Please also note that the particular choice of 0-20 ms was made in direct response to one of the reviewer comments from the previous manuscript draft. The reviewer had suggested to pick a fixed time window to avoid the possibility that our effects were dominated by only a subset of movements with certain durations (in the end, the same results were obtained with either approach).

In any case, we believe that Figures 5, 6 (and their new and old supplements) clearly indicate the full times of influence.

4. Regression analysis. Readers will have difficulty with the linear regression analyses of Figure 4B and related figures. Specific comments: (a) It is questionable whether the linear regression is convincing for data beyond 4.5 deg eccentricity given the distribution of the data. The accompanying figure is an image of Figure 4—figure supplement 3, with the dark blue points circled in red. The linear fit does reflect the trend in the plotted points. Thus, either the regression analysis is incorrect or the illustration is inappropriate for the analysis. (b) The number of data points for 0 intrasaccadic spikes is about 5 times greater than for 1 and 2 spikes. Does this have an impact on the regression analysis output? Should another strategy be used? (c) It appears that the data for 0 intrasaccadic spikes are largely obtained from a baseline period. It is possible that the neural state during baseline could be different than around the time visual processing occurs. Thus, a stricter criterion for selection of microsaccades with 0 intrasaccadic visual spikes might be warranted.

a. We checked, and this was a mistake in the visualization script. The figure is now corrected. We apologize for this mistake. The different eccentricity bins all follow linear trends. Please see Figure 4 —figure supplement 3.

b. Similar conclusions can be reached if we do not include 0 spikes at all in our regression analyses. We have now confirmed this, and also mentioned it in the manuscript (e.g. please see lines 297-298, 1117-1121).

c. Actually, the data for 0 spikes were indeed always for microsaccades occurring within the same time windows as the microsaccades analyzed with >0 spikes. This was also true in Figure 7 and its supplement. That is, whatever the time window that we analyzed for the presence of peripheral activity at the time of microsaccade triggering, we looked for microsaccades in the same time window but without accompanying spikes. Therefore, in Figure 4, the neural state with 0 spikes was similar to that with >0 spikes (i.e. microsaccades occurring shortly after stimulus onset). Similarly, in Figure 7, the neural state was always the presence of a sustained stimulus inside the RF, irrespective of whether there was an intra-movement spike or not. We have now clarified this point further in the revised manuscript (please see lines 281-284, 1077-1080).

https://doi.org/10.7554/eLife.64150.sa2

Article and author information

Author details

  1. Antimo Buonocore

    1. Werner Reichardt Centre for Integrative Neuroscience, Tübingen University, Tübingen, Germany
    2. Hertie Institute for Clinical Brain Research, Tübingen University, Tübingen, Germany
    Contribution
    Conceptualization, Formal analysis, Validation, Visualization, Writing - original draft, Writing - review and editing
    Contributed equally with
    Xiaoguang Tian
    For correspondence
    antimo.buonocore@cin.uni-tuebingen.de
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3917-510X
  2. Xiaoguang Tian

    1. Werner Reichardt Centre for Integrative Neuroscience, Tübingen University, Tübingen, Germany
    2. Hertie Institute for Clinical Brain Research, Tübingen University, Tübingen, Germany
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Visualization, Writing - review and editing
    Contributed equally with
    Antimo Buonocore
    Competing interests
    No competing interests declared
  3. Fatemeh Khademi

    1. Werner Reichardt Centre for Integrative Neuroscience, Tübingen University, Tübingen, Germany
    2. Hertie Institute for Clinical Brain Research, Tübingen University, Tübingen, Germany
    Contribution
    Formal analysis, Validation, Visualization, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1854-4343
  4. Ziad M Hafed

    1. Werner Reichardt Centre for Integrative Neuroscience, Tübingen University, Tübingen, Germany
    2. Hertie Institute for Clinical Brain Research, Tübingen University, Tübingen, Germany
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9968-119X

Funding

Deutsche Forschungsgemeinschaft (FOR1847 (project A6: HA6749/2-1))

  • Antimo Buonocore
  • Ziad M Hafed

Deutsche Forschungsgemeinschaft (DFG EXC307)

  • Antimo Buonocore
  • Xiaoguang Tian
  • Ziad M Hafed

Deutsche Forschungsgemeinschaft (SFB1233 "Robust Vision" (project TP11; project number 276693517))

  • Fatemeh Khademi
  • Ziad M Hafed

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We were funded by the Deutsche Forschungsgemeinschaft (DFG) through the Research Unit: FOR1847 (project A6: HA6749/2-1). We were also funded by the Werner Reichardt Centre for Integrative Neuroscience (CIN; DFG EXC307). ZMH and FK were additionally supported by the DFG Collaborative Research Centre: Robust Vision (SFB1233; TP 11; project number 276693517).

Ethics

Animal experimentation: The experiments were approved (licenses: CIN3/13; CIN4/19G) by ethics committees at the regional governmental offices of the city of Tuebingen and were in accordance with European Union guidelines on animal research and the associated implementations of these guidelines in German law.

Senior Editor

  1. Richard B Ivry, University of California, Berkeley, United States

Reviewing Editor

  1. Martin Vinck, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Germany

Reviewer

  1. Terrence R Stanford, Wake Forest School of Medicine, United States

Publication history

  1. Received: October 19, 2020
  2. Accepted: May 5, 2021
  3. Accepted Manuscript published: May 6, 2021 (version 1)
  4. Version of Record published: May 24, 2021 (version 2)

Copyright

© 2021, Buonocore et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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