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

Download asset Open asset

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

Download 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

Download asset Open asset

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

Download 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.

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

Download asset Open asset

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

Download 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.

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 1–3).

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

Download asset Open asset

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

Download 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.

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

Download asset Open asset

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

Download 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

Download asset Open asset

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

Download 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).

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 2–6 were contingent on ‘bursting’ activity in the SC, or whether any spiking could still matter).

Figure 7 with 1 supplement see all

Download asset Open asset

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

Download 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 5–7) in which any movement-unrelated spikes in sites other than the saccade goal representation can induce a systematic variation in the motor program.

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 4–7). 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.

Figure 8

Download asset Open asset

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 2–6), 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.

Figure 9

Download asset Open asset

Figure 9—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig9-data1-v2.xlsx

Download elife-64150-fig9-data1-v2.xlsx

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.

Figure 10

Download asset Open asset

Figure 10—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig10-data1-v2.xlsx

Download elife-64150-fig10-data1-v2.xlsx

Across the population of rostral and caudal SC neurons recorded during this additional experiment, we observed consistent results with the above examples in Figures 8–10. 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).

Figure 11

Download asset Open asset

Figure 11—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig11-data1-v2.xlsx

Download elife-64150-fig11-data1-v2.xlsx

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.

Figure 12

Download asset Open asset

Figure 12—source data 1

Excel table with the source data for this figure.

https://cdn.elifesciences.org/articles/64150/elife-64150-fig12-data1-v2.xlsx

Download elife-64150-fig12-data1-v2.xlsx

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 2–7 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 8–12 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.

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 2–6. 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.

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 4–7). 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 3–6).

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).

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 8–12), 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 9–12). On the contrary, when microsaccades were triggered simultaneously with peripheral visual bursts, the rostral SC neurons actually exhibited activity bursts (Figures 9–12). 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.

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.

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.

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.

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.

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.

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).

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

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).

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.

© 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.