The allocation of visual spatial attention is associated with both the enhancement of neuronal activity at the attended location (Desimone and Duncan, 1995; Krauzlis et al., 2013; Reynolds and Chelazzi, 2004) and the tendency to make microsaccades toward the covertly attended stimulus while fixating (Engbert and Kliegl, 2003; Hafed and Clark, 2002; Lowet et al., 2018). A recent study provided evidence that the generation of microsaccades could play a causal role in the attention-related modulation of neuronal activity (Lowet et al., 2018). In a spatial attention task in which subjects were rewarded for making a saccade to a cued stimulus after it changed color, cortical neurons displayed attention-related enhancement only following microsaccades directed toward the attended stimulus.

These findings provide interesting evidence about the links between covert attention, neuronal modulation, and fixational eye movements. However, they also raise potentially serious questions about how to interpret neuronal data obtained during the fixation tasks commonly used to study visual attention. Given that microsaccades are unavoidably generated during fixation, could the well-known modulation of neurons during covert visual attention tasks be an artifact of microsaccade generation? Is attention-related neuronal modulation obligately tied to the oculomotor intention to orient toward the attended stimulus, as suggested by the premotor theory of attention (Rizzolatti et al., 1987), and this dependence has been overlooked because sometimes it is a microsaccade toward the attended stimulus?

Here, we tested the relationship between microsaccade generation and attention-related neuronal modulation in the primate superior colliculus (SC), one of the most important brain structures for the control of visual spatial attention. Neurons in the SC provided the first evidence for neural correlates of visual attention (Goldberg and Wurtz, 1972) and are modulated during both overt and covert attention tasks (Herman and Krauzlis, 2017; Ignashchenkova et al., 2004). Most relevant to our questions, SC activity is causally related to behavioral performance in attention tasks: inactivation causes attention deficits specifically for the affected location and conversely, microstimulation can selectively facilitate attention performance (Cavanaugh and Wurtz, 2004; Herman et al., 2018; Lovejoy and Krauzlis, 2010; Müller et al., 2005). Thus, if microsaccades are a necessary part of allocating attention, their causal role should be evident in the activity of SC neurons.

To investigate the possible role of microsaccades in attention-related modulation in the SC, we collected neuronal activity and eye movement data in two monkeys (Macaca mulatta) during a covert spatial attention task that has been used in our previous studies examining the neuronal mechanisms of attention (Herman et al., 2018; Herman and Krauzlis, 2017). SC extracellular activity was recorded with linear electrode arrays and eye position was measured with an infrared eye-tracker.

In the covert spatial attention task (Figure 1a), head-fixed monkeys were required to release a joystick in response to a change in color saturation for the stimulus patch at the cued location and to withhold their response if the change occurred at an opposing foil location. Monkeys were required to maintain central fixation throughout the entire trial such that any allocation of attention to the cued stimulus patch was only done covertly. The behavioral performance was very consistent across sessions (Figure 1b). Monkey subjects had hit rates of ~80% (mean hit rates: 82% in monkey 1% and 84% in monkey 2), as expected since the size of the change in color saturation was set near the monkeys’ detection thresholds as described previously (Herman and Krauzlis, 2017), and the monkeys rarely responded to the foil changes (mean false-alarm rates: 1% in monkey 1 and 9% in monkey 2), indicating that they followed the attention cue and attended to the correct stimulus location.

Figure 1

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While monkeys performed the task, many SC neurons displayed attention-related modulation. The time course of SC population firing rate with respect to the onset of the color patches onset is shown in Figure 1c for both monkeys (34 units in monkey 1 and 34 units in monkey 2). SC neurons displayed a phasic response shortly after the onset of the color patches, and during the delay period (200–1000 ms) that followed, neuronal activity became steadily higher when the cued stimulus was inside the response field (RF) of the SC neurons compared to when it was outside the RF. This pattern recapitulates the well-known pattern of attention-related modulation in the SC and elsewhere (Desimone and Duncan, 1995; Herman et al., 2018; Herman and Krauzlis, 2017; Krauzlis et al., 2013; Reynolds and Chelazzi, 2004).

To confirm that SC attention-related modulation was indeed linked to performance in our attention task, we compared the modulation on correctly and incorrectly performed trials (Figure 1d). We measured the cue-related difference in firing rate in each neuron (i.e., cue-in-RF minus cue-out-of-RF) during the delay period (gray shaded area in Figure 1c) separately for hit (correct detections) and miss trials. We found that SC neurons displayed significantly higher average attention-related modulation in hit trials compared to miss trials (monkey 1: p=0.0004, monkey 2: p=0.00099, Wilcoxon signed-rank test), verifying the link between SC neuronal activity and performance in this attention task (Herman et al., 2018).

Simultaneous to SC neuronal recording, we measured the subjects’ fixational eye movements. Traces of horizontal and vertical eye position from one example trial are shown in Figure 2a. Even though monkeys maintained fixation throughout the trial, they generated a series of fixational microsaccades consisting of abrupt and miniscule (typically smaller than 1°) deflections in eye position, as expected from previous findings (Hafed, 2011; Martinez-Conde et al., 2013; Rucci and Poletti, 2015).

Figure 2

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To summarize when microsaccades occurred and where they were directed during the covert attention task, we calculated the probability of microsaccades on the same time axis as the SC neuronal firing rate (Figure 2b). To identify how the direction of microsaccades was influenced by the location of the spatial cue, microsaccades were grouped based on whether they were directed toward or away from the cued hemifield. Overall, the probability of microsaccades both toward and away from the cued hemifield decreased sharply after patch onset and then rebounded during the following delay period. During the delay period (Figure 2b, gray shaded area), the probability of microsaccades toward and away from the cued hemifield were similar, with slightly higher probability of away microsaccades in monkey 2. The polar plots in Figure 2b provide a more detailed picture of the directional distributions of microsaccades relative to the cued location during the delay period. Microsaccades in monkey 1 showed two predominant directions directly toward and away from the cued location, whereas microsaccades in monkey 2 showed a weaker cue-related bias and idiosyncratic vertical tendencies unrelated to the cue. Thus, during sustained attention in the delay period, monkey subjects generated frequent microsaccades but their overall direction was not systematically biased toward the cued location.

Although microsaccades during the delay period were not biased toward the cue, microsaccade direction was associated with some differences in task performance (Figure 2c). These effects were identified by subdividing the monkeys’ hit rates (Figure 2c, first row) and reaction times (Figure 2c, second row) into three sets based on the microsaccades in a 100-ms window centered on the change onset: no microsaccades, microsaccades toward the cued location, and microsaccades away from the cued location. We observed only minor differences in hit rate but consistent effects on reaction times. Both monkeys had slower reaction times when microsaccades were directed away from the cued location compared to when there were no microsaccades (monkey 1: p=0.0002, monkey 2: p=0.002, Wilcoxon rank-sum test) or microsaccades toward the cued location (monkey 1: p=0.002, monkey 2: p=0.016, Wilcoxon rank-sum test).

Effects of microsaccades on the time course of SC attention-related modulation

We next assessed how the occurrence of microsaccades was related to the time course of SC attention-related modulation (Figure 3). Each panel in Figure 3a depicts the population average normalized SC firing rate from subsets of trials in which there were either no microsaccades (top row), microsaccades toward the cued location (middle row), or microsaccades away from the cued location (bottom row), within a particular 100-ms epoch indicated by the gray shaded area. The eye speed trace in each panel serves to verify the inclusion or exclusion of microsaccades within each epoch. In total, we used five different epochs during the delay period, corresponding to the columns in Figure 3a. To summarize the neuronal data, we measured the average normalized firing rates in 100-ms windows (dashed boxes) immediately after each microsaccade epoch and plotted these averages as a function of epoch in Figure 3b. This choice of measurement window was motivated by the recent finding that cortical attention-related modulation emerged ~100 ms after microsaccade onset (Lowet et al., 2018), but we found similar results with other windows (Figure 3—figure supplement 1).

Figure 3 with 1 supplement see all

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In trials with no microsaccades in each epoch, the pattern of attention-related neuronal modulation (Figure 3a, top row) was qualitatively similar to the one observed when including all trials (Figure 1c). We found steadily higher population average neuronal activity during ‘cue-in-RF’ condition compared to ‘cue-out-of-RF condition’ and this attention-related modulation was significant from the third epoch onwards (Figure 3b, top row, ANOVA, post hoc comparisons, p<0.05). Thus, the exclusion of trials with microsaccades did not prevent the emergence of attention-related modulation over time during the delay period.

In trials with microsaccades in each epoch, SC neuronal activity was suppressed. Distinct dips in the firing rate traces were evident toward the end of each epoch, regardless of whether the microsaccades were directed toward the cue (Figure 3a, middle row), or away from the cue (Figure 3a, bottom row).

In addition to this suppression of firing rate that occurred regardless of microsaccade direction, we also found an attention-related modulation that did vary with the direction of the microsaccades. In trials with microsaccades toward the cued location (Figure 3a, middle row), the difference between neuronal activity for ‘cue-in-RF’ versus ‘cue-out-of-RF’ conditions was significant in all the epochs (Figure 3b, middle row, ANOVA, post hoc comparisons, all p<0.05). In contrast, for trials with microsaccades away from the cued location (Figure 3a, bottom row), the attention-related modulation was reduced and only emerged as significant in the last time epoch (Figure 3b, bottom row, ANOVA, post hoc comparison, p<0.05).

Thus, the presence of SC attention-related modulation did not require the generation of microsaccades. Instead, microsaccades were associated with the suppression of firing rates, consistent with saccadic suppression (Hafed and Krauzlis, 2010). Nonetheless, there was a systematic relationship between the amplitude of the attention-related modulation and the direction of the microsaccades—we found more consistent attention-related modulation when microsaccades were directed toward the cue but not when they were directed away, suggesting that there might be a causal relationship between the two.

Peri-microsaccade attention-related modulation

We next investigated the timing of the attention-related modulation relative to microsaccades by aligning SC neuronal activity to the onset of individual microsaccades directed toward (Figure 4a, middle row) or away from the cued location (Figure 4a, bottom row). For comparison, we also generated control data sets that contained no microsaccades during 400-ms windows chosen to match the timing of our microsaccade-aligned data (Figure 4a, top row). In these ‘no microsaccades’ data, we still observed substantial attention-related modulation, again confirming that microsaccades were not necessary for SC attention-related modulation.

Figure 4 with 3 supplements see all

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For the data aligned on microsaccades, neuronal activity was suppressed immediately after microsaccade onset regardless of microsaccade direction or cue conditions (Figure 4a), consistent with the results in Figure 3. In contrast, the amplitude of the attention-related modulation did vary with microsaccade direction—the modulation was present only when the microsaccade was directed toward rather than away from the cued location. These results were robust with respect to the particular microsaccade inclusion window used for the analysis (Figure 4—figure supplement 1) and also to the choice of threshold used to detect microsaccades (Figure 4—figure supplement 2).

The difference in attention-related modulation between microsaccade conditions (toward vs. away from cue) was not triggered by the microsaccade but was evident before microsaccade onset. To quantify changes in firing rates and attention-related modulation around the time of microsaccades, we calculated the average normalized firing rate before and after microsaccade onset (Figure 4b). The dashed boxes in Figure 4a depict the ‘before’ and ‘after’ windows we used for the calculation. For the ‘no microsaccades’ and ‘toward cue’ data sets, we found significant cue-related modulation (firing rate with cue-in-RF was higher than with cue-out-of-RF) in both the ‘before’ and ‘after’ windows (ANOVA, post hoc comparisons, all p<0.05). In contrast, for the ‘away from cue’ data sets, we did not find significant attention-related modulation in either the ‘before’ or ‘after’ window (ANOVA, post hoc comparisons, all p>0.05). We also found a significant suppression of neuronal activity in the ‘after’ window compared to ‘before,’ regardless of cue condition, for both microsaccade directions (ANOVA, pos hoc comparisons, all p<0.05), but not for the no-microsaccade condition (p>0.05).

As there were both attention-related modulation and response suppression around the occurrence of microsaccades, we investigated how these two processes interacted with each other. First, we tested whether the attention-related modulation present before microsaccades was changed when the overall neuronal response was suppressed after microsaccades (Figure 4c). To compare the attention-related modulation, we measured the difference in population average normalized firing rates between cue-in-RF and cue-out-of-RF conditions during both ‘before’ and ‘after’ windows. We did not observe any significant differences in attention-related modulation between ‘before’ and ‘after’ windows for any of the three microsaccade-related data sets (ANOVA, post hoc comparisons, all p>0.05). Thus, the amplitude of the attention-related modulation was largely preserved through the occurrence of the microsaccade.

Next, we investigated whether the microsaccade-related neuronal suppression observed in Figure 4b was affected by the cueing condition (Figure 4d). We calculated the difference in normalized firing rates between ‘after’ and ‘before’ windows for both ‘cue-in-RF’ and ‘cue-out-of-RF’ conditions. We did not find any significant differences in the amplitude of the suppression effect across cueing conditions for any of the three microsaccade-related conditions (ANOVA, post hoc comparisons, all p>0.05). This indicates that the amplitude of the microsaccade-related suppression was not influenced by the cue-related modulation. Finally, we confirmed that our microsaccade-related findings could not be explained by motor effects related to the generation of microsaccades or variations in eye position (Figure 4—figure supplement 3).

In summary, aligning firing rates on microsaccade onset clarifies the causal relationship between attention-related modulation and microsaccades. SC neurons display large attention-related modulation during epochs that contain no microsaccades. When microsaccades do occur, the attention-related modulation is present before microsaccade onset and has an amplitude at least as large as that found after microsaccades. Thus, microsaccades do not appear to cause the attention-related modulation but may be influenced by a shared process.

Our findings demonstrate that microsaccades are not necessary for attention-related modulation in the midbrain SC. First, attention-related modulation emerged over the same time course during the attention task, regardless of the occurrence of microsaccades (Figure 3). Second, attention-related modulation was still observed when microsaccades were completely absent over long time periods (Figure 4). Third, when microsaccades did occur, the neuronal attention-related modulation was already present prior to microsaccade onset and the occurrence of the microsaccade—and the accompanying saccade-related suppression—did not flip the pre-existing trend of attention-related modulation (Figure 4). Thus, the attention-related modulation of SC neurons was readily dissociated from the occurrence of microsaccades during the sustained allocation of visual spatial attention.

Why are our findings different from those in a recent study showing that microsaccades might play a causal role in the neuronal attention-related modulation (Lowet et al., 2018)? There are several factors that could have contributed to this difference. The first factor is the time window used for microsaccade analysis. The previous study focused on microsaccades immediately after cue onset. Thus, the cue-induced change in attention state might be expected to trigger changes in both fixational eye movements and neuronal modulation. In our study, the time window we focused on, the ‘delay period,’ is hundreds of milliseconds after the cue, and is the time window used in most neurophysiological studies of attention (Bogadhi et al., 2021; McAdams and Maunsell, 1999). The second factor is how the spatial cues were presented. In our paradigm, the cue ring briefly appeared in the periphery and then disappeared. In contrast, the previous paradigm used a cue presented near fixation that persisted throughout the trial. Our cue therefore provided less of an impetus to generate small saccades directed toward the cue, compared to the case when the cue is continuously near the center of gaze. The third factor relates to response modality. In our task, monkeys were trained to release a joystick to report their detection of stimulus events, whereas in Lowet et al., monkeys made a saccade to the attended stimulus. Because human and monkey subjects tend to make microsaccades in the same direction as their upcoming saccadic choices (Yu et al., 2016), the directions of microsaccades in the previous attention task might be related to the motor preparation of the upcoming saccade choice as well as related to the allocation of attention. By using a joystick release, we minimized these lateralized effects related to saccade preparation. These same three factors also help explain why the distribution of microsaccade directions in our study was not strongly biased toward the cue location as found in some previous studies (Engbert and Kliegl, 2003; Hafed and Clark, 2002; Laubrock et al., 2010; Pastukhov and Braun, 2010).

How are our findings related to the previous studies showing that attention task performance covaries with microsaccades? First, the main finding from our study is that the attention-related modulation of SC neurons does not require the occurrence of microsaccades. This aspect of our results is entirely consistent with recent work showing that attentional effects are present even in the absence of microsaccades (Liu et al., 2021; Poletti et al., 2017). Second, we did find that the amplitude of attention-related modulation varied with microsaccade direction when they did occur. Crucially these differences in modulation across microsaccade conditions preceded microsaccade onset. Moreover, the attention-related modulation that preceded microsaccades toward the cued location was commensurate to that found in the no-microsaccade condition. This aspect of our results supports viewing microsaccades as a ‘marker’ for the state of attention where microsaccade direction may be correlated with the spatial allocation of attention, but is not causally necessary (Hafed, 2013). Since some of the same brain structures that control spatial attention are also involved in generating microsaccades (Hafed et al., 2009; Lovejoy and Krauzlis, 2010), the occurrence and direction of microsaccades would be expected to covary with the allocation of attention as measured in behavioral tasks (Engbert and Kliegl, 2003; Hafed and Clark, 2002; Yuval-Greenberg et al., 2014).

Finally, we acknowledge that tasks like those used in this study are somewhat unnatural. Outside these types of test situations, it would be rare for monkeys to selectively attend a stimulus in the periphery for extended periods of time while maintaining central fixation. Would similar results hold under more natural conditions when subjects look directly at the peripheral stimulus? Of course, without imposing central fixation, the period of peripheral attention would be much shorter and include few if any microsaccades, but we would expect to see similar attention-related neuronal modulation at the peripheral site, consistent with the effects of pre-saccadic modulation of attention (Li et al., 2021). Once the attended stimulus is foveated, similar attention-related effects might take place for neurons representing the central visual field, based on recent behavioral studies demonstrating that attention can be selectively distributed even within the fovea (Poletti et al., 2017). Considering the now substantial evidence that the foveal portion of the SC map is activated when the behaviorally relevant location is at the center of the visual field (e.g., during parafoveal smooth pursuit as in Hafed and Krauzlis, 2008), we expect that SC neurons with foveal RFs would display similar attention-related modulation as we found here. However, further studies are needed to understand the neuronal mechanisms that control how attention is allocated in and around the fovea.

Data for all the figures are available via Dryad http://doi.org/10.5061/dryad.83bk3j9s9.

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Author details

1. Gongchen Yu

   Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Software, Visualization, Writing - original draft, Writing – review and editing

   For correspondence

   yugongchen1990@gmail.com

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9216-8174

2. James P Herman

   Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Software, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6916-2807

3. Leor N Katz

   Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, United States

   Contribution

   Data curation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2742-6533

4. Richard J Krauzlis

   Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Software, Writing – review and editing

   For correspondence

   richard.krauzlis@nih.gov

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-1826-0447

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