|Home | About | Journals | Submit | Contact Us | Français|
We make fast, ballistic eye movements called saccades more often than our heart beats. Even though every saccade causes a large movement of the image of the environment on our retina, we never perceive this motion. This aspect of perceptual stability is often referred to as saccadic suppression: a reduction of visual sensitivity around the time of saccades. Here, we investigated the neural basis of this perceptual phenomenon with extracellular recordings from awake, behaving monkeys in the middle temporal (MT), medial superior temporal (MST), ventral intraparietal (VIP), and lateral intraparietal (LIP) areas. We found that in each of these areas the neural response to a visual stimulus changes around an eye movement. The perisaccadic response changes are qualitatively different in each of these areas, suggesting that they do not arise from a change in a common input area. Importantly, our data show that the suppression in the dorsal stream starts well before the eye movement. This clearly shows that the suppression is not just a consequence of the changes in visual input during the eye movement, but rather must involve a process that actively modulates neural activity just before a saccade.
While reading this article, your eyes jump from word to word. Each jump causes the retinal image to move. Normally, however, you are blissfully unaware of such motion: this is the behavioral phenomenon called saccadic suppression. Saccadic suppression is important to allow the perception of a stable environment (Helmholtz, 1867;Holt, 1903;Bridgeman et al., 1993;Ilg and Hoffmann, 1993). Psychophysical studies have demonstrated that not all visual stimuli are suppressed; stimuli processed by the functional subsystem that serves motion and space encoding are strongly suppressed while stimuli processed by the object and color vision subsystem are largely unimpacted (Ross et al., 1996). This behavioral dichotomy matches the two information processing streams in the primate visual system (Ungerleider and Mishkin, 1982).
Results from behavioral studies (Holt, 1903;Burr et al., 1994) and transcranial magnetic stimulation (Thilo et al., 2004) have been used to argue that the neural mechanism of saccadic suppression is a reduction of the input to the visual cortex at the level of the LGN. Physiological studies confirm that visually driven activity in the LGN is affected by eye movements. However, LGN neurons mainly show post-saccadic increases in response and these effects are quite similar for the magno- and parvocellular subdivisions (Fischer et al., 1996;Reppas et al., 2002). It seems therefore that the perisaccadic changes in LGN response properties by themselves are not sufficient to explain the behavioral phenomenon of saccadic suppression and rather might be the consequence of top-down signaling from cortex to the thalamus. We therefore continued the search for neural correlates of saccadic suppression in macaque areas MT, MST, VIP, and LIP. We reasoned that, if saccadic suppression originates at the level of the LGN, and cortical areas merely inherit this suppression, one would expect a relatively uniform effect of eye movements on the activity of neurons in all four areas. Our data do not support this view; instead, a unique pattern of saccadic suppression was found in each of these dorsal stream areas.
Not only is the locus of the neural basis of saccadic suppression uncertain, the mechanism of saccadic suppression is also poorly understood. Some have claimed that an active process reduces visibility even before the eyes start to move (Burr et al., 1994;Ross et al., 2001;Ibbotson et al., 2008), others have concluded that the reduced visibility of pre-saccadic stimuli is caused mainly by backward masking of the visual scene that is present after the eye movement (Campbell and Wurtz, 1978;Ibbotson and Cloherty, 2009).
To shed light on this issue, we recorded the complete time course of neural excitability around saccadic eye movements. The time course we found in motion sensitive areas MT, MST, and VIP was quite similar to what has been found psychophysically; neural suppression started for stimuli presented well before the saccade, reached a maximum at saccade onset, and, after a brief enhancement of neural responsiveness, it returned to normal after the saccade. Neural suppression for stimuli that are presented to stationary eyes - just before they start to move – shows that active processes play a role in saccadic suppression. These results have previously been published in abstract form (Bremmer et al., 2002) and a subset of the data has been used to construct a Bayesian model to decode position information from dorsal stream neurons (Krekelberg et al., 2003).
The procedures for monkey training and electrophysiological recordings have been described in detail in previous papers (Bremmer et al., 1997a;Bremmer et al., 1997b;Schlack et al., 2005). In brief, monkeys were prepared for recordings under general anesthesia and under sterile surgical conditions. Each animal was implanted with a device for holding the head. A recording chamber for microelectrode penetrations through the intact dura was placed in a sagittal plane with an angle of 60° with respect to the vertical for recordings in areas MT and MST and in a frontal plane at an angle of 45° with respect to the vertical for recordings in areas LIP and VIP. Additionally, scleral search coils were implanted to monitor eye position. During the experiment the animal sat in a primate chair with the head restrained, facing a translucent screen. All procedures were in accordance with published guidelines on the use of animals in research (European Communities Council Directive 86/609/EEC, National Institute of Health Guide for the Care and Use of Laboratory Animals).
Visual stimuli and saccade targets were back-projected onto a screen subtending 60° by 60° of the visual field. The animal received liquid rewards for correctly performing the saccade task. Saccades always had the same metric: along the horizontal meridian from 10° left to 10° right (in the second animal: from 10° right to 10° left). A brief visual stimulus (width: 10°, height: 60°, duration: 8 ms) was presented at one of six neighboring but non-overlapping locations (Figure 1). By stimulating the whole visual field across different trials we could be sure that one of our stimuli always hit the most sensitive region within the RF. This avoids issues with shifting receptive fields that are known to occur in these areas (Duhamel et al., 1992;Duhamel et al., 1997;Nakamura and Colby, 2002). The flashed stimuli could appear either long before (pre-stimulus), around (peri-stimulus), or long after (post-stimulus) a saccade. Pre-stimuli occurred on average 550 ms before a saccade. Peri-stimulus occurrence ranged (in pseudo-randomized order) from 200 ms before saccade onset to 200 ms after saccade onset. Post-stimuli occurred on average 550 ms after a saccade.
In separate trials, the animal was instructed to make the same saccades, following the same visual cues, without the presentation of the vertical bar. Given the absence of strong visual stimulation, we refer to these trials as the saccade-only condition.
For the single-cell example in Figure 2 we aligned spike times to stimulus onset and sorted the trials by the time from stimulus onset to saccade onset. Spike density functions were generated by convolving the spike trains per trial with a Gaussian filter (sigma = 5ms), and averaging across trials.
For the coarse-grained population analysis of Figure 3, we determined the response of each cell in a predefined response window (60ms – 120ms after stimulus onset). The average response in this window was considered the cell’s response. The average of all cells’ responses was then determined separately for all stimuli presented more than 300ms before (pre), or more than 300ms after a saccade (post), and for all stimuli presented from 100ms before until 100ms after saccade onset (peri). For ease of comparison across cells and areas, we expressed each cell’s average response in the peri and post periods as a percentage of the average response of that very cell in the pre-period.
For Figure 4 we calculated the time course of the average population discharge. Had we simply averaged the neural responses, then the variability in neural latencies (across cells and around eye movements) would have resulted in a smeared-out population response. While this calculation would provide an accurate reflection of the activity in the brain, its ability to shed light on typical changes in response around saccades would be limited. Hence, for the computation of the population average, we corrected each cell for its response latency. To estimate a cell’s response latency, we first determined the mean and standard deviation of the firing rate in the 200ms before stimulus onset. Then, we determined the average response after stimulus onset in time bins of 20ms. The response latency was defined as the first bin in which the average response exceeded the baseline firing by at least 3 standard deviations. The smallest value across all stimulus positions was taken as the cell’s latency. This response latency was determined separately in the pre-, peri- and post-saccadic windows.
After correcting for individual cells’ response latency, we simply averaged the response across all cells in an area. Again, this was done separately for the pre-, peri-, and post-saccadic window. The average stimulus presentation time in the pre-window was 550ms before saccade onset, in the post-window 550ms after saccade onset, for the peri-window we chose the window of maximum suppression; the first 75ms after saccade onset: [0ms,75ms). Confidence intervals (95%) for the average of the population time course were set to 1.96 times the standard error in the mean of the population time course.
To calculate the population excitability of Figure 5, we aligned for each of the four areas all responses to saccade onset and averaged across all trials and neurons. We then cross-correlated the behavioral sensitivity data as reported by Diamond and colleagues (Diamond et al., 2000) with the neural activity profiles. This allowed us to determine the best match between behavioral and neural data. Neural response functions as obtained from motion sensitive areas MT, MST, and VIP were then corrected for the respective latencies and superimposed onto the behavioral data. Note that for this analysis we ignored when exactly a stimulus was presented. This provides an estimate of the average population activity at any point before, during and after an eye movement. For each temporal epoch this population activity estimate is based on the response to at least 750 flashed stimuli, hence even if the number of flashes in each time window is not constant, our estimate of the average neural response will be precise.
For the cell-by-cell population analysis (Figure 6) we first grouped stimulus presentation times into three windows (−1000ms, −400ms], (−75ms, 0ms], and (0ms, 75ms], where the times were defined with respect to saccade onset. Accordingly, the first interval defines a presaccadic time window, while the second and third intervals define two different perisaccadic time windows. For each cell and each window, we then determined the maximum response for any of the flashed stimuli. With these values at hand we calculated a suppression index SI (for further details: see Results).
For a more fine-grained view of the time course, we determined the average population response separately for stimuli presented in 25ms time windows around saccade onset (from 125ms before until 175ms after saccade onset). For each of these stimulus presentation windows, we determined the average activity from 280ms before response onset until 300ms after response onset. This results in a response matrix that is shown in Figure 7.
To quantify perisaccadic suppression, we compared the perisaccadic population response matrix of Figure 7 with the population responses evoked long before a saccade. We defined a response modulation index as the difference between the perisaccadic response and the presaccadic response, divided by the standard error of the presaccadic response. To estimate statistical significance of this modulation index we calculated how much stimuli presented in the (−500ms, −300ms] window were suppressed compared to the stimuli presented in the (−700ms, −500ms] window. Saccades should have no influence in this pre-saccadic window, hence the suppression thus measured must be spurious and provides a null distribution against which to test the suppression in the perisaccadic window. We considered significant only those perisaccadic modulation (suppression) indices for which we could reject the null hypothesis that they could have been drawn from the presaccadic modulation index distribution. The threshold for significance was set to p<0.01 and to correct for multiple comparisons we selected only those regions of significance that consisted of a contiguous region of four or more significant time windows. Figure 8 shows the significant modulation indices: suppression (red) and enhancement (green). Note that due to the correction for multiple comparisons some time windows which appear very dark in Figure 7 nevertheless do not appear in the conservatively thresholded Figure 8.
We distinguished among three subpopulations of LIP neurons by analyzing their response in the saccade-only condition. We first determined the average firing rate in a 200ms time window centered on saccade onset (sacc), and compared this to the firing rate in a 100ms time window long before the saccade, during steady fixation (fix). We then calculated a saccade modulation index as (sacc−fix)/( sacc+fix)*100%. LIP neurons with a saccade modulation index above 10% were labeled as LIP+; the response-field of these neurons must have matched the direction of the saccade (N=82). LIP neurons with a saccade modulation less than −10% were classified as LIP−; the response field of these neurons was presumably in the direction opposite to the saccade (N=45). Neurons with a saccade modulation index between −10% and +10% were classified as LIP-0. By definition, these had only minor purely saccade-driven modulations; they were mainly driven by visual input (N=27).
We recorded extracellularly from neurons in the middle temporal area (MT, n = 40), the medial superior temporal area (MST, n = 104), the ventral intraparietal area (VIP, n = 180) and the lateral intraparietal area (LIP, n = 154) in four hemispheres of two macaque monkeys. In each trial, the monkey made a 20 degree horizontal saccade, and a large vertical bar was flashed at one of six screen positions. These visual stimuli were presented in pseudo-randomized order for 8ms long before (pre), long after (post), or in the temporal vicinity of the saccade (peri) (Figure 1).
In Figure 2 we illustrate the peri-saccadic changes in neural responses with a recording from a single MT neuron. Flashes presented just to the right of the fovea either long before (panel A) or long after (panel B) a saccade lead to a robust response. The spike density (panel E) reaches peaks of about 60 spikes per second and is comparable for stimuli flashed in the pre (red curve) and post-saccadic (blue curve) window. Panel C shows the response of the same neuron to stimuli flashed in its pre-saccadic receptive field around the time of saccade onset. The trials in the raster plot are ordered such that trials in which the stimulus was presented long before the saccade are at the top, and trials in which the stimulus was presented long after the saccade are at the bottom. Saccade onset time is indicated by the red triangles.
Reading the raster from top to bottom, we see a robust response for flashes presented 100 or more milliseconds before the saccade. Flashes presented between 75 and 0 ms before the saccade, however, evoke fewer spikes. The spike density for stimuli presented in this peri-saccadic window is shown as the solid green curve in panel E. The peak response does not rise above 35Hz; a reduction of nearly 50% compared to the response during fixation (red/blue curves). Because the eye has not moved yet when the flash is presented, this suppression of the response must involve an active process of suppression and cannot be caused by changes in the retinal input due to the motion of the eye.
Continuing stepping through the trials in panel C, we reach the trials in which flashes are presented after the eye has started to move. The average response to these flashes (green dashed curve in panel E) is also much less than those presented during fixation. This reduction can be caused by active processes, but it almost certainly also involves the (passive) reduction in firing expected from the fact that the receptive field, which is presumed to be yoked to the eye, moves away from the position where the stimulus is flashed.
Panel D shows the response to flashes presented in the future field, i.e. the location on the screen where the receptive field will be after the saccade. For flashes presented before the saccade, responses at this location are small and delayed (solid black curve in panel E). This likely includes a passive effect; when these flashes are presented the receptive field does not yet encompass their location. It also could reflect a memory trace as described e.g. in area LIP (Duhamel et al., 1992). But, the raster plot shows that even for flashes presented more than 50ms after saccade onset, when the eye has reached its new position and the flashes are again presented within the receptive field, the response is also reduced compared to fixation (dashed black curve in panel E).
The single cell example of Figure 2 demonstrates that it is critical to distinguish between the time of a response relative to the stimulus, and the time of the stimulus relative to the saccade. Moreover, it illustrates how active sources of saccadic suppression can be isolated by investigating responses evoked by flashes presented just before or just after an eye movement. We believe, however, that passive sources of saccadic suppression may also play a role in perisaccadic perception. To illustrate this, consider an ideal observer with access to a perfect eye position signal. This observer, when faced with a detection task, always knows which neurons to consult about the presence of a visual stimulus on the screen. Therefore, this observer does not suffer from passive mechanisms of suppression, because as soon as the eye starts to move, the observer will select to read out a different neuron whose receptive field is now in the appropriate position. In contrast, any mechanism for detection that does not have access to a perfect eye position signal would suffer from passive suppression. For instance, if the eye position signal were delayed, the detection mechanism may retrieve information from a neuron whose receptive field no longer encompasses the stimulus (as in the lower half of Figure 2C). The passively reduced signal from this neuron could therefore increase the detection threshold of this mechanism. We believe that it is conceivable, even likely, that perceptual mechanisms have imperfect access to the current eye position and would therefore be expected to suffer from both passive and active suppression. For this reason, the following analysis first investigates the combined effect of passive and active suppression, in an attempt to show the overall reduction in sensitivity during eye movements (Data shown in Figure 3 and Figure 4). Subsequent analyses (Figure 6 to Figure 8) will study active suppression in isolation.
At the coarsest level, we performed a population analysis that simply compared average activity per area in a fixed time window after stimulus onset. Figure 3 shows the average population response separately for the four areas and for stimuli flashed long before (pre), near (peri), and long after a saccade (post). The response in the pre period was set to 100%. Responsiveness in motion sensitive areas MT, MST, and VIP was less during saccades than during steady fixation. In areas MT and MST perisaccadic activity was reduced to a level of 83% (Area MT) and 88% (Area MST), while responses in area VIP were reduced to 91% of the presaccadic level. This difference was statistically significant in each area (RM-ANOVA on ranks followed by Tukey-Kramer post-hoc tests, p<0.05). Postsaccadic responses were enhanced to levels of 106% (Area MT), 106% (Area MST), and 108% (Area VIP). This effect reached statistical significance in both VIP and MST, but not in MT.
In the LIP population as a whole, the average response did not differ significantly between the three periods (peri: 106%, post: 104%). Within this population of cells, however, some showed a strong increase in firing in the saccade-only condition (i.e. without any flashed visual stimuli), while others showed a strong decrease in the saccade-only condition. In other words, the average response shown in Figure 3D is a mixture of pure saccade responses and visual responses. Given that almost all LIP cells in our population were modulated in the saccade-only condition, we are unable to perfectly isolate a pure visual response in the perisaccadic window. Within the subpopulation of cells in which the saccade alone evoked a response modulation of less than +/− 10% (LIP-0; see Methods), however, the responsivity was qualitatively similar (peri: 108%, post: 99%).
Next, we calculated a time-resolved population response, by aligning each neuron’s response to response onset (i.e. we corrected for the cell’s individual latency). We ignored the spatial location of the flashed bars and simply averaged across all cells and trials; as such this is an estimate of the overall population response. We determined this average separately for flashes presented in three time windows; long before the saccade (Pre), long after the saccade (Post), and in the time window in which suppression was maximal (Peri; [0 75]). In this time window both active and passive suppression mechanisms can operate. This analysis also allowed us to compare the visual response to the average response of these same neurons in the saccade-only condition (i.e. without any flashed bars). Figure 4 compares these pre-, peri-, post-, and saccade responses for the four populations of neurons. A comparison of the pre- and post-saccadic responses across areas shows that our visual stimuli led to clear and qualitatively comparable population responses in each area. Moreover, in each area, the pre-and postsaccadic responses are approximately the same, which demonstrates the consistency of the responses, as well as the fact that the coverage of the population receptive field was approximately the same before and after the saccade.
In areas MT, MST, and VIP the average perisaccadic responses were clearly reduced. The mechanisms underlying this suppression, however, are likely to be different in these areas. In areas MT and VIP the neural response in the saccade-only condition was largely unaffected by the saccade, hence the suppression was specific to visual responses during the saccade. In the MST population, however, we found a clear reduction of activity even in the absence of visual stimuli (black curve). The suppression of visual activity during saccades (green curve) could at least qualitatively be explained as a linear summation of the suppression of activity evoked in the saccade-only condition (black curve) and the response to visual stimuli during fixation (red/blue curves).
The response pattern in LIP was quite different. Not unexpectedly, the saccade-only conditions led to large eye-movement related activity in LIP (black curve). Visual stimuli presented during the saccade could not drive the LIP population above this saccade related activity and - about 50ms after stimulus onset - even reduced the average LIP activity below the activity evoked in the saccade-only condition.
The behavioral phenomenon of saccadic suppression has a well-known time course. Our goal in this section is to determine whether changes in neural response in areas of the dorsal stream match this time course. To link neural activity with behavior, we determined what we call the population excitability (See Methods). This measure can be interpreted as the average neural response to a continuous stream of flashes presented to the retina. To allow a comparison across areas, we scaled each area’s population excitability at around 100ms before saccade onset to 100%. Note that changes in this measure of population excitability around saccades include both active and passive mechanisms of suppression.
To relate the population excitability to the behavioral data obtained in humans, we made assumptions about the neural code that are necessarily tentative. We assumed that the neural response corresponds to the visibility of a stimulus that was presented some fixed amount of time earlier. With this assumption the link between neural response and stimulus perception can be quantified by a single number; the latency. We estimated this latency by cross-correlating the behavioral sensitivity data with the neural activity profiles. We used the behavioral data of Diamond et al. (Diamond et al., 2000) and found that the temporal shift as obtained from this cross-correlation analysis was very similar but not identical for the three areas, MT, MST and VIP, respectively. In areas MT and MST, neurophysiological data had to be shifted by τ = 98ms to obtain an optimal match with the behavioral data (Maximum of the normalized cross-correlation coefficient: rMax = 0.6153 (area MST) and rMax = 0.6073 (area MT)). Data from area VIP had to be shifted by τ = 112 ms (rMax = 0.6087). In other words, if perception were based on neural activity about 100ms after stimulus onset, then the suppression of neural activity in areas MT, MST and VIP would be a good predictor of perisaccadic reductions of visibility. In Figure 5 we shifted the ongoing population activity of areas MT and MST by τ = 98ms and population activity of area VIP by τ = 112ms and overlaid it with the behavioral sensitivity data of Diamond et al. (Diamond et al., 2000).
Psychophysical studies have investigated the temporal evolution of saccadic suppression by measuring contrast sensitivity for luminance gratings presented shortly before, during, or after saccades (Diamond et al., 2000). The suppression of contrast sensitivity starts for stimuli presented well before saccade onset and is maximal for stimuli presented at the time the eyes start to move. Contrast sensitivity returns back to control level for stimuli presented about 50–100ms after saccade offset. While this shows that pre-saccadic stimuli are suppressed, this does not by itself imply that the saccadic suppression mechanism must operate before the eye movement starts. The reason for this is that the response of the subject only comes after the saccade; hence there is ample time for intra- and post-saccadic mechanisms to change the behavioral response to the pre-saccadic stimulus. Behavioral methods or imaging methods relying on the slow BOLD response (Kleiser et al., 2004;Vallines and Greenlee, 2006) inevitably suffer from this delay between the measurement and the stimulus presentation time. In an electrophysiological recording this delay is reduced to the response latency of the cell (plus minimal latencies in the recording equipment). This allowed us to address the temporal dynamics of suppression with high fidelity.
In this section we zoom in on the peri-saccadic time window. First, we quantify suppression on a cell-by-cell basis (Figure 6) and then we show the average population response for stimuli flashed at different times with respect to saccade onset (Figure 7 & Figure 8).
The response of the example cell in Figure 2 was reduced even for flashes that were presented to a stationary retina. This is what we refer to as active suppression. To quantify the strength of active and passive suppression across areas, we determined the peak of the response for stimuli flashed long before a saccade and compared that with the peak response evoked by stimuli flashed (i) just before or (ii) during a saccade. Determining the peak response across spatial positions of the flashed bar ensured that we always compared stimuli flashed in the most sensitive part of the receptive field, irrespective of when and where the RF moved relative to the saccade. We calculated a suppression index as: SI = ((perisaccadic response/presaccadic response) − 1) ×100%. An SI of zero corresponds to a cell whose peak firing rate is not affected by the saccade; a negative SI corresponds to saccadic suppression, while a positive SI corresponds to saccadic enhancement. We calculated these indices separately for the two perisaccadic time windows. The effects in the first perisaccadic time window (− 75ms, 0ms] are due to pure active suppression; we refer to them as SIa. The effects in the second perisaccadic time window (0ms, 75ms] include both active and passive mechanisms; we refer to them as SIa&p.
The four panels (A–D) in Figure 6 show histograms of the suppression indices for each of the populations. Overall, the magnitude of saccadic suppression was similar in range across areas, ranging from ~60% suppression, to ~40% enhancement. The median indices (indicated by blue (before, SIa) and red (during, SIa&p) arrows in each panel) were always below zero; hence perisaccadic peak responses were typically reduced compared to presaccadic peak responses. The median suppression index for stimuli presented just before the saccade (SIa) was: MT: −26%, MST: −19%, VIP: −20%. The median suppression for combined active and passive mechanisms (SIa&p) was: MT: −29%, MST: −18%, VIP: −22%. These reductions in peak response as compared to the presaccadic peak responses were statistically significant in both perisaccadic time windows and in all areas (p<0.001, paired sign test). The difference in reduction between the two time windows was not significant in MT, MST, or VIP (p>0.6, paired sign test).
In LIP both active and combined active and passive suppression indices were also significantly below zero (SIa =−22%, SIa&p=−18%; p<0.001, paired sign test). Note that these data may appear to contradict the findings shown in Figure 4 where we showed that the average perisaccadic response in LIP (green curve) is higher than the average presaccadic response (red curve). Here we show that the peak perisaccadic response is lower than the peak pre-saccadic response. The resolution of this paradox lies in the fact that the LIP response in the perisaccadic windows most likely is a motor response that is independent of the position of the flash; hence its average over all positions (shown in Figure 4) is higher than the average taken long before the eye movement when the response is truly visual and restricted to a few locations on the screen. Therefore, a different way of phrasing the LIP results is that visual stimuli drive the cells during fixation, but that the same visual stimuli cannot increase the response during or just before a saccade, when the cell is already responding strongly in response to the saccade itself. In fact, if anything, the visual stimuli reduce the saccade response.
Consistent with this, we found that the suppression index during the saccade was slightly less negative than just before the saccade (SIa&p > SIa ; p<0.01, paired sign test). This is presumably due to the fact that most of our LIP cells increased their firing perisaccadically even in the saccade-only condition. To confirm this, we performed this analysis separately for the subpopulation of LIP cells that had enhanced responses in the saccade-only condition (LIP+), those that reduced their responses during saccades (LIP−), and those that were only modestly modulated by saccades (LIP-0) (See Methods). In the LIP+ population, the suppression index was −15% (p<0.01) for both time windows. In the LIP-population SIa was increased to −43% (p<0.01) while SIa&p was −31% (p<0.01). In the LIP-0 population SIa was −23% (p<0.01) and - SIa&p was −10% (p>0.05). This shows that in the perisaccadic time window, the LIP population as a whole but also each of its subpopulations is driven mainly by saccade planning; visual stimuli that arrive around this time are actively suppressed.
To provide further insight into the detailed temporal dynamics of the population activity around a saccade, Figure 7 displays the full time courses as two-dimensional activity maps. The two-dimensions correspond to two important temporal factors that determine the neural response; the time of stimulus presentation relative to saccade onset (horizontal) and the time relative to response onset (vertical). Zero on the horizontal axis corresponds to stimuli that land on the retina when the saccade starts. Positive values indicate that the stimulus was presented after saccade onset. Zero on the vertical axis is the time at which the first response can reliably be detected in a cell (i.e. the response time is corrected for each cell’s latency).
There are two important features to note in this diagram. First, the horizontal yellow-red bands in panels A, B, and C show that in areas MT, MST, and VIP the stimulus triggered a clear response that lasted about 70 ms. This response, however, was reduced for stimuli presented just before and during the saccade. This reinforces the finding described in Figure 4 and shows that a reduction in visual activity is found for stimuli presented around saccade onset.
The second feature of interest is most notable in MST. A diagonal dark band of suppressed activity aligns with the black line indicating saccade onset. Given that this suppression starts before saccade onset, it cannot be caused by changes in the retinal stimulation, but must be due to an active process of suppression. Neurons in area LIP show a quite different response pattern; the population shows strong saccade related activity (yellow-red diagonal band), but responds little if at all to the stimulus (absence of a horizontal band). This occurs even though this same population responds quite well to visual stimuli during fixation (not shown in this format, but see Figure 4).
We performed a statistical analysis (see Methods) to determine when the perisaccadic neural response (shown in Figure 7) was different from the response to visual stimuli long before a saccade. Figure 8 shows the results of this analysis in approximately the same format as Figure 7; the main difference is that in this representation the color red shows a statistically significant suppression and, conversely, the color green indicates a significant enhancement of perisaccadic activity (see Methods). This statistical thresholding reveals a much clearer pattern of suppression. To refer to specific parts of these maps we use tx to refer to the time of stimulus presentation relative to saccade onset (x-axis) and ty to the time after response onset (y-axis).
In area MT the main features are a saccadic enhancement (green) of stimuli presented 100 to 50ms before the saccade (tx = [−100ms, −50ms], ty~250ms), and a suppression (red) of the response to stimuli presented perisaccadically (tx = [−20ms, 100ms], ty~80ms).
In area MST we see an enhancement (green) of the response to stimuli presented before the saccade (tx = [−100 ms, 0ms], both near ty~0ms and ty~250ms) as well as an enhancement of responses for stimuli presented after the saccade (tx > 100ms, ty~50ms). The main feature, however, is a trough of suppression (red) that starts before saccade onset and extends well beyond the saccade. The alignment with the diagonal white line of saccade onset, and the presence of significant suppression before stimulus response onset (ty = 0ms), shows that this suppression is saccade-related, and an active process that takes place even without the presence of visual responses. Additionally, the fact that this suppression is significant even before the onset of the saccade (white line) shows that this suppression cannot be due to the retinal slip caused by the saccades.
In area VIP, all significant suppression (red) was observed after stimulus response onset, and never in the absence of visual stimuli. The strongest enhancement (green) was found in the late (ty~250ms) response to stimuli presented 100ms before until 50ms after saccade onset (tx = [−100ms, 50ms]). A weaker enhancement appears to precede saccade onset, even before the visual response.
In area LIP the statistical analysis confirms that cells are typically more strongly driven by (impending) saccades than by visual stimuli. The isolated island of suppression near tx = 50ms, ty = 50ms corresponds to the reduction in response following a visual stimulus presented during a saccade visible in Figure 4.
We investigated neural correlates of saccadic suppression in the dorsal stream of the macaque visual cortical system. In each of the investigated areas, we found clear interactions between the visual response and the eye movements that reflect suppression of neural activity. First, the pattern of suppression was qualitatively different in each of the areas; this is at odds with an early cut-off of visual input to the cortex during saccades. Second, we found that reductions in firing rate can be observed well before the eye starts to move, and even independently of the presence of a visual stimulus. This shows that at least part of the neural suppression must be due to an active process independent of intra- or post-saccadic changes in the visual input caused by the saccade. Third, we showed that the time course of neural excitability in the motion sensitive areas of the dorsal stream matched well with the time course of perceptual suppression in humans. This strengthens the case that these neural changes are indeed neural correlates of the behavioral phenomenon of saccadic suppression. We will discuss these findings in the light of previous behavioral, imaging, and physiological studies of saccadic suppression.
Much of the psychophysical debate has centered on the question whether saccadic suppression is an active process or not (Ross et al., 2001;Castet et al., 2001;Vallines and Greenlee, 2006). In other words, does the visual system actively attenuate processing, or is the reduced visibility a consequence of the changes in the retinal input caused by the eye-movements themselves? The fact that pre-saccadic stimuli are perceptually suppressed does not necessarily imply that suppression is an active process. The reason for this is that the subject’s response always occurs well after the eye movement and can therefore be influenced by intra-saccadic retinal image motion or the visual input evoked by the landing of the eye at the new position (Campbell and Wurtz, 1978). Behavioral studies clearly show that such passive, retinal processes play an important role in saccadic suppression (Campbell and Wurtz, 1978). Previous physiological studies have shown pre-saccadic changes in receptive field size and location, hence there can be no doubt that active processes play a role in visual processing around eye movements (For review, see (Ross et al., 2001;Wurtz, 2008)). The more specific question, whether an active process underlies saccadic suppression, however, is more difficult to answer. Our approach was to use the same visual stimulus to map the full temporal dynamics of changes in responsivity around saccades in four dorsal stream areas. This allowed us to show that a presaccadic, active, extraretinal suppression process operates in the areas strongly associated with motion perception.
Moreover, our approach of using the same stimulus in multiple areas provided us with a measure of neural suppression that could be compared across areas. Because the qualitative effects were similar across motion areas, we believe that it is reasonable to expect that these neural changes would have significant perceptual effects. In Figure 5 we compared the neural data obtained from motion areas to behavioral data obtained in humans and found a striking resemblance. Even though the comparison was across species, we believe that this strengthens the claim that these neural changes may indeed be responsible for the behavioral changes associated with saccadic suppression. Nevertheless, future work that performs a direct, trial by trial comparison of neural activity and the perceptual report of the animal is needed to demonstrate a causal link between the neural and behavioral phenomena of saccadic suppression.
Previous physiological studies in macaque area MT have reported a number of perisaccadic changes in responsivity. Thiele et al. (Thiele et al., 2002) reported that some MT cells reduced their firing rate during eye-movements. Consistent with this, a reduced BOLD response to luminance modulated stimuli has also been reported in human MT (Kleiser et al., 2004). Our findings confirm a general reduction in the response of MT and MST cells around saccades, but additionally and most importantly, allow us to demonstrate that these changes start before the saccade.
In agreement with previous findings concerning the dorsal aspect of area MST (MSTd) (Ibbotson et al., 2007;Ibbotson et al., 2008) we find a post-saccadic enhancement of the neural response in areas MT and MST. Additionally, we show that such an enhancement also occurs in VIP. There are several interesting hypotheses about the functional role of this enhancement. First, as Ibbotson et al. (2007) have suggested, this enhancement could be related to the enhanced post-saccadic ocular following response reported by Miles et al. (Kawano and Miles, 1986). In monkeys, area MST is involved in the execution of these short latency eye movement responses (Inoue et al., 1998). Moreover, these areas are known to be involved in motion perception (for reviews, see (Born and Bradley, 2005;Britten, 2008)), hence one could expect an enhanced neural response to result in an enhanced perceptual sensitivity. There is some evidence in the behavioral literature to support this view (see e.g. Figure 4 in Diamond et al. (2000)), but this phenomenon has not yet been studied in detail. Finally, Ibbotson and Cloherty (2009) have recently suggested that post-saccadic increases in firing could be the neural source of backward masking. In this view, the enhanced response to the post-saccadic scene helps to remove the weak response to peri-saccadic stimuli from awareness.
An important difference between our findings in MST and those of Ibbotson and colleagues (Ibbotson et al., 2008) is that we find suppression when the animal makes saccades in darkness while Ibbotson et al. find no evidence for this. The most likely reason for this discrepancy is that ‘darkness’ in our case was not as complete as that of Ibbotson et al. In our experimental setup, the saccades in darkness were made in response to a small red dot, and the video projector (projecting ‘black’) was on, hence the projection screen was not completely dark. We note, however, that because suppression in MST starts before saccade onset (Figure 8), the suppression cannot be due to saccade-induced retinal slip. Taken together the two studies suggest that an active process of suppression takes place in MST even before the saccade starts, but only if there is at least some residual visual input.
We are not aware of any previous studies that have addressed these issues in VIP. Our data show that VIP responds in a manner that is quite similar to MT and MST. The main difference appears to be that both suppression and postsaccadic enhancement in VIP occur later. A more mechanistic difference is that in MST the response to visual stimuli during a saccade is well described by the linear sum of the activity in the saccade-only condition and the response to visual stimuli during fixation. In VIP and MT on the other hand this interaction must be distinctly non-linear because there was no significant suppression of activity in the saccade-only conditions. We see this as further evidence that partially separate mechanisms must underlie the perisaccadic changes in visual responses in these areas.
The high perisaccadic activity in LIP should not be misconstrued as evidence for the absence of suppression. On the contrary, with our visual stimuli, it was not possible to drive LIP cells beyond the activity they had during saccades in darkness. In other words, suppression of the visual response in LIP was 100%. For the later response windows, the presence of a visual stimulus even led to a reduction of the neural response below the level seen during saccades in darkness. Activity in LIP, however, is not typically associated with direct visual perception of stimuli, but rather with the allocation of attention (Colby and Goldberg, 1999;Bisley and Goldberg, 2003). If LIP activity reflects a mechanism that allocates spatial attention, the fact that these cells cannot be driven by visual stimuli at that time may be related to the behavioral phenomenon of the attentional blink. In this interpretation LIP does not process attentional cues while attention is being re-allocated (i.e. LIP is already active). Such a mechanism could be useful to prevent the saccade-generated retinal motion from being interpreted as an exogenous cue for attention.
This view further highlights the fact that different areas, with different functional roles, may have different demands on perisaccadic signals. Some areas may require a complete cut-off of input, while others may still be able to extract useful information from the incoming retinal signal. It is conceivable, for instance, that the retinal motion signal generated by the saccade is used as a source of information about the speed and direction of the saccade. Rather than a nuisance, that information could be useful for the mechanism that constructs perceptual stability, as long as the motion signals are sufficiently dampened to prevent them from reaching awareness (Watson and Krekelberg, 2009). This view of perceptual stability and perisaccadic processing is consistent with the idea that the behavioral reduction of visibility around saccades is not due to an early (thalamic) cut-off of all visual input to the cortex. Instead of such an early cut-off, our new data suggest that there can be multiple separate mechanisms that adjust the perisaccadic visual signals to match the requirements of processing in a particular area.
This work was supported by grants from the Deutsche Forschungsgemeinschaft (DFG: SFB 509/B7 and FOR 560/A3), the Human Frontiers Science Program (HFSP RG00149/1999-B), the NIH (R01EY017605), and the EU research grant MEMORY (6 FP/043236 NEST).