The disparity between the apparent stability of the perceived image and the rapidly shifting retinal image during saccadic eye movements has long captivated scientific interest (for a review, see Wurtz, 2008). A key facet of this perceived visual stability is the marked difference in the subjective perception of an external stimulus displacement compared to a similar retinal shift caused by a saccade, which likely reflects an active, extra-retinal compensation for the saccade (Thiele et al., 2002). Apart from its relevance to the understanding of visuo-oculomotor function, this striking discrepancy between optics and perception offers a unique means of probing whether and how a given neural representation is related to the contents of subjective visual awareness under highly ubiquitous and ecological conditions.

The most investigated candidates for the neural underpinning of the perceptual distinction between external stimulus displacements and saccades are dorsal higher-level visual regions, and in particular the middle temporal (MT/V5) and the middle superior temporal (MST) areas, whose neurons were shown to strongly differentiate between external and saccadic movements (Thiele et al., 2002). This response pattern is compatible with the association of MT/MST activity with perceived (versus retinal) motion (Tootell et al., 1995; Zeki et al., 1993) and was recently linked with input originating from the superior colliculus and arriving in MT through the pulvinar (Ridder and Tomlinson, 1997; Uematsu et al., 2013). Other players related to this process are the lateral and ventral intraparietal area where remapping effects (Duhamel et al., 1992) and head-centered receptive fields (Duhamel et al., 1997) were documented.

Early retinotopic visual cortex (V1/V2/V3), in contrast, is usually believed to reflect retinal displacements regardless of whether they were produced by self- or external- motion (e.g., for a recent demonstration see Meirovithz et al., 2012). However, this view is not unanimous, and multiple conflicting findings have been reported. Starting with the pioneering work of Wurtz (1969), several groups have argued for similar responses of V1 to external and saccadic stimulus displacements, implying retinal-like coding of motion in V1 (e.g. Ilg and Thier, 1996; Fischer et al., 1981). Others have reported responses that were mostly compatible with at least some level of extra-retinal modulation (e.g., Gawne and Martin, 2002; Kagan et al., 2008) and some have argued strongly for differential responses, including very recent work readdressing this old but yet unsettled question (e.g., Troncoso et al., 2015; McFarland et al., 2015). This discrepancy across studies may be related to differences in the experimental paradigms and data analysis methods employed (Troncoso et al., 2015).

Another less discussed potential contributor to perceptual stability is ventral high-level visual cortex (or Inferior Temporal, in non-human primates). This area, characterized by category-selective responses, has traditionally been viewed as having extremely large receptive fields (see review in Sayres et al., 2010), and therefore insensitive to both small saccades and small external displacements as long as they are not large enough to replace the objects benefiting from foveal acuity (Levy et al., 2001). However, findings indicating a release from adaptation following small external stimulus displacements (Grill-Spector et al., 1999) as well as reports of position-dependent responses (Sayres et al., 2010), show that much is still unknown regarding whether and how ventral high-level visual cortex handles the rapid stimulus displacements caused by saccades. Recent findings of saccade-related suppression in V4 (Zanos et al., 2016) may suggest that higher-level ventral regions might be affected by saccadic efferent copy as well.

Where in the visual cortex does the distinction between external- and saccade-related motion arise? Does it start at early retinotopic processing or does it appear exclusively downstream? While recordings in non-human primates have provided the bulk of existing knowledge on eye-position related visual processing, such studies are typically very focused in their anatomical coverage, targeting one or two areas. This narrow anatomical coverage might veil the greater functional-anatomical context by which saccades are neurally distinguished from external displacements. In particular, studies focused on MT without sampling earlier cortical regions cannot preclude the possibility that the observed effects in MT are inherited from the early retinotopic visual areas. Conversely, observing significant differences between saccades and external displacements in studies focused exclusively on V1 does not rule out the possibility that higher-level regions may display a far greater level of differential processing of saccades compared to external displacements. However, to the best of our knowledge, such a direct electrophysiological comparison of saccades and external displacements across the visual hierarchy has not been made yet.

Human intracranial EEG recordings (ECoG/SEEG), conducted for clinical diagnostic purposes, often sample the cortex with a substantial anatomical coverage, while still accessing population activity at the millimeter/millisecond spatiotemporal scale. We have recently used this technique to address a similar perceived stability issue arising during eye blinks. In that study, we found that in high-level visual cortex transient responses to visual interruptions were suppressed when such interruptions were produced by blinks, but not when they were produced by external stimulus blanking (Golan et al., 2016). In contrast, both kinds of interruptions elicited similar responses in early visual cortex. Here, we tested whether these findings can be generalized to include the distinction between external stimulus displacements and saccades, by contrasting the cortical responses induced by these two events in the experimental sessions previously reported in Golan et al. (2016).

Twelve subjects undergoing invasive neurophysiological monitoring for clinical indications viewed still images (15.8° wide) of faces, as well as non-face control stimuli (1 s of continuous display per image). Blocks of ten trials (ten consecutive images) were separated by an intermittent gray screen lasting three seconds, serving as a baseline. In some of the blocks (12 out of 44), a red dot was presented at the center of the stimulus, and the subjects were pre-instructed to fixate on it. In the other 32 blocks, no fixation cross was presented, and the subjects viewed the stimuli freely. During the fixation blocks, excluded from analysis in Golan et al. (2016), horizontal image displacements of either 1.3° or 3.7° visual degrees were introduced at latencies of 300, 500 or 700 ms from trial onset. Eye position was monitored by a video eye tracker (EyeLink 1000, SR Research, Ontario, Canada) synchronized with the stimulus-presenting laptop and the iEEG recording station. Offline, saccades verified to be unrelated with eye blinks and within the magnitude range of 1.3° to 3.7° were marked for comparison with the external stimulus displacements. Note that both the external displacements and the selected saccades were considerably smaller than the extent of the stimuli (15.8°). Subjects were instructed to click a mouse button when they saw an animal image, and these trials were excluded from further analysis.

High-frequency broadband activity (HFB, 70–150 Hz) was estimated from the intracranial recordings as a proxy of population mean firing rate (for further details see Golan et al., 2016). 115 contacts showed significant and considerable visual response to the images (inclusion criteria: p<0.05 Bonferroni corrected and effect size ≥2 baseline standard deviations). A General Linear Model (GLM) with a Finite Impulse Response (FIR) basis set was used as a means of deconvolving the overlapping neural responses to the appearance of new stimuli, external stimulus displacements, and saccades, estimating the unique contribution of each experimental condition to the observed timecourse (see Material and methods). Blinks and gaps were accounted for as well in the FIR GLM model, but their estimates are not reported here (see Golan et al., 2016). Saccades smaller than 1.3° or larger than 3.7° were also accounted for using separate predictor sets but are not further analyzed as there were no matching external displacements that would enable a controlled comparison.

Grand averages of the contribution of external displacements and saccades to HFB

We averaged the deconvolved traces related with selected saccades or external displacements across electrodes and subjects, using seven visual regions of interest (ROIs): V1, V2, V3, V4, VO, face-selective electrodes and high-level non-face selective electrodes (Figure 1). As can be readily observed, in early visual areas, both external displacements and saccades produced a subsequent burst of HFB activity, yielding an overall similar activity profile for these two conditions. However, in higher order areas along the visual hierarchy- areas V4, VO, face-selective and non face-selective high-level visual regions, saccades produced almost no HFB response modulation whereas external displacements of the stimulus were still effective in triggering an HFB activity increase.

Figure 1 with 1 supplement see all

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Within-electrode testing of external displacements against saccades

To statistically test this apparent divergence of saccade-related and external displacement-related responses, we conducted a random permutation test within each electrode by shuffling saccade and external displacement event-labels 10,000 times, re-estimating their GLM FIR models in each simulation. For each condition (saccades and external displacements), we detected the largest cluster of continuously above zero HFB-response.

The test statistic was defined as the area under the displacements-related cluster minus the area under the saccades-related cluster. This approach does not assume exact temporal registration of saccade and displacement traces, and it minimizes any potential offsetting of positive HFB responses by negative ones (in contrast to plain averaging of response traces over time). Figure 2 presents the results of this test for all electrodes, plotted on a common cortical map, comparing both small and large external displacements to saccades. Multiple sites (36/115) showed significantly greater HFB contribution of external displacements compared to saccades (p_FDR < 0.05), with greater occurrence of significant difference in visual regions anterior to V3: V1,(1/15), V2 (0/11), V3 (3/12), V4 (4/6), VO (2/6), face-selective electrode (6/15) and high-level non face-selective electrodes (10/18), the latter ROI including both ventral and dorsal high-level sites. The differences showed a significant discrepancy across ROIs (randomization test of independence, χ²(6)=12.64, p=0.004). No site showed a significantly greater HFB increase for saccades compared with external displacements. Repeating this analysis while using only saccades whose onsets were in the range of 300–700 ms post trial-onset resulted in a highly comparable statistical map (Figure 2—figure supplement 1), with 39/115 electrodes showing significantly greater HFB contribution of external displacements compared to saccades and one V2 electrode showing the opposite effect. Last, comparing the saccades with only the small (1.3°, Figure 2—figure supplement 2) or large (3.7°, Figure 2—figure supplement 3) external displacements also found qualitatively similar results, yet with a lower number of significant sites (25/115 and 27/115 significant electrodes, respectively), likely due to the reduced statistical power of these smaller sample analyses.

Figure 2 with 3 supplements see all

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Figure 2—source data 1

Individual electrode data for Figure 2.

Each row describes an electrode, with its SUMA standardized mesh nearest vertex (index, hemisphere and MNI coordinates), region of interest (if assigned), FDR-corrected p value for external displacements greater than saccades, and FDR-corrected p value for saccades greater than external displacements.

https://doi.org/10.7554/eLife.27819.008

Download elife-27819-fig2-data1-v1.csv

Single cases with simultaneous low- and high-level recordings

Since these results were pooled across multiple subjects, one might argue that the observed pattern of increased differential response to displacements versus saccades along the cortical hierarchy might be an artifact produced by the juxtaposition of effects recorded in different individuals, who might be confounded by uncontrolled behavioral or neuronal differences. Evidence against this possibility is provided by saccade and displacement-related responses acquired simultaneously in low and high-level sites. This is illustrated in Figure 3 in which each panel depicts recordings obtained in different electrodes implanted within an individual subject. The higher-level traces demonstrate marked HFB activity increases following external displacements but not following saccades. The traces from early visual sites show similar HFB response increases following both events.

Figure 3

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Some additional, more subtle aspects of the response to displacements versus saccades are evident in these individual traces. In subject P57 (Figure 3a), V1 (left column) and MST (right column, an electrode located slightly less than 1 cm anterior to the anatomically defined MST/TO2) sites were recorded simultaneously. In this particular case, the saccade-related activity increase in V1 was preceded by an activity decrease. This trend was not sufficiently strong to pass our false-discovery rate control when compared with displacements at the group level.

In subject P39 (Figure 3b), a V2 response (leftmost column, responses collapsed over face and non-face trials) is compared with three face-selective sites sampling posterior and anterior FFA (FFA-1 and FFA-2,Weiner and Grill-Spector, 2012) and a probable anterior temporal face patch (rightmost column, see Rajimehr et al., 2009). Beyond replicating the pattern of HFB activity increase in high-level visual regions following external displacements but not after saccades, this particular case may hint at a hierarchical gradient within face-selective sites, with insensitivity to the saccadic displacement at anterior but not posterior FFA and relatively invariant response both to saccades and external displacements in the anterior face patch site.

Comparison of suppression of eye blink- and saccade-related transients

An interesting question concerns the possible relationship between the suppression of saccadic-related transients and the previously reported (Golan et al., 2016) suppression of blink-related transients. To quantitatively test for such an association, we first examined the level of overlap between two sets of electrodes: those that showed a significantly greater HFB increase in response to external displacements compared with saccades and those that showed a significantly greater HFB increase in response to 'gaps' (blank frames) compared with eye blinks obtained from Golan et al. (2016). The overlap between the two sets of electrodes was far above chance level, with a Sørensen–Dice coefficient of 0.5763 (p=0.000018, random permutation test, see Materials and methods).

In order to gain a more detailed understanding of the association between the saccade and blink suppression effects, we defined two indices as follows: First, we defined a suppression index for blinks, ${\displaystyle \frac{gap-blink}{gap+blink}}$, where ‘gap’ indicates the HFB increase following the offset of blank frames, while ‘blink’ indicates the HFB increase following the offset of spontaneous blinks. For this measure we used the cross-validated response estimates for both events (see Golan et al., 2016). Similarly, we defined a suppression index for saccades as ${\displaystyle \frac{displacement-saccade}{displacement+saccade}}$. Figure 4 depicts the two resulting indices, averaged within each of the seven ROIs. All of the ROIs except for V4 were well fit by a linear relation between the two indices (r = 0.95, n = 6). Since such an opportunistic removal of an outlier introduces positive bias to the correlation, the correlation's significance was tested by a randomization procedure that takes into account this issue (p=0.0111, see Materials and methods). V4 was notably above the trend line, showing greater suppression of saccades than expected. However, since our V4 sample was small (6 electrodes), we cannot unequivocally determine from the current data whether this sample-level deviation reflects that V4, in general, has a particularly strong suppression effect for saccades compared with blinks.

Figure 4

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Figure 4—source data 1

Individual electrode data for Figure 4.

Each row describes an electrode, with its SUMA standardized mesh nearest vertex (index, hemisphere and MNI coordinates), region of interest (only electrodes with assigned ROIs participated in this analysis), blink suppression index and saccade suppression index.

https://doi.org/10.7554/eLife.27819.011

Download elife-27819-fig4-data1-v1.csv

We compared human intracranial recordings following retinal displacements of naturalistic stimuli caused either by small external displacements of the stimuli or by saccades of similar magnitude. External displacements triggered a subsequent HFB activity increase that affected both lower-level visual regions and higher-level visual regions, including both the dorsal and ventral streams. In contrast, the activity increase following saccades was mostly confined to early visual areas—V1 to V3—and waned to nil as the visual signal proceeded forward in the visual hierarchy. This spatiotemporal response pattern was reflected in the gradual appearance of significant differences between the external displacement-related and saccade-related HFB activity increases along the progression of the cortical hierarchy.

Unless stated otherwise, all data acquisition and analysis steps are compatible with the Materials and methods section of Golan et al. (2016), including electrode-localization, regions of interest (ROIs) definition, data modeling and statistical testing.

1. 1. Wang L
   2. Mruczek RE
   3. Arcaro MJ
   4. Kastner S

   (2015) Probabilistic Maps of Visual Topography in Human Cortex

   Publicly available at Princeton University Website.

   http://scholar.princeton.edu/napl/resources

1. 1. Collewijn H
   2. van der Steen J
   3. Steinman RM

   (1985)

   Human eye movements associated with blinks and prolonged eyelid closure

   Journal of neurophysiology 54:11–27.

   • PubMed
   • Google Scholar
2. 1. Crick F
   2. Koch C

   (1995) Are we aware of neural activity in primary visual cortex?

   Nature 375:121–123.

   https://doi.org/10.1038/375121a0

   • PubMed
   • Google Scholar
3. 1. Destrieux C
   2. Fischl B
   3. Dale A
   4. Halgren E

   (2010) Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature

   NeuroImage 53:1–15.

   https://doi.org/10.1016/j.neuroimage.2010.06.010

   • PubMed
   • Google Scholar
4. 1. DiCarlo JJ
   2. Maunsell JH

   (2000) Form representation in monkey inferotemporal cortex is virtually unaltered by free viewing

   Nature Neuroscience 3:814–821.

   https://doi.org/10.1038/77722

   • PubMed
   • Google Scholar
5. 1. Diamond MR
   2. Ross J
   3. Morrone MC

   (2000)

   Extraretinal control of saccadic suppression

   Journal of Neuroscience 20:3449–3455.

   • PubMed
   • Google Scholar
6. 1. Duhamel JR
   2. Colby CL
   3. Goldberg ME

   (1992) The updating of the representation of visual space in parietal cortex by intended eye movements

   Science 255:90.

   https://doi.org/10.1126/science.1553535

   • PubMed
   • Google Scholar
7. 1. Duhamel JR
   2. Bremmer F
   3. Ben Hamed S
   4. Graf W

   (1997) Spatial invariance of visual receptive fields in parietal cortex neurons

   Nature 389:845–848.

   https://doi.org/10.1038/39865

   • PubMed
   • Google Scholar
8. 1. Fischer B
   2. Boch R
   3. Bach M

   (1981) Stimulus versus eye movements: comparison of neural activity in the striate and prelunate visual cortex (A17 and A19) of trained rhesus monkey

   Experimental Brain Research 43:69–77.

   https://doi.org/10.1007/BF00238811

   • PubMed
   • Google Scholar
9. 1. Gawne TJ
   2. Martin JM

   (2002) Responses of primate visual cortical neurons to stimuli presented by flash, saccade, blink, and external darkening

   Journal of Neurophysiology 88:2178–2186.

   https://doi.org/10.1152/jn.00151.200

   • PubMed
   • Google Scholar
10. 1. Golan T
    2. Davidesco I
    3. Meshulam M
    4. Groppe DM
    5. Mégevand P
    6. Yeagle EM
    7. Goldfinger MS
    8. Harel M
    9. Melloni L
    10. Schroeder CE
    11. Deouell LY
    12. Mehta AD
    13. Malach R

    (2016) Human intracranial recordings link suppressed transients rather than 'filling-in' to perceptual continuity across blinks

    eLife 5:e17243.

    https://doi.org/10.7554/eLife.17243

    • PubMed
    • Google Scholar
11. 1. Grill-Spector K
    2. Kushnir T
    3. Edelman S
    4. Avidan G
    5. Itzchak Y
    6. Malach R

    (1999) Differential processing of objects under various viewing conditions in the human lateral occipital complex

    Neuron 24:187–203.

    https://doi.org/10.1016/S0896-6273(00)80832-6

    • PubMed
    • Google Scholar
12. 1. Grill-Spector K
    2. Malach R

    (2004) The human visual cortex

    Annual Review of Neuroscience 27:649–677.

    https://doi.org/10.1146/annurev.neuro.27.070203.144220

    • PubMed
    • Google Scholar
13. 1. Hamamé CM
    2. Vidal JR
    3. Perrone-Bertolotti M
    4. Ossandón T
    5. Jerbi K
    6. Kahane P
    7. Bertrand O
    8. Lachaux JP

    (2014) Functional selectivity in the human occipitotemporal cortex during natural vision: evidence from combined intracranial EEG and eye-tracking

    NeuroImage 95:276–286.

    https://doi.org/10.1016/j.neuroimage.2014.03.025

    • PubMed
    • Google Scholar
14. Website

    1. Howell DC

    (2015) Overview of randomization tests [Online]

    Accessed July 2017.

    https://www.uvm.edu/~dhowell/StatPages/Randomization%20Tests/RandomizationTestsOverview.html
15. 1. Ilg UJ
    2. Thier P

    (1996) Inability of rhesus monkey area V1 to discriminate between self-induced and externally induced retinal image slip

    European Journal of Neuroscience 8:1156–1166.

    https://doi.org/10.1111/j.1460-9568.1996.tb01283.x

    • PubMed
    • Google Scholar
16. 1. Kagan I
    2. Gur M
    3. Snodderly DM

    (2008) Saccades and drifts differentially modulate neuronal activity in V1: effects of retinal image motion, position, and extraretinal influences

    Journal of Vision 8:19.

    https://doi.org/10.1167/8.14.19

    • PubMed
    • Google Scholar
17. 1. Leopold DA
    2. Logothetis NK

    (1998) Microsaccades differentially modulate neural activity in the striate and extrastriate visual cortex

    Experimental Brain Research 123:341–345.

    https://doi.org/10.1007/s002210050577

    • PubMed
    • Google Scholar
18. 1. Levy I
    2. Hasson U
    3. Avidan G
    4. Hendler T
    5. Malach R

    (2001) Center-periphery organization of human object areas

    Nature neuroscience 4:533–539.

    https://doi.org/10.1038/87490

    • PubMed
    • Google Scholar
19. 1. McFarland JM
    2. Bondy AG
    3. Saunders RC
    4. Cumming BG
    5. Butts DA

    (2015) Saccadic modulation of stimulus processing in primary visual cortex

    Nature Communications 6:8110.

    https://doi.org/10.1038/ncomms9110

    • PubMed
    • Google Scholar
20. 1. Meirovithz E
    2. Ayzenshtat I
    3. Werner-Reiss U
    4. Shamir I
    5. Slovin H

    (2012) Spatiotemporal effects of microsaccades on population activity in the visual cortex of monkeys during fixation

    Cerebral Cortex 22:294–307.

    https://doi.org/10.1093/cercor/bhr102

    • PubMed
    • Google Scholar
21. 1. Mukamel R
    2. Gelbard H
    3. Arieli A
    4. Hasson U
    5. Fried I
    6. Malach R

    (2005) Coupling between neuronal firing, field potentials, and FMRI in human auditory cortex

    Science 309:951–954.

    https://doi.org/10.1126/science.1110913

    • PubMed
    • Google Scholar
22. 1. Podvalny E
    2. Yeagle E
    3. Mégevand P
    4. Sarid N
    5. Harel M
    6. Chechik G
    7. Mehta AD
    8. Malach R

    (2017) Invariant Temporal Dynamics Underlie Perceptual Stability in Human Visual Cortex

    Current Biology 27:155–165.

    https://doi.org/10.1016/j.cub.2016.11.024

    • PubMed
    • Google Scholar
23. 1. Rajimehr R
    2. Young JC
    3. Tootell RB

    (2009) An anterior temporal face patch in human cortex, predicted by macaque maps

    PNAS 106:1995–2000.

    https://doi.org/10.1073/pnas.0807304106

    • PubMed
    • Google Scholar
24. 1. Ridder WH
    2. Tomlinson A

    (1997) A comparison of saccadic and blink suppression in normal observers

    Vision Research 37:3171–3179.

    https://doi.org/10.1016/S0042-6989(97)00110-7

    • PubMed
    • Google Scholar
25. Website

    1. Sayres R
    2. Weiner KS
    3. Wandell, B A
    4. Grill-Spector, K A

    (2010) Stimulus-dependent position sensitivity in human ventral temporal cortex

    http://vision.stanford.edu/teaching/cs423_spring0910/sayres_weiner_wandell_grillspector.pdf
26. 1. Sylvester R
    2. Haynes JD
    3. Rees G

    (2005) Saccades differentially modulate human LGN and V1 responses in the presence and absence of visual stimulation

    Current Biology 15:37–41.

    https://doi.org/10.1016/j.cub.2004.12.061

    • PubMed
    • Google Scholar
27. 1. Thiele A
    2. Henning P
    3. Kubischik M
    4. Hoffmann KP

    (2002) Neural mechanisms of saccadic suppression

    Science 295:2460–2462.

    https://doi.org/10.1126/science.1068788

    • PubMed
    • Google Scholar
28. 1. Tootell RB
    2. Reppas JB
    3. Dale AM
    4. Look RB
    5. Sereno MI
    6. Malach R
    7. Brady TJ
    8. Rosen BR

    (1995) Visual motion aftereffect in human cortical area MT revealed by functional magnetic resonance imaging

    Nature 375:139–141.

    https://doi.org/10.1038/375139a0

    • PubMed
    • Google Scholar
29. 1. Troncoso XG
    2. McCamy MB
    3. Jazi AN
    4. Cui J
    5. Otero-Millan J
    6. Macknik SL
    7. Costela FM
    8. Martinez-Conde S

    (2015) V1 neurons respond differently to object motion versus motion from eye movements

    Nature Communications 6:8114.

    https://doi.org/10.1038/ncomms9114

    • PubMed
    • Google Scholar
30. 1. Uematsu M
    2. Matsuzaki N
    3. Brown EC
    4. Kojima K
    5. Asano E

    (2013) Human occipital cortices differentially exert saccadic suppression: Intracranial recording in children

    NeuroImage 83:224–236.

    https://doi.org/10.1016/j.neuroimage.2013.06.046

    • PubMed
    • Google Scholar
31. 1. Wang L
    2. Mruczek RE
    3. Arcaro MJ
    4. Kastner S

    (2015) Probabilistic Maps of Visual Topography in Human Cortex

    Cerebral cortex 25:bhu277.

    https://doi.org/10.1093/cercor/bhu277

    • PubMed
    • Google Scholar
32. 1. Weiner KS
    2. Grill-Spector K

    (2012) The improbable simplicity of the fusiform face area

    Trends in Cognitive Sciences 16:251–254.

    https://doi.org/10.1016/j.tics.2012.03.003

    • PubMed
    • Google Scholar
33. 1. Wurtz RH

    (1969)

    Comparison of effects of eye movements and stimulus movements on striate cortex neurons of the monkey

    Journal of neurophysiology 32:987–994.

    • PubMed
    • Google Scholar
34. 1. Wurtz RH

    (2008) Neuronal mechanisms of visual stability

    Vision Research 48:2070–2089.

    https://doi.org/10.1016/j.visres.2008.03.021

    • PubMed
    • Google Scholar
35. 1. Zanos TP
    2. Mineault PJ
    3. Guitton D
    4. Pack CC

    (2016) Mechanisms of Saccadic Suppression in Primate Cortical Area V4

    Journal of Neuroscience 36:9227–9239.

    https://doi.org/10.1523/JNEUROSCI.1015-16.2016

    • PubMed
    • Google Scholar
36. 1. Zeki S
    2. Watson JD
    3. Frackowiak RS

    (1993) Going beyond the information given: the relation of illusory visual motion to brain activity

    Proceedings of the Royal Society B: Biological Sciences 252:215–222.

    https://doi.org/10.1098/rspb.1993.0068

    • PubMed
    • Google Scholar

Author details

1. Tal Golan

   Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel

   Contribution

   Conceptualization, Formal analysis, Methodology, Writing—original draft, Acquisition of data

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7940-7473

2. Ido Davidesco

   Department of Psychology, New York University, New York, United States

   Contribution

   Conceptualization, Writing—review and editing, Acquisition of data

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-0754-5807

3. Meir Meshulam

   Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel

   Contribution

   Writing—review and editing, Acquisition of data

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5899-7681

4. David M Groppe

   1. Department of Neurosurgery, Hofstra Northwell School of Medicine, Manhasset, United States
   2. The Feinstein Institute for Medical Research, Manhasset, United States
   3. The Krembil Neuroscience Centre, Toronto, Canada

   Contribution

   Writing—review and editing, Acquisition of data

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3282-2514

5. Pierre Mégevand

   1. Department of Neurosurgery, Hofstra Northwell School of Medicine, Manhasset, United States
   2. The Feinstein Institute for Medical Research, Manhasset, United States

   Contribution

   Writing—review and editing, Acquisition of data

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0427-547X

6. Erin M Yeagle

   1. Department of Neurosurgery, Hofstra Northwell School of Medicine, Manhasset, United States
   2. The Feinstein Institute for Medical Research, Manhasset, United States

   Contribution

   Writing—review and editing, Acquisition of data

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1147-4976

7. Matthew S Goldfinger

   1. Department of Neurosurgery, Hofstra Northwell School of Medicine, Manhasset, United States
   2. The Feinstein Institute for Medical Research, Manhasset, United States

   Contribution

   Writing—review and editing, Acquisition of data

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9274-8742

8. Michal Harel

   Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel

   Contribution

   Implant digital reconstruction

   Competing interests

   No competing interests declared

9. Lucia Melloni

   1. Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
   2. NYU Comprehensive Epilepsy Center, Department of Neurology, School of Medicine, New York University, New York, United States

   Contribution

   Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8743-5071

10. Charles E Schroeder

    1. Department of Neurosurgery, Columbia University College of Physicians and Surgeons, New York, United States
    2. Cognitive Neuroscience and Schizophrenia Program, Nathan Kline Institute, Orangeburg, United States

    Contribution

    Conceptualization, Writing—review and editing

    Competing interests

    Reviewing editor, eLife

11. Leon Y Deouell

    1. Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
    2. Department of Psychology, The Hebrew University of Jerusalem, Jerusalem, Israel

    Contribution

    Conceptualization, Writing—review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-6147-5208

12. Ashesh D Mehta

    1. Department of Neurosurgery, Hofstra Northwell School of Medicine, Manhasset, United States
    2. The Feinstein Institute for Medical Research, Manhasset, United States

    Contribution

    Conceptualization, Writing—review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-7293-1101

13. Rafael Malach

    Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel

    Contribution

    Conceptualization, Writing—review and editing

    For correspondence

    rafi.malach@gmail.com

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-2869-680X

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