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Vision Research

journal homepage: www.elsevier.com/locate/visres

Contextual effects on binocular matching are evident in primary visualcortex

Reuben Rideaux⁎, Andrew E. WelchmanDepartment of Psychology, University of Cambridge, UK

A R T I C L E I N F O

Keywords:StereopsisContextual effectsFunctional imagingPrimary visual cortex

A B S T R A C T

Global context can dramatically influence local visual perception. This phenomenon is well-documented formonocular features, e.g., the Kanizsa triangle. It has been demonstrated for binocular matching: the dis-ambiguation of the Wallpaper Illusion via the luminance of the background. For monocular features, there isevidence that global context can influence neuronal responses as early as V1. However, for binocular matching,the activity in this area of the visual cortex is thought to represent local processing, suggesting that the influenceof global context may occur at later stages of cortical processing. Here we sought to test if binocular matching isinfluenced by contextual effects in V1, using fMRI to measure brain activity while participants viewed per-ceptually ambiguous “wallpaper” stereograms whose depth was disambiguated by the luminance of the sur-rounding region. We localized voxels in V1 corresponding to the ambiguous region of the pattern, i.e., where thesignal received from the eyes was not predictive of depth, and despite the ambiguity of the input signal, usingmulti-voxel pattern analysis we were able to reliably decode perceived (near/far) depth from the activity of thesevoxels. These findings indicate that stereoscopic related neural activity is influenced by global context as early asV1.

1. Introduction

Visual perception is influenced by spatial context. For instance, twoobjects of equal luminance can appear to have different levels ofbrightness if they are observed in different contexts (Fig. 1a). Similarly,the perception of luminance defined contours can be induced by thepresence of spatially distinct elements within a visual scene if they arearranged such that the visual system extrapolates the presence of anoccluding surface, as in the Kanizsa triangle illusion (Kanizsa, 1979;Fig. 1b).

Spatial context can influence the perception of depth. For instance,a repetitive pattern presented to the two eyes can pose a challenge tothe visual system in that a range of different interpretations of thematches between the left and right eyes’ views are possible – theWallpaper Illusion (Brewster, 1844). Spatial context can influencewhich interpretation is selected by determining which of the similarelements are matched between the two eyes. In particular, when the leftand right eyes are presented with square-wave gratings with a 180°phase offset (such that a light bar in the left eye corresponds to a darkbar in the right eye and vice versa) there are two ways that the imagescan be stereoscopically matched. The images can be “shifted” nasally ortemporally to align the stripes in the centre of the gratings while

producing half-occlusions at the edges. When the background lumi-nance of the grating is mid-way between the light and dark bars, thenasal/temporal stereoscopic matching solutions are equally probable,producing a bistable situation in which the perceived depth of thegrating alternates between near vs. far interpretations. By manipulatingthe background luminance of the grating, it is possible to constrain theperceptual interpretation of the stimulus from its ambiguous state sothat one perceptual interpretation is chosen (Anderson & Nakayama,1994; Fig. 1c). This is thought to occur as a result of the visual systemseeking to preserve contrast polarity during the matching of monocularinputs. Critically, while this matching constraint is only present at theleft and right edges of the stereogram, the entire pattern is perceived asconsistently near or far. This suggests a neural mechanism sensitive toextensive portions of the viewed scene.

It is interesting to consider how such displays might influence theresponses of binocular neurons in the visual cortex. Within primaryvisual cortex, neurons have small receptive fields, meaning that theycould only register the disparity of a small portion of the display. Whileneurons sampling the edges of the display may have their responsesdisambiguated by the contrast of the background, we would expectthose sampling from the centre of the wallpaper pattern to provideambiguous information as to whether the image features projected onto

https://doi.org/10.1016/j.visres.2019.04.001Received 9 November 2018; Received in revised form 2 April 2019; Accepted 6 April 2019

⁎ Corresponding author.E-mail address: reuben.rideaux@gmail.com (R. Rideaux).

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Available online 16 April 20190042-6989/ © 2019 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/).

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one retina should be matched nasally or temporally with respect to theimage on the other retina (Fig. 2). Disambiguation of the signal couldoccur as early as V1: lateral or feedback connections from neurons re-ceiving input from the edges of the pattern could influence the local(ambiguous) activity of those receiving input from the centre. However,

electrophysiological recordings in macaques suggest that the activity ofV1 neurons may not be representative of perceived depth. Cummingand Parker (2000) manipulated the perceived depth of a stimulus whilstmaintaining the same retinal input within the receptive field of bino-cular neurons in V1 and showed the activity of these neurons was lar-gely unaffected by the manipulation. Further, Cumming and Parker(1997) showed that binocular neurons in V1 respond to anti-correlatedrandom-dot stereograms, i.e., in which the polarity of dots is reversedbetween the left and right eyes, which do not produce a percept ofdepth. These results suggest that V1 activity does not always accordwith the stereo depth percept of the observer, and thus that the influ-ence of spatial context may occur at a later stage of processing.

Here we rely on the spatial resolution of fMRI to examine in-formation about the responses to depth stimuli within the visual cortex.Specifically, in V1, where receptive fields are relatively small, neuronssampling information from the edges encode depth signals that areconstrained by the local contrast signals. By contrast, neurons samplingfrom the centre of the pattern receive ambiguous input that can bematched in a temporal or nasal direction. If local activity in V1 is un-affected by the global context of the edges, the pattern of fMRI activityin a subregion of V1 responsive to the centre of the pattern should notbe predictive of apparent depth. However, if perceived depth can bereliably predicted from activity in this region, this shows that con-textual influence occurs as early as V1.

Thus, to examine whether global context influences fMRI activity inV1 during binocular matching, here we use multi-voxel pattern analysis(MVPA) of BOLD activity to decode depth from regions of V1 receivingambiguous binocular input whilst perception is influenced by spatialcontext. We find some evidence that perceived depth can be decodedfrom regions of V1 that receive ambiguous depth information. Thissuggests a modulation of the local BOLD signal in V1 that is influencedby the global process of establishing binocular correspondence.

2. Materials and methods

2.1. Observers

Fifteen healthy observers from the University of Cambridge withnormal or corrected-to-normal vision participated in the fMRI experi-ment. The mean age was 26 yr (range=21–32 yr; 9 women, 5 men).Two participants’ data were excluded from the analysis because of ex-cessive head movements during scanning, which prevented voxel cor-respondence necessary for multi-voxel pattern analysis (MVPA).Excessive head movement was defined as ≥1mm displacement be-tween consecutive volumes or ≥3mm total displacement over thecourse of a 7min run. After runs that exceeded these thresholds wereexcluded, two participants had fewer than five remaining runs and sowere excluded entirely as there were insufficient data for MVPA.Participants were screened for stereoacuity (< 1° arcmin near/far dis-crimination threshold) and contraindications to MRI prior to the ex-periment. All experiments were conducted in accordance with theethical guidelines of the Declaration of Helsinki and were approved bythe University of Cambridge STEM and all participants provided in-formed consent.

2.2. Stimuli: main experiment

To assess whether global context alters local stereoscopic V1 ac-tivity, we ran two depth conditions: 1) an ambiguous “wallpaper”condition in which two stereoscopic matches are likely and the per-ceived depth of the stimulus is disambiguated by the background lu-minance of the pattern, and 2) a standard disparity condition in whichthe perceived depth of the stimulus is produced by introducing a po-sition shift between the patterns presented in the left and right eyes.Stimuli were full contrast greyscale stereograms of square-wave grat-ings, 4.8° wide and 4° high, surrounded by a 0.6° thick light-grey or

Fig. 1. Demonstrations of spatial contextual effects. a) Simultaneous brightnesscontrast, the perceived luminance of the disks is determined by the luminanceof the background. b) A Kanisza triangle, the ‘pacman’ disks induce illusoryluminance contours to complete the perceptually inferred triangle. c)Stereograms of the Wallpaper stimulus designed for cross-eyed fusion. Whenfusing the left and right eye images in the top pair, the reader should experienceand ambiguous perceptual interpretation that alternates between the centralregion appearing ‘near’ or ‘far’ relative to the surround. Changing the lumi-nance of the background from mid-grey to light grey (middle) or dark grey(bottom) changes the perceptual interpretation: the middle stimulus shouldlook ‘far’ while the bottom stimulus should appear ‘near’.

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dark-grey background (Fig. 3). The spatial period of the square-wavegrating was 1.2°, resulting in 8 segments in each pattern.

In the ambiguous depth condition, a 180° phase offset in the square-wave was introduced between stimuli presented in the left and righteye, producing a±36 arcmin binocular disparity when fused. The bi-nocular disparity was relatively large, as it is dependent on the spatialperiod of the grating, and this was required to be sufficiently large topermit effective localization of different regions of the pattern, i.e., thecentre and flankers. In the standard depth condition, the phase of thegratings was kept constant between the left and right eyes, while theposition of the gratings was shifted 18 arcmin horizontally in each eye,to produce an offset (i.e., either near or far) corresponding to thatproduced by matching the gratings in the ambiguous condition. (It isworth clarifying that in this standard depth condition, there is an un-ambiguous overall disparity, but, by design, the central portion of the

stimulus contains local information that could be matched in a tem-poral or a nasal direction for a neuron with a small receptive field. Thisis common to almost all binocular images containing self-similar ele-ments, and is conceptually similar to the motion aperture problem.) Theposition and size of the background in the standard depth condition wasadjusted so as to appear equivalent to that in the ambiguous condition.

Two stereogram gratings were presented on each trial, in the top-right and bottom-left quadrants of the screen, centred on the obliqueaxis, at a distance of 4.8° from the centre. In addition to the phase offsetbetween gratings presented to the left and right eye, the top and bottomgratings were offset by 180°. Thus, there were eight conditions: ambi-guity (ambiguous/standard)× background in the top/bottom (dark-light/light-dark)× phase in the top/bottom (0°-180°/180°-0°). Theseconditions were designed such that there were two possible depthconfigurations (near-far, far-near), equally balanced across conditions

Fig. 2. Illustration of contextual influence on binocular matching of an ambiguous ‘wallpaper’ image. The left and right eyes are presented with square-wavegratings, with a 180° phase offset. The images can be stereoscopically matched in two ways (i.e., nasal/temporal) with half-occlusions at the edges (oblique patterns:leftward tilt, viewed by left eye; rightward tilt, viewed by right eye). At the centre of the pattern (cyan rectangle) near vs. far matching solutions are equally likely,and thus ambiguous, as both preserve polarity contrast (solid circles). As shown in the (left-side) ambiguous example, if the luminance of the background is at themidpoint between the light and dark stripes of the pattern, this is also true for the edges, resulting in an ambiguous bistable (near/far) percept. However, as shown inthe (right-side) disambiguated example, if the background is darker (or lighter) than the midpoint, matching solutions produce outcomes of different perceptuallikelihood at the left and right edges of the pattern – while polarity contrast is preserved for the far solution, i.e., dark-light is matched with dark-light (solid circles),the near solution violates this rule, i.e., dark-dark is matched with dark-light (empty circles). In V1, receptive fields are relatively small and only sample from localregions of the pattern. While neurons with receptive fields positioned at the edges of the pattern receive a disambiguating signal, the majority of neurons (samplingfrom region within the cyan rectangle) receive ambiguous signal. Despite the disambiguating signals only featuring at the edges of the pattern, they are sufficient toproduce a reliable depth percept over its entire surface. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version ofthis article.)

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(that is, four of each). See Table 1 for a summary of the experimentalmanipulations across conditions. Stimuli were presented on a mid-greybackground, surrounded by a grid of black and white squares (75%density) designed to provide an unambiguous background reference.

2.3. Stimuli: checkerboard localizer

We localized regions of interest (ROIs) corresponding to the spatiallocation of the experimental stimulus for each participant in two se-parate runs. Subjects were presented with full contrast flickeringcheckerboard stimuli (10 Hz, black and white checks, checksize= 12×12 arcmin; Fig. 4). The localizer contained four types oftrials, corresponding to the locations of ROIs of the experimental sti-mulus: the central six segments (center) of the (1) left and (2) rightpatterns, (3) the two outer segments (flankers), and (4) the background.The contrast of the checkerboards decayed according to a cosinefunction over 12 arcmin from the edges. Stimuli were programmed andpresented in MATLAB (The MathWorks, Natick, MA) with Psycho-physics Toolbox extensions (Brainard, 1997; Pelli, 1997). Stereoscopicpresentation in the scanner was achieved using a “PROPixx” DLP LEDprojector (VPixx Technologies) with a refresh rate of 120 Hz and re-solution of 1920× 1080, operating in RB3D mode. The left and rightimages were separated by a fast-switching circular polarization mod-ulator in front of the projector lens (DepthQ; Lightspeed Design). Theonset of each orthogonal polarization was synchronized with the videorefresh, enabling interleaved rates of 60 Hz for each eye’s image. MR-safe circular polarization filter glasses were worn by subjects in thescanner to dissociate the left and right eye’s view of the image. Stimuliwere back-projected onto a polarization-preserving screen (StewartFilmscreen, model 150) inside the bore of the magnet and viewed via afront-surfaced mirror attached to the head coil and angled at 45° abovethe observers’ heads. This resulted in a viewing distance of 82 cm, fromwhich both wallpaper stimuli were visible within the binocular field ofview.

2.4. Vernier task

During both experimental and checkerboard localizer scans, parti-cipants performed an attentionally demanding Vernier task at fixation.Participants were instructed to fixate a central cross hair fixationmarker. The fixation marker consisted of a white square outline (sidelength 30 arcmin) and horizontal and vertical nonius lines (length 22arcmin). One horizontal and one vertical line were presented to eacheye in order to promote stable vergence and to provide a reference for aVernier task (Popple, Smallman, & Findlay, 1998). The vertical Verniertarget line (6.4× 2.1 arcmin) was presented at seven evenly spacedhorizontal offsets of between± 6.4 arcmin for 500ms (with rando-mized onset relative to stimulus) on 20% of TRs during experimentalscans and 50% during checkerboard localizer scans. During thecheckerboard localizer scans, participants were instructed to indicate,via button press, which (left/right) side of the upper vertical nonius linethe target appeared. The target was presented monocularly to the righteye. During the experimental scans, observers were instructed to in-dicate, by button press, whether the pattern on the same (left/right)side as the Vernier line was near or far, relative to the background. Forboth scan types the Vernier task served to maintain observers’ fixationon the central crosshair, while in the experimental scans it also served

Fig. 3. Illustration of the (top) entire stimulus as seen through one eye,(middle) ambiguous depth and (bottom) standard depth stimuli used in theexperiment; cross-fuse to observe depth.

Table 1Summary of experimental manipulations.

Condition number Ambiguous Background luminance in the top/bottom

Pattern phase shift in the top/bottom

Pattern position shift in the top/bottom

Perceived depth in the top/bottom

1 No Light, dark 0, 180 Crossed, uncrossed Near, far2 No Dark, light 180, 0 Crossed, uncrossed Near, far3 No Light, dark 180, 0 Uncrossed, crossed Far, near4 No Dark, light 0, 180 Uncrossed, crossed Far, near5 Yes Light, dark 0, 180 None Near, far6 Yes Dark, light 180, 0 None Near, far7 Yes Light, dark 180, 0 None Far, near8 Yes Dark, light 0, 180 None Far, near

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to provide a measure of the perceptual strength of depth.

2.5. Psychophysics

In a separate session, prior to being scanned, participants performeda single-interval two-alternative forced-choice discrimination task inwhich they were presented one of the four stimuli from the ambiguousdepth conditions, drawn pseudo-randomly. Their task was to indicate,via (up/down) button press, the location of the grating that appearednearer than the background. No duration restriction was enforced, butobservers were asked to respond as soon as they made a judgement.Observers completed 50 trials for each condition, for a total of 200trials. For each condition, responses were assigned either a 1 (up) or−1(down) and the average was taken to produce a measure of perfor-mance.

2.6. Imaging

Data were collected at the Cognition and Brain Sciences Unit with a3T Siemens Prisma MRI scanner with a 32-channel head coil. Bloodoxygen level-dependent (BOLD) fMRI data were acquired with a gra-dient echo-planar imaging (EPI) sequence [echo time (TE) 29ms; re-petition time (TR) 2000ms; voxel size 1.5×1.5×2mm, 30 slicescovering occipital cortex] for experimental and localizer scans. Sliceorientation was near to coronal section but rotated about the medio-lateral axis with the ventral edge of the volume more anterior in orderto ensure coverage of lateral occipital cortex (Fig. 5a). A T1-weightedanatomical scan (voxel size 1mm isotropic) was additionally acquiredfor each participant.

2.7. Retinotopy

In a separate session, we performed ROI localization for each par-ticipant using retinotopic and stimulus contrast mapping procedures(Fig. 5b); the details of which are reproduced from (Murphy, Ban, &Welchman, 2013). Retinotopically organized visual areas (V1, V2, V3v,V4, V3d, V3A, V3B/KO, and V7) were defined using polar and eccen-tricity maps, which were derived from fMRI responses to rotatingwedge and expanding concentric ring stimulus presentations, respec-tively (DeYoe et al., 1996; Sereno et al., 1995). Area V3 was separatedinto ventral and dorsal quadrants in each hemisphere (V3v/d) con-sistent with previous delineation based on functional and cytoarchi-tectonic differences (Wilms et al., 2010). V4 was defined as the ventralregion of visual cortex adjacent to V3v comprising a representation ofthe upper quadrant of the contralateral visual field (Tootell, 2001; Tyleret al., 2005). V7 was defined as the region of retinotopic activity dorsaland anterior to V3A (Tootell, 2001; Tsao et al., 2003; Tyler et al., 2005).V3B/KO (Tyler, Likova, Kontsevich, & Wade, 2006; Zeki, Perry, &Bartels, 2003) was defined as the area containing the union of re-tinotopically mapped V3B and the kinetic occipital region (KO), whichwas functionally localized by its preference for motion-definedboundaries compared with transparent motion of white and black dots(Dupont et al., 1997; Tootell, 2001; Tyler et al., 2006; Zeki et al., 2003).This area contained a full hemifield representation, inferior to V7 andlateral to, and sharing a foveal confluence with, V3A (Tyler et al.,2005). Lateral occipital complex (LOC) was defined as voxels in thelateral occipito-temporal cortex that preferred intact, compared withscrambled, images of objects (Kourtzi, Betts, Sarkheil, & Welchman,2005). LOC subregion LO was defined based on overlap of anatomical

Fig. 4. Illustration of the checkerboard stimuli used for functional localization of the (top) left and right centres, (bottom-left) flankers, and (bottom-right) back-ground, of the stimuli.

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structures and functional activations, in line with previous work (Grill-Spector, Kushnir, Hendler, & Malach, 2000).

2.8. fMRI design

In the fMRI experiment, runs consisted of 24 blocks (block length16 s) that began and ended with a 16 s fixation period during whichonly the background and fixation marker were presented. The mainexperimental blocks consisted of a stimulus from one of the eightconditions being presented for 1 s followed by a 1 s fixation period, thusstimuli were presented for a total of 8 s per 16 s block. The checker-board blocks were the same (24 blocks), except the stimulus was drawnfrom one of the four checkerboard conditions. Total block run lengthwas 7min 4 s. Block order was randomized, and each of the eight/fourconditions was presented for three blocks per run. Observers completeda total of nine runs: seven of the main experiment and two of thecheckerboard localizer (at the beginning and the end).

2.9. fMRI data analysis

For each participant, anatomical scans were transformed intoTalairach space (Jean & Tournoux, 1988), and inflated/flattened sur-faces were rendered with BrainVoyager QX (BrainInnovation, Maas-tricht, The Netherlands). Functional data were preprocessed with slicetiming correction, head motion correction, and high-pass filtering be-fore being aligned to the participant’s anatomical scan and transformedinto Talairach space. Global signal variance across each run was cal-culated and (2) runs with excessive variance (> 0.5) were removed.

2.10. ROI analysis

Within each condition, we tested the discriminability of BOLD re-sponses to the two different depth configurations (near-far vs. far-near).For example, for the standard disparity condition we compared theactivity of runs from conditions one and two and to three and four(Table 1). For each ROI we selected grey matter voxels and ranked themon the basis of their response (as indicated by t-values calculated withthe standard general linear model) to a contrast between the “centre”region localizer and fixation. Thus, voxel selection was based on dataindependent from the classification data and prioritized voxels re-sponding to the region of the stimulus that was perceived as near or far.Assessment of the point at which classification accuracies tended tosaturate as a function of pattern size resulted in the selection of 200voxels per ROI. This method of voxel selection has been validated by

previous studies (Kamitani & Tong, 2005; Preston, Li, Kourtzi, &Welchman, 2008).

To minimize baseline differences across runs we normalized eachvoxel time course for each experimental run (by calculating z scores).The multivariate analysis data vectors were produced by applying a 4 stemporal shift to the fMRI time series, which compensates for the lagtime of the hemodynamic response function, and then averaging alltime series data points of an experimental condition. We used a supportvector machine (SVM; SVMlight toolbox, http://svmlight.joachims.org)for classification and performed a sixfold leave-one-out cross-valida-tion, in which data from six runs were used as training patterns (24patterns, 4 per run for each configuration) and data from the remainingrun were used as test patterns (4 per run for each configuration). Foreach participant, the mean accuracy across cross-validations was taken.

Previous work has shown that depth can be accurately decodedfrom retinotopic areas in the primary visual cortex (Ban, Preston,Meeson, & Welchman, 2012; Preston et al., 2008). There were threesubjects for whom the average decoding accuracy across all retinotopicareas in the standard disparity condition was not significantly abovechance. Including data from subjects for whom standard disparitycannot be decoded reduces the interpretability of the results from theambiguous condition; thus, these subjects were omitted from the ana-lysis. For the remaining ten subjects, the average decoding accuracywas relatively high (63%), indicating that the (3) omitted subjects hadpoor data quality. We screened observers for discrimination of smalldisparities (> 1 arcmin), whereas the disparity used in the experimentwas relatively large (± 36 arcmin); thus, one explanation for the in-ability to decode depth in the standard condition for these three ob-servers is that they suffered from specific stereo deficits for large dis-parities (Van Ee & Richards, 2002), which we did not detect duringscreening, and could not perceive the depth of the stimuli. Alter-natively, observers may have had specific difficulty in perceiving thedepth of the stimuli as they were presented in the fMRI scanner.

2.11. SubROI analysis

Data from the checkerboard localizer scans was averaged over eachblock to define V1 ‘subROIs’. SubROIs were defined by contrasting eachV1 voxel’s response between checkerboard localizer conditions (as in-dicated by t-values calculated with the standard general linear model).For instance, in a contrast between the centre localizer and the flankerand background localizers, voxels with t-value larger than 2.0 wereconsidered “centre voxels”. A cluster correction was then used to re-move potentially spurious groups of< 25 voxels, and the remaining

Fig. 5. a) Sagittal view of an anatomical MRI scan of one participant; the yellow overlay illustrates the slice orientation of functional scans. b) Representative inflatedcortical surface reconstruction maps showing the visual regions of interest (V1, V2, V3v, V4, V3d, V3A, V3B/KO, V7, LO) from one participant. Gyri are rendered alighter grey than sulci. Superimposed on the maps are subregions of interest: green, centre; blue, flankers; red, frame. (For interpretation of the references to colour inthis figure legend, the reader is referred to the web version of this article.)

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http://svmlight.joachims.org

voxels were considered subROIs (Fig. 5b). This procedure resulted inthe selection of 85 voxels per subROI. For some subROIs in some sub-jects, 85 voxels were not available, in which case we used the maximumnumber of voxels available.

The same procedure was also used to define subROIs in V2 and V3.However, whereas the procedure yielded centre subROIs in V1 for allparticipants with over 80 voxels, in V2 the same subROI with over 80voxels was produced for only three participants. Similarity, no centresubROIs were found in V3 with more than 80 voxels. While foveal re-ceptive fields in V2 are relatively small, the stimuli were presentedparafoveally; this likely contributed to the meagre number of voxels inV2 (and V3) that we could label as receiving input from one section ofthe stimulus, e.g., the centre, but not the others, e.g., frame/flankers.Thus, due to the severely limited number of subROI voxels establishedin V2 and V3, we did not include them in the subROI analysis.

3. Results

3.1. Psychophysics

We measured the perceptual consistency of depth produced by thestimuli in the ambiguous condition for all participants. Specifically, wepresented each of the four (background×phase) stimuli and assessedthe frequency with which participants reported the same depth con-figuration (near-far or far-near). A score of one indicates the participantperceived a near-far configuration on all trials, a score of minus oneindicates they perceived a far-near configuration on all trials, and ascore of zero indicates they perceived it equally often in each config-uration. The ideal observer would always perceive the stimuli in amanner where binocular matches preserve contrast polarity (Fig. 6a).All participants showed the same pattern of “polarity preserving” re-sults, with varying degrees of consistency. For each condition, groupaverage performance was significantly different than zero (Fig. 6b).

3.2. fMRI

To assess information about the displayed stimulus contained in thefMRI response, we used a machine learning classifier to decode thestimulus from the brain activity. We did this across the multiple ROIswe had sampled, for both the ambiguous and standard stimuli (Fig. 7a).A repeated measures analysis of variance (ANOVA) revealed a maineffect of condition (Ambigous vs. standard depth; F1,9= 26.1,P=6.4e−4) but not ROI (F8,72= 1.2, P= .28). Consistent with pre-vious work (Ban et al., 2012; Preston et al., 2008), we were able todecode depth from (standard) binocular disparity across all of the

retinotopic areas we sampled (F1,9= 47.9, P=6.9e−5), with highestaccuracies found in visual area V3A (Fig. 7a). By contrast, when wetrained the classifier on fMRI activity evoked by ambiguous stimuli, wewere unable to decode depth reliably in any of the ROIs (F1,9= 0.001,P=0.97). A possible explanation for this is that the percept of depthwas less robust for ambiguous stimuli, evoking more variable fMRIresponses that provided a poor basis on which to train the machinelearning classifier. For instance, while the presence of some noise in thedata used to train a classifier can improve performance, by reducingoverfitting, too much noise will completely prevent the classifier fromlearning the categories (Elbir, Mishra, & Eldar, 2018). We thereforetested whether depth could be decoded for ambiguous stimuli when theclassifier had been trained on fMRI activity evoked by the standardstimuli and vice versa (Fig. 7b). As we expected, we found that we wereunable to reliably decode standard depth using a classifier trained onambiguous depth (F1,9= 3.5, P=0.20), supporting the interpretationthat the ambiguous stimuli provided a poorer training set than thestandard stimuli. Similarly, were we unable to decode ambiguous depthusing a classifier trained on activity evoked by the standard the depthstimuli (F1,9= 3.5, P=0.09).

The results of the dual Vernier-depth classification task support theinterpretation that the perceived depth of the ambiguous stimuli wasless clear/consistent than the unambiguous stimuli. That is, perfor-mance on the task was significantly better in the unambiguous condi-tions than in the ambiguous conditions (paired t-test: t9= 6.42,P= .0001). Indeed, performance in the ambiguous conditions was notsignificantly different from chance (t9= 0.21, P= .83). In the un-ambiguous condition, performance was relatively low (66%), but sig-nificantly better than chance (t9= 6.99, P=6.4e−5), and worse thanon the classic Vernier task performed in the localizer runs (t9= 3.51,P= .007), reflecting the difficulty of the dual task.

When we considered the aggregate activity of voxels within area V1,we found that we were unable to reliably decode depth from fMRIactivity evoked by ambiguous stimuli (Fig. 7). However, our particularinterest was to examine responses within subregions of the viewedstimuli. Thus, to test whether global context influences local stereo-scopic-related activity in V1 we used MVPA to decode fMRI activityfrom each of the subROIs corresponding to the centre, flankers, andbackground of the stimulus. If V1 activity is influenced by global con-text, we would expect to be able to decode depth from activity in theflankers and centre subROIs, but not the background. That is, thebackground should influence the perceived depth of the pattern, but notthe other way around.

We first tested whether we could reliably decode the depth ofstandard stimuli from the fMRI activity within the V1 subROIs. While

Fig. 6. Predicted ideal observer and actual results of psychophysical test of ambiguous wallpaper task. a) Predicted depth judgements in each of the four (back-ground× phase) conditions based on binocular matching that preserves contrast polarity. b) Average group performance across conditions. The consistency indexindicates the proportion of depth configuration judgements that were near-far: 1= 100%, 0= 50%, and −1=0%.

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the central region of the standard stimulus could also provide ambig-uous information to neurons with spatially-limited receptive fields,binocular matches are possible for all elements of the stereogram, i.e.,there is a single probable matching solution that is unaffected by theluminance of the background. Thus, while decoding activity evoked bystandard stimuli is not diagnostic of contextual influence, it provides asanity check that perceived depth can be decoded from the activity inthese subregions. We found that we could reliably decode depth fromall subROIs (centre, t9= 5.18, P=5.8e−4; flankers, t9= 4.21,P= .002; background, t9= 4.41, P= .002; Fig. 8a). This would appearto be contradictory of the previous prediction, i.e., activity from thebackground should be undiagnostic of depth; however, the subROI lo-calizers were designed for the ambiguous stimuli, where the position ofthe pattern is held constant. In contrast, we shifted the position of thestandard stimuli nasally and temporally to produce a binocular dis-parity, meaning that the areas contained by the background subROI

also contained partial flanker sections of these stimuli. These mono-cular cues, i.e., whether the pattern was shifted nasally or temporally,explain why we were still able to reliably decode the depth config-uration from activity within the background subROI.

We next tested whether we could decode the depth of the ambig-uous stimuli from the activity within V1 subROIs. Consistent with theretinotopic ROI analysis, we were unable to reliably decode depth ofambiguous stimuli from any of the subROIs using a classifier trained onthe ambiguous depth stimuli (Fig. 8a). We then tested for transfer be-tween the conditions by training the classifier on fMRI activity evokedby stimuli in one condition and testing on activity evoked by stimuli inthe other. Using a classifier trained on standard depth stimuli evokedactivity, we were able to reliably decode the depth of the ambiguousstimuli from activity in the centre subROI (t9= 2.58, P= .029; Fig. 8b).As the input to this subregion was ambiguous, i.e., information from thebackground/edges is needed to disambiguate the signal, the fact that

Fig. 7. Classifier decoding accuracy for discriminating far-near vs. near-far depth stimulus configurations, for all retinotopic regions of interest. Prediction per-formance is shown for (a) classifiers trained and tested on activity within ambiguity conditions and (b) classifiers trained on activity from one ambiguity conditionand tested on the other (transfer test). For (b), the legend labels refer to the condition that the classifiers were tested on. For all regions, we used performance basedon activity of 200 voxels. Error bars indicate s.e.m.

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depth can be reliably decoded from its activity shows that it is influ-enced by the global context of the stimulus, i.e., the edges/background.Consistent with the results from the ROI analysis and the interpretationthat the ambiguous dataset could not be used to train an effectiveclassifier, using a classifier trained on activity evoked by ambiguousstimuli, we were unable to reliably decode the depth of the standardstimuli using from activity from in the same (centre) subregion(t9= 1.63, P= .138).

While the decoding accuracy of the activity in the centre subROIthat suggests global context influences stereoscopic related activity inV1 was significantly above chance, it is worth noting that the sig-nificance of this difference does not survive Bonferroni correction forsix tests. However, in contrast with the ROI analysis, we had an a priorihypothesis regarding the results of the subROI analysis and designedthe experiment to test this hypothesis. As such, we did not apply a fa-milywise correction to the alpha values used for the pairwise tests in thesubROI analysis.

We were unable to decode depth from the flankers and background(Fig. 8b). As noted previously, to produce the percept of depth for thestandard stimuli the position of the pattern was shifted horizontallybetween left and right eyes, resulting in misalignment of the flankersand background relative to the subregion localizers. To decode the“depth” in the flanker and background subregions, the classifier couldrely on monocular cues, i.e., the relative position of the flankers to thebackground. By contrast, these monocular cues were not present in theambiguous stimuli, as the position of the pattern was held constant.Thus, it is likely that training did not transfer from standard to am-biguous stimuli in these subregions as the classifier could not use thesame monocular cues to decode fMRI activity from the ambiguous testset.

We designed the experiment such that the stimulus manipulationswere balanced across conditions. This allowed us to test the stimulusinformation that the classifier was capable of decoding from the fMRIactivity within each subregion. We carefully designed the localizers toonly include voxels whose activity was evoked by specific subregions ofthe ambiguous stimulus and contrasted between them to exclude sharedvoxels. However, a possible concern is that some of the voxels may havesampled information from the other subregions as a result of eyemovements. Thus, we tested from which subregions the (light/dark)luminance of the background could be reliably decoded. As expected,we found that background luminance could be reliably decoded fromthe background subROI (t9= 3.04, P= .014). Critically, we were notable to reliably decode the background luminance of the ambiguous

stimuli from the centre subROI using a classifier trained on either ac-tivity evoked from ambiguous (t9= 1.53, P= .16) or standard stimuli(t9= 1.03, P= .33). This shows that the capacity to decode depth from(ambiguous stimuli evoked) activity in the centre subregion was notdue to unintentional sampling from the background, but evidence thatstereoscopic-related activity in V1 is influenced by global context.

Another possible concern is that decoding accuracy may reflect eyemovements made in response to stimulus presentation. However, thisseems unlikely for two reasons. First, observers were required to per-form an attentionally demanding Vernier task, which required constantmonitoring of the fixation. Second, the depth of stimuli was balancedwithin presentations, i.e., each presentation consisted of a near and afar stimulus, thus there was no global difference in depth betweenconditions to promote one pattern of vergence eye movements overanother.

4. Discussion

The offset between an image projected onto the left and right re-tinae (binocular disparity) is sufficient to produce an estimate of depth.To compute this offset, it has long been understood that the visualsystem must first match the features of the image between the retinae(“solve the correspondence problem”). This problem is nontrivial, asthe number possible solutions rapidly increases with the number of to-be-matched elements. Classically, investigations of the correspondenceproblem in stereopsis have focused on the how local features facilitatematching. In contrast, with the exception of a few notable studies(Anderson & Nakayama, 1994; McKee, Verghese, Ma-Wyatt, & Petrov,2007), the role of global context has not been tested extensively.

To test whether global context influences the activity of V1 duringbinocular matching, here we used fMRI to measure observers’ brainactivity while viewing ambiguous stereograms, whose binocularmatching (producing the perception of either near or far depths) wasdetermined by the luminance of the background. Using multi-voxelpattern analysis (MVPA), we found that near vs. far depth could bereliably decoded from the activity in regions of V1 that only receiveambiguous information, indicating that the local activity of V1 is in-fluenced by global context.

While we were able to reliably decode depth from activity evokedby the centre subregion of the ambiguous stimulus using a classifiertrained on the standard depth stimuli, we were unable to decode depthusing a classifier trained on ambiguous stimuli. This is most probablyexplained by the ambiguous stimulus providing a less stable

Fig. 8. Classifier decoding accuracy for dis-criminating far-near vs. near-far depth sti-mulus configurations, for stimulus-relatedV1 subregions of interest. Prediction per-formance is shown for (a) classifiers trainedand tested on activity within ambiguityconditions and (b) classifiers trained on ac-tivity from one ambiguity condition andtested on the other (transfer test). For (b),the legend labels refer to the condition thatthe classifiers were trained on. For all re-gions, we used performance based on ac-tivity of 85 voxels. Error bars indicate s.e.m.Asterisks indicate areas where performanceis significantly above chance.

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interpretation of depth: while manipulating the background luminancebiases perceived depth, there remains some bistability in the percept.Thus, for some presentations of the ambiguous stimulus, observers mayhave perceived the opposite depth to that which the activity was la-belled, reducing the capacity of the SVM to learn a pattern of activityassociated with the label. Despite this, it is reassuring to find evidenceof transfer of decoding accuracy for a classifier trained on standarddepth signals and tested on ambiguous depth signals, as it indicates thatthe SVM is using (at least partially) shared stereoscopic-related brainactivity to classify the stimuli.

In the ROI analysis, consistent with previous work (Ban et al., 2012;Preston et al., 2008), for standard disparity-defined stimuli we find thatdepth can be reliably decoded from all retinotopically defined ROIs (V1,V2, V3d, V3A, V3B/KO V4, V7, & LO), with maximum decoding ac-curacy in V3A. By contrast, for ambiguous stimuli, we find that depthcannot be reliably decoded from any of the ROIs we tested.

The finding that V1 stereoscopic-related BOLD activity is influencedby context is consistent with previous neurophysiological work withmacaque showing contextual modulation in V1 for monocular features,i.e., figure-ground regions defined by texture (Rossi, Desimone, &Ungerleider, 2001; Zipser, Lamme, & Schiller, 1996). By contrast, theseresults seem at odds with neurophysiological work indicating the ac-tivity of disparity-selective V1 neurons does not reflect depth percep-tion (Cumming and Parker, 2000, 1997). However, for many neuronsthe activity produced by anti-correlated matches is attenuated com-pared to that produced by correlated matches (Cumming & Parker,1997). Thus, a possible mechanism of the global influence on V1 ac-tivity observed here may be through inhibitory feedback or lateralconnections, perhaps originating from a higher area involved in resol-ving perceptual ambiguity.

A limitation of the current study is that it cannot distinguish the twopossible mechanisms through which contextual influence in V1 is rea-lized, that is, lateral and feedback connections. Previous theoreticalmodelling (Friston, 2005; Mumford, 1992; Phillips, Clark, & Silverstein,2015) and fMRI work investigating other effects of spatial context invision (Kok & De Lange, 2014; Muckli et al., 2015) suggest that con-textual effects are facilitated by feedback, rather than lateral, connec-tions within the primary visual cortex; however, to resolve this ambi-guity for the effect of global context on stereoscopic activity, futureresearch could employ fMRI with higher spatial resolution to examineactivity at different laminar layers (Muckli et al., 2015).

In sum, here we provide evidence that the global context in ste-reoscopic matching can modulate the activity of binocular stimuli in theprimary visual cortex. These findings have implications for models ofstereopsis, which focus on local binocular matching, underscoring theimportance of considering both local and global stereoscopic activity, asearly as V1, in the computation of depth from binocular disparity.

Acknowledgements

This work was supported by the Leverhulme Trust (ECF-2017-573 toRR), the Isaac Newton Trust (17.08(o) to RR), and the Wellcome Trust(095183/Z/10/Z to AEW).

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Contextual effects on binocular matching are evident in primary visual cortexIntroductionMaterials and methodsObserversStimuli: main experimentStimuli: checkerboard localizerVernier taskPsychophysicsImagingRetinotopyfMRI designfMRI data analysisROI analysisSubROI analysis

ResultsPsychophysicsfMRI

DiscussionAcknowledgementsReferences