Right Parietal Brain Activity Precedes Perceptual Alternation During Binocular Rivalry

r Human Brain Mapping 32:1432–1442 (2011) r

Juliane Britz,1* Michael A. Pitts,2 and Christoph M. Michel2

1Department of Fundamental Neuroscience, University of Geneva, Geneva, Switzerland 2Department of Neurosciences, University of California, San Diego, California

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Abstract: We investigated perceptual reversals for intermittently presented stimuli during binocular rivalry and physical alternation while the ongoing EEG was recorded from 64 channels. EEG topographies immediately preceding stimulus-onset were analyzed and two topographies doubly dissociated perceptual reversals from non-reversals. The estimated intracranial generators associated with these topographies were stronger in right inferior parietal cortex and weaker bilaterally in the ventral stream before perceptual reversals. No such differences were found for physical alternation of the same stimuli. These results replicate and extend findings from a previous study with the Necker cube and suggest common neural mechanisms associated with perceptual reversals during binocular rivalry and ambiguous figure perception. For both types of multi-stable stimuli, the dorsal stream is more active preceding perceptual reversals. Activity in the ventral stream, however, differed for binocular rivalry compared to ambiguous figures. The results from the two studies suggest a causal role for the right inferior parietal cortex in generating perceptual reversals regardless of the type of multi-stable stimulus, while activity in the ventral stream appears to depend on the particular type of stimulus. Hum Brain Mapp 32:1432–1442, 2011. VC 2010 Wiley-Liss, Inc.

Key words: EEG; EEG mapping; binocular rivalry; inverse solution; LORETA; right inferior parietal

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INTRODUCTION every few seconds between the two rivaling percepts. Because these perceptual alternations happen spontane- Binocular rivalry arises when two dissimilar images are ously and randomly and without any changes in the phys- presented simultaneously to the two eyes. The resulting ical input, binocular rivalry and other forms of multi- percept is not a stable composite of the two competing stable perception such as bi-stable ambiguous figures are images, but perceptual awareness alternates stochastically powerful tools for dissociating perceptual awareness from sensory processing [Sterzer et al., 2009]. Both the mechanisms and timing of perceptual domi- Contract grant sponsor: National Institutes of Health; Contract nance/suppression remain a matter of debate. The effects grant numbers: 5 T32 MH20002, 2 R01 EY016984-35; Contract grant of binocular rivalry occur in many areas along the visual sponsor: The Swiss National Science Foundation; Contract grant number: 32003B-118315; Contract grant sponsors: The Center for stream. For example, functional imaging studies in Biomedical Imaging (CIBM) of the Geneva and Lausanne humans suggest that rivalry is already resolved at the ear- Universities, EPFL, The Leenaards and Louis-Jeantet foundations. liest stages of visual processing, namely the LGN and V1 *Correspondence to: Juliane Britz, Ph.D., Department of Funda- [Haynes et al., 2005; Lee et al., 2005; Polonsky et al., 2000; mental Neuroscience, Centre Me´dical Universitaire, 1 Rue Michel Wunderlich et al., 2005] and extrastriate areas [Haynes Servet, CH-1211 Gene`ve, Switzerland. and Rees, 2005; Meng et al., 2005; Tong et al., 1998]. On E-mail: [email protected] the other hand, electrophysiological studies in non-human Received for publication 18 May 2010; Accepted 5 June 2010 primates have failed to show the resolution of binocular DOI: 10.1002/hbm.21117 rivalry at these early stages; they found that local field Published online 5 August 2010 in Wiley Online Library potentials (LFPs) in extrastriate visual areas and in inferior (wileyonlinelibrary.com). temporal cortex reflect the currently active percept

VC 2010 Wiley-Liss, Inc. r State Dependent Alternations in Binocular Rivalry r

[Leopold and Logothetis, 1996; Logothetis et al., 1996; Log- topography of the scalp potential field remains stable for othetis and Schall, 1989; Sheinberg and Logothetis, 1997]. short periods of time (100 ms), presumably reflecting the In addition to visual areas, activity in frontal and parietal momentary mind state [Lehmann et al., 1993, 2010]. We areas is also modulated as a function of subjective visual have recently shown that these different topographies (so- awareness [Lumer et al., 1998; Lumer and Rees, 1999]. called microstates) correlate with some of the well-known Thus, many of the brain areas involved in binocular resting states, indicating that different networks might be rivalry have been identified, but much less is known about momentarily active when the stimulus is presented [Britz the exact timing underlying the suppression of a percept et al., 2010]. Since this activation pattern changes about ev- and the emergence of its rivaling counterpart. ery 100 ms, we assume that the momentary state just Recent ERP studies have begun to investigate the timing within the 100 ms around the stimulus is most crucial for of perceptual alternations during ambiguous figure per- determining the fate of the stimulus. Previous studies sup- ception [Britz et al., 2009; Kornmeier and Bach, 2004, 2005, port this hypothesis [Britz et al., 2009; Kondakor et al., 2006; Pitts et al., 2009]. These studies identified ERP com- 1995, 1997; Lehmann et al., 1998; Mohr et al., 2005]. ponents associated with perceptual reversals of a Necker We contrasted internally generated perceptual reversals cube (or Necker lattice) during intermittent presentation, during binocular rivalry with physical alternations of the which allows precise time-locking of the EEG with stimu- same stimuli when presented monocularly and according lus onsets. These reversal-related components occurred to our hypothesis, only the internally generated, but not during two time periods after stimulus onset: an occipital the physically driven perceptual alternations should mani- negativity at 250 ms (‘‘Reversal Negativity’’) and a parie- fest in different EEG topographies immediately before tal positivity at 340 ms (‘‘Late Positive Component’’). stimulus onset. Under both conditions, we assessed the Both of these components were also elicited by physical momentary topography of the pre-stimulus state and their reversals of an unambiguous lattice [Kornmeier and Bach, concomitant source differences by means of distributed 2004]. Although these ERP studies indicate rather late source localization procedures. Differences in topography effects that are similar for physical and endogenous alter- necessarily imply different generators [Helmholtz, 1853; nations, we recently demonstrated differences in electro- Vaughan, 1982], whereas the opposite is not necessarily cortical activity between reversal and non-reversal true: identical topographies can be generated by different perception immediately before stimulus onset [Britz et al., sources. Like all EEG and MEG source localization meth- 2009]. This dissociation of perceptual reversals from non- ods, the distributed inverse solutions are non-unique and reversals was evident in the global momentary brain state depend on the implemented constraints and regularization reflected by the EEG topography at the time of stimulus parameters of the source model. However, numerous stud- arrival. The sources of the concomitant generators of these ies provide compelling evidence that distributed linear EEG topographies differed in the right inferior parietal inverse solutions provide reasonable source estimates lobe, suggesting a role for the parietal cortex in initiating [Groening et al., 2009; James et al., 2009; Laganaro et al., in perceptual alternations. Although binocular rivalry and press; Michel et al., 2004; Murray et al., 2006; Schulz et al., ambiguous figure perception arise from different proc- 2008; Vulliemoz et al., 2009; Zumsteg et al., 2006]. esses—namely the suppression/dominance of two monoc- On the basis of previous findings for the Necker cube ular stimuli and the mutually exclusive interpretations of [Britz et al., 2009], we further hypothesized that spontane- the same ambiguous stimulus—they share a common phe- ous perceptual reversals for binocular rivalry would mani- nomenology, namely spontaneous alternations of percep- fest in increased activity in right inferior parietal cortex. tion despite constant sensory stimulation. It is thus Because this reversal-related activity is assumed to be possible that these internally generated alternations arise internally generated, we also predicted no such effects for from a common process that may be reflected by common the physical alternation of the same stimuli. pre-stimulus brain states that cause perceptual change. In the present study, we used Electrical Neuroimaging [Michel et al., 2009; Murray et al., 2008] to investigate METHODS spontaneous perceptual alternations in binocular rivalry Subjects using an intermittent stimulus presentation [Kornmeier and Bach, 2004]. We hypothesized that perceptual alterna- Fourteen healthy adults (8 female, mean age 20 years, tions in binocular rivalry are generated internally and range 18–23) participated in the two experiments (binocu- spontaneously and that the momentary state of the brain lar rivalry and physical alternation) on separate days; the should determine the fate of the incoming rivaling stimu- order of experiments was counterbalanced across subjects. lus. The EEG topography, that is, the configuration of the One subject was excluded from the analyses due to sub- scalp potential field is a direct measure of the momentary stantial contamination by artifacts, and the data of 13 sub- global state of the brain. It reflects the spatial summation jects were submitted to subsequent analyses. All had of all concurrently active intracranial electrical sources normal or corrected-to normal visual acuity and no history irrespective of their frequency that can be measured at the of psychiatric or neurological impairments. All partici- surface of the scalp. Several studies have shown that the pants were recruited as volunteers and gave informed

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Figure 1. Stimuli and task. (a) Binocular rivalry procedure. Subjects viewed monocular pairs of Gabor gratings orthogonal in color, orientation, and spatial frequency and indicated the color of their percepts via button-presses. (b) Physical alternation procedure. Subjects viewed successions of one stimulus of a pair while again reporting the color of their percepts. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] consent prior to each experiment. The experimental proce- allows the separate stimulation of the left and right eyes. dures were approved by the University of California at Participants adjusted the angle of the mirrors to achieve San Diego Institutional Review Board. stereo fusion. To help maintain fusion, a fixation cross (1) was presented in the center of a gray/white circle (0.75). Stimuli and Procedure All stimuli were presented at fixation. Figure 1 illustrates the stimuli and experimental procedure. We first titrated the optimal durations for both the stim- In the binocular rivalry experiment, stimuli were pre- ulus presentation and the blank intervals in a behavioral sented as pairs, one to each eye. They were square-shaped pilot study such that in each trial, only one of the rivaling sinusoidal gratings subtending 6 of visual angle in diame- images could be clearly perceived and that no reversals ter. To minimize piece-meal rivalry, the pairs were orthog- occurred during the presentation. This was based in part onal on three dimensions: color (red vs. green), orientation on evidence from behavioral studies showing that dichop- (45 vs. 135), and spatial frequency (1 cpd vs. 5 cpd). tic orthogonal gratings fuse into ‘‘plaids’’ when presented Including the factor eye (left vs. right), this yielded eight for less than 150 ms [Wolfe, 1983] on the one hand and different pairs of stimuli. Each pair was equated in lumi- that the extension of the inter-stimulus interval to several nance (by chromatic photometry) and was presented in six seconds prevents perceptual reversals altogether [Leopold non-consecutive blocks of trials (counterbalanced across et al., 2002; Sterzer and Rees, 2008]. blocks), yielding 48 blocks. During each block, stimuli Stimuli were presented on a black background and cen- were presented 50 times (1 min), and subjects took self- tered horizontally within the left and right halves of a paced breaks between blocks. All stimuli were presented CRT computer screen with a refresh rate of 60 Hz. Subjects intermittently for 600 ms, and the inter-stimulus interval viewed the stimuli through a mirror-stereoscope which varied randomly between 500 and 700 ms.

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For each stimulus, participants were asked to indicate the We evaluated the autocorrelation function of the rever- color of their percept by means of a button press. They were sal intervals by correlating the reversal duration in trial n instructed to withhold their response in the case that they with that in trial n þ m with m ¼ 1:10. We assessed the perceived a piece-meal mixture between the two stimuli. distribution of these durations by computing the Maxi- In the physical alternation experiment, only one stimu- mum Likelihood Estimates of the parameters from the lus of a pair was presented to one eye, and the input to cumulative probability distribution both of the scale and the other eye was kept blank. The two stimuli of a pair shape parameters (a and b) of the gamma distribution and were presented in alternation at rates that mimicked the mean and standard deviation (l and r) of the lognormal switching rates under binocular rivalry with random alter- distribution. We used a Kolmogorov-Smirnov test to assess nations every 1.2–6.0 s. To equate the response-task these distributions. between the rivalry and physical alternation conditions, We further evaluated whether the stable and reversal subjects were again asked to indicate the color of their per- trials differed systematically with respect to piece-meal cept after each stimulus presentation. percepts in the preceding trial.

EEG Acquisition and Raw Data Processing Analysis of Pre-Stimulus Global EEG States The EEG was recorded from 64 tin electrodes mounted in The momentary scalp topography of the EEG reflects all an elastic cap (Electrocap International), band-pass filtered concurrently active sources of the brain irrespective of between 0.1 and 80 Hz continuously digitized at 250 Hz and their frequency [Lehmann et al., 1987]. The topography of amplified with a battery-powered amplifier (SA Instrumen- the scalp potential field remains quasi-stable for short peri- tation) with a gain of 10,000. Impedances were kept below 5 ods (80–120 ms) during which only its strength, but not kX, and the EEG was referenced online to the right mastoid. its configuration vary [Koenig et al., 2002; Lehmann et al., Horizontal and vertical eye movements were monitored 2009]. These periods of stability have been termed ‘‘func- with a bilateral external canthus montage and a sub-orbital tional microstates’’ [Lehmann and Skrandies, 1980] which electrode referenced to the right mastoid; offline the EEG have been found to influence both perception [Britz et al., was re-computed to the common average reference. 2009] and cognition [Mohr et al., 2005] and to characterize The analysis was performed using the Cartool software the nature of spontaneous thoughts [Lehmann et al., 1998]. by Denis Brunet (http://brainmapping.unige.ch/Cartool. The latter of these studies found that the behavioral htm). Before selecting the relevant EEG epochs, we first response could only be related to the microstate immedi- removed the DC component and then band-pass filtered ately prior to the stimulus onset (in that case, an auditory the raw EEG between 1 and 30 Hz. A 2nd order Butter- prompt), which is why subsequent studies focused only worth filter with a 12 db/octave roll-off was used. The on the microstate immediately before stimulus onset. A filter was computed linearly with two passes (one forward measure of field strength is the global field power (GFP), and one backward), eliminating the phase shift, and with which is equivalent to the spatial standard deviation of poles calculated each time to the desired cut-off frequency. the potential field [Lehmann and Skrandies, 1980], and This was done using epochs spanning 500 to þ500 ms consequently, the maximum of the GFP is the best repre- around the selected epoch. sentative of a momentary microstate in terms of signal-to- For each stimulus, we determined whether perception noise-ratio. As the average duration of a microstate is alternated (reversed) or remained the same (stable) by com- about 100 ms and the arrival of a stimulus does not ‘‘dis- paring the current response with the response to the preced- rupt’’ a momentary microstate, we reasoned that the GFP ing stimulus. The EEG was then segmented into epochs maximum in the 50 ms before the onset is the best repre- ranging from 50 ms before until stimulus onset. Epochs con- sentative of the microstate immediately before the stimu- taminated by oculomotor and other artifacts were rejected. lus onset. We thus extracted the map representing the momentary scalp topography of the GFP maximum in the Analysis of Behavioral Data and Statistical 50 ms before stimulus onset that was temporally closest to Properties of the Reversal Intervals the stimulus onset as the representative of the pre-stimulus microstate in each trial [Britz et al., 2009; Kondakor We computed the average and median durations for the et al., 1995, 1997; Lehmann et al., 1994; Mohr et al., 2005]. reversal intervals and the reaction times. We then assessed We used a spatial cluster analysis to identify the most the statistical properties of the reversal intervals by means dominant EEG microstates [Michel et al., 2004; Pascual- of their autocorrelation function and by means of their dis- Marqui et al., 1995]. An Atomize-Agglomerate Hierarchical tribution. The reversal intervals of binocular rivalry do not Clustering (AAHC) method was used [Britz et al., 2009; show short-term intercorrelations [Lehky, 1995; Mamassian Murray et al., 2008]. The cluster analysis yields templates and Goutcher, 2005] and can be approximated by gamma of the most dominant topographies that represent the [Leopold and Logothetis, 1999] and lognormal [Lehky, microstates. The optimal number of clusters, that is, the 1995] functions. best solution of the cluster analysis was determined by

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between the template maps and all extracted maps and matched (i.e., labeled) each GFP peak with the template map it best corresponded with. On the basis of measures of frequency of occurrence and global explained variance, we determined the two maps that best differentiated the Rever- sal and Stable conditions within each subject. In a second step, we identified those maps that best differentiate the Reversal and Stable conditions across subjects. We concurrently submitted all those maps identified in the first step to a second AAHC cluster analysis and determined its best solution by means of the cross-validation criterion. We then computed the spatial correlation between the templates of the best solution and all maps submitted to the 2nd cluster analysis. We finally determined which maps best differentiated the Reversal and Stable conditions across subjects by statistically comparing their frequency of occurrence and global explained variance between the two conditions.

Analysis of Pre-Stimulus Source Differences

We extracted the maps that best differentiated the Rever- sal and Stable condition across subjects (i.e., that were identified in the 2nd cluster analysis) from each individual and estimated their intracranial current distributions with a LOR- ETA inverse solution. LORETA was calculated in a simpli- fied realistic head model called SMAC [Spinelli et al., 2000]: The average template brain of the Montreal Neurological Institute (MNI) was used as standard brain for all subjects. The brain surface was extracted from this MRI and the best fitting sphere was estimated. Then the MRI was warped according to the ratio of the sphere radius and the real surface radius. Three thousand five solution points were then defined in regular distances within the gray matter of this standard brain. The forward problem was then solved with Figure 2. an analytical solution with a 3-layer conductor model. Addi- Statistical properties of the reversal intervals. (a) Autocorrela- tional details can be found in Michel et al. [2004]. The sim- tion function of the reversal intervals for the lags 1–10. The y- plified realistic head model offers an easy and fast extraction axis shows the correlation coefficients for the respective lags. of the head model and a fast and accurate analytical solution (b) Histogram and probability density function of the reversal to the forward problem at the expense of being maybe intervals. The dashed line represents the fitted lognormal func- somewhat less precise than finite element models based on tion and the dotted line the fitted gamma function. the individual anatomy. Nevertheless, accurate source localization using this head model has been demonstrated in different clinical and experimental studies in the past means of the cross-validation criterion [Pascual-Marqui [Groening et al., 2009; Michel et al., 2004; Phillips et al., et al., 1995]. The cross-validation criterion is a measure of 2005; Sperli et al., 2006; Vulliemoz et al., 2009]. predictive residual variance. The minimum of the cross We used conservative statistical analyses to investigate validation criterion is considered as the optimal number of differences between the source estimations of the two condi- clusters, that is, the number of clusters for which the resid- tions, which helps to eliminate spurious sources of activity. ual variance is minimal. The template maps of these clus- Equivalent to statistical parametric mapping in fMRI, we ters correspond to the mean of all maps belonging to this assessed their statistical difference by means of paired t tests cluster. We made no a priori assumptions on the number between the Reversal and Stable conditions at each solution of clusters or on the minimum of explained variance, points. The P values were adjusted for multiple testing with because we wanted our analysis to be strictly data driven. the Sidak correction [Sidak, 1967]. We used the number of In a first step, we identified those maps, that is, the scalp electrodes (n ¼ 63) as the independent measure because in topography representing the momentary microstate, that EEG source imaging the electrodes on the scalp constitute best differentiate the Reversal and Stable conditions within the independent measures, not the solution points [Grave de each subject. We then computed a spatial correlation Peralta Menendez et al., 2004; Michel et al., 2004].

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Figure 3. Templates of the pre-stimulus microstates identified by the cluster isk indicates statistically significant differences. (c)Thet values for analysis. The two maps that doubly dissociated the two conditions the statistical comparison of the Frequency of Occurrence in the are labeled. (a)Thet values for the statistical comparison of the Reversal and Stable condition for each map in the physical alterna- Frequency of Occurrence in the Reversal and Stable condition for tion experiment. (d)Thet values for the statistical comparison of each map in the rivalry experiment. The asterisk indicates statisti- the Global Explained Variance in the Reversal and Stable condition cally significant differences. (b)Thet values for the statistical com- in the physical alternation experiment. [Color figure can be viewed parison of the Global Explained Variance in the Reversal and in the online issue, which is available at wileyonlinelibrary.com.] Stable condition for each map in the rivalry experiment. The aster-

RESULTS and 2,448 ms, respectively, and a standard deviation of 2,080 ms. The mean reaction time was 529 ms, and reac- Behavioral Results and Statistical Properties tions were performed on average 609 ms before the onset of the Reversal Intervals of the next stimulus. The autocorrelation function of the After artifact rejection, an average of 1,030 reversal and reversal intervals (Fig. 2a) shows that there were no corre- 1,238 stable trials were obtained for each subject, yielding lations between the reversal intervals in a trial n and those a total of 13,394 reversal and 16,095 stable trials. The rever- of the subsequent 10 reversals. Figure 2b,c show the Prob- sal intervals had a mean and median duration of 3,052 ability Density Function and Cumulative Probability

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tial correlation between the 11 templates and all maps and statistically compared their frequency of occurrence. Two maps doubly dissociated the Reversal and Stable conditions both in terms of Frequency of Occurrence and Global Explained Variance (Reversal: Frequency of Occurrence: t¼ 2.35, P ¼ 0.047, GEV: t ¼ 2.4, P ¼ 0.034; Stable: Fre- quency of Occurrence: t ¼ 2.69, P ¼ 0.012, GEV: t ¼ 2.98, P ¼ 0.012). To make sure that these maps could be identi- ﬁed in all subjects, we determined their global presence by means of the variance they explained in each subject (Fig. 4). Both maps could be identiﬁed in each subject, and they explained 38% and 34.21% of the variance. Physical alternation experiment

In the first step, we again identified those maps that best differentiate the Reversal and Stable conditions within each subject. The AAHC cluster analysis identified on average 6.69 (1.03) template maps as the optimal solution Figure 4. which explained on average 69.23% (7.05%) of the Global Global presence of the template maps. Bars indicate the per- Variance. Again, we identified those two maps that differ- centage of Global Explained Variance of the Reversal (light gray) entiated the Reversal and Stable conditions in each subject and Stable (dark gray) map in each individual subject. [Color fig- based on their frequency of occurrence. ure can be viewed in the online issue, which is available at In the 2nd step, we determined which maps differentiate wileyonlinelibrary.com.] the two conditions across subjects. We retained the maps determined in the first step and submitted them to a 2nd Function, respectively. A Kolmogorov-Smirnov test AAHC cluster analysis. The cross validation criterion iden- revealed that the reversal intervals followed both a gamma tified six maps as the optimal solution. These six maps a ¼ b ¼ ¼ l ¼ ( 2.73, 1.065, P 0) and a lognormal ( 2917.68, explained 67.45% of the variance (Fig. 3c,d). We computed r ¼ ¼ 2086.01, P 0) distribution. again a strength-independent spatial correlation between In the Stable condition, 1.3% ( 1.7%) of trials were pre- the six templates and all maps and statistically compared ceded by piece-meal percepts, and in the Reversal condi- their frequency of occurrence. We did not identify any tion, 1.8% (1.8%) of trials were preceded by piece-meal map that could significantly dissociate the two conditions. percepts. This difference was not significant (t < 1). Pre-Stimulus Source Differences Pre-Stimulus EEG Microstates Binocular rivalry experiment Binocular rivalry experiment We computed distributed LORETA inverse solutions for In the first step, we identified those maps that best differen- the two pre-stimulus EEG maps that doubly dissociated tiate the Reversal and Stable conditions within each subject. the Reversal and Stable conditions and compared the sta- The cross-validation criterion in the AAHC cluster analysis tistical differences of their intracranial generators across identified on average 6.3 (1.6) template maps as the optimal subjects by paired t tests at each solution point (Fig. 5). solution which explained on average 68.02% (7.24%) of the Positive differences, that is, increased activations before Global Variance. We computed a strength-independent spa- Reversals were found in the Right Inferior Parietal Lobule tial correlation between the templates and all maps and thus (Talairach coordinates of the maximum: 50 50 45, t ¼ identified the two maps that best differentiated the Reversal 3.95, P ¼ 0.006). Negative differences, that is, decreased andStableconditionsineachsubjectbasedontheirfrequency activations before Reversals were found bilaterally in the of occurrence, that is, we retained the one map that occurred ventral stream the Middle Occipital Gyrus (left: 43 74 most frequently in the Reversal and the one that occurred 3, t ¼3.02, P ¼ 0.02; right: 43 68 8; t ¼ 4.37, P ¼ most frequently in the Stable condition. 0.004), left Fusiform Gyrus (42 45 13, t ¼3.73, P ¼ In the second step, we determined which maps best dif- 0.008); and the Middle and Inferior Temporal Gyri. Activa- ferentiate the Reversal and Stable conditions across sub- tion foci are summarized in Table I. jects. We retained the maps identified in the first step and submitted them to a 2nd AAHC cluster analysis. The cross DISCUSSION validation criterion identified 11 maps as the optimal solution (Fig. 3a,b). These 11 maps explained 75.29% of the We investigated pre-stimulus brain states associated variance. We computed again a strength-independent spa- with perceptual reversals during binocular rivalry by

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in bilateral lateral occipital and temporal areas preceding perceptual reversals These findings replicate and extend our previous findings for reversals of the Necker cube [Britz et al., 2009], in which we likewise identified two pre-stimulus scalp topographies that doubly dissociated perceptual reversals from perceptual stability. Also, the concomitant intracranial generators differed in virtually the same area in the right inferior parietal lobe preceding reversals of the Necker cube and reversals during rivalry. As temporal precedence provides evidence for a putative causal role, these results provide strong evidence for the idea that this area plays a central role in the initiation of perceptual reversals irrespective of whether the reversals are between different perceptual interpretations of an ambiguous figure or between competing monocular stimuli. This finding sheds new light on the differential role of top–down influence in ambiguous figure perception and binocular rivalry. Previous research suggests that binocular rivalry is less susceptible to top–down modulation than ambiguous figure perception [Meng and Tong, 2004]: subjects can more easily control their perception of ambiguous figures than of binocularly rivaling stimuli when instructed to do so. We did not manipulate volitional control over perceptual reversals in our two studies, so our results are not directly comparable to those of Meng and Tong. What we can state from the results in the present and our previous study is that the spontaneous reversals of both ambiguous figures and during binocular rivalry recruit the same higher level and non-visual brain areas immediately preceding reversals. The temporal order of activity suggests that those higher level areas become active before primary sensory areas which could be interpreted as top–down influence. The right inferior parietal lobe has been consistently identified in fMRI studies using bi-stable ambiguous stimuli [Inui et al., 2000; Kleinschmidt et al., 1998; Slotnick and Yantis, 2005] and binocular rivalry [Lumer et al., 1998; Lumer and Rees, 1999; Wilcke et al., 2009], but its function had been interpreted as an ap- praisal of the altered percept rather than its cause. This Figure 5. area has been found to be involved in change detection Pre-stimulus map sources and source differences. (a) LORETA and change blindness [Beck et al., 2001, 2006; Kim and source estimation for the Reversal template map. (b) LORETA Blake, 2005; Pessoa and Ungerleider, 2004]. Other studies source estimation for Stable template map. (c) Statistical para- have found that this same area is important for reorienting metric maps (P values on the top and t values on the bottom) attention [Corbetta, 1998; Corbetta et al., 2000, 2008]. It depicting significant differences for the LORETA source estima- appears that activity in this area biases an altered percep- tions depicted in a and b. Orange–red colors indicate stronger tion of the incoming stimulus, possibly by reorienting current densities in the Reversal condition and blue–violet col- attention. Because of the slow time-course of the hemody- ors indicate stronger differences in the Stable condition. namic response function, the temporal and functional implications of fMRI activations remain a challenge. With the precise temporal resolution of Electrical Neuroimaging, we found that this region was activated immediately prior using an intermittent stimulus presentation approach. Two to reversals, which suggests that its role may be causal. pre-stimulus EEG topographies that doubly dissociate per- Further evidence for a causal role of right inferior parietal ceptual reversals from non-reversals were identified. Sta- cortex for perceptual reversals comes from a study in tistical parametric mapping of their estimated intracranial which repetitive Transcranial Magnetic Stimulation (rTMS) current densities revealed increased current density in the over right, but not left, inferior parietal cortex decreased right inferior parietal lobe and decreased current density perceptual reversals of the continuous wagon wheel

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TABLE I. Foci of statistical differences in current density this intermittent presentation might not yield ‘‘natural’’ re- of the pre-stimulus EEG maps in the reversal versal conditions. However, the intermittent presentation and stable conditions of bi-stable ambiguous stimuli elicits reversal rates similar to continuous stimulus presentation [Britz et al., 2009; xyz t PKornmeier et al., 2007]. Our analyses of the statistical properties of the reversal intervals, namely their autocorre- Positive difference lation function and their distribution show that our sub- Right Inferior Parietal Lobe 50 50 45 3.95 0.006 Negative differences jects showed the same behavior as under continuous Left Middle Occipital Gyrus 43 74 3 3.025 0.02 stimulus presentation: the reversal intervals have virtually Right Middle Occipital Gyrus 43 68 8 4.38 0.004 the same duration, they occur randomly, i.e. without a Left Fusiform Gyrus 42 45 13 3.73 0.008 clear periodicity and they follow a gamma and lognormal Left Middle Temporal Gyrus 74 55 1 2.88 0.024 function. Right Middle Temporal Gyrus 43 68 8 4.38 0.004 Eye movements—or rather retinal image shifts—have Left Inferior Temporal Gyrus 48 50 13 3.54 0.001 been shown to cause perceptual alternations during binoc- Right Inferior Temporal Gyrus 45 6 31 2.944 0.022 ular rivalry during continuous stimulus presentation: saccades occurred 500–100 ms prior to button presses indicating perceptual reversals [van Dam and van Ee, illusion [VanRullen et al., 2008]. Also, our current findings 2006]. However, to our knowledge, eye movements have confirmed that this right parietal activation is associated never been shown to induce perceptual reversals during with endogenously driven but not exogenously driven per- an intermittent stimulus presentation. We did not monitor ceptual switches. We found no differences in pre-stimulus eye movements in our study, so we can not completely scalp topography for the physical alternation of the same rule out that they induced the perceptual reversals, but we stimuli. are rather sure that our intermittent stimulus presentation The role of non-sensory brain areas in the initiation of precluded saccades as the cause of perceptual reversals. perceptual alternations has been described in both lesion Given the timing between saccades and button presses on and fMRI studies [Sterzer and Kleinschmidt, 2007; Wind- one hand and the timing of our intermittently presented mann et al., 2006]. They suggest a role of bilateral prefron- stimuli on the other hand, saccades that might have tal areas in the control over multi-stable perception. occurred while the stimuli were on the screen—which lead Patients with pre-frontal lesions show normal spontaneous to retinal image shifts—would have caused perceptual reversal rates for ambiguous figures, but they can not vol- reversals in the time window when the screen was blank. untarily generate perceptual reversals [Windmann et al., Saccades during the blank interval—which leave the reti- 2006]. Likewise, the temporal precedence of activity in nal image unaltered—could not have caused perceptual non-visual areas (right inferior frontal cortex) over that in reversals. visual areas suggests a causal role of the former in initiat- An alternative explanation of our pre-stimulus findings ing perceptual reversals [Sterzer and Kleinschmidt, 2007]. might be that they represent post-response effects rather In a previous study using an intermittent presentation of than pre-reversal effects. However, this explanation is an ambiguous figure [Britz et al., 2009] we found bilateral rather unlikely because subjects reported their percept in prefrontal activity in the retention interval preceding both every trial, such that every stimulus is both followed and reversal and stable trials, however, it was not modulated preceded by a motor response. Moreover, reactions were differently for perceptual reversals. In the present study, performed on average 609 ms before each stimulus, that we found no specific activation of the prefrontal cortex in is, well before the time window we analyzed. the time period immediately preceding perceptual reversals. Conclusions The present finding also extends the findings from our previous study. In addition to increased parietal activity Although perceptual alternations elicited during binocu- preceding reversals, we found increased activity in bilat- lar rivalry and bi-stable ambiguous figures may seem to eral lateral occipital and inferior temporal areas preceding arise from fundamentally different processes, that is, non-reversals. Single-cell recordings from awake behaving mutually exclusive interpretations of an ambiguous stimu- monkeys showed that discharge rates in extrastriate visual lus versus suppression/dominance of one of two monocu- and inferior temporal areas reflect the reported percept lar images, the current study suggests that the neural during continuous stimulus presentation [Leopold and events preceding perceptual reversals may be similar. Both Logothetis, 1996; Logothetis and Schall, 1989; Sheinberg types of reversals occur randomly and are generated inter- and Logothetis, 1997]. nally, and both can be related to the momentary state of To our knowledge, this is the first EEG study that has the brain at the moment of stimulus arrival. For both the used an intermittent instead of a continuous stimulus pre- Necker cube and binocular rivalry increased activity in the sentation during binocular rivalry and has focused on per- right inferior parietal lobe precedes perceptual reversals ceptual reversals vs. non-reversals. One could argue that which supports the notion that it is causal for the

r 1440 r r State Dependent Alternations in Binocular Rivalry r generation of these reversals. No such common mecha- James C, Morand S, Barcellona-Lehmann S, Michel CM, Schnider nism was identified when the percept remains stable; per- A (2009): Neural transition from short- to long-term memory ceptual stability appears to depend on the kind of stimuli, and the medial temporal lobe: A human evoked-potential whereas perceptual reversals are generated by the same study. Hippocampus 19:371–378. mechanism irrespective of the physical nature of the Kim C-Y, Blake R (2005): Psychophysical magic: Rendering the visible invisible. Trends Cogn Sci 9:381–388. stimuli. Kleinschmidt A, Bu¨ chel C, Zeki S, Frackowiak RS (1998): Human brain activity during spontaneously reversing perception of am- ACKNOWLEDGMENTS biguous figures. Proc R Soc Lond Ser B: Biol Sci 265:2427–2427. Koenig T, Prichep L, Lehmann D, Sosa PV, Braeker E, Kleinlogel The Cartool software (http://brainmapping.unige.ch/ H, Isenhart R, John ER (2002): Millisecond by Millisecond, Cartool.htm) has been programed by Denis Brunet from Year by Year: Normative EEG microstates and developmental the Functional Brain Mapping Laboratory, Geneva, stages. Neuroimage 16:41–48. Switzerland. Kondakor I, Pascual-Marqui RD, Michel CM, Lehmann D (1995): Event-related potential map differences depend on the prestimulus microstates. J Med Eng Technol 19:66–69. REFERENCES Kondakor I, Lehmann D, Michel CM, Brandeis D, Kochi K, Koe- nig T (1997): Prestimulus EEG microstates influence visual Beck DM, Rees G, Frith CD, Lavie N (2001): Neural correlates of event-related potential microstates in field maps with 47 chan- change detection and change blindness. Nat Neurosci 4: nels. J Neural Transm V104:161–173. 645–650. Kornmeier J, Bach M (2004): Early neural activity in Necker-cube Beck DM, Muggleton N, Walsh V, Lavie N (2006): Right parietal reversal: Evidence for low-level processing of a gestalt phe- cortex plays a critical role in change blindness. Cereb Cortex nomenon. Psychophysiology 41:1–8. 16:712–717. Kornmeier J, Bach M (2005): The Necker cube—An ambiguous figure Britz J, Landis T, Michel CM (2009): Right parietal brain activity disambiguated in early visual processing. Vision Res 45:955–960. precedes perceptual alternation of bistable stimuli. Cereb Cor- Kornmeier J, Bach M (2006): Bistable perception—Along the proc- tex 19:55–65. essing chain from ambiguous visual input to a stable percept. Int J Psychophysiol 62:345–349. Britz J, Van De Ville D, Michel CM: BOLD correlates of EEG to- Kornmeier J, Ehm W, Bigalke H, Bach M (2007): Discontinuous pography reveal rapid resting-state network dynamics. Neuro- presentation of ambiguous figures: How interstimulus-interval image 52:1162–1170. durations affect reversal dynamics and ERPs. Psychophysiol- Corbetta M (1998): Frontoparietal cortical networks for directing ogy 44:552–560. attention and the eye to visual locations: Identical, independ- Laganaro M, Morand S, Michel CM, Spinelli L, Schnider A: ERP ent, or overlapping neural systems? Proc Natl Acad Sci USA correlates of word production before and after stroke in an 95:831–838. aphasic patient. J Cognit Neurosci, in press. Corbetta M, Kincade JM, Ollinger JM, McAvoy MP, Shulman GL Lee SH, Blake R, Heeger DJ (2005): Traveling waves of activity in (2000): Voluntary orienting is dissociated from target detection primary visual cortex during binocular rivalry. Nat Neurosci in human posterior parietal cortex. Nat Neurosci 3:292–297. 8:22–23. Corbetta M, Patel G, Shulman GL (2008): The reorienting system Lehky S (1995): Binocular rivalry is not chaotic. Proc R Soc Lond of the human brain: From environment to theory of mind. Ser B: Biol Sci 259:71–76. Neuron 58:306–324. Lehmann D, Ozaki H, Pal I (1987): EEG alpha map series: Brain Grave de Peralta Menendez R, Murray MM, Michel CM, Martuzzi micro-states by space-oriented adaptive segmentation. Electro- R, Gonzalez Andino SL (2004): Electrical neuroimaging based encephalogr Clin Neurophysiol 67:271–288. on biophysical constraints. Neuroimage 21:527–539. Lehmann D, Wackermann J, Michel CM, Koenig T (1993): Space- Groening K, Brodbeck V, Moeller F, Wolff S, van Baalen A, Michel oriented EEG segmentation reveals changes in brain electric CM, Jansen O, Boor R, Wiegand G, Stephani U (2009): Combi- field maps under the influence of a nootropic drug. Psychiatry nation of EEG-fMRI and EEG source analysis improves inter- Res 50:275–282. pretation of spike-associated activation networks in paediatric Lehmann D, Michel CM, Pal I, Pascual-Marqui RD (1994): Event- pharmacoresistant focal epilepsies. Neuroimage 46:827–833. related potential maps depend on prestimulus brain electric Haynes J-D, Rees G (2005): Predicting the stream of consciousness microstate map. Int J Neurosci 74:239–248. from activity in human visual cortex. Curr Biol 15:1301–1307. Lehmann D, Strik WK, Henggeler B, Koenig T, Koukkou M (1998): Haynes JD, Deichmann R, Rees G (2005): Eye-specific effects of Brain electric microstates and momentary conscious mind states binocular rivalry in the human lateral geniculate nucleus. as building blocks of spontaneous thinking: I. Visual imagery Nature 438:496–499. and abstract thoughts. Int J Psychophysiol 29:1–11. Helmholtz HLF (1853): U¨ ber einige Gesetze der Vertheilung elek- Lehmann D, Pascual-Marqui RD, Michel CM (2009): EEG micro- trischer Stro¨me in ko¨rperlichen Leitern mit Anwendung auf states. Scholarpedia 4:7632. die thierisch-elektrischen Versuche. Annalen der Physik und Lehmann D, Pascual-Marqui RD, Strik WK, Koenig T (2010): Core Chemie 9:221–233. networks for visual-concrete and abstract thought content: A Inui T, Tanaka S, Okada T, Nishizawa S, Katayama M, Konishi J brain electric microstate analysis. Neuroimage 49:1073–1079. (2000): Neural substrates for depth perception of the Necker Lehmann D, Skrandies W (1980): Reference-free identification of cube: A functional magnetic resonance imaging study in components of checkerboard-evoked multichannel potential human subjects. Neurosci Lett 282:145–148. fields. Electroencephalogr Clin Neurophysiol 48:609–621.

r 1441 r r Britz et al. r

Leopold DA, Logothetis NK (1996): Activity changes in early vis- tence reading in children with dyslexia: Combined fMRI and ual cortex reflect monkeys’ percepts during binocular rivalry. ERP evidence. Neuroimage 41:153–168. Nature 379:549–553. Sheinberg DL, Logothetis NK (1997): The role of temporal cortical Leopold DA, Logothetis NK (1999): Multistable phenomena: areas in perceptual organization. Proc Natl Acad Sci 94: Changing views in perception. Trends Cogn Sci 3:254–264. 3408–3413. Leopold DA, Wilke M, Maier A, Logothetis NK (2002): Stable per- Sidak Z (1967): Rectangular confidence region for the means of ception of visually ambiguous patterns. Nat Neurosci 5:605– multivariate normal distributions. J Am Stat Assoc 62:626–633. 609. Slotnick SD, Yantis S (2005): Common neural substrates for the Logothetis NK, Leopold DA, Sheinberg DL (1996): What is rival- control and effects of visual attention and perceptual bistabil- ling during binocular rivalry? Nature 380:621–624. ity. Cogn Brain Res 24:97–108. Logothetis NK, Schall JD (1989): Neuronal correlates of subjective Sperli F, Spinelli L, Seeck M, Kurian M, Michel CM, Lantz G visual perception. Science 245:761–763. (2006): EEG source imaging in pediatric epilepsy surgery: A Lumer ED, Friston KJ, Rees G (1998): Neural correlates of percep- new perspective in presurgical workup. Epilepsia 47:981–990. tual rivalry in the human brain. Science 280:1930–1934. Spinelli L, Gonzalez Andino S, Lantz G, Seeck M, Michel CM Lumer ED, Rees G (1999): Covariation of activity in visual and (2000): Electromagnetic inverse solutions in anatomically con- prefrontal cortex associated with subjective visual perception. strained spherical head models. Brain Topogr 13:115–125. Proc Natl Acad Sci USA 96:1669–1673. Sterzer P, Kleinschmidt A (2007): A neural basis for inference in Mamassian P, Goutcher R (2005): Temporal dynamics in bistable perceptual ambiguity. Proc Natl Acad Sci USA 104:323–328. perception. J Vis 5:361–375. Sterzer P, Kleinschmidt A, Rees G (2009): The neural bases of Meng M, Remus DA, Tong F (2005): Filling-in of visual phantoms multistable perception. Trends Cogn Sci 13:310–318. in the human brain. Nat Neurosci 8:1248–1254. Sterzer P, Rees G (2008): A neural basis for percept stabilization in Meng M, Tong F (2004): Can attention selectively bias bistable binocular rivalry. J Cognit Neurosci 20:389–399. perception? Differences between binocular rivalry and ambigu- Tong F, Nakayama K, Vaughan JT, Kanwisher N (1998): Binocular ous figures. J Vis 4:539–551. rivalry and visual awareness in human extrastriate cortex. Michel CM, Murray MM, Lantz G, Gonzalez S, Spinelli L, Grave Neuron 21:753–759. de Peralta R (2004): EEG source imaging. Clin Neurophysiol van Dam LCJ, van Ee R (2006): Retinal image shifts, but not eye 115:2195–2222. movements per se, cause alternations in awareness during bin- Michel CM, Koenig T, Brandeis D, Gianotti L, Wackermann J ocular rivalry. J Vis 6:1172–1179. (2009): Electrical Neuroimaging. Cambridge: Cambridge Uni- VanRullen R, Pascual-Leone A, Battelli L (2008): The continuous versity Press. Wagon wheel illusion and the ‘‘When’’ pathway of the right Mohr C, Michel CM, Lantz G, Ortigue S, Viaud-Delmon I, Landis parietal lobe: A repetitive transcranial magnetic stimulation T (2005): Brain state-dependent functional hemispheric special- study. PLoS ONE 3:e2911. ization in men but not in women. Cereb Cortex 15:1451–1458. Vaughan HGJ (1982): The neural origins of human event-related Murray MM, Camen C, Gonzalez Andino SL, Bovet P, Clarke S potentials. Ann N Y Acad Sci 388:125–138. (2006): Rapid brain discrimination of sounds of objects. J Neu- Vulliemoz S, Thornton R, Rodionov R, Carmichael DW, Guye M, rosci 26:1293–1302. Lhatoo S, McEvoy AW, Spinelli L, Michel CM, Duncan JS Murray MM, Brunet D, Michel CM (2008): Topographic ERP anal- (2009): The spatio-temporal mapping of epileptic networks: yses: A step-by-step tutorial review. Brain Topogr 20:249–264. Combination of EEG-fMRI and EEG source imaging. Neuro- Pascual-Marqui RD, Michel CM, Lehmann D (1995): Segmentation image 46:834–843. of brain electrical activity into microstates: Model estimation Wilcke JC, O’Shea RP, Watts R (2009): Frontoparietal activity and and validation. IEEE Trans Biomed Eng 42:658–665. its structural connectivity in binocular rivalry. Brain Res Pessoa L, Ungerleider LG (2004): Neural correlates of change 1305:96–107. detection and change blindness in a working memory task. Windmann S, Wehrmann M, Calabrese P, Gu¨ ntu¨ rku¨ n O (2006): Cereb Cortex 14:511–520. Role of the prefrontal cortex in attentional control over bistable Phillips C, Mattout J, Rugg MD, Maquet P, Friston KJ (2005): An vision. J Cognit Neurosci 18:456–471. empirical Bayesian solution to the source reconstruction prob- Wolfe JM (1983): Influence of spatial frequency, luminance, and lem in EEG. Neuroimage 24:997–1011. duration on binocular rivalry and abnormal fusion of briefly Pitts MA, Martinez A, Stalmaster C, Nerger JL, Hillyard SA presented dichoptic stimuli. Perception 12:447–456. (2009): Neural generators of ERPs linked with Necker cube Wunderlich K, Schneider KA, Kastner S (2005): Neural correlates reversals. Psychophysiology 46:694–702. of binocular rivalry in the human lateral geniculate nucleus. Polonsky A, Blake R, Braun J, Heeger DJ (2000): Neuronal activity Nat Neurosci 8:1595–1602. in human primary visual cortex correlates with perception Zumsteg D, Friedman A, Wieser HG, Wennberg RA (2006): Propa- during binocular rivalry. Nat Neurosci 3:1153–1159. gation of interictal discharges in temporal lobe epilepsy: Corre- Schulz E, Maurer U, van der Mark S, Bucher K, Brem S, Martin E, lation of spatiotemporal mapping with intracranial foramen Brandeis D (2008): Impaired semantic processing during sen- ovale electrode recordings. Clin Neurophysiol 117:2615–2626.

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