Increasing the accuracy of electromagnetic inverses using functional area source correlation constraints

Estimating neural activity from visual areas using functionally defined EEG templates

Electroencephalography (EEG) is a common and inexpensive method to record neural activity in humans. However, it lacks spatial resolution making it difficult to determine which areas of the brain are responsible for the observed EEG response. Here we present a new easy-to-use method that relies on EEG topographical templates. Using MRI and fMRI scans of 50 participants, we simulated how the activity in each visual area appears on the scalp and averaged this signal to produce functionally defined EEG templates. Once created, these templates can be used to estimate how much each visual area contributes to the observed EEG activity. We tested this method on extensive simulations and on real data. The proposed procedure is as good as bespoke individual source localization methods, robust to a wide range of factors, and has several strengths. First, because it does not rely on individual brain scans, it is inexpensive and can be used on any EEG data set, past or present. Second, the results are readily interpretable in terms of functional brain regions and can be compared across neuroimaging techniques. Finally, this method is easy to understand, simple to use and expandable to other brain sources.

Neural correlates of intra-saccadic motion perception

Retinal motion of the visual scene is not consciously perceived during ocular saccades in normal everyday conditions. It has been suggested that extra-retinal signals actively suppress intra-saccadic motion perception to preserve stable perception of the visual world. However, using stimuli optimized to preferentially activate the M-pathway, Castet and Masson (2000) demonstrated that motion can be perceived during a saccade. Based on this psychophysical paradigm, we used electroencephalography and eye-tracking recordings to investigate the neural correlates related to the conscious perception of intra-saccadic motion. We demonstrated the effective involvement during saccades of the cortical areas V1-V2 and MT-V5, which convey motion information along the M-pathway. We also showed that individual motion perception was related to retinal temporal frequency.

EEGSourceSim: A framework for realistic simulation of EEG scalp data using MRI-based forward models and biologically plausible signals and noise

BACKGROUND

Electroencephalography (EEG) is widely used to investigate human brain function. Simulation studies are essential for assessing the validity of EEG analysis methods and the interpretability of results.

NEW METHOD

Here we present a simulation environment for generating EEG data by embedding biologically plausible signal and noise into MRI-based forward models that incorporate individual-subject variability in structure and function.

RESULTS

The package includes pipelines for the evaluation and validation of EEG analysis tools for source estimation, functional connectivity, and spatial filtering. EEG dynamics can be simulated using realistic noise and signal models with user specifiable signal-to-noise ratio (SNR). We also provide a set of quantitative metrics tailored to source estimation, connectivity and spatial filtering applications.

COMPARISON WITH EXISTING METHOD(S)

We provide a larger set of forward solutions for individual MRI-based head models than has been available previously. These head models are surface-based and include two sets of regions-of-interest (ROIs) that have been brought into registration with the brain of each individual using surface-based alignment - one from a whole brain and the other from a visual cortex atlas. We derive a realistic model of noise by fitting different model components to measured resting state EEG. We also provide a set of quantitative metrics for evaluating source-localization, functional connectivity and spatial filtering methods.

CONCLUSIONS

The inclusion of a larger number of individual head-models, combined with surface-atlas based labeling of ROIs and plausible models of signal and noise, allows for simulation of EEG data with greater realism than previous packages.

Parallel attentional facilitation of features and objects in early visual cortex

Selective attention can enhance the processing of attended features across the entire visual field. Attention also spreads within objects, enhancing all internal locations and task-irrelevant features of selected objects. Here, we examine the extent to which attentional enhancement of a feature spreads across attended and unattended objects. Two fully overlapping counter-rotating bicolored surfaces of light and dark random dots were presented on a gray background of intermediate luminance. This stimulus creates a percept of two separate semitransparent surfaces and allows the measurement of feature- and object-based selections while controlling spatial attention. On each trial, human participants attended to a subset of dots defined by feature (luminance polarity) and object (surface) in order to detect brief episodes of radial motion while ignoring any events in the unattended groups of dots. Attentional selection was assessed by means of steady-state visual evoked potentials (SSVEPs) and behavioral measures. SSVEP amplitudes recorded at medial occipital electrode sites were modulated both by surface-based and luminance polarity-based selection in a manner consistent with independent multiplicative enhancement of attentional effects in different dimensions in early visual cortex. This finding supports the view that feature-based attention spreads across object boundaries, at least at an early stage of processing. However, SSVEPs elicited at more lateral electrode sites showed a hierarchical pattern of selection, potentially reflecting the binding of surface-defining features with luminance features to enable surface-based attention.

Dynamics of perceptual decisions about symmetry in visual cortex

Neuroimaging studies have identified multiple extra-striate visual areas that are sensitive to symmetry in planar images (Kohler et al., 2016; Sasaki et al., 2005). Here, we investigated which of these areas are directly involved in perceptual decisions about symmetry, by recording high-density EEG in participants (n = 25) who made rapid judgments about whether an exemplar image contained rotation symmetry or not. Stimulus-locked sensor-level analysis revealed symmetry-specific activity that increased with increasing order of rotation symmetry. Response-locked analysis identified activity occurring between 600 and 200 ms before the button-press, that was directly related to perceptual decision making. We then used fMRI-informed EEG source imaging to characterize the dynamics of symmetry-specific activity within an extended network of areas in visual cortex. The most consistent cortical source of the stimulus-locked activity was VO1, a topographically organized area in ventral visual cortex, that was highly sensitive to symmetry in a previous study (Kohler et al., 2016). Importantly, VO1 activity also contained a strong decision-related component, suggesting that this area plays a crucial role in perceptual decisions about symmetry. Other candidate areas, such as lateral occipital cortex, had weak stimulus-locked symmetry responses and no evidence of correlation with response timing.

Functional connectivity analysis in EEG source space: The choice of method

Functional connectivity (FC) is among the most informative features derived from EEG. However, the most straightforward sensor-space analysis of FC is unreliable owing to volume conductance effects. An alternative-source-space analysis of FC-is optimal for high- and mid-density EEG (hdEEG, mdEEG); however, it is questionable for widely used low-density EEG (ldEEG) because of inadequate surface sampling. Here, using simulations, we investigate the performance of the two source FC methods, the inverse-based source FC (ISFC) and the cortical partial coherence (CPC). To examine the effects of localization errors of the inverse method on the FC estimation, we simulated an oscillatory source with varying locations and SNRs. To compare the FC estimations by the two methods, we simulated two synchronized sources with varying between-source distance and SNR. The simulations were implemented for hdEEG, mdEEG, and ldEEG. We showed that the performance of both methods deteriorates for deep sources owing to their inaccurate localization and smoothing. The accuracy of both methods improves with the increasing between-source distance. The best ISFC performance was achieved using hd/mdEEG, while the best CPC performance was observed with ldEEG. In conclusion, with hdEEG, ISFC outperforms CPC and therefore should be the preferred method. In the studies based on ldEEG, the CPC is a method of choice.

Sparse EEG/MEG source estimation via a group lasso

Non-invasive recordings of human brain activity through electroencephalography (EEG) or magnetoencelphalography (MEG) are of value for both basic science and clinical applications in sensory, cognitive, and affective neuroscience. Here we introduce a new approach to estimating the intra-cranial sources of EEG/MEG activity measured from extra-cranial sensors. The approach is based on the group lasso, a sparse-prior inverse that has been adapted to take advantage of functionally-defined regions of interest for the definition of physiologically meaningful groups within a functionally-based common space. Detailed simulations using realistic source-geometries and data from a human Visual Evoked Potential experiment demonstrate that the group-lasso method has improved performance over traditional ℓ2 minimum-norm methods. In addition, we show that pooling source estimates across subjects over functionally defined regions of interest results in improvements in the accuracy of source estimates for both the group-lasso and minimum-norm approaches.

Degraded attentional modulation of cortical neural populations in strabismic amblyopia

Behavioral studies have reported reduced spatial attention in amblyopia, a developmental disorder of spatial vision. However, the neural populations in the visual cortex linked with these behavioral spatial attention deficits have not been identified. Here, we use functional MRI–informed electroencephalography source imaging to measure the effect of attention on neural population activity in the visual cortex of human adult strabismic amblyopes who were stereoblind. We show that compared with controls, the modulatory effects of selective visual attention on the input from the amblyopic eye are substantially reduced in the primary visual cortex (V1) as well as in extrastriate visual areas hV4 and hMT+. Degraded attentional modulation is also found in the normal-acuity fellow eye in areas hV4 and hMT+ but not in V1. These results provide electrophysiological evidence that abnormal binocular input during a developmental critical period may impact cortical connections between the visual cortex and higher level cortices beyond the known amblyopic losses in V1 and V2, suggesting that a deficit of attentional modulation in the visual cortex is an important component of the functional impairment in amblyopia. Furthermore, we find that degraded attentional modulation in V1 is correlated with the magnitude of interocular suppression and the depth of amblyopia. These results support the view that the visual suppression often seen in strabismic amblyopia might be a form of attentional neglect of the visual input to the amblyopic eye.

Representation of Maximally Regular Textures in Human Visual Cortex

Naturalistic textures with an intermediate degree of statistical regularity can capture key structural features of natural images (Freeman and Simoncelli, 2011). V2 and later visual areas are sensitive to these features, while primary visual cortex is not (Freeman et al., 2013). Here we expand on this work by investigating a class of textures that have maximal formal regularity, the 17 crystallographic wallpaper groups (Fedorov, 1891). We used texture stimuli from four of the groups that differ in the maximum order of rotation symmetry they contain, and measured neural responses in human participants using functional MRI and high-density EEG. We found that cortical area V3 has a parametric representation of the rotation symmetries in the textures that is not present in either V1 or V2, the first discovery of a stimulus property that differentiates processing in V3 from that of lower-level areas. Parametric responses were also seen in higher-order ventral stream areas V4, VO1, and lateral occipital complex (LOC), but not in dorsal stream areas. The parametric response pattern was replicated in the EEG data, and source localization indicated that responses in V3 and V4 lead responses in LOC, which is consistent with a feedforward mechanism. Finally, we presented our stimuli to four well developed feedforward models and found that none of them were able to account for our results. Our results highlight structural regularity as an important stimulus dimension for distinguishing the early stages of visual processing, and suggest a previously unrecognized role for V3 in the visual form-processing hierarchy. Significance statement: Hierarchical processing is a fundamental organizing principle in visual neuroscience, with each successive processing stage being sensitive to increasingly complex stimulus properties. Here, we probe the encoding hierarchy in human visual cortex using a class of visual textures--wallpaper patterns--that are maximally regular. Through a combination of fMRI and EEG source imaging, we find specific responses to texture regularity that depend parametrically on the maximum order of rotation symmetry in the textures. These parametric responses are seen in several areas of the ventral visual processing stream, as well as in area V3, but not in V1 or V2. This is the first demonstration of a stimulus property that differentiates processing in V3 from that of lower-level visual areas.

From evoked potentials to cortical currents: Resolving V1 and V2 components using retinotopy constrained source estimation without fMRI

Despite evoked potentials' (EP) ubiquity in research and clinical medicine, insights are limited to gross brain dynamics as it remains challenging to map surface potentials to their sources in specific cortical regions. Multiple sources cancellation due to cortical folding and cross-talk obscures close sources, e.g. between visual areas V1 and V2. Recently retinotopic functional magnetic resonance imaging (fMRI) responses were used to constrain source locations to assist separating close sources and to determine cortical current generators. However, an fMRI is largely infeasible for routine EP investigation. We developed a novel method that replaces the fMRI derived retinotopic layout (RL) by an approach where the retinotopy and current estimates are generated from EEG or MEG signals and a standard clinical T1-weighted anatomical MRI. Using the EEG-RL, sources were localized to within 2 mm of the fMRI-RL constrained localized sources. The EEG-RL also produced V1 and V2 current waveforms that closely matched the fMRI-RL's (n = 2) r(1,198)  = 0.99, P < 0.0001. Applying the method to subjects without fMRI (n = 4) demonstrates it generates waveforms that agree closely with the literature. Our advance allows investigators with their current EEG or MEG systems to create a library of brain models tuned to individual subjects' cortical folding in retinotopic maps, and should be applicable to auditory and somatosensory maps. The novel method developed expands EP's ability to study specific brain areas, revitalizing this well-worn technique. Hum Brain Mapp 37:1696-1709, 2016. © 2016 Wiley Periodicals, Inc.

The steady-state visual evoked potential in vision research: A review

Periodic visual stimulation and analysis of the resulting steady-state visual evoked potentials were first introduced over 80 years ago as a means to study visual sensation and perception. From the first single-channel recording of responses to modulated light to the present use of sophisticated digital displays composed of complex visual stimuli and high-density recording arrays, steady-state methods have been applied in a broad range of scientific and applied settings.The purpose of this article is to describe the fundamental stimulation paradigms for steady-state visual evoked potentials and to illustrate these principles through research findings across a range of applications in vision science.

How to use fMRI functional localizers to improve EEG/MEG source estimation

EEG and MEG have excellent temporal resolution, but the estimation of the neural sources that generate the signals recorded by the sensors is a difficult, ill-posed problem. The high spatial resolution of functional MRI makes it an ideal tool to improve the localization of the EEG/MEG sources using data fusion. However, the combination of the two techniques remains challenging, as the neural generators of the EEG/MEG and BOLD signals might in some cases be very different. Here we describe a data fusion approach that was developed by our team over the last decade in which fMRI is used to provide source constraints that are based on functional areas defined individually for each subject. This mini-review describes the different steps that are necessary to perform source estimation using this approach. It also provides a list of pitfalls that should be avoided when doing fMRI-informed EEG/MEG source imaging. Finally, it describes the advantages of using a ROI-based approach for group-level analysis and for the study of sensory systems.

Localization of MEG human brain responses to retinotopic visual stimuli with contrasting source reconstruction approaches

Magnetoencephalography (MEG) allows the physiological recording of human brain activity at high temporal resolution. However, spatial localization of the source of the MEG signal is an ill-posed problem as the signal alone cannot constrain a unique solution and additional prior assumptions must be enforced. An adequate source reconstruction method for investigating the human visual system should place the sources of early visual activity in known locations in the occipital cortex. We localized sources of retinotopic MEG signals from the human brain with contrasting reconstruction approaches (minimum norm, multiple sparse priors, and beamformer) and compared these to the visual retinotopic map obtained with fMRI in the same individuals. When reconstructing brain responses to visual stimuli that differed by angular position, we found reliable localization to the appropriate retinotopic visual field quadrant by a minimum norm approach and by beamforming. Retinotopic map eccentricity in accordance with the fMRI map could not consistently be localized using an annular stimulus with any reconstruction method, but confining eccentricity stimuli to one visual field quadrant resulted in significant improvement with the minimum norm. These results inform the application of source analysis approaches for future MEG studies of the visual system, and indicate some current limits on localization accuracy of MEG signals.

The evolution of a disparity decision in human visual cortex

We used fMRI-informed EEG source-imaging in humans to characterize the dynamics of cortical responses during a disparity-discrimination task. After the onset of a disparity-defined target, decision-related activity was found within an extended cortical network that included several occipital regions of interest (ROIs): V4, V3A, hMT+ and the Lateral Occipital Complex (LOC). By using a response-locked analysis, we were able to determine the timing relationships in this network of ROIs relative to the subject's behavioral response. Choice-related activity appeared first in the V4 ROI almost 200 ms before the button press and then subsequently in the V3A ROI. Modeling of the responses in the V4 ROI suggests that this area provides an early contribution to disparity discrimination. Choice-related responses were also found after the button-press in ROIs V4, V3A, LOC and hMT+. Outside the visual cortex, choice-related activity was found in the frontal and temporal poles before the button-press. By combining the spatial resolution of fMRI-informed EEG source imaging with the ability to sort out neural activity occurring before, during and after the behavioral manifestation of the decision, our study is the first to assign distinct functional roles to the extra-striate ROIs involved in perceptual decisions based on disparity, the primary cue for depth.

Dynamics and cortical distribution of neural responses to 2D and 3D motion in human

The perception of motion-in-depth is important for avoiding collisions and for the control of vergence eye-movements and other motor actions. Previous psychophysical studies have suggested that sensitivity to motion-in-depth has a lower temporal processing limit than the perception of lateral motion. The present study used functional MRI-informed EEG source-imaging to study the spatiotemporal properties of the responses to lateral motion and motion-in-depth in human visual cortex. Lateral motion and motion-in-depth displays comprised stimuli whose only difference was interocular phase: monocular oscillatory motion was either in-phase in the two eyes (lateral motion) or in antiphase (motion-in-depth). Spectral analysis was used to break the steady-state visually evoked potentials responses down into even and odd harmonic components within five functionally defined regions of interest: V1, V4, lateral occipital complex, V3A, and hMT+. We also characterized the responses within two anatomically defined regions: the inferior and superior parietal cortex. Even harmonic components dominated the evoked responses and were a factor of approximately two larger for lateral motion than motion-in-depth. These responses were slower for motion-in-depth and were largely independent of absolute disparity. In each of our regions of interest, responses at odd-harmonics were relatively small, but were larger for motion-in-depth than lateral motion, especially in parietal cortex, and depended on absolute disparity. Taken together, our results suggest a plausible neural basis for reduced psychophysical sensitivity to rapid motion-in-depth.

Optimization of retinotopy constrained source estimation constrained by prior

Studying how the timing and amplitude of visual evoked responses (VERs) vary between visual areas is important for understanding visual processing but is complicated by difficulties in reliably estimating VERs in individual visual areas using noninvasive brain measurements. Retinotopy constrained source estimation (RCSE) addresses this challenge by using multiple, retinotopically mapped stimulus locations to simultaneously constrain estimates of VERs in visual areas V1, V2, and V3, taking advantage of the spatial precision of fMRI retinotopy and the temporal resolution of magnetoencephalography (MEG) or electroencephalography (EEG). Nonlinear optimization of dipole locations, guided by a group-constrained RCSE solution as a prior, improved the robustness of RCSE. This approach facilitated the analysis of differences in timing and amplitude of VERs between V1, V2, and V3, elicited by stimuli with varying luminance contrast in a sample of eight adult humans. The V1 peak response was 37% larger than that of V2 and 74% larger than that of V3, and also ~10-20 ms earlier. Normalized contrast response functions were nearly identical for the three areas. Results without dipole optimization, or with other nonlinear methods not constrained by prior estimates were similar but suffered from greater between-subject variability. The increased reliability of estimates offered by this approach may be particularly valuable when using a smaller number of stimulus locations, enabling a greater variety of stimulus and task manipulations.

The selectivity of task-dependent attention varies with surrounding context

Attention is thought to operate by enhancing the target of interest and suppressing the surroundings. We hypothesized that the spatial profile of attention depends on the surround's relationship to the target. Using high-density electroencephalographic measurements, we examined the spatial profile of attention to a grating target surrounded by an annular grating that was either coextensive with the target (unsegmented) or appeared segmented from it due to a gap or phase offset. We directly probed the spread of attention from the central target into the surround by flickering the surround and monitoring frequency-tagged steady-state visual-evoked potentials. Observers were required to detect a contrast increment that occurred only on the target. Successful detection of the increment required selecting the target and suppressing the surround, particularly when the target did not readily segment from the surround. The profile of attention was investigated in five visual regions of interest (ROIs) (V1, V4, V3A, lateral occipital complex, and human middle temporal area), mapped in a separate anatomical magnetic resonance imaging scan. We found that in most ROIs, attention to the target generated smaller responses from the surrounding annulus when it was contiguous compared with when it was clearly segmented. This result shows that the profile of attention depends on task demands and on surrounding context; attention is tightly focused when the target region needs to be isolated but loosely focused when the target region is clearly segmented.

The time course of shape discrimination in the human brain

The lateral occipital cortex (LOC) activates selectively to images of intact objects versus scrambled controls, is selective for the figure-ground relationship of a scene, and exhibits at least some degree of invariance for size and position. Because of these attributes, it is considered to be a crucial part of the object recognition pathway. Here we show that human LOC is critically involved in perceptual decisions about object shape. High-density EEG was recorded while subjects performed a threshold-level shape discrimination task on texture-defined figures segmented by either phase or orientation cues. The appearance or disappearance of a figure region from a uniform background generated robust visual evoked potentials throughout retinotopic cortex as determined by inverse modeling of the scalp voltage distribution. Contrasting responses from trials containing shape changes that were correctly detected (hits) with trials in which no change occurred (correct rejects) revealed stimulus-locked, target-selective activity in the occipital visual areas LOC and V4 preceding the subject's response. Activity that was locked to the subjects' reaction time was present in the LOC. Response-locked activity in the LOC was determined to be related to shape discrimination for several reasons: shape-selective responses were silenced when subjects viewed identical stimuli but their attention was directed away from the shapes to a demanding letter discrimination task; shape-selectivity was present across four different stimulus configurations used to define the figure; LOC responses correlated with participants' reaction times. These results indicate that decision-related activity is present in the LOC when subjects are engaged in threshold-level shape discriminations.

Harmony: EEG/MEG linear inverse source reconstruction in the anatomical basis of spherical harmonics

EEG/MEG source localization based on a "distributed solution" is severely underdetermined, because the number of sources is much larger than the number of measurements. In particular, this makes the solution strongly affected by sensor noise. A new way to constrain the problem is presented. By using the anatomical basis of spherical harmonics (or spherical splines) instead of single dipoles the dimensionality of the inverse solution is greatly reduced without sacrificing the quality of the data fit. The smoothness of the resulting solution reduces the surface bias and scatter of the sources (incoherency) compared to the popular minimum-norm algorithms where single-dipole basis is used (MNE, depth-weighted MNE, dSPM, sLORETA, LORETA, IBF) and allows to efficiently reduce the effect of sensor noise. This approach, termed Harmony, performed well when applied to experimental data (two exemplars of early evoked potentials) and showed better localization precision and solution coherence than the other tested algorithms when applied to realistically simulated data.

Distinct effects of attention on the neural responses to form and motion processing: a SSVEP source-imaging study

We measured neural responses to local and global aspects of form and motion stimuli using frequency-tagged, steady-state visual evoked potentials (SSVEPs) combined with magnetic resonance imaging (MRI) data. Random dot stimuli were used to portray either dynamic Glass patterns (Glass, 1969) or coherent motion displays. SSVEPs were used to estimate neural activity in a set of fMRI-defined visual areas in each subject. To compare activity associated with local versus global processing, we analyzed two frequency components of the SSVEP in each visual area: the high temporal frequency at which the local dots were updated (30 Hz) and the much lower frequency corresponding to updates in the global structure (0.83 Hz). Local and global responses were evaluated in the context of two different behavioral tasks--subjects had to either direct their attention toward or away from the global coherence of the stimuli. The data show that the effect of attention on global and local responses is both stimulus and visual area dependent. When attention was directed away from stimulus coherence, both local and global responses were higher in the coherent motion than Glass pattern condition. Directing attention to coherence in Glass patterns enhanced global activity in areas LOC, hMT+, V4, V3a, and V1, while attention to global motion modulated responses by a smaller amount in a smaller set of areas: V4, hMT+, and LOC. In contrast, directing attention towards stimulus coherence weakly increased local responses to both coherent motion and Glass patterns. These results suggest that visual attention differentially modulates the activity of early visual areas at both local and global levels of structural encoding.

The time course of segmentation and cue-selectivity in the human visual cortex

Texture discontinuities are a fundamental cue by which the visual system segments objects from their background. The neural mechanisms supporting texture-based segmentation are therefore critical to visual perception and cognition. In the present experiment we employ an EEG source-imaging approach in order to study the time course of texture-based segmentation in the human brain. Visual Evoked Potentials were recorded to four types of stimuli in which periodic temporal modulation of a central 3° figure region could either support figure-ground segmentation, or have identical local texture modulations but not produce changes in global image segmentation. The image discontinuities were defined either by orientation or phase differences across image regions. Evoked responses to these four stimuli were analyzed both at the scalp and on the cortical surface in retinotopic and functional regions-of-interest (ROIs) defined separately using fMRI on a subject-by-subject basis. Texture segmentation (tsVEP: segmenting versus non-segmenting) and cue-specific (csVEP: orientation versus phase) responses exhibited distinctive patterns of activity. Alternations between uniform and segmented images produced highly asymmetric responses that were larger after transitions from the uniform to the segmented state. Texture modulations that signaled the appearance of a figure evoked a pattern of increased activity starting at ∼143 ms that was larger in V1 and LOC ROIs, relative to identical modulations that didn't signal figure-ground segmentation. This segmentation-related activity occurred after an initial response phase that did not depend on the global segmentation structure of the image. The two cue types evoked similar tsVEPs up to 230 ms when they differed in the V4 and LOC ROIs. The evolution of the response proceeded largely in the feed-forward direction, with only weak evidence for feedback-related activity.

Disparity-specific spatial interactions: evidence from EEG source imaging

Using cortical source estimation techniques based on high-density EEG and fMRI measurements in humans, we measured how a disparity-defined surround influenced the responses to the changing disparity of a central disk within five visual ROIs: V1, V4, lateral occipital complex (LOC), hMT+, and V3A. The responses in the V1 ROI were not consistently affected either by changes in the characteristics of the surround (correlated or uncorrelated) or by its disparity value, consistent with V1 being responsive only to absolute, not relative, disparity. Correlation in the surround increased the responses in the V4, LOC, and hMT+ ROIs over those measured with the uncorrelated surround. Thus, these extrastriate areas contain neurons that are sensitive to disparity differences. However, their evoked responses did not vary systematically with the surround disparity. Responses in the V3A ROI, in contrast, were increased by correlation in the surround and varied with its disparity. We modeled these V3A responses as attributable to a gain modulation of the absolute disparity response, where the gain amplitude is proportional to the center-surround disparity difference. An additional experiment identified a nonlinear center-surround interaction in V3A that facilitates the responses when center and surround are misaligned but suppresses it when they share the same disparity plane.

Bridging the gap: global disparity processing in the human visual cortex

The human stereoscopic system is remarkable in its ability to utilize widely separated features as references to support fine depth discrimination. In a search for possible neural substrates of this ability, we recorded high-density EEG and used a distributed inverse technique to estimate population-level disparity responses in five regions of interest (ROIs): V1, V3A, hMT+, V4, and lateral occipital complex (LOC). The stimulus was a central modulating disk surrounded by a correlated "reference" annulus presented in the fixation plane. We varied a gap separating the disk from the annulus parametrically from 0 to 5.5° as a test of long-range disparity integration. In the V1, LOC, and hMT+ ROIs, the responses with gaps >0.5° were equal to those obtained in a control condition where the surround was composed of uncorrelated noise (no reference). By contrast, in the V4 and V3A ROIs, responses with gaps as large as 5.5° were still significantly higher than the control. As a test of the spatial distribution of the disparity reference information, we manipulated the properties of the stimulus by placing noise between the center and the surround or throughout the surround. The V3A ROI was particularly sensitive to disparity noise between the center and annulus regions, suggesting an important contribution of disparity edge detectors in this ROI.