Low-level Visual Areas Research Articles

Brain activation during processing of mouth actions in patients with disorders of consciousness.

In the past 2 decades, several attempts have been made to promote a correct diagnosis and possible restorative interventions in patients suffering from disorders of consciousness. Sensory stimulation has been proved to be useful in sustaining the level of arousal/awareness and to improve behavioural responsiveness with a significant effect on oro-motor functions. Recently, action observation has been proposed as a stimulation strategy in patients with disorders of consciousness, based on neurophysiological evidence that the motor cortex can be activated not only during action execution but also when actions are merely observed in the absence of motor output, or during listening to action sounds and speech. This mechanism is provided by the activity of mirror neurons. In the present study, a group of patients with disorders of consciousness (11 males, 4 females; median age: 55 years; age range: 19-74 years) underwent task-based functional MRI in which they had, in one condition, to observe and listen to the sound of mouth actions, and in another condition, to listen to verbs with motor or abstract content. In order to verify the presence of residual activation of the mirror neuron system, the brain activations of patients were compared with that of a group of healthy individuals (seven males, eight females; median age: 33.4 years; age range: 24-65 years) performing the same tasks. The results show that brain activations were lower in patients with disorders of consciousness compared with controls, except for primary auditory areas. During the audiovisual task, 5 out of 15 patients with disorders of consciousness showed only residual activation of low-level visual and auditory areas. Activation of high-level parieto-premotor areas was present in six patients. During the listening task, three patients showed only low-level activations, and six patients activated also high-level areas. Interestingly, in both tasks, one patient with a clinical diagnosis of vegetative state showed activations of high-level areas. Region of interest analysis on blood oxygen level dependent signal change in temporal, parietal and premotor cortex revealed a significant linear relation with the level of clinical functioning, assessed with coma recovery scale-revised. We propose a classification of the patient's response based on the presence of low-level and high-level activations, combined with the patient's functional level. These findings support the use of action observation and listening as possible stimulation strategies in patients with disorders of consciousness and highlight the relevance of combined methods based on functional assessment and brain imaging to provide more detailed neuroanatomical specificity about residual activated areas at both cortical and subcortical levels.

Network dynamics underlying alterations in apparent object size.

A target circle surrounded by small circles looks larger than an identical circle surrounded by large circles (termed as the Ebbinghaus illusion). While previous research has shown that both early and high-level visual regions are involved in the generation of the illusion, it remains unclear how these regions work together to modulate the illusion effect. Here, we used functional MRI and dynamic causal modelling to investigate the neural networks underlying the illusion in conditions where the focus of attention was manipulated via participants directing their attention to and maintain fixation on only one of the two illusory configurations at a time. Behavioural findings confirmed the presence of the illusion. Accordingly, functional MRI activity in the extrastriate cortex accounted for the illusory effects: apparently larger circles elicited greater activation than apparently smaller circles. Interestingly, this spread of activity for size overestimation was accompanied by a decrease in the inhibitory self-connection in the extrastriate region, and an increase in the feedback connectivity from the precuneus to the extrastriate region. These findings demonstrate that the representation of apparent object size relies on feedback projections from higher- to lower-level visual areas, highlighting the crucial role of top-down signals in conscious visual perception.

Perceptual learning: Training together makes us better

Perceptual learning is often thought to rely primarily on low-level visual areas. A new study shows that learning with a partner can improve perceptual learning performance, demonstrating that higher cognitive processes play a larger role in perceptual learning than previously supposed.

Deep Neural Networks and Visuo-Semantic Models Explain Complementary Components of Human Ventral-Stream Representational Dynamics.

Deep neural networks (DNNs) are promising models of the cortical computations supporting human object recognition. However, despite their ability to explain a significant portion of variance in neural data, the agreement between models and brain representational dynamics is far from perfect. We address this issue by asking which representational features are currently unaccounted for in neural time series data, estimated for multiple areas of the ventral stream via source-reconstructed magnetoencephalography data acquired in human participants (nine females, six males) during object viewing. We focus on the ability of visuo-semantic models, consisting of human-generated labels of object features and categories, to explain variance beyond the explanatory power of DNNs alone. We report a gradual reversal in the relative importance of DNN versus visuo-semantic features as ventral-stream object representations unfold over space and time. Although lower-level visual areas are better explained by DNN features starting early in time (at 66 ms after stimulus onset), higher-level cortical dynamics are best accounted for by visuo-semantic features starting later in time (at 146 ms after stimulus onset). Among the visuo-semantic features, object parts and basic categories drive the advantage over DNNs. These results show that a significant component of the variance unexplained by DNNs in higher-level cortical dynamics is structured and can be explained by readily nameable aspects of the objects. We conclude that current DNNs fail to fully capture dynamic representations in higher-level human visual cortex and suggest a path toward more accurate models of ventral-stream computations.SIGNIFICANCE STATEMENT When we view objects such as faces and cars in our visual environment, their neural representations dynamically unfold over time at a millisecond scale. These dynamics reflect the cortical computations that support fast and robust object recognition. DNNs have emerged as a promising framework for modeling these computations but cannot yet fully account for the neural dynamics. Using magnetoencephalography data acquired in human observers during object viewing, we show that readily nameable aspects of objects, such as 'eye', 'wheel', and 'face', can account for variance in the neural dynamics over and above DNNs. These findings suggest that DNNs and humans may in part rely on different object features for visual recognition and provide guidelines for model improvement.

Seeing and extrapolating motion trajectories share common informative activation patterns in primary visual cortex.

The natural environment is dynamic and moving objects become constantly occluded, engaging the brain in a challenging completion process to estimate where and when the object might reappear. Although motion extrapolation is critical in daily life-imagine crossing the street while an approaching car is occluded by a larger standing vehicle-its neural underpinnings are still not well understood. While the engagement of low-level visual cortex during dynamic occlusion has been postulated, most of the previous group-level fMRI-studies failed to find evidence for an involvement of low-level visual areas during occlusion. In this fMRI-study, we therefore used individually defined retinotopic maps and multivariate pattern analysis to characterize the neural basis of visible and occluded changes in motion direction in humans. To this end, participants learned velocity-direction change pairings (slow motion-upwards; fast motion-downwards or vice versa) during a training phase without occlusion and judged the change in stimulus direction, based on its velocity, during a following test phase with occlusion. We find that occluded motion direction can be predicted from the activity patterns during visible motion within low-level visual areas, supporting the notion of a mental representation of motion trajectory in these regions during occlusion.

High-Level Visual Encoding Model Framework with Hierarchical Ventral Stream-Optimized Neural Networks.

Visual encoding models based on deep neural networks (DNN) show good performance in predicting brain activity in low-level visual areas. However, due to the amount of neural data limitation, DNN-based visual encoding models are difficult to fit for high-level visual areas, resulting in insufficient encoding performance. The ventral stream suggests that higher visual areas receive information from lower visual areas, which is not fully reflected in the current encoding models. In the present study, we propose a novel visual encoding model framework which uses the hierarchy of representations in the ventral stream to improve the model’s performance in high-level visual areas. Under the framework, we propose two categories of hierarchical encoding models from the voxel and the feature perspectives to realize the hierarchical representations. From the voxel perspective, we first constructed an encoding model for the low-level visual area (V1 or V2) and extracted the voxel space predicted by the model. Then we use the extracted voxel space of the low-level visual area to predict the voxel space of the high-level visual area (V4 or LO) via constructing a voxel-to-voxel model. From the feature perspective, the feature space of the first model is extracted to predict the voxel space of the high-level visual area. The experimental results show that two categories of hierarchical encoding models effectively improve the encoding performance in V4 and LO. In addition, the proportion of the best-encoded voxels for different models in V4 and LO show that our proposed models have obvious advantages in prediction accuracy. We find that the hierarchy of representations in the ventral stream has a positive effect on improving the performance of the existing model in high-level visual areas.

Graph Theoretical Analysis of Structural Covariance Reveals the Relevance of Visuospatial and Attentional Areas in Essential Tremor Recovery After Stereotactic Radiosurgical Thalamotomy.

Essential tremor (ET) is the most common movement disorder. Its pathophysiology is only partially understood. Here, we leveraged graph theoretical analysis on structural covariance patterns quantified from morphometric estimates for cortical thickness, surface area, and mean curvature in patients with ET before and one year after (to account for delayed clinical effect) ventro-intermediate nucleus (Vim) stereotactic radiosurgical thalamotomy. We further contrasted the observed patterns with those from matched healthy controls (HCs). Significant group differences at the level of individual morphometric properties were specific to mean curvature and the post-/pre-thalamotomy contrast, evidencing brain plasticity at the level of the targeted left thalamus, and of low-level visual, high-level visuospatial and attentional areas implicated in the dorsal visual stream. The introduction of cross-correlational analysis across pairs of morphometric properties strengthened the presence of dorsal visual stream readjustments following thalamotomy, as cortical thickness in the right lingual gyrus, bilateral rostral middle frontal gyrus, and left pre-central gyrus was interrelated with mean curvature in the rest of the brain. Overall, our results position mean curvature as the most relevant morphometric feature to understand brain plasticity in drug-resistant ET patients following Vim thalamotomy. They also highlight the importance of examining not only individual features, but also their interactions, to gain insight into the routes of recovery following intervention.

Reconstructing rapid natural vision with fMRI-conditional video generative adversarial network.

Recent functional magnetic resonance imaging (fMRI) studies have made significant progress in reconstructing perceived visual content, which advanced our understanding of the visual mechanism. However, reconstructing dynamic natural vision remains a challenge because of the limitation of the temporal resolution of fMRI. Here, we developed a novel fMRI-conditional video generative adversarial network (f-CVGAN) to reconstruct rapid video stimuli from evoked fMRI responses. In this model, we employed a generator to produce spatiotemporal reconstructions and employed two separate discriminators (spatial and temporal discriminators) for the assessment. We trained and tested the f-CVGAN on two publicly available video-fMRI datasets, and the model produced pixel-level reconstructions of 8 perceived video frames from each fMRI volume. Experimental results showed that the reconstructed videos were fMRI-related and captured important spatial and temporal information of the original stimuli. Moreover, we visualized the cortical importance map and found that the visual cortex is extensively involved in the reconstruction, whereas the low-level visual areas (V1/V2/V3/V4) showed the largest contribution. Our work suggests that slow blood oxygen level-dependent signals describe neural representations of the fast perceptual process that can be decoded in practice.

Network Path Convergence Shapes Low-Level Processing in the Visual Cortex.

Hierarchical counterstream via feedforward and feedback interactions is a major organizing principle of the cerebral cortex. The counterstream, as a topological feature of the network of cortical areas, is captured by the convergence and divergence of paths through directed links. So defined, the convergence degree (CD) reveals the reciprocal nature of forward and backward connections, and also hierarchically relevant integrative properties of areas through their inward and outward connections. We asked if topology shapes large-scale cortical functioning by studying the role of CD in network resilience and Granger causal coupling in a model of hierarchical network dynamics. Our results indicate that topological synchronizability is highly vulnerable to attacking edges based on CD, while global network efficiency depends mostly on edge betweenness, a measure of the connectedness of a link. Furthermore, similar to anatomical hierarchy determined by the laminar distribution of connections, CD highly correlated with causal coupling in feedforward gamma, and feedback alpha-beta band synchronizations in a well-studied subnetwork, including low-level visual cortical areas. In contrast, causal coupling did not correlate with edge betweenness. Considering the entire network, the CD-based hierarchy correlated well with both the anatomical and functional hierarchy for low-level areas that are far apart in the hierarchy. Conversely, in a large part of the anatomical network where hierarchical distances are small between the areas, the correlations were not significant. These findings suggest that CD-based and functional hierarchies are interrelated in low-level processing in the visual cortex. Our results are consistent with the idea that the interplay of multiple hierarchical features forms the basis of flexible functional cortical interactions.

The human visual system differentially represents subjectively and objectively invisible stimuli.

The study of unconscious processing requires a measure of conscious awareness. Awareness measures can be either subjective (based on participant's report) or objective (based on perceptual performance). The preferred awareness measure depends on the theoretical position about consciousness and may influence conclusions about the extent of unconscious processing and about the neural correlates of consciousness. We obtained functional magnetic resonance imaging (fMRI) measurements from 43 subjects while they viewed masked faces and houses that were either subjectively or objectively invisible. Even for objectively invisible (perceptually indiscriminable) stimuli, we found significant category information in both early, lower-level visual areas and in higher-level visual cortex, although representations in anterior, category-selective ventrotemporal areas were less robust. For subjectively invisible stimuli, similar to visible stimuli, there was a clear posterior-to-anterior gradient in visual cortex, with stronger category information in ventrotemporal cortex than in early visual cortex. For objectively invisible stimuli, however, category information remained virtually unchanged from early visual cortex to object- and category-selective visual areas. These results demonstrate that although both objectively and subjectively invisible stimuli are represented in visual cortex, the extent of unconscious information processing is influenced by the measurement approach. Furthermore, our data show that subjective and objective approaches are associated with different neural correlates of consciousness and thus have implications for neural theories of consciousness.

Top-down control of visual cortex by the frontal eye fields through oscillatory realignment

Voluntary allocation of visual attention is controlled by top-down signals generated within the Frontal Eye Fields (FEFs) that can change the excitability of lower-level visual areas. However, the mechanism through which this control is achieved remains elusive. Here, we emulated the generation of an attentional signal using single-pulse transcranial magnetic stimulation to activate the FEFs and tracked its consequences over the visual cortex. First, we documented changes to brain oscillations using electroencephalography and found evidence for a phase reset over occipital sites at beta frequency. We then probed for perceptual consequences of this top-down triggered phase reset and assessed its anatomical specificity. We show that FEF activation leads to cyclic modulation of visual perception and extrastriate but not primary visual cortex excitability, again at beta frequency. We conclude that top-down signals originating in FEF causally shape visual cortex activity and perception through mechanisms of oscillatory realignment.

α-Band activity tracks a two-dimensional spotlight of attention during spatial working memory maintenance.

Covert spatial attention is thought to facilitate the maintenance of locations in working memory, and EEG α-band activity (8-12 Hz) is proposed to track the focus of covert attention. Recent work has shown that multivariate patterns of α-band activity track the polar angle of remembered locations relative to fixation. However, a defining feature of covert spatial attention is that it facilitates processing in a specific region of the visual field, and prior work has not determined whether patterns of α-band activity track the two-dimensional (2-D) coordinates of remembered stimuli within a visual hemifield or are instead maximally sensitive to the polar angle of remembered locations around fixation. Here, we used a lateralized spatial estimation task, in which observers remembered the location of one or two target dots presented to one side of fixation, to test this question. By applying a linear discriminant classifier to the topography of α-band activity, we found that we were able to decode the location of remembered stimuli. Critically, model comparison revealed that the pattern of classifier choices observed across remembered positions was best explained by a model assuming that α-band activity tracks the 2-D coordinates of remembered locations rather than a model assuming that α-band activity tracks the polar angle of remembered locations relative to fixation. These results support the hypothesis that this α-band activity is involved in the spotlight of attention, and arises from mid- to lower-level visual areas involved in maintaining spatial locations in working memory.NEW & NOTEWORTHY A substantial body of work has shown that patterns of EEG α-band activity track the angular coordinates of attended and remembered stimuli around fixation, but whether these patterns track the two-dimensional coordinates of stimuli presented within a visual hemifield remains an open question. Here, we demonstrate that α-band activity tracks the two-dimensional coordinates of remembered stimuli within a hemifield, showing that α-band activity reflects a spotlight of attention focused on locations maintained in working memory.

Generative Feedback Explains Distinct Brain Activity Codes for Seen and Mental Images

The relationship between mental imagery and vision is a long-standing problem in neuroscience. Currently, it is not known whether differences between the activity evoked during vision and reinstated during imagery reflect different codes for seen and mental images. To address this problem, we modeled mental imagery in the human brain as feedback in a hierarchical generative network. Such networks synthesize images by feeding abstract representations from higher to lower levels of the network hierarchy. When higher processing levels are less sensitive to stimulus variation than lower processing levels, as in the human brain, activity in low-level visual areas should encode variation in mental images with less precision than seen images. To test this prediction, we conducted an fMRI experiment in which subjects imagined and then viewed hundreds of spatially varying naturalistic stimuli. To analyze these data, we developed imagery-encoding models. These models accurately predicted brain responses to imagined stimuli and enabled accurate decoding of their position and content. They also allowed us to compare, for every voxel, tuning to seen and imagined spatial frequencies, as well as the location and size of receptive fields in visual and imagined space. We confirmed our prediction, showing that, in low-level visual areas, imagined spatial frequencies in individual voxels are reduced relative to seen spatial frequencies and that receptive fields in imagined space are larger than in visual space. These findings reveal distinct codes for seen and mental images and link mental imagery to the computational abilities of generative networks.

Neural correlates of semantic and syntactic processing in German Sign Language

The study of deaf and hearing native users of signed languages can offer unique insights into how biological constraints and environmental input interact to shape the neural bases of language processing. Here, we use functional magnetic resonance imaging (fMRI) to address two questions: (1) Do semantic and syntactic processing in a signed language rely on anatomically and functionally distinct neural substrates as it has been shown for spoken languages? and (2) Does hearing status affect the neural correlates of these two types of linguistic processing? Deaf and hearing native signers performed a sentence judgement task on German Sign Language (Deutsche Gebärdensprache: DGS) sentences which were correct or contained either syntactic or semantic violations. We hypothesized that processing of semantic and syntactic violations in DGS relies on distinct neural substrates as it has been shown for spoken languages. Moreover, we hypothesized that effects of hearing status are observed within auditory regions, as deaf native signers have been shown to activate auditory areas to a greater extent than hearing native signers when processing a signed language. Semantic processing activated low-level visual areas and the left inferior frontal gyrus (IFG), suggesting both modality-dependent and independent processing mechanisms. Syntactic processing elicited increased activation in the right supramarginal gyrus (SMG). Moreover, psychophysiological interaction (PPI) analyses revealed a cluster in left middle occipital regions showing increased functional coupling with the right SMG during syntactic relative to semantic processing, possibly indicating spatial processing mechanisms that are specific to signed syntax. Effects of hearing status were observed in the right superior temporal cortex (STC): deaf but not hearing native signers showed greater activation for semantic violations than for syntactic violations in this region. Taken together, the present findings suggest that the neural correlates of language processing are partly determined by biological constraints, but that they may additionally be influenced by the unique processing demands of the language modality and different sensory experiences.

Neuroimaging Findings on Amodal Completion: A Review.

Amodal completion is the phenomenon of perceiving completed objects even though physically they are partially occluded. In this review, we provide an extensive overview of the results obtained from a variety of neuroimaging studies on the neural correlates of amodal completion. We discuss whether low-level and high-level cortical areas are implicated in amodal completion; provide an overview of how amodal completion unfolds over time while dissociating feedforward, recurrent, and feedback processes; and discuss how amodal completion is represented at the neuronal level. The involvement of low-level visual areas such as V1 and V2 is not yet clear, while several high-level structures such as the lateral occipital complex and fusiform face area seem invariant to occlusion of objects and faces, respectively, and several motor areas seem to code for object permanence. The variety of results on the timing of amodal completion hints to a mixture of feedforward, recurrent, and feedback processes. We discuss whether the invisible parts of the occluded object are represented as if they were visible, contrary to a high-level representation. While plenty of questions on amodal completion remain, this review presents an overview of the neuroimaging findings reported to date, summarizes several insights from computational models, and connects research of other perceptual completion processes such as modal completion. In all, it is suggested that amodal completion is the solution to deal with various types of incomplete retinal information, and highly depends on stimulus complexity and saliency, and therefore also give rise to a variety of observed neural patterns.

Retinal-specific category learning.

Virtually all cognitive theories of category learning (such as prototype theory1-5 and exemplar theory6-8) view this important skill as a high-level process that uses abstract representations of objects in the world. Because these representations are removed from visual characteristics of the display, such theories suggest that category learning occurs in higher-level (such as association) areas and therefore should be immune to the visual field dependencies that characterize processing of objects mediated by representations in low-level visual areas. Here we challenge that view by describing a fully controlled demonstration of visual-field dependence in category learning. Eye-tracking was used to control gaze while participants either learned rule-based categories known to recruit prefrontal-based explicit reasoning, or information-integration categories known to depend on basal-ganglia-mediated procedural learning9. Results showed that learning was visual-field dependent with information-integration categories, but we found no evidence of visual-field dependence with rule-based categories. A theoretical interpretation of this difference is offered in terms of the underlying neurobiology. Finally, these results are situated within the broad perceptual-learning literature in an attempt to motivate further research on the similarities and differences between category and perceptual learning.

Neural Correlates of Enhanced Visual Attentional Control in Action Video Game Players: An Event-Related Potential Study.

Action video game players (AVGPs) outperform non-action video game players (NAVGPs) on a range of perceptual and attentional tasks. Although several studies have reported neuroplastic changes within the frontoparietal networks of attention in AVGPs, little is known about possible changes in attentional modulation in low-level visual areas. To assess the contribution of these different levels of neural processing to the perceptual and attentional enhancements noted in AVGPs, visual event-related potentials (ERPs) were recorded from 14 AVGPs and 14 NAVGPs during a target discrimination task that required participants to attend to rapid sequences of Gabor patches under either focused or divided attention conditions. AVGPs responded faster to target Gabors in the focused attention condition compared with the NAVGPs. Correspondingly, ERPs to standard Gabors revealed a more pronounced negativity in the time range of the parietally generated anterior N1 component in AVGPs compared with NAVGPs during focused attention. In addition, the P2 component of the visual ERP was more pronounced in AVGPs than in NAVGPs over the hemisphere contralateral to the stimulus position in response to standard Gabors. Contrary to predictions, however, attention-modulated occipital components generated in the low-level extrastriate visual pathways, including the P1 and posterior N1, showed no significant group differences. Thus, the main neural signature of enhanced perceptual and attentional control functions in AVGPs appears linked to an attention-dependent parietal process, indexed by the anterior N1 component, and possibly to more efficient higher-order perceptual processing, indexed by the P2 component.

Position Information Encoded by Population Activity in Hierarchical Visual Areas.

Neurons in high-level visual areas respond to more complex visual features with broader receptive fields (RFs) compared to those in low-level visual areas. Thus, high-level visual areas are generally considered to carry less information regarding the position of seen objects in the visual field. However, larger RFs may not imply loss of position information at the population level. Here, we evaluated how accurately the position of a seen object could be predicted (decoded) from activity patterns in each of six representative visual areas with different RF sizes [V1–V4, lateral occipital complex (LOC), and fusiform face area (FFA)]. We collected functional magnetic resonance imaging (fMRI) responses while human subjects viewed a ball randomly moving in a two-dimensional field. To estimate population RF sizes of individual fMRI voxels, RF models were fitted for individual voxels in each brain area. The voxels in higher visual areas showed larger estimated RFs than those in lower visual areas. Then, the ball’s position in a separate session was predicted by maximum likelihood estimation using the RF models of individual voxels. We also tested a model-free multivoxel regression (support vector regression, SVR) to predict the position. We found that regardless of the difference in RF size, all visual areas showed similar prediction accuracies, especially on the horizontal dimension. Higher areas showed slightly lower accuracies on the vertical dimension, which appears to be attributed to the narrower spatial distributions of the RF centers. The results suggest that much position information is preserved in population activity through the hierarchical visual pathway regardless of RF sizes and is potentially available in later processing for recognition and behavior.

The cerebral anatomy of word reading: From Dejerine to brain imaging

The cerebral processes which support word reading may be analyzed into two stages. The first stage takes place within the visual system, and allows for the invariant identification of letters and their order. This process involves sequentially low-level visual areas and the so-called visual word form area (VWFA), located in the lateral occipitotemporal sulcus (Cohen et al., 2000). During the second word processing stage, orthographic information is transferred to language areas, where it will allow the reader to access sound and meaning representations. Pure alexia, or alexia without agraphia, which was perfectly described by Dejerine (1892, 1895), consists in a selective impairment of reading resulting from the disruption or the deafferentation of the VWFA. However, the pathophysiological account put forward by Dejerine was somewhat different from the currently prevailing explanation ( Figure 1 ). During reading, the left occipital cortex (yellow) receives input from the left lateral geniculate through the optic radiations [1] , from the opposite hemisphere through callosal fibers [2] , and it projects to later stations in the reading network. Dejerine proposed that the target of such projections was the angular gyrus, although the corresponding fiber tract was purely hypothetical [3] . According to the current data, the target of occipital projections is actually the VWFA (red), which is reached through the ILF (3′), which was disrupted in the patient reported in Epelbaum et al. (2008) [4] , as it was in Dejerine's patient.

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.