Not one extrastriate body area: using anatomical landmarks, hMT+, and visual field maps to parcellate limb-selective activations in human lateral occipitotemporal cortex

A unifying framework for functional organization in early and higher ventral visual cortex

A key feature of cortical systems is functional organization: the arrangement of functionally distinct neurons in characteristic spatial patterns. However, the principles underlying the emergence of functional organization in the cortex are poorly understood. Here, we develop the topographic deep artificial neural network (TDANN), the first model to predict several aspects of the functional organization of multiple cortical areas in the primate visual system. We analyze the factors driving the TDANN's success and find that it balances two objectives: learning a task-general sensory representation and maximizing the spatial smoothness of responses according to a metric that scales with cortical surface area. In turn, the representations learned by the TDANN are more brain-like than in spatially unconstrained models. Finally, we provide evidence that the TDANN's functional organization balances performance with between-area connection length. Our results offer a unified principle for understanding the functional organization of the primate ventral visual system.

Natural scenes reveal diverse representations of 2D and 3D body pose in the human brain

Human pose, defined as the spatial relationships between body parts, carries instrumental information supporting the understanding of motion and action of a person. A substantial body of previous work has identified cortical areas responsive to images of bodies and different body parts. However, the neural basis underlying the visual perception of body part relationships has received less attention. To broaden our understanding of body perception, we analyzed high-resolution fMRI responses to a wide range of poses from over 4,000 complex natural scenes. Using ground-truth annotations and an application of three-dimensional (3D) pose reconstruction algorithms, we compared similarity patterns of cortical activity with similarity patterns built from human pose models with different levels of depth availability and viewpoint dependency. Targeting the challenge of explaining variance in complex natural image responses with interpretable models, we achieved statistically significant correlations between pose models and cortical activity patterns (though performance levels are substantially lower than the noise ceiling). We found that the 3D view-independent pose model, compared with two-dimensional models, better captures the activation from distinct cortical areas, including the right posterior superior temporal sulcus (pSTS). These areas, together with other pose-selective regions in the LOTC, form a broader, distributed cortical network with greater view-tolerance in more anterior patches. We interpret these findings in light of the computational complexity of natural body images, the wide range of visual tasks supported by pose structures, and possible shared principles for view-invariant processing between articulated objects and ordinary, rigid objects.

Rethinking cortical recycling in ventral temporal cortex

High-level visual areas in ventral temporal cortex (VTC) support recognition of important categories, such as faces and words. Word-selective regions are left lateralized and emerge at the onset of reading instruction. Face-selective regions are right lateralized and have been documented in infancy. Prevailing theories suggest that face-selective regions become right lateralized due to competition with word-selective regions in the left hemisphere. However, recent longitudinal studies examining face- and word-selective responses in childhood do not provide support for this theory. Instead, there is evidence that word representations recycle cortex previously involved in processing other stimuli, such as limbs. These findings call for more longitudinal investigations of cortical recycling and a new era of work that links visual experience and behavior with neural responses.

Sound-encoded faces activate the left fusiform face area in the early blind

Face perception in humans and nonhuman primates is accomplished by a patchwork of specialized cortical regions. How these regions develop has remained controversial. In sighted individuals, facial information is primarily conveyed via the visual modality. Early blind individuals, on the other hand, can recognize shapes using auditory and tactile cues. Here we demonstrate that such individuals can learn to distinguish faces from houses and other shapes by using a sensory substitution device (SSD) presenting schematic faces as sound-encoded stimuli in the auditory modality. Using functional MRI, we then asked whether a face-selective brain region like the fusiform face area (FFA) shows selectivity for faces in the same subjects, and indeed, we found evidence for preferential activation of the left FFA by sound-encoded faces. These results imply that FFA development does not depend on experience with visual faces per se but may instead depend on exposure to the geometry of facial configurations.

Neural tracking of social hierarchies in adolescents' real-world social networks

In the current study, we combined sociometric nominations and neuroimaging techniques to examine adolescents' neural tracking of peers from their real-world social network that varied in social preferences and popularity. Adolescent participants from an entire school district (N = 873) completed peer sociometric nominations of their grade at school, and a subset of participants (N = 117, Mage = 13.59 years) completed a neuroimaging task in which they viewed peer faces from their social networks. We revealed two neural processes by which adolescents track social preference: (1) the fusiform face area, an important region for early visual perception and social categorization, simultaneously represented both peers high in social preference and low in social preference; (2) the dorsolateral prefrontal cortex (DLPFC), which was differentially engaged in tracking peers high and low in social preference. No regions specifically tracked peers high in popularity and only the inferior parietal lobe, temporoparietal junction, midcingulate cortex and insula were involved in tracking unpopular peers. This is the first study to examine the neural circuits that support adolescents' perception of peer-based social networks. These findings identify the neural processes that allow youths to spontaneously keep track of peers' social value within their social network.

Voxelwise encoding models of body stimuli reveal a representational gradient from low-level visual features to postural features in occipitotemporal cortex

Research on body representation in the brain has focused on category-specific representation, using fMRI to investigate the response pattern to body stimuli in occipitotemporal cortex without so far addressing the issue of the specific computations involved in body selective regions, only defined by higher order category selectivity. This study used ultra-high field fMRI and banded ridge regression to investigate the coding of body images, by comparing the performance of three encoding models in predicting brain activity in occipitotemporal cortex and specifically the extrastriate body area (EBA). Our results suggest that bodies are encoded in occipitotemporal cortex and in the EBA according to a combination of low-level visual features and postural features.

Distributed and hierarchical neural encoding of multidimensional biological motion attributes in the human brain

The human visual system can efficiently extract distinct physical, biological, and social attributes (e.g. facing direction, gender, and emotional state) from biological motion (BM), but how these attributes are encoded in the brain remains largely unknown. In the current study, we used functional magnetic resonance imaging to investigate this issue when participants viewed multidimensional BM stimuli. Using multiple regression representational similarity analysis, we identified distributed brain areas, respectively, related to the processing of facing direction, gender, and emotional state conveyed by BM. These brain areas are governed by a hierarchical structure in which the respective neural encoding of facing direction, gender, and emotional state is modulated by each other in descending order. We further revealed that a portion of the brain areas identified in representational similarity analysis was specific to the neural encoding of each attribute and correlated with the corresponding behavioral results. These findings unravel the brain networks for encoding BM attributes in consideration of their interactions, and highlight that the processing of multidimensional BM attributes is recurrently interactive.

A Unifying Principle for the Functional Organization of Visual Cortex

A key feature of many cortical systems is functional organization: the arrangement of neurons with specific functional properties in characteristic spatial patterns across the cortical surface. However, the principles underlying the emergence and utility of functional organization are poorly understood. Here we develop the Topographic Deep Artificial Neural Network (TDANN), the first unified model to accurately predict the functional organization of multiple cortical areas in the primate visual system. We analyze the key factors responsible for the TDANN's success and find that it strikes a balance between two specific objectives: achieving a task-general sensory representation that is self-supervised, and maximizing the smoothness of responses across the cortical sheet according to a metric that scales relative to cortical surface area. In turn, the representations learned by the TDANN are lower dimensional and more brain-like than those in models that lack a spatial smoothness constraint. Finally, we provide evidence that the TDANN's functional organization balances performance with inter-area connection length, and use the resulting models for a proof-of-principle optimization of cortical prosthetic design. Our results thus offer a unified principle for understanding functional organization and a novel view of the functional role of the visual system in particular.

A large-scale brain network of species-specific dynamic human body perception

This ultrahigh field 7 T fMRI study addressed the question of whether there exists a core network of brain areas at the service of different aspects of body perception. Participants viewed naturalistic videos of monkey and human faces, bodies, and objects along with mosaic-scrambled videos for control of low-level features. Independent component analysis (ICA) based network analysis was conducted to find body and species modulations at both the voxel and the network levels. Among the body areas, the highest species selectivity was found in the middle frontal gyrus and amygdala. Two large-scale networks were highly selective to bodies, dominated by the lateral occipital cortex and right superior temporal sulcus (STS) respectively. The right STS network showed high species selectivity, and its significant human body-induced node connectivity was focused around the extrastriate body area (EBA), STS, temporoparietal junction (TPJ), premotor cortex, and inferior frontal gyrus (IFG). The human body-specific network discovered here may serve as a brain-wide internal model of the human body serving as an entry point for a variety of processes relying on body descriptions as part of their more specific categorization, action, or expression recognition functions.

Functional relevance of the extrastriate body area for visual and haptic object recognition: a preregistered fMRI-guided TMS study

The extrastriate body area (EBA) is a region in the lateral occipito-temporal cortex (LOTC), which is sensitive to perceived body parts. Neuroimaging studies suggested that EBA is related to body and tool processing, regardless of the sensory modalities. However, how essential this region is for visual tool processing and nonvisual object processing remains a matter of controversy. In this preregistered fMRI-guided repetitive transcranial magnetic stimulation (rTMS) study, we examined the causal involvement of EBA in multisensory body and tool recognition. Participants used either vision or haptics to identify 3 object categories: hands, teapots (tools), and cars (control objects). Continuous theta-burst stimulation (cTBS) was applied over left EBA, right EBA, or vertex (control site). Performance for visually perceived hands and teapots (relative to cars) was more strongly disrupted by cTBS over left EBA than over the vertex, whereas no such object-specific effect was observed in haptics. The simulation of the induced electric fields confirmed that the cTBS affected regions including EBA. These results indicate that the LOTC is functionally relevant for visual hand and tool processing, whereas the rTMS over EBA may differently affect object recognition between the 2 sensory modalities.

Functionally and structurally distinct fusiform face area(s) in over 1000 participants

The fusiform face area (FFA) is a widely studied region causally involved in face perception. Even though cognitive neuroscientists have been studying the FFA for over two decades, answers to foundational questions regarding the function, architecture, and connectivity of the FFA from a large (N>1000) group of participants are still lacking. To fill this gap in knowledge, we quantified these multimodal features of fusiform face-selective regions in 1053 participants in the Human Connectome Project. After manually defining over 4,000 fusiform face-selective regions, we report five main findings. First, 68.76% of hemispheres have two cortically separate regions (pFus-faces/FFA-1 and mFus-faces/FFA-2). Second, in 26.69% of hemispheres, pFus-faces/FFA-1 and mFus-faces/FFA-2 are spatially contiguous, yet are distinct based on functional, architectural, and connectivity metrics. Third, pFus-faces/FFA-1 is more face-selective than mFus-faces/FFA-2, and the two regions have distinct functional connectivity fingerprints. Fourth, pFus-faces/FFA-1 is cortically thinner and more heavily myelinated than mFus-faces/FFA-2. Fifth, face-selective patterns and functional connectivity fingerprints of each region are more similar in monozygotic than dizygotic twins and more so than architectural gradients. As we share our areal definitions with the field, future studies can explore how structural and functional features of these regions will inform theories regarding how visual categories are represented in the brain.

Functionally and structurally distinct fusiform face area(s) in over 1000 participants

The fusiform face area (FFA) is a widely studied region causally involved in face perception. Even though cognitive neuroscientists have been studying the FFA for over two decades, answers to foundational questions regarding the function, architecture, and connectivity of the FFA from a large (N>1000) group of participants are still lacking. To fill this gap in knowledge, we quantified these multimodal features of fusiform face-selective regions in 1053 participants in the Human Connectome Project. After manually defining over 4,000 fusiform face-selective regions, we report five main findings. First, 68.76% of hemispheres have two cortically separate regions (pFus-faces/FFA-1 and mFus-faces/FFA-2). Second, in 26.69% of hemispheres, pFus-faces/FFA-1 and mFus-faces/FFA-2 are spatially contiguous, yet are distinct based on functional, architectural, and connectivity metrics. Third, pFus-faces/FFA-1 is more face-selective than mFus-faces/FFA-2, and the two regions have distinct functional connectivity fingerprints. Fourth, pFus-faces/FFA-1 is cortically thinner and more heavily myelinated than mFus-faces/FFA-2. Fifth, face-selective patterns and functional connectivity fingerprints of each region are more similar in monozygotic than dizygotic twins and more so than architectural gradients. As we share our areal definitions with the field, future studies can explore how structural and functional features of these regions will inform theories regarding how visual categories are represented in the brain.

Meta-analytic evidence for a novel hierarchical model of conceptual processing

Conceptual knowledge plays a pivotal role in human cognition. Grounded cognition theories propose that concepts consist of perceptual-motor features represented in modality-specific perceptual-motor cortices. However, it is unclear whether conceptual processing consistently engages modality-specific areas. Here, we performed an activation likelihood estimation (ALE) meta-analysis across 212 neuroimaging experiments on conceptual processing related to 7 perceptual-motor modalities (action, sound, visual shape, motion, color, olfaction-gustation, and emotion). We found that conceptual processing consistently engages brain regions also activated during real perceptual-motor experience of the same modalities. In addition, we identified multimodal convergence zones that are recruited for multiple modalities. In particular, the left inferior parietal lobe (IPL) and posterior middle temporal gyrus (pMTG) are engaged for three modalities: action, motion, and sound. These "trimodal" regions are surrounded by "bimodal" regions engaged for two modalities. Our findings support a novel model of the conceptual system, according to which conceptual processing relies on a hierarchical neural architecture from modality-specific to multimodal areas up to an amodal hub.

More Than the Face: Representations of Bodies in the Inferior Temporal Cortex

Visual representations of bodies, in addition to those of faces, contribute to the recognition of con- and heterospecifics, to action recognition, and to nonverbal communication. Despite its importance, the neural basis of the visual analysis of bodies has been less studied than that of faces. In this article, I review what is known about the neural processing of bodies, focusing on the macaque temporal visual cortex. Early single-unit recording work suggested that the temporal visual cortex contains representations of body parts and bodies, with the dorsal bank of the superior temporal sulcus representing bodily actions. Subsequent functional magnetic resonance imaging studies in both humans and monkeys showed several temporal cortical regions that are strongly activated by bodies. Single-unit recordings in the macaque body patches suggest that these represent mainly body shape features. More anterior patches show a greater viewpoint-tolerant selectivity for body features, which may reflect a processing principle shared with other object categories, including faces. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

OUP accepted manuscript

Neuralgic amyotrophy is a common peripheral nerve disorder caused by autoimmune inflammation of the brachial plexus, clinically characterized by acute pain and weakness of the shoulder muscles, followed by motor impairment. Despite recovery of the peripheral nerves, patients often have residual motor dysfunction of the upper extremity, leading to persistent pain related to altered biomechanics of the shoulder region. Building on clinical signs that suggest a role for cerebral mechanisms in these residual complaints, here we show and characterize cerebral alterations following neuralgic amyotrophy. Neuralgic amyotrophy patients often develop alternative motor strategies, which suggests that (mal)adaptations may occur in somatomotor and/or visuomotor brain areas. Here, we tested where changes in cerebral sensorimotor representations occur in neuralgic amyotrophy, while controlling for altered motor execution due to peripheral neuropathy. We additionally explore the relation between potential cerebral alterations in neuralgic amyotrophy and clinical symptoms. During functional MRI scanning, 39 neuralgic amyotrophy patients with persistent, lateralized symptoms in the right upper extremity and 23 matched healthy participants solved a hand laterality judgement task that can activate sensorimotor representations of the upper extremity, across somatomotor and visuomotor brain areas. Behavioural and cerebral responses confirmed the involvement of embodied, sensorimotor processes across groups. Compared with healthy participants, neuralgic amyotrophy patients were slower in hand laterality judgement and had decreased cerebral activity specific to their affected limb in two higher-order visual brain regions: the right extrastriate cortex and the parieto-occipital sulcus. Exploratory analyses revealed that across patients, extrastriate activity specific to the affected limb decreased as persistent pain increased, and affected limb-related parieto-occipital activity decreased as imagery performance of the affected limb became slower. These findings suggest that maladaptive cerebral plasticity in visuomotor areas involved in sensorimotor integration plays a role in residual motor dysfunction and subsequent persistent pain in neuralgic amyotrophy. Rehabilitation interventions that apply visuomotor strategies to improve sensorimotor integration may help to treat neuralgic amyotrophy patients.

Decoding the difference between explicit and implicit body expression representation in high level visual, prefrontal and inferior parietal cortex

Recent studies provide an increasing understanding of how visual objects categories like faces or bodies are represented in the brain and also raised the question whether a category based or more dynamic network inspired models are more powerful. Two important and so far sidestepped issues in this debate are, first, how major category attributes like the emotional expression directly influence category representation and second, whether category and attribute representation are sensitive to task demands. This study investigated the impact of a crucial category attribute like emotional expression on category area activity and whether this varies with the participants' task. Using (fMRI) we measured BOLD responses while participants viewed whole body expressions and performed either an explicit (emotion) or an implicit (shape) recognition task. Our results based on multivariate methods show that the type of task is the strongest determinant of brain activity and can be decoded in EBA, VLPFC and IPL. Brain activity was higher for the explicit task condition in VLPFC and was not emotion specific. This pattern suggests that during explicit recognition of the body expression, body category representation may be strengthened, and emotion and action related activity suppressed. Taken together these results stress the importance of the task and of the role of category attributes for understanding the functional organization of high level visual cortex.

A computational neuroethology perspective on body and expression perception

Survival prompts organisms to prepare adaptive behavior in response to environmental and social threat. However, what are the specific features of the appearance of a conspecific that trigger such adaptive behaviors? For social species, the prime candidates for triggering defense systems are the visual features of the face and the body. We propose a novel approach for studying the ability of the brain to gather survival-relevant information from seeing conspecific body features. Specifically, we propose that behaviorally relevant information from bodies and body expressions is coded at the levels of midlevel features in the brain. These levels are relatively independent from higher-order cognitive and conscious perception of bodies and emotions. Instead, our approach is embedded in an ethological framework and mobilizes computational models for feature discovery.

Reading: The Confluence of Vision and Language

The scientific study of reading has a rich history that spans disciplines from vision science to linguistics, psychology, cognitive neuroscience, neurology, and education. The study of reading can elucidate important general mechanisms in spatial vision, attentional control, object recognition, and perceptual learning, as well as the principles of plasticity and cortical topography. However, literacy also prompts the development of specific neural circuits to process a unique and artificial stimulus. In this review, we describe the sequence of operations that transforms visual features into language, how the key neural circuits are sculpted by experience during development, and what goes awry in children for whom learning to read is a struggle. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Top-Down Attention Guidance Shapes Action Encoding in the pSTS

The posterior superior temporal sulcus (pSTS) is a brain region characterized by perceptual representations of human body actions that promote the understanding of observed behavior. Increasingly, action observation is recognized as being strongly shaped by the expectations of the observer (Kilner 2011; Koster-Hale and Saxe 2013; Patel et al. 2019). Therefore, to characterize top-down influences on action observation, we evaluated the statistical structure of multivariate activation patterns from the action observation network (AON) while observers attended to the different dimensions of action vignettes (the action kinematics, goal, or identity of avatars jumping or crouching). Decoding accuracy varied as a function of attention instruction in the right pSTS and left inferior frontal cortex (IFC), with the right pSTS classifying actions most accurately when observers attended to the action kinematics and the left IFC classifying most accurately when observed attended to the actor's goal. Functional connectivity also increased between the right pSTS and right IFC when observers attended to the actions portrayed in the vignettes. Our findings are evidence that the attentive state of the viewer modulates sensory representations in the pSTS, consistent with proposals that the pSTS occupies an interstitial zone mediating top-down context and bottom-up perceptual cues during action observation.

Distinct brain oscillatory responses for the perception and identification of one's own body from other's body

The body recognition process includes complex visual processing, the sensation, perception, and distinction stages of the stimulus. This study examined this process by using the time-frequency analysis of EEG signals and analyzed the obtained data by using the event-related oscillations method. This study aimed to examine the oscillatory brain responses and distinguish one's own body from other's body. In the present study, 17 young adults were included and the EEGs were recorded with 32 electrodes placed in different locations. Event-related power spectrum and phase-locking analyzes were performed. ITC and ERSP data were analyzed using 2 (condition) × 11 (location) × 2 (hemisphere) ANOVA Design. As we observed a prolonged response in the theta band in the grand averages, we included the time variable in the overall model. As a result, we found that the phase-locking and the event-related power spectrum of the theta response in recognizing one's own body were higher when compared to the phase-locking and the event-related power spectrum of the theta response in recognizing others' body (p < 0.05). When the time variable was included, the early theta response was more phase-locked and had a higher power spectrum compared to the late theta response (p < 0.05). As a result of the power spectrum analysis, the condition × hemisphere interaction effect in the beta band was higher in the left hemisphere regarding increased responses in recognizing one's own body (p < 0.05). As a result of ITC, the main effect of the condition was higher in the recognition of the stimulus of one's own body (p < 0.05). Finally, the theta oscillator response stood out in distinguishing one's own body from other's body. Similarly, the power spectrum in the beta response was higher in the left hemisphere, and this finding is consistent with the literature.

A Probabilistic Functional Atlas of Human Occipito-Temporal Visual Cortex

Human visual cortex contains many retinotopic and category-specific regions. These brain regions have been the focus of a large body of functional magnetic resonance imaging research, significantly expanding our understanding of visual processing. As studying these regions requires accurate localization of their cortical location, researchers perform functional localizer scans to identify these regions in each individual. However, it is not always possible to conduct these localizer scans. Here, we developed and validated a functional region of interest (ROI) atlas of early visual and category-selective regions in human ventral and lateral occipito-temporal cortex. Results show that for the majority of functionally defined ROIs, cortex-based alignment results in lower between-subject variability compared to nonlinear volumetric alignment. Furthermore, we demonstrate that 1) the atlas accurately predicts the location of an independent dataset of ventral temporal cortex ROIs and other atlases of place selectivity, motion selectivity, and retinotopy. Next, 2) we show that the majority of voxel within our atlas is responding mostly to the labeled category in a left-out subject cross-validation, demonstrating the utility of this atlas. The functional atlas is publicly available (download.brainvoyager.com/data/visfAtlas.zip) and can help identify the location of these regions in healthy subjects as well as populations (e.g., blind people, infants) in which functional localizers cannot be run.

The Functional Organization of High-Level Visual Cortex Determines the Representation of Complex Visual Stimuli

A hallmark of high-level visual cortex is its functional organization of neighboring areas that are selective for single categories, such as faces, bodies, and objects. However, visual scenes are typically composed of multiple categories. How does a category-selective cortex represent such complex stimuli? Previous studies have shown that the representation of multiple stimuli can be explained by a normalization mechanism. Here we propose that a normalization mechanism that operates in a cortical region composed of neighboring category-selective areas would generate a representation of multi-category stimuli that varies continuously across a category-selective cortex as a function of the magnitude of category selectivity for its components. By using fMRI, we can examine this correspondence between category selectivity and the representation of multi-category stimuli along a large, continuous region of cortex. To test these predictions, we used a linear model to fit the fMRI response of human participants (both sexes) to a multi-category stimulus (e.g., a whole person) based on the response to its component stimuli presented in isolation (e.g., a face or a body). Consistent with our predictions, the response of cortical areas in high-level visual cortex to multi-category stimuli varies in a continuous manner along a weighted mean line, as a function of the magnitude of its category selectivity. This was the case for both related (face + body) and unrelated (face+wardrobe) multi-category pairs. We conclude that the functional organization of neighboring category-selective areas may enable a dynamic and flexible representation of complex visual scenes that can be modulated by higher-level cognitive systems according to task demands.SIGNIFICANCE STATEMENT It is well established that the high-level visual cortex is composed of category-selective areas that reside in nearby locations. Here we predicted that this functional organization together with a normalization mechanism would generate a representation for multi-category stimuli that varies as a function of the category selectivity for its components. Consistent with this prediction, in an fMRI study we found that the representation of multi-category stimuli varies along high-level visual cortex, in a continuous manner, along a weighted mean line, in accordance with the category selectivity for a given area. These findings suggest that the functional organization of high-level visual cortex enables a flexible representation of complex scenes that can be modulated by high-level cognitive systems according to task demands.

Sulcal Depth in the Medial Ventral Temporal Cortex Predicts the Location of a Place-Selective Region in Macaques, Children, and Adults

The evolution and development of anatomical-functional relationships in the cerebral cortex is of major interest in neuroscience. Here, we leveraged the fact that a functional region selective for visual scenes is located within a sulcus in the medial ventral temporal cortex (VTC) in both humans and macaques to examine the relationship between sulcal depth and place selectivity in the medial VTC across species and age groups. To do so, we acquired anatomical and functional magnetic resonance imaging scans in 9 macaques, 26 human children, and 28 human adults. Our results revealed a strong structural-functional coupling between sulcal depth and place selectivity across age groups and species in which selectivity was strongest near the deepest sulcal point (the sulcal pit). Interestingly, this coupling between sulcal depth and place selectivity strengthens from childhood to adulthood in humans. Morphological analyses suggest that the stabilization of sulcal-functional coupling in adulthood may be due to sulcal deepening and areal expansion with age as well as developmental differences in cortical curvature at the pial, but not the white matter surfaces. Our results implicate sulcal features as functional landmarks in high-level visual cortex and highlight that sulcal-functional relationships in the medial VTC are preserved between macaques and humans despite differences in cortical folding.

Computation-Based Feature Representation of Body Expressions in the Human Brain

Humans and other primate species are experts at recognizing body expressions. To understand the underlying perceptual mechanisms, we computed postural and kinematic features from affective whole-body movement videos and related them to brain processes. Using representational similarity and multivoxel pattern analyses, we showed systematic relations between computation-based body features and brain activity. Our results revealed that postural rather than kinematic features reflect the affective category of the body movements. The feature limb contraction showed a central contribution in fearful body expression perception, differentially represented in action observation, motor preparation, and affect coding regions, including the amygdala. The posterior superior temporal sulcus differentiated fearful from other affective categories using limb contraction rather than kinematics. The extrastriate body area and fusiform body area also showed greater tuning to postural features. The discovery of midlevel body feature encoding in the brain moves affective neuroscience beyond research on high-level emotion representations and provides insights in the perceptual features that possibly drive automatic emotion perception.

Combined Neural Tuning in Human Ventral Temporal Cortex Resolves the Perceptual Ambiguity of Morphed 2D Images

We have an amazing ability to categorize objects in the world around us. Nevertheless, how cortical regions in human ventral temporal cortex (VTC), which is critical for categorization, support this behavioral ability, is largely unknown. Here, we examined the relationship between neural responses and behavioral performance during the categorization of morphed silhouettes of faces and hands, which are animate categories processed in cortically adjacent regions in VTC. Our results reveal that the combination of neural responses from VTC face- and body-selective regions more accurately explains behavioral categorization than neural responses from either region alone. Furthermore, we built a model that predicts a person's behavioral performance using estimated parameters of brain-behavior relationships from a different group of people. Moreover, we show that this brain-behavior model generalizes to adjacent face- and body-selective regions in lateral occipitotemporal cortex. Thus, while face- and body-selective regions are located within functionally distinct domain-specific networks, cortically adjacent regions from both networks likely integrate neural responses to resolve competing and perceptually ambiguous information from both categories.

Neural activity for hip-knee control in those with anterior cruciate ligament reconstruction: A task-based functional connectivity analysis

Anterior cruciate ligament injury may induce neurophysiological changes for sensorimotor control. Neuroimaging investigations have revealed unique brain activity patterns for knee movement following injury, indicating potential neural mechanisms underlying aberrant neuromuscular control that may contribute to heightened risk of secondary injury, altered movement patterns and poor patient outcomes. However, neuroimaging paradigms thus far have been limited to single joint, single motion knee tasks. Therefore, we sought to overcome prior limitations to understand the effects of injury on neural control of lower extremity movement by employing a multi-joint motor paradigm and determining differences in neural activity between ACL-reconstructed (ACLr) individuals relative to healthy matched controls. Fifteen patients with left anterior cruciate ligament reconstruction and fifteen matched healthy controls participated in this study. Neural activity was examined using functional magnetic resonance imaging during a block-designed knee-hip movement paradigm (similar to a supine heel-slide). Participants for each group were monitored and task performance was controlled via a metronome to ensure the same spatial-temporal parameters. We observed that those with ACL reconstruction displayed increased activation within the intracalcarine cortex, lingual gyrus, occipital fusiform gyrus, lateral occipital cortex, angular gyrus, and superior parietal lobule relative to controls. A follow-up task-based functional connectivity analyses using seed regions identified from the group analysis revealed connectivity among fronto-insular-temporal and sensorimotor regions within the ACLr participants. The results of this fMRI investigation suggest ACLr individuals require increased activity and connectivity in areas responsible for visual-spatial cognition and orientation, and attention for hip and knee motor control.

Processing of Real-World, Dynamic Natural Stimuli in Autism is Linked to Corticobasal Function

Many individuals with autism spectrum disorder (ASD) have been shown to perceive everyday sensory information differently compared to peers without autism. Research examining these sensory differences has primarily utilized nonnatural stimuli or natural stimuli using static photos with few having utilized dynamic, real-world nonverbal stimuli. Therefore, in this study, we used functional magnetic resonance imaging to characterize brain activation of individuals with high-functioning autism when viewing and listening to a video of a real-world scene (a person bouncing a ball) and anticipating the bounce. We investigated both multisensory and unisensory processing and hypothesized that individuals with ASD would show differential activation in (a) primary auditory and visual sensory cortical and association areas, and in (b) cortical and subcortical regions where auditory and visual information is integrated (e.g. temporal-parietal junction, pulvinar, superior colliculus). Contrary to our hypotheses, the whole-brain analysis revealed similar activation between the groups in these brain regions. However, compared to controls the ASD group showed significant hypoactivation in the left intraparietal sulcus and left putamen/globus pallidus. We theorize that this hypoactivation reflected underconnectivity for mediating spatiotemporal processing of the visual biological motion stimuli with the task demands of anticipating the timing of the bounce event. The paradigm thus may have tapped into a specific left-lateralized aberrant corticobasal circuit or loop involved in initiating or inhibiting motor responses. This was consistent with a dual "when versus where" psychophysical model of corticobasal function, which may reflect core differences in sensory processing of real-world, nonverbal natural stimuli in ASD. Autism Res 2020, 13: 539-549. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: To understand how individuals with autism perceive the real-world, using magnetic resonance imaging we examined brain activation in individuals with autism while watching a video of someone bouncing a basketball. Those with autism had similar activation to controls in auditory and visual sensory brain regions, but less activation in an area that processes information about body movements and in a region involved in modulating movements. These areas are important for understanding the actions of others and developing social skills.

Factors Determining Where Category-Selective Areas Emerge in Visual Cortex

A hallmark of functional localization in the human brain is the presence of areas in visual cortex specialized for representing particular categories such as faces and words. Why do these areas appear where they do during development? Recent findings highlight several general factors to consider when answering this question. Experience-driven category selectivity arises in regions that have: (i) pre-existing selectivity for properties of the stimulus, (ii) are appropriately placed in the computational hierarchy of the visual system, and (iii) exhibit domain-specific patterns of connectivity to nonvisual regions. In other words, cortical location of category selectivity is constrained by what category will be represented, how it will be represented, and why the representation will be used.

Differential sustained and transient temporal processing across visual streams

How do high-level visual regions process the temporal aspects of our visual experience? While the temporal sensitivity of early visual cortex has been studied with fMRI in humans, temporal processing in high-level visual cortex is largely unknown. By modeling neural responses with millisecond precision in separate sustained and transient channels, and introducing a flexible encoding framework that captures differences in neural temporal integration time windows and response nonlinearities, we predict fMRI responses across visual cortex for stimuli ranging from 33 ms to 20 s. Using this innovative approach, we discovered that lateral category-selective regions respond to visual transients associated with stimulus onsets and offsets but not sustained visual information. Thus, lateral category-selective regions compute moment-to-moment visual transitions, but not stable features of the visual input. In contrast, ventral category-selective regions process both sustained and transient components of the visual input. Our model revealed that sustained channel responses to prolonged stimuli exhibit adaptation, whereas transient channel responses to stimulus offsets are surprisingly larger than for stimulus onsets. This large offset transient response may reflect a memory trace of the stimulus when it is no longer visible, whereas the onset transient response may reflect rapid processing of new items. Together, these findings reveal previously unconsidered, fundamental temporal mechanisms that distinguish visual streams in the human brain. Importantly, our results underscore the promise of modeling brain responses with millisecond precision to understand the underlying neural computations.

How does the brain encode the timing of our visual experience? Using functional magnetic resonance imaging (fMRI) and a generative temporal model with millisecond resolution, we discovered that visual regions in the lateral and ventral processing streams fundamentally differ in their temporal processing of the visual input. Regions in lateral temporal cortex process visual transients associated with the beginning and ending of the stimulus, but not its stable aspects. That is, lateral regions appear to compute moment-to-moment changes in the visual input. In contrast, regions in ventral temporal cortex process both stable and transient components of the visual input, even as the response to the former exhibits adaptation. Surprisingly, the model predicts that in ventral regions responses to stimulus endings are larger than beginnings. We suggest that ending responses may reflect a memory trace of the stimulus, when it is no longer visible, and the beginning responses may reflect processing of new inputs. Together, these findings (i) reveal a fundamental temporal mechanism that distinguishes visual streams and (ii) highlight both the importance and utility of modeling brain responses with millisecond precision to understand the temporal dynamics of neural computations in the human brain.

Emotion modulation of the body-selective areas in the developing brain

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Passive viewing fMRI task using dynamic emotional bodies and non-human objects.

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Adults showed increased activation in the body-selective areas compared with children.

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Adults also showed more activation than adolescents, but only in the right hemisphere.

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Crucially, we found no age differences in the emotion modulation of these areas.

Emotions are strongly conveyed by the human body and the ability to recognize emotions from body posture or movement is still developing through childhood and adolescence. To date, very few studies have explored how these behavioural observations are paralleled by functional brain development. Furthermore, currently no studies have explored the development of emotion modulation in these areas. In this study, we used functional magnetic resonance imaging (fMRI) to compare the brain activity of 25 children (age 6–11), 18 adolescents (age 12–17) and 26 adults while they passively viewed short videos of angry, happy or neutral body movements. We observed that when viewing dynamic bodies generally, adults showed higher activity than children bilaterally in the body-selective areas; namely the extra-striate body area (EBA), fusiform body area (FBA), posterior superior temporal sulcus (pSTS), as well as the amygdala (AMY). Adults also showed higher activity than adolescents, but only in the right hemisphere. Crucially, however, we found that there were no age differences in the emotion modulation of activity in these areas. These results indicate, for the first time, that despite activity selective to body perception increasing across childhood and adolescence, emotion modulation of these areas in adult-like from 7 years of age.

A probabilistic atlas of the human motion complex built from large-scale functional localizer data

Accurate motion perception is critical to dealing with the changing dynamics of our visual world. A cluster known as the human MT+ complex (hMT+) has been identified as a core region involved in motion perception. Several atlases defined based on cytoarchitecture, retinotopy, connectivity, and multimodal features include homologs of the hMT+. However, an hMT+ atlas defined directly based on this region's response for motion is still lacking. Here, we identified the hMT+ based on motion responses from functional magnetic resonance imaging (fMRI) localizer data in 509 participants and then built a probabilistic atlas of the hMT+. As a result, four main findings were revealed. First, the hMT+ showed large interindividual variability across participants. Second, the atlases stabilized when the number of participants used to build the atlas was more than 100. Third, the functional hMT+ showed good agreement with the hMT+ atlases built based on cytoarchitecture, retinotopy, and connectivity, suggesting a good structural-functional correspondence. Fourth, tests on multiple fMRI data sets acquired from independent participants, imaging parameters and paradigms revealed that the functional hMT+ showed higher sensitivity than all other atlases in ROI analysis except that connectivity and multimodal hMT+ atlases in the left hemisphere could infrequently attain comparable sensitivity to the functional atlas. Taken together, our findings reveal the benefit of using large-scale functional localizer data to build a reliable and representative hMT+ atlas. Our atlas is freely available for download; it can be used to localize the hMT+ in individual participants when functional localizer data are not available.

Development of population receptive fields in the lateral visual stream improves spatial coding amid stable structural-functional coupling

Human visual cortex encompasses more than a dozen visual field maps across three major processing streams. One of these streams is the lateral visual stream, which extends from V1 to lateral-occipital (LO) and temporal-occipital (TO) visual field maps and plays a prominent role in shape as well as motion perception. However, it is unknown if and how population receptive fields (pRFs) in the lateral visual stream develop from childhood to adulthood, and what impact this development may have on spatial coding. Here, we used functional magnetic resonance imaging and pRF modeling in school-age children and adults to investigate the development of the lateral visual stream. Our data reveal four main findings: 1) The topographic organization of eccentricity and polar angle maps of the lateral stream is stable after age five. 2) In both age groups there is a reliable relationship between eccentricity map transitions and cortical folding: the middle occipital gyrus predicts the transition between the peripheral representation of LO and TO maps. 3) pRFs in LO and TO maps undergo differential development from childhood to adulthood, resulting in increasing coverage of the central visual field in LO and of the peripheral visual field in TO. 4) Model-based decoding shows that the consequence of pRF and visual field coverage development is improved spatial decoding from LO and TO distributed responses in adults vs. children. Together, these results explicate both the development and topography of the lateral visual stream. Our data show that the general structural-functional organization is laid out early in development, but fine-scale properties, such as pRF distribution across the visual field and consequently, spatial precision, become fine-tuned across childhood development. These findings advance understanding of the development of the human visual system from childhood to adulthood and provide an essential foundation for understanding developmental deficits.

Evaluating the organizational structure and specificity of network topology within the face processing system

There is increasing appreciation that network-level interactions among regions produce components of face processing previously ascribed to individual regions. Our goals were to use an exhaustive data-driven approach to derive and quantify the topology of directed functional connections within a priori defined nodes of the face processing network and evaluate whether the topology is category-specific. Young adults were scanned with fMRI as they viewed movies of faces, objects, and scenes. We employed GIMME to model effective connectivity among core and extended face processing regions, which allowed us to evaluate all possible directional connections, under each viewing condition (face, object, place). During face processing, we observed directional connections from the right posterior superior temporal sulcus to both the right occipital face area and right fusiform face area (FFA), which does not reflect the topology reported in prior studies. We observed connectivity between core and extended regions during face processing, but this limited to a feed-forward connection from the FFA to the amygdala. Finally, the topology of connections was unique to face processing. These findings suggest that the pattern of directed functional connections within the face processing network, particularly in the right core regions, may not be as hierarchical and feed-forward as described previously. Our findings support the notion that topologies of network connections are specialized, emergent, and dynamically responsive to task demands.

Action perception and motor imagery: Mental practice of action

Motor cognition is related to the planning and generation of actions as well as to the recognition and imagination of motor acts. Recently, there is evidence that the motor system participates not only in overt actions but also in mental processes supporting covert actions. Within this framework, we have investigated the cortical areas engaged in execution, observation, and imagination of the same action, by the use of the high resolution quantitative ¹⁴C-deoxyglucose method in monkeys and by fMRI in humans, throughout the entire primate brain. Our data demonstrated that observing or imagining an action excites virtually the same sensory-motor cortical network which supports execution of that same action. In general agreement with the results of five relevant meta-analyses that we discuss extensively, our results imply mental practice, i.e. internal rehearsal of the action including movements and their sensory effects. We suggest that we actively perceive and imagine actions by selecting and running off-line restored sensory-motor memories, by mentally simulating the actions. We provide empirical evidence that mental simulation of actions underlies motor cognition, and conceptual representations are grounded in sensory-motor codes. Motor cognition may, therefore, be embodied and modal. Finally, we consider questions regarding agency attribution and the possible causal or epiphenomenal role the involved sensory-motor network could play in motor cognition.

Converging Evidence From Electrocorticography and BOLD fMRI for a Sharp Functional Boundary in Superior Temporal Gyrus Related to Multisensory Speech Processing

Although humans can understand speech using the auditory modality alone, in noisy environments visual speech information from the talker’s mouth can rescue otherwise unintelligible auditory speech. To investigate the neural substrates of multisensory speech perception, we compared neural activity from the human superior temporal gyrus (STG) in two datasets. One dataset consisted of direct neural recordings (electrocorticography, ECoG) from surface electrodes implanted in epilepsy patients (this dataset has been previously published). The second dataset consisted of indirect measures of neural activity using blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI). Both ECoG and fMRI participants viewed the same clear and noisy audiovisual speech stimuli and performed the same speech recognition task. Both techniques demonstrated a sharp functional boundary in the STG, spatially coincident with an anatomical boundary defined by the posterior edge of Heschl’s gyrus. Cortex on the anterior side of the boundary responded more strongly to clear audiovisual speech than to noisy audiovisual speech while cortex on the posterior side of the boundary did not. For both ECoG and fMRI measurements, the transition between the functionally distinct regions happened within 10 mm of anterior-to-posterior distance along the STG. We relate this boundary to the multisensory neural code underlying speech perception and propose that it represents an important functional division within the human speech perception network.

Effect of Different Movement Speed Modes on Human Action Observation: An EEG Study

Action observation (AO) generates event-related desynchronization (ERD) suppressions in the human brain by activating partial regions of the human mirror neuron system (hMNS). The activation of the hMNS response to AO remains controversial for several reasons. Therefore, this study investigated the activation of the hMNS response to a speed factor of AO by controlling the movement speed modes of a humanoid robot's arm movements. Since hMNS activation is reflected by ERD suppressions, electroencephalography (EEG) with BCI analysis methods for ERD suppressions were used as the recording and analysis modalities. Six healthy individuals were asked to participate in experiments comprising five different conditions. Four incremental-speed AO tasks and a motor imagery (MI) task involving imaging of the same movement were presented to the individuals. Occipital and sensorimotor regions were selected for BCI analyses. The experimental results showed that hMNS activation was higher in the occipital region but more robust in the sensorimotor region. Since the attended information impacts the activations of the hMNS during AO, the pattern of hMNS activations first rises and subsequently falls to a stable level during incremental-speed modes of AO. The discipline curves suggested that a moderate speed within a decent inter-stimulus interval (ISI) range produced the highest hMNS activations. Since a brain computer/machine interface (BCI) builds a path-way between human and computer/mahcine, the discipline curves will help to construct BCIs made by patterns of action observation (AO-BCI). Furthermore, a new method for constructing non-invasive brain machine brain interfaces (BMBIs) with moderate AO-BCI and motor imagery BCI (MI-BCI) was inspired by this paper.

Defining the most probable location of the parahippocampal place area using cortex-based alignment and cross-validation

The parahippocampal place area (PPA) is a widely studied high-level visual region in the human brain involved in place and scene processing. The goal of the present study was to identify the most probable location of place-selective voxels in medial ventral temporal cortex. To achieve this goal, we first used cortex-based alignment (CBA) to create a probabilistic place-selective region of interest (ROI) from one group of 12 participants. We then tested how well this ROI could predict place selectivity in each hemisphere within a new group of 12 participants. Our results reveal that a probabilistic ROI (pROI) generated from one group of 12 participants accurately predicts the location and functional selectivity in individual brains from a new group of 12 participants, despite between subject variability in the exact location of place-selective voxels relative to the folding of parahippocampal cortex. Additionally, the prediction accuracy of our pROI is significantly higher than that achieved by volume-based Talairach alignment. Comparing the location of the pROI of the PPA relative to published data from over 500 participants, including data from the Human Connectome Project, shows a striking convergence of the predicted location of the PPA and the cortical location of voxels exhibiting the highest place selectivity across studies using various methods and stimuli. Specifically, the most predictive anatomical location of voxels exhibiting the highest place selectivity in medial ventral temporal cortex is the junction of the collateral and anterior lingual sulci. Methodologically, we make this pROI freely available (vpnl.stanford.edu/PlaceSelectivity), which provides a means to accurately identify a functional region from anatomical MRI data when fMRI data are not available (for example, in patient populations). Theoretically, we consider different anatomical and functional factors that may contribute to the consistent anatomical location of place selectivity relative to the folding of high-level visual cortex.

A preference for mathematical processing outweighs the selectivity for Arabic numbers in the inferior temporal gyrus

A region in the posterior inferior temporal gyrus (ITG), referred to as the number form area (NFA, here ITG-numbers) has been implicated in the visual processing of Arabic numbers. However, it is unknown if this region is specifically involved in the visual encoding of Arabic numbers per se or in mathematical processing more broadly. Using functional magnetic resonance imaging (fMRI) during experiments that systematically vary tasks and stimuli, we find that mathematical processing, not preference to Arabic numbers, consistently drives both mean and distributed responses in the posterior ITG. While we replicated findings of higher responses in ITG-numbers to numbers than other visual stimuli during a 1-back task, this preference to numbers was abolished when participants engaged in mathematical processing. In contrast, an ITG region (ITG-math) that showed higher responses during an adding task vs. other tasks maintained this preference for mathematical processing across a wide range of stimuli including numbers, number/letter morphs, hands, and dice. Analysis of distributed responses across an anatomically-defined posterior ITG expanse further revealed that mathematical task but not Arabic number form can be successfully and consistently decoded from these distributed responses. Together, our findings suggest that the function of neuronal regions in the posterior ITG goes beyond the specific visual processing of Arabic numbers. We hypothesize that they ascribe numerical content to the visual input, irrespective of the format of the stimulus.

Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans

Resting-state networks offer a unique window into the brain’s functional architecture, but their characterization remains limited to instantaneous connectivity thus far. Here, we describe a novel resting-state network based on the delayed connectivity between the brain and the slow electrical rhythm (0.05 Hz) generated in the stomach. The gastric network cuts across classical resting-state networks with partial overlap with autonomic regulation areas. This network is composed of regions with convergent functional properties involved in mapping bodily space through touch, action or vision, as well as mapping external space in bodily coordinates. The network is characterized by a precise temporal sequence of activations within a gastric cycle, beginning with somato-motor cortices and ending with the extrastriate body area and dorsal precuneus. Our results demonstrate that canonical resting-state networks based on instantaneous connectivity represent only one of the possible partitions of the brain into coherent networks based on temporal dynamics.

The brain is always active. Even when it is not receiving sensory input, it generates its own spontaneous activity. This activity shapes how we interpret future sensory signals and creates our inner mental world. Moreover, this spontaneous activity is not random. When a healthy volunteer lies inside a brain scanner without performing any task, his or her brain shows predictable patterns of activity. Specific groups of brain regions – often with related roles – become active at the same time as one another. Each set of regions is referred to as a resting state network.

Of course, the brain does not operate in isolation from the rest of the body. Our internal organs continuously send signals to the brain via the spinal cord and cranial nerves. Specialized cells in the stomach wall in particular produce a slow rhythmic pattern of electrical activity. Known as the gastric rhythm, this activity helps ensure that the stomach muscles contract at the correct speed for digestion. But the stomach also produces this rhythm even when empty, suggesting that it has other roles too.

To find out what these might be, Rebollo et al. placed electrodes on the abdomen of healthy volunteers lying inside brain scanners. By examining the volunteers’ spontaneous brain activity, Rebollo et al. identified a new resting state network that is active in synchrony with the gastric rhythm. The regions within this so-called gastric network are not active at the same time as each other, but instead become active in a specific sequence that is repeated at each gastric cycle. Many of the regions within the gastric network belong to other resting state networks too. Some of the regions help regulate automatic bodily functions such as heart rate, while others process information about the body’s position in space.

The existence of the gastric network suggests a link between the automatic regulation of processes such as digestion, and spontaneous brain activity. Future studies could examine whether this link impacts perception and cognition, and whether this link plays a role in disorders where the connection between the digestive system and the brain appears to be altered.

On object selectivity and the anatomy of the human fusiform gyrus

pFs is a functionally-defined region in the human brain that is involved in recognizing objects. A recent trend refers to pFs as the posterior fusiform sulcus, which is a neuroanatomical structure that does not exist. Here, we correct this mistake. To achieve this goal, we first recount the original definitions of pFs and then review the identification of sulci within and surrounding the fusiform gyrus (FG) including the mid-fusiform sulcus (MFS), which is a tertiary sulcus within the FG. We highlight that tertiary sulci, such as the MFS, are often absent from brain atlases, which complicates the accurate localization of functional regions, as well as the understanding of structural-functional relationships in ventral temporal cortex (VTC). When considering the location of object-selective pFs from previously published data relative to the sulci surrounding the FG, as well as the MFS, we illustrate that (1) pFs spans several macroanatomical structures, which is consistent with the original definitions of pFs (Grill-Spector et al., 1999, 2000), and (2) the topological relationship between pFs and MFS has both stable and variable features. To prevent future confusion regarding the anatomical location of functional regions within VTC, as well as to complement tools that automatically identify sulci surrounding the FG, we provide a method to automatically identify the MFS in individual brains using FreeSurfer. Finally, we highlight the benefits of using cortical surface reconstructions in large datasets to identify and quantify tertiary sulci compared to classic dissection methods because the latter often fail to differentiate tertiary sulci from shallow surface indentations produced by veins and arteries. Altogether, we propose that the inclusion of definitions and labels for tertiary sulci in neuroanatomical atlases and neuroimaging software packages will enhance understanding of functional-structural relationships throughout the human brain.

Theta synchronization over occipito-temporal cortices during visual perception of body parts

Categorical clustering in the visual system is thought to have evolved as a function of intrinsic (intra-areal) and extrinsic (interareal) connectivity and experience. In the visual system, the extrastriate body area (EBA), an occipito-temporal region, responds to full body and body part images under the organizational principle of their functional/semantic meaning. Although frequency-specific modulations of neural activity associated with perceptive and cognitive functions are increasingly attracting the interest of neurophysiologists and cognitive neuroscientists, perceiving single body parts with different functional meaning and full body images induces time-frequency modulations over occipito-temporal electrodes are yet to be described. Here, we studied this issue by measuring EEG in participants who passively observed fingers, hands, arms and faceless full body images with four control plant stimuli, each bearing hierarchical analogy with the body stimuli. We confirmed that occipito-temporal electrodes (compatible with the location of EBA) show a larger event-related potential (ERP, N190) for body-related images. Furthermore, we identified a body part-specific (i.e. selective for hands and arms) theta event-related synchronization increase under the same electrodes. This frequency modulation associated with the perception of body effectors over occipito-temporal cortices is in line with recent findings of categorical organization of neural responses to human effectors in the visual system.

Encoding model of temporal processing in human visual cortex

How is temporal information processed in human visual cortex? Visual input is relayed to V1 through segregated transient and sustained channels in the retina and lateral geniculate nucleus (LGN). However, there is intense debate as to how sustained and transient temporal channels contribute to visual processing beyond V1. The prevailing view associates transient processing predominately with motion-sensitive regions and sustained processing with ventral stream regions, while the opposing view suggests that both temporal channels contribute to neural processing beyond V1. Using fMRI, we measured cortical responses to time-varying stimuli and then implemented a two temporal channel-encoding model to evaluate the contributions of each channel. Different from the general linear model of fMRI that predicts responses directly from the stimulus, the encoding approach first models neural responses to the stimulus from which fMRI responses are derived. This encoding approach not only predicts cortical responses to time-varying stimuli from milliseconds to seconds but also, reveals differential contributions of temporal channels across visual cortex. Consistent with the prevailing view, motion-sensitive regions and adjacent lateral occipitotemporal regions are dominated by transient responses. However, ventral occipitotemporal regions are driven by both sustained and transient channels, with transient responses exceeding the sustained. These findings propose a rethinking of temporal processing in the ventral stream and suggest that transient processing may contribute to rapid extraction of the content of the visual input. Importantly, our encoding approach has vast implications, because it can be applied with fMRI to decipher neural computations in millisecond resolution in any part of the brain.

The Functional Neuroanatomy of Human Face Perception

Face perception is critical for normal social functioning and is mediated by a network of regions in the ventral visual stream. In this review, we describe recent neuroimaging findings regarding the macro- and microscopic anatomical features of the ventral face network, the characteristics of white matter connections, and basic computations performed by population receptive fields within face-selective regions composing this network. We emphasize the importance of the neural tissue properties and white matter connections of each region, as these anatomical properties may be tightly linked to the functional characteristics of the ventral face network. We end by considering how empirical investigations of the neural architecture of the face network may inform the development of computational models and shed light on how computations in the face network enable efficient face perception.

Development of Neural Sensitivity to Face Identity Correlates with Perceptual Discriminability

Face perception is subserved by a series of face-selective regions in the human ventral stream, which undergo prolonged development from childhood to adulthood. However, it is unknown how neural development of these regions relates to the development of face-perception abilities. Here, we used functional magnetic resonance imaging (fMRI) to measure brain responses of ventral occipitotemporal regions in children (ages, 5-12 years) and adults (ages, 19-34 years) when they viewed faces that parametrically varied in dissimilarity. Since similar faces generate lower responses than dissimilar faces due to fMRI adaptation, this design objectively evaluates neural sensitivity to face identity across development. Additionally, a subset of subjects participated in a behavioral experiment to assess perceptual discriminability of face identity. Our data reveal three main findings: (1) neural sensitivity to face identity increases with age in face-selective but not object-selective regions; (2) the amplitude of responses to faces increases with age in both face-selective and object-selective regions; and (3) perceptual discriminability of face identity is correlated with the neural sensitivity to face identity of face-selective regions. In contrast, perceptual discriminability is not correlated with the amplitude of response in face-selective regions or of responses of object-selective regions. These data suggest that developmental increases in neural sensitivity to face identity in face-selective regions improve perceptual discriminability of faces. Our findings significantly advance the understanding of the neural mechanisms of development of face perception and open new avenues for using fMRI adaptation to study the neural development of high-level visual and cognitive functions more broadly.

SIGNIFICANCE STATEMENT

Face perception, which is critical for daily social interactions, develops from childhood to adulthood. However, it is unknown what developmental changes in the brain lead to improved performance. Using fMRI in children and adults, we find that from childhood to adulthood, neural sensitivity to changes in face identity increases in face-selective regions. Critically, subjects' perceptual discriminability among faces is linked to neural sensitivity: participants with higher neural sensitivity in face-selective regions demonstrate higher perceptual discriminability. Thus, our results suggest that developmental increases in face-selective regions' sensitivity to face identity improve perceptual discrimination of faces. These findings significantly advance understanding of the neural mechanisms underlying the development of face perception and have important implications for assessing both typical and atypical development.

The Face-Processing Network Is Resilient to Focal Resection of Human Visual Cortex

Human face perception requires a network of brain regions distributed throughout the occipital and temporal lobes with a right hemisphere advantage. Present theories consider this network as either a processing hierarchy beginning with the inferior occipital gyrus (occipital face area; IOG-faces/OFA) or a multiple-route network with nonhierarchical components. The former predicts that removing IOG-faces/OFA will detrimentally affect downstream stages, whereas the latter does not. We tested this prediction in a human patient (Patient S.P.) requiring removal of the right inferior occipital cortex, including IOG-faces/OFA. We acquired multiple fMRI measurements in Patient S.P. before and after a preplanned surgery and multiple measurements in typical controls, enabling both within-subject/across-session comparisons (Patient S.P. before resection vs Patient S.P. after resection) and between-subject/across-session comparisons (Patient S.P. vs controls). We found that the spatial topology and selectivity of downstream ipsilateral face-selective regions were stable 1 and 8 month(s) after surgery. Additionally, the reliability of distributed patterns of face selectivity in Patient S.P. before versus after resection was not different from across-session reliability in controls. Nevertheless, postoperatively, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1 of the resected hemisphere. Diffusion weighted imaging in Patient S.P. and controls identifies white matter tracts connecting retinotopic areas to downstream face-selective regions, which may contribute to the stable and plastic features of the face network in Patient S.P. after surgery. Together, our results support a multiple-route network of face processing with nonhierarchical components and shed light on stable and plastic features of high-level visual cortex following focal brain damage.

SIGNIFICANCE STATEMENT

Brain networks consist of interconnected functional regions commonly organized in processing hierarchies. Prevailing theories predict that damage to the input of the hierarchy will detrimentally affect later stages. We tested this prediction with multiple brain measurements in a rare human patient requiring surgical removal of the putative input to a network processing faces. Surprisingly, the spatial topology and selectivity of downstream face-selective regions are stable after surgery. Nevertheless, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1. White matter connections from outside the face network may support these stable and plastic features. As processing hierarchies are ubiquitous in biological and nonbiological systems, our results have pervasive implications for understanding the construction of resilient networks.

Human-Object Interactions Are More than the Sum of Their Parts

Understanding human-object interactions is critical for extracting meaning from everyday visual scenes and requires integrating complex relationships between human pose and object identity into a new percept. To understand how the brain builds these representations, we conducted 2 fMRI experiments in which subjects viewed humans interacting with objects, noninteracting human-object pairs, and isolated humans and objects. A number of visual regions process features of human-object interactions, including object identity information in the lateral occipital complex (LOC) and parahippocampal place area (PPA), and human pose information in the extrastriate body area (EBA) and posterior superior temporal sulcus (pSTS). Representations of human-object interactions in some regions, such as the posterior PPA (retinotopic maps PHC1 and PHC2) are well predicted by a simple linear combination of the response to object and pose information. Other regions, however, especially pSTS, exhibit representations for human-object interaction categories that are not predicted by their individual components, indicating that they encode human-object interactions as more than the sum of their parts. These results reveal the distributed networks underlying the emergent representation of human-object interactions necessary for social perception.

Task alters category representations in prefrontal but not high-level visual cortex

A central question in neuroscience is how cognitive tasks affect category representations across the human brain. Regions in lateral occipito-temporal cortex (LOTC), ventral temporal cortex (VTC), and ventro-lateral prefrontal cortex (VLFPC) constitute the extended "what" pathway, which is considered instrumental for visual category processing. However, it is unknown (1) whether distributed responses across LOTC, VTC, and VLPFC explicitly represent category, task, or some combination of both, and (2) in what way representations across these subdivisions of the extended 'what' pathway may differ. To fill these gaps in knowledge, we scanned 12 participants using fMRI to test the effect of category and task on distributed responses across LOTC, VTC, and VLPFC. Results reveal that task and category modulate responses in both high-level visual regions, as well as prefrontal cortex. However, we found fundamentally different types of representations across the brain. Distributed responses in high-level visual regions are more strongly driven by category than task, and exhibit task-independent category representations. In contrast, distributed responses in prefrontal cortex are more strongly driven by task than category, and contain task-dependent category representations. Together, these findings of differential representations across the brain support a new idea that LOTC and VTC maintain stable category representations allowing efficient processing of visual information, while prefrontal cortex contains flexible representations in which category information may emerge only when relevant to the task.