A stimulus-driven approach reveals vertical luminance gradient as a stimulus feature that drives human cortical scene selectivity.

Human neuroimaging studies have revealed a dedicated cortical system for visual scene processing. But what is a "scene"? Here, we use a stimulus-driven approach to identify a stimulus feature that selectively drives cortical scene processing. Specifically, using fMRI data from BOLD5000, we examined the images that elicited the greatest response in the cortical scene processing system, and found that there is a common "vertical luminance gradient" (VLG), with the top half of a scene image brighter than the bottom half; moreover, across the entire set of images, VLG systematically increases with the neural response in the scene-selective regions (Study 1). Thus, we hypothesized that VLG is a stimulus feature that selectively engages cortical scene processing, and directly tested the role of VLG in driving cortical scene selectivity using tightly controlled VLG stimuli (Study 2). Consistent with our hypothesis, we found that the scene-selective cortical regions-but not an object-selective region or early visual cortex-responded significantly more to images of VLG over control stimuli with minimal VLG. Interestingly, such selectivity was also found for images with an "inverted" VLG, resembling the luminance gradient in night scenes. Finally, we also tested the behavioral relevance of VLG for visual scene recognition (Study 3); we found that participants even categorized tightly controlled stimuli of both upright and inverted VLG to be a place more than an object, indicating that VLG is also used for behavioral scene recognition. Taken together, these results reveal that VLG is a stimulus feature that selectively engages cortical scene processing, and provide evidence for a recent proposal that visual scenes can be characterized by a set of common and unique visual features.

A model for transforming egocentric views into goal-directed behavior.

Neurons in the rat postrhinal cortex (POR) respond to the egocentric (observer-centered) bearing and distance of the boundaries, or geometric center, of an enclosed space. Understanding of the precise geometric and sensory properties of the environment that generate these signals is limited. Here we model how this signal may relate to visual perception of motion parallax along environmental boundaries. A behavioral extension of this tuning is the known 'centering response', in which animals follow a spatial gradient function based on boundary parallax to guide behavior toward the center of a corridor or enclosure. Adding an allocentric head direction signal to this representation can translate the gradient across two-dimensional space and provide a new gradient for directing behavior to any location. We propose a model for how this signal may support goal-directed navigation via projections to the dorsomedial striatum. The result is a straightforward code for navigational variables derived from visual geometric properties of the surrounding environment, which may be used to map space and transform incoming sensory information into an appropriate motor output.

Impaired Filtering and Hyperfocusing: Neural Evidence for Distinct Selective Attention Abnormalities in People with Schizophrenia.

Although schizophrenia is classically thought to involve impaired attentional filtering, people with schizophrenia (PSZ) exhibit a more intense and more exclusive attentional focus than healthy control subjects (HCS) in many tasks. To resolve this contradiction, this functional magnetic resonance imaging study tested the impact of attentional control demands on the modulation of stimulus-induced activation in the fusiform face area and parahippocampal place area when participants (43 PSZ and 43 HCS) were looking for a target face versus house. Stimuli were presented individually, or as face-house overlays that challenged attentional control. Responses were slower for house than face stimuli and when prioritizing houses over faces in overlays, suggesting a difference in salience. Blood-oxygen-level-dependent activity reflected poorer attentional selectivity in PSZ than HCS when attentional control was challenged most, that is, when stimuli were overlaid and the task required detecting the lower-salience house target. By contrast, attentional selectivity was exaggerated in PSZ when control was challenged least, that is, when stimuli were presented sequentially and the task required detecting the higher-salience face target. These findings are consistent with 2 distinct attentional abnormalities in schizophrenia leading to impaired and exaggerated selection under different conditions: attentional control deficits, and hyperfocusing once attention has been directed toward a stimulus.

Connectivity at the origins of domain specificity in the cortical face and place networks.

It is well established that the adult brain contains a mosaic of domain-specific networks. But how do these domain-specific networks develop? Here we tested the hypothesis that the brain comes prewired with connections that precede the development of domain-specific function. Using resting-state fMRI in the youngest sample of newborn humans tested to date, we indeed found that cortical networks that will later develop strong face selectivity (including the "proto" occipital face area and fusiform face area) and scene selectivity (including the "proto" parahippocampal place area and retrosplenial complex) by adulthood, already show domain-specific patterns of functional connectivity as early as 27 d of age (beginning as early as 6 d of age). Furthermore, we asked how these networks are functionally connected to early visual cortex and found that the proto face network shows biased functional connectivity with foveal V1, while the proto scene network shows biased functional connectivity with peripheral V1. Given that faces are almost always experienced at the fovea, while scenes always extend across the entire periphery, these differential inputs may serve to facilitate domain-specific processing in each network after that function develops, or even guide the development of domain-specific function in each network in the first place. Taken together, these findings reveal domain-specific and eccentricity-biased connectivity in the earliest days of life, placing new constraints on our understanding of the origins of domain-specific cortical networks.

The parahippocampal place area and hippocampus encode the spatial significance of landmark objects.

Landmark objects are points of reference that can anchor one's internal cognitive map to the external world while navigating. They are especially useful in indoor environments where other cues such as spatial geometries are often similar across locations. We used functional magnetic resonance imaging (fMRI) and multivariate pattern analysis (MVPA) to understand how the spatial significance of landmark objects is represented in the human brain. Participants learned the spatial layout of a virtual building with arbitrary objects as unique landmarks in each room during a navigation task. They were scanned while viewing the objects before and after learning. MVPA revealed that the neural representation of landmark objects in the right parahippocampal place area (rPPA) and the hippocampus transformed systematically according to their locations. Specifically, objects in different rooms became more distinguishable than objects in the same room. These results demonstrate that rPPA and the hippocampus encode the spatial significance of landmark objects in indoor spaces.

Concavity as a diagnostic feature of visual scenes.

Despite over two decades of research on the neural mechanisms underlying human visual scene, or place, processing, it remains unknown what exactly a "scene" is. Intuitively, we are always inside a scene, while interacting with the outside of objects. Hence, we hypothesize that one diagnostic feature of a scene may be concavity, portraying "inside", and predict that if concavity is a scene-diagnostic feature, then: 1) images that depict concavity, even non-scene images (e.g., the "inside" of an object - or concave object), will be behaviorally categorized as scenes more often than those that depict convexity, and 2) the cortical scene-processing system will respond more to concave images than to convex images. As predicted, participants categorized concave objects as scenes more often than convex objects, and, using functional magnetic resonance imaging (fMRI), two scene-selective cortical regions (the parahippocampal place area, PPA, and the occipital place area, OPA) responded significantly more to concave than convex objects. Surprisingly, we found no behavioral or neural differences between images of concave versus convex buildings. However, in a follow-up experiment, using tightly-controlled images, we unmasked a selective sensitivity to concavity over convexity of scene boundaries (i.e., walls) in PPA and OPA. Furthermore, we found that even highly impoverished line drawings of concave shapes are behaviorally categorized as scenes more often than convex shapes. Together, these results provide converging behavioral and neural evidence that concavity is a diagnostic feature of visual scenes.

The Relationship between Age, Neural Differentiation, and Memory Performance.

Healthy aging is associated with decreased neural selectivity (dedifferentiation) in category-selective cortical regions. This finding has prompted the suggestion that dedifferentiation contributes to age-related cognitive decline. Consistent with this possibility, dedifferentiation has been reported to negatively correlate with fluid intelligence in older adults. Here, we examined whether dedifferentiation is associated with performance in another cognitive domain-episodic memory-that is also highly vulnerable to aging. Given the proposed role of dedifferentiation in age-related cognitive decline, we predicted there would be a stronger link between dedifferentiation and episodic memory performance in older than in younger adults. Young (18-30 years) and older (64-75 years) male and female humans underwent fMRI scanning while viewing images of objects and scenes before a subsequent recognition memory test. We computed a differentiation index in two regions of interest (ROIs): parahippocampal place area (PPA) and lateral occipital complex (LOC). This index quantified the selectivity of the BOLD response to preferred versus nonpreferred category of an ROI (scenes for PPA, objects for LOC). The differentiation index in the PPA, but not the LOC, was lower in older than in younger adults. Additionally, the PPA differentiation index predicted recognition memory performance for the studied items. This relationship was independent of and not moderated by age. The PPA differentiation index also predicted performance on a latent "fluency" factor derived from a neuropsychological test battery; this relationship was also age invariant. These findings suggest that two independent factors, one associated with age, and the other with cognitive performance, influence neural differentiation.SIGNIFICANCE STATEMENT Aging is associated with neural dedifferentiation-reduced neural selectivity in "category-selective" cortical brain regions-which has been proposed to contribute to cognitive aging. Here, we examined whether neural differentiation is predictive of episodic memory performance, and whether the relationship is moderated by age. A neural differentiation index was estimated for scene-selective (PPA) and object-selective (LOC) cortical regions while participants studied images for a subsequent memory test. Age-related reductions were observed for the PPA, but not for the LOC, differentiation index. Importantly, the PPA differentiation index demonstrated age-invariant correlations with subsequent memory performance and a fluency factor derived from a neuropsychological battery. Together, these findings suggest that neural differentiation is associated with two independent factors: age and cognitive performance.

Dissociable Neural Systems for Recognizing Places and Navigating through Them.

When entering an environment, we can use the present visual information from the scene to either recognize the kind of place it is (e.g., a kitchen or a bedroom) or navigate through it. Here we directly test the hypothesis that these two processes, what we call "scene categorization" and "visually-guided navigation", are supported by dissociable neural systems. Specifically, we manipulated task demands by asking human participants (male and female) to perform a scene categorization, visually-guided navigation, and baseline task on images of scenes, and measured both the average univariate responses and multivariate spatial pattern of responses within two scene-selective cortical regions, the parahippocampal place area (PPA) and occipital place area (OPA), hypothesized to be separably involved in scene categorization and visually-guided navigation, respectively. As predicted, in the univariate analysis, PPA responded significantly more during the categorization task than during both the navigation and baseline tasks, whereas OPA showed the complete opposite pattern. Similarly, in the multivariate analysis, a linear support vector machine achieved above-chance classification for the categorization task, but not the navigation task in PPA. By contrast, above-chance classification was achieved for both the navigation and categorization tasks in OPA. However, above-chance classification for both tasks was also found in early visual cortex and hence not specific to OPA, suggesting that the spatial patterns of responses in OPA are merely inherited from early vision, and thus may be epiphenomenal to behavior. Together, these results are evidence for dissociable neural systems involved in recognizing places and navigating through them.SIGNIFICANCE STATEMENT It has been nearly three decades since Goodale and Milner demonstrated that recognizing objects and manipulating them involve distinct neural processes. Today we show the same is true of our interactions with our environment: recognizing places and navigating through them are neurally dissociable. More specifically, we found that a scene-selective region, the parahippocampal place area, is active when participants are asked to categorize a scene, but not when asked to imagine navigating through it, whereas another scene-selective region, the occipital place area, shows the exact opposite pattern. This double dissociation is evidence for dissociable neural systems within scene processing, similar to the bifurcation of object processing described by Goodale and Milner (1992).

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.

Age-related macular degeneration changes the processing of visual scenes in the brain.

In age-related macular degeneration (AMD), the processing of fine details in a visual scene, based on a high spatial frequency processing, is impaired, while the processing of global shapes, based on a low spatial frequency processing, is relatively well preserved. The present fMRI study aimed to investigate the residual abilities and functional brain changes of spatial frequency processing in visual scenes in AMD patients. AMD patients and normally sighted elderly participants performed a categorization task using large black and white photographs of scenes (indoors vs. outdoors) filtered in low and high spatial frequencies, and nonfiltered. The study also explored the effect of luminance contrast on the processing of high spatial frequencies. The contrast across scenes was either unmodified or equalized using a root-mean-square contrast normalization in order to increase contrast in high-pass filtered scenes. Performance was lower for high-pass filtered scenes than for low-pass and nonfiltered scenes, for both AMD patients and controls. The deficit for processing high spatial frequencies was more pronounced in AMD patients than in controls and was associated with lower activity for patients than controls not only in the occipital areas dedicated to central and peripheral visual fields but also in a distant cerebral region specialized for scene perception, the parahippocampal place area. Increasing the contrast improved the processing of high spatial frequency content and spurred activation of the occipital cortex for AMD patients. These findings may lead to new perspectives for rehabilitation procedures for AMD patients.

Coding of Object Size and Object Category in Human Visual Cortex.

A salient aspect of objects is their real-world size. Large objects tend to be fixed in the world and can act as navigational barriers and landmarks, whereas small objects tend to be moveable and manipulable. Previous work has identified regions of visual cortex that respond differentially to large versus small objects, but the role of size in organizing representations of object categories has not been fully explored. To address this issue, we scanned subjects while they viewed large and small objects drawn from 20 categories, with retinotopic extent equated across size classes. Univariate analyses replicated previous results showing a greater response to large than small objects in scene-responsive regions and the converse effect in the left occipitotemporal sulcus. Critically, multivariate analyses revealed organization-by-size both within and across functional regions, as evidenced by activation patterns that were more similar for object categories of the same size than for object categories of different size. This effect was observed in both scene- and object-responsive regions and across high-level visual cortex as a whole, but not in early visual cortex. We hypothesize that real-world size is an important dimension for object category organization because of the many ecologically significant differences between large and small objects.

The Cytoarchitecture of Domain-specific Regions in Human High-level Visual Cortex.

A fundamental hypothesis in neuroscience proposes that underlying cellular architecture (cytoarchitecture) contributes to the functionality of a brain area. However, this hypothesis has not been tested in human ventral temporal cortex (VTC) that contains domain-specific regions causally involved in perception. To fill this gap in knowledge, we used cortex-based alignment to register functional regions from living participants to cytoarchitectonic areas in ex vivo brains. This novel approach reveals 3 findings. First, there is a consistent relationship between domain-specific regions and cytoarchitectonic areas: each functional region is largely restricted to 1 cytoarchitectonic area. Second, extracting cytoarchitectonic profiles from face- and place-selective regions after back-projecting each region to 20-µm thick histological sections indicates that cytoarchitectonic properties distinguish these regions from each other. Third, some cytoarchitectonic areas contain more than 1 domain-specific region. For example, face-, body-, and character-selective regions are located within the same cytoarchitectonic area. We summarize these findings with a parsimonious hypothesis incorporating how cellular properties may contribute to functional specialization in human VTC. Specifically, we link computational principles to correlated axes of functional and cytoarchitectonic segregation in human VTC, in which parallel processing across domains occurs along a lateral-medial axis while transformations of information within domain occur along an anterior-posterior axis.

Sex-linked association between cortical scene selectivity and navigational ability.

Spatial navigation is a crucial ability for living. Previous studies have shown that males are better at navigation than females, but little is known about the neural basis underlying the sex differences. In this study, we investigated whether cortical scene processing in three well-established scene-selective regions was sexually different, by examining sex differences in scene selectivity and its behavioral relevance to navigation. To do this, we used functional magnetic resonance imaging (fMRI) to scan the parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA) in a large cohort of healthy young adults viewing navigationally relevant scenes (N = 202), and correlated their neural selectivity to scenes with their self-reported navigational ability. Behaviorally, we replicated the previous finding that males were better at navigation than females. Neurally, we found that the scene selectivity in the bilateral PPA, not in the RSC or OPA, was significantly higher in males than females. Such differences could not be explained by confounding factors including brain size and fMRI data quality. Importantly, males, not females, with stronger scene selectivity in the left PPA possessed better navigational ability. This brain-behavior association could not be accounted for by non-navigational abilities (i.e., intelligence and mental rotation ability). Overall, our study provides novel empirical evidence demonstrating sex differences in the brain activity, inviting further studies on sex differences in the neural network for spatial navigation.

Attentional selection of multiple objects in the human visual system.

Classic theories of object-based attention assume a single object of selection but real-world tasks, such as driving a car, often require attending to multiple objects simultaneously. However, whether object-based attention can operate on more than one object at a time remains unexplored. Here, we used functional magnetic resonance imaging (fMRI) to address this question as human participants performed object-based attention tasks that required simultaneous attention to two objects differing in either their features or locations. Simultaneous attention to two objects differing in features (face and house) did not show significantly different responses in the fusiform face area (FFA) or parahippocampal place area (PPA), respectively, compared to attending a single object (face or house), but did enhance the response in the inferior frontal gyrus (IFG). Simultaneous attention to two circular arcs differing in locations did not show significantly different responses in the primary visual cortex (V1) compared to attending a single circular arc, but did enhance the response in the intraparietal sulcus (IPS). These results suggest that object-based attention can simultaneously select at least two objects differing in their features or locations, processes mediated by the frontal and parietal cortex, respectively.

Conjoint representation of texture ensemble and location in the parahippocampal place area.

Texture provides crucial information about the category or identity of a scene. Nonetheless, not much is known about how the texture information in a scene is represented in the brain. Previous studies have shown that the parahippocampal place area (PPA), a scene-selective part of visual cortex, responds to simple patches of texture ensemble. However, in natural scenes textures exist in spatial context within a scene. Here we tested two hypotheses that make different predictions on how textures within a scene context are represented in the PPA. The Texture-Only hypothesis suggests that the PPA represents texture ensemble (i.e., the kind of texture) as is, irrespective of its location in the scene. On the other hand, the Texture and Location hypothesis suggests that the PPA represents texture and its location within a scene (e.g., ceiling or wall) conjointly. We tested these two hypotheses across two experiments, using different but complementary methods. In experiment 1, by using multivoxel pattern analysis (MVPA) and representational similarity analysis, we found that the representational similarity of the PPA activation patterns was significantly explained by the Texture-Only hypothesis but not by the Texture and Location hypothesis. In experiment 2, using a repetition suppression paradigm, we found no repetition suppression for scenes that had the same texture ensemble but differed in location (supporting the Texture and Location hypothesis). On the basis of these results, we propose a framework that reconciles contrasting results from MVPA and repetition suppression and draw conclusions about how texture is represented in the PPA.NEW & NOTEWORTHY This study investigates how the parahippocampal place area (PPA) represents texture information within a scene context. We claim that texture is represented in the PPA at multiple levels: the texture ensemble information at the across-voxel level and the conjoint information of texture and its location at the within-voxel level. The study proposes a working hypothesis that reconciles contrasting results from multivoxel pattern analysis and repetition suppression, suggesting that the methods are complementary to each other but not necessarily interchangeable.

A Neural Basis for Developmental Topographic Disorientation.

Developmental topographic disorientation (DTD) is a life-long condition in which affected individuals are severely impaired in navigating around their environment. Individuals with DTD have no apparent structural brain damage on conventional imaging and the neural mechanisms underlying DTD are currently unknown. Using functional and diffusion tensor imaging, we present a comprehensive neuroimaging study of an individual, J.N., with well defined DTD. J.N. has intact scene-selective responses in the parahippocampal place area (PPA), transverse occipital sulcus, and retrosplenial cortex (RSC), key regions associated with scene perception and navigation. However, detailed fMRI studies probing selective tuning properties of these regions, as well as functional connectivity, suggest that J.N.'s RSC has an atypical response profile and an atypical functional coupling to PPA compared with human controls. This deviant functional profile of RSC is not due to compromised structural connectivity. This comprehensive examination suggests that the RSC may play a key role in navigation-related processing and that an alteration of the RSC's functional properties may serve as the neural basis for DTD. SIGNIFICANCE STATEMENT: Individuals with developmental topographic disorientation (DTD) have a life-long impairment in spatial navigation in the absence of brain damage, neurological conditions, or basic perceptual or memory deficits. Although progress has been made in identifying brain regions that subserve normal navigation, the neural basis of DTD is unknown. Using functional and structural neuroimaging and detailed statistical analyses, we investigated the brain regions typically involved in navigation and scene processing in a representative DTD individual, J.N. Although scene-selective regions were identified, closer scrutiny indicated that these areas, specifically the retrosplenial cortex (RSC), were functionally disrupted in J.N. This comprehensive examination of a representative DTD individual provides insight into the neural basis of DTD and the role of the RSC in navigation-related processing.

Outside Looking In: Landmark Generalization in the Human Navigational System.

The use of landmarks is central to many navigational strategies. Here we use multivoxel pattern analysis of fMRI data to understand how landmarks are coded in the human brain. Subjects were scanned while viewing the interiors and exteriors of campus buildings. Despite their visual dissimilarity, interiors and exteriors corresponding to the same building elicited similar activity patterns in the parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA), three regions known to respond strongly to scenes and buildings. Generalization across stimuli depended on knowing the correspondences among them in the PPA but not in the other two regions, suggesting that the PPA is the key region involved in learning the different perceptual instantiations of a landmark. In contrast, generalization depended on the ability to freely retrieve information from memory in RSC, and it did not depend on familiarity or cognitive task in OPA. Together, these results suggest a tripartite division of labor, whereby PPA codes landmark identity, RSC retrieves spatial or conceptual information associated with landmarks, and OPA processes visual features that are important for landmark recognition. SIGNIFICANCE STATEMENT: A central element of spatial navigation is the ability to recognize the landmarks that mark different places in the world. However, little is known about how the brain performs this function. Here we show that the parahippocampal place area (PPA), a region in human occipitotemporal cortex, exhibits key features of a landmark recognition mechanism. Specifically, the PPA treats different perceptual instantiations of the same landmark as representationally similar, but only when subjects have enough experience to know the correspondences among the stimuli. We also identify two other brain regions that exhibit landmark generalization, but with less sensitivity to familiarity. These results elucidate the brain networks involved in the learning and recognition of navigational landmarks.

Temporal Processing Capacity in High-Level Visual Cortex Is Domain Specific.

Prevailing hierarchical models propose that temporal processing capacity--the amount of information that a brain region processes in a unit time--decreases at higher stages in the ventral stream regardless of domain. However, it is unknown if temporal processing capacities are domain general or domain specific in human high-level visual cortex. Using a novel fMRI paradigm, we measured temporal capacities of functional regions in high-level visual cortex. Contrary to hierarchical models, our data reveal domain-specific processing capacities as follows: (1) regions processing information from different domains have differential temporal capacities within each stage of the visual hierarchy and (2) domain-specific regions display the same temporal capacity regardless of their position in the processing hierarchy. In general, character-selective regions have the lowest capacity, face- and place-selective regions have an intermediate capacity, and body-selective regions have the highest capacity. Notably, domain-specific temporal processing capacities are not apparent in V1 and have perceptual implications. Behavioral testing revealed that the encoding capacity of body images is higher than that of characters, faces, and places, and there is a correspondence between peak encoding rates and cortical capacities for characters and bodies. The present evidence supports a model in which the natural statistics of temporal information in the visual world may affect domain-specific temporal processing and encoding capacities. These findings suggest that the functional organization of high-level visual cortex may be constrained by temporal characteristics of stimuli in the natural world, and this temporal capacity is a characteristic of domain-specific networks in high-level visual cortex. Significance statement: Visual stimuli bombard us at different rates every day. For example, words and scenes are typically stationary and vary at slow rates. In contrast, bodies are dynamic and typically change at faster rates. Using a novel fMRI paradigm, we measured temporal processing capacities of functional regions in human high-level visual cortex. Contrary to prevailing theories, we find that different regions have different processing capacities, which have behavioral implications. In general, character-selective regions have the lowest capacity, face- and place-selective regions have an intermediate capacity, and body-selective regions have the highest capacity. These results suggest that temporal processing capacity is a characteristic of domain-specific networks in high-level visual cortex and contributes to the segregation of cortical regions.

The occipital place area represents the local elements of scenes.

Neuroimaging studies have identified three scene-selective regions in human cortex: parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA). However, precisely what scene information each region represents is not clear, especially for the least studied, more posterior OPA. Here we hypothesized that OPA represents local elements of scenes within two independent, yet complementary scene descriptors: spatial boundary (i.e., the layout of external surfaces) and scene content (e.g., internal objects). If OPA processes the local elements of spatial boundary information, then it should respond to these local elements (e.g., walls) themselves, regardless of their spatial arrangement. Indeed, we found that OPA, but not PPA or RSC, responded similarly to images of intact rooms and these same rooms in which the surfaces were fractured and rearranged, disrupting the spatial boundary. Next, if OPA represents the local elements of scene content information, then it should respond more when more such local elements (e.g., furniture) are present. Indeed, we found that OPA, but not PPA or RSC, responded more to multiple than single pieces of furniture. Taken together, these findings reveal that OPA analyzes local scene elements - both in spatial boundary and scene content representation - while PPA and RSC represent global scene properties.

Contour junctions underlie neural representations of scene categories in high-level human visual cortex.

Humans efficiently grasp complex visual environments, making highly consistent judgments of entry-level category despite their high variability in visual appearance. How does the human brain arrive at the invariant neural representations underlying categorization of real-world environments? We here show that the neural representation of visual environments in scene-selective human visual cortex relies on statistics of contour junctions, which provide cues for the three-dimensional arrangement of surfaces in a scene. We manipulated line drawings of real-world environments such that statistics of contour orientations or junctions were disrupted. Manipulated and intact line drawings were presented to participants in an fMRI experiment. Scene categories were decoded from neural activity patterns in the parahippocampal place area (PPA), the occipital place area (OPA) and other visual brain regions. Disruption of junctions but not orientations led to a drastic decrease in decoding accuracy in the PPA and OPA, indicating the reliance of these areas on intact junction statistics. Accuracy of decoding from early visual cortex, on the other hand, was unaffected by either image manipulation. We further show that the correlation of error patterns between decoding from the scene-selective brain areas and behavioral experiments is contingent on intact contour junctions. Finally, a searchlight analysis exposes the reliance of visually active brain regions on different sets of contour properties. Statistics of contour length and curvature dominate neural representations of scene categories in early visual areas and contour junctions in high-level scene-selective brain regions.