Neuroarchitecture: How the Perception of Our Surroundings Impacts the Brain

The study of neuroarchitecture is concerned with the significant effects of architecture on human behavior, emotions and thought processes. This review explores the intricate relationship between the brain and perceived environments, focusing on the roles of the anterior cingulate cortex (ACC) and parahippocampal place area (PPA) in processing architectural stimuli. It highlights the importance of mirror neurons in generating empathetic responses to our surroundings and discusses how architectural elements like lighting, color, and space layout significantly impact emotional and cognitive experiences. The review also presents insights into the concept of cognitive maps and spatial navigation, emphasizing the role of architecture in facilitating wayfinding and orientation. Additionally, it addresses how neuroarchitecture can be applied to enhance learning and healing environments, drawing upon principles from the Reggio Emilia approach and considerations for designing spaces for the elderly and those with cognitive impairments. Overall, this review offers a neuroscientific basis for understanding how human cognition, emotions, spatial navigation, and well-being are influenced by architectural design.

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.

Allocentric representation in the human amygdala and ventral visual stream

The hippocampus and the entorhinal cortex are considered the main brain structures for allocentric representation of the external environment. Here, we show that the amygdala and the ventral visual stream are involved in allocentric representation. Thirty-one young men explored 35 virtual environments during high-resolution functional magnetic resonance imaging (fMRI) of the medial temporal lobe (MTL) and were subsequently tested on recall of the allocentric pattern of the objects in each environment-in other words, the positions of the objects relative to each other and to the outer perimeter. We find increasingly unique brain activation patterns associated with increasing allocentric accuracy in distinct neural populations in the perirhinal cortex, parahippocampal cortex, fusiform cortex, amygdala, hippocampus, and entorhinal cortex. In contrast to the traditional view of a hierarchical MTL network with the hippocampus at the top, we demonstrate, using recently developed graph analyses, a hierarchical allocentric MTL network without a main connector hub.

Mapping the Scene and Object Processing Networks by Intracranial EEG

Human perception and cognition are based predominantly on visual information processing. Much of the information regarding neuronal correlates of visual processing has been derived from functional imaging studies, which have identified a variety of brain areas contributing to visual analysis, recognition, and processing of objects and scenes. However, only two of these areas, namely the parahippocampal place area (PPA) and the lateral occipital complex (LOC), were verified and further characterized by intracranial electroencephalogram (iEEG). iEEG is a unique measurement technique that samples a local neuronal population with high temporal and anatomical resolution. In the present study, we aimed to expand on previous reports and examine brain activity for selectivity of scenes and objects in the broadband high-gamma frequency range (50–150 Hz). We collected iEEG data from 27 epileptic patients while they watched a series of images, containing objects and scenes, and we identified 375 bipolar channels responding to at least one of these two categories. Using K-means clustering, we delineated their brain localization. In addition to the two areas described previously, we detected significant responses in two other scene-selective areas, not yet reported by any electrophysiological studies; namely the occipital place area (OPA) and the retrosplenial complex. Moreover, using iEEG we revealed a much broader network underlying visual processing than that described to date, using specialized functional imaging experimental designs. Here, we report the selective brain areas for scene processing include the posterior collateral sulcus and the anterior temporal region, which were already shown to be related to scene novelty and landmark naming. The object-selective responses appeared in the parietal, frontal, and temporal regions connected with tool use and object recognition. The temporal analyses specified the time course of the category selectivity through the dorsal and ventral visual streams. The receiver operating characteristic analyses identified the PPA and the fusiform portion of the LOC as being the most selective for scenes and objects, respectively. Our findings represent a valuable overview of visual processing selectivity for scenes and objects based on iEEG analyses and thus, contribute to a better understanding of visual processing in the human brain.

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.

Late Development of Navigationally Relevant Motion Processing in the Occipital Place Area

Human adults flawlessly and effortlessly navigate boundaries and obstacles in the immediately visible environment, a process we refer to as "visually guided navigation." Neuroimaging work in adults suggests this ability involves the occipital place area (OPA) [1, 2]-a scene-selective region in the dorsal stream that selectively represents information necessary for visually guided navigation [3-9]. Despite progress in understanding the neural basis of visually guided navigation, however, little is known about how this system develops. Is navigationally relevant information processing present in the first few years of life? Or does this information processing only develop after many years of experience? Although a handful of studies have found selective responses to scenes (relative to objects) in OPA in childhood [10-13], no study has explored how more specific navigationally relevant information processing emerges in this region. Here, we do just that by measuring OPA responses to first-person perspective motion information-a proxy for the visual experience of actually navigating the immediate environment-using fMRI in 5- and 8-year-old children. We found that, although OPA already responded more to scenes than objects by age 5, responses to first-person perspective motion were not yet detectable at this same age and rather only emerged by age 8. This protracted development was specific to first-person perspective motion through scenes, not motion on faces or objects, and was not found in other scene-selective regions (the parahippocampal place area or retrosplenial complex) or a motion-selective region (MT). These findings therefore suggest that navigationally relevant information processing in OPA undergoes prolonged development across childhood.

Human Scene-Selective Areas Represent 3D Configurations of Surfaces

It has been argued that scene-selective areas in the human brain represent both the 3D structure of the local visual environment and low-level 2D features (such as spatial frequency) that provide cues for 3D structure. To evaluate the degree to which each of these hypotheses explains variance in scene-selective areas, we develop an encoding model of 3D scene structure and test it against a model of low-level 2D features. We fit the models to fMRI data recorded while subjects viewed visual scenes. The fit models reveal that scene-selective areas represent the distance to and orientation of large surfaces, at least partly independent of low-level features. Principal component analysis of the model weights reveals that the most important dimensions of 3D structure are distance and openness. Finally, reconstructions of the stimuli based on the model weights demonstrate that our model captures unprecedented detail about the local visual environment from scene-selective areas.

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).

Neural Codes for One's Own Position and Direction in a Real-World "Vista" Environment

Humans, like animals, rely on an accurate knowledge of one’s spatial position and facing direction to keep orientated in the surrounding space. Although previous neuroimaging studies demonstrated that scene-selective regions (the parahippocampal place area or PPA, the occipital place area or OPA and the retrosplenial complex or RSC), and the hippocampus (HC) are implicated in coding position and facing direction within small-(room-sized) and large-scale navigational environments, little is known about how these regions represent these spatial quantities in a large open-field environment. Here, we used functional magnetic resonance imaging (fMRI) in humans to explore the neural codes of these navigationally-relevant information while participants viewed images which varied for position and facing direction within a familiar, real-world circular square. We observed neural adaptation for repeated directions in the HC, even if no navigational task was required. Further, we found that the amount of knowledge of the environment interacts with the PPA selectivity in encoding positions: individuals who needed more time to memorize positions in the square during a preliminary training task showed less neural attenuation in this scene-selective region. We also observed adaptation effects, which reflect the real distances between consecutive positions, in scene-selective regions but not in the HC. When examining the multi-voxel patterns of activity we observed that scene-responsive regions and the HC encoded both spatial information and that the RSC classification accuracy for positions was higher in individuals scoring higher to a self-reported questionnaire of spatial abilities. Our findings provide new insight into how the human brain represents a real, large-scale “vista” space, demonstrating the presence of neural codes for position and direction in both scene-selective and hippocampal regions, and revealing the existence, in the former regions, of a map-like spatial representation reflecting real-world distance between consecutive positions.

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.

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.

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.

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.

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.

Functional connectivity constrains the category-related organization of human ventral occipitotemporal cortex

One of the most robust and oft-replicated findings in cognitive neuroscience is that several spatially distinct, functionally dissociable ventral occipitotemporal cortex (VOTC) regions respond preferentially to different categories of concrete entities. However, the determinants of this category-related organization remain to be fully determined. One recent proposal is that privileged connectivity of these VOTC regions with other regions that store and/or process category-relevant properties may be a major contributing factor. To test this hypothesis, we used a multicategory functional magnetic resonance imaging (MRI) localizer to individually define category-related brain regions of interest (ROIs) in a large group of subjects (n = 33). We then used these ROIs in resting-state functional connectivity MRI analyses to explore spontaneous functional connectivity among these regions. We demonstrate that during rest, distinct category-preferential VOTC regions show differentially stronger functional connectivity with other regions that have congruent category-preference, as defined by the functional localizer. Importantly, a "tool"-preferential region in the left medial fusiform gyrus showed differentially stronger functional connectivity with other left lateralized cortical regions associated with perceiving and knowing about common tools-posterior middle temporal gyrus (involved in perception of nonbiological motion), lateral parietal cortex (critical for reaching, grasping, manipulating), and ventral premotor cortex (involved in storing/executing motor programs)-relative to other category-related regions in VOTC of both the right and left hemisphere. Our findings support the claim that privileged connectivity with other cortical regions that store and/or process category-relevant properties constrains the category-related organization of VOTC.

Applying artificial vision models to human scene understanding

How do we understand the complex patterns of neural responses that underlie scene understanding? Studies of the network of brain regions held to be scene-selective—the parahippocampal/lingual region (PPA), the retrosplenial complex (RSC), and the occipital place area (TOS)—have typically focused on single visual dimensions (e.g., size), rather than the high-dimensional feature space in which scenes are likely to be neurally represented. Here we leverage well-specified artificial vision systems to explicate a more complex understanding of how scenes are encoded in this functional network. We correlated similarity matrices within three different scene-spaces arising from: (1) BOLD activity in scene-selective brain regions; (2) behavioral measured judgments of visually-perceived scene similarity; and (3) several different computer vision models. These correlations revealed: (1) models that relied on mid- and high-level scene attributes showed the highest correlations with the patterns of neural activity within the scene-selective network; (2) NEIL and SUN—the models that best accounted for the patterns obtained from PPA and TOS—were different from the GIST model that best accounted for the pattern obtained from RSC; (3) The best performing models outperformed behaviorally-measured judgments of scene similarity in accounting for neural data. One computer vision method—NEIL (“Never-Ending-Image-Learner”), which incorporates visual features learned as statistical regularities across web-scale numbers of scenes—showed significant correlations with neural activity in all three scene-selective regions and was one of the two models best able to account for variance in the PPA and TOS. We suggest that these results are a promising first step in explicating more fine-grained models of neural scene understanding, including developing a clearer picture of the division of labor among the components of the functional scene-selective brain network.

Distributed cognitive maps reflecting real distances between places and views in the human brain

KEEPING ORIENTED IN THE ENVIRONMENT IS A MULTIFACETED ABILITY THAT REQUIRES KNOWLEDGE OF AT LEAST THREE PIECES OF INFORMATION: one's own location ("place") and orientation ("heading") within the environment, and which location in the environment one is looking at ("view"). We used functional magnetic resonance imaging (fMRI) in humans to examine the neural signatures of these information. Participants were scanned while viewing snapshots which varied for place, view and heading within a virtual room. We observed adaptation effects, proportional to the physical distances between consecutive places and views, in scene-responsive (retrosplenial complex and parahippocampal gyrus), fronto-parietal and lateral occipital regions. Multivoxel pattern classification of signals in scene-responsive regions and in the hippocampus allowed supra-chance decoding of place, view and heading, and revealed the existence of map-like representations, where places and views closer in physical space entailed activity patterns more similar in neural representational space. The pattern of hippocampal activity reflected both view- and place-based distances, the pattern of parahippocampal activity preferentially discriminated between views, and the pattern of retrosplenial activity combined place and view information, while the fronto-parietal cortex only showed transient effects of changes in place, view, and heading. Our findings provide evidence for the presence of map-like spatial representations which reflect metric distances in terms of both one's own and landmark locations.

Evidence for participation by object-selective visual cortex in scene category judgments

Scene recognition is a core function of the visual system, drawing both on scenes' intrinsic global features, prominently their spatial properties, and on the identities of the objects scenes contain. Neuroimaging and neuropsychological studies have associated spatial property-based scene categorization with parahippocampal cortex, while processing of scene-relevant object information is associated with the lateral occipital complex (LOC), wherein activity patterns distinguish between categories of standalone objects and those embedded in scenes. However, despite the importance of objects to scene categorization and the role of LOC in processing them, damage or disruption to LOC that hampers object recognition has been shown to improve scene categorization. To address this paradox, we used functional magnetic resonance imaging (fMRI) to directly assess the contributions of LOC and the parahippocampal place area (PPA) to category judgments of indoor scenes that were devoid of objective identity signals. Observers were alternately cued to base judgments on scenes' objects or spatial properties. In both LOC and PPA, multivoxel activity patterns better decoded judgments based on their typically associated features: LOC more accurately decoded object-based judgments, while PPA more accurately decoded spatial property-based judgments. The cue contingency of LOC decoding accuracy indicates that it was not an outcome of feedback from judgments and is instead consistent with dependency of judgments on the output of object processing pathways in which LOC participates.

Thinking outside the box: rectilinear shapes selectively activate scene-selective cortex

Fifteen years ago, an intriguing area was found in human visual cortex. This area (the parahippocampal place area [PPA]) was initially interpreted as responding selectively to images of places. However, subsequent studies reported that PPA also responds strongly to a much wider range of image categories, including inanimate objects, tools, spatial context, landmarks, objectively large objects, indoor scenes, and/or isolated buildings. Here, we hypothesized that PPA responds selectively to a lower-level stimulus property (rectilinear features), which are common to many of the above higher-order categories. Using a novel wavelet image filter, we first demonstrated that rectangular features are common in these diverse stimulus categories. Then we tested whether PPA is selectively activated by rectangular features in six independent fMRI experiments using progressively simplified stimuli, from complex real-world images, through 3D/2D computer-generated shapes, through simple line stimuli. We found that PPA was consistently activated by rectilinear features, compared with curved and nonrectangular features. This rectilinear preference was (1) comparable in amplitude and selectivity, relative to the preference for category (scenes vs faces), (2) independent of known biases for specific orientations and spatial frequency, and (3) not predictable from V1 activity. Two additional scene-responsive areas were sensitive to a subset of rectilinear features. Thus, rectilinear selectivity may serve as a crucial building block for category-selective responses in PPA and functionally related areas.

Seeing scenes: topographic visual hallucinations evoked by direct electrical stimulation of the parahippocampal place area

In recent years, functional neuroimaging has disclosed a network of cortical areas in the basal temporal lobe that selectively respond to visual scenes, including the parahippocampal place area (PPA). Beyond the observation that lesions involving the PPA cause topographic disorientation, there is little causal evidence linking neural activity in that area to the perception of places. Here, we combined functional magnetic resonance imaging (fMRI) and intracranial EEG (iEEG) recordings to delineate place-selective cortex in a patient implanted with stereo-EEG electrodes for presurgical evaluation of drug-resistant epilepsy. Bipolar direct electrical stimulation of a cortical area in the collateral sulcus and medial fusiform gyrus, which was place-selective according to both fMRI and iEEG, induced a topographic visual hallucination: the patient described seeing indoor and outdoor scenes that included views of the neighborhood he lives in. By contrast, stimulating the more lateral aspect of the basal temporal lobe caused distortion of the patient's perception of faces, as recently reported (Parvizi et al., 2012). Our results support the causal role of the PPA in the perception of visual scenes, demonstrate that electrical stimulation of higher order visual areas can induce complex hallucinations, and also reaffirm direct electrical brain stimulation as a tool to assess the function of the human cerebral cortex.

The neural bases of spatial frequency processing during scene perception

Theories on visual perception agree that scenes are processed in terms of spatial frequencies. Low spatial frequencies (LSF) carry coarse information whereas high spatial frequencies (HSF) carry fine details of the scene. However, how and where spatial frequencies are processed within the brain remain unresolved questions. The present review addresses these issues and aims to identify the cerebral regions differentially involved in low and high spatial frequency processing, and to clarify their attributes during scene perception. Results from a number of behavioral and neuroimaging studies suggest that spatial frequency processing is lateralized in both hemispheres, with the right and left hemispheres predominantly involved in the categorization of LSF and HSF scenes, respectively. There is also evidence that spatial frequency processing is retinotopically mapped in the visual cortex. HSF scenes (as opposed to LSF) activate occipital areas in relation to foveal representations, while categorization of LSF scenes (as opposed to HSF) activates occipital areas in relation to more peripheral representations. Concomitantly, a number of studies have demonstrated that LSF information may reach high-order areas rapidly, allowing an initial coarse parsing of the visual scene, which could then be sent back through feedback into the occipito-temporal cortex to guide finer HSF-based analysis. Finally, the review addresses spatial frequency processing within scene-selective regions areas of the occipito-temporal cortex.

Encoding-Stage Crosstalk Between Object- and Spatial Property-Based Scene Processing Pathways

Scene categorization draws on 2 information sources: The identities of objects scenes contain and scenes' intrinsic spatial properties. Because these resources are formally independent, it is possible for them to leads to conflicting judgments of scene category. We tested the hypothesis that the potential for such conflicts is mitigated by a system of "crosstalk" between object- and spatial layout-processing pathways, under which the encoded spatial properties of scenes are biased by scenes' object contents. Specifically, we show that the presence of objects strongly associated with a given scene category can bias the encoded spatial properties of scenes containing them toward the average of that category, an effect which is evident both in behavioral measures of scenes' perceived spatial properties and in scene-evoked multivoxel patterns recorded with functional magnetic resonance imaging from the parahippocampal place area (PPA), a region associated with the processing of scenes' spatial properties. These results indicate that harmonization of object- and spatial property-based estimates of scene identity begins when spatial properties are encoded, and that the PPA plays a central role in this process.

Neural mechanisms of object-based attention

What neural mechanisms underlie the ability to attend to a complex object in the presence of competing overlapping stimuli? We evaluated whether object-based attention might involve pattern-specific feedback to early visual areas to selectively enhance the set of low-level features corresponding to the attended object. Using fMRI and multivariate pattern analysis, we found that activity patterns in early visual areas (V1-V4) are strongly biased in favor of the attended object. Activity patterns evoked by single faces and single houses reliably predicted which of the 2 overlapping stimulus types was being attended with high accuracy (80-90% correct). Superior knowledge of upright objects led to improved attentional selection in early areas. Across individual blocks, the strength of the attentional bias signal in early visual areas was highly predictive of the modulations found in high-level object areas, implying that pattern-specific attentional filtering at early sites can determine the quality of object-specific signals that reach higher level visual areas. Through computational modeling, we show how feedback of an average template to V1-like units can improve discrimination of exemplars belonging to the attended category. Our findings provide a mechanistic account of how feedback to early visual areas can contribute to the attentional selection of complex objects.

Differential connectivity within the Parahippocampal Place Area

The Parahippocampal Place Area (PPA) has traditionally been considered a homogeneous region of interest, but recent evidence from both human studies and animal models has suggested that PPA may be composed of functionally distinct subunits. To investigate this hypothesis, we utilize a functional connectivity measure for fMRI that can estimate connectivity differences at the voxel level. Applying this method to whole-brain data from two experiments, we provide the first direct evidence that anterior and posterior PPA exhibit distinct connectivity patterns, with anterior PPA more strongly connected to regions in the default mode network (including the parieto-medial temporal pathway) and posterior PPA more strongly connected to occipital visual regions. We show that object sensitivity in PPA also has an anterior-posterior gradient, with stronger responses to abstract objects in posterior PPA. These findings cast doubt on the traditional view of PPA as a single coherent region, and suggest that PPA is composed of one subregion specialized for the processing of low-level visual features and object shape, and a separate subregion more involved in memory and scene context.

Neural indices of improved attentional modulation over middle childhood

The ability to control the focus of attention relies on top-down modulation of cortical activity in areas involved in stimulus processing, and this ability is critical for maintaining items in working memory in the presence of distraction. Prior research demonstrates that children are less capable of focusing attention, relative to adults, and that this ability develops significantly during middle childhood. Here, using fMRI and a face/scene working memory task adapted from Gazzaley and colleagues (Gazzaley et al. 2005), we compared top-down modulation in fifteen children (aged 8-13) and fifteen young adults (aged 19-26). Replicating prior results, in young adults, attention to scenes modulated activity in the parahippocampal place area (PPA). In addition, modulation of PPA activity increased as a function of age in children. PPA activity was also related to performance in this group, on the working memory task as well on a test of subsequent memory. Dorsolateral PFC also demonstrated increasing task-specific activation, as a function of age, in children. The present findings support the idea that children's reduced ability to maintain items in working memory, especially in the presence of distraction, is driven by weaker top-down modulation of activity in areas involved in stimulus processing.

Multiple object properties drive scene-selective regions

Neuroimaging studies have identified brain regions that respond preferentially to specific stimulus categories, including 3 areas that activate maximally during viewing of real-world scenes: The parahippocampal place area (PPA), retrosplenial complex (RSC), and transverse occipital sulcus (TOS). Although these findings suggest the existence of regions specialized for scene processing, this interpretation is challenged by recent reports that activity in scene-preferring regions is modulated by properties of isolated single objects. To understand the mechanisms underlying these object-related responses, we collected functional magnetic resonance imaging data while subjects viewed objects rated along 7 dimensions, shown both in isolation and on a scenic background. Consistent with previous reports, we find that scene-preferring regions are sensitive to multiple object properties; however, results of an item analysis suggested just 2 independent factors--visual size and the landmark suitability of the objects--sufficed to explain most of the response. This object-based modulation was found in PPA and RSC irrespective of the presence or absence of a scenic background, but was only observed in TOS for isolated objects. We hypothesize that scene-preferring regions might process both visual qualities unique to scenes and spatial qualities that can appertain to either scenes or objects.

The Internal Anticipation of Sensory Action Effects: When Action Induces FFA and PPA Activity

Voluntary action – in particular the ability to produce desired effects in the environment – is fundamental to human existence. According to ideomotor theory we can achieve goals in the environment by means of anticipating their outcomes. We aimed at providing neurophysiological evidence for the assumption that performing actions calls for the activation of brain areas associated with the sensory effects usually evoked by the actions. We conducted an fMRI study in which right and left button presses lead to the presentation of face and house pictures. We compared a baseline phase with the same phase after participants experienced the association between button presses and pictures. We found an increase in the parahippocampal place area (PPA) for the response that has been associated with house pictures and fusiform face area (FFA) for the response that has been coupled with face pictures. This observation constitutes support for ideomotor theory.

Location, Location, Location: Alterations in the Functional Topography of Face- but not Object- or Place-Related Cortex in Adolescents with Autism

In autism, impairments in face processing are a relatively recent discovery, but have quickly become a widely accepted aspect of the behavioral profile. Only a handful of studies have investigated potential atypicalities in autism in the development of the neural substrates mediating face processing. High-functioning individuals with autism (HFA) and matched typically developing (TD) controls watched dynamic movie vignettes of faces, common objects, buildings, and scenes of navigation while undergoing an fMRI scan. With these data, we mapped the functional topography of category-selective activation for faces bilaterally in the fusiform gyrus, occipital face area, and posterior superior temporal sulcus. Additionally, we mapped category-selective activation for objects in the lateral occipital area and for places in the parahippocampal place area in the two groups. Our findings do not indicate a generalized disruption in the development of the entire ventral visual pathway in autism. Instead, our results suggest that the functional topography of face-related cortex is selectively disrupted in autism and that this alteration is present in early adolescence. Furthermore, for those HFA adolescents who do exhibit face-selective activation, this activation tends to be located in traditionally object-related regions, which supports the hypothesis that perceptual processing of faces in autism may be more akin to the perceptual processing of common objects in TD individuals.

Differential development of the ventral visual cortex extends through adolescence

The ventral temporal cortex (VTC) in humans includes functionally defined regions that preferentially respond to objects, faces, and places. Recent developmental studies suggest that the face selective region in the fusiform gyrus (‘fusiform face area’, FFA) undergoes a prolonged development involving substantial increases in its volume after 7 years of age. However, the endpoint of this development is not known. Here we used functional magnetic resonance imaging (fMRI) to examine the development of face-, object- and place selective regions in the VTC of adolescents (12–16 year olds) and adults (18–40 year olds). We found that the volume of face selective activations in the right fusiform gyrus was substantially larger in adults than in adolescents, and was positively correlated with age. This development was associated with higher response amplitudes and selectivity for faces in face selective regions of VTC and increased differentiation of the distributed response patterns to faces versus non-face stimuli across the entire VTC. Furthermore, right FFA size was positively correlated with face recognition memory performance, but not with recognition memory of objects or places. In contrast, the volume of object- and place selective cortical regions or their response amplitudes did not change across these age groups. Thus, we found a striking and prolonged development of face selectivity across the VTC during adolescence that was specifically associated with proficiency in face recognition memory. These findings have important implications for theories of development and functional specialization in VTC.

How reliable are visual context effects in the parahippocampal place area?

The parahippocampal place area (PPA) is a region of human cortex that responds more strongly to visual scenes (e.g., landscapes or cityscapes) than to other visual stimuli. It has been proposed that the primary function of the PPA is encoding of contextual information about object co-occurrence. Supporting this context hypothesis are reports that the PPA responds more strongly to strong-context than to weak-context objects and more strongly to famous faces (for which contextual associations are available) than to nonfamous faces. We reexamined the reliability of these 2 effects by scanning subjects with functional magnetic resonance imaging while they viewed strong- and weak-context objects, scrambled versions of these objects, and famous and nonfamous faces. "Contextual" effects for objects were observed to be reliable in the PPA at slow presentation rates but not at faster presentation rates intended to discourage scene imagery. We were unable to replicate the earlier finding of preferential PPA response to famous versus nonfamous faces. These results are difficult to reconcile with the hypothesis that the PPA encodes contextual associations but are consistent with a competing hypothesis that the PPA encodes scenic layout.