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.

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.

Cytoarchitectonic parcellation and functional characterization of four new areas in the caudal parahippocampal cortex.

Brain areas at the parahippocampal gyrus of the temporal-occipital transition region are involved in different functions including processing visual-spatial information and episodic memory. Results of neuroimaging experiments have revealed a differentiated functional parcellation of this region, but its microstructural correlates are less well understood. Here we provide probability maps of four new cytoarchitectonic areas, Ph1, Ph2, Ph3 and CoS1 at the parahippocampal gyrus and collateral sulcus. Areas have been identified based on an observer-independent mapping of serial, cell-body stained histological sections of ten human postmortem brains. They have been registered to two standard reference spaces, and superimposed to capture intersubject variability. The comparison of the maps with functional imaging data illustrates the different involvement of the new areas in a variety of functions. Maps are available as part of Julich-Brain atlas and can be used as anatomical references for future studies to better understand relationships between structure and function of the caudal parahippocampal cortex.

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.

Three cortical scene systems and their development.

Since the discovery of three scene-selective regions in the human brain, a central assumption has been that all three regions directly support navigation. We propose instead that cortical scene processing regions support three distinct computational goals (and one not for navigation at all): (i) The parahippocampal place area supports scene categorization, which involves recognizing the kind of place we are in; (ii) the occipital place area supports visually guided navigation, which involves finding our way through the immediately visible environment, avoiding boundaries and obstacles; and (iii) the retrosplenial complex supports map-based navigation, which involves finding our way from a specific place to some distant, out-of-sight place. We further hypothesize that these systems develop along different timelines, with both navigation systems developing slower than the scene categorization system.

Lower-Resolution Retrieval of Scenes in Older Adults With Subjective Cognitive Decline.

OBJECTIVE: Scenes with more perceptual detail can help detect subtle memory deficits more than scenes with less detail. Here, we investigated whether older adults with subjective cognitive decline (SCD) show less brain activation and more memory deficits to scenes with more (vs. scenes with less) perceptual detail compared to controls (CON). METHOD: In 37 healthy older adults (SCD: 16), we measured blood oxygenation level-dependent-functional magnetic resonance imaging during encoding and behavioral performance during retrieval. RESULTS: During encoding, higher activation to scenes with more (vs. less) perceptual detail in the parahippocampal place area predicted better memory performance in SCD and CON. During retrieval, superior performance for new scenes with more (vs. less) perceptual detail was significantly more pronounced in CON than inSCD. CONCLUSIONS: Together, these results suggest a present, but attenuated benefit from perceptual detail for memory retrieval in SCD. Memory complaints in SCD might, thus, refer to a decreased availability of perceptual detail of previously encoded stimuli.

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.

Interdependent self-construal predicts increased gray matter volume of scene processing regions in the brain.

Interdependent self-construal (SC) is thought to lead to a more holistic cognitive style that emphasizes the processing of the background scene of a focal object. At present, little is known about whether the structural properties of the brain might underlie this functional relationship. Here, we examined the gray matter (GM) volume of three cortical regions involved in scene processing -- a cornerstone of contextual processing. Study 1 tested 78 European American non-student adults and found that interdependent (vs. independent) SC predicts higher GM volume in the parahippocampal place area (PPA), one of the three target regions. Testing both European American and East Asian college students (total N = 126), Study 2 replicated this association. Moreover, the GM volume of all the three target regions was greater for East Asians than for European Americans. Our findings suggest that there is a structural neural underpinning for the cultural variation in cognitive style.

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.

Functions of ventral visual cortex after bilateral medial temporal lobe damage.

Repeated stimuli elicit attenuated responses in visual cortex relative to novel stimuli. This adaptation can be considered as a form of rapid learning and a signature of perceptual memory. Adaptation occurs not only when a stimulus is repeated immediately, but also when there is a lag in terms of time and other intervening stimuli before the repetition. But how does the visual system keep track of which stimuli are repeated, especially after long delays and many intervening stimuli? We hypothesized that the hippocampus and medial temporal lobe (MTL) support long-lag adaptation, given that this memory system can learn from single experiences, maintain information over delays, and send feedback to visual cortex. We tested this hypothesis with fMRI in an amnesic patient, LSJ, who has encephalitic damage to the MTL resulting in extensive bilateral lesions including complete hippocampal loss. We measured adaptation at varying time lags between repetitions in functionally localized visual areas that were intact in LSJ. We observed that these areas track information over a few minutes even when the hippocampus and extended parts of the MTL are unavailable. LSJ and controls were identical when attention was directed away from the repeating stimuli: adaptation occurred for lags up to three minutes, but not six minutes. However, when attention was directed toward stimuli, controls now showed an adaptation effect at six minutes but LSJ did not. These findings suggest that visual cortex can support one-shot perceptual memories lasting for several minutes but that the hippocampus and surrounding MTL structures are necessary for adaptation in visual cortex after longer delays when stimuli are task-relevant.

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.

Impaired behavioral and neural representation of scenes in Williams syndrome.

Boundaries are crucial to our representation of the geometric shape of scenes, which can be used to reorient in space. Behavioral research has shown that children and adults share exquisite sensitivity to a defining feature of a boundary: its vertical extent. Imaging studies have shown that this boundary property is represented in the parahippocampal place area (PPA) among typically developed (TD) adults. Here, we show that sensitivity to the vertical extent of scene boundaries is impaired at both the behavioral and neural level in people with Williams syndrome (WS), a genetic deficit that results in severely impaired spatial functions. Behavioral reorientation was tested in three boundary conditions: a flat Mat, a 5 cm high Curb, and full Walls. Adults with WS could reorient in a rectangular space defined by Wall boundaries, but not Curb or Mat boundaries. In contrast, TD age-matched controls could reorient by all three boundary types and TD 4-year-olds could reorient by either Wall or Curb boundaries. Using fMRI, we find that the WS behavioral deficit is echoed in their neural representation of boundaries. While TD age-matched controls showed distinct neural responses to scenes depicting Mat, Curb, and Wall boundaries in the PPA, people with WS showed only a distinction between the Wall and Mat or Curb, but no distinction between the Mat and Curb. Taken together, these results reveal a close coupling between the representation of boundaries as they are used in behavioral reorientation and neural encoding, suggesting that damage to this key element of spatial representation may have a genetic foundation.

Parsing rooms: the role of the PPA and RSC in perceiving object relations and spatial layout.

The perception of a scene involves grasping the global space of the scene, usually called the spatial layout, as well as the objects in the scene and the relations between them. The main brain areas involved in scene perception, the parahippocampal place area (PPA) and retrosplenial cortex (RSC), are supposed to mostly support the processing of spatial layout. Here we manipulated the objects and their relations either by arranging objects within rooms in a common way or by scattering them randomly. The rooms were then varied for spatial layout by keeping or removing the walls of the room, a typical layout manipulation. We then combined a visual search paradigm, where participants actively search for an object within the room, with multivariate pattern analysis (MVPA). Both left and right PPA were sensitive to the layout properties, but the right PPA was also sensitive to the object relations even when the information about objects and their relations is used in the cross-categorization procedure on novel stimuli. The left and right RSC were sensitive to both spatial layout and object relations, but could only use the information about object relations for cross-categorization to novel stimuli. These effects were restricted to the PPA and RSC, as other control brain areas did not display the same pattern of results. Our results underline the importance of employing paradigms that require participants to explicitly retrieve domain-specific processes and indicate that objects and their relations are processed in the scene areas to a larger extent than previously assumed.

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.

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.

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).