Neural compass in the human brain during naturalistic virtual navigation.

Humans and animals maintain a consistent representation of their facing direction during spatial navigation. In rodents, head direction cells are believed to support this "neural compass", but identifying a similar mechanism in humans during dynamic naturalistic navigation has been challenging. To address this issue, we acquired fMRI data while participants freely navigated through a virtual reality city. Encoding model analyses revealed voxel clusters in retrosplenial complex and superior parietal lobule that exhibited reliable tuning as a function of facing direction. Crucially, these directional tunings were consistent across perceptually different versions of the city, spatially separated locations within the city, and motivationally distinct phases of the behavioral task. Analysis of the model weights indicated that these regions may represent facing direction relative to the principal axis of the environment. These findings reveal specific mechanisms in the human brain that allow us to maintain a sense of direction during naturalistic, dynamic navigation.

The format of the cognitive map depends on the structure of the environment.

Humans and animals form cognitive maps that allow them to navigate through large-scale environments. Here we address a central unresolved question about these maps: whether they exhibit similar characteristics across all environments, or-alternatively-whether different environments yield different types of maps. To investigate this question, we examined spatial learning in three virtual environments: an open courtyard with patios connected by paths (open maze), a set of rooms connected by corridors (closed maze), and a set of isolated rooms connected only by teleporters (teleport maze). All three environments shared the same underlying topological graph structure. Postlearning tests showed that participants formed representations of the three environments that varied in accuracy, format, and individual variability. The open maze was most accurately remembered, followed by the closed maze, and then the teleport maze. In the open maze, most participants developed representations that reflected the Euclidean structure of the space, whereas in the teleport maze, most participants constructed representations that aligned more closely with a mental model of an interconnected graph. In the closed maze, substantial individual variability emerged, with some participants forming Euclidean representations and others forming graph-like representations. These results indicate that an environment's features shape the quality and nature of the spatial representations formed within it, determining whether spatial knowledge takes a Euclidean or graph-like format. Consequently, experimental findings obtained in any single environment may not generalize to others with different features. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Recruitment of grid-like responses in human entorhinal and piriform cortices by odor landmark-based navigation.

Olfactory navigation is universal across the animal kingdom. Humans, however, have rarely been considered in this context. Here, we combined olfactometry techniques, virtual reality (VR) software, and neuroimaging methods to investigate whether humans can navigate an olfactory landscape by learning the spatial relationships among discrete odor cues and integrating this knowledge into a spatial map. Our data show that over time, participants improved their performance on the odor navigation task by taking more direct paths toward targets and completing more trials within a given time period. This suggests that humans can successfully navigate a complex odorous environment, reinforcing the notion of human olfactory navigation. fMRI data collected during the olfactory navigation task revealed the emergence of grid-like responses in entorhinal and piriform cortices that were attuned to the same grid orientation. This result implies the existence of a specialized olfactory grid network tasked with guiding spatial navigation based on odor landmarks.

Distinct neural mechanisms for heading retrieval and context recognition in the hippocampus during spatial reorientation.

Reorientation, the process of regaining one's bearings after becoming lost, requires identification of a spatial context (context recognition) and recovery of heading direction within that context (heading retrieval). We previously showed that these processes rely on the use of features and geometry, respectively. Here, we examine reorientation behavior in a task that creates contextual ambiguity over a long timescale to demonstrate that mice learn to combine both featural and geometric cues to recover heading with experience. At the neural level, most CA1 neurons persistently align to geometry, and this alignment predicts heading behavior. However, a small subset of cells shows feature-sensitive place field remapping, which serves to predict context. Efficient heading retrieval and context recognition require integration of featural and geometric information in the active network through rate changes. These data illustrate how context recognition and heading retrieval are coded in CA1 and how these processes change with experience.

Exploration patterns shape cognitive map learning.

Spontaneous, volitional spatial exploration is crucial for building up a cognitive map of the environment. However, decades of research have primarily measured the fidelity of cognitive maps after discrete, controlled learning episodes. We know little about how cognitive maps are formed during naturalistic free exploration. Here, we investigated whether exploration trajectories predicted cognitive map accuracy, and how these patterns were shaped by environmental structure. In two experiments, participants freely explored a previously unfamiliar virtual environment. We related their exploration trajectories to a measure of how long they spent in areas with high global environmental connectivity (integration, as assessed by space syntax). In both experiments, we found that participants who spent more time on paths that offered opportunities for integration formed more accurate cognitive maps. Interestingly, we found no support for our pre-registered hypothesis that self-reported trait differences in navigation ability would mediate this relationship. Our findings suggest that exploration patterns predict cognitive map accuracy, even for people who self-report low ability, and highlight the importance of considering both environmental structure and individual variability in formal theory- and model-building.

Early Electrophysiological Markers of Navigational Affordances in Scenes.

Scene perception and spatial navigation are interdependent cognitive functions, and there is increasing evidence that cortical areas that process perceptual scene properties also carry information about the potential for navigation in the environment (navigational affordances). However, the temporal stages by which visual information is transformed into navigationally relevant information are not yet known. We hypothesized that navigational affordances are encoded during perceptual processing and therefore should modulate early visually evoked ERPs, especially the scene-selective P2 component. To test this idea, we recorded ERPs from participants while they passively viewed computer-generated room scenes matched in visual complexity. By simply changing the number of doors (0 doors, 1 door, 2 doors, 3 doors), we were able to systematically vary the number of pathways that afford movement in the local environment, while keeping the overall size and shape of the environment constant. We found that rooms with 0 doors evoked a higher P2 response than rooms with three doors, consistent with prior research reporting higher P2 amplitude to closed relative to open scenes. Moreover, we found P2 amplitude scaled linearly with the number of doors in the scenes. Navigability effects on the ERP waveform were also observed in a multivariate analysis, which showed significant decoding of the number of doors and their location at earlier time windows. Together, our results suggest that navigational affordances are represented in the early stages of scene perception. This complements research showing that the occipital place area automatically encodes the structure of navigable space and strengthens the link between scene perception and navigation.

The human brain uses spatial schemas to represent segmented environments.

Humans and animals use cognitive maps to represent the spatial structure of the environment. Although these maps are typically conceptualized as extending in an equipotential manner across known space, psychological evidence suggests that people mentally segment complex environments into subspaces. To understand the neurocognitive mechanisms behind this operation, we familiarized participants with a virtual courtyard that was divided into two halves by a river; we then used behavioral testing and fMRI to understand how spatial locations were encoded within this environment. Participants' spatial judgments and multivoxel activation patterns were affected by the division of the courtyard, indicating that the presence of a boundary can induce mental segmentation even when all parts of the environment are co-visible. In the hippocampus and occipital place area (OPA), the segmented organization of the environment manifested in schematic spatial codes that represented geometrically equivalent locations in the two subspaces as similar. In the retrosplenial complex (RSC), responses were more consistent with an integrated spatial map. These results demonstrate that people use both local spatial schemas and integrated spatial maps to represent segmented environment. We hypothesize that schematization may serve as a general mechanism for organizing complex knowledge structures in terms of their component elements.

Object representations in the human brain reflect the co-occurrence statistics of vision and language.

A central regularity of visual perception is the co-occurrence of objects in the natural environment. Here we use machine learning and fMRI to test the hypothesis that object co-occurrence statistics are encoded in the human visual system and elicited by the perception of individual objects. We identified low-dimensional representations that capture the latent statistical structure of object co-occurrence in real-world scenes, and we mapped these statistical representations onto voxel-wise fMRI responses during object viewing. We found that cortical responses to single objects were predicted by the statistical ensembles in which they typically occur, and that this link between objects and their visual contexts was made most strongly in parahippocampal cortex, overlapping with the anterior portion of scene-selective parahippocampal place area. In contrast, a language-based statistical model of the co-occurrence of object names in written text predicted responses in neighboring regions of object-selective visual cortex. Together, these findings show that the sensory coding of objects in the human brain reflects the latent statistics of object context in visual and linguistic experience.

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.

Environmental deformations dynamically shift human spatial memory.

Place and grid cells in the hippocampal formation are commonly thought to support a unified and coherent cognitive map of space. This mapping mechanism faces a challenge when a navigator is placed in a familiar environment that has been deformed from its original shape. Under such circumstances, many transformations could plausibly serve to map a navigator's familiar cognitive map to the deformed space. Previous empirical results indicate that the firing fields of rodent place and grid cells stretch or compress in a manner that approximately matches the environmental deformation, and human spatial memory exhibits similar distortions. These effects have been interpreted as evidence that reshaping a familiar environment elicits an analogously reshaped cognitive map. However, recent work has suggested an alternative explanation, whereby deformation-induced distortions of the grid code are attributable to a mechanism that dynamically anchors grid fields to the most recently experienced boundary, thus causing history-dependent shifts in grid phase. This interpretation raises the possibility that human spatial memory will exhibit similar history-dependent dynamics. To test this prediction, we taught participants the locations of objects in a virtual environment and then probed their memory for these locations in deformed versions of this environment. Across three experiments with variable access to visual and vestibular cues, we observed the predicted pattern, whereby the remembered locations of objects were shifted from trial to trial depending on the boundary of origin of the participant's movement trajectory. These results provide evidence for a dynamic anchoring mechanism that governs both neuronal firing and spatial memory.

Structuring Knowledge with Cognitive Maps and Cognitive Graphs.

Humans and animals use mental representations of the spatial structure of the world to navigate. The classical view is that these representations take the form of Euclidean cognitive maps, but alternative theories suggest that they are cognitive graphs consisting of locations connected by paths. We review evidence suggesting that both map-like and graph-like representations exist in the mind/brain that rely on partially overlapping neural systems. Maps and graphs can operate simultaneously or separately, and they may be applied to both spatial and nonspatial knowledge. By providing structural frameworks for complex information, cognitive maps and cognitive graphs may provide fundamental organizing schemata that allow us to navigate in physical, social, and conceptual spaces.

Scene Perception in the Human Brain.

Humans are remarkably adept at perceiving and understanding complex real-world scenes. Uncovering the neural basis of this ability is an important goal of vision science. Neuroimaging studies have identified three cortical regions that respond selectively to scenes: parahippocampal place area, retrosplenial complex/medial place area, and occipital place area. Here, we review what is known about the visual and functional properties of these brain areas. Scene-selective regions exhibit retinotopic properties and sensitivity to low-level visual features that are characteristic of scenes. They also mediate higher-level representations of layout, objects, and surface properties that allow individual scenes to be recognized and their spatial structure ascertained. Challenges for the future include developing computational models of information processing in scene regions, investigating how these regions support scene perception under ecologically realistic conditions, and understanding how they operate in the context of larger brain networks.

Dissociable spatial memory systems revealed by typical and atypical human development.

Rodent lesion studies have revealed the existence of two causally dissociable spatial memory systems, localized to the hippocampus and striatum that are preferentially sensitive to environmental boundaries and landmark objects, respectively. Here we test whether these two memory systems are causally dissociable in humans by examining boundary- and landmark-based memory in typical and atypical development. Adults with Williams syndrome (WS)-a developmental disorder with known hippocampal abnormalities-and typical children and adults, performed a navigation task that involved learning locations relative to a boundary or a landmark object. We found that boundary-based memory was severely impaired in WS compared to typically-developing mental-age matched (MA) children and chronological-age matched (CA) adults, whereas landmark-based memory was similar in all groups. Furthermore, landmark-based memory matured earlier in typical development than boundary-based memory, consistent with the idea that the WS cognitive phenotype arises from developmental arrest of late maturing cognitive systems. Together, these findings provide causal and developmental evidence for dissociable spatial memory systems in humans.

Environmental deformations dynamically shift the grid cell spatial metric.

In familiar environments, the firing fields of entorhinal grid cells form regular triangular lattices. However, when the geometric shape of the environment is deformed, these time-averaged grid patterns are distorted in a grid scale-dependent and local manner. We hypothesized that this distortion in part reflects dynamic anchoring of the grid code to displaced boundaries, possibly through border cell-grid cell interactions. To test this hypothesis, we first reanalyzed two existing rodent grid rescaling datasets to identify previously unrecognized boundary-tethered shifts in grid phase that contribute to the appearance of rescaling. We then demonstrated in a computational model that boundary-tethered phase shifts, as well as scale-dependent and local distortions of the time-averaged grid pattern, could emerge from border-grid interactions without altering inherent grid scale. Together, these results demonstrate that environmental deformations induce history-dependent shifts in grid phase, and implicate border-grid interactions as a potential mechanism underlying these dynamics.

Adaptation decorrelates shape representations.

Perception and neural responses are modulated by sensory history. Visual adaptation, an example of such an effect, has been hypothesized to improve stimulus discrimination by decorrelating responses across a set of neural units. While a central theoretical model, behavioral and neural evidence for this theory is limited and inconclusive. Here, we use a parametric 3D shape-space to test whether adaptation decorrelates shape representations in humans. In a behavioral experiment with 20 subjects, we find that adaptation to a shape class improves discrimination of subsequently presented stimuli with similar features. In a BOLD fMRI experiment with 10 subjects, we observe that adaptation to a shape class decorrelates the multivariate representations of subsequently presented stimuli with similar features in object-selective cortex. These results support the long-standing proposal that adaptation improves perceptual discrimination and decorrelates neural representations, offering insights into potential underlying mechanisms.

The Neurocognitive Basis of Spatial Reorientation.

The ability to recover one's bearings when lost is a skill that is fundamental for spatial navigation. We review the cognitive and neural mechanisms that underlie this ability, with the aim of linking together previously disparate findings from animal behavior, human psychology, electrophysiology, and cognitive neuroscience. Behavioral work suggests that reorientation involves two key abilities: first, the recovery of a spatial reference frame (a cognitive map) that is appropriate to the current environment; and second, the determination of one's heading and location relative to that reference frame. Electrophysiological recording studies, primarily in rodents, have revealed potential correlates of these operations in place, grid, border/boundary, and head-direction cells in the hippocampal formation. Cognitive neuroscience studies, primarily in humans, suggest that the perceptual inputs necessary for these operations are processed by neocortical regions such as the retrosplenial complex, occipital place area and parahippocampal place area, with the retrosplenial complex mediating spatial transformations between the local environment and the recovered spatial reference frame, the occipital place area supporting perception of local boundaries, and the parahippocampal place area processing visual information that is essential for identification of the local spatial context. By combining results across these various literatures, we converge on a unified account of reorientation that bridges the cognitive and neural domains.

Computational mechanisms underlying cortical responses to the affordance properties of visual scenes.

Biologically inspired deep convolutional neural networks (CNNs), trained for computer vision tasks, have been found to predict cortical responses with remarkable accuracy. However, the internal operations of these models remain poorly understood, and the factors that account for their success are unknown. Here we develop a set of techniques for using CNNs to gain insights into the computational mechanisms underlying cortical responses. We focused on responses in the occipital place area (OPA), a scene-selective region of dorsal occipitoparietal cortex. In a previous study, we showed that fMRI activation patterns in the OPA contain information about the navigational affordances of scenes; that is, information about where one can and cannot move within the immediate environment. We hypothesized that this affordance information could be extracted using a set of purely feedforward computations. To test this idea, we examined a deep CNN with a feedforward architecture that had been previously trained for scene classification. We found that responses in the CNN to scene images were highly predictive of fMRI responses in the OPA. Moreover the CNN accounted for the portion of OPA variance relating to the navigational affordances of scenes. The CNN could thus serve as an image-computable candidate model of affordance-related responses in the OPA. We then ran a series of in silico experiments on this model to gain insights into its internal operations. These analyses showed that the computation of affordance-related features relied heavily on visual information at high-spatial frequencies and cardinal orientations, both of which have previously been identified as low-level stimulus preferences of scene-selective visual cortex. These computations also exhibited a strong preference for information in the lower visual field, which is consistent with known retinotopic biases in the OPA. Visualizations of feature selectivity within the CNN suggested that affordance-based responses encoded features that define the layout of the spatial environment, such as boundary-defining junctions and large extended surfaces. Together, these results map the sensory functions of the OPA onto a fully quantitative model that provides insights into its visual computations. More broadly, they advance integrative techniques for understanding visual cortex across multiple level of analysis: from the identification of cortical sensory functions to the modeling of their underlying algorithms.

Human entorhinal cortex represents visual space using a boundary-anchored grid.

When participants performed a visual search task, functional MRI responses in entorhinal cortex exhibited a sixfold periodic modulation by gaze-movement direction. The orientation of this modulation was determined by the shape and orientation of the bounded search space. These results indicate that human entorhinal cortex represents visual space using a boundary-anchored grid, analogous to that used by rodents to represent navigable space.

The cognitive map in humans: spatial navigation and beyond.

The 'cognitive map' hypothesis proposes that brain builds a unified representation of the spatial environment to support memory and guide future action. Forty years of electrophysiological research in rodents suggest that cognitive maps are neurally instantiated by place, grid, border and head direction cells in the hippocampal formation and related structures. Here we review recent work that suggests a similar functional organization in the human brain and yields insights into how cognitive maps are used during spatial navigation. Specifically, these studies indicate that (i) the human hippocampus and entorhinal cortex support map-like spatial codes, (ii) posterior brain regions such as parahippocampal and retrosplenial cortices provide critical inputs that allow cognitive maps to be anchored to fixed environmental landmarks, and (iii) hippocampal and entorhinal spatial codes are used in conjunction with frontal lobe mechanisms to plan routes during navigation. We also discuss how these three basic elements of cognitive map based navigation-spatial coding, landmark anchoring and route planning-might be applied to nonspatial domains to provide the building blocks for many core elements of human thought.

Expectation modulates repetition priming under high stimulus variability.

Neural responses to stimuli are often attenuated by repeated presentation. When observed in blood oxygen level-dependent signals, this attenuation is known as fMRI adaptation (fMRIa) or fMRI repetition suppression. According to a prominent account, fMRIa reflects the fulfillment of perceptual expectations during recognition of repeated items (Summerfield, Trittschuh, Monti, Mesulam, & Egner, 2008). Supporting this idea, expectation has been shown to modulate fMRIa under some circumstances; however, it is not currently known whether expectation similarly modulates recognition performance. To address this lacuna, we measured behavioral and fMRI responses to faces while varying the extent to which each stimulus was informative about its successor. Behavioral priming was greater when repetitions were more likely, suggesting that recognition was facilitated by the expectation than an item would repeat. Notably, this effect was only observed when stimuli were drawn from a broad set of faces including many ethnicities and both genders, but not when stimuli were drawn from a narrower face set, thus making repetitions less informative. Moreover, expectation did not modulate fMRIa in face-selective cortex, contrary to previous studies, although an exploratory analysis indicated that it did so in a medial frontal region. These results support the idea that expectation modulates recognition efficiency, but insofar as behavioral effects of expectation were not accompanied by fMRI effects in visual cortex, they suggest that fMRIa cannot be entirely explained in terms of fulfilled expectations.