Navigating cognition: Spatial codes for human thinking

By Jacob L. S. Bellmund, Peter Gärdenfors, Edvard I. Moser, Christian F. Doeller. Science, 2018

563 citations recorded by the source corpus.

A framework for cognitive spaces Ever since Tolman's proposal of cognitive maps in the 1940s, the question of how spatial representations support flexible behavior has been a contentious topic. Bellmund et al. review and combine concepts from cognitive science and philosophy with findings from neurophysiology of spatial navigation in rodents to propose a framework for cognitive neuroscience. They argue that spatial-processing principles in the hippocampalentorhinal region provide a geometric code to map information domains of cognitive spaces for high-level cognition and discuss recent evidence for this proposal. Science, this issue p. eaat6766 BACKGROUND Ever since Edward Tolman’s proposal that comprehensive cognitive maps underlie spatial navigation and, more generally, psychological functions, the question of how past experience guides behavior has been contentious. The discovery of place cells in rodents, signaling the animal’s position in space, suggested that such cognitive maps reside in the hippocampus, a core brain region for human memory. Building on the description of place cells, several other functionally defined cell types were discovered in the hippocampal-entorhinal region. Among them are grid cells in the entorhinal cortex, whose characteristic periodic, six-fold symmetric firing patterns are thought to provide a spatial metric. These findings were complemented by insights into key coding principles of the hippocampal-entorhinal region: Spatial representations vary in scale along the hippocampal long axis, place cells remap to map different environments, and sequential hippocampal activity represents nonlocal trajectories through space. In humans, the existence of spatially tuned cells has been demonstrated in presurgical patients, and functional magnetic resonance imaging provides proxy measures for the noninvasive investigation of these processing mechanisms in human cognition. Intriguingly, recent advances indicate that place and grid cells can encode positions along dimensions of experience beyond Euclidean space for navigation, suggesting a more general role of hippocampal-entorhinal processing mechanisms in cognition. ADVANCES We combine hippocampal-entorhinal processing mechanisms identified in spatial navigation research with ideas from cognitive science describing a spatial representational format for cognition. Cognitive spaces are spanned by dimensions satisfying geometric constraints such as betweenness and equidistance, enabling the representation of properties and concepts as convex regions of cognitive space. We propose that the continuous population code of place and grid cells in the hippocampal-entorhinal region maps the dimensions of cognitive spaces. In these, each stimulus is located according to its feature values along the relevant dimensions, resulting in nearby positions for similar stimuli and larger distances between dissimilar stimuli. The low-dimensional, rigid firing properties of the entorhinal grid system make it a candidate to provide a metric or distance code for cognitive spaces, whereas hippocampal place cells flexibly represent positions in a given space. This mapping of cognitive spaces is complemented by the additional coding principles outlined above: Along the hippocampal long axis, cognitive spaces are mapped with varying spatial scale, supporting memory and knowledge representations at different levels of granularity. Via hippocampal remapping, spaces spanned by different dimensions can be flexibly mapped and established maps can be reinstated via attractor dynamics. The geometric definition of cognitive spaces allows flexible generalization and inference, and sequential hippocampal activity can simulate trajectories through cognitive spaces for adaptive decision-making and behavior. OUTLOOK Cognitive spaces provide a domain-general format for processing in the hippocampal-entorhinal region, in line with its involvement beyond navigation and memory. Spatial navigation serves as a model system to identify key coding principles governing cognitive spaces. An important question concerns the extent to which firing properties of spatially tuned cells are preserved in cognitive spaces. Technological advances such as calcium imaging will clarify coding principles on the population level and facilitate the translation to human cognitive neuroscience. Spatial navigation is mostly investigated in two dimensions and naturally limited to three dimensions; however, the processing of complex, multidimensional concepts is vital to high-level human cognition, and the representation of such high-dimensional spaces is an intriguing question for future research. Further, the role of brain networks acting in concert with the hippocampus, in navigation specifically and cognitive function in general, will provide insight into whether and how cognitive spaces are supported beyond the hippocampal-entorhinal region. Finally, the precise way in which cognitive spaces and trajectories through them are read out for behavior remains to be elucidated. Place and grid cells map cognitive spaces. Cognitive spaces are defined by dimensions satisfying geometric constraints. The example space (left) is spanned by the dimensions of engine power and car weight. Black dots show different vehicles whose positions reflect their feature combinations. Place cells (center; colored circles represent firing fields of different cells) and grid cells (right; circles illustrate firing pattern of one cell) provide a continuous code for cognitive spaces. The hippocampal formation has long been suggested to underlie both memory formation and spatial navigation. We discuss how neural mechanisms identified in spatial navigation research operate across information domains to support a wide spectrum of cognitive functions. In our framework, place and grid cell population codes provide a representational format to map variable dimensions of cognitive spaces. This highly dynamic mapping system enables rapid reorganization of codes through remapping between orthogonal representations across behavioral contexts, yielding a multitude of stable cognitive spaces at different resolutions and hierarchical levels. Action sequences result in trajectories through cognitive space, which can be simulated via sequential coding in the hippocampus. In this way, the spatial representational format of the hippocampal formation has the capacity to support flexible cognition and behavior.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Sensory Systems

View Paper: https://www.semanticscholar.org/paper/727332fd6bd446a4dd402368988a1f34fb0649c8

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Citations in the corpus

If deep learning is the answer, what is the question? (2020, background): “There are even hints that this coding scheme may apply to non-spatial as well as spatial domains 92 , potentially laying the foundations for a theory of higher-order human reasoning 112 .”
Task Switch Costs Scale with Dissimilarity between Task Rules (2024, background): “Recently, it has been proposed that common reference frames, such as cognitive space (Bellmund, Gärdenfors, Moser, & Doeller, 2018) can be used to organize non-perceptual abstract information such as (Park, Miller, Nili, Ranganath, & Boorman, 2020; Tavares et al., 2015) and ratios (Constantinescu,…”
Rhythms of human attention and memory: An embedded process perspective (2022, background): “Another intriguing question regards the physiological nature of neural representations (for recent developments in the ﬁeld, see Deuker et al., 2016; Bellmund et al., 2018) and how they change over time, in the process of mnemonic updating and consolidation (Nadel and Moscovitch, 1997).”
Human Beta Oscillations Reflect Magnitude and Fidelity of Priority Shifts in Working Memory (2026, unknown): “Cognitive control operations more generally may therefore depend on the representational geometry of task-relevant features, consistent with reports of map-like representations for other cognitive functions (Bellmund et al., 2018).”