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A learned map for places and concepts in the human MTL.

Nora A HerwegLukas KunzDaniel R SchonhautArmin BrandtPaul A WandaAshwini D SharanMickael R SperlingAndreas Schulze-BonhageMichael Jacob Kahana
Published in: The Journal of neuroscience : the official journal of the Society for Neuroscience (2023)
Distinct lines of research in both humans and animals point to a specific role of the hippocampus in both spatial and episodic memory function. The discovery of concept cells in the hippocampus and surrounding medial-temporal lobe (MTL) regions suggests that the MTL maps physical and semantic spaces with a similar neural architecture. Here, we studied the emergence of such maps using MTL micro-wire recordings from 20 patients (9 female, 11 male) navigating a virtual environment featuring salient landmarks with established semantic meaning. We present several key findings: The array of local field potentials in the MTL contains sufficient information for above chance decoding of subjects' instantaneous location in the environment. Closer examination revealed that, as subjects gain experience with the environment, the field potentials come to represent both the subjects' locations in virtual space and in high-dimensional semantic space. Similarly, we observe a learning effect on temporal sequence coding. Over time, field potentials come to represent future locations, even after controlling for spatial proximity. This predictive coding of future states, more so than the strength of spatial representations per se, is linked to variability in subjects' navigation performance. Our results thus support the conceptualization of the MTL as a memory space, representing both spatial- and non-spatial information to plan future actions and predict their outcomes. SIGNIFICANCE STATEMENT: Using rare micro-wire recordings, we studied the representation of spatial, semantic and temporal information in the human MTL. Our findings demonstrate that subjects acquire a cognitive map that simultaneously represents the spatial and semantic relations between landmarks. We further show that the same learned representation is used to predict future states, implicating MTL cell assemblies as the building blocks of prospective memory functions.
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