著者: Huanqiu Zhang , Phil Rich , Albert K. Lee , Tatyana O. Sharpee - Nature Neuroscience 2022 被引用: 62
Daily experience suggests that we perceive distances near us linearly. However, the actual geometry of spatial representation in the brain is unknown. Here we report that neurons in the CA1 region of rat hippocampus that mediate spatial perception represent space according to a non-linear hyperbolic geometry. This geometry uses an exponential scale and yields greater positional information than a linear scale. We found that the size of the representation matches the optimal predictions for the number of CA1 neurons. The representations also dynamically expanded proportional to the logarithm of time that the animal spent exploring the environment, in correspondence with the maximal mutual information that can be received. The dynamic changes tracked even small variations due to changes in the running speed of the animal. These results demonstrate how neural circuits achieve efficient representations using dynamic hyperbolic geometry.
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Dynamics of the Hippocampal Ensemble… Dynamics of the Hippocampal Ensemble Code for Space Microstructure of a spatial map in the… Microstructure of a spatial map in the entorhinal cortex Unmasking the CA1 Ensemble Place Code by… Unmasking the CA1 Ensemble Place Code by Exposures to Small and Large Environments: More Place Cells and Multiple, Irregularly Arranged, and Expanded Place Fields in the Larger Space Finite Scale of Spatial Representation in the… Finite Scale of Spatial Representation in the Hippocampus Network Dynamics Underlying the Formatio… Network Dynamics Underlying the Formation of Sparse, Informative Representations in the Hippocampus Large environments reveal the statistical… Large environments reveal the statistical structure governing hippocampal representations Behavioral time scale synaptic plasticity… Behavioral time scale synaptic plasticity underlies CA1 place fields Hyperbolic geometry of the olfactory space Hyperbolic geometry of the olfactory space An argument for hyperbolic geometry in… An argument for hyperbolic geometry in neural circuits Multiscale representation of very… Multiscale representation of very large environments in the hippocampus of flying bats Toroidal topology of population activity in… Toroidal topology of population activity in grid cells Geometry of abstract learned knowledge in th… Geometry of abstract learned knowledge in the hippocampus Quantifying the distribution of feature… Quantifying the distribution of feature values over data represented in arbitrary dimensional spaces Multi-scale goal distance representation… Multi-scale goal distance representations in human hippocampus during virtual spatial navigation Grid cells, border cells, and discrete… Grid cells, border cells, and discrete complex analysis Tracking the topology of neural manifolds across… Tracking the topology of neural manifolds across populations The Dimensions of dimensionality The Dimensions of dimensionality Adaptive data embedding for curved spaces Adaptive data embedding for curved spaces ImAge quantitates aging and rejuvenation ImAge quantitates aging and rejuvenation Hippocampal neuronal activity is aligned wit… Hippocampal neuronal activity is aligned with action plans Integration of cognitive tasks into artificial… Integration of cognitive tasks into artificial general intelligence test for large models Hyperbolic Deep Learning in Computer Vision: A… Hyperbolic Deep Learning in Computer Vision: A Survey Topological Neuroscience: Linking… Topological Neuroscience: Linking Circuits to Function Universal statistics of hippocampal place field… Universal statistics of hippocampal place fields across species and dimensionalities Hippocampal spatial representations exhibit… Hippocampal spatial representations exhibit a hyperbolic geometry that expands with experience 過去の参考文献 中心の論文 この論文を引用する論文 古い 新しい ノードをクリックするとフォーカスを固定、空白をクリックすると本論文に戻ります。ホバーで一時的にプレビューできます。各ノードのページはタイトルから開けます。