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Neural Representation of Spatial Topology in the Rodent Hippocampus

By Zhe Chen, Stephen N. Gomperts, Jun Yamamoto and Matthew A. Wilson

Abstract

Pyramidal cells in the rodent hippocampus often exhibit clear spatial tuning in navigation. Although it has been long suggested that pyramidal cell activity may underlie a topological code rather than a topographic code, it remains unclear whether an abstract spatial topology can be encoded in the ensemble spiking activity of hippocampal place cells. Using a statistical approach developed previously, we investigate this question and related issues in greater detail. We recorded ensembles of hippocampal neurons as rodents freely foraged in one- and two-dimensional spatial environments and used a “decode-to-uncover” strategy to examine the temporally structured patterns embedded in the ensemble spiking activity in the absence of observed spatial correlates during periods of rodent navigation or awake immobility. Specifically, the spatial environment was represented by a finite discrete state space. Trajectories across spatial locations (“states”) were associated with consistent hippocampal ensemble spiking patterns, which were characterized by a state transition matrix. From this state transition matrix, we inferred a topology graph that defined the connectivity in the state space. In both one- and two-dimensional environments, the extracted behavior patterns from the rodent hippocampal population codes were compared against randomly shuffled spike data. In contrast to a topographic code, our results support the efficiency of topological coding in the presence of sparse sample size and fuzzy space mapping. This computational approach allows us to quantify the variability of ensemble spiking activity, examine hippocampal population codes during off-line states, and quantify the topological complexity of the environment.National Institutes of Health (U.S.) (Grant RO1-MH061976)United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N00014-10-1-0936)National Science Foundation (U.S.) (Collaborative Research in Computational Neuroscience Award IIS-1307645)Mathematical Biosciences Institute at the Ohio State University (Early Career Award)National Institutes of Health (U.S.) (Career Development Award KO8-MH081027)RIKEN-MIT Center for Neural Circuit Genetics (Research Center Grant

Publisher: MIT Press
Year: 2013
DOI identifier: 10.1162/NECO_a_00538
OAI identifier: oai:dspace.mit.edu:1721.1/83901
Provided by: DSpace@MIT
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