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Choice of method of place cell classification determines the population of cells identified

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Version 2 2023-06-12, 09:55
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posted on 2023-06-12, 09:55 authored by Dorieke Grijseels, Kira ShawKira Shaw, Caswell Barry, Catherine HallCatherine Hall
Place cells, spatially responsive hippocampal cells, provide the neural substrate supporting navigation and spatial memory. Historically most studies of these neurons have used electrophysiological recordings from implanted electrodes but optical methods, measuring intracellular calcium, are becoming increasingly common. Several methods have been proposed as a means to identify place cells based on their calcium activity but there is no common standard and it is unclear how reliable different approaches are. Here we tested four methods that have previously been applied to two-photon hippocampal imaging or electrophysiological data, using both model datasets and real imaging data. These methods use different parameters to identify place cells, including the peak activity in the place field, compared to other locations (the Peak method); the stability of cells’ activity over repeated traversals of an environment (Stability method); a combination of these parameters with the size of the place field (Combination method); and the spatial information held by the cells (Information method). The methods performed differently from each other on both model and real data. In real datasets, vastly different numbers of place cells were identified using the four methods, with little overlap between the populations identified as place cells. Therefore, choice of place cell detection method dramatically affects the number and properties of identified cells. Ultimately, we recommend the Peak method be used in future studies to identify place cell populations, as this method is robust to moderate variations in place field within a session, and makes no inherent assumptions about the spatial information in place fields, unless there is an explicit theoretical reason for detecting cells with more narrowly defined properties.

History

Publication status

  • Published

File Version

  • Published version

Journal

PLoS Computational Biology

ISSN

1553-734X

Publisher

Public Library of Science

Issue

7

Volume

17

Page range

1-32

Article number

a1008835

Department affiliated with

  • Psychology Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2021-07-26

First Open Access (FOA) Date

2021-07-26

First Compliant Deposit (FCD) Date

2021-07-01

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