On Information Metrics for Spatial Coding

[Display omitted] •Information metrics for spatial coding by neuronal spikes were studied.•Mutual information correlates better with spatial decoding than commonly used metrics.•Firing rate addition, multiplication and consistency differently affect the metrics.•Surrogate-based normalization equaliz...

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Vydané v:Neuroscience Ročník 375; s. 62 - 73
Hlavní autori: Souza, Bryan C., Pavão, Rodrigo, Belchior, Hindiael, Tort, Adriano B.L.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States Elsevier Ltd 01.04.2018
Predmet:
hippocampus
information
place cell
place field
spatial coding
spike train analysis
spike train analysis
hippocampus
spatial coding
place field
information
MI
place cell
ISSN:0306-4522, 1873-7544, 1873-7544
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Shrnutí:[Display omitted] •Information metrics for spatial coding by neuronal spikes were studied.•Mutual information correlates better with spatial decoding than commonly used metrics.•Firing rate addition, multiplication and consistency differently affect the metrics.•Surrogate-based normalization equalizes performance across information metrics. The hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon’s mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice.
Bibliografia:ObjectType-Article-1
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content type line 23
ISSN:0306-4522
1873-7544
1873-7544
DOI:10.1016/j.neuroscience.2018.01.066