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dc.contributor.authorSouza, Bryan C.-
dc.contributor.authorPavão, Rodrigo-
dc.contributor.authorBelchior, Hindiael-
dc.contributor.authorTort, Adriano B. L.-
dc.identifier.citationSouza, B. C. et al. On information metrics for spatial coding. [s.l.], Neuroscience, v. 375, p. 62-73, abr./2018.pt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectPlace cellpt_BR
dc.subjectPlace fieldpt_BR
dc.subjectSpatial codingpt_BR
dc.subjectSpike train analysispt_BR
dc.titleOn information metrics for spatial codingpt_BR
dc.description.resumoThe 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.pt_BR
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