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Autori principali: Ost, Guilherme, Reynaud-Bouret, Patricia
Natura: Preprint
Pubblicazione: 2022
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Accesso online:https://arxiv.org/abs/2209.00950
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author Ost, Guilherme
Reynaud-Bouret, Patricia
author_facet Ost, Guilherme
Reynaud-Bouret, Patricia
contents We take the testing perspective to understand what the minimal discrimination time between two stimuli is for different types of rate coding neurons. Our main goal is to describe the testing abilities of two different encoding systems: place cells and grid cells. In particular, we show, through the notion of adaptation, that a fixed place cell system can have a minimum discrimination time that decreases when the stimuli are further away. This could be a considerable advantage for the place cell system that could complement the grid cell system, which is able to discriminate stimuli that are much closer than place cells.
format Preprint
id arxiv_https___arxiv_org_abs_2209_00950
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Neural Coding as a Statistical Testing Problem
Ost, Guilherme
Reynaud-Bouret, Patricia
Statistics Theory
Neurons and Cognition
We take the testing perspective to understand what the minimal discrimination time between two stimuli is for different types of rate coding neurons. Our main goal is to describe the testing abilities of two different encoding systems: place cells and grid cells. In particular, we show, through the notion of adaptation, that a fixed place cell system can have a minimum discrimination time that decreases when the stimuli are further away. This could be a considerable advantage for the place cell system that could complement the grid cell system, which is able to discriminate stimuli that are much closer than place cells.
title Neural Coding as a Statistical Testing Problem
topic Statistics Theory
Neurons and Cognition
url https://arxiv.org/abs/2209.00950