Revealing neural correlates of behavior without behavioral measurements

Neuronal tuning is typically measured in response to a priori defined behavioural variables of interest. Here, the authors use an unsupervised learning approach to recover neuronal tuning with respect to the recorded network activity and show that this can reveal the relevant behavioural variables.

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Detalles Bibliográficos
Autores principales: Alon Rubin, Liron Sheintuch, Noa Brande-Eilat, Or Pinchasof, Yoav Rechavi, Nitzan Geva, Yaniv Ziv
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
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Acceso en línea:https://doaj.org/article/52bff245461b4ef69a8966b072828b31
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Descripción
Sumario:Neuronal tuning is typically measured in response to a priori defined behavioural variables of interest. Here, the authors use an unsupervised learning approach to recover neuronal tuning with respect to the recorded network activity and show that this can reveal the relevant behavioural variables.