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Identification of interacting neural populations: methods and statistical considerations

As improved recording technologies have created new opportunities for neurophysiological investigation, emphasis has shifted from individual neurons to multiple populations that form circuits, and it has become important to provide evidence of cross-population coordinated activity. We review various...

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Detalles Bibliográficos
Autores principales: Kass, Robert E., Bong, Heejong, Olarinre, Motolani, Xin, Qi, Urban, Konrad N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Physiological Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10642974/
https://www.ncbi.nlm.nih.gov/pubmed/37465897
http://dx.doi.org/10.1152/jn.00131.2023
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author Kass, Robert E.
Bong, Heejong
Olarinre, Motolani
Xin, Qi
Urban, Konrad N.
author_facet Kass, Robert E.
Bong, Heejong
Olarinre, Motolani
Xin, Qi
Urban, Konrad N.
author_sort Kass, Robert E.
collection PubMed
description As improved recording technologies have created new opportunities for neurophysiological investigation, emphasis has shifted from individual neurons to multiple populations that form circuits, and it has become important to provide evidence of cross-population coordinated activity. We review various methods for doing so, placing them in six major categories while avoiding technical descriptions and instead focusing on high-level motivations and concerns. Our aim is to indicate what the methods can achieve and the circumstances under which they are likely to succeed. Toward this end, we include a discussion of four cross-cutting issues: the definition of neural populations, trial-to-trial variability and Poisson-like noise, time-varying dynamics, and causality. Listen to this article’s corresponding podcast at https://jneurophysiol.podbean.com/e/jnp-micro-podcasts-four-questions-robert-kass/.
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spelling pubmed-106429742023-11-14 Identification of interacting neural populations: methods and statistical considerations Kass, Robert E. Bong, Heejong Olarinre, Motolani Xin, Qi Urban, Konrad N. J Neurophysiol Review As improved recording technologies have created new opportunities for neurophysiological investigation, emphasis has shifted from individual neurons to multiple populations that form circuits, and it has become important to provide evidence of cross-population coordinated activity. We review various methods for doing so, placing them in six major categories while avoiding technical descriptions and instead focusing on high-level motivations and concerns. Our aim is to indicate what the methods can achieve and the circumstances under which they are likely to succeed. Toward this end, we include a discussion of four cross-cutting issues: the definition of neural populations, trial-to-trial variability and Poisson-like noise, time-varying dynamics, and causality. Listen to this article’s corresponding podcast at https://jneurophysiol.podbean.com/e/jnp-micro-podcasts-four-questions-robert-kass/. American Physiological Society 2023-09-01 2023-07-19 /pmc/articles/PMC10642974/ /pubmed/37465897 http://dx.doi.org/10.1152/jn.00131.2023 Text en Copyright © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Licensed under Creative Commons Attribution CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/) . Published by the American Physiological Society.
spellingShingle Review
Kass, Robert E.
Bong, Heejong
Olarinre, Motolani
Xin, Qi
Urban, Konrad N.
Identification of interacting neural populations: methods and statistical considerations
title Identification of interacting neural populations: methods and statistical considerations
title_full Identification of interacting neural populations: methods and statistical considerations
title_fullStr Identification of interacting neural populations: methods and statistical considerations
title_full_unstemmed Identification of interacting neural populations: methods and statistical considerations
title_short Identification of interacting neural populations: methods and statistical considerations
title_sort identification of interacting neural populations: methods and statistical considerations
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10642974/
https://www.ncbi.nlm.nih.gov/pubmed/37465897
http://dx.doi.org/10.1152/jn.00131.2023
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