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The dynamics and geometry of choice in premotor cortex
The brain represents sensory variables in the coordinated activity of neural populations, in which tuning curves of single neurons define the geometry of the population code. Whether the same coding principle holds for dynamic cognitive variables remains unknown because internal cognitive processes...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10401920/ https://www.ncbi.nlm.nih.gov/pubmed/37546748 http://dx.doi.org/10.1101/2023.07.22.550183 |
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author | Genkin, Mikhail Shenoy, Krishna V. Chandrasekaran, Chandramouli Engel, Tatiana A. |
author_facet | Genkin, Mikhail Shenoy, Krishna V. Chandrasekaran, Chandramouli Engel, Tatiana A. |
author_sort | Genkin, Mikhail |
collection | PubMed |
description | The brain represents sensory variables in the coordinated activity of neural populations, in which tuning curves of single neurons define the geometry of the population code. Whether the same coding principle holds for dynamic cognitive variables remains unknown because internal cognitive processes unfold with a unique time course on single trials observed only in the irregular spiking of heterogeneous neural populations. Here we show the existence of such a population code for the dynamics of choice formation in the primate premotor cortex. We developed an approach to simultaneously infer population dynamics and tuning functions of single neurons to the population state. Applied to spike data recorded during decision-making, our model revealed that populations of neurons encoded the same dynamic variable predicting choices, and heterogeneous firing rates resulted from the diverse tuning of single neurons to this decision variable. The inferred dynamics indicated an attractor mechanism for decision computation. Our results reveal a common geometric principle for neural encoding of sensory and dynamic cognitive variables. |
format | Online Article Text |
id | pubmed-10401920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-104019202023-08-05 The dynamics and geometry of choice in premotor cortex Genkin, Mikhail Shenoy, Krishna V. Chandrasekaran, Chandramouli Engel, Tatiana A. bioRxiv Article The brain represents sensory variables in the coordinated activity of neural populations, in which tuning curves of single neurons define the geometry of the population code. Whether the same coding principle holds for dynamic cognitive variables remains unknown because internal cognitive processes unfold with a unique time course on single trials observed only in the irregular spiking of heterogeneous neural populations. Here we show the existence of such a population code for the dynamics of choice formation in the primate premotor cortex. We developed an approach to simultaneously infer population dynamics and tuning functions of single neurons to the population state. Applied to spike data recorded during decision-making, our model revealed that populations of neurons encoded the same dynamic variable predicting choices, and heterogeneous firing rates resulted from the diverse tuning of single neurons to this decision variable. The inferred dynamics indicated an attractor mechanism for decision computation. Our results reveal a common geometric principle for neural encoding of sensory and dynamic cognitive variables. Cold Spring Harbor Laboratory 2023-07-25 /pmc/articles/PMC10401920/ /pubmed/37546748 http://dx.doi.org/10.1101/2023.07.22.550183 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Genkin, Mikhail Shenoy, Krishna V. Chandrasekaran, Chandramouli Engel, Tatiana A. The dynamics and geometry of choice in premotor cortex |
title | The dynamics and geometry of choice in premotor cortex |
title_full | The dynamics and geometry of choice in premotor cortex |
title_fullStr | The dynamics and geometry of choice in premotor cortex |
title_full_unstemmed | The dynamics and geometry of choice in premotor cortex |
title_short | The dynamics and geometry of choice in premotor cortex |
title_sort | dynamics and geometry of choice in premotor cortex |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10401920/ https://www.ncbi.nlm.nih.gov/pubmed/37546748 http://dx.doi.org/10.1101/2023.07.22.550183 |
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