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When Neural Activity Fails to Reveal Causal Contributions

Neuroscientists rely on distributed spatio-temporal patterns of neural activity to understand how neural units contribute to cognitive functions and behavior. However, the extent to which neural activity reliably indicates a unit's causal contribution to the behavior is not well understood. To...

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Detalles Bibliográficos
Autores principales: Fakhar, Kayson, Dixit, Shrey, Hadaeghi, Fatemeh, Kording, Konrad P., Hilgetag, Claus C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10274733/
https://www.ncbi.nlm.nih.gov/pubmed/37333375
http://dx.doi.org/10.1101/2023.06.06.543895
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author Fakhar, Kayson
Dixit, Shrey
Hadaeghi, Fatemeh
Kording, Konrad P.
Hilgetag, Claus C.
author_facet Fakhar, Kayson
Dixit, Shrey
Hadaeghi, Fatemeh
Kording, Konrad P.
Hilgetag, Claus C.
author_sort Fakhar, Kayson
collection PubMed
description Neuroscientists rely on distributed spatio-temporal patterns of neural activity to understand how neural units contribute to cognitive functions and behavior. However, the extent to which neural activity reliably indicates a unit's causal contribution to the behavior is not well understood. To address this issue, we provide a systematic multi-site perturbation framework that captures time-varying causal contributions of elements to a collectively produced outcome. Applying our framework to intuitive toy examples and artificial neuronal networks revealed that recorded activity patterns of neural elements may not be generally informative of their causal contribution due to activity transformations within a network. Overall, our findings emphasize the limitations of inferring causal mechanisms from neural activities and offer a rigorous lesioning framework for elucidating causal neural contributions.
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spelling pubmed-102747332023-06-17 When Neural Activity Fails to Reveal Causal Contributions Fakhar, Kayson Dixit, Shrey Hadaeghi, Fatemeh Kording, Konrad P. Hilgetag, Claus C. bioRxiv Article Neuroscientists rely on distributed spatio-temporal patterns of neural activity to understand how neural units contribute to cognitive functions and behavior. However, the extent to which neural activity reliably indicates a unit's causal contribution to the behavior is not well understood. To address this issue, we provide a systematic multi-site perturbation framework that captures time-varying causal contributions of elements to a collectively produced outcome. Applying our framework to intuitive toy examples and artificial neuronal networks revealed that recorded activity patterns of neural elements may not be generally informative of their causal contribution due to activity transformations within a network. Overall, our findings emphasize the limitations of inferring causal mechanisms from neural activities and offer a rigorous lesioning framework for elucidating causal neural contributions. Cold Spring Harbor Laboratory 2023-06-07 /pmc/articles/PMC10274733/ /pubmed/37333375 http://dx.doi.org/10.1101/2023.06.06.543895 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Fakhar, Kayson
Dixit, Shrey
Hadaeghi, Fatemeh
Kording, Konrad P.
Hilgetag, Claus C.
When Neural Activity Fails to Reveal Causal Contributions
title When Neural Activity Fails to Reveal Causal Contributions
title_full When Neural Activity Fails to Reveal Causal Contributions
title_fullStr When Neural Activity Fails to Reveal Causal Contributions
title_full_unstemmed When Neural Activity Fails to Reveal Causal Contributions
title_short When Neural Activity Fails to Reveal Causal Contributions
title_sort when neural activity fails to reveal causal contributions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10274733/
https://www.ncbi.nlm.nih.gov/pubmed/37333375
http://dx.doi.org/10.1101/2023.06.06.543895
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