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Establishing brain states in neuroimaging data

The definition of a brain state remains elusive, with varying interpretations across different sub-fields of neuroscience—from the level of wakefulness in anaesthesia, to activity of individual neurons, voltage in EEG, and blood flow in fMRI. This lack of consensus presents a significant challenge t...

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Autores principales: Dezhina, Zalina, Smallwood, Jonathan, Xu, Ting, Turkheimer, Federico E., Moran, Rosalyn J., Friston, Karl J., Leech, Robert, Fagerholm, Erik D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10602380/
https://www.ncbi.nlm.nih.gov/pubmed/37844124
http://dx.doi.org/10.1371/journal.pcbi.1011571
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author Dezhina, Zalina
Smallwood, Jonathan
Xu, Ting
Turkheimer, Federico E.
Moran, Rosalyn J.
Friston, Karl J.
Leech, Robert
Fagerholm, Erik D.
author_facet Dezhina, Zalina
Smallwood, Jonathan
Xu, Ting
Turkheimer, Federico E.
Moran, Rosalyn J.
Friston, Karl J.
Leech, Robert
Fagerholm, Erik D.
author_sort Dezhina, Zalina
collection PubMed
description The definition of a brain state remains elusive, with varying interpretations across different sub-fields of neuroscience—from the level of wakefulness in anaesthesia, to activity of individual neurons, voltage in EEG, and blood flow in fMRI. This lack of consensus presents a significant challenge to the development of accurate models of neural dynamics. However, at the foundation of dynamical systems theory lies a definition of what constitutes the ’state’ of a system—i.e., a specification of the system’s future. Here, we propose to adopt this definition to establish brain states in neuroimaging timeseries by applying Dynamic Causal Modelling (DCM) to low-dimensional embedding of resting and task condition fMRI data. We find that ~90% of subjects in resting conditions are better described by first-order models, whereas ~55% of subjects in task conditions are better described by second-order models. Our work calls into question the status quo of using first-order equations almost exclusively within computational neuroscience and provides a new way of establishing brain states, as well as their associated phase space representations, in neuroimaging datasets.
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spelling pubmed-106023802023-10-27 Establishing brain states in neuroimaging data Dezhina, Zalina Smallwood, Jonathan Xu, Ting Turkheimer, Federico E. Moran, Rosalyn J. Friston, Karl J. Leech, Robert Fagerholm, Erik D. PLoS Comput Biol Research Article The definition of a brain state remains elusive, with varying interpretations across different sub-fields of neuroscience—from the level of wakefulness in anaesthesia, to activity of individual neurons, voltage in EEG, and blood flow in fMRI. This lack of consensus presents a significant challenge to the development of accurate models of neural dynamics. However, at the foundation of dynamical systems theory lies a definition of what constitutes the ’state’ of a system—i.e., a specification of the system’s future. Here, we propose to adopt this definition to establish brain states in neuroimaging timeseries by applying Dynamic Causal Modelling (DCM) to low-dimensional embedding of resting and task condition fMRI data. We find that ~90% of subjects in resting conditions are better described by first-order models, whereas ~55% of subjects in task conditions are better described by second-order models. Our work calls into question the status quo of using first-order equations almost exclusively within computational neuroscience and provides a new way of establishing brain states, as well as their associated phase space representations, in neuroimaging datasets. Public Library of Science 2023-10-16 /pmc/articles/PMC10602380/ /pubmed/37844124 http://dx.doi.org/10.1371/journal.pcbi.1011571 Text en © 2023 Dezhina et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Dezhina, Zalina
Smallwood, Jonathan
Xu, Ting
Turkheimer, Federico E.
Moran, Rosalyn J.
Friston, Karl J.
Leech, Robert
Fagerholm, Erik D.
Establishing brain states in neuroimaging data
title Establishing brain states in neuroimaging data
title_full Establishing brain states in neuroimaging data
title_fullStr Establishing brain states in neuroimaging data
title_full_unstemmed Establishing brain states in neuroimaging data
title_short Establishing brain states in neuroimaging data
title_sort establishing brain states in neuroimaging data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10602380/
https://www.ncbi.nlm.nih.gov/pubmed/37844124
http://dx.doi.org/10.1371/journal.pcbi.1011571
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