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Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results

Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental...

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Autores principales: Bottenhorn, Katherine L., Flannery, Jessica S., Boeving, Emily R., Riedel, Michael C., Eickhoff, Simon B., Sutherland, Matthew T., Laird, Angela R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326731/
https://www.ncbi.nlm.nih.gov/pubmed/30793072
http://dx.doi.org/10.1162/netn_a_00050
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author Bottenhorn, Katherine L.
Flannery, Jessica S.
Boeving, Emily R.
Riedel, Michael C.
Eickhoff, Simon B.
Sutherland, Matthew T.
Laird, Angela R.
author_facet Bottenhorn, Katherine L.
Flannery, Jessica S.
Boeving, Emily R.
Riedel, Michael C.
Eickhoff, Simon B.
Sutherland, Matthew T.
Laird, Angela R.
author_sort Bottenhorn, Katherine L.
collection PubMed
description Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental processes of interest. However, a growing literature shows how dynamic, interactive tasks have allowed researchers to study cognition as it more naturally occurs. Collective analysis across such neuroimaging experiments may answer broader questions regarding how naturalistic cognition is biologically distributed throughout the brain. We applied an unbiased, data-driven, meta-analytic approach that uses k-means clustering to identify core brain networks engaged across the naturalistic functional neuroimaging literature. Functional decoding allowed us to, then, delineate how information is distributed between these networks throughout the execution of dynamical cognition in realistic settings. This analysis revealed six recurrent patterns of brain activation, representing sensory, domain-specific, and attentional neural networks that support the cognitive demands of naturalistic paradigms. Although gaps in the literature remain, these results suggest that naturalistic fMRI paradigms recruit a common set of networks that allow both separate processing of different streams of information and integration of relevant information to enable flexible cognition and complex behavior.
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spelling pubmed-63267312019-02-21 Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results Bottenhorn, Katherine L. Flannery, Jessica S. Boeving, Emily R. Riedel, Michael C. Eickhoff, Simon B. Sutherland, Matthew T. Laird, Angela R. Netw Neurosci Research Articles Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use highly controlled tasks to isolate mental processes of interest. However, a growing literature shows how dynamic, interactive tasks have allowed researchers to study cognition as it more naturally occurs. Collective analysis across such neuroimaging experiments may answer broader questions regarding how naturalistic cognition is biologically distributed throughout the brain. We applied an unbiased, data-driven, meta-analytic approach that uses k-means clustering to identify core brain networks engaged across the naturalistic functional neuroimaging literature. Functional decoding allowed us to, then, delineate how information is distributed between these networks throughout the execution of dynamical cognition in realistic settings. This analysis revealed six recurrent patterns of brain activation, representing sensory, domain-specific, and attentional neural networks that support the cognitive demands of naturalistic paradigms. Although gaps in the literature remain, these results suggest that naturalistic fMRI paradigms recruit a common set of networks that allow both separate processing of different streams of information and integration of relevant information to enable flexible cognition and complex behavior. MIT Press 2018-10-01 /pmc/articles/PMC6326731/ /pubmed/30793072 http://dx.doi.org/10.1162/netn_a_00050 Text en © 2018 Massachusetts Institute of Technology This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.
spellingShingle Research Articles
Bottenhorn, Katherine L.
Flannery, Jessica S.
Boeving, Emily R.
Riedel, Michael C.
Eickhoff, Simon B.
Sutherland, Matthew T.
Laird, Angela R.
Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results
title Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results
title_full Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results
title_fullStr Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results
title_full_unstemmed Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results
title_short Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results
title_sort cooperating yet distinct brain networks engaged during naturalistic paradigms: a meta-analysis of functional mri results
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326731/
https://www.ncbi.nlm.nih.gov/pubmed/30793072
http://dx.doi.org/10.1162/netn_a_00050
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