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Functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands

Multiple large-scale networks populate human association cortex. Here, we explored the functional properties of these networks by exploiting trial-to-trial variation in component-processing demands. In two behavioral studies (n = 136 and n = 238), participants quantified strategies used to solve ind...

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Autores principales: DiNicola, Lauren M., Ariyo, Oluwatobi I., Buckner, Randy L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Physiological Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9799157/
https://www.ncbi.nlm.nih.gov/pubmed/36197013
http://dx.doi.org/10.1152/jn.00211.2022
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author DiNicola, Lauren M.
Ariyo, Oluwatobi I.
Buckner, Randy L.
author_facet DiNicola, Lauren M.
Ariyo, Oluwatobi I.
Buckner, Randy L.
author_sort DiNicola, Lauren M.
collection PubMed
description Multiple large-scale networks populate human association cortex. Here, we explored the functional properties of these networks by exploiting trial-to-trial variation in component-processing demands. In two behavioral studies (n = 136 and n = 238), participants quantified strategies used to solve individual task trials that spanned remembering, imagining future scenarios, and various control trials. These trials were also all scanned in an independent sample of functional MRI participants (n = 10), each with sufficient data to precisely define within-individual networks. Stable latent factors varied across trials and correlated with trial-level functional responses selectively across networks. One network linked to parahippocampal cortex, labeled Default Network A (DN-A), tracked scene construction, including for control trials that possessed minimal episodic memory demands. To the degree, a trial encouraged participants to construct a mental scene with imagery and awareness about spatial locations of objects or places, the response in DN-A increased. The juxtaposed Default Network B (DN-B) showed no such response but varied in relation to social processing demands. Another adjacent network, labeled Frontoparietal Network B (FPN-B), robustly correlated with trial difficulty. These results support that DN-A and DN-B are specialized networks differentially supporting information processing within spatial and social domains. Both networks are dissociable from a closely juxtaposed domain-general control network that tracks cognitive effort. NEW & NOTEWORTHY Tasks shown to differentially recruit parallel association networks are multifaceted, leaving open questions about network processes. Here, examining trial-to-trial network response properties in relation to trial traits reveals new insights into network functions. In particular, processes linked to scene construction selectively recruit a distributed network with links to parahippocampal and retrosplenial cortices, including during trials designed not to rely on the personal past. Adjacent networks show distinct patterns, providing novel evidence of functional specialization.
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spelling pubmed-97991572023-01-09 Functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands DiNicola, Lauren M. Ariyo, Oluwatobi I. Buckner, Randy L. J Neurophysiol Research Article Multiple large-scale networks populate human association cortex. Here, we explored the functional properties of these networks by exploiting trial-to-trial variation in component-processing demands. In two behavioral studies (n = 136 and n = 238), participants quantified strategies used to solve individual task trials that spanned remembering, imagining future scenarios, and various control trials. These trials were also all scanned in an independent sample of functional MRI participants (n = 10), each with sufficient data to precisely define within-individual networks. Stable latent factors varied across trials and correlated with trial-level functional responses selectively across networks. One network linked to parahippocampal cortex, labeled Default Network A (DN-A), tracked scene construction, including for control trials that possessed minimal episodic memory demands. To the degree, a trial encouraged participants to construct a mental scene with imagery and awareness about spatial locations of objects or places, the response in DN-A increased. The juxtaposed Default Network B (DN-B) showed no such response but varied in relation to social processing demands. Another adjacent network, labeled Frontoparietal Network B (FPN-B), robustly correlated with trial difficulty. These results support that DN-A and DN-B are specialized networks differentially supporting information processing within spatial and social domains. Both networks are dissociable from a closely juxtaposed domain-general control network that tracks cognitive effort. NEW & NOTEWORTHY Tasks shown to differentially recruit parallel association networks are multifaceted, leaving open questions about network processes. Here, examining trial-to-trial network response properties in relation to trial traits reveals new insights into network functions. In particular, processes linked to scene construction selectively recruit a distributed network with links to parahippocampal and retrosplenial cortices, including during trials designed not to rely on the personal past. Adjacent networks show distinct patterns, providing novel evidence of functional specialization. American Physiological Society 2023-01-01 2022-10-05 /pmc/articles/PMC9799157/ /pubmed/36197013 http://dx.doi.org/10.1152/jn.00211.2022 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 Research Article
DiNicola, Lauren M.
Ariyo, Oluwatobi I.
Buckner, Randy L.
Functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands
title Functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands
title_full Functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands
title_fullStr Functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands
title_full_unstemmed Functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands
title_short Functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands
title_sort functional specialization of parallel distributed networks revealed by analysis of trial-to-trial variation in processing demands
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9799157/
https://www.ncbi.nlm.nih.gov/pubmed/36197013
http://dx.doi.org/10.1152/jn.00211.2022
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