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Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function
The human cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks using a Multi-Session Hierarchical Bayesian Model (MS-HBM) applied to intensively sampled within-individual functional MRI (fMRI) data. The network estimation procedure was init...
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/PMC10441314/ https://www.ncbi.nlm.nih.gov/pubmed/37609246 http://dx.doi.org/10.1101/2023.08.08.552437 |
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author | Du, Jingnan DiNicola, Lauren M. Angeli, Peter A. Saadon-Grosman, Noam Sun, Wendy Kaiser, Stephanie Ladopoulou, Joanna Xue, Aihuiping Yeo, B.T. Thomas Eldaief, Mark C. Buckner, Randy L. |
author_facet | Du, Jingnan DiNicola, Lauren M. Angeli, Peter A. Saadon-Grosman, Noam Sun, Wendy Kaiser, Stephanie Ladopoulou, Joanna Xue, Aihuiping Yeo, B.T. Thomas Eldaief, Mark C. Buckner, Randy L. |
author_sort | Du, Jingnan |
collection | PubMed |
description | The human cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks using a Multi-Session Hierarchical Bayesian Model (MS-HBM) applied to intensively sampled within-individual functional MRI (fMRI) data. The network estimation procedure was initially developed and tested in two participants (each scanned 31 times) and then prospectively applied to 15 new participants (each scanned 8 to 11 times). Detailed analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that also linked to distant regions. Third-order networks each possessed regions distributed widely throughout association cortex. Moreover, regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated similarly across multiple cortical zones. We refer to these as Supra-Areal Association Megaclusters (SAAMs). Within each SAAM, two candidate control regions were typically adjacent to three separate domain-specialized regions. Independent task data were analyzed to explore functional response properties. The somatomotor and visual first-order networks responded to body movements and visual stimulation, respectively. A subset of the second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient or novel events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions within each SAAM did not track working memory load but rather dissociated across language, social, and spatial / episodic processing domains. These results support a model of the cerebral cortex in which progressively higher-order networks nest outwards from primary sensory and motor cortices. Within the apex zones of association cortex there is specialization of large-scale networks that divides domain-flexible from domain-specialized regions repeatedly across parietal, temporal, and prefrontal cortices. We discuss implications of these findings including how repeating organizational motifs may emerge during development. |
format | Online Article Text |
id | pubmed-10441314 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-104413142023-08-22 Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function Du, Jingnan DiNicola, Lauren M. Angeli, Peter A. Saadon-Grosman, Noam Sun, Wendy Kaiser, Stephanie Ladopoulou, Joanna Xue, Aihuiping Yeo, B.T. Thomas Eldaief, Mark C. Buckner, Randy L. bioRxiv Article The human cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks using a Multi-Session Hierarchical Bayesian Model (MS-HBM) applied to intensively sampled within-individual functional MRI (fMRI) data. The network estimation procedure was initially developed and tested in two participants (each scanned 31 times) and then prospectively applied to 15 new participants (each scanned 8 to 11 times). Detailed analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that also linked to distant regions. Third-order networks each possessed regions distributed widely throughout association cortex. Moreover, regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated similarly across multiple cortical zones. We refer to these as Supra-Areal Association Megaclusters (SAAMs). Within each SAAM, two candidate control regions were typically adjacent to three separate domain-specialized regions. Independent task data were analyzed to explore functional response properties. The somatomotor and visual first-order networks responded to body movements and visual stimulation, respectively. A subset of the second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient or novel events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions within each SAAM did not track working memory load but rather dissociated across language, social, and spatial / episodic processing domains. These results support a model of the cerebral cortex in which progressively higher-order networks nest outwards from primary sensory and motor cortices. Within the apex zones of association cortex there is specialization of large-scale networks that divides domain-flexible from domain-specialized regions repeatedly across parietal, temporal, and prefrontal cortices. We discuss implications of these findings including how repeating organizational motifs may emerge during development. Cold Spring Harbor Laboratory 2023-08-10 /pmc/articles/PMC10441314/ /pubmed/37609246 http://dx.doi.org/10.1101/2023.08.08.552437 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Du, Jingnan DiNicola, Lauren M. Angeli, Peter A. Saadon-Grosman, Noam Sun, Wendy Kaiser, Stephanie Ladopoulou, Joanna Xue, Aihuiping Yeo, B.T. Thomas Eldaief, Mark C. Buckner, Randy L. Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function |
title | Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function |
title_full | Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function |
title_fullStr | Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function |
title_full_unstemmed | Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function |
title_short | Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function |
title_sort | within-individual organization of the human cerebral cortex: networks, global topography, and function |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10441314/ https://www.ncbi.nlm.nih.gov/pubmed/37609246 http://dx.doi.org/10.1101/2023.08.08.552437 |
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