Mapping the structure-function relationship along macroscale gradients in the human brain

Functional coactivation between human brain regions is partly explained by white matter connections; however, how the structure-function relationship varies by function remains unclear. Here, we reference large data repositories to compute maps of structure-function correspondence across hundreds of specific functions and brain regions. We use natural language processing to accurately predict structure-function correspondence for specific functions and to identify macroscale gradients across the brain that correlate with structure-function correspondence as well as cortical thickness. Our findings suggest structure-function correspondence unfolds along a sensory-fugal organizational axis, with higher correspondence in primary sensory and motor cortex for perceptual and motor functions, and lower correspondence in association cortex for cognitive functions. Our study bridges neuroscience and natural language to describe how structure-function coupling varies by region and function in the brain, offering insight into the diversity and evolution of neural network properties.

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Publication Details

Journal
Nature Communications
Published
2024-08-16
DOI
https://doi.org/10.1038/s41467-024-51395-6
Citations
12
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
4.11

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article

Mapping the structure-function relationship along macroscale gradients in the human brain

Xilin Shen, Xenophon Papademetris, Hari McGrath, Sami Obaïd et al.
12 citations
Nature Communications
Functional Brain Connectivity Studies
4.11
article

Mapping the structure-function relationship along macroscale gradients in the human brain

Xilin Shen, Xenophon Papademetris, Hari McGrath, Sami Obaïd, Evan Collins, Omar Chishti, Hitten P. Zaveri, R. Todd Constable, Jagriti Arora, Dennis D. Spencer, Alex King
article en
12 citations

Abstract

Functional coactivation between human brain regions is partly explained by white matter connections; however, how the structure-function relationship varies by function remains unclear. Here, we reference large data repositories to compute maps of structure-function correspondence across hundreds of specific functions and brain regions. We use natural language processing to accurately predict structure-function correspondence for specific functions and to identify macroscale gradients across the brain that correlate with structure-function correspondence as well as cortical thickness. Our findings suggest structure-function correspondence unfolds along a sensory-fugal organizational axis, with higher correspondence in primary sensory and motor cortex for perceptual and motor functions, and lower correspondence in association cortex for cognitive functions. Our study bridges neuroscience and natural language to describe how structure-function coupling varies by region and function in the brain, offering insight into the diversity and evolution of neural network properties.

Nature CommunicationsVol. 15(1)
University of Cambridge (GB), Yale University (US), Montreal Police Service (CA), Max Planck Institute for Human Cognitive and Brain Sciences (DE), Centre Hospitalier de l’Université de Montréal (CA), Massachusetts Institute of Technology (US), Université de Montréal (CA), University of California, Berkeley (US)
Swebilius Foundation, Center for Information Technology
Quality Education
Openalex Percentile: Top 5%
Functional Brain Connectivity Studies
4.11
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