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Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease
Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain’s network architecture. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate...
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/PMC10055141/ https://www.ncbi.nlm.nih.gov/pubmed/36993597 http://dx.doi.org/10.1101/2023.03.16.532981 |
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author | Luppi, Andrea I. Singleton, S. Parker Hansen, Justine Y. Bzdok, Danilo Kuceyeski, Amy Betzel, Richard F. Misic, Bratislav |
author_facet | Luppi, Andrea I. Singleton, S. Parker Hansen, Justine Y. Bzdok, Danilo Kuceyeski, Amy Betzel, Richard F. Misic, Bratislav |
author_sort | Luppi, Andrea I. |
collection | PubMed |
description | Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain’s network architecture. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic engine. We also systematically incorporate neurotransmitter receptor density maps (18 receptors and transporters) and disease-related cortical abnormality maps (11 neurodegenerative, psychiatric and neurodevelopmental diseases; N = 17 000 patients, N = 22 000 controls). Integrating large-scale multimodal neuroimaging data from functional MRI, diffusion tractography, cortical morphometry, and positron emission tomography, we simulate how anatomically-guided transitions between cognitive states can be reshaped by pharmacological or pathological perturbation. Our results provide a comprehensive look-up table charting how brain network organisation and chemoarchitecture interact to manifest different cognitive topographies. This computational framework establishes a principled foundation for systematically identifying novel ways to promote selective transitions between desired cognitive topographies. |
format | Online Article Text |
id | pubmed-10055141 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-100551412023-03-30 Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease Luppi, Andrea I. Singleton, S. Parker Hansen, Justine Y. Bzdok, Danilo Kuceyeski, Amy Betzel, Richard F. Misic, Bratislav bioRxiv Article Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain’s network architecture. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic engine. We also systematically incorporate neurotransmitter receptor density maps (18 receptors and transporters) and disease-related cortical abnormality maps (11 neurodegenerative, psychiatric and neurodevelopmental diseases; N = 17 000 patients, N = 22 000 controls). Integrating large-scale multimodal neuroimaging data from functional MRI, diffusion tractography, cortical morphometry, and positron emission tomography, we simulate how anatomically-guided transitions between cognitive states can be reshaped by pharmacological or pathological perturbation. Our results provide a comprehensive look-up table charting how brain network organisation and chemoarchitecture interact to manifest different cognitive topographies. This computational framework establishes a principled foundation for systematically identifying novel ways to promote selective transitions between desired cognitive topographies. Cold Spring Harbor Laboratory 2023-03-17 /pmc/articles/PMC10055141/ /pubmed/36993597 http://dx.doi.org/10.1101/2023.03.16.532981 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Luppi, Andrea I. Singleton, S. Parker Hansen, Justine Y. Bzdok, Danilo Kuceyeski, Amy Betzel, Richard F. Misic, Bratislav Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease |
title | Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease |
title_full | Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease |
title_fullStr | Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease |
title_full_unstemmed | Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease |
title_short | Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease |
title_sort | transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10055141/ https://www.ncbi.nlm.nih.gov/pubmed/36993597 http://dx.doi.org/10.1101/2023.03.16.532981 |
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