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Heritability of the human connectome: A connectotyping study
Recent progress in resting-state neuroimaging demonstrates that the brain exhibits highly individualized patterns of functional connectivity—a “connectotype.” How these individualized patterns may be constrained by environment and genetics is unknown. Here we ask whether the connectotype is familial...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MIT Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6130446/ https://www.ncbi.nlm.nih.gov/pubmed/30215032 http://dx.doi.org/10.1162/netn_a_00029 |
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author | Miranda-Dominguez, Oscar Feczko, Eric Grayson, David S. Walum, Hasse Nigg, Joel T. Fair, Damien A. |
author_facet | Miranda-Dominguez, Oscar Feczko, Eric Grayson, David S. Walum, Hasse Nigg, Joel T. Fair, Damien A. |
author_sort | Miranda-Dominguez, Oscar |
collection | PubMed |
description | Recent progress in resting-state neuroimaging demonstrates that the brain exhibits highly individualized patterns of functional connectivity—a “connectotype.” How these individualized patterns may be constrained by environment and genetics is unknown. Here we ask whether the connectotype is familial and heritable. Using a novel approach to estimate familiality via a machine-learning framework, we analyzed resting-state fMRI scans from two well-characterized samples of child and adult siblings. First we show that individual connectotypes were reliably identified even several years after the initial scanning timepoint. Familial relationships between participants, such as siblings versus those who are unrelated, were also accurately characterized. The connectotype demonstrated substantial heritability driven by high-order systems including the fronto-parietal, dorsal attention, ventral attention, cingulo-opercular, and default systems. This work suggests that shared genetics and environment contribute toward producing complex, individualized patterns of distributed brain activity, rather than constraining local aspects of function. These insights offer new strategies for characterizing individual aberrations in brain function and evaluating heritability of brain networks. |
format | Online Article Text |
id | pubmed-6130446 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MIT Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61304462018-09-11 Heritability of the human connectome: A connectotyping study Miranda-Dominguez, Oscar Feczko, Eric Grayson, David S. Walum, Hasse Nigg, Joel T. Fair, Damien A. Netw Neurosci Research Recent progress in resting-state neuroimaging demonstrates that the brain exhibits highly individualized patterns of functional connectivity—a “connectotype.” How these individualized patterns may be constrained by environment and genetics is unknown. Here we ask whether the connectotype is familial and heritable. Using a novel approach to estimate familiality via a machine-learning framework, we analyzed resting-state fMRI scans from two well-characterized samples of child and adult siblings. First we show that individual connectotypes were reliably identified even several years after the initial scanning timepoint. Familial relationships between participants, such as siblings versus those who are unrelated, were also accurately characterized. The connectotype demonstrated substantial heritability driven by high-order systems including the fronto-parietal, dorsal attention, ventral attention, cingulo-opercular, and default systems. This work suggests that shared genetics and environment contribute toward producing complex, individualized patterns of distributed brain activity, rather than constraining local aspects of function. These insights offer new strategies for characterizing individual aberrations in brain function and evaluating heritability of brain networks. MIT Press 2018-06-01 /pmc/articles/PMC6130446/ /pubmed/30215032 http://dx.doi.org/10.1162/netn_a_00029 Text en © 2017 Massachusetts Institute of Technology http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Miranda-Dominguez, Oscar Feczko, Eric Grayson, David S. Walum, Hasse Nigg, Joel T. Fair, Damien A. Heritability of the human connectome: A connectotyping study |
title | Heritability of the human connectome: A connectotyping study |
title_full | Heritability of the human connectome: A connectotyping study |
title_fullStr | Heritability of the human connectome: A connectotyping study |
title_full_unstemmed | Heritability of the human connectome: A connectotyping study |
title_short | Heritability of the human connectome: A connectotyping study |
title_sort | heritability of the human connectome: a connectotyping study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6130446/ https://www.ncbi.nlm.nih.gov/pubmed/30215032 http://dx.doi.org/10.1162/netn_a_00029 |
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