Age differences in the functional architecture of the human brain.

Autor:	Setton R; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada., Mwilambwe-Tshilobo L; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada., Girn M; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada., Lockrow AW; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada., Baracchini G; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada., Hughes C; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada., Lowe AJ; Institute of Neurology, University College London, London, UK., Cassidy BN; Department of Psychiatry, University of Toronto, Toronto, ON, Canada., Li J; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA., Luh WM; National Institutes of Health, National Institute on Aging, Baltimore, MD, USA., Bzdok D; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.; Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.; McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada.; School of Computer Science, McGill University, Montreal, QC, Canada.; Mila - Quebec Artificial Intelligence Institute, Montreal, QC, Canada., Leahy RM; Department of Electrical Engineering-Systems, University of Southern California, Los Angeles, CA, USA., Ge T; Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA., Margulies DS; Integrative Neuroscience and Cognition Center (UMR 8002), Centre National de la Recherche Scientifique (CNRS) and Université de Paris, Paris, France., Misic B; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.; McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada., Bernhardt BC; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.; McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada., Stevens WD; Department of Psychology, York University, Toronto, ON, Canada., De Brigard F; Department of Philosophy, Duke University, Durham, NC, USA.; Department of Psychology and Neuroscience, Durham, NC, USA., Kundu P; Icahn School of Medicine at Mount Sinai, New York, NY, USA., Turner GR; Department of Psychology, York University, Toronto, ON, Canada., Spreng RN; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.; McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada.; Departments of Psychiatry and Psychology, McGill University, Montreal, QC, Canada.; Douglas Mental Health University Institute, Verdun, QC, Canada.
Jazyk:	angličtina
Zdroj:	Cerebral cortex (New York, N.Y. : 1991) [Cereb Cortex] 2022 Dec 15; Vol. 33 (1), pp. 114-134.
DOI:	10.1093/cercor/bhac056
Abstrakt:	The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, from global reductions in modularity and segregation of distributed brain systems, to network-specific patterns of dedifferentiation. Whether dedifferentiation reflects an inevitable, global shift in brain function with age, circumscribed, experience-dependent changes, or both, is uncertain. We employed a multimethod strategy to interrogate dedifferentiation at multiple spatial scales. Multi-echo (ME) resting-state fMRI was collected in younger (n = 181) and older (n = 120) healthy adults. Cortical parcellation sensitive to individual variation was implemented for precision functional mapping of each participant while preserving group-level parcel and network labels. ME-fMRI processing and gradient mapping identified global and macroscale network differences. Multivariate functional connectivity methods tested for microscale, edge-level differences. Older adults had lower BOLD signal dimensionality, consistent with global network dedifferentiation. Gradients were largely age-invariant. Edge-level analyses revealed discrete, network-specific dedifferentiation patterns in older adults. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal control network regions showed greater connectivity; and the dorsal attention network was more integrated with heteromodal regions. These findings highlight the importance of multiscale, multimethod approaches to characterize the architecture of functional brain aging. (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)
Databáze:	MEDLINE
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