Sex-dependent nonlinear Granger connectivity patterns of brain aging in healthy population.

Autor: Fu Y; Lanzhou University, Lanzhou, China; Zhejiang University, Hangzhou, China., Xue L; Huashan Hospital and Human Phenome Institute, Fudan University, Shanghai, China., Niu M; Lanzhou University, Lanzhou, China; Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, China., Gao Y; Zhejiang University, Hangzhou, China., Huang Y; The University of Hong Kong, Hong Kong, China., Zhang H; Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China. Electronic address: hzhang21@zju.edu.cn., Tian M; Huashan Hospital and Human Phenome Institute, Fudan University, Shanghai, China. Electronic address: tianmei@fudan.edu.cn., Zhuo C; Zhejiang University, Hangzhou, China. Electronic address: czhuo@zju.edu.cn.
Jazyk: angličtina
Zdroj: Progress in neuro-psychopharmacology & biological psychiatry [Prog Neuropsychopharmacol Biol Psychiatry] 2024 Dec 20; Vol. 135, pp. 111088. Date of Electronic Publication: 2024 Jul 20.
DOI: 10.1016/j.pnpbp.2024.111088
Abstrakt: Background: Brain aging is a complex process that involves functional alterations in multiple subnetworks and brain regions. However, most previous studies investigating aging-related functional connectivity (FC) changes using resting-state functional magnetic resonance images (rs-fMRIs) have primarily focused on the linear correlation between brain subnetworks, ignoring the nonlinear casual properties of fMRI signals.
Methods: We introduced the neural Granger causality technique to investigate the sex-dependent nonlinear Granger connectivity (NGC) during aging on a publicly available dataset of 227 healthy participants acquired cross-sectionally in Leipzig, Germany.
Results: Our findings indicate that brain aging may cause widespread declines in NGC at both regional and subnetwork scales. These findings exhibit high reproducibility across different network sparsities, demonstrating the efficacy of static and dynamic analysis strategies. Females exhibit greater heterogeneity and reduced stability in NGC compared to males during aging, especially the NGC between the visual network and other subnetworks. Besides, NGC strengths can well reflect the individual cognitive function, which may therefore work as a sensitive metric in cognition-related experiments for individual-scale or group-scale mechanism understanding.
Conclusion: These findings indicate that NGC analysis is a potent tool for identifying sex-dependent brain aging patterns. Our results offer valuable perspectives that could substantially enhance the understanding of sex differences in neurological diseases in the future, especially in degenerative disorders.
Competing Interests: Declaration of competing interest The authors confirm that there are no conflicts of interest.
(Copyright © 2024 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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