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From Default Mode Network to the Basal Configuration

Sex Differences in the Resting-State Brain Connectivity as a Function of Age and Their Clinical Correlates

Bibliographic Data

ID15526239
AuthorsSean D Conrin (University of Illinois Chicago), Liang Zhan (0000-0002-7920-4828, University of Wisconsin–Stout), Zachery D Morrissey (0000-0002-8346-4876, University of Illinois Chicago), Mengqi Xing (0009-0003-5821-1855, University of Illinois Chicago), Angus G Forbes (0000-0002-8700-7795, University of California, Santa Cruz), Angus Forbes, Pauline M Maki (0000-0002-8443-3430, University of Illinois Chicago), Pauline Maki, Mohammed R Milad (0000-0002-8620-5132, University of Illinois Chicago), Olusola Ajilore (0000-0003-0737-0437, University of Illinois Chicago), Scott A Langenecker (0000-0002-7932-5494, University of Illinois Chicago), Alex Leow (0000-0002-5660-8651, University of Illinois Chicago, corresponding author), Alex D Leow
Year2018
Volume9
Pages365-365
Publication date2018-08-13
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Psychiatry (JOURNAL)
Journal identifiersISSN: 1664-0640 • E-ISSN: 1664-0640
PublisherFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2018.00365
PMID30150944
OpenAlexW2885436153
LanguageEN
References cited50

Connectomics is a framework that models brain structure and function interconnectivity as a network, rather than narrowly focusing on select regions-of-interest. MRI-derived connectomes can be structural, usually based on diffusion-weighted MR imaging, or functional, usually formed by examining fMRI blood-oxygen-level-dependent (BOLD) signal correlations. Recently, we developed a novel method for assessing the hierarchical modularity of functional brain networks-the probability associated community estimation (PACE). PACE uniquely permits a dual formulation, thus yielding equivalent connectome modular structure regardless of whether positive or negative edges are considered. This method was rigorously validated using the 1,000 functional connectomes project data set (F1000, RRID:SCR_005361) (1) and the Human Connectome Project (HCP, RRID:SCR_006942) (2, 3) and we reported novel sex differences in resting-state connectivity not previously reported. (4) This study further examines sex differences in regard to hierarchical modularity as a function of age and clinical correlates, with findings supporting a basal configuration framework as a more nuanced and dynamic way of conceptualizing the resting-state connectome that is modulated by both age and sex. Our results showed that differences in connectivity between men and women in the 22-25 age range were not significantly different. However, these same non-significant differences attained significance in both the 26-30 age group ( p = 0.003) and the 31-35 age group ( p basal configuration between sexes

Connectome · Connectomics · Default mode network · Functional connectivity · Functional magnetic resonance imaging · Human Connectome Project · Resting state fMRI · Advanced Neuroimaging Techniques and Applications · Functional Brain Connectivity Studies · Mental Health Research Topics · Neuroscience · Psychology

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