Open AccessChanges in the interaction of resting‐state neural networks from adolescence to adulthood
Author(s) -
Stevens Michael C.,
Pearlson Godfrey D.,
Calhoun Vince D.
Publication year - 2009
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.20673
Subject(s) - default mode network , resting state fmri , psychology , causality (physics) , normative , neuroscience , artificial neural network , correlation , granger causality , biological neural network , cognition , nerve net , association (psychology) , developmental psychology , artificial intelligence , computer science , machine learning , mathematics , philosophy , physics , geometry , epistemology , quantum mechanics , psychotherapist
This study examined how the mutual interactions of functionally integrated neural networks during resting‐state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12–30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system “causal density” estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within‐network connectivity and more efficient between‐network influences with greater development. Supplemental tests showed that this normative age‐related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age‐related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal‐parietal circuits and “default mode” networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.