Temporal stability of functional brain modules associated with human intelligence

  • Individual differences in general cognitive ability (i.e., intelligence) have been linked to individual variations in the modular organization of functional brain networks. However, these analyses have been limited to static (time-averaged) connectivity, and have not yet addressed whether dynamic changes in the configuration of brain networks relate to general intelligence. Here, we used multiband functional MRI resting-state data (N = 281) and estimated subject-specific time-varying functional connectivity networks. Modularity optimization was applied to determine individual time-variant module partitions and to assess fluctuations in modularity across time. We show that higher intelligence, indexed by an established composite measure, the Wechsler Abbreviated Scale of Intelligence (WASI), is associated with higher temporal stability (lower temporal variability) of brain network modularity. Post-hoc analyses reveal that subjects with higher intelligence scores engage in fewer periods of extremely high modularity — which are characterized by greater disconnection of task-positive from task-negative networks. Further, we show that brain regions of the dorsal attention network contribute most to the observed effect. In sum, our study suggests that investigating the temporal dynamics of functional brain network topology contributes to our understanding of the neural bases of general cognitive abilities.

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Author:Kirsten HilgerORCiDGND, Makoto Fukushima, Olaf SpornsORCiDGND, Christian FiebachORCiDGND
URN:urn:nbn:de:hebis:30:3-638097
DOI:https://doi.org/10.1002/hbm.24807
ISSN:1097-0193
Parent Title (English):Human brain mapping
Publisher:Wiley-Liss
Place of publication:New York, NY
Document Type:Article
Language:English
Date of Publication (online):2019/10/06
Date of first Publication:2019/10/06
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2022/01/11
Tag:dynamic networks; graph theory; intelligence; modularity; resting-state fMRI
Volume:41
Issue:2
Page Number:11
First Page:362
Last Page:372
Note:
The research leading to these results has received funding from the German Research Foundation (grant FI848/6-1) and from the Initia- tive for the Development of Scientific and Economic Excellence of the state of Hessen (LOEWE Center for Individual Development and Adaptive Education). C. J. Fiebach was furthermore supported by the European Community's Seventh Framework Programme (FP7/2013) under grant agreement no. 617891. O. Sporns acknowledges funding support by the National Institutes of Health (R01 AT009036-01). Data were provided by the Nathan S. Kline Institute for Psychiatric Research, founded and operated by the New York State Office of Mental Health.
HeBIS-PPN:490814611
Institutes:Psychologie und Sportwissenschaften
Dewey Decimal Classification:1 Philosophie und Psychologie / 15 Psychologie / 150 Psychologie
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0