%0 Journal Article
%A Sasse, Leonard
%A Larabi, Daouia
%A Omidvarnia, Amir
%A Jung, Kyesam
%A Hoffstaedter, Felix
%A Jocham, Gerhard
%A Eickhoff, Simon B.
%A Patil, Kaustubh R.
%T Intermediately synchronised brain states optimise trade-off between subject specificity and predictive capacity
%J Communications biology
%V 6
%N 1
%@ 2399-3642
%C London
%I Springer Nature
%M FZJ-2023-02718
%P 705
%D 2023
%X Functional connectivity (FC) refers to the statistical dependencies between activity of distinct brain areas. To study temporal fluctuations in FC within the duration of a functional magnetic resonance imaging (fMRI) scanning session, researchers have proposed the computation of an edge time series (ETS) and their derivatives. Evidence suggests that FC is driven by a few time points of high-amplitude co-fluctuation (HACF) in the ETS, which may also contribute disproportionately to interindividual differences. However, it remains unclear to what degree different time points actually contribute to brain-behaviour associations. Here, we systematically evaluate this question by assessing the predictive utility of FC estimates at different levels of co-fluctuation using machine learning (ML) approaches. We demonstrate that time points of lower and intermediate co-fluctuation levels provide overall highest subject specificity as well as highest predictive capacity of individual-level phenotypes.
%F PUB:(DE-HGF)16
%9 Journal Article
%$ 37429937
%U <Go to ISI:>//WOS:001025904900005
%R 10.1038/s42003-023-05073-w
%U https://juser.fz-juelich.de/record/1009258