TY  - JOUR
AU  - Sasse, Leonard
AU  - Larabi, Daouia
AU  - Omidvarnia, Amir
AU  - Jung, Kyesam
AU  - Hoffstaedter, Felix
AU  - Jocham, Gerhard
AU  - Eickhoff, Simon B.
AU  - Patil, Kaustubh R.
TI  - Intermediately synchronised brain states optimise trade-off between subject specificity and predictive capacity
JO  - Communications biology
VL  - 6
IS  - 1
SN  - 2399-3642
CY  - London
PB  - Springer Nature
M1  - FZJ-2023-02718
SP  - 705
PY  - 2023
AB  - 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.
LB  - PUB:(DE-HGF)16
C6  - 37429937
UR  - <Go to ISI:>//WOS:001025904900005
DO  - DOI:10.1038/s42003-023-05073-w
UR  - https://juser.fz-juelich.de/record/1009258
ER  -