The turbulence dynamics (TD) framework has proven to be informative of whole-brain network synchronicity and rigidity, and is related to neuropsychiatric disorders and antidepressant response prediction. However, studies conducted so far have used small samples and have not accounted for individual differences in demographic and other confounding variables. We aimed to investigate whether demographics were associated with TD read-outs and -if so- built a Normative Model (NM) to account for such demographic variability.
We analysed resting-state fMRI data from the UK Biobank (N = 11,184) and extracted TD features. We analysed associations between TD and age, sex and head motion during scanning across 11 spatial scales (λ:0.01–0.31). We then evaluated the benefit of correcting for these covariates using Normative Modeling (NM) by its association with recent depressive symptoms using the RDS-4 questionnaire.
Age, sex and motion during scanning were statistically significantly associated with all TD features, though with generally small effect sizes (η_p2
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