Abstract
Metastability of BOLD fMRI signals is a commonly used proxy of brain dynamics in behavioral and clinical studies. To date, little has been done to assess the confidence with which we can use estimates of metastability as reliable biomarkers of individual brain state. We analyze whole-brain and network-specific metastability for a highly sampled individual brain (84 sessions taken over 18 months) and quantify the within-subject reliability for the metrics as a function of the amount of data used, which we find to be comparable to that seen for static functional connectivity. As considerable variability is observed across networks in the required amount of data, we combine the networks' metrics in one novel feature vector that exhibits an order of magnitude improvement in reliability. We then test reproducibility by analyzing the Midnight Scan Club dataset (10 subjects imaged over 10 consecutive days). Finally, we examine the susceptibility to change of the proposed metastability measure in another dataset examining brain dynamics under the effect of psilocybin. We conclude that the networks' metastability feature vector exhibits strong within-subject reliability that renders it a promising candidate for the study of individual-specific biomarkers of brain dynamics and potential targets for precision neuromodulation.