Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations.

ABSTRACT: Multilayer network models have been proposed as an effective means of capturing the dynamic configuration of distributed neural circuits and quantitatively describing how communities vary over time. Beyond general insights into brain function, a growing number of studies have begun to employ these methods for the study of individual differences. However, test-retest reliabilities for multilayer network measures have yet to be fully quantified or optimized, potentially limiting their utility for individual difference studies. Here, we systematically evaluated the impact of multilayer community detection algorithms, selection of network parameters, scan duration, and task condition on test-retest reliabilities of multilayer network measures (i.e., flexibility, integration, and recruitment).

SUBMITTER: Yang Z 

PROVIDER: S-EPMC7829665 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature