Bridging mental health, cognition and the brain in mild traumatic brain injury: A multilayer network analysis of the TRACK-TBI study

BackgroundMild traumatic brain injury (mTBI) patients suffer from several mental health symptoms (e.g., anxiety, depressive symptoms) and cognitive deficits (e.g., attentional deficits, slowed processing speed). However, symptoms in TBI are largely investigated in isolation, using univariate approaches, ignoring the interactions between symptoms and the underlying large-scale brain networks. We constructed the first multilayer network in mTBI to examine the relationships between networks of cognition, mental health and structural brain measures and to identify key variables bridging relationships across these networks. MethodsChronic phase cross-sectional data (6-month follow-up) from 457 mTBI patients was extracted from the TRACK-TBI Longitudinal study. We selected four variables from self-report mental health questionnaires (affective layer), eight cognitive test scores from the NIH toolbox (cognitive layer), and grey matter volumes from eight brain regions of the central executive and salience networks from anatomical MRI scans (brain layer). We used a multilayer network approach to examine the relationships (edges) between all variables (nodes) across layers. We then used the bridge strength centrality metric to identify nodes that bridge the affective, cognitive, and brain layers. ResultsInsomnia severity, immediate verbal memory, somatisation and processing speed nodes exceeded an a priori 80th percentile threshold on the bridge strength scores and can therefore be regarded as key nodes bridging relationships across affective, cognitive and brain layers. ConclusionsThe bridging nodes identified in our multilayer network analyses suggest targets for future studies to develop more customized, efficient, and efficacious treatments to alleviate mental health symptoms and cognitive deficits in mTBI patients.