Multimodal multilayer network centrality relates to executive functioning

Abstract

Executive functioning (EF) is a higher order cognitive process that is thought to depend on a network organization facilitating integration across subnetworks, in the context of which the central role of the fronto-parietal network (FPN) has been described across imaging and neurophysiological modalities. However, the potentially complementary unimodal information on the relevance of the FPN for EF has not yet been integrated. We employ a multilayer framework to allow for integration of different modalities into one ‘network of networks.’ We used diffusion MRI, resting-state functional MRI, MEG, and neuropsychological data obtained from 33 healthy adults to construct modality-specific single-layer networks as well as a single multilayer network per participant. We computed single-layer and multilayer eigenvector centrality of the FPN as a measure of integration in this network and examined their associations with EF. We found that higher multilayer FPN centrality, but not single-layer FPN centrality, was related to better EF. We did not find a statistically significant change in explained variance in EF when using the multilayer approach as compared to the single-layer measures. Overall, our results show the importance of FPN integration for EF and underline the promise of the multilayer framework toward better understanding cognitive functioning.

Author Summary: Until now, the relationship between brain network topology and cognition has mostly been studied using isolated modal information (e.g., functional MRI or magnetoencephalography). Such isolated analyses ignore potentially complementary information. Here, we use multimodal imaging and neuropsychological data collected from healthy adults to demonstrate that increased centrality of the fronto-parietal network in a multilayer network is related to better executive functioning. We find no such relation for single-layer networks. These results show the importance of fronto-parietal network integration for executive functioning, as well as the value of a multilayer framework in network analyses of the brain.