Age-dependent changes in the dynamic functional organization of the brain at rest: a cross-cultural replication approach

Abstract

Age-associated changes in brain function play an important role in the development of neurodegenerative diseases. Although previous work has examined age-related changes in static functional connectivity, accumulating evidence suggests that advancing age is especially associated with alterations in the dynamic interactions and transitions between different brain states, which hitherto have received less attention. Conclusions of previous studies in this domain are moreover limited by suboptimal replicability of resting-state functional magnetic resonance imaging (fMRI) and culturally homogenous cohorts. Here, we investigate the robustness of age-associated changes in dynamic functional connectivity (dFC) by capitalizing on the availability of fMRI cohorts from two cultures (Western European and Chinese). In both the LEMON (Western European) and SALD (Chinese) cohorts, we consistently identify two distinct states: a more frequent segregated within-network connectivity state (state I) and a less frequent integrated between-network connectivity state (state II). Moreover, in both these cohorts, older (55–80 years) compared to younger participants (20–35 years) exhibited lower occurrence of and spent less time in state I. Older participants also tended to exhibit more transitions between networks and greater variance in global efficiency. Overall, our cross-cultural replication of age-associated changes in dFC metrics implies that advancing age is robustly associated with a reorganization of dynamic brain activation that favors the use of less functionally specific networks.

Pathological brain states in Alzheimer’s disease

“…Our results provide a mechanistic framework in which existing accounts of functional network changes can be interpreted. Prior investigations of age and Alzheimer's disease network changes based on static [31][32][33] and dynamic [34][35][36][37][38][39] functional connectivity have proposed compelling models characterized by failures, strength changes, and disconnections between networks. While the previous studies were not able to leverage the moment-to-moment reconfiguration of unconstrained brain states 1 due to methodological limitations 3,4 , they provide complementary information to our highly dynamic coactivation approach.…”

“…In contrast to the extensive characterization of functional networks in aging and Alzheimer's disease using static metrics of functional networks [31][32][33] , and to a lesser extent, dynamic functional connectivity approaches with sliding time windows [34][35][36][37][38][39] , time-varying dynamics of brain states, specifically reflecting coactivation patterns at single time points, have not yet been investigated. Insight into the rapid spatiotemporal dynamics of brain states would provide a more precise understanding of the mechanism underlying how network dysfunction may emerge.…”