Myelin-Weighted Core Network Connectivity Supports Trait-Level Future Thinking

Abstract

Why are some individuals able to recollect past events and imagine future events more richly than others? Here we examine how structural connectivity within a ‘core network’ supporting mnemonic cognition, substantially overlapping with the canonical default network, underpins inter-individual variation in autobiographical thought. We analysed state-of-the-art magnetic resonance imaging data from 109 adults collected on a high-gradient 3T Connectom scanner, in relation to their Survey of Autobiographical Memory (SAM) scores - a psychometric measure of self-reported episodic autobiographical, semantic, spatial, and future thinking abilities. We anatomically defined a core network, employed streamline tractography to derive participant-specific structural brain networks, and weighted their connections with the myelin water fraction derived from quantitative multicomponent relaxometry. We investigated associations between graph theoretical metrics of the core network and self-reported mnemonic abilities. We found a negative association between future thinking abilities and characteristic path length, and a positive association between future thinking abilities and mean clustering coefficient. Further analysis showed that the node-specific clustering coefficient of most core network nodes was positively correlated with future thinking scores, with frontotemporal nodes showing the strongest associations. Our findings indicate that both efficient integration and local segregation of the core network are important for trait-level future thinking. Author Summary People vary considerably in how richly they imagine autobiographical events. Although functional brain activity has been linked to individual differences in autobiographical cognition, less is known about how the structural organisation of this network contributes to these differences. Using advanced MRI data from 109 healthy adults, we examined whether the organisation of white matter connections within a core autobiographical memory network relates to self-reported memory and future thinking abilities. We found that individuals reporting stronger future thinking abilities exhibited shorter characteristic path length and higher clustering within the core network linked to autobiographical cognition. This suggests that individual differences in imagining the future may emerge from how this core network is structurally organised, indicating that both efficient integration and local segregation support trait-level future thinking.