Myelin-weighted Core Network Connectivity Supports Trait-Level Future Thinking
- 1University of Birmingham
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.
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BibTeX
@misc{reed2026myelinweighted,
title = {{Myelin-weighted Core Network Connectivity Supports Trait-Level Future Thinking}},
author = {L. S. Reed and E. Messaritaki and C. Hedge and C. J. Hodgetts and C. B. McNabb and D. K. Jones and A. D. Lawrence},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.29.754335},
url = {https://www.biorxiv.org/content/10.64898/2026.09.29.754335v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Myelin-weighted Core Network Connectivity Supports Trait-Level Future Thinking
AU - L. S. Reed
AU - E. Messaritaki
AU - C. Hedge
AU - C. J. Hodgetts
AU - C. B. McNabb
AU - D. K. Jones
AU - A. D. Lawrence
PY - 2026
DA - 2026/09/29
PB - bioRxiv
DO - 10.64898/2026.09.29.754335
UR - https://www.biorxiv.org/content/10.64898/2026.09.29.754335v1
AB - 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.
ER -