Edge-Community Entropy Is a Novel Neural Correlate of Aging and Moderator of Fluid Cognition

Anita Shankar, Jacob C. Tanner, Tianrui Mao, Richard F. Betzel, Ruchika S. Prakash

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Decreased neuronal specificity of the brain in response to cognitive demands (i.e., neural dedifferentiation) has been implicated in age-related cognitive decline. Investigations into functional connectivity analogs of these processes have focused primarily on measuring segregation of nonoverlapping networks at rest. Here, we used an edge-centric network approach to derive entropy, a measure of specialization, from spatially overlapping communities during cognitive task fMRI. Using Human Connectome Project Lifespan data (713 participants, 36–100 years old, 55.7% female), we characterized a pattern of nodal despecialization differentially affecting the medial temporal lobe and limbic, visual, and subcortical systems. At the whole-brain level, global entropy moderated declines in fluid cognition across the lifespan and uniquely covaried with age when controlling for the network segregation metric modularity. Importantly, relationships between both metrics (entropy and modularity) and fluid cognition were age dependent, although entropy’s relationship with cognition was specific to older adults. These results suggest entropy is a potentially important metric for examining how neurological processes in aging affect functional specialization at the nodal, network, and whole-brain level.

Original languageEnglish (US)
Article numbere1701232024
JournalJournal of Neuroscience
Volume44
Issue number25
DOIs
StatePublished - Jun 19 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024 the authors.

Keywords

  • aging
  • cognition
  • fMRI
  • network neuroscience

PubMed: MeSH publication types

  • Journal Article

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