Resting State Network Connectivity Patterns in Early Aging: Late Middle-age Adults Contrasted with Young Adults

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2 Citations (Scopus)

Abstract

Research on brain aging using resting-state functional magnetic resonance imaging (rs-fMRI) has typically focused on comparing “older” adults to younger adults. Importantly, these studies have often neglected the middle age group, which is also significantly impacted by brain aging, including by early changes in motor, memory, and cognitive functions. This study aims to address this limitation by examining the resting state networks in middle-aged adults via an exploratory whole-brain ROI-to-ROI analysis. Using rs-fMRI, we compared middle-aged adults (n=30) with younger adults (n=70) via an ROI-to-ROI correlation analysis, showing lower connectivity between the cerebellar (posterior) network and the salience network (left rostral prefrontal cortex), as well as between the salience network and the visual network (occipital regions) in the middle-aged group. This reduced connectivity suggests that aging affects how these brain regions synchronize and process information, potentially impairing the integration of cognitive, sensory, and emotional inputs. Additional within-group analyses showed that middle-aged adults exhibited weakened connections between networks but increased connections within the dorsal attention, fronto-parietal, visual, and default mode networks. In contrast, younger adults demonstrated enhanced connections between networks. These results underscore the role of the cerebellar, salience, and visual networks in brain aging and reveal distinct connectivity patterns associated with signs of early aging.

Original languageEnglish
Pages (from-to)282-294
Number of pages13
JournalExperimental Neurobiology
Volume33
Issue number6
DOIs
Publication statusPublished - 2024 Dec

Bibliographical note

Publisher Copyright:
© Experimental Neurobiology 2024.

Keywords

  • Cerebellum
  • Cognitive aging
  • Magnetic resonance imaging

ASJC Scopus subject areas

  • Clinical Neurology
  • Cellular and Molecular Neuroscience

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