Older adults benefit from more widespread brain network integration during working memory.

Journal Article (Journal Article)

Neuroimaging evidence suggests that the aging brain relies on a more distributed set of cortical regions than younger adults in order to maintain successful levels of performance during demanding cognitive tasks. However, it remains unclear how task demands give rise to this age-related expansion in cortical networks. To investigate this issue, functional magnetic resonance imaging was used to measure univariate activity, network connectivity, and cognitive performance in younger and older adults during a working memory (WM) task. Here, individuals performed a WM task in which they held letters online while reordering them alphabetically. WM load was titrated to obtain four individualized difficulty levels with different set sizes. Network integration-defined as the ratio of within-versus between-network connectivity-was linked to individual differences in WM capacity. The study yielded three main findings. First, as task difficulty increased, network integration decreased in younger adults, whereas it increased in older adults. Second, age-related increases in network integration were driven by increases in right hemisphere connectivity to both left and right cortical regions, a finding that helps to reconcile existing theories of compensatory recruitment in aging. Lastly, older adults with higher WM capacity demonstrated higher levels of network integration in the most difficult task condition. These results shed light on the mechanisms of age-related network reorganization by demonstrating that changes in network connectivity may act as an adaptive form of compensation, with older adults recruiting a more distributed cortical network as task demands increase.

Full Text

Duke Authors

Cited Authors

  • Crowell, CA; Davis, SW; Beynel, L; Deng, L; Lakhlani, D; Hilbig, SA; Palmer, H; Brito, A; Peterchev, AV; Luber, B; Lisanby, SH; Appelbaum, LG; Cabeza, R

Published Date

  • September 2020

Published In

Volume / Issue

  • 218 /

Start / End Page

  • 116959 -

PubMed ID

  • 32442638

Pubmed Central ID

  • PMC7571507

Electronic International Standard Serial Number (EISSN)

  • 1095-9572

Digital Object Identifier (DOI)

  • 10.1016/j.neuroimage.2020.116959

Language

  • eng

Conference Location

  • United States