Journal article
Global functional connectivity of cognitive control networks predicts task-switching performance in older adults
Cortex
01/2026
DOI: 10.1016/j.cortex.2026.01.002
Abstract
Older adults have difficulty switching between competing goals with increasing age due to declines in executive function (EF) and changes in brain network connectivity, including the Cognitive Control Network (CCN). Prior research shows that greater global functional connectivity (GFC) in the CCN supports cognitive flexibility. However, it is unclear whether CCN GFC is associated with task-switching in older adults. Task-switching performance relies on both switching and working memory. Mixing cost reflects the ability to maintain and coordinate multiple task rules in working memory and is sensitive to age-related declines in EF, whereas switching cost is more closely linked to age-related general slowing in processing speed. This study investigates how CCN GFC relates to task-switching performance in older adults using two task versions. Participants aged 55-80 years old performed the Separate and Overlap versions for behavioral analyses (n = 118). Six 8-minute resting-state fMRI sessions were collected over two days for brain behavior analyses (n = 112). Whole grey-matter GFC was calculated, followed by average GFC extraction from the CCN, Default Mode Network (DMN), and Somatomotor Network (SMN). Results showed that older adults were slower and less accurate in the Overlap version. Greater CCN, DMN, and SMN GFC were associated with smaller mixing costs in the Overlap version. SMN GFC was linked to larger mixing costs and smaller switching costs in the Separate version. Our findings suggest that greater integration of the CCN, DMN, and SMN, as measured by GFC, is associated with better task-switch performance under increasing working memory demands.
Details
- Title: Subtitle
- Global functional connectivity of cognitive control networks predicts task-switching performance in older adults
- Creators
- Vincent A. Magnotta - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Cortex
- DOI
- 10.1016/j.cortex.2026.01.002
- ISSN
- 0010-9452
- Publisher
- Elsevier Ltd
- Language
- English
- Electronic publication date
- 01/2026
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Psychiatry; Iowa Neuroscience Institute
- Record Identifier
- 9985130238102771
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