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Related Experiment Video

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A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
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Predicting response time variability from task and resting-state functional connectivity in the aging brain.

Oyetunde Gbadeyan1, James Teng1, Ruchika Shaurya Prakash2

  • 1Department of Psychology, The Ohio State University, 139 Psychology Building, 1835 Neil Avenue, Columbus, OH 43210, USA.

Neuroimage
|January 10, 2022
PubMed
Summary
This summary is machine-generated.

Task-based functional connectivity predicts age-related cognitive decline, specifically response time variability, unlike resting-state connectivity. This finding aids understanding of aging and attention. (32 words)

Keywords:
AgingConnectome-based modelingFunctional connectivityFunctional magnetic resonance imagingMachine learningMind-wanderingResponse time variability

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Area of Science:

  • Neuroscience
  • Cognitive Aging
  • Functional Connectivity

Background:

  • Aging impairs cognitive functions like attention and executive control.
  • Mind-wandering declines in older adults, contrary to expectations.
  • Neural basis of mind-wandering in aging remains understudied, focusing on young adults.

Purpose of the Study:

  • Characterize whole-brain functional networks linked to mind-wandering in aging.
  • Investigate task-based vs. resting-state functional connectivity for predicting attention lapses.
  • Examine the generalizability of predictive models across older adult cohorts.

Main Methods:

  • Utilized response time variability as an indirect marker of mind-wandering.
  • Developed brain-based predictive models from whole-brain task functional connectivity.
  • Compared predictive power of task-based versus resting-state functional connectivity.

Main Results:

  • Task functional connectivity successfully predicted individual response time variability within samples.
  • Resting-state functional connectivity alone did not predict response time variability.
  • Models derived from resting-state connectivity failed to generalize to independent older adult cohorts.

Conclusions:

  • Task-based functional connectivity is valuable for predicting age-related attention variability.
  • Resting-state connectivity alone is insufficient for predicting these cognitive fluctuations in aging.
  • Further research is needed for more robust and generalizable predictive models of cognitive aging.