Do intrinsic brain functional networks predict working memory from childhood to adulthood?
Han Zhang1,2, Shuji Hao2, Annie Lee1
1Department of Biomedical Engineering and Clinical Imaging Research Center, National University of Singapore, Singapore, Singapore.
Human Brain Mapping
|January 19, 2021
Summary
Brain functional networks predict working memory (WM) in adults and adolescents, but not in children. This predictive power changes across the lifespan, highlighting developmental shifts in cognitive neuroscience.
Area of Science:
- Neuroscience
- Cognitive Science
- Developmental Psychology
Background:
- Working memory (WM) is crucial for goal-directed behavior and academic success.
- WM deficits are associated with neurodevelopmental disorders.
- Understanding the neural basis of WM across development is essential.
Purpose of the Study:
- To investigate the predictive power of intrinsic functional brain networks for working memory (WM) across different age groups.
- To compare the efficacy of ALE-based versus whole-brain intrinsic functional networks in predicting WM.
- To explore developmental trends in the relationship between brain networks and WM capacity.
Main Methods:
- Utilized resting-state fMRI (rs-fMRI) data from 468 participants aged 4 to 55 years.
- Defined intrinsic functional networks using activation likelihood estimation (ALE) meta-analysis and whole-brain approaches.
- Applied connectome-based predictive modeling (CPM) to predict individual WM performance.
Main Results:
- Connectome-based predictive modeling (CPM) successfully predicted WM in adults using both ALE-based and whole-brain networks, with ALE-based networks showing superior performance.
- Whole-brain networks predicted WM in adolescents, but ALE-based networks did not.
- Neither network approach predicted WM in any of the child groups (preschoolers, early/late school-age children).
Conclusions:
- Intrinsic functional brain networks show age-dependent predictive power for working memory.
- The predictive utility of brain networks for WM increases from childhood to adulthood.
- ALE-based intrinsic functional networks offer a more targeted approach for predicting WM in adults compared to whole-brain networks.
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