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Updated: Jan 28, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Cognitive correlates of cortical thickness, white matter volume, and resting-state connectivity in mild cognitive
Nido Dipo Wardana1,2,3, Stefanie Enriquez-Geppert2, Peter Paul De Deyn4
1Center for Clinical Neuroscience and Cognition, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Abstract:
BackgroundIndividuals with mild cognitive impairment (MCI) are at an increased risk of developing Alzheimer's disease. Anatomical and functional brain alterations associated with this condition are still elusive.ObjectiveThis study explored the cognitive correlates of cortical thickness, white matter (WM) volume, and resting-state connectivity among people with MCI.MethodsA total of 56 older participants (aged 51 to 92 years) with amnestic MCI were recruited. Cognitive abilities were measured using the Trail Making Task, the Stroop Color-Word Test, the Forward and Backward Digit Span test, and computerized n-back tasks. Morphometry was used to measure cortical thickness and WM volume from 3 T MR images, while functional connectivity was measured using resting-state fMRI and calculated using Independent Component Analysis. Voxel-wise regressions were used to test associations between cognitive scores and brain measures.ResultsWorse working memory updating (n-back) performance was associated with lower cortical thickness of the left middle temporal gyrus. Additionally, at a lower demand, working memory performance was linked to frontoparietal network (FPN) intrinsic connectivity, while WM volume within the anterior segment of the left arcuate fasciculus and default mode network (DMN) resting-state connectivity were relevant when the demand was higher. Lower DMN connectivity was also associated with worse conflict monitoring (Stroop) performance (all cluster-corrected ps < 0.05).ConclusionsThe findings highlight the relevance of the perisylvian region to working memory updating and conflict monitoring in people with MCI.
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