Cognitive aging and reserve factors in the Metropolit 1953 Danish male cohort
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Updated: Jun 7, 2025

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
Published on: February 14, 2014
Mostafa Mehdipour Ghazi1, Olalla Urdanibia-Centelles2, Aftab Bakhtiari3,4
1Pioneer Centre for AI, Department of Computer Science, Faculty of Science, University of Copenhagen, Copenhagen, Denmark. ghazi@di.ku.dk.
Abstract:
Identifying early predictors of cognitive decline and at-risk individuals is essential for timely intervention and prevention of dementia. This study aimed to detect neurobiological changes and factors related to cognitive performance in the Metropolit 1953 Danish male birth cohort. We analyzed data from 582 participants, aged 57-68 years, using machine learning techniques to group cognitive trajectories into four clusters differentiating high- and low-performing groups. These clusters were then evaluated with MRI, EEG, and lifestyle/familial risk factors to identify predictors of cognitive decline. Low education and occupation, alcohol consumption, and type 2 diabetes were associated with lower cognitive performance. Declines in neocortical volume and increases in frontotemporal alpha and temporoparietal gamma activity preceded clinical symptoms of cognitive decline. Neocortical atrophy and disruptions in network activity were prominent in lower-performing groups, with higher education and IQ scores and a lower prevalence of lifestyle factors moderating cognitive decline.
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