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Updated: May 25, 2025

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
Published on: February 14, 2014
Decoding cognitive aging: how white matter tracts and demographics distinguish potential Super-Agers
Mohammad Fili1, Parvin Mohammadiarvejeh2, Guiping Hu3
1School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, 74078, USA. mohammad.fili@okstate.edu.
None:
Most adults experience age-related cognitive decline. However, "Positive-Agers" exhibit superior cognition compared to their age-matched peers. Distinguishing between those with superior cognitive performance and those with cognitive decline over time could better inform treatment therapies in older adults. We developed an algorithm called Optimal Cognitive Scoring (OptiCS) that accurately differentiates "Positive-Agers" from "Cognitive Decliners." This study draws on a cohort of 5797 participants longitudinally enrolled in the UK Biobank. Using a predictive pipeline, OptiCS could strongly differentiate Positive-Agers versus Cognitive Decliners (area under the curve, or AUC of 83%). The top diffusion MRI attributes highlighted tracts implicated in pathological aging, including the fornix from the hippocampus, the tapetum from the splenium of the corpus callosum, and other key tracts. This study provides three key insights: (I) The proposed algorithm offers a robust cognitive scoring system for subtle cognitive changes, (II) OptiCS can use diffusion MRI to accurately gauge cognitive performance, and (III) OptiCS provides a predictive framework for early detection of cognitive decline.
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