Using a cognitive plasticity measure to detect mild cognitive impairment
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Updated: May 8, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Alicia Sales-Galán1, Juan Carlos Meléndez-Moral, Teresa Mayordomo-Rodríguez
1Department of Developmental Psychology, Faculty of Psychology, University of Valencia, Spain.
Abstract:
This study compared performance in two groups of older adults, one healthy and another with mild cognitive impairment (MCI), in order to determine whether or not they exhibit plasticity and to analyze whether or not plastic and non-plastic participants differed after a delay. To measure cognitive plasticity, the Spain-Complutense Verbal Learning Test (TAVEC) was applied to a total of 113 participants over 65 who were divided into two groups: MCI (N = 51) and control (N = 62). It was concluded that healthy participants performed better, but impaired participants also demonstrated some capacity for learning and plasticity, and it was shown that these improvements were maintained after a delay. Therefore, TAVEC seems a fitting, simple procedure with which to measure cognitive plasticity, and an effective indicator of impairment.

