Refining cognitive dispersion metrics for brain-behavior prediction in aging and mild cognitive impairment
Truc Tran Thanh Nguyen1, Yu-Ling Chang2,3,4,5,6
1Taiwan International Graduate Program in Interdisciplinary Neuroscience National Taiwan University and Academia Sinica Taipei Taiwan.
Introduction:
This study addresses three key issues in the standardization of cognitive dispersion: its operationalizations though intra-individual standard deviation (ISD) versus coefficient of variation (CoV), its reliability, and its dependence on the size of the neuropsychological battery.
Methods:
Cognitive dispersion was calculated in 318 older adults (Mage = 70.7, 61% female). Linear regression tested whether ISD, in the context of mean cognitive performance, provided greater explanatory power than CoV for brain morphometry. We further evaluated 2-year reliability of dispersion and compared psychometric properties across four battery sizes.
Results:
We found that ISD, modeled jointly with mean cognitive performance, was a stronger predictor of entorhinal cortex thickness than CoV, which obscured critical mean-dispersion interactions.
Discussion:
These findings suggest that ISD, rather than CoV, offers a more valid quantification of cognitive dispersion, and that dispersion measures are most informative when derived from adequately comprehensive neuropsychological batteries.
