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Brain aging and psychometric intelligence: a longitudinal study.

Lutz JänckeS SeleF LiemJ OschwaldS Merillat
Published in: Brain structure & function (2019)
In this study, we examined a large sample of 231 generally healthy older adults across 4 years with regard to several brain anatomical measures (volumes of total grey matter volume: GM, normal appearing white matter: NAWM, lateral ventricle: LV, and white matter hypointensities: WMH) and psychometric intelligence (verbal and non-verbal). The dataset comprised four measurement occasions (baseline, 1-, 2-, and 4-year follow-ups). With this longitudinal data set, we evaluated level-level, level-change, and change-change relationships between the anatomical and psychometric measures using latent growth curve models. Our analyses indicate that GM and NAWM decreased significantly over the course of 4 years with annual percent changes of - 0.73% and - 0.79%, respectively. WMH and LV volumes increase with annual percent changes of 7.3% and 4%, respectively. Verbal and nonverbal IQ measures remained stable in our sample. In addition, we uncovered evidence for level-level and -change associations between several of the brain anatomical measures. With regard to brain-IQ associations, we observed a positive level-level association for GM and NAWM, indicating that participants with larger brain volumes demonstrate higher IQ measures. No substantial evidence was identified for level- or change-change associations between any of the brain metrics and the IQ measures. Taken together, these results suggest that while healthy older adults demonstrated age-related neuroanatomical decline over a time span of 4 years, these degenerative changes are not necessarily linked to simultaneous cognitive deterioration.
Keyphrases
  • white matter
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  • machine learning
  • big data