Multimodal MRI prediction of cognitive functioning across the lifespan: separating between-person differences from within-person changes

Brain MRI shows promise for predicting cognitive functioning, but its utility depends on its capacity to capture stable between-person differences (e.g., patient stratification), longitudinal within-person changes (e.g., prognosis, treatment monitoring), or both. Using longitudinal data from 450 adults (aged 21–90; up to three waves, five years apart) in the Dallas Lifespan Brain Study, we benchmarked five modalities, task fMRI, functional connectivity (FC), structural MRI (sMRI), diffusion-weighted imaging (DWI), and arterial spin labeling (ASL), across 37 phenotypes and their combination. Stacking all MRI modalities into one marker predicted cognitive functioning with the highest accuracy (R²=.51), followed by DWI and FC. Variance decomposition showed MRI markers explained substantial between-person variance (up to 60.3%) but modest within-person changes (up to 17.2%) in cognitive functioning. Commonality analysis revealed most markers, except ASL, overlapped with age-related variance in cognitive functioning. These findings clarify the strengths and limitations of MRI markers for stratifying and monitoring cognitive aging. Competing Interest Statement The authors have declared no competing interest. Footnotes

We acknowledge the contribution of data from the Dallas Lifespan Brain Study, see Park, D.C. et al. The Dallas Lifespan Brain Study: A Comprehensive Adult Lifespan Data Set of Brain and Cognitive Aging. Sci Data 12, 846 (2025). https://doi.org/10.1038/s41597-025-04847-7. N.P. was supported by New Zealand Health Research Council Funding (grant numbers 21/618 and 24/838), by Neurological Foundation of New Zealand (grant number 2350 PRG) and by New Zealand Ministry of Business, Innovation & Employment Catalyst Fund (UOA2421 and RTVU2403). https://github.com/HAM-lab-Otago-University/Multimodal-MRI-prediction-Dallas-dataset