Aging is associated with gradual alterations in structural and neurochemical characteristics of the brain, which can be assessed in vivo by MRI and MRS modalities. The process of brain aging occurs in accord with a general decline in cognitive-motor performance and increases the risk of neurodegeneration. We used MRI-MRS data from 86 individuals as inputs for machine learning models5 to predict motor performance in healthy individuals. Our analysis shows that application of machine learning algorithms on combination of age, gender and MR data can accurately predict motor performance and has potential to be used as a biomarker for neuro related diseases.
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