Predicting Mental and Neurological Illnesses Based on Cerebellar Normative Features.

ABSTRACT:

Background

Mental and neurological conditions have been linked to structural brain variations. However, aside from dementia, the value of brain structural characteristics derived from brain scans for prediction is relatively low. One reason for this limitation is the clinical and biological heterogeneity inherent to such conditions. Recent studies have implicated aberrations in the cerebellum, a relatively understudied brain region, in these clinical conditions.

Methods

Here, we used machine learning to test the value of individual deviations from normative cerebellar development across the lifespan (based on trained data from >27,000 participants) for prediction of autism spectrum disorder (ASD) (n = 317), bipolar disorder (n = 238), schizophrenia (SZ) (n</

SUBMITTER: Kim M 

PROVIDER: S-EPMC12268537 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature