Ty O. Easley

The paper develops a deep-learning model to translate spatial topography maps into individualized connectomes, confirming its accuracy and ability to retain brain-cognition associations.

The paper identifies aging profiles using cognitive, affective, and brain reserve measures from UK Biobank data, revealing distinct patterns of emotional wellbeing and cognitive decline.

This study identifies neuroimaging correlates of depression across six large-scale datasets, finding gray matter reductions in specific brain regions and unexpected results in subcortical and functional connectivity analyses.

The paper evaluates the accuracy of classifying ICD-10 diagnostic groups using neuroimaging and socio-demographic features from the UK Biobank, finding limited success compared to age classification.

This paper replicates and improves mental health trait predictions using fMRI data through data manipulations like feature expansion and phenotype balancing.