Ram Ballem

DECODE decomposes brain functional states into structure-coupled and decoupled components, revealing AD-related differences in temporal dynamics and connectivity organization.

This study identifies three psychosis neurosubtypes using imaging data, showing distinct connectivity patterns and supporting their biological validity through relative alignment.

The paper identifies sex-dominant neurosubtypes in psychosis using fMRI data and shows their unique dysconnectivity patterns and cognitive implications.

This paper develops a model using resting-state fMRI to identify functional connectivity patterns in schizophrenia, finding a robust cerebellothalamic disruption signature.

This study uses QPP and cPCA to analyze spatiotemporal network changes in AD progression, identifying early disruptions in specific brain networks and showing their potential as biomarkers.

This study uses sgr-ICA with 500 components on a large rsfMRI dataset to identify fine-grained intrinsic connectivity networks (ICNs) and reveals dysconnectivity patterns in schizophrenia.

This study links multi-scale brain connectivity networks to cognitive and behavioral functions in adolescents, finding significant associations with attention, working memory, and behavioral regulation.