Elizabeth A. Osuch

The paper presents a WM intrinsic connectivity network template derived from 100,000 fMRI scans, showing distinct WM and GM networks with task-related activity and differences in schizophrenia.

This paper introduces a template-driven method to generate dynamic functional network connectivity features from neuroimaging data, showing improved prediction of medication response in mood disorders.

The paper develops a reliable network template and methods to estimate individualized functional networks from resting-state fMRI data across 100k+ individuals, showing how data length and spatial resolution affect network estimation.

The paper uses a kernel SVM algorithm with neuromark ICA to predict treatment response in bipolar and major depressive disorders with up to 89% accuracy.