Daniel A. Kessler

The paper maps whole-brain c-Fos activity to identify distinct neuronal ensembles associated with morphine administration and withdrawal, revealing their spatial and molecular characteristics.

This paper introduces a method to improve fMRI network classification by integrating transcriptional data, enhancing prediction accuracy for schizophrenia and enabling biological interpretation of functional connectivity features.

The paper identifies a low-rank structure in resting state connectomes, showing that a small number of components account for most inter-individual variation and can predict neurocognitive and clinical variables.