Elizaveta Levina

Identifying a neurochemical signature of the paraventricular nucleus of the thalamus that predicts individual variability in cue-reward learning

The paper identifies a neurochemical signature in the paraventricular nucleus of the thalamus that predicts individual differences in cue-reward learning in rats.

Guiding and interpreting brain network classification with transcriptional data

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.

Fundamental Differences: A Basis Set for Characterizing Inter-Individual Variation in Resting State Connectomes

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.