The functional neurobiology of negative affective traits across regions, networks, signatures, and a machine learning multiverse
Maurizio Sicorello, Peter J. Gianaros, Aidan G.C. Wright, Paul Bogdan, Thomas E. Kraynak, Stephen B. Manuck, Christian G. Schmahl, Tor Dessart Wager
The paper investigates the neural basis of negative affective traits using fMRI data from 458 adults, finding that whole-brain machine learning models better predict stress vulnerability than region- or network-level measures.
bioRxiv · May 15, 2025 · PreprintNeuroscience