Spatiotemporal Dynamics of Stress-Induced Network Reconfigurations Reflect Negative Affectivity

• Published in: Biological psychiatry (1969) Vol. 92; no. 2; pp. 158 - 169
• Main Authors: Kühnel, Anne, Czisch, Michael, Sämann, Philipp G., Brückl, Tanja, Spoormaker, Victor I., Erhardt, Angelika, Grandi, Norma C., Ziebula, Julius, Elbau, Immanuel G., Namendorf, Tamara, Lucae, Susanne, Binder, Elisabeth B., Kroemer, Nils B.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15-07-2022
• Subjects: Dynamic functional connectivity; fMRI; Mood and anxiety disorders; Negative affectivity; Stress; Transdiagnostic; fMRI; Transdiagnostic; Dynamic functional connectivity; Stress; Mood and anxiety disorders; Negative affectivity
• ISSN: 0006-3223; 1873-2402
• DOI: 10.1016/j.biopsych.2022.01.008

Maladaptive stress responses are important risk factors in the etiology of mood and anxiety disorders, but exact pathomechanisms remain to be understood. Mapping individual differences of acute stress-induced neurophysiological changes, especially on the level of neural activation and functional connectivity (FC), could provide important insights in how variation in the individual stress response is linked to disease risk.
Using an established psychosocial stress task flanked by two resting states, we measured subjective, physiological, and brain responses to acute stress and recovery in 217 participants with and without mood and anxiety disorders. To estimate blockwise changes in stress-induced activation and FC, we used hierarchical mixed-effects models based on denoised time series within predefined stress-related regions. We predicted inter- and intraindividual differences in stress phases (anticipation vs. stress vs. recovery) and transdiagnostic dimensions of stress reactivity using elastic net and support vector machines.
We identified four subnetworks showing distinct changes in FC over time. FC but not activation trajectories predicted the stress phase (accuracy = 70%, pperm < .001) and increases in heart rate (R2 = 0.075, pperm < .001). Critically, individual spatiotemporal trajectories of changes across networks also predicted negative affectivity (ΔR2 = 0.075, pperm = .030) but not the presence or absence of a mood and anxiety disorder.
Spatiotemporal dynamics of brain network reconfiguration induced by stress reflect individual differences in the psychopathology dimension of negative affectivity. These results support the idea that vulnerability for mood and anxiety disorders can be conceptualized best at the level of network dynamics, which may pave the way for improved prediction of individual risk.