Brain-wide Electrical Spatiotemporal Dynamics Encode Depression Vulnerability

Rainbo Hultman, Kyle Ulrich, Benjamin D. Sachs, Cameron Blount, David E. Carlson, Nkemdilim Ndubuizu, Rosemary C. Bagot, Eric M. Parise, Mai Anh T. Vu, Neil M. Gallagher, Joyce Wang, Alcino J. Silva, Karl Deisseroth, Stephen D. Mague, Marc G. Caron, Eric J. Nestler, Lawrence Carin*, Kafui Dzirasa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

106 Scopus citations


Brain-wide fluctuations in local field potential oscillations reflect emergent network-level signals that mediate behavior. Cracking the code whereby these oscillations coordinate in time and space (spatiotemporal dynamics) to represent complex behaviors would provide fundamental insights into how the brain signals emotional pathology. Using machine learning, we discover a spatiotemporal dynamic network that predicts the emergence of major depressive disorder (MDD)-related behavioral dysfunction in mice subjected to chronic social defeat stress. Activity patterns in this network originate in prefrontal cortex and ventral striatum, relay through amygdala and ventral tegmental area, and converge in ventral hippocampus. This network is increased by acute threat, and it is also enhanced in three independent models of MDD vulnerability. Finally, we demonstrate that this vulnerability network is biologically distinct from the networks that encode dysfunction after stress. Thus, these findings reveal a convergent mechanism through which MDD vulnerability is mediated in the brain. Patterns of brain activity predict vulnerability versus resilience to depression in response to stress.

Original languageEnglish (US)
Pages (from-to)166-180.e14
Issue number1
StatePublished - Mar 22 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Inc.


  • brain
  • depression
  • electricity
  • ketamine
  • networks
  • oscillations
  • spatiotemporal dynamics
  • stress

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology


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