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

doi:10.1016/j.cell.2018.02.012

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Brain-wide Electrical Spatiotemporal Dynamics Encode Depression Vulnerability

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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, …

Cell (Cambridge), Vol.173(1), pp.166-180.e14

03/22/2018

DOI: 10.1016/j.cell.2018.02.012

PMCID: PMC6005365

PMID: 29502969

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Abstract

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. [Display omitted] •Brain-wide electrical spatiotemporal dynamic map of stress states•Hippocampally directed network signals stress vulnerability in stress-naive animals•Early life stress increases activity in stress vulnerability network•Stress vulnerability network is mechanistically distinct from pathology networks Patterns of brain activity predict vulnerability versus resilience to depression in response to stress.

stress

ketamine

electricity

depression

networks

brain

oscillations

spatiotemporal dynamics

Details

Title: Subtitle: Brain-wide Electrical Spatiotemporal Dynamics Encode Depression Vulnerability
Creators: Rainbo Hultman - Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
Kyle Ulrich - Department of Electrical and Computer Engineering, Duke University, Durham, NC 22208, USA
Benjamin D Sachs - Department of Psychological and Brain Sciences, Villanova University, Villanova, PA, 19085, USA
Cameron Blount - Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
David E Carlson - Department of Civil and Electrical Engineering, Biostatistics and Bioinformatics, Duke University, Durham, NC 22208, USA
Nkemdilim Ndubuizu - Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
Rosemary C Bagot - Fishberg, Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, New York, NY 10029, USA
Eric M Parise - Fishberg, Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, New York, NY 10029, USA
Mai-Anh T Vu - Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
Neil M Gallagher - Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
Joyce Wang - Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
Alcino J Silva - Departments of Neurobiology, Psychiatry & Behavioral Sciences and Psychology, Integrative Center for Learning and Memory, Brain Research Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
Karl Deisseroth - Departments of Bioengineering and Psychiatry and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
Stephen D Mague - Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
Marc G Caron - Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA
Eric J Nestler - Fishberg, Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, New York, NY 10029, USA
Lawrence Carin - Department of Electrical and Computer Engineering, Duke University, Durham, NC 22208, USA
Kafui Dzirasa - Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
Resource Type: Journal article
Publication Details: Cell (Cambridge), Vol.173(1), pp.166-180.e14
Publisher: Elsevier Inc
DOI: 10.1016/j.cell.2018.02.012
PMID: 29502969
PMCID: PMC6005365
ISSN: 0092-8674
eISSN: 1097-4172
Grant note: DOI: 10.13039/100000002, name: NIH, award: MH79201-03S1; DOI: 10.13039/100000002, name: NIH, award: MH79201; name: Lennon Family Foundation; DOI: 10.13039/100000002, name: NIH, award: MH099192-05S1, MH099192-05S2, MH096890, MH099192-05S2; name: DARPA HIST Program; name: One Mind Institute; DOI: 10.13039/100000002, name: NIH, award: MH099192; name: Kerima L. Collier
Language: English
Date published: 03/22/2018
Academic Unit: Molecular Physiology and Biophysics; Psychiatry; Iowa Neuroscience Institute
Record Identifier: 9984065750302771

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