Changes in Functional Connectivity Predict Outcome of Repetitive Transcranial Magnetic Stimulation Treatment of Major Depressive Disorder.

Journal: Cerebral cortex (New York, N.Y. : 1991)
PMID:

Abstract

Repetitive transcranial magnetic stimulation (rTMS) treatment of major depressive disorder (MDD) is associated with changes in brain functional connectivity (FC). These changes may be related to the mechanism of action of rTMS and explain the variability in clinical outcome. We examined changes in electroencephalographic FC during the first rTMS treatment in 109 subjects treated with 10 Hz stimulation to left dorsolateral prefrontal cortex. All subjects subsequently received 30 treatments and clinical response was defined as ≥40% improvement in the inventory of depressive symptomatology-30 SR score at treatment 30. Connectivity change was assessed with coherence, envelope correlation, and a novel measure, alpha spectral correlation (αSC). Machine learning was used to develop predictive models of outcome for each connectivity measure, which were compared with prediction based upon early clinical improvement. Significant connectivity changes were associated with clinical outcome (P < 0.001). Machine learning models based on αSC yielded the most accurate prediction (area under the curve, AUC = 0.83), and performance improved when combined with early clinical improvement measures (AUC = 0.91). The initial rTMS treatment session produced robust changes in FC, which were significant predictors of clinical outcome of a full course of treatment for MDD.

Authors

  • Juliana Corlier
    TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles CA 90024, USA.
  • Andrew Wilson
    Jenny Alderden is an assistant professor, School of Nursing, Boise State University, Boise, Idaho, and an adjunct assistant professor, College of Nursing, University of Utah, Salt Lake City, Utah. Ginette Alyce Pepper is a professor, and Andrew Wilson is a clinical assistant professor, College of Nursing, University of Utah. Joanne D. Whitney is a professor, College of Nursing, University of Washington, Seattle, Washington. Stephanie Richardson is a professor, Rocky Mountain University of the Health Professions, Provo, Utah. Ryan Butcher is a senior data architect, Biomedical Informatics Team, Center for Clinical and Translational Science, University of Utah. Yeonjung Jo is a doctoral (PhD) student in population health science, College of Nursing, University of Utah. Mollie Rebecca Cummins is a professor, College of Nursing, University of Utah.
  • Aimee M Hunter
    TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles CA 90024, USA.
  • Nikita Vince-Cruz
    TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles CA 90024, USA.
  • David Krantz
    TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles CA 90024, USA.
  • Jennifer Levitt
    TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles CA 90024, USA.
  • Michael J Minzenberg
    TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles CA 90024, USA.
  • Nathaniel Ginder
    TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles CA 90024, USA.
  • Ian A Cook
    TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles CA 90024, USA.
  • Andrew F Leuchter
    TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles CA 90024, USA.