Brain Stimulation (Mar 2022)

Large-scale EEG neural network changes in response to therapeutic TMS

  • Michael C. Gold,
  • Shiwen Yuan,
  • Eric Tirrell,
  • E. Frances Kronenberg,
  • Jee Won D. Kang,
  • Lauren Hindley,
  • Mohamed Sherif,
  • Joshua C. Brown,
  • Linda L. Carpenter

Journal volume & issue
Vol. 15, no. 2
pp. 316 – 325

Abstract

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Background: Transcranial magnetic stimulation (TMS) is an effective therapy for patients with treatment-resistant depression. TMS likely induces functional connectivity changes in aberrant circuits implicated in depression. Electroencephalography (EEG) “microstates” are topographies hypothesized to represent large-scale resting networks. Canonical microstates have recently been proposed as markers for major depressive disorder (MDD), but it is not known if or how they change following TMS. Methods: Resting EEG was obtained from 49 MDD patients at baseline and following six weeks of daily TMS. Polarity-insensitive modified k-means clustering was used to segment EEGs into constituent microstates. Microstates were localized via sLORETA. Repeated-measures mixed models tested for within-subject differences over time and t-tests compared microstate features between TMS responder and non-responder groups. Results: Six microstates (MS-1 - MS-6) were identified from all available EEG data. Clinical response to TMS was associated with increases in features of MS-2, along with decreased metrics of MS-3. Nonresponders showed no significant changes in any microstate. Change in occurrence and coverage of both MS-2 (increased) and MS-3 (decreased) correlated with symptom change magnitude over the course of TMS treatment. Conclusions: We identified EEG microstates associated with clinical improvement following a course of TMS therapy. Results suggest selective modulation of resting networks observable by EEG, which is inexpensive and easily acquired in the clinic setting.

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