Predictive and mechanistic biomarkers of treatment response to Transcranial Magnetic Stimulation (TMS) in Psychiatric and Neurocognitive Disorders, identified via TMS-Electroencephalography (EEG) and Resting-State EEG: A systematic review

Electroencephalography (EEG) is a comparatively inexpensive and non-invasive recording technique of neural activity, making it a valuable tool for biomarker discovery in transcranial magnetic stimulation (TMS). This systematic review aimed to examine mechanistic and predictive biomarkers, identified through TMS-EEG or resting-state EEG, of treatment response to TMS in psychiatric and neurocognitive disorders. Nineteen articles were obtained via Embase, APA PsycInfo, MEDLINE, and manual search; conditions included, unipolar depression (k = 13), Alzheimer's disease (k = 3), bipolar depression (k = 2), and schizophrenia (k = 2). Two mechanistic biomarkers were identified: one TMS-EEG marker, reductions in N100 post-dorsolateral prefrontal cortex (DLPFC) repetitive TMS or intermittent theta burst stimulation (iTBS) in unipolar depression (n = 120; k = 2), and one resting-state marker, reductions in theta connectivity post-DLPFC repetitive TMS in unipolar and bipolar depression (n = 89; k = 2). Whereas one predictive TMS-EEG biomarker was isolated: greater baseline N100 was predictive of unipolar depression improvement in DLPFC repetitive TMS and iTBS (n = 113; k = 2). Promising markers were briefly discussed for future research in Alzheimer's disease and schizophrenia. In conclusion, across the psychiatric and neurocognitive disorders considered in this study, TMS-EEG and resting-state mechanistic and predictive biomarkers of depression appear to hold the most promise. Further research is needed to validate the biomarkers identified in depression, to help guide treatment plans and advance precision medicine in psychiatry.