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Transcranial magnetic stimulation (TMS) is utilized as a treatment method for a variety of neurological and psychiatric disorders. The standard dose parameter for administration of TMS is known as the resting motor threshold (RMT). Between individuals, the RMT has traditionally been thought to reflect differences in neuroanatomy; however, the functional state of the brain has also been shown to have an influence on this value. In this study, 19 mild traumatic brain injury participants (mTBI) resting state electroencephalography (EEG) was obtained before undergoing TMS treatment. Various time frequency and power spectra values were derived from this EEG data to examine the relationship between RMT and neurophysiology. These EEG connectivity metrics were then used to establish relationships with RMT alone and accounting for differences in individual neuroanatomy. We found that the incorporation of EEG functional connectivity improved multiple regression model predictions of inter-participant RMT variability than neuroanatomy alone. Future investigations into the evaluation of EEG in predicting RMT variability should include a larger participant population with a healthy control.

Transcranial magnetic stimulation is a noninvasive neuromodulation technique utilized to treat several neuropsychiatric disorders. Schizophrenia patients typically experience positive and negative symptoms, which are commonly treated with antipsychotic medications. Repetitive (r)TMS is explored to alleviate these symptoms by modulating cortical excitability. TMS stimulation strength is determined by the resting motor threshold (RMT), which is determined from single pulse stimulation to the precentral gyrus region of the brain. In this study, 62 schizophrenia and 41 healthy participants’ magnetic resonance imaging (MRI) were used to create anatomically accurate head models. Head models were then used to calculate the coil-to-cortex distance (CCD), gray matter volume (GMV), and finite element analysis was performed to calculate the induced electric field strength (EFS) and depolarized gray matter volume (DGMV). These MRI-derived parameters were then evaluated to establish their relationship with clinically collected RMT in both healthy and schizophrenia populations. In both populations, RMT correlated with CCD, EFS, and DGMV. Our hypothesis that the presence of schizophrenia would have a negative impact on the influence of MRI model-driven parameters was largely supported. Future investigations into RMT variability should incorporate structural connectivity using white matter-based fiber tractography and functional connectivity.