Investigating Network Plasticity Effects of Repetitive Brain Stimulation Following Invasive and Noninvasive Methods in Humans

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Project Summary The goal of this Mentored Patient-Oriented Research Career Development Award (K23) application is to support the additional training, mentorship and experience needed to develop a new methodology for analyzing the effects of repetitive brain stimulation using intracranial electroencephalography (iEEG) in humans. One form of repetitive brain stimulation is transcranial magnetic stimulation (TMS). TMS has revolutionized the field of therapeutics for neuropsychiatric disorders – it is a novel, noninvasive treatment option used most commonly for medication-refractory major depressive disorder. Despite this, remission rates from its use are suboptimal and ideal stimulation parameters are unknown. Suboptimal outcomes are due in large part to our poor understanding of TMS neurophysiology and antidepressant effects. TMS is thought to work by altering brain excitability within a network of targeted brain structures; for depression, this target is an emotional network including the dorsolateral prefrontal cortex. The ability of the brain to change excitability in response to repeated stimuli is referred to as plasticity. Noninvasive methods of measuring plasticity, such as scalp EEG and magnetic resonance imaging (MRI), are often imprecise and unreliable. This project proposes a novel method to invasively characterize brain plasticity induced by intracranial stimulation (Aim 1) or TMS (Aim 2) with exquisite spatiotemporal resolution. The method involves using iEEG single-pulse evoked potentials to probe and quantify excitability change (a correlate of plasticity) after repetitive stimulation in epilepsy patients. Network connectivity profiles will be analyzed with both iEEG and resting state MRI (Aim 3) to provide a unique bridge between invasive and noninvasive physiology measures. This project tests the hypothesis that repetitive brain stimulation (delivered via TMS and intracranial stimulation) will alter brain excitability in a parameter-dependent manner, and these effects will be most pronounced within the nodes of the stimulated brain network. A better understanding of how repetitive stimulation propagates through brain networks and alters brain excitability will revitalize the to-date fruitless search for reproducible biomarkers of target engagement and treatment response with these new technologies. Novel aspects of this study include the use of TMS in human subjects with iEEG, and the unique combination of both invasive and noninvasive connectivity measures (iEEG and MRI) to deeply characterize network effects of stimulation. Future directions will be 1) using this method to evaluate and refine novel brain stimulation protocols to optimize plasticity and therapeutic efficacy, and 2) applying learned principles about network effects of repetitive stimulation to inform clinical trial design and therapeutic use in other brain disorders, such as depression. The University of Iowa and this mentor team provide a rich research environment and world-class facilities for implementing this proposal. These K23 activities align with my long-term career goal of optimizing therapeutic brain stimulation to improve patient care.