Optimized methods for measuring brain excitability in depression

Stanford University, Stanford CA

Investigators

Linked publications, trials & patents

Abstract

PROJECT SUMMARY Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression, but clinical responses are highly variable. This is because the underlying neural mechanisms, as well as the optimal treatment parameters, remain unclear. Treatment targeting the dorsolateral prefrontal cortex (dlPFC) aims to improve symptoms by restoring impaired prefrontal excitability. However, evidence of impaired excitability in depression and subsequent neural change after rTMS is limited due to the lack of reliable markers of prefrontal excitability that can be measured and tracked during rTMS. There is an urgent need for reliable markers of prefrontal excitability to direct personalized treatment and guide systematic screening of novel protocols. Our long-term goal is to improve depression treatment by establishing reliable markers of prefrontal excitability. We hypothesize that biologically-grounded TMS parameter adjustments can optimize prefrontal excitability measurements to effectively capture alterations in depression and modulation following rTMS. The early local TMS-evoked potential (EL-TEP) is a short-latency response recorded over the dlPFC stimulation site that has been shown to be altered in depression and correlate with treatment outcome, but has suffered from low signal-to-noise and reliability issues. We recently developed TARGET (Targeting with Automated Real-time Guidance for Enhancing TEPs) to enhance EL-TEPs by dynamically adjusting TMS parameters, increasing EL- TEP signal-to-noise three-fold and reliability two-fold. However, TARGET's lengthy optimization time, lack of full automation, unclear neural impact, and uncharacterized alteration in depression limit its current utility. We will 1) investigate how adjusting TMS parameters affects neural activity measured with intracranial EEG, 2) optimize TARGET and study EL-TEPs in depression, and 3) test how optimized EL-TEPs detect changes in prefrontal excitability induced by cognitive tasks and rTMS. Impact: This research will characterize TMS parameter effects on neural responses and develop efficient methods for cortical excitability assessment. Success will enhance brain-based monitoring and facilitate novel personalized treatments guided by cortical excitability. Future work will apply this approach to obtain reliable noninvasive measures of cortical excitability across various brain regions and disorders. This work will lay the foundation for clinical trials using TARGET-optimized EL-TEPs as surrogate endpoints for rapid evaluation of treatment effects.