Input-Output Slope Predicts Effects of cTBS on Motor Evoked Potentials

Shreya working on cTBS rig


SEAS 2021
Engineering and Applied Sciences

Project Summary

Transcranial Magnetic Stimulation (TMS) is a non-invasive brain stimulation method used to treat many neuropsychological disorders. Continuous Theta Burst Stimulation (cTBS) uses 50 Hz triplets of TMS delivered at 5 Hz, and is frequently characterized as inhibitory stimulation. However there is high inter-individual variability in cTBS effects. Measures to predict the neuromodulatory effects of cTBS on an individual basis would advance therapeutics by informing understanding of factors that influence cortical excitability.

In this experiment, TMS was applied to the motor cortex to stimulate hand muscle twitches called motor evoked potentials (MEPs), which indicate the intensity of response to TMS. MEPs were recorded immediately before, after and at 10 minute intervals for 30 minutes after administering cTBS. An input-output curve (IO) of MEPs, which indicates excitability with respect to varying stimulation intensities, was also collected. Then we explored whether IO slope measured prior to the administration of cTBS could predict subsequent changes in MEPs induced by cTBS.

I derived IO curves for each individual and obtained a slope of the linear regression, to correlate with the change in MEP in subjects at times after cTBS. A power regression was used to fit curves to graphs. IO slope was significantly correlated (p<0.05) with cTBS-induced changes in MEP amplitude at 0 and 10, but not at 20 and 30 minutes after cTBS stimulation. IO slope was also correlated with the average of MEP change across all time-points (p<0.05).

Thus IO slopes derived prior to the administration of cTBS, may serve as a reliable predictor of post-stimulation MEP responses after cTBS. Using this may point toward a strategy for stratifying individuals who are most likely to experience inhibitory or excitatory cortical after-effects from cTBS stimulation. Statistical significance of regressions as predictors at various times post-stimulation may provide insight into the duration of modeled effects of cTBS.

Doing this research, I learnt about neural technologies development and use to better understand the human brain. I was able to investigate a technology that modulates neural plasticity to apply such research to help patients regain brain function and improve lives. Over the course of the summer, I conducted Electromyography (EMG) to measure muscle activity of the first dorsal interosseous and analyzed it as MEP data. I also conducted Electroencephalography (EEG) which included setting up a montage, running the equipment, and using specialized software to filter that data. I learnt about compatibility of different imaging and stimulation technologies. I also gained valuable interactions with the subjects coming into the lab during the process of recruitment, scheduling, and testing.

I also had the opportunity to submit an abstract to the 2018 NYC Neuromodulation Conference, and my poster about this study was selected to be presented on August 24th, 2018. Attending the conference, I gained great exposure to the vast field of neuromodulation. These summer experiences have been valuable for defining my career goals in medical research.