Journal article
TMS motor evoked potential input-output curves predict the neuroplasticity effects of continuous theta burst stimulation
Clinical neurophysiology, v 178, 2110943
01 Oct 2025
PMID: 40752316
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Objective: Continuous theta burst stimulation (cTBS), a form of repetitive transcranial magnetic stimulation (rTMS) known for its inhibitory effects, shows variable responses between individuals, potentially due to differences in neuroplasticity. This study explores whether motor evoked potential (MEP) input–output (IO) parameters measured prior to neuromodulation can predict responses to cTBS. Methods: IO curves were sampled from healthy adults by recording MEPs over a range of single-pulse TMS intensities to obtain parameters including MEP
and S
(midpoint intensity). Subjects later received cTBS (80% AMT, low intensity) over the same location of motor cortex, and their MEPs before and after stimulation were compared. Results: Both MEP
and S
predicted responses, significantly correlating (p < 0.05, R
> 0.25) with individuals’ MEP changes from 10 to 30 min after cTBS. We also validated an easily implementable biomarker not requiring time-consuming sampling of full IO curve: MEP
(median of 10 MEPs at 130 % RMT), which strongly predicted cTBS response (p < 0.005, R
> 0.3). Head-to-head comparison against a genetic biomarker of rTMS responses (BDNF polymorphism) showed that IO based predictors had superior performance in explaining response variability. Conclusion: IO curves derived prior to neuromodulation quickly, reliably predict cTBS-induced changes in cortical excitability. Significance: This work provides an accessible strategy for stratifying responders in diagnostic and therapeutic applications of rTMS; potentially boosting response rates to brain stimulation.
Metrics
6 Record Views
Details
- Title
- TMS motor evoked potential input-output curves predict the neuroplasticity effects of continuous theta burst stimulation
- Creators
- Shreya Parchure - Center for the Neural Basis of CognitionZihang Xu - Center for the Neural Basis of CognitionPriyanka Shah-Basak - Center for the Neural Basis of CognitionBrian Erickson - Drexel University, Psychological and Brain Sciences (Psychology)Denise Harvey - Center for the Neural Basis of CognitionRachel Wurzman - Center for the Neural Basis of CognitionDarrian McAfee - Center for the Neural Basis of CognitionDaniela Sacchetti - Laboratory for Cognition and Neural Stimulation, University of Pennsylvania, Philadelphia, PA, United StatesOlufunsho Faseyitan - Laboratory for Cognition and Neural Stimulation, University of Pennsylvania, Philadelphia, PA, United StatesRoy H. Hamilton - University of Pennsylvania
- Publication Details
- Clinical neurophysiology, v 178, 2110943
- Grant note
- Dana Foundation (100001068) R01 DC012780-01A1; 5T32NS043126-13; 5T32NS091006-10 / National Institutes of Health (http://data.elsevier.com/vocabulary/SciValFunders/100000002) 5T32NS043126-13 / National Institutes of Health (100000002) National Institutes of Health (http://data.elsevier.com/vocabulary/SciValFunders/100000002) University of Pennsylvania (http://data.elsevier.com/vocabulary/SciValFunders/100006920) R01 DC012780-01A1 / National Institutes of Health (100000002) National Institute of Neurological Disorders and Stroke (http://data.elsevier.com/vocabulary/SciValFunders/100000065) University of Pennsylvania (100006920) Dana Foundation (http://data.elsevier.com/vocabulary/SciValFunders/100001068) 5T32NS091006-10 / National Institutes of Health (100000002)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:001546875400001
- Scopus ID
- 2-s2.0-105012199668
- Other Identifier
- 991022065228004721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Clinical Neurology
- Neurosciences