Automated-parameterization of the motor evoked potential and cortical silent period induced by transcranial magnetic stimulation

Christopher A. Rábago, Jack L. Lancaster, Shalini Narayana, Wei Zhang, Peter T. Fox

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Objective: To standardize the characterization of motor evoked potential (MEP) and cortical silent period (CSP) recordings elicited with transcranial magnetic stimulation (TMS). Methods: A computer-based, automated-parameterization program (APP) was developed and tested which provides a comprehensive set of electromyography (EMG) magnitude and temporal measures. The APP was tested using MEP, CSP, and isolated CSP (iCSP) TMS stimulus-response data from a healthy adult population (N = 13). Results: The APP had the highest internal reliability (Cronbach's alpha = .98) for CSP offset time compared with two prominent automated methods. The immediate post-CSP EMG recovery level was 49% higher than the pre-TMS EMG level. MEP size (peak amplitude, mean amplitude, peak-to-peak amplitude, and area) correlated higher with effective E-field (Eeff) than other intensity measures (r ≈ 0.5 vs. r ≈ 0.3) suggesting that Eeff is better suited for standardizing MEP stimulus-response relationships. Conclusions: The APP successfully characterized individual and mean epochs containing MEP, CSP, and iCSP responses. The APP provided common signal and temporal measures consistent with previous studies and novel additional parameters. Significance: With the use of the APP modeling method and the Eeff, a standard approach for the analysis and reporting of MEP-CSP complex and iCSP measurements is achievable.

Original languageEnglish (US)
Pages (from-to)1577-1587
Number of pages11
JournalClinical Neurophysiology
Volume120
Issue number8
DOIs
StatePublished - Aug 2009

Keywords

  • Automated-parameterization
  • Cortical silent period
  • Effective electrical-field
  • Motor evoked potential
  • Transcranial magnetic stimulation

ASJC Scopus subject areas

  • Sensory Systems
  • Neurology
  • Clinical Neurology
  • Physiology (medical)

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