False positives associated with responder/non-responder analyses based on motor evoked potentials

Area of Science:

• Neuroscience
• Biomedical Engineering

Background:

• Non-invasive brain stimulation research often uses responder analysis to classify participants.
• This method dichotomizes or trichotomizes continuous data to categorize individuals as responders or non-responders.

Purpose of the Study:

• To investigate the Type I error rate in motor evoked potential (MEP) data when subjected to responder analyses.
• To evaluate the reliability of classifying participants as responders or non-responders.

Main Methods:

• Recorded motor evoked potentials (MEPs) from the first dorsal interosseous muscle in 52 healthy volunteers.
• Applied four different classification techniques: two-step cluster analysis, dichotomized thresholding, relative method, and baseline variance method.
• Classified participants as responders or non-responders based on MEP data.

Main Results:

• A substantial proportion of participants were classified as responders (21-71%) even in the absence of any intervention.
• This indicates a high rate of false positives when using responder analyses on continuous MEP data.

Conclusions:

• Responder analysis applied to continuous variables like Transcranial Magnetic Stimulation (TMS) MEPs is associated with a very large Type I error.
• The findings underscore the need for caution and alternative analytical approaches when interpreting responder status in neurostimulation studies.