Considerations for stimulus-response curves in stroke: an investigation comparing collection and analysis methods

Area of Science:

• Neuroscience
• Rehabilitation Medicine
• Biomedical Engineering

Background:

• Stimulus-response curves (SRCs) assess corticospinal tract (CST) neurophysiological strength.
• Standardized methods for SRC measurement and analysis in stroke survivors are lacking.
• CST integrity is crucial for motor recovery post-stroke.

Purpose of the Study:

• To characterize the utility of an abbreviated SRC method in stroke survivors.
• To compare two data collection and two analysis approaches for SRCs.
• To establish a reliable method for assessing corticospinal excitability in stroke.

Main Methods:

• Transcranial magnetic stimulation (TMS) was used to elicit motor evoked potentials (MEPs) in 25 stroke survivors.
• SRCs were collected using TMS intensities referenced to motor threshold (MT) or stimulator output.
• Data were analyzed using a three-parameter sigmoid function and linear regression.

Main Results:

• No significant difference in prediction accuracy (r2) was found between the sigmoid and linear regression analyses.
• Slope parameters differed significantly based on analysis method, independent of data collection approach.
• Linear regression accurately represents SRC slope, correlates strongly with peak slope, and is computationally simpler than the sigmoid function.

Conclusions:

• A linear regression analysis provides a valid and computationally efficient method for analyzing SRCs in stroke studies.
• This approach can serve as a reliable outcome measure for assessing corticospinal excitability in stroke rehabilitation research.
• The findings support the use of linear analysis for abbreviated SRCs in clinical stroke research.