Movement Recovery Lab Publishes New Method for Measuring Effects of Nervous System Stimulation

A new paper published in Brain Stimulation reports an efficient approach that provides faster and more reliable estimates of how muscles respond to increasing levels of stimulation delivered to the brain or spinal cord. By gradually increasing stimulation intensity and recording muscle activity, researchers generate “recruitment curves” that show how the nervous system facilitates movement.

These curves are critical in studies of nervous system injury and recovery, but collecting enough data can be time-consuming and uncomfortable for study participants. The new method aims to make this process more efficient while better accounting for uncertainty in the measurements.

The method was developed by the Movement Recovery Lab’s data scientist Vishweshwar Tyagi, MS, together with James McIntosh, PhD and colleagues. Their approach is designed to perform well with limited data and helps clinicians reduce experiment duration and participant discomfort while maintaining accuracy. The authors report that the method can reduce the number of study participants needed to detect changes in motor threshold and nervous system excitability in intervention studies by up to 44%. An accompanying open-source Python software allows other researchers to use the method in their studies.

This work builds on the lab’s ongoing efforts to understand how the brain and spinal cord interact during recovery. The team, led by Jason B. Carmel, MD, PhD, continues to investigate how precise measurements and modeling can help evaluate therapies aimed at restoring movement after nervous system injury.