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A Novel Experimental Protocol for Studying the Task-Dependent Contribution of the Brainstem to Long-Latency Responses via MRI-Compatible Robotics

Rebecca C. Nikonowicz, Fabrizio Sergi

Year
2024
Citations
2

Abstract

Methodological constraints have hindered direct in vivo measurement of reticulospinal tract (RST) function. The RST contributes to the increase in the amplitude of a long latency response (LLR), a stereotypical response evoked in stretched muscles, that arises when participants are asked to “resist” a perturbation. Thus, functional magnetic resonance imaging (fMRI) during robot-evoked LLRs under different task goals may be a method to measure motor-related RST function. We developed the Dual Motor StretchWrist (DMSW), a new MR-compatible robotic perturbation system, and validated its functionality via experiments that used surface electromyography (sEMG) and fMRI. In a first study conducted outside the MRI scanner, we used sEMG to measure wrist flexor muscle activity associated with LLRs under different task instructions on six participants. Participants were given a Yield or Resist instruction before each trial and performance feedback based on the measured resistive torque was provided after every “Resist” trial to standardize LLR amplitude. In a second study, ten participants completed two sessions of perturbations under 1) Yield, 2) Resist, and 3) Yield Slow task conditions (control) during whole-brain fMRI. Statistical analysis of sEMG data shows significantly greater LLR amplitude in Resist relative to Yield. fMRI analysis indicates increased activation primarily in the bilateral medulla, contralateral pons (both possible RST contributions), and primary motor cortex in the Resist condition. The results validate the capability of the DMSW to elicit LLRs of wrist muscles with different amplitudes as a function of task instruction, and its capability of simultaneous operation during fMRI.

Keywords

BrainstemLatency (audio)RoboticsComputer scienceProtocol (science)Artificial intelligenceTask (project management)NeuroscienceRobotPsychology

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