Effects of Perturbation Velocity, Direction, Background muscle activation, and Task Instruction on Long-Latency Responses Measured from Forearm Muscles
Authors: Weinman Jacob , Fatollahkhani Paria Arfa , Zonnino Andrea , Nikonowicz Rebecca , Sergi Fabrizio 
Published: October 2020

AbstractThe centeral nervous system uses feedback processes that occur at multiple time scales to control interactions with the environment. Insight on the neuromechanical mechanisms subserving the faster feedback processes can be gained by applying rapid mechanical perturbations to the limb, and observing the ensuing muscle responses using electromyography (EMG). The long-latency response (LLR) is the fastest process that directly involve cortical areas, with a motorneuron response measurable 50 ms following an imposed limb displacement. Several behavioral factors concerning perturbation mechanics and the active role of muscles prior or during the perturbation can modulate the long-latency response amplitude (LLRa) in the upper limbs, but the interaction between many of these factors had not been systematically studied before.We conducted a behavioral study on thirteen healthy individuals to determine the effect and interaction of four behavioral factors -- background muscle torque, perturbation direction, perturbation velocity, and task instruction -- on the LLRa evoked from the flexor carpi radialis (FCR) and extensor carpi ulnaris (ECU) muscles following the application of wrist displacements. The effects of the four factors listed above were quantified using both a 0D statistical analysis on the average perturbation-evoked EMG signal in the period corresponding to an LLR, and using a timeseries analysis of EMG signals.All factors significantly modulated LLRa, and that their combination nonlinearly contributed to modulating the LLRa. Specifically, all the three-way interaction terms that could be computed without including the interaction between instruction and velocity significantly modulated the LLR. Analysis of the three-way interaction terms of the 0D model indicated that for the ECU muscle, the LLRa evoked when subjects are asked to maintain their muscle activation in response to the perturbations (DNI) was greater than the one observed when subjects yielded (Y) to the perturbations (ΔLLRa — DNI vs. Y: 1.76±0.16 nu, p<0.001), but this effect was not measured for muscles undergoing shortening or in absence of background muscle activation. Moreover, higher perturbation velocity increased the LLRa evoked from the stretched muscle in presence of a background torque (ΔLLRa 200−125 deg/s: 0.94±0.20 nu, p<0.001; ΔLLRa 125−50 deg/s: 1.09 ±0.20 nu, p<0.001), but no effects of velocity were measured in absence of background torque, nor effects of any of those factors was measured on muscles shortened by the perturbations. The time-series analysis indicated the significance of some effects in the LLR region also for muscles undergoing shortening. As an example, the interaction between torque and instruction was significant also for the ECU muscle undergoing shortening, in part due to the composition of a positive and negative modulation of the response due to the interaction between of the two terms. The absence of a nonlinear interaction between task instruction and perturbation velocity suggest that the modulation introduced by these two factors are processed by distinct neural pathways.