Temporal Evolution of “Automatic Gain-Scaling”

Author:

Pruszynski J. Andrew,Kurtzer Isaac,Lillicrap Timothy P.,Scott Stephen H.

Abstract

The earliest neural response to a mechanical perturbation, the short-latency stretch response (R1: 20–45 ms), is known to exhibit “automatic gain-scaling” whereby its magnitude is proportional to preperturbation muscle activity. Because gain-scaling likely reflects an intrinsic property of the motoneuron pool (via the size-recruitment principle), counteracting this property poses a fundamental challenge for the nervous system, which must ultimately counter the absolute change in load regardless of the initial muscle activity (i.e., show no gain-scaling). Here we explore the temporal evolution of gain-scaling in a simple behavioral task where subjects stabilize their arm against different background loads and randomly occurring torque perturbations. We quantified gain-scaling in four elbow muscles (brachioradialis, biceps long, triceps lateral, triceps long) over the entire sequence of muscle activity following perturbation onset—the short-latency response, long-latency response (R2: 50–75 ms; R3: 75–105 ms), early voluntary corrections (120–180 ms), and steady-state activity (750–1250 ms). In agreement with previous observations, we found that the short-latency response demonstrated substantial gain-scaling with a threefold increase in background load resulting in an approximately twofold increase in muscle activity for the same perturbation. Following the short-latency response, we found a rapid decrease in gain-scaling starting in the long-latency epoch (∼75-ms postperturbation) such that no significant gain-scaling was observed for the early voluntary corrections or steady-state activity. The rapid decrease in gain-scaling supports our recent suggestion that long-latency responses and voluntary control are inherently linked as part of an evolving sensorimotor control process through similar neural circuitry.

Publisher

American Physiological Society

Subject

Physiology,General Neuroscience

Reference79 articles.

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