| Temporal evolution of "automatic gain-scaling". | |
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MedLine Citation:
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PMID: 19439680 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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 ( approximately 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. |
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Authors:
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J Andrew Pruszynski; Isaac Kurtzer; Timothy P Lillicrap; Stephen H Scott |
Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't Date: 2009-05-13 |
Journal Detail:
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Title: Journal of neurophysiology Volume: 102 ISSN: 0022-3077 ISO Abbreviation: J. Neurophysiol. Publication Date: 2009 Aug |
Date Detail:
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Created Date: 2009-08-03 Completed Date: 2009-09-24 Revised Date: 2010-09-27 |
Medline Journal Info:
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Nlm Unique ID: 0375404 Medline TA: J Neurophysiol Country: United States |
Other Details:
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Languages: eng Pagination: 992-1003 Citation Subset: IM |
Affiliation:
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Centre for Neuroscience Studies, Queen's University, Kingston, Ontario K7L 3N6, Canada. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Analysis of Variance Biomechanics Elasticity Elbow / physiology* Electromyography Hand Humans Models, Biological* Motor Activity / physiology* Muscle, Skeletal / physiology* Regression Analysis Time Factors |
| Comments/Corrections | |
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