Journal of NeurophysiologyNeurosciencePeer-reviewed journal article
Estimating descending activation patterns from EMG in fast and slow movements using a model of the stretch reflex
Abstract
Due to spinal reflex loops, descending activation from the brain is not the only source of muscle activation that ultimately generates movement. This study directly estimates descending activation patterns from measured patterns of muscle activation (EMG) during human arm movements. A simple model of the spinal stretch reflex is calibrated in a postural unloading task and then used to estimate descending activation patterns from muscle EMG patterns and kinematics during voluntary arm motion performed at different speeds. We observed three key features of the estimated descending activation patterns: (1) Within about the first 15% of movement duration, descending and muscle activations are temporally aligned. Thereafter, they diverge and develop qualitatively different temporal profiles. (2) The time course of descending activation is monotonic for slow movements, non-monotonic for fast movements. (3) Varying model parameters like the spinal reflex gain or the level of co-contraction does not qualitatively change the temporal pattern of estimated descending activation. Our findings highlight the substantial contribution of spinal reflex loops to movement generation, while at the same time providing evidence that the brain must generate qualitatively different descending activation patterns for movements that vary in their mechanical dynamics. New & NoteworthyWe propose a new method that directly estimates descending activation from measured EMG signals and arm kinematics by inverting a model of the spinal stretch reflex, without the need for muscle models or for an arm dynamics model. This approach identifies key features of the time structure of descending activation as movement speed is varied, while also revealing the significant contribution of the spinal stretch reflex to movement generation.
- Citations
- 1
- FWCI
- 0.11
- Field percentile
- 33th percentile
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