Separating neural influences from peripheral mechanics: the speed-curvature relation in mechanically constrained actions
| Autor: | James Hermus, Dagmar Sternad, Neville Hogan, Joseph A. Doeringer |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Adult
Male Physiology Computer science 0206 medical engineering 02 engineering and technology Kinematics Motor Activity Curvature Rendering (computer graphics) Young Adult 03 medical and health sciences 0302 clinical medicine Control theory Humans Crank General Neuroscience Mechanical impedance 020601 biomedical engineering Biomechanical Phenomena Maxima and minima Complex dynamics Maxima Psychomotor Performance 030217 neurology & neurosurgery Research Article |
| Zdroj: | J Neurophysiol |
| ISSN: | 1522-1598 0022-3077 |
| DOI: | 10.1152/jn.00536.2019 |
| Popis: | While the study of unconstrained movements has revealed important features of neural control, generalizing those insights to more sophisticated object manipulation is challenging. Humans excel at physical interaction with objects, even when those objects introduce complex dynamics and kinematic constraints. This study examined humans turning a horizontal planar crank (radius 10.29 cm) at their preferred and three instructed speeds (with visual feedback), both in clockwise and counterclockwise directions. To explore the role of neuromechanical dynamics, the instructed speeds covered a wide range: fast (near the limits of performance), medium (near preferred speed), and very slow (rendering dynamic effects negligible). Because kinematically constrained movements involve significant physical interaction, disentangling neural control from the influences of biomechanics presents a challenge. To address it, we modeled the interactive dynamics to “subtract off” peripheral biomechanics from observed force and kinematic data, thereby estimating aspects of underlying neural action that may be expressed in terms of motion. We demonstrate the value of this method: remarkably, an approximately elliptical path emerged, and speed minima coincided with curvature maxima, similar to what is seen in unconstrained movements, even though the hand moved at nearly constant speed along a constant-curvature path. These findings suggest that the neural controller takes advantage of peripheral biomechanics to simplify physical interaction. As a result, patterns seen in unconstrained movements persist even when physical interaction prevents their expression in hand kinematics. The reemergence of a speed-curvature relation indicates that it is due, at least in part, to neural processes that emphasize smoothness and predictability. NEW & NOTEWORTHY Physically interacting with kinematic constraints is commonplace in everyday actions. We report a study of humans turning a crank, a circular constraint that imposes constant hand path curvature and hence should suppress variations of hand speed due to the power-law speed-curvature relation widely reported for unconstrained motions. Remarkably, we found that, when peripheral biomechanical factors are removed, a speed-curvature relation reemerges, indicating that it is, at least in part, of neural origin. |
| Databáze: | OpenAIRE |
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