title: Two-phase strategy of neural control for planar reaching movements: I. XY coordination variability and its relation to end-point variability.
abstract: A quantitative model of optimal transport-aperture coordination (TAC) during reach-to-grasp movements has been developed in our previous studies. The utilization of that model for data analysis allowed, for the first time, to examine the phase dependence of the precision demand specified by the CNS for neurocomputational information processing during an ongoing movement. It was shown that the CNS utilizes a two-phase strategy for movement control. That strategy consists of reducing the precision demand for neural computations during the initial phase, which decreases the cost of information processing at the expense of lower extent of control optimality. To successfully grasp the target object, the CNS increases precision demand during the final phase, resulting in higher extent of control optimality. In the present study, we generalized the model of optimal TAC to a model of optimal coordination between X and Y components of point-to-point planar movements (XYC). We investigated whether the CNS uses the two-phase control strategy for controlling those movements, and how the strategy parameters depend on the prescribed movement speed, movement amplitude and the size of the target area. The results indeed revealed a substantial similarity between the CNS's regulation of TAC and XYC. First, the variability of XYC within individual trials was minimal, meaning that execution noise during the movement was insignificant. Second, the inter-trial variability of XYC was considerable during the majority of the movement time, meaning that the precision demand for information processing was lowered, which is characteristic for the initial phase. That variability significantly decreased, indicating higher extent of control optimality, during the shorter final movement phase. The final phase was the longest (shortest) under the most (least) challenging combination of speed and accuracy requirements, fully consistent with the concept of the two-phase control strategy. This paper further discussed the relationship between motor variability and XYC variability.
authors.affiliation: IfADo-Leibniz Research Centre for Working Environment and Human Factors, Ardeystrasse 67, 44139, Dortmund, Germany. rand@ifado.de
authors.forename: Miya K
authors.initials: MK
authors.lastname: Rand
authors.forename: Yury P
authors.initials: YP
authors.lastname: Shimansky
mesh_terms: D000328:Adult; D000465:Algorithms; D001132:Arm / Q000502:physiology*; D001696:Biomechanical Phenomena; D003627:Data Interpretation, Statistical; D023381:Endpoint Determination; D005260:Female; D006225:Hand / Q000502:physiology*; D006801:Humans; D008297:Male; D008959:Models, Neurological; D015233:Models, Statistical; D009010:Monte Carlo Method; D009068:Movement / Q000502:physiology; D011597:Psychomotor Performance / Q000502:physiology*; D055815:Young Adult