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Erschienen in: Experimental Brain Research 1-2/2010

01.11.2010 | Research Article

Phase dependence of transport–aperture coordination variability reveals control strategy of reach-to-grasp movements

verfasst von: Miya K. Rand, Y. P. Shimansky, Abul B. M. I. Hossain, George E. Stelmach

Erschienen in: Experimental Brain Research | Ausgabe 1-2/2010

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Abstract

Based on an assumption of movement control optimality in reach-to-grasp movements, we have recently developed a mathematical model of transport–aperture coordination (TAC), according to which the hand–target distance is a function of hand velocity and acceleration, aperture magnitude, and aperture velocity and acceleration (Rand et al. in Exp Brain Res 188:263–274, 2008). Reach-to-grasp movements were performed by young adults under four different reaching speeds and two different transport distances. The residual error magnitude of fitting the above model to data across different trials and subjects was minimal for the aperture-closure phase, but relatively much greater for the aperture-opening phase, indicating considerable difference in TAC variability between those phases. This study’s goal is to identify the main reasons for that difference and obtain insights into the control strategy of reach-to-grasp movements. TAC variability within the aperture-opening phase of a single trial was found minimal, indicating that TAC variability between trials was not due to execution noise, but rather a result of inter-trial and inter-subject variability of motor plan. At the same time, the dependence of the extent of trial-to-trial variability of TAC in that phase on the speed of hand transport was sharply inconsistent with the concept of speed–accuracy trade-off: the lower the speed, the larger the variability. Conversely, the dependence of the extent of TAC variability in the aperture-closure phase on hand transport speed was consistent with that concept. Taking into account recent evidence that the cost of neural information processing is substantial for movement planning, the dependence of TAC variability in the aperture-opening phase on task performance conditions suggests that it is not the movement time that the CNS saves in that phase, but the cost of neuro-computational resources and metabolic energy required for TAC regulation in that phase. Thus, the CNS performs a trade-off between that cost and TAC regulation accuracy. It is further discussed that such trade-off is possible because, due to a special control law that governs optimal switching from aperture opening to aperture closure, the inter-trial variability of the end of aperture opening does not affect the high accuracy of TAC regulation in the subsequent aperture-closure phase.
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Fußnoten
1
The difference in residual error magnitude (the black columns in Fig. 1a) between the low-speed condition and the normal-speed condition was significant both for the short-transport distance (t test: t(24196) = 29.8, P < 0.001) and the long-transport distance (t(31898) = 40.3, P < 0.001).
 
2
To someone who is used to thinking about motor control in terms of kinematic parameters as continuous sequences of values within a specific time interval, it might seem that, since, for instance, acceleration as a function of time can be computed as a time derivative of velocity, it must be sufficient to include only one such parameter in equations. In the case of the equation describing transport-aperture coordination; however, instantaneous values of such parameters are involved and, therefore, a different logic applies. Knowledge of hand velocity at a certain time point t in general does not allow one to calculate hand acceleration and vice versa. For this reason, these kinematic variables are viewed in theoretical mechanics as state coordinates independent of each other.
 
3
From an optimality approach perspective, this means that expenditures related to the utilization of neuro-computational resources must be included in the criterion of task performance optimality as a component with a significant weight, while the weight of performance time in that criterion is much less significant. Under different experimental conditions, in which time expenditures are critical, for example, when reach-to-grasp is performed in a context of a game in which the overall speed improves the score, the criterion of reach-to-grasp optimality should include the time duration of hand transport optimality.
 
4
According to the traditional two-component model for aiming movements, the initial component of hand transport is controlled in a ballistic manner for saving movement time, and during the later component, the arm is guided to the target in a (visual) feedback control mode (Elliott et al. 2001). However, since the TAC model for the aperture-closure phase is highly accurate even without vision (Rand et al. 2007), the TAC model’s precision does not critically depend on processing visual feedback.
 
5
It is assumed here that the “turning on” does not take significant time because the CNS is a highly parallel system.
 
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Metadaten
Titel
Phase dependence of transport–aperture coordination variability reveals control strategy of reach-to-grasp movements
verfasst von
Miya K. Rand
Y. P. Shimansky
Abul B. M. I. Hossain
George E. Stelmach
Publikationsdatum
01.11.2010
Verlag
Springer-Verlag
Erschienen in
Experimental Brain Research / Ausgabe 1-2/2010
Print ISSN: 0014-4819
Elektronische ISSN: 1432-1106
DOI
https://doi.org/10.1007/s00221-010-2428-7

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