Joint angle variability in 3D bimanual pointing: uncontrolled manifold analysis

Domkin, Dmitry; Laczkó, József; Djupsjöbacka, Mats; Jarić, Slobodan; Latash, Mark L.

doi:10.1007/s00221-004-2137-1

Cited by 103 publications

(87 citation statements)

References 29 publications

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“…These studies have shown that indices of synergies can increase with practice (Kang et al 2004;Latash et al 2003), or decrease (Domkin et al 2002), or stay unchanged (Domkin et al 2005). A conclusion has been drawn that early stages of practice of a novel task are characterized by emergence and strengthening of synergies stabilizing important performance variables.…”

Section: Effects Of Practice On Modes and Synergiesmentioning

confidence: 99%

Learning effects on muscle modes and multi-mode postural synergies

et al. 2007

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We used the framework of the uncontrolled manifold hypothesis to explore the effects of practice on the composition of muscle groups (M-modes) and multi-M-mode synergies stabilizing the location of the center of pressure (COP). In particular, we tested a hypothesis that practice could lead to a transition from co-contraction muscle activation patterns to reciprocal patterns. We also tested a hypothesis that new sets of M-modes would form stronger synergies stabilizing COP location. Subjects practiced load release tasks for five days while standing on a board with a narrow support surface ("unstable board"). Their M-modes and indices of multi-M-mode synergies were computed during standing without instability and during standing on an unstable board before practice, in the middle of practice, and at the end of practice. During standing without instability, subjects showed two consistent M-modes uniting dorsal and ventral muscles of the body respectively (reciprocal modes). While standing on an unstable board, prior to practice, subjects commonly showed M-modes uniting muscle pairs with opposing actions at major leg joints -co-contraction modes. Such sets of M-modes failed to stabilize the COP location in the anterior-posterior direction. Practice led to better task performance reflected in fewer incidences of lost balance. This was accompanied by a drop in the occurrence of co-contraction M-modes and the emergence of multi-mode synergies stabilizing the COP location. We conclude that the central nervous system uses flexible sets of elemental variables (modes) to ensure stable trajectories of important performance variables (such as COP location). Practice can lead to adjustments in both the composition of M-modes and M-mode covariation patterns resulting in stronger synergies stabilizing COP location.

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Section: Effects Of Practice On Modes and Synergiesmentioning

confidence: 99%

Learning effects on muscle modes and multi-mode postural synergies

et al. 2007

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“…During two-arm pointing, the joints within each arm have been shown to stabilize the trajectory of the endpoint while across two-arms the vectorial distance between the endpoints was stabilized (Domkin et al 2002(Domkin et al , 2005.…”

Section: Hierarchies Of Synergies In Natural Movementsmentioning

confidence: 99%

“…However, in all the cited studies of prehension, the subjects received no feedback on the action of the VF; nevertheless, its action was stabilized by combined action of the four fingers. During pointing tasks, the subject's attention was drawn to relative motion of the two hands; nevertheless, multi-joint synergies stabilized each hand's trajectory were seen (Domkin et al 2002(Domkin et al , 2005. Similarly, during postural tasks, multi-muscle analysis revealed the presence of synergies stabilizing shifts of the center of pressure (COP, the point of application of the resultant force acting on the body from the support surface) despite the fact that no feedback was available on the COP shifts (Krishnamoorthy et al 2003;Wang et al 2005).…”

Section: Hierarchies Of Synergies In Natural Movementsmentioning

confidence: 99%

Hierarchies of synergies: an example of two-hand, multi-finger tasks

2006

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We explored the ability of the central nervous system (CNS) to assemble synergies stabilizing the output of sets of effectors at two levels of a control hierarchy. Specifically, we asked a question: can the CNS organize both two-hand and within-a-hand force stabilizing synergies in a simple two-hand force production task that involves two fingers per hand? Intuitively, one could expect a positive answer; that is, forces produced by each hand are expected to co-vary negatively across trials to bring down the total force variability, while forces produced by each finger within-a-hand are expected to co-vary negatively to reduce the variability of that hand's contribution to the total force. The subjects were instructed to follow a trapezoidal time profile with the signal corresponding to the force produced by a set of instructed fingers in one-hand tasks with two-finger force production and in two-hand tasks with involvement of both symmetrical and asymmetrical finger pairs in the two hands. Finger force co-variation across trials was quantified and used as an index of stabilization of the force produced by all the instructed fingers, and of the force produced by finger pairs within-a-hand. No major differences were seen between the dominant and the non-dominant hand and between the twohand tasks with symmetrical and asymmetrical finger involvement. Stronger synergies were seen in the index-middle finger pair as compared to the ring-little finger pair. The main result of the study is the significantly weaker or even lacking two-finger force stabilizing synergies within-a-hand during two-hand tasks while such synergies were present in one-hand tasks. This observation points at a potential limitation in the ability of the CNS to organize synergies at two levels of a control hierarchy simultaneously. It also allows suggesting a hypothesis on two types of synergies in the human motor repertoire, well-practiced synergies that form a library serving as the foundation for all novel actions, and freshly assembled synergies.

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“…A relatively common thread of those studies which used the UCM approach to address changes in movement coordination has been a decrease in both components of variance with learning (Domkin et al 2005(Domkin et al ,2002Yang and Scholz 2005). Depending on the study, the decrease in V UCM could be smaller than , equal to (Domkin et al 2005) or greater than (Domkin et al 2002) the decrease in V ORT . Based on the results of learning a challenging finger force production task, Latash et al (2003) proposed two stages of motor learning.…”

Section: Goal-equivalent Joint Configuration Variance Increased In Rementioning

confidence: 99%

“…Most studies in adults revealed a decrease in both components of joint configuration variance (V UCM and V ORT ) with practice. However, the decrease in V UCM could be larger than (Domkin et al 2002), equal to (Domkin et al 2005), or smaller than (Kang et al 2004;Yang and Scholz 2005) the decrease in V ORT with practice. A related experiment using a slightly different approach to distinguish variance components revealed primarily decreases in V ORT in an early stage of practice, leading to a higher ratio of the two components, while V UCM decreased more than V ORT at a later stage .…”

Section: Introductionmentioning

confidence: 99%

The role of kinematic redundancy in adaptation of reaching

2006

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Although important differences exist between learning a new motor skill and adapting a well-learned skill to new environmental constraints, studies of force field adaptation have been used frequently in recent years to identify processes underlying learning. Most of these studies have been of reaching tasks that were each hand position was specified by a unique combination of joint angles. At the same time, evidence has been provided from a variety of tasks that the central nervous system takes advantage of the redundancy available to it when planning and executing functional movements. The current study attempted to determine whether a change in the use of joint motion redundancy is associated with the adaptation process. Both experimental and control subjects performed 160 trials of reaching in each of four adaptation phases, while holding the handle of a robot manipulandum. During the first and last adaptation phases, the robot motors were turned off. During phases 2 and 3 the motors produced a velocity-dependent force field to which experimental subjects had to adapt to regain relatively straight line hand movements during reaching to a target, while the motors remained off for the control group. The uncontrolled manifold (UCM) method was used to partition the variance of planar clavicle-scapular, shoulder, elbow and wrist joint movements into two orthogonal components, one (V UCM ) that reflected combinations of joint angles that were equivalent with respect to achieving the average hand path and another (V ORT ) that took the hand away from its average path. There was no change in either variance component for the control group performing 640 nonperturbed reaches across four 'pseudo-adaptation' phases. The experimental group showed adaptation to reaching in the force field that was accompanied initially by an increase in both components of variance, followed by a smaller decrease of V UCM than V ORT during 320 practice reaches in the force field. After initial re-adaptation to reaching to the null field, V UCM was higher in experimental than in control subjects after performing a comparable number of reaches. V UCM was also larger in the experimental group after re-adaptation when compared to the 160 null field reaching trials performed prior to initial force field introduction. The results suggest that the central nervous system makes use of kinematic redundancy, or flexibility of motor patterns, to adapt reaching performance to unusual force fields, a fact that has implications for the hypothesis that motor adaptation requires learning of formal models of limb and environmental dynamics.

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Joint angle variability in 3D bimanual pointing: uncontrolled manifold analysis

Cited by 103 publications

References 29 publications

Learning effects on muscle modes and multi-mode postural synergies

Learning effects on muscle modes and multi-mode postural synergies

Hierarchies of synergies: an example of two-hand, multi-finger tasks

The role of kinematic redundancy in adaptation of reaching

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