The Cascade Neural Network Model and a Speed-Accuracy Trade-Off of Arm Movement

Hirayama, Makoto; Kawato, Mitsuo; Jordan, Michael I.

doi:10.1080/00222895.1993.9942047

Cited by 31 publications

(19 citation statements)

References 31 publications

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“…Such differences in the pattern of interlimb transfer for initial direction and final position errors provide further support for the hypothesis that these two parameters may be specified independently during the movement preparation process (Hirayama et al 1993;Gottlieb 1996;Sainburg and Wang 2002).…”

Section: Discussionmentioning

confidence: 63%

Mechanisms underlying interlimb transfer of visuomotor rotations

2003

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We previously reported that opposite arm training improved the initial direction of dominant arm movements, whereas it only improved the final position accuracy of non-dominant arm movements. We now ask whether each controller accesses common, or separate, short-term memory resources. To address this question, we investigated interlimb transfer of learning for visuomotor rotations that were directed oppositely [clockwise (CW)/counterclockwise (CCW)] for the two arms. We expected that if information obtained by initial training was stored in the same short-term memory space for both arms, opposite arm training of a CW rotation would interfere with subsequent adaptation to a CCW rotation. All subjects first adapted to a 30° rotation (CW) in the visual display during reaching movements. Following this, they adapted to a 30° rotation in the opposite direction (CCW) with the other arm. In contrast to our previous findings for interlimb transfer of same direction rotations (CCW/CCW), no effects of opposite arm adaptation were indicated in the initial trials performed. This indicates that interlimb transfer is not obligatory, and suggests that short-term memory resources for the two limbs are independent. Through single trial analysis, we found that the direction and final position errors of the first trial of movement, following opposite arm training, were always the same as those of naive performance. This was true whether the opposite arm was trained with the same or the opposing rotation. When trained with the same rotation, transfer of learning did not occur until the second trial. These findings suggest that the selective use of opposite arm information is dependent on the first trial to probe current movement conditions. Interestingly, the final extent of adaptation appeared to be reduced by opposite arm training of opposing rotations. Thus, the extent of adaptation, but not initial information transfer, appears obligatorily affected by prior opposite arm adaptation. According to our findings, it is plausible that the initiation and the final extent of adaptation involve two independent neural processes. Theoretical implications of these findings are discussed.

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Section: Discussionmentioning

confidence: 63%

Mechanisms underlying interlimb transfer of visuomotor rotations

2003

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“…In particular, the small oscillations are not reproduced. In addition, the models of Plamondon (1995a, b) and Kawato (Hirayama et al 1993), as well as Meyer's model, do not consider the visual feedback. Ho (1992) used optimal control theory to model the control of reaching movements.…”

Section: Review Of the Literaturementioning

confidence: 97%

“…Several other models of reaching movements have been proposed recently (Bullock et al 1993;Hirayama et al 1993;Plamondon 1995a,b). The trajectories generated using these models have smooth velocity pro®les and reproduce the speed/accuracy trade-o found in human movements.…”

Section: Review Of the Literaturementioning

confidence: 97%

Quantization of human motions and learning of accurate movements

Burdet

Milner

1998

Biological Cybernetics

123

102

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This paper presents a mathematical model for the learning of accurate human arm movements. Its main features are that the movement is the superposition of smooth submovements, the intrinsic deviation of arm movements is considered, visual and kinesthetic feed-back are integrated in the motion control, and the movement duration and accuracy are optimized with practice. This model is consistent with the jerky arm movements of infants, and may explain how the adult motion behavior emerges from the infant behavior. Comparison with measurements of adult movements shows that the kinematics of accurate movements are well predicted by the model.

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“…At least two different models may account for this finding. One possibility is that trajectory regulation and final position regulation are mediated by two different control mechanisms (Dizio and Lackner 1995;Hirayama et al 1993;Kawato 1991;see also Ghez 1979;Massion 1992). The first operates in a feed forward manner and regulates trajectory execution while the second regulates final limb posture and is strongly influenced by ongoing visual feedback.…”

Section: Separation Of Trajectory and Final Position Control?mentioning

confidence: 99%