Arm trajectory formation in monkeys

Bizzi, Emilio; Accornero, N.; Chapple, William D.; Hogan, Neville

doi:10.1007/bf00238107

Cited by 313 publications

(78 citation statements)

References 15 publications

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“…This idea appears somewhat consistent with equilibrium point hypotheses, which suggest that central representation of aimed movements is best described as a series of programmed postures (Bizzi et al 1982;Feldman 1966;Feldman et al 1998;Jaric et al 1994;Latash and Gottlieb 1990;Latash and Gutman 1993;Bizzi 1978, 1979). Jaric et al (1992Jaric et al ( , 1994 provided evidence for such positional control through a learning study in which different groups of subjects practiced single joint movements from several start locations to either a fixed position in space or a fixed distance from start location.…”

Section: Specification Of Movement Extentsupporting

confidence: 73%

“…In contrast to this hypothesis, a separate line of research has supported the idea that limb configurations, corresponding to final hand position, best reflect the central representation of aimed movements (Bizzi et al 1982;Feldman 1966;Feldman et al 1998;Jaric et al 1994;Latash and Gottlieb 1990;Latash and Gutman 1993;Bizzi 1978, 1979). The equilibrium point hypothesis, developed by Feldman (1966) and originally supported by an elegant series of experiments in deafferented monkeys Bizzi 1978, 1979), proposes that the CNS controls movements by modifying the length-tension characteristics of muscles such that the equilibrium position for a set of agonist/antagonist muscles corresponds to a desired limb configuration.…”

Section: Introductionmentioning

confidence: 99%

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Effects of Altering Initial Position on Movement Direction and Extent

Sainburg¹,

Lateiner

Latash

et al. 2003

Journal of Neurophysiology

103

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. Effects of altering initial position on movement direction and extent. J Neurophysiol 89: 401-415, 2003; 10.1152/jn.00243.2002. The purpose of this study was to examine the relative influence of initial hand location on the direction and extent of planar reaching movements. Subjects performed a horizontal-plane reaching task with the dominant arm supported above a table top by a frictionless air-jet system. A start circle and a target were reflected from a horizontal projection screen onto a horizontally positioned mirror, which blocked the subject's view of the arm. A cursor, representing either actual or virtual finger location, was only displayed between each trial to allow subjects to position the cursor in the start circle. Prior to occasional "probe trials," we changed the start location of the finger relative to the cursor. Subjects reported being unaware of the discrepancy between cursor and finger. Our results indicate that regardless of initial hand location, subjects did not alter the direction of movement. However, movement distance was systematically adjusted in accord with the baseline target position. Thus when the hand start position was perpendicularly displaced relative to the target direction, neither the direction nor the extent of movement varied relative to that of baseline. However, when the hand was displaced along the target direction, either anterior or posterior, movements were made in the same direction as baseline trials but were shortened or lengthened, respectively. This effect was asymmetrical such that movements from anterior displaced positions showed greater distance adjustment than those from posterior displaced positions. Inverse dynamic analysis revealed substantial changes in elbow and shoulder muscle torque strategies for both right/left and anterior/posterior pairs of displacements. In the case of right/left displacements, such changes in muscle torque compensated changes in limb configuration such that movements were made in the same direction and to the same extent as baseline trials. Our results support the hypothesis that movement direction is specified relative to an origin at the current location of the hand. Movement extent, on the other hand, appears to be affected by the workspace learned during baseline movement experience.

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Section: Specification Of Movement Extentsupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Effects of Altering Initial Position on Movement Direction and Extent

Sainburg¹,

Lateiner

Latash

et al. 2003

Journal of Neurophysiology

103

View full text Add to dashboard Cite

show abstract

“…The planned movement was given as an input signal consisting of three EP's: the starting angle, an angle midway, and the planned angle at the endpoint. This double-step EP-trajectory was similar to the trajectory used by Kistemaker et al (2006) and chosen this way since it has been indicated that EP does not shift instantaneously from starting to endpoint (Bizzi et al 1982). For simplicity, feedback gains were kept at constant values of −0.4 m −1 for muscle fiber length and −0.15 s/m for muscle fiber contraction velocity in all simulations described in this study.…”

Section: Modelsmentioning

confidence: 99%

Conclusions on motor control depend on the type of model used to represent the periphery

et al. 2012

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Within the field of motor control, there is no consensus on which kinematic and kinetic aspects of movements are planned or controlled. Perturbing goal-directed movements is a frequently used tool to answer this question. To be able to draw conclusions about motor control from kinematic responses to perturbations, a model of the periphery (i.e., the skeleton, muscle-tendon complexes, and spinal reflex circuitry) is required. The purpose of the present study was to determine to what extent such conclusions depend on the level of simplification with which the dynamical properties of the periphery are modeled. For this purpose, we simulated fast goal-directed single-joint movement with four existing types of models. We tested how three types of perturbations affected movement trajectory if motor commands remained unchanged. We found that the four types of models of the periphery showed different robustness to the perturbations, leading to different predictions on how accurate motor commands need to be, i.e., how accurate the knowledge of external conditions needs to be. This means that when interpreting kinematic responses obtained in perturbation experiments the level of error correction attributed to adaptation of motor commands depends on the type of model used to describe the periphery.

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“…In our study, we considered the first and second levels, in that we addressed 3-dimensional goal-directed reaching movements, characterized by a single target position. By leaving out the question of how such high-level control is then translated into muscle synergies and the control of posture and muscle tone, we follow the observation that: electrical stimulation of the brain motor area elicits reaching movements in primates (Graziano et al 2002(Graziano et al , 2005 and leg movements in frogs (Bizzi et al 1982). Interestingly, all of these movements converge to the same position in extrinsic space independently from the initial posture.…”

Section: Assumptions Of the Modelmentioning

confidence: 93%

Movement curvature planning through force field internal models

Petreska

Billard

2009

Biol Cybern

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Human motion studies have focused primarily on modeling straight point-to-point reaching movements. However, many goal-directed reaching movements, such as movements directed towards oneself, are not straight but rather follow highly curved trajectories. These movements are particularly interesting to study since they are essential in our everyday life, appear early in development and are routinely used to assess movement deficits following brain lesions. We argue that curved and straight-line reaching movements are generated by a unique neural controller and that the observed curvature of the movement is the result of an active control strategy that follows the geometry of one's body, for instance to avoid trajectories that would hit the body or yield postures close to the joint limits. We present a mathematical model that accounts for such an active control strategy and show that the model reproduces with high accuracy the kinematic features of human data during unconstrained reaching movements directed toward the head. The model consists of a nonlinear dynamical system with a single stable attractor at the target. Embodiment-related task constraints are expressed as a force field that acts on the dynamical system. Finally, we discuss the biological plausibility and neural correlates of the model's parameters and suggest that embodiment should be considered as a main cause for movement trajectory curvature.

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Arm trajectory formation in monkeys

Cited by 313 publications

References 15 publications

Effects of Altering Initial Position on Movement Direction and Extent

Effects of Altering Initial Position on Movement Direction and Extent

Conclusions on motor control depend on the type of model used to represent the periphery

Movement curvature planning through force field internal models

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