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Cited by 1,330

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An organizing principle for a class of voluntary movements

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Hogan, N·1984·The Journal of Neuroscience

Abstract

This paper presents a mathematical model which predicts both the major qualitative features and, within experimental error, the quantitative details of a class of perturbed and unperturbed large-amplitude, voluntary movements performed at intermediate speed by primates. A feature of the mathematical model is that a concise description of the behavioral organization of the movement has been formulated which is separate and distinct from the description of the dynamics of movement execution. Based on observations of voluntary movements in primates, the organization has been described as though the goal were to make the smoothest movement possible under the circumstances, i.e., to minimize the accelerative transients. This has been formalized by using dynamic optimization theory to determine the movement which minimizes the rate of change of acceleration (jerk) of the limb. Based on observations of muscle mechanics, the concept of a “virtual position” determined by the active states of the muscles is rigorously defined as one of the mechanical consequences of the neural commands to the muscles. This provides insight into the mechanics of perturbed and unperturbed movements and is a useful aid in the separation of the descriptions of movement organization and movement execution.

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Crossref · 10.1523/jneurosci.04-11-02745.1984

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Metadata

Authors
Hogan, N.
Venue
The Journal of Neuroscience
Published
1984-11-01
Volume
4
Issue
11
Pages
2745-2754
ISSN
  • 0270-6474 (ISSN-L)
  • 1529-2401
OpenAlex
W1892385946
Cited by
1,330
References
0
FWCI
12.45
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: An organizing principle for a class of voluntary movements. https://app.cochat.ai/papers/10.1523/jneurosci.04-11-02745.1984
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Hogan, N. (1984). An organizing principle for a class of voluntary movements. The Journal of Neuroscience. https://doi.org/10.1523/jneurosci.04-11-02745.1984

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.