Intentional and unintentional multi-joint movements: Their nature and structure of variance

T. Zhou, L. Zhang, M. L. Latash

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

We tested predictions of a hierarchical scheme on the control of natural movements with referent body configurations. Subjects occupied an initial hand position against a bias force generated by a HapticMaster robot. A smooth force perturbation was applied to the hand consisting of an increase in the bias force, keeping it at a new level for 5. s, and decreasing it back to the bias value. When the force returned to the bias value, the arm stopped at a position different from the initial one interpreted as an involuntary movement. We then asked subjects to make voluntary movements to targets corresponding to the measured end-position of the unintentional movements. No target for hand orientation was used. The joint configuration variance was compared between intentional and unintentional movements within the framework of the uncontrolled manifold hypothesis. Our central hypothesis was that both unintentional and intentional movements would be characterized by structure of joint configuration variance reflecting task-specific stability of salient performance variables, such as hand position and orientation. The analysis confirmed that most variance at the final steady states was compatible with unchanged values of both hand position and orientation following both intentional and unintentional movements. We interpret unintentional movements as consequences of back-coupling between the actual and referent configurations at the task level. The results suggested that both intentional and unintentional movements resulted from shifts of the body referent configuration produced intentionally or as a result of the hypothesized back-coupling. Inter-trial variance signature reflects similar task-specific stability properties of the system following both types of movements, intentional and unintentional.

Original languageEnglish (US)
Pages (from-to)181-193
Number of pages13
JournalNeuroscience
Volume289
DOIs
Publication statusPublished - Mar 9 2015

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All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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