Modeling Human Motor Systems in Nonlinear Dynamics: Intentionality and Discrete Movement Behaviors
- Cite this article as:
- Davids, K., Button, C. & Bennett, S. Nonlinear Dynamics Psychol Life Sci (1999) 3: 3. doi:10.1023/A:1022429522099
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Attempts to understand human movement systems from the perspective of nonlinear dynamics have increased in recent years, although research has almost exclusively focused on modeling rhythmical movements as limit cycle oscillators. Only a limited amount of work has been undertaken on discrete movements, generally only in the form of numerical simulations and mathematical models. In this paper we briefly overview the key findings from previous research on movement systems as nonlinear dynamical systems, and report data from a behavioral experiment on the coordination observed in a prehension movement under both discrete and rhythmical conditions. In a rhythmical condition subjects grasped dowels in time to a metronomic beat, whereas in a discrete condition a target dowel was grasped within a predetermined movement time. A ‘scanning procedure’ was implemented to monitor changes in the time of relative final hand closure during hand transport to the dowel. For each condition, a pre-test and post-test of 10 trials were also conducted either side of the scanning trial block. No effects between condition or trial block were noted and there was a large amount of within-subject variability in the coordination data. The findings support previous theoretical modeling suggesting that subject intentionality acts as a more powerful constraint on the intrinsic dynamics of the movement system in discrete compared to rhythmical conditions. The high levels of individual variability were interpreted as being due to the competition between specific and non-specific control parameters (e.g., the subject's intentionality and the metronomic beat). It is concluded that discrete prehension movements appear amenable to a nonlinear dynamical analysis. The data also point to the innovative use of within-subject analyses in future work modeling motor systems as nonlinear dynamical systems.