Learning a bimanual rhythmic coordination: Schemas as dynamics

Generativity--the ability of an individual to produce a skill under novel circumstances--is a persistent problem in motor learning addressed traditionally in the context of motor schema theory (R. A. Schmidt, 1976). The acquisition of an effective motor schema requires practice condition variability and knowledge of results (KR; e.g., Heuer & R. A. Schmidt, 1988; Kernodle & Carlton, 1992). The hand-held pendulums paradigm of Kugler and Turvey (1987) was used in five experiments to study the acquisition of a bimanual rhythmic coordination with relative phasing of either $-\pi/2$ or $-\pi/4$. In Experiment 1, participants acquired $-\pi/2$ under limited practice conditions and without KR. Despite these limitations, they demonstrated generativity in Experiment 2. Evidence was found for the effector-independence of the motor schema. The suggestion was made that the content of the motor schema is a coordination dynamic, whose acquisition is reliant on neither practice condition variability nor KR. In Experiment 3, the acquisition of two different motor schemas (one each for $-\pi/2$ and $-\pi/4$) was found to be identical at the level of the coordination but nonidentical in terms of the degrees of freedom recruited to produce the movements of the individual hands. Dimensionality analysis--meaningful only in the context of the schema as dynamics--revealed that the pattern dynamic at the level of the hands for both $-\pi/2$ and $-\pi/4$ was a strange attractor (chaotic in nature), rather than the commonly assumed noisy limit cycle (Kay, 1988). Evidence was found in support of the power law of learning (Fitts, 1964). In Experiment 4, generativity was demonstrated for both $-\pi/2$ and $-\pi/4$, with the coordination dynamics of $-\pi/4$ displaced uniformly in the direction of $-\pi/2$. In Experiment 5, acquisition of $-\pi/2$ and $-\pi/4$ was found to have caused an overall deformation in the attractor landscape of intrinsically stable patterns of in-phase and anti-phase. Together with the evidence that learning is of a coordination dynamic and that learning influences a coordination dynamic, evidence of chaos at subsystem levels indicates that generativity in learning comes from the chaotic nature of the coordination dynamic.

Coupling of breathing and movement during manual wheelchair propulsion

The hypothesis of this study was that stable coordination patterns may be found both within and between physiological subsystems. Many studies have been conducted on both monofrequency and multifrequency coordination, with a focus on both the frequency and phase relations among the limbs. In the present study, locomotor-respiratory coupling was observed in the maintenance of small-integer frequency ratios (2:1, 3:1, and 4:1) and in the consistent placement of the inspiratory phase just after the onset of the movement cycle during wheelchair propulsion. Level of experience and various motor and respiratory parameters were manipulated. Coupling was observed across levels of experience. Increases in movement frequency were accompanied by a shift to larger-integer ratios, suggesting that a single modeling strategy (e.g., the Farey tree; D. L. González & O. Piro, 1985) may be used for coordination both within the motor subsystem and between it and other physiological subsystems

Coupling of breathing and movement during manual wheelchair propulsion.

The hypothesis of this study was that stable coordination patterns may be found both within and between physiological subsystems. Many studies have been conducted on both monofrequency and multifre-quency coordination, with a focus on both the frequency and phase relations among the limbs. In the present study, locomotor-respiratory coupling was observed in the maintenance of small-integer fre-quency ratios (2:1, 3:1, and 4:1) and in the consistent placement of the inspiratory phase just after the onset of the movement cycle during wheelchair propulsion. Level of experience and various motor and respiratory parameters were manipulated. Coupling was observed across levels of experience. Increases in movement frequency were accompanied by a shift to larger-integer ratios, suggesting that a single modeling strategy (e.g., the Farey tree; D. L. Gonzalez & O. Piro, 1985) may be used for coordination both within the motor subsystem and between it and other physiological subsystems. Humans and animals alike demonstrate a discrete number of stable coordination patterns. Patterns of locomotion, called gaits, are limited in number and easily recognizable. For quadrupeds, the three most common gaits are the walk, trot, and gallop, although more complex subdivisions of gait are possible (for an overview

Dynamical analyses for developmental science:A primer for intrigued scientists

Dynamical systems theory is becoming more popular in social and developmental science. However, unfamiliarity with dynamical analysis techniques remains an obstacle for developmentalists who would like to quantitatively apply dynamics in their own research. The goal of this article is to address this issue by clearly and simply presenting several analytical techniques for the study of dynamics. We placed emphasis on the use of dynamical analysis techniques for the examination of social and developmental phenomena. We present descriptions of five techniques, which include examples of how they have been or can be used in developmental research, with reference to seminal and approachable resources when appropriate.</p