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A theoretical framework based on the concepts and tools of nonlinear dynamical systems is advanced to account for both the persistent and transitory changes traditionally shown for the learning and development of motor skills. The multiple time scales of change in task outcome over time are interpreted as originating from the system's trajectory on an evolving attractor landscape. Different bifurcations between attractor organizations and transient phenomena can lead to exponential, power law, or S-shaped learning curves. This unified dynamical account of the functions and time scales in motor learning and development offers several new hypotheses for future research on the nature of change in learning theory.

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This study was designed to test the hypothesis derived from information theory that increases in the variability of motor responses result from increases in perceptual-motor noise. Young adults maintained isometric force for extended periods at different levels of their maximum voluntary contraction. Force variability (SD) increased exponentially as a function of force level. However, the signal-to-noise ratio (M/SD), an index of information transmission, as well as measures of noise in both the time (approximate entropy) and frequency (power spectrum) domains, changed according to an inverted U-shaped function over the range of force levels. These findings indicate that force variability is not directly related to noise but that force output noisiness is positively correlated with the amount of information transmitted.