The motor system does not learn the dynamics of the arm by rote memorization of past experience.

By M. Conditt, F. Gandolfo, Ferdinando A. Mussa-Ivaldi. 1997

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Citations in the corpus

Quantifying Generalization from Trial-by-Trial Behavior of Adaptive Systems that Learn with Basis Functions: Theory and Experiments in Human Motor Control (2003, background): “, 1999), at other arm configurations (Shadmehr and Moussavi, 2000), with different trajectories (Conditt et al., 1997; Goodbody and Wolpert, 1998), and even movements of the other arm (Criscimagna-Hemminger, et al.”
Persistence of motor adaptation during constrained, multi-joint, arm movements. (2000, methodology): “…studies have shown that human arm movements do indeed exhibit adaptive behavior when subjects are presented with predictable, perturbing, mechanical environments (Conditt et al. 1997; Dizio and Lackner 1995; Lackner and Dizio 1994; Shadmehr and Brashers-Krug 1997; Shadmehr and Mussa-Ivaldi 1994).”
Motor Adaptation as a Process of Reoptimization (2008, unknown): “In our view, such an approach would be inconsistent with the large body of data from experiments in generalization (Conditt et al., 1997).”
Neural primitives for motion control (2004, background): “3) Adaptation is achieved by the central nervous system through the formation of a local map that associates the states (positions and velocities) visited during the training period with the corresponding forces [82], [83].”
Computational principles of movement neuroscience (2000, background): “, learning depends on the states experienced but not on their temporal orde”
Robotics, motor learning, and neurologic recovery. (2004, background): “However, the internal model formed during straight-line reaching movements generalized well to circular drawing movements (11).”
Learning of action through adaptive combination of motor primitives (2000, background): “The learning of dynamics, however, affects movements outside the region of trainin”
Perspectives and problems in motor learning. (2001, background): “…it has been shown that: (1) learning of dynamics generalizes in joint-based coordinates 40 ; (2) learning depends on the states experienced but not on the order in which they are experienced 42 ; and (3) state-dependent fields are learned more efficiently than temporally changing fields 43 .”