TY - JOUR
T1 - Intermediate motor learning as decreasing active (dynamical) degrees of freedom
AU - Mitra, Suvobrata
AU - Amazeen, Polemnia G.
AU - Turvey, M. T.
N1 - Funding Information:
This researchw as supportedb y National ScienceF oundation Grant SBR 94-22650a wardedt o M.T. Turvey and a Universityo f ConnecticutD isserta-tion Fellowship awardedt o P.G. Amazeen.T he authorst hank Henry Abar-banel,E lliot Saltzman,R ichard Schmidt,B ruce Kay, Michael Riley, David Collins, RameshB alasubramaniama,n d Claudia Carello.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 1998/1
Y1 - 1998/1
N2 - A classical view is that motor learning has distinguishable early, intermediate, and late phases. A recent view is that motor learning is the acquisition of an abstract equation of motion that specifies the time evolution of a pattern of coordination. The pattern is expressed by a collective variable that enslaves or orders component subsystems that, in turn, act on and generate the collective variable. In these latter terms, early learning resolves the collective variable and its motion equation, intermediate learning stabilizes and standardizes the subsystems or active degrees of freedom (DFs) producing the collective variable's dynamics. The preceding ideas, and the phase-space reconstruction methods required to determine active DFs, are developed in tutorial fashion in the context of an experimental investigation of learning a bimanual rhythmic coordination. Results show that intermediate learning reduces the dimensionality of the learned coordination's dynamics and renders those dynamics more deterministic. The tutorial development relates the preceding concepts, results and methods of analyses to (a) the contrast between Poincaréan and Newtonian dynamics, (b) contemporary interpretations of random processes, (c) definitions of DFs in respect to Bernstein's problem, (d) the potential contribution of chaos to the adaptability of a learned coordination, and (e) possible links between active (dynamical) DFs and the control variables r, c, and μ identified by the λ hypothesis.
AB - A classical view is that motor learning has distinguishable early, intermediate, and late phases. A recent view is that motor learning is the acquisition of an abstract equation of motion that specifies the time evolution of a pattern of coordination. The pattern is expressed by a collective variable that enslaves or orders component subsystems that, in turn, act on and generate the collective variable. In these latter terms, early learning resolves the collective variable and its motion equation, intermediate learning stabilizes and standardizes the subsystems or active degrees of freedom (DFs) producing the collective variable's dynamics. The preceding ideas, and the phase-space reconstruction methods required to determine active DFs, are developed in tutorial fashion in the context of an experimental investigation of learning a bimanual rhythmic coordination. Results show that intermediate learning reduces the dimensionality of the learned coordination's dynamics and renders those dynamics more deterministic. The tutorial development relates the preceding concepts, results and methods of analyses to (a) the contrast between Poincaréan and Newtonian dynamics, (b) contemporary interpretations of random processes, (c) definitions of DFs in respect to Bernstein's problem, (d) the potential contribution of chaos to the adaptability of a learned coordination, and (e) possible links between active (dynamical) DFs and the control variables r, c, and μ identified by the λ hypothesis.
KW - Chaos
KW - Coordination dynamics
KW - Coordinative structures
KW - Degrees of freedom problem
KW - Dynamical systems
KW - Equilibrium point hypothesis
KW - Learning
KW - Phase-space reconstruction
KW - Skill acquisition
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U2 - 10.1016/S0167-9457(97)00023-7
DO - 10.1016/S0167-9457(97)00023-7
M3 - Article
AN - SCOPUS:0031610071
SN - 0167-9457
VL - 17
SP - 17
EP - 65
JO - Human Movement Science
JF - Human Movement Science
IS - 1
ER -