Thermodynamic study of motor behaviour optimization

Abstract

Our work is aimed at studying the optimization of a complex motor behaviour from a global perspective. First, ‘free climbing’ as a sport will be briefly introduced while emphasizing in particular its psychomotor aspect called ‘route finding’. The basic question raised here is how does the optimization of a sensorimotoricity-environment system take place. The material under study is the free climber's trajectory, viewed as the ‘signature’ of climbing behaviour (i.e., the spatial dimension). The concepts of learning, optimization, constraint, and degrees of freedom of a system will be discussed using the synergistic approach to the study of movement (Bernstein, 1967; Kelso, 1977). Measures of a trajectory's length and convex hull can be used to define an index whose equation resembles that of an entropy. This index is a measure of the trajectory's overall complexity. Some important concepts related to the thermodynamics of curves will also be discussed. The optimization process will be studied by examining the changes in entropy over time for a set of trajectories generated during the learning of a route (ten successive repetitions of the same climb). It will be shown that the entropy of the trajectories decreases as learning progresses, that each level of expertise has its own characteristic entropy curve, and that for the subjects tested, the mean entropy of skilled climbers is lower than that of average climbers. Basing our analysis on the concepts of degrees of freedom and constraint equations, an attempt is made to relate trajectory entropy to system entropy. Based on the postulate that trajectory entropy is equal to the difference in entropy between the unconstrained and constrained system, a model of motor optimization is proposed. This model is illustrated by an entropy graph reflecting a dynamic release process. In the light of our results, two opposing views will be examined: movement construction vs. movement emergence.

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References

  1. Bernstein, N. (1967). The Coordination and Regulation of Movements. Oxford, Pergamon Press.

    Google Scholar 

  2. Cordier, P. and P. Bolon (1992). Etude thermodynamique de la trajectoire du grimpeur. Communication au Congrès ‘Sport et Montagne’. Grenoble, Fevrier.

    Google Scholar 

  3. Haken, H. (1977). Synergetics: An Introduction. Heidelberg, Springer Verlag.

    Google Scholar 

  4. Keele, S.W. and J.J. Summers (1976). The structure of motor programs. In: G.E. Stelmach, ed., Motor Control: Issues and Trends, pp. 109–142. New York, Academic Press.

    Google Scholar 

  5. Kelso, J.A.S. (1977). Motor control mechanisms underlying human movement production. Journal of Experimental Psychology: Human Perception and Performance 3: 529–543.

    Google Scholar 

  6. Kelso, J.A.S., K.G. Holt, P.N. Kugler and M.T. Turvey (1980). On the concept of coordinative structures as dissipative structures: II. Empirical lines of convergency. In: G.E. Stelmach & J. Requin, eds., Tutorials in Motor Behavior, pp. 49–70. Amsterdam, North-Holland.

    Google Scholar 

  7. Kugler, P.N., J.A.S. Kelso and M.T. Turvey (1980). On the concept of coordinative structures as dissipative structures: I. Theoretical line. In: G.E. Stelmach & J. Requin, eds., Tutorials in Motor Behavior, pp. 3–37. Amsterdam, North-Holland.

    Google Scholar 

  8. Marteniuk, R.G. and S.K.E. Romanow (1983). Human movement organization and learning as revealed by variability in movement, use of kinematic information, and Fourier analysis. In: R.A. Magill, ed., Memory and Control of Action, pp. 167–198. New York, North-Holland.

    Google Scholar 

  9. Mendès France, M. (1981). Chaotic curves. In Rhythms in biology and other fields of applications. Proc. Journ. Soc. Math. France, Luminy.

  10. Mendès France M. (1983). Lecture notes in biomathematics 49, pp. 352–357. Berlin-Heidelberg-New York, Springer-Verlag.

    Google Scholar 

  11. Mendès France, M. (1991). The Planck constant of a curve. In: J. Blair & S. Dubuc, Eds., Franctal Geometry and Analysis, pp. 325–366. Netherlands, Kluwer Academic Publishers.

    Google Scholar 

  12. Pattee, H.H. (1977). Dynamic and linguistic modes of complex systems. International Journal of General Systems 3: 259–266.

    Google Scholar 

  13. Santalo, L.A. (1976). Integral Geometry and Geometric Probability. Addison, Wesley.

  14. Schöner, G. and J.A.S. Kelso (1988). A dynamic pattern theory of behavioral change. Journal of Theoretical Biology 135: 501–524.

    Google Scholar 

  15. Thom, R. (1968). Stabilité structurelle et morphogénèse.

  16. Turvey, M.T., H.L. Fitch and J.A.S. Kelso (1982). The Bernstein perspective: I. In: J.A.S. Kelso, ed., Human Motor Behavior: An Introduction, pp. Hillsdale, NJ, Lawrence Erlbaum Publishers.

    Google Scholar 

  17. Turvey, M.T., R. Shaw and W. Mace (1978). Issues in a theory of actions: Degrees of freedom, coordinative structures and coalitions. In: J. Requin, ed., Attention and Performance VII. Hillsdale, NJ, Lawrence Erlbaum Publishers.

    Google Scholar 

  18. Vereijken, B., R.E.A. van Emmerik, H.T.A. Whiting and K.M. Newell (1992). Free(z)ing Degrees of Freedom in Skill Acquisition. Journal of motor behavior 24, no. 1: 133–142.

    Google Scholar 

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Cordier, P., France, M.M., Bolon, P. et al. Thermodynamic study of motor behaviour optimization. Acta Biotheor 42, 187–201 (1994). https://doi.org/10.1007/BF00709490

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Keywords

  • Motor Behaviour
  • Route Finding
  • Complex Motor
  • Characteristic Entropy
  • Successive Repetition