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Adaptive Model Theory: Modelling the Modeller

  • Peter D. NeilsonEmail author
  • Megan D. Neilson
Chapter
Part of the Simulation Foundations, Methods and Applications book series (SFMA)

Abstract

Adaptive Model Theory is a computational theory of the brain processes that control purposive coordinated human movement. It sets out a feedforward-feedback optimal control system that employs both forward and inverse adaptive models of (i) muscles and their reflex systems, (ii) biomechanical loads on muscles, and (iii) the external world with which the body interacts. From a computational perspective, formation of these adaptive models presents a major challenge. All three systems are high dimensional, multiple input, multiple output, redundant, time-varying, nonlinear and dynamic. The use of Volterra or Wiener kernel modelling is prohibited because the resulting huge number of parameters is not feasible in a neural implementation. Nevertheless, it is well demonstrated behaviourally that the nervous system does form adaptive models of these systems that are memorized, selected and switched according to task. Adaptive Model Theory describes biologically realistic processes using neural adaptive filters that provide solutions to the above modelling challenges. In so doing we seek to model the supreme modeller that is the human brain.

Keywords

Adaptive nonlinear models Neural adaptive filters Feature extraction Movement synergies Riemannian geometry 

References

  1. 1.
    Neilson PD, Neilson MD, O’Dwyer NJ (1985) Acquisition of motor skills in tracking tasks: learning internal models. In: Russell DG, Abernethy B (eds) Motor memory and control: the otago symposium, Dunedin, New Zealand, 1982. Human Performance Associates, Dunedin, NZ, pp 25–36Google Scholar
  2. 2.
    Neilson PD, Neilson MD, O’Dwyer NJ (1988) Internal models and intermittency: a theoretical account of human tracking behavior. Biol Cybern 58:101–112CrossRefGoogle Scholar
  3. 3.
    Neilson PD, Neilson MD, O’Dwyer NJ (1992) Adaptive model theory: application to disorders of motor control. In: Summers JJ (ed) Approaches to the study of motor control and learning. North Holland, Amsterdam, pp 495–548CrossRefGoogle Scholar
  4. 4.
    Neilson PD (1993) The problem of redundancy in movement control: the adaptive model theory approach. Psychol Res 55:99–106CrossRefGoogle Scholar
  5. 5.
    Neilson PD, Neilson MD, O’Dwyer NJ (1997) Adaptive model theory: central processing in acquisition of skill. In: Connolly K, Forssberg H (eds) Neurophysiology and neuropsychology of motor development. Mac Keith Press, London, pp 346–370Google Scholar
  6. 6.
    Neilson PD, Neilson MD (2005) An overview of adaptive model theory: solving the problems of redundancy, resources, and nonlinear interactions in human movement control. J Neural Eng 2:S279–S312CrossRefGoogle Scholar
  7. 7.
    Bye RT, Neilson PD (2008) The BUMP model of response planning: variable horizon predictive control accounts for the speed–accuracy tradeoffs and velocity profiles of aimed movement. Hum Mov Sci 27:771–798CrossRefGoogle Scholar
  8. 8.
    Neilson PD, Neilson MD (2010) On theory of motor synergies. Hum Mov Sci 29:655–683CrossRefGoogle Scholar
  9. 9.
    Neilson PD, Neilson MD, Bye RT (2015) A Riemannian geometry theory of human movement: the geodesic synergy hypothesis. Hum Mov Sci 44:42–72CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of Electrical Engineering & TelecommunicationsUniversity of New South WalesSydneyAustralia

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