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Digital Library of the
European Council for Modelling and Simulation |
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Title: |
Adaptive Model Theory: Modelling the Modeller |
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Authors: |
Peter D.
Neilson, Megan D. Neilson |
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Published in:
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(2013).ECMS 2013 Proceedings edited
by: W. Rekdalsbakken, R. T. Bye, H. Zhang European Council for Modeling
and Simulation. doi:10.7148/2013 ISBN:
978-0-9564944-6-7 27th
European Conference on Modelling and Simulation, Aalesund, Norway, May 27th –
30th, 2013 |
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Citation
format: |
Peter D. Neilson, Megan D.
Neilson (2013). Adaptive Model Theory: Modelling
the Modeller, ECMS
2013 Proceedings edited by: W. Rekdalsbakken, R. T. Bye, H. Zhang, European Council for Modeling
and Simulation. doi:10.7148/2013-0012 |
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DOI: |
http://dx.doi.org/10.7148/2013-0012 |
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Abstract: |
The
human brain is an analogical modelling device. It
forms adaptive models of the environment and of the body in interaction with
the environment and it uses these models in the planning and control of
purposive movement. The movement system includes the entire musculoskeletal
system in interaction with the environment. There are some 700 functional muscles
(groups of muscle fibres with the same mechanical
action that are controlled independently by the nervous system) controlling
about 110 elemental movements. From the perspective of the brain, the system
to be controlled consists of three multiple input–multiple output nonlinear
dynamical systems connected in cascade (i) muscle
control systems (muscles and their reflex systems), (ii) biomechanical system
(biomechanical loads on muscles), and (iii) external systems (external
world). Sensory systems continuously monitor the input and output signals of
all three of these subsystems and form adaptive models of the nonlinear
dynamical relations within and between the various sensory modalities
involved. The brain compares model predictions with actual sensory signals (afference) and takes discrepancies very seriously.
Discrepancies lead to an increase in brain activity as the brain analyses
errors and attempts to update its models. It also defends against
perturbations by slowing movements and stiffening. |
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