Volume 10 Supplement 1

Eighteenth Annual Computational Neuroscience Meeting: CNS*2009

Open Access

Critical adaptive control may cause scaling laws in human behavior

BMC Neuroscience200910(Suppl 1):P17

DOI: 10.1186/1471-2202-10-S1-P17

Published: 13 July 2009

When humans perform closed-loop control tasks like in upright standing or while balancing a stick, their behavior exhibits non-Gaussian fluctuations with long-tailed distributions [1, 2]. The origin of these fluctuations is not known, but their statistics suggests a fine-tuning of the underlying system to a critical point [3]. We investigated whether self-tuning may be caused by the annihilation of local predictive information due to success of control [4]. We found that this mechanism can lead to critical noise amplification, a fundamental principle that produces complex dynamics even in very low-dimensional state estimation tasks. It generally emerges when an unstable dynamical system becomes stabilized by an adaptive controller that has a finite memory [5]. It is also compatible with control based on optimal recursive Bayesian estimation of a varying hidden parameter. Starting from this theory, we developed a realistic model of adaptive closed-loop control by including constraints on memory and delays. To test this model, we performed psychophysical experiments where humans balanced an unstable target on a computer screen. It turned out, that the model reproduces the long tails of the distributions together with other characteristics of the human control dynamics. Fine-tuning the model to match the experimental dynamics identifies parameters characterizing a subjects control system which can be independently tested. Our results suggest that the nervous system involved in closed-loop motor control nearly optimally estimates system parameters on-line from very short epochs of past observations.

Authors’ Affiliations

(1)
Institute for Theoretical Physics, University of Bremen

References

  1. Bormann R, Cabrera JL, Milton JG, Eurich CW: Visuomotor tracking on a computer screen – an experimental paradigm to study the dynamics of motor control. Neurocomputing. 2004, 58–60: 517-523. 10.1016/j.neucom.2004.01.089.View ArticleGoogle Scholar
  2. Cabrera JL, Milton JG: On-off intermittency in a human balancing task. Phys Rev Lett. 2002, 89: 158702-158705. 10.1103/PhysRevLett.89.158702.PubMedView ArticleGoogle Scholar
  3. Sornette D: Critical phenomena in natural sciences: chaos, fractals, self-organisation and disorder: concepts and tools. 2004, Berlin Heidelberg New York: Springer-Verlag, 2Google Scholar
  4. Eurich C, Pawelzik K: Optimal control yields power law behavior. Edited by: Duch W, et al. 2005, ICANN LNCS, 3697: 365-370.Google Scholar
  5. Patzelt F, Riegel M, Ernst U, Pawelzik KR: Self-organized critical noise amplification in human closed loop control. Front Comput Neurosci. 2007, 1: 4-10.3389/neuro.10.004.2007. Epub 2007 Nov 2.PubMed CentralPubMedView ArticleGoogle Scholar

Copyright

© Patzelt and Pawelzik; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd.

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