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Nature 436, 36-37 (7 July 2005) | doi:10.1038/436036b; Published online 6 July 2005
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Nonlinear dynamics: When instability makes sense
Abstract
Mathematical models that use instabilities to describe changes of weather patterns or spacecraft trajectories are well established. Could such principles apply to the sense of smell, and to other aspects of neural computation?
Dynamical stability is ubiquitous in many systems — and more often than not is desirable. Travelling down a straight road, a cyclist with stable dynamics will continue in more or less a straight line despite a gust of wind or a bumpy surface.
- Peter Ashwin is at the School of Engineering, Computer Science and Mathematics, University of Exeter, Exeter, Devon EX4 4QE, UK.
Email: P.Ashwin@ex.ac.uk - Marc Timme is at the Max Planck Institute for Dynamics and Self-Organization, and the Bernstein Center for Computational Neuroscience, Bunsenstra
e 10, 37073 Göttingen, Germany.
Email: timme@chaos.gwdg.de
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