Title :
Nonlinear prediction on squid axon response
Author :
Ikeguchi, T. ; Aihara, K.
Author_Institution :
Dept. of Appl. Electron., Sci. Univ. of Tokyo, Japan
Abstract :
Membrane response of squid giant axon stimulated by sinusoidal force is analyzed by deterministic nonlinear prediction in order to evaluate short-term predictability and long-term unpredictability, which are important properties peculiar to deterministic chaos. As a result, it is shown that correlation coefficients decrease with increase of prediction steps, which is due to sensitive dependence on initial conditions. In order to obtain more reliable results, the method of surrogate data is also applied to the time series data of squid axon response and statistical significances are calculated. The result shows a strong evidence that the squid giant axon response cannot be explained without nonlinear dynamics and implies that the approach with deterministic nonlinear prediction has potential ability for identification of deterministic chaos in a real world data, even though it is almost impossible to obtain information on deterministic models explicitly
Keywords :
biomembrane transport; chaos; neurophysiology; nonlinear dynamical systems; physiological models; prediction theory; time series; correlation coefficients; deterministic chaos; deterministic nonlinear prediction; long-term unpredictability; membrane response; nonlinear dynamics; nonlinear prediction; short-term predictability; sinusoidal force; squid axon response; squid giant axon; statistical significances; surrogate data; time series data; Bifurcation; Biomembranes; Chaos; Ear; Electronics industry; Equations; Industrial electronics; Nerve fibers; Physics; SQUIDs;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.487285