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.
|Number of pages||6|
|Publication status||Published - 1 Dec 1995|
|Event||Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust|
Duration: 27 Nov 1995 → 1 Dec 1995
|Conference||Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)|
|Period||27/11/95 → 1/12/95|