Reconstruction and Characterisation of Neuronal Dynamics: How Attractive is 
Chaos?

Preißl, H; Aertsen, A

doi:10.1007/978-3-642-49967-8_19

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Reconstruction and Characterisation of Neuronal Dynamics: How Attractive is Chaos?

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Preißl, H
Former Department Structure and Function of Natural Nerve-Net , Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Aertsen, A
Former Department Structure and Function of Natural Nerve-Net , Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Preißl, H., & Aertsen, A. (1992). Reconstruction and Characterisation of Neuronal Dynamics: How Attractive is Chaos? In A. Aertsen, & V. Braitenberg (Eds.), Information Processing in the Cortex: Experiments and Theory (pp. 285-297). Berlin, Germany: Springer.

Cite as: https://hdl.handle.net/21.11116/0000-0005-0C66-C

Abstract

During the last years there has been a great emphasis on the possibility of characterising neuronal dynamics with methods from non-linear dynamical system theory. These new methods, especially the determination of the correlation dimension of time series, were applied to continuous activity as measured by the EEG and also to pulse train activity of single neurons. We could show that the calculation of the correlation dimension leads to incompatible results for a continuous process and for a pulse train generated from that process. This result has implications not only for neuronal data but also for other fields in biology and physics, where one deals with these two types of data.