30 March 1995 Chaos in the brain: imaging via chaoticity of EEG/MEG signals
Author Affiliations +
Brain electro- (EEG) or magnetoencephalogram (MEG) can be analyzed by using methods of the nonlinear system theory. We show that even for very short and nonstationary time series it is possible to functionally differentiate various brain activities. Usually the analysis assumes that the analyzed signals are both long and stationary, so that the classic spectral methods can be used. Even more convincing results can be obtained under these circumstances when the dimensional analysis or estimation of the Kolmogorov entropy or the Lyapunov exponent are performed. When measuring the spontaneous activity of a human brain the assumption of stationarity is questionable and `static' methods (correlation dimension, entropy, etc.) are then not adequate. In this case `dynamic' methods like pointwise-D2 dimension or chaoticity measures should be applied. Predictability measures in the form of local Lyapunov exponents are capable of revealing directly the chaoticity of a given process, and can practically be applied for functional differentiation of brain activity. We exemplify these in cases of apallic syndrome, tinnitus and schizophrenia. We show that: the average chaoticity in apallic syndrome differentiates brain states both in space and time, chaoticity changes temporally in case of schizophrenia (critical jumps of chaoticity), chaoticity changes locally in space, i.e., in the cortex plane in case of tinnitus.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zbigniew J. Kowalik, Zbigniew J. Kowalik, Thomas Elbert, Thomas Elbert, Brigitte Rockstroh, Brigitte Rockstroh, Manfried Hoke, Manfried Hoke, } "Chaos in the brain: imaging via chaoticity of EEG/MEG signals", Proc. SPIE 2390, Optical Biophysics, (30 March 1995); doi: 10.1117/12.205992; https://doi.org/10.1117/12.205992


A methodology for dynamic functional connectivity
Proceedings of SPIE (March 09 2011)
Nonlinear aspects of the EEG during sleep in children
Proceedings of SPIE (May 23 2005)
Joint time frequency analysis of EEG signals based on a...
Proceedings of SPIE (October 15 2012)
Application of the fractal and chaos theory in the fault...
Proceedings of SPIE (November 14 2007)
Detection of broad-band communications signals
Proceedings of SPIE (November 18 1993)

Back to Top