DocumentCode :
2493716
Title :
Chaotic behavior in probabilistic cellular neural networks
Author :
Kozma, Robert ; Puljic, Marko
Author_Institution :
Dept. of Math. Sci., Univ. of Memphis, Memphis, TN, USA
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
7
Abstract :
Experiments conducted in brains by electroencephalographic and magnetoencephalographic techniques reveal widespread coherent oscillations. The oscillations over multiple frequency bands overlap and result in signals with broad spectra. Previous studies showed that various frequencies can be modeled by probabilistic cellular automata with coupled inhibitory and excitatory interactions. In this work we show that coupled oscillator layers can create broad-spectrum chaotic oscillations with power spectral densities over long times segments converging to Brown noise features. Models of cortical neurodynamics provide an interpretation of the observed phenomena.
Keywords :
biology; cellular automata; chaos; electroencephalography; magnetoencephalography; neural nets; Brown noise features; brains; broad-spectrum chaotic oscillations; chaotic behavior; cortical neurodynamics; coupled oscillator layers; electroencephalographic techniques; magnetoencephalographic techniques; probabilistic cellular automata; probabilistic cellular neural networks; Brain models; Couplings; Neurons; Oscillators; Principal component analysis; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
ISSN :
1098-7576
Print_ISBN :
978-1-4244-6916-1
Type :
conf
DOI :
10.1109/IJCNN.2010.5596718
Filename :
5596718
Link To Document :
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