Changes of Chaoticness in Spontaneous EEG/MEG

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KOWALIK, Zbigniew J., Thomas ELBERT, 1994. Changes of Chaoticness in Spontaneous EEG/MEG. In: Integrative Psychological and Behavioral Science. 29(3), pp. 270-282. Available under: doi: 10.1007/BF02691331

@article{Kowalik1994Chang-10076, title={Changes of Chaoticness in Spontaneous EEG/MEG}, year={1994}, doi={10.1007/BF02691331}, number={3}, volume={29}, journal={Integrative Psychological and Behavioral Science}, pages={270--282}, author={Kowalik, Zbigniew J. and Elbert, Thomas} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dc:creator>Elbert, Thomas</dc:creator> <dc:format>application/pdf</dc:format> <dcterms:rights rdf:resource=""/> <dspace:hasBitstream rdf:resource=""/> <dcterms:bibliographicCitation>First publ. in: Integrative Psychological and Behavioral Science 29 (1994), 3, pp. 270-282</dcterms:bibliographicCitation> <dc:contributor>Kowalik, Zbigniew J.</dc:contributor> <dc:date rdf:datatype="">2011-03-25T09:13:55Z</dc:date> <dc:language>eng</dc:language> <dc:contributor>Elbert, Thomas</dc:contributor> <dcterms:issued>1994</dcterms:issued> <dcterms:available rdf:datatype="">2011-03-25T09:13:55Z</dcterms:available> <dcterms:title>Changes of Chaoticness in Spontaneous EEG/MEG</dcterms:title> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:abstract xml:lang="eng">Depending on the task being investigated in EEG/MEG experiments, the corresponding signal is more or less ordered. The question still open is how can one detect the changes of this order while the tasks performed by the brain vary continuously. By applying a static measurement of the fractal dimension or Lyapunov exponent, different brain states could be characterized. However, transitions between different states may not be detected, especially if the moments of transitions are not strictly defined. Here we show how the dynamical measure based on the largest local Lyapunov exponent can be applied for the detection of the changes of the chaoticity of the brain processes measured in EEG and MEG experiments. In this article, we demonstrate an algorithm for computation of chaoticity that is especially useful for nonstationary signals. Moreover, we introduce the idea that chaoticity is able to detect, locally in time, critical jumps (phase-transition-like phenomena) in the human brain, as well as the information flow through the cortex.</dcterms:abstract> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Kowalik, Zbigniew J.</dc:creator> <bibo:uri rdf:resource=""/> <dcterms:hasPart rdf:resource=""/> <dcterms:isPartOf rdf:resource=""/> <dc:rights>Attribution-NonCommercial-NoDerivs 2.0 Generic</dc:rights> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> </rdf:Description> </rdf:RDF>

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