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Dynamic transitions among multiple oscillators of synchronized bursts in cultured neural networks

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dc.contributor.authorKim, June Hoan-
dc.contributor.authorHeo, Ryoun-
dc.contributor.authorChoi, Joon Ho-
dc.contributor.authorLee, Kyong J.-
dc.date.accessioned2021-09-05T10:06:45Z-
dc.date.available2021-09-05T10:06:45Z-
dc.date.created2021-06-15-
dc.date.issued2014-04-
dc.identifier.issn1742-5468-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/98865-
dc.description.abstractSynchronized neural bursts are a salient dynamic feature of biological neural networks, having important roles in brain functions. This report investigates the deterministic nature behind seemingly random temporal sequences of inter-burst intervals generated by cultured networks of cortical cells. We found that the complex sequences were an intricate patchwork of several noisy 'burst oscillators', whose periods covered a wide dynamic range, from a few tens of milliseconds to tens of seconds. The transition from one type of oscillator to another favored a particular passage, while the dwelling time between two neighboring transitions followed an exponential distribution showing no memory. With different amounts of bicuculline or picrotoxin application, we could also terminate the oscillators, generate new ones or tune their periods.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherIOP PUBLISHING LTD-
dc.subjectRAT-
dc.subjectPATTERNS-
dc.subjectCORTEX-
dc.subjectHZ-
dc.titleDynamic transitions among multiple oscillators of synchronized bursts in cultured neural networks-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Kyong J.-
dc.identifier.doi10.1088/1742-5468/2014/04/P04019-
dc.identifier.scopusid2-s2.0-84899621339-
dc.identifier.wosid000336140700019-
dc.identifier.bibliographicCitationJOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT-
dc.relation.isPartOfJOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT-
dc.citation.titleJOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMechanics-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryMechanics-
dc.relation.journalWebOfScienceCategoryPhysics, Mathematical-
dc.subject.keywordPlusRAT-
dc.subject.keywordPlusPATTERNS-
dc.subject.keywordPlusCORTEX-
dc.subject.keywordPlusHZ-
dc.subject.keywordAuthordynamics (experiment)-
dc.subject.keywordAuthorneuronal networks (experiment)-
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