{"title":"脑电的节段性结构比连续的可塑性结构更能揭示脑组织的动态多稳定性","authors":"A. Kaplan","doi":"10.1109/ICONIP.1999.845668","DOIUrl":null,"url":null,"abstract":"A critical review of the principal strategies of the EEG description as a piecewise stationary process is given and new methodology of EEG segmentation, based on nonparametric statistical analysis, is proposed. Our methodology provides the detection of moments of quasi-stationary segments' boundaries in almost any EEG characteristic for a given level of false alarm probability. Relatively high temporal resolution of the method makes it possible to formulate a new approach to investigation of the functional synchrony between different brain areas. We discuss also the achievements, problems, and prospects of EEG signal segmentation.","PeriodicalId":237855,"journal":{"name":"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Segmental structure of EEG more likely reveals the dynamic multistability of the brain tissue than the continual plasticity one\",\"authors\":\"A. Kaplan\",\"doi\":\"10.1109/ICONIP.1999.845668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A critical review of the principal strategies of the EEG description as a piecewise stationary process is given and new methodology of EEG segmentation, based on nonparametric statistical analysis, is proposed. Our methodology provides the detection of moments of quasi-stationary segments' boundaries in almost any EEG characteristic for a given level of false alarm probability. Relatively high temporal resolution of the method makes it possible to formulate a new approach to investigation of the functional synchrony between different brain areas. We discuss also the achievements, problems, and prospects of EEG signal segmentation.\",\"PeriodicalId\":237855,\"journal\":{\"name\":\"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICONIP.1999.845668\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONIP.1999.845668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Segmental structure of EEG more likely reveals the dynamic multistability of the brain tissue than the continual plasticity one
A critical review of the principal strategies of the EEG description as a piecewise stationary process is given and new methodology of EEG segmentation, based on nonparametric statistical analysis, is proposed. Our methodology provides the detection of moments of quasi-stationary segments' boundaries in almost any EEG characteristic for a given level of false alarm probability. Relatively high temporal resolution of the method makes it possible to formulate a new approach to investigation of the functional synchrony between different brain areas. We discuss also the achievements, problems, and prospects of EEG signal segmentation.