就寝中覚醒の確率過程モデリング - 脳波による視床-皮質間結合強度の解析結果から
Waking during nocturnal sleep (WS) is gaining attention in the health science field. Although some findings, (e.g., the power-law distribution of the wake duration time) have been reported, the mechanism of it is still unclear. In this talk, we light on this issue. In a previous study, we showed tha...
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Published in | Transactions of Japanese Society for Medical and Biological Engineering Vol. 54Annual; no. 28AM-Abstract; p. S294 |
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Main Authors | , , , , |
Format | Journal Article |
Language | Japanese |
Published |
公益社団法人 日本生体医工学会
2016
Japanese Society for Medical and Biological Engineering |
Online Access | Get full text |
ISSN | 1347-443X 1881-4379 |
DOI | 10.11239/jsmbe.54Annual.S294 |
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Abstract | Waking during nocturnal sleep (WS) is gaining attention in the health science field. Although some findings, (e.g., the power-law distribution of the wake duration time) have been reported, the mechanism of it is still unclear. In this talk, we light on this issue. In a previous study, we showed that corticothalamic feedback loop strength (c2), estimated by an EEG analysis method, clearly tracks the wake-to-sleep transition just before nocturnal sleep. This time, we applied this method to nocturnal sleep. The c2-distribution (n = 52) during nocturnal sleep exhibited clear bimodal, which can be well approximated by superposition of two Gaussian distributions corresponding to sleep (Non-REM 1-4 and REM) and wake states, respectively. This observation suggests that the dynamical change of c2 obeys the Ornstein-Uhlenbeck process in each state. Based on these findings, we show an attempt for stochastic process modeling of WS. |
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AbstractList | Waking during nocturnal sleep (WS) is gaining attention in the health science field. Although some findings, (e.g., the power-law distribution of the wake duration time) have been reported, the mechanism of it is still unclear. In this talk, we light on this issue. In a previous study, we showed that corticothalamic feedback loop strength (c2), estimated by an EEG analysis method, clearly tracks the wake-to-sleep transition just before nocturnal sleep. This time, we applied this method to nocturnal sleep. The c2-distribution (n = 52) during nocturnal sleep exhibited clear bimodal, which can be well approximated by superposition of two Gaussian distributions corresponding to sleep (Non-REM 1-4 and REM) and wake states, respectively. This observation suggests that the dynamical change of c2 obeys the Ornstein-Uhlenbeck process in each state. Based on these findings, we show an attempt for stochastic process modeling of WS. |
Author | 東郷, 史治 山本, 義春 中村, 亨 岸, 哲史 山口, 郁博 |
Author_FL | Yamamoto Yoshiharu Nakamura Toru Kishi Akifumi Yamaguchi Ikuhiro Togo Fumiharu |
Author_FL_xml | – sequence: 1 fullname: Yamaguchi Ikuhiro – sequence: 2 fullname: Togo Fumiharu – sequence: 3 fullname: Kishi Akifumi – sequence: 4 fullname: Nakamura Toru – sequence: 5 fullname: Yamamoto Yoshiharu |
Author_xml | – sequence: 1 fullname: 岸, 哲史 organization: 東京大学大学院教育学研究科 身体教育学コース – sequence: 1 fullname: 中村, 亨 organization: 東京大学大学院教育学研究科 身体教育学コース – sequence: 1 fullname: 山口, 郁博 organization: 東京大学大学院教育学研究科 身体教育学コース – sequence: 1 fullname: 東郷, 史治 organization: 東京大学大学院教育学研究科 身体教育学コース – sequence: 1 fullname: 山本, 義春 organization: 東京大学大学院教育学研究科 身体教育学コース |
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DocumentTitleAlternate | Stochastic process modeling for waking during nocturnal sleep; based on EEG analysis using a corticothalamic model |
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Snippet | Waking during nocturnal sleep (WS) is gaining attention in the health science field. Although some findings, (e.g., the power-law distribution of the wake... |
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Title | 就寝中覚醒の確率過程モデリング - 脳波による視床-皮質間結合強度の解析結果から |
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