ID 39804
タイトルヨミ
BP ニューラル ネットワーク オ モチイタ サーカディアン リズムゲン ノ システム ドウテイ
タイトル別表記
BP neural netrworks approach for identifying biological rhythm source in circadian data fluctuations
著者
長篠, 博文 徳島大学医学部保健学科医用放射線科学講座 徳島大学 教育研究者総覧 KAKEN研究者をさがす
芥川, 正武 徳島大学医学部保健学科医用放射線科学講座 徳島大学 教育研究者総覧 KAKEN研究者をさがす
Cisse, Youssouf 徳島大学工学部電気電子工学科|ラヴァル大学医学部医学科
キーワード
circadian rhythms
sleep-wake rhythm
system identification
neural network
moving average process
資料タイプ
学術雑誌論文
抄録
Almost all land animals coordinate their behavior with circadian rhythms, matching their functions to the daily cycles of lightness and darkness that result from the rotation of the earth corresponding to 24 hours. Through external stimuli, such as dairy life activities or other sources from our environment may influence the internal rhythmicity of sleep and waking properties. However, the rhythms are regulated to keep their activity constant by homeostasis while fluctuating by incessant influences of external forces. A modeling study has been developed to identify homeostatic dynamics properties underlying a circadian rhythm activity of sleep and wake data measured from normal subjects, using an MA (Moving Average) model associated with backpropagation (BP) algorithm. As a result, we found out that the neural network can capture the regularity and irregularity components included in the data. The order of MA neural network model depends on subject’s behavior. The last two data are usually dominant in the case without strong external forces. The adaptive changes of the dynamics are evaluated by the change of weight vectors, a kind of internal representation of the trained network. The dynamics is kept in a steady state for more than 20 days. Identified properties reflect the subject’s behavior, and hence may be useful for medical diagnoses of disorders related to circadian rhythms.
掲載誌名
四国医学雑誌
ISSN
00373699
cat書誌ID
AN00102041
出版者
徳島医学会
59
6
開始ページ
304
終了ページ
314
並び順
304
発行日
2003-12-25
備考
EDB ID
フルテキストファイル
言語
jpn
部局
理工学系
医学系