Journal article
Patterns of attractor dimensions of sleep EEG
Dept. of Psychopharmacology, National Institute of Mental Health & Neurosciences, Bangalore, India.1
Low dimensional chaos is a property of many physiological oscillatory systems including the brain. Time series of sleep EEG records have been analyzed in the framework of recent developments in nonlinear dynamics. One of the characteristics of a chaotic time series is its attractor dimension. The running attractor dimension of a chaotic time series may reflect changes in states more accurately than manually scored records.
In the present study the attractor dimensions of consecutive EEG segments of five sleep records were analyzed. The block of the EEG segment (window) was shifted by various lengths along the entire sleep data of each subject thus producing a running attractor dimension curve for each record. The attractor dimension values for different sleep stages were significantly different.
The pattern of the running attractor dimension closely matched the scored hypnograms in these five sleep records.
Language: | English |
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Year: | 1995 |
Pages: | 455-462 |
ISSN: | 18790534 and 00104825 |
Types: | Journal article |
DOI: | 10.1016/0010-4825(95)00032-y |
Adolescent Adult Algorithms Attractor dimension Brain Chaos EEG Electroencephalography Humans Hypnogram Middle Aged Nonlinear Dynamics Nonlinear dynamics Pattern Recognition, Automated Polysomnography Running attractor dimension Signal Processing, Computer-Assisted Sleep Sleep Stages Sleep stages Sleep, REM Wakefulness