PATTERNS OF ATTRACTOR DIMENSIONS OF SLEEP EEG

Low dimensional chaos is a property of many physiological oscillatory systems including the brain. Time series of sleep EEG records have bee n analyzed in the framework of recent developments in nonlinear dynami cs. One of the characteristics of a chaotic time series is its attract or dimension. The running attractor dimension of a chaotic time series may reflect changes in states more accurately than manually scored re cords. In the present study the attractor dimensions of consecutive EE G segments of five sleep records were analyzed. The block of the EEG s egment (window) was shifted by various lengths along the entire sleep data of each subject thus producing a running attractor dimension curv e for each record. The attractor dimension values for different sleep stages were significantly different. The pattern of the running attrac tor dimension closely matched the scored hypnograms in these five slee p records.