Quantitative study of the sleep onset period via detrended fluctuation analysis: Normal vs. narcoleptic subjects

• Published in: Clinical neurophysiology Vol. 120; no. 7; pp. 1245 - 1251
• Main Authors: Kim, Jong Won, Shin, Hong-Beom, Robinson, Peter A
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ireland Ltd 01.07.2009; Elsevier
• Subjects: Adolescent; Adult; Biological and medical sciences; Brain - physiopathology; Case-Control Studies; Disorders of higher nervous function. Focal brain diseases. Central vestibular syndrome and deafness. Brain stem syndromes; Dynamic detrended fluctuation analysis; Electroencephalogram; Electroencephalography; Electrophysiological Phenomena - physiology; Female; Fundamental and applied biological sciences. Psychology; Humans; Male; Medical sciences; Models, Biological; Narcolepsy; Narcolepsy - diagnosis; Narcolepsy - physiopathology; Nervous system (semeiology, syndromes); Neurology; Scaling exponent; Sleep - physiology; Sleep onset; Sleep onset period; Sleep Stages - physiology; Sleep. Vigilance; Vertebrates: nervous system and sense organs; Young Adult; Scaling exponent; Narcolepsy; Dynamic detrended fluctuation analysis; Electroencephalogram; Sleep onset; Sleep onset period; Human; Nervous system diseases; Sample size; Central nervous system; Sleep disorder; Barrier; Spectral analysis; Dynamic method; Encephalon; Electrodiagnosis; Analysis method; Sleep; Sleep wake cycle; Diagnosis; Neurological disorder
• ISSN: 1388-2457; 1872-8952
• DOI: 10.1016/j.clinph.2009.04.018

Abstract Objective To examine the process of the sleep onset quantitatively and explore differences between narcoleptics and controls during the sleep onset period (SOP). Method Dynamic detrended fluctuation analysis (DFA) was applied to electroencephalograms recorded during multiple sleep latency tests of 11 drug-free narcoleptic patients ( 19.3 ± 4.4 yrs; 8 males) and 9 healthy controls ( 23.8 ± 6.3 yrs; 6 males). The SOP of each group was estimated by fitting the time courses of the DFA scaling exponents to a parametric curve. Results The sequence of DFA exponents showed that electrophysiological brain activity was changing rapidly across the SOP. This transition was also verified by a conventional method (i.e., dynamic spectral analysis). The SOP durations of narcoleptics and controls were estimated as 239 ± 25 s and 145 ± 20 s, respectively. Conclusions The significantly larger SOP of narcoleptics, compared to controls, is consistent with the wake state of narcolepsy being more susceptible to sleep due to a lower barrier to transitioning to sleep. Significance Our results suggest that electrophysiological signatures of narcolepsy could be quantified by dynamic DFA, so the method may have promise as a potential tool to help the diagnosis of narcolepsy despite the present study’s limited sample size.