Algorithm for sleep scoring in experimental animals based on fast Fourier transform power spectrum analysis of the electroencephalogram

We developed a simple computer-based, sleep scoring algorithm that categorizes three vigilance states of rats and mice as wakefulness, rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep, based on fast Fourier transform analyses of an electroencephalogram (EEG) classified in the frequency bands of δ (0.75–4 Hz) and θ (6–10 Hz), and other parameters such as electromyogram (EMG) integral and animal movement. This algorithm is composed of four steps. Step 1, active wakefulness, is specified when activity is detected by monitoring the animal with an infrared locomotion sensor. Step 2, NREM, is decided by an EEG δ power greater than the threshold. Step 3, REM, is specified by a higher EEG θ/(δ + θ) ratio and a lower EMG integral than the threshold values and Step 4, an undefined epoch, is classified as a state of quiet wakefulness. This algorithm was found to be in >90% agreement with the waveform recognition procedure and decreased processing time to 40 min for 24-h recording data from eight animals. New software, SleepSign ver. 3, was designed to calculate automatically the three threshold values based on percentage of time spent in each sleep stage thus far reported in rodents.

[1]  T YOKOTA,et al.  Analysis of the electroencephalogram of children by histogram method. , 1958, Electroencephalography and clinical neurophysiology.

[2]  A. Rechtschaffen,et al.  A manual of standardized terminology, technique and scoring system for sleep stages of human subjects , 1968 .

[3]  L. Astic,et al.  Ontogenesis of the states of sleep in rat, cat, and guinea pig during the first postnatal month. , 1970, Developmental psychobiology.

[4]  R. D. Joseph,et al.  Pattern recognition of EEG-EOG as a technique for all-night sleep stage scoring. , 1972, Electroencephalography and clinical neurophysiology.

[5]  A. Rechtschaffen,et al.  Mammalian Sleep, Longevity, and Energy Metabolism; pp. 425–446 , 1974 .

[6]  R. Meddis.  The sleep instinct , 1977 .

[7]  G. Paxinos,et al.  The Rat Brain in Stereotaxic Coordinates , 1983 .

[8]  J. Allan Hobson,et al.  A microcomputer-based system for automated EEG collection and scoring of behavioral state in cats , 1988, Brain Research Bulletin.

[9]  H. Kuwahara,et al.  Automatic real-time analysis of human sleep stages by an interval histogram method. , 1988, Electroencephalography and clinical neurophysiology.

[10]  C J Goeller,et al.  A microcomputer-based sleep stage analyzer. , 1989, Computer methods and programs in biomedicine.

[11]  P. Achermann,et al.  Period‐amplitude analysis and power spectral analysis: a comparison based on all‐night sleep EEG recordings , 1993, Journal of sleep research.

[12]  D. Neckelmann,et al.  The reliability and functional validity of visual and semiautomatic sleep/wake scoring in the Møll-Wistar rat. , 1994, Sleep.

[13]  C J Griffiths,et al.  Automated recognition of EEG changes accompanying arousal in respiratory sleep disorders. , 1996, Sleep.

[14]  H. Matsumura,et al.  Continuous recordings of brain regional circulation during sleep/wake state transitions in rats. , 1996, The American journal of physiology.

[15]  S. Uchida,et al.  Computerization of Fujimori's method of waveform recognition A review and methodological considerations for its application to all-night sleep EEG , 1996, Journal of Neuroscience Methods.

[16]  George Paxinos,et al.  The Mouse Brain in Stereotaxic Coordinates , 2001 .

[17]  Y. Urade,et al.  Strong rebound of wakefulness follows prostaglandin D2‐ or adenosine A2a receptor agonist‐induced sleep , 2000, Journal of sleep research.

[18]  T. Kaneko,et al.  Dominant localization of prostaglandin D receptors on arachnoid trabecular cells in mouse basal forebrain and their involvement in the regulation of non-rapid eye movement sleep , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[19]  K. Loparo,et al.  Automated detection of tracé alternant during sleep in healthy full-term neonates using discrete wavelet transform , 2001, Clinical Neurophysiology.

[20]  Y. Urade,et al.  Arousal effect of orexin A depends on activation of the histaminergic system , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Richard Stephenson,et al.  Design and validation of a computer-based sleep-scoring algorithm , 2004, Journal of Neuroscience Methods.

[22]  R. Jakus,et al.  Effects of a single dose of 3,4-methylenedioxymethamphetamine on circadian patterns, motor activity and sleep in drug-naive rats and rats previously exposed to MDMA , 2004, Psychopharmacology.

[23]  Accuracy evaluation of sleep-wake stage analysis with SleepSign Ver2.0 , 2004 .

[24]  Masayoshi Kuwahara,et al.  Changes in autonomic control of heart associated with classical appetitive conditioning in rats. , 2005, Experimental animals.

[25]  B. Fredholm,et al.  Adenosine A2A, but not A1, receptors mediate the arousal effect of caffeine , 2005, Nature Neuroscience.

[26]  Wei-Min Qu,et al.  Altered sleep-wake characteristics and lack of arousal response to H3 receptor antagonist in histamine H1 receptor knockout mice. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[27]  K. Müller,et al.  Automatic sleep stage classification using two-channel electro-oculography , 2007, Journal of Neuroscience Methods.