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The Science of Sleep

2.26.2008

Modeling the Dynamics of Sleep Using State Space Analysis

SPEAKER:
Tom Scammell, MD
HMS, BIDMC

MODERATOR:
Clifford B. Saper, MD, PhD: HMS, BIDMC


  • Summary
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Modeling the Dynamics of Sleep Using State Space Analysis

Narcolepsy is a common disease that causes daytime sleepiness often in conjunction with hypnagogic hallucinations (vivid dreams as one falls asleep), sleep paralysis (paralysis upon waking up), and cataplexy (muscle weakness triggered by strong emotions).  In patients with the disease, the brain has lost almost all the neurons responsible for producing the peptide neurotransmitter orexin, also known as hypocretin.  Mice engineered to lack orexin display many of the symptoms of narcolepsy, transitioning very frequently between wakefulness and sleepiness.  Using discrete state variables to describe the sleeping and waking states of these “narcoleptic” mice does not capture the breadth of their behavior, so researchers in the lab of Tom Scammell have come up with a continuous two-dimensional state space upon which the sleepiness of the mice can be measured. 

In their state space, the relative number of low-frequency waves is measured on one axis, and the relative number of middle-frequency (theta) waves is depicted on the other.  One-second electroencephalogram (EEG) recordings can be plotted in this state space, and by sampling the sleep state of a mouse every second, researchers can trace the mouse’s trajectory through the state space.  In the state space, REM sleep, non-REM sleep, and wakefulness occupied distinct areas.  Dr. Scammell’s team found that the “wakefulness” and “non-REM” areas were closer for “narcoleptic” mice than for regular mice.  They also found that the “narcoleptic” mice transitioned from one area to another more quickly than the normal mice.  These observations suggest intriguing ideas about narcolepsy, and the “state space” concept offers a promising new way to look at sleep.      

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