A closer reading of EEGs was also how researchers, working in Parma, Italy, more than 20 years ago, discovered the cyclic alternating pattern. These scientists noticed spontaneously occurring “unstable” periods in NREM during which brain waves alternate rapidly between frequencies. A CAP repeats every 20 to 60 seconds or so and alternates with more stable periods of NREM. The researchers think that during the times of unstable CAP, the sleeper undergoes frequent sleep disturbances and even microarousals that are so subtle they may not be readily visible on conventional sleep studies.

CAP is part of the normal fabric of sleep, but it becomes more pronounced in sleep disorders. During the two decades since they first identified CAP, the Parma researchers have sought to show connections between unusual CAP activity and sleep problems. One study, which they reported in 1996 in the Journal of Clinical Neurophysiology, compared 12 sleepers with periodic limb movements to 12 control subjects. Those with PLMS showed above-normal CAP activity, and almost all of their jarring movements occurred during CAP. More recently, a May 2007 study in the journal Sleep found a link between excessive CAP and subjective complaints of daytime sleepiness in patients with previously undiagnosed upper airway resistance syndrome.

In their work with electrocardiograms, Thomas and Goldberger also found two sleep patterns, unstable and stable sleep, “as different from each other as Metallica and Beethoven,” Thomas says. These patterns are similar to the CAP (unstable) and non-CAP (stable) patterns visible to the trained eye on an EEG, but instead of just reflecting a brain state, they represent the coupling of many biological systems, including the autonomic nervous system, respiration and heart rate. Stable and unstable patterns oscillate along a recurring time scale, much as CAP episodes do, and are independent of standard sleep stages. It seems everyone has some unstable sleep, but sleep disorders produce more of it.

Hard to glean from EEG squiggles, stable and unstable sleep patterns are easily recognized on the new readouts produced by Goldberger’s algorithm. These graphs, called sleep spectrograms, resemble 3-D mountain ranges, with the landscape of stable sleep hovering over the unstable ranges. By showing the impact of arousals or breathing disruptions, the landscapes may essentially map how well someone is sleeping.

The stable sleep of a healthy subject produces much higher peaks on a spectrogram than does unstable sleep, whereas in a patient with sleep apnea, for example, the stable landscape almost disappears, and the unstable ranges dominate. Yet after an apnea patient is aided with a special breathing device, a healthy landscape profile will immediately appear on the spectrogram. According to Goldberger and Thomas, this method also makes it easier to distinguish obstructive sleep apnea, caused by mechanical blockage at the throat, from the rarer central sleep apnea, caused by faulty brain signals or by heart failure. That’s an important distinction, because central sleep apnea often requires different treatments, including drugs to modulate breathing control, and may be worsened by conventional therapies for obstructive apnea.

In addition to helping physicians diagnose disorders, stable and unstable patterns reveal something about sleep quality that doesn’t involve measuring age-variable slow-wave sleep. While healthy 60-year-olds show little slow-wave sleep on an EEG—apparently, older people get much less SWS—their ECG-derived spectrograms show plenty of stable sleep. Indeed, Thomas thinks that stable patterns, which aren’t captured at all in standard sleep studies, could be an effective measure of sleep quality. In stable sleep, the brain, the heart and respiration become calm, whereas in unstable sleep, everything fluctuates as on a choppy sea—the brain undergoes more frequent microarousals, or CAP, and heart and respiration rates rise and fall, for instance—and this produces a less restorative slumber.

Because neither CAP nor stable-unstable sleep patterns correspond with standard sleep stages, many sleep physicians are skeptical of their importance. But others, including Verma, welcome this research as an attempt to explain what’s going on with patients who don’t meet the criteria for sleep apnea but whose sleep isn’t refreshing. And Virend Somers, a consultant cardiologist at the Mayo Clinic in Rochester, Minn., likes having an alternative approach for evaluating the quality and nature of sleep and identifying its pathologies. “What happens to the heart during sleep, as measured by an ECG, is an important emerging area,” Somers says.

Yet Verma doesn’t think the sleep spectrograms will soon replace the EEG as a diagnostic tool. Despite the statistical association between CAP and ECG-measured unstable sleep, directly gauging CAP activity on an EEG is much further along, in terms of scientific validity and widespread acceptance, than the new ECG-based approach, Verma says. Still, the ECG research, plus several other independent lines of inquiry into alternating brain patterns, has finally begun to modify our 40-year-old conception of what sleep is. As Sejnowski says of his powerful new model for recognizing previously invisible EEG patterns, “We’re zooming in on the nuances of sleep and finding things no one has ever seen.” It could take years before the average sleep clinic is equipped to uncover such nuances. Racing against the almost-daily news about the ill effects of poor sleep, it can catch up none too soon.

Dossier

1. “An Electrocardiogram-Based Technique to Assess Cardiopulmonary Coupling During Sleep,” by Robert Thomas, Joseph Mietus, Chung-Kang Peng and Ary Goldberger, Sleep, September 2005. An introduction to the new method of “listening” to sleep by analyzing patterns from heart signals, then displaying those patterns in a visual format called a sleep spectrogram.

2. “The Nature of Arousal in Sleep,” by Péter Halász, Mario Terzano, Liborio Parrino and Róbert Bódizs, Journal of Sleep Research, Vol. 13, 2004. The authors theorize that, one, microarousals result from the cyclic alternating pattern (CAP) of brain waves; and, two, contrary to conventional views, arousals are normal elements of sleep that become dangerous only in sleep disorders.

3. “The Cyclic Alternating Pattern Demonstrates Increased Sleep Instability and Correlates With Fatigue and Sleepiness in Adults With Upper Airway Resistance Syndrome,” by Christian Guilleminault, Cecilia Lopes, Chad Hagen and Agostinho da Rosa, Sleep, May 1, 2007. This small but intriguing study found that patients complaining of excessive daytime sleepiness have a mild breathing disorder that conventional sleep studies do not detect, but that CAP analysis can.

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