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Counting Sleep

Illustrations by Dung Hoang

Counting Sleep (continued)

The study points to a surprising fact: Though sleep, as described by Keats, is “more secret than a nest of nightingales,” it generates an enormous amount of data. This plethora of second-by-second information can be both dream and nightmare for researchers.

The Architecture of Sleep

In the atrium of a Johns Hopkins Bayview Medical Center building, a mobile of blue spheres hangs in a surreal constellation. Deeper inside the building is a suite of seven bedrooms. Each room has a bathroom, television, furniture—and a modem-sized electronic unit, which gathers data on the sleeping occupant.

Welcome to the Sleep Study Center.  

This type of research suite marks the gold standard for getting quality data about what happens during sleep. Here, people like Joe Higgins spend a night and have their sleep patterns assessed. Electrodes are affixed to various parts of the body to gather measurements. The sensors in each room send the data to a central hub, where Punjabi points to a page with more than a dozen graphs stacked atop each other. For each subject the scientists gather a dozen or so types of data on eye movement, heart activity, leg activity, oxygen levels, respiration flow and so on. (The Greek roots of polysomnography explain it well: “poly”– many, “somno” – sleep, and “graphy” – write).

Electrodes affixed to various body parts of a sleep subject generate a plethora of second-by-second information that is both dream and nightmare for researchers.

“The thing about [studying] sleep is that it’s a very, very quantitative field,” says Punjabi. “You’re measuring brain activity, and you’re collecting data every second.” He continues, “A hundred to five hundred times per second you’re collecting EEG data. That’s one of the most voluminous things in medicine.”

Yet up to now, the methods for assessing sleep as a series of these discrete stages have been “extremely crude.” That’s why he sees the work of biostatisticians Caffo and Crainiceanu as so important: they’re helping fine-tune the picture from the growing volume of data. “It’s [a matter] of taking a tremendous amount of extracted data and making sense of it,” says Caffo, PhD.

Scientists study our “sleep architecture”— the relative structure of our time sleeping portioned out among five stages, identified by EEG data: stages 1 through 4, plus REM (rapid eye movement) sleep. In The Family That Couldn’t Sleep, D.T. Max describes the typical sequence: Sleep begins with rough alpha waves (stage 1), deepens into longer theta waves (stage 2), followed by sleep spindles, which take the sleeper into the profound sleep of the rolling delta wave of stages 3 and 4. These get interrupted periodically by the jagged lines of REM sleep.

Caffo and colleagues have managed to recast this conventional categorization of sleep as a sequence of five stages and uncover a new pattern that allows clearer correlations to a person’s health. In a 2008 paper in the Journal of Clinical Sleep Medicine, Caffo and Punjabi showed that two groups that seemed to have the same sleep architecture (meaning they spent similar proportions of sleep in the various stages according to conventional interpretation) were in fact very different in their vulnerability to disease.

Research on sleep-disordered breathing has traditionally been based on “composite” sleep-stage summaries, notes Caffo. These were high-level views that could only show the percentage of time spent in each stage of sleep. Caffo and Punjabi wanted to explore the data more precisely. So Caffo and his colleagues tapped two biostatistical tools—log linear and multi-state analysis—to analyze the multiple types of sleep data and tease out previously unknown differences in the transitions between the various sleep stages.

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  • kay smolin

    palo alto 94303 11/20/2009 09:22:54 PM

    good info, need more specific fix

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