Select your localized edition:

Close ×

More Ways to Connect

Discover one of our 28 local entrepreneurial communities »

Be the first to know as we launch in new countries and markets around the globe.

Interested in bringing MIT Technology Review to your local market?

MIT Technology ReviewMIT Technology Review - logo

 

Unsupported browser: Your browser does not meet modern web standards. See how it scores »

Sleep is a vital part of our existence–we spend a third of our lives asleep, our memory and motor skills fade with lack of sleep, various diseases are associated with disorders of sleep–and yet no one truly knows why we need it. Scientists at the University of California, San Diego, hope to change that. They have developed a method of analyzing brain activity during sleep, which they say is much simpler than current techniques and could potentially be used to study a myriad of sleep disturbances.

“Sleep is a major health problem and scientific mystery,” says Terry Sejnowski, a head of the Computational Neurobiology Laboratory at the Salk Institute for Biological Studies, in La Jolla, CA. “We have a tool here that might help us get to the bottom of that mystery.”

To be diagnosed with a sleep disorder, a patient typically spends the night at a specialized clinic, hooked up to machines that record brain activity, muscle activity, and other factors. A technician or doctor then pores over the data, searching for signs that the patient’s peaceful slumber has gone awry. However, results of the test can vary widely, depending on who analyzes the data.

A new analysis method developed by Sejnowski and Philip Low, a graduate student at the Salk, could make the process much easier and more automated. The researchers have created an algorithm that can detect subtle but statistically significant changes in brain activity. The result is a program that can differentiate the phases of sleep, such as REM (rapid eye movement) sleep, which is typically when we dream, and deep sleep, using less data than other methods do. “The technique has a unique temporal resolution that may be able to define sleep states more accurately,” says Jean-Paul Spire, a neurologist and scientist at the University of Chicago who was not involved in the research.

1 comment. Share your thoughts »

Tagged: Biomedicine

Reprints and Permissions | Send feedback to the editor

From the Archives

Close

Introducing MIT Technology Review Insider.

Already a Magazine subscriber?

You're automatically an Insider. It's easy to activate or upgrade your account.

Activate Your Account

Become an Insider

It's the new way to subscribe. Get even more of the tech news, research, and discoveries you crave.

Sign Up

Learn More

Find out why MIT Technology Review Insider is for you and explore your options.

Show Me
×

A Place of Inspiration

Understand the technologies that are changing business and driving the new global economy.

September 23-25, 2014
Register »