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Brain network scanning could predict effects of injury

A new brain scanning technique could help doctors identify and even predict the effects of brain injuries such as strokes.
Written by Andrew Nusca, Contributor

A brain scanning technique could help doctors identify and even predict the effects of brain injuries such as strokes.

Neurologists at the Washington University School of Medicine in St. Louis used the method, called resting-state functional connectivity, or FC, to find damaged brain networks.

The technique was originally developed to study how brain networks facilitate collaboration between various parts of the brain. But researchers Maurizio Corbetta and Alex Carter believe it can help them better link changes in patient impairment to actual brain damage, allowing for better treatment.

The FC method uses magnetic resonance imaging, or MRI, scanners that track changes in blood flow to various brain regions.

Blood flow in the brain tends to rise and fall in sync with brain activity.

In a study of 23 patients who had recently survived strokes, the researchers discovered that those with damage to networks that cross both sides of the brain were more impaired than those with damage to networks in just one side of the brain.

Though scientists already believed that one part of the brain can control the other, the researchers' results suggest that our brains may be far more complex in the way they are wired.

In other words: while each side of the brain controls the opposite side of the body, it appears that proper function requires both sides functioning in balance.

"It's not wrong to say that one side of your brain controls the opposite side of your body, but we're starting to realize that it oversimplifies things," said assistant professor and lead author Alex Carter in a statement. "It's starting to seem like proper function requires the two hemispheres to be competing for attention, pushing against each other and thereby achieving some kind of balance."

Their results were published in the March issue of Annals of Neurology.

This post was originally published on Smartplanet.com

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