WASHINGTON Inspired by the use of microarray chips that look for gene combinations, psychologists are using "pattern array" software to spot movements in rats that might help them predict diseases such as Lou Gehrig's syndrome.
A report in the August issue of Behavioral Neuroscience, published by the American Psychological Association, describes how this novel use of data mining may enable investigators to test therapies to delay or even prevent disease, starting with hereditary forms.
The authors demonstrated their original software on mutant rats used as an animal model of amyotrophic lateral sclerosis (ALS), a progressive and fatal neurodegenerative disease that's inherited about one in 10 times. (The origins of the other cases are still under investigation.) The disease, which attacks the nerve cells that control movement, is identified with Yankee slugger Lou Gehrig, who died of ALS in 1941, two years after diagnosis.
Researchers led by Neri Kafkafi, PhD, of the Maryland Psychiatric Research Center, part of the University of Maryland's School of Medicine, mathematically analyzed about 50,000 predetermined movement patterns that resulted when rats roamed freely, one by one, in a small arena. The software created an abstract space defined by combinations of behavior such as speed, acceleration and direction of movement. Mining the resulting behavioral data enabled researchers to test many more facets of behavior than they could analyze manually.
After videotaping the movement of two groups of rats one type with the mutation that results in an ALS-type syndrome, the other type normal controls -- the scientists used the computer to "pan" for differences between groups and identified a unique motor pattern in mutant rats two months before disease onset (which would equate to roughly five to 10 years in humans).
Of the multitude of behavior patterns analyzed, the predefined "heavily braking while slightly
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American Psychological Association