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 Cracking the brain's numerical code

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Date posted: 24/09/2009

By carefully observing and analyzing the pattern of activity in the brain, researchers have found that they can tell what number a person has just seen. They can similarly tell how many dots a person has been presented with, according to a report published online on September 24th in Current Biology.

These findings confirm the notion that numbers are encoded in the brain via detailed and specific activity patterns and open the door to more sophisticated exploration of humans' high-level numerical abilities. Although "number-tuned" neurons have been found in monkeys, scientists hadn't managed to get any farther than particular brain regions before now in humans.

"It was not at all guaranteed that with functional imaging it would be possible to pick this up," said Evelyn Eger of INSERM in France. "In the monkey, neurons preferring one or the other numerosity appear highly intermixed among themselves as well as with neurons responding to other things, so it might seem highly unlikely that with fMRI [functional magnetic resonance imaging] at 1.5 mm resolution?where one voxel contains many thousands of neurons?one would be able to detect differences in activity patterns between individual numbers. The fact that this worked means that there is probably a somewhat more structured layout of preferences for individual numbers that has yet to be revealed by neurophysiological methods."

The researchers presented ten study participants with either number symbols or dots while their brains were scanned with fMRI. They then used a multivariate analysis method to devise a way of decoding the numbers or number of dots people had observed.

Although the brain patterns corresponding to number symbols differed somewhat from those for the same number of objects, the numerosity of dot sets can be predicted above chance from the brain activation patterns evoked by digits, the researchers show. That doesn't work the other way around, however.

See the full Story via external site: www.physorg.com



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