The neurons are turning visual stimuli into units of information, Nemenman explains. "The data is a way for us to read the sentences the fly's vision neurons are conveying to the rest of the brain."
Nemenman and his co-authors took a fresh look at this fly data for the new paper in Physical Review Letters. "We were trying to understand if there is a relationship between ideas of universality, or criticality, in physical systems and neural examples of how animals learn," he says.
In order to navigate in flight, the flies' visual neurons adapt to changes in the visual signal, such as velocity. When the world moves faster in front of a fly, these sensitive neurons adapt and rescale. These adaptions enable the flies to adjust to new environments, just as our own eyes adapt and rescale when we move from a darkened theater to a brightly lit room.
"We showed mathematically that the system becomes Zipfian when you're recording the activity of many units, such as neurons, and all of the units are responding to the same variable," Nemenman says. "The fact that Zipf's law will occur in a system with just 40 or 50 such units shows that biological units are in some sense special they must be adapted to the outside world."
The researchers provide mathematical simulations to back up their theory. "Not only can we predict that Zipf's law is going to emerge in any system which consists of many units responding to variable outside signals," Nemenman says, "we can also tell you how many units you need to develop Zipf's law, given how variable the response is of a single unit."
They are now researching whether they can bring their work full circle, by showing that the mechanism they identified applies to Zipf's law in language.
"Letters and words in language are sequences that encode a description of something that is changing over time, like the plotline in a story," Nemenman s
|Contact: Megan Terraso McRainey|
Emory Health Sciences