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Neural-net Modeling and Decision Making

Dr. Daniel Levine

Research Description

Professor Daniel Levine's laboratory deals with theory and computer modeling of neural networks that simulate interacting brain regions involved in behavior, cognitive functions, cognitive-emotional interactions, and decision making.
One of their projects deals with modeling how a change in context changes the attributes that determine preferences among objects. An example is that when Coca-Cola introduced New Coke, the new flavor was favored over Old Coke in taste test because of sweetness, but flopped in the marketplace because of unfamiliarity. We are looking at areas of the frontal lobes and limbic system that may be involved in such selections.
Another of their projects deals with modeling the cognitive effects of nicotine, as indicated by experimental results (from another laboratory) showing that smokers who are recently quit are deficient in performance of an attention and short term memory task involving a response to seeing 3 odd or 3 even digits in a row when the digits are rapidly presented on a screen. Our model relates this effect to nicotine's stimulation of the neurotransmitter acetylcholine, which enhances information processing in the cerebral cortex.

For information about applying to work in Dr. Dan Levine’s lab, contact him at Levine@uta.edu (817-272-3598), or contact the graduate advisor, Dr. Martha Mann, at mann@uta.edu.

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