Duke University, Durham, North Carolina
Miguel Nicolelis, John Chapin, John Kaas
Awarded $600,000 over two years in support of a collaborative activity project to study how neuronal networks accomplish motor learning.

How does a student driver acquire the sensory/motor associations necessary to execute the actions needed to stop for a red light, proceed at a green light, and begin to slow down (or is it speed up?) when the light is yellow? Monitoring patterns of neuronal activity while subjects perform tasks similar to these that require motor learning is a model for studying how information is integrated across multiple brain systems, e.g., sensory motor integration.

To date, such studies have been hampered by technical limitations. The necessary experiments require electrode arrays capable of simultaneously recording electrical activity from large numbers of neurons in multiple brain sites, over a relatively long learning period.

Moreover, interpreting the highly complex data sets that result from such experiments requires new computational and statistical tools. Drs. Miguel Nicolelis (Duke University), John Chapin (State University of New York), and Jon Kaas (Vanderbilt University) propose a collaborative effort to overcome these limitations. They hope to determine how large networks of neurons interact to mediate the perceptual, motor, and cognitive mechanisms that underlie basic problem-solving strategies primates use in daily life.

This collaboration is not only asking a fundamentally important question – how is information integrated across distributed neural systems, but it is also attempting to push the technology to a higher level of complexity, sophistication, and usefulness.