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Learning about Learning - by Directly Driving Networks of Neurons Aaron Batista Associate Professor of Bioengineering University of Pittsburgh New behaviors require new patterns of neural activity among the population of neurons that control behavior. How can the brain find a pattern of activity appropriate for the desired behavior? Why does that learning process take time? To tackle questions like these, we reverse the normal order of operations in systems neuroscience: instead of teaching animals a new behavior and then searching for its neural correlate, we specify a neural activity pattern and then through neurofeedback, we guide the animal to try to exhibit the behavior which would require that activity pattern. Our research question is, which types of neural activity patterns can animals learn to exhibit? We have observed that one type of new neural activity pattern can be learned readily, and another type of neural activity pattern takes longer for animals to learn to exhibit. This provides new insight into the neural mechanisms of skill learning.