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The Center for Control, Dynamical Systems, and Computation University of California at Santa Barbara
 

Summary: The Center for Control, Dynamical Systems, and Computation
University of California at Santa Barbara
Spring 2008 Seminar Series
Presents
How Difficult Skills Become Automatic:
A Computational Neuroscience Approach
F. Gregory Ashby
UC Santa Barbara, Laboratory for Computational Cognitive Neuroscience
Friday, May 23, 2008 3:00-4:00pm Harold Frank Hall 1104
Abstract:
Abiologicallydetailedcomputationalmodelisdescribedofhowvisual-motorskillsbecome
automatic. The model assumes there are two neural pathways from the relevant visual
association area to the premotor area that mediates response selection. A longer and
slower path projects to premotor cortex via the striatum, globus pallidus, and thalamus,
whereas a faster, purely cortical path projects directly from the visual association area
to the premotor area. The model assumes that the subcortical path, although slower,
has greater neural plasticity because of a dopamine-mediated learning signal from
the substantia nigra. In contrast, the faster cortical-cortical path learns more slowly via
(dopamine independent) classical two-factor Hebbian learning. Because of its greater
plasticity, early performance is dominated by the subcortical path, but the development

  

Source: Akhmedov, Azer - Department of Mathematics, University of California at Santa Barbara

 

Collections: Mathematics