Computational Neuroscience
The University of Minnesota has a very strong computational neuroscience
community, with modeling efforts ranging from the molecular to the
cellular to the systems scales. Computational neuroscience in the
Graduate Program in Neuroscience is well integrated with experimental
research. Most labs with computational components also have fully
developed experimental programs. Examples of computational neuroscience
at the University of Minnesota include molecular models of protein
folding, subcellular models of synaptic vesicle release, cellular
models of retinal cells, network models of hippocampus, and temporal-difference
models of the striatum. Courses in computational neuroscience offered
each year include one course on cellular models and one course on
systems and information processing.
[Picture of network settling.]
Intrinsic connections force an attractor network model of the head
direction system to settle from noise to a coherent representation
of orientation.
Graduate Program Faculty
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