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Computational neuroscience has grown, in distinct directions, from the
success of biophysical models neural activity, the attractiveness of
the brain-as-computer metaphor, and the increasing prominence of
statistical and machine learning methods throughout science. This has
helped create a rich set of ideas and tools associated with
``computation'' to studying the nervous system, but it has also led to
a kind of balkanization of expertise. There is, especially, very
little overlap between mathematical and statistical research in this
area. Important breakthroughs in computational neuroscience could
come from research strategies that are able to combine what are
currently largely distinct approaches.
One purpose of this workshop is to explore potentially
fruitful interactions of modeling ideas that come from mathematics,
statistics, and biophysics. An additional purpose of the workshop is to
bring together U.S. and Japanese researchers in this area. While computational
neuroscience is represented strongly in both the U.S. and Japan there
has been too little concrete communication and interaction between
research groups across our two countries. Interaction across American
and Japanese researchers should facilitate the advance of
cross-disciplinary work.
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