Data sharing for computational neuroscience.
Computational neuroscience is a subfield of neuroscience that develops models to integrate complex experimental data in order to understand brain function. To constrain and test computational models, researchers need access to a wide variety of experimental data. Much of those data are not readily accessible because neuroscientists fall into separate communities that study the brain at different levels and have not been motivated to provide data to researchers outside their community. To foster sharing of neuroscience data, a workshop was held in 2007, bringing together experimental and theoretical neuroscientists, computer scientists, legal experts and governmental observers. Computational neuroscience was recommended as an ideal field for focusing data sharing, and specific methods, strategies and policies were suggested for achieving it. A new funding area in the NSF/NIH Collaborative Research in Computational Neuroscience (CRCNS) program has been established to support data sharing, guided in part by the workshop recommendations. The new funding area is dedicated to the dissemination of high quality data sets with maximum scientific value for computational neuroscience. The first round of the CRCNS data sharing program supports the preparation of data sets which will be publicly available in 2008. These include electrophysiology and behavioral (eye movement) data described towards the end of this article.
Teeters
Jeffrey L
JL
Redwood Center for Theoretical Neuroscience & Helen Wills Neuroscience Institute, University of California, Berkeley, 3210F Tolman Hall, MC 3192, Berkeley, CA 94720-3192, USA.
Harris
Kenneth D
KD
Millman
K Jarrod
KJ
Olshausen
Bruno A
BA
Sommer
Friedrich T
FT
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