In computational neuroscience, as in science in general, it is essential that results be testable in depth by other laboratories using the same methods. The obstacles to replicating and testing published computational models are considerable. For example, most papers do not include a complete model specification, and typographical errors are common. In principle one should be able to determine the model specification from the authors' computer code, but there are many reasons why this seldom works out in practice--in the interval between completion of the work and publication of the article, hard drives crash, archived copies are lost, key authors move to new positions leaving noone in the lab who can identify the files that were actually used. Thus there is a critical need for a database where published models can be archived so that they can be openly accessed, downloaded, and tested.