Data mining through simulation.

Abstract

Data integration is particularly difficult in neuroscience; we must organize vast amounts of data around only a few fragmentary functional hypotheses. It has often been noted that computer simulation, by providing explicit hypotheses for a particular system and bridging across different levels of organization, can provide an organizational focus, which can be leveraged to form substantive hypotheses. Simulations lend meaning to data and can be updated and adapted as further data come in. The use of simulation in this context suggests the need for simulator adjuncts to manage and evaluate data. We have developed a neural query system (NQS) within the NEURON simulator, providing a relational database system, a query function, and basic data-mining tools. NQS is used within the simulation context to manage, verify, and evaluate model parameterizations. More importantly, it is used for data mining of simulation data and comparison with neurophysiology.