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The growing number of large-scale neuronal network models has created a need for standards and guidelines to ease model sharing and facilitate the replication of results across different simulators. To foster community efforts towards such standards, the International Neuroinformatics Coordinating Facility (INCF) has formed its Multiscale Modeling program,(More)
The behavior of immature cortical networks in vivo remains largely unknown. Using multisite extracellular and patch-clamp recordings, we observed recurrent bursts of synchronized neuronal activity lasting 0.5 to 3 seconds that occurred spontaneously in the hippocampus of freely moving and anesthetized rat pups. The influence of slow rhythms (0.33 and 0.1(More)
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As computational neuroscience matures, many simulation environments are available that are useful for neuronal network modeling. However, methods for successfully documenting models for publication and for exchanging models and model components among these projects are still under development. Here we briefly review existing software and applications for(More)
While an increasing number of biophysically detailed neuronal models (featuring (semi-) realistic morphologies and voltage and ligand gated conductances) are being shared across the community through resources like ModelDB, these usually only represent a snapshot of the model at the time of publication, in a format specific to the original simulator used.(More)
Almost all research work in computational neuroscience involves software. As researchers try to understand ever more complex systems, there is a continual need for software with new capabilities. Because of the wide range of questions being investigated, new software is often developed rapidly by individuals or small groups. In these cases, it can be hard(More)
We describe a novel method for calculating the quasi-static electrical potential on tetrahedral meshes, which we call E-Field. The E-Field method is implemented in STEPS, which performs stochastic spatial reaction-diffusion computations in tetrahedral-based cellular geometry reconstructions. This provides a level of integration between electrical(More)
Methods for storing and sharing biological models tend to focus on directly encoding a model and its equations. However, many models share the same equations, subject only to differences in parameter values or the number of instances of particular processes. We have therefore developed a mechanism within NeuroML[1] to express the common structural and(More)