Brian 2 allows scientists to simply and efficiently simulate spiking neural network models.
These models can feature novel dynamical equations, their interactions with the …

Sustainable research on computational models of neuronal networks requires published
models to be understandable, reproducible, and extendable. Missing details or ambiguities …

Modern graphics cards contain hundreds of cores that can be programmed for intensive
calculations. They are beginning to be used for spiking neural network simulations. The goal …

Large-scale numerical simulations of detailed brain circuit models are important for
identifying hypotheses on brain functions and testing their consistency and plausibility. An …

At many scales in neuroscience, appropriate mathematical models take the form of complex
dynamical systems. Parameterizing such models to conform to the multitude of available …

Simulating biological neuronal networks is a core method of research in computational
neuroscience. A full specification of such a network model includes a description of the …

Computational models are increasingly important for studying complex neurophysiological
systems. As scientific tools, it is essential that such models can be reproduced and critically …

NEST is a widely used tool to simulate biological spiking neural networks. Here we explain
the improvements, guided by a mathematical model of memory consumption, that enable us …

Objective: Like all scientific research, computational neuroscience research must be
reproducible. Big data science, including simulation research, cannot depend exclusively on …

Advances in experimental techniques and computational power allowing researchers to
gather anatomical and electrophysiological data at unprecedented levels of detail have …