Trends in programming language development and adoption point to Python as the high-level systems integration language of choice. Python leverages a vast developer-base external to the Neuroscience community, and promises leaps in simulation complexity and maintainability to any neural simulator which adopts it. As more and more simulators support Python, model development times can be drastically reduced by promoting code sharing and reuse across simulator communities. As a result, modellers can devote their software development time to innovating new simulation tools such as network topology databases, stimulus programming, analysis and visualisation tools, and simulation accounting, to name a few.

NeuralEnsemble is a multilateral effort to coordinate and organise Neuroscience software development efforts into a larger meta-simulator software system, a natural and alternate approach to incrementally address what is known as the complexity bottleneck, presently a major roadblock for neural modelling. While a solution here is arguably a necessary condition for resolving the present stalemate for understanding the complexities of brain-like computing, a successful initiative could also end up being a major innovation of the field for the larger computing community.

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