Collaborative Modeling in Neuroscience: Time to Go Open Model?

Abstract

Computational modeling in neuroscience has traditionally followed the ‘single researcher’s project’ approach. Building a model and using it to investigate a scientific question is often the work of one scientist or, at most, of a few people working closely together in one research group. This is quite similar to how most experiments are still being done in neuroscience, where, typically, each student or postdoc have their ‘own’ project. But the rest of biology has been evolving away from this modus operandi. Especially since the success of Human Genome Project the consortium-based research approach is commonly used to tackle complex problems. Slowly such large-scale ‘anonymous’ research projects are also finding their way into neuroscience and into computational neuroscience. The most famous and controversial example of the latter is the Blue Brain Project, which uses a supercomputer infrastructure to simulate the cortical column. But while the Blue Brain Project and other similar initiatives involve consortia of collaborating researchers, the projects have been closed to outsiders. Several new initiatives promote a different approach to model building, similar to the open source development of computer code. While open source software is often mainly seen as ‘free’, more importantly in the context of this editorial, it is usually also understood to be developed in a public, collaborative manner. A first example of open source code development in computational neuroscience was the GENESIS simulator and a more recent example is the NEST simulator. A full comparison of these two simulators and how they are being developed is beyond the scope of this editorial, but the different ways in which they organize collaborative development reflects global trends in the open source movement (e.g. the need to policeWikipedia). Where GENESIS code development was unstructured, both at the human and at the IT end, NEST development is controlled by an association, the NEST Initiative, and uses modern IT tools like version control and continuous integration-based workflows. But despite these differences, the underlying philosophy is identical: code development for large software products is labor intensive and beyond the scope of one laboratory. This can be overcome by collaborative development, with many research groups contributing, and because the list of candidate developers is not known a priori a public, open model promotes the widest involvement. Similar considerations can be brought to model building. Creating a detailed computational model from scratch takes a lot of time, in my experience at least one man year for a single neuron model. But recent modeling ambitions are