title: Collaborative modelling: the future of computational neuroscience?
abstract: Given the complexity of biological neural circuits and of their component cells and synapses, building and simulating robust, well-validated, detailed models increasingly surpasses the resources of an individual researcher or small research group. In this article, I will briefly review possible solutions to this problem, argue for open, collaborative modelling as the optimal solution for advancing neuroscience knowledge, and identify potential bottlenecks and possible solutions.
authors.affiliation: Unité de Neurosciences, Information et Complexité UNIC, CNRS UPR 3293, Gif sur Yvette, France. andrew.davison@unic.cnrs-gif.fr
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Davison
mesh_terms: D000818:Animals; D003198:Computer Simulation; D003299:Cooperative Behavior; D006801:Humans; D033181:Information Dissemination / Q000379:methods; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009488:Neurosciences / Q000639:trends*; D011381:Programming Languages; D012984:Software / Q000639:trends*; D049490:Systems Biology / Q000639:trends*