%0 Journal Article
%A Plesser, Hans Ekkehard
%A Davison, Andrew P.
%A Diesmann, Markus
%A Fukai, Tomoki
%A Gemmeke, Tobias
%A Gleeson, Padraig
%A Knight, James C.
%A Nowotny, Thomas
%A René, Alexandre
%A Rhodes, Oliver
%A Roque, Antonio C.
%A Senk, Johanna
%A Schwalger, Tilo
%A Stadtmann, Tim
%A Tiddia, Gianmarco
%A van Albada, Sacha
%T Building on Models — A Perspective for Computational Neuroscience
%J Cerebral cortex
%V 35
%N 11
%@ 1047-3211
%C Oxford
%I Oxford Univ. Press
%M FZJ-2025-03958
%P bhaf295
%D 2025
%X Neural circuit models are essential for integrating observations of the nervous system into a consistent whole. Public sharing of well-documented codes for such models facilitates further development. Nevertheless, scientific practice in computational neuroscience suffers from replication problems and little re-use of circuit models. One exception is a data-driven model of early sensory cortex by Potjans and Diesmann which has advanced computational neuroscience as a building block for more complex models. As a widely accepted benchmark for correctness and performance, the model has driven the development of CPU-based, GPU-based, and neuromorphic simulators. On the tenth anniversary of the publication of this model, experts convened at the Käte-Hamburger-Kolleg Cultures of Research at RWTH Aachen University to reflect on the reasons for the model’s success, its effect on computational neuroscience and technology development, and the perspectives this offers for the future of computational neuroscience. This report summarizes the observations by the workshop participants.
%F PUB:(DE-HGF)16
%9 Journal Article
%R 10.1093/cercor/bhaf295
%U https://juser.fz-juelich.de/record/1046791