PT - JOURNAL ARTICLE AU - Svenn-Arne Dragly AU - Milad Hobbi Mobarhan AU - Andreas Våvang Solbrå AU - Simen Tennøe AU - Anders Hafreager AU - Anders Malthe-Sørenssen AU - Marianne Fyhn AU - Torkel Hafting AU - Gaute T. Einevoll TI - Neuronify: An Educational Simulator for Neural Circuits AID - 10.1523/ENEURO.0022-17.2017 DP - 2017 Mar 01 TA - eneuro PG - ENEURO.0022-17.2017 VI - 4 IP - 2 4099 - http://www.eneuro.org/content/4/2/ENEURO.0022-17.2017.short 4100 - http://www.eneuro.org/content/4/2/ENEURO.0022-17.2017.full SO - eNeuro2017 Mar 01; 4 AB - Educational software (apps) can improve science education by providing an interactive way of learning about complicated topics that are hard to explain with text and static illustrations. However, few educational apps are available for simulation of neural networks. Here, we describe an educational app, Neuronify, allowing the user to easily create and explore neural networks in a plug-and-play simulation environment. The user can pick network elements with adjustable parameters from a menu, i.e., synaptically connected neurons modelled as integrate-and-fire neurons and various stimulators (current sources, spike generators, visual, and touch) and recording devices (voltmeter, spike detector, and loudspeaker). We aim to provide a low entry point to simulation-based neuroscience by allowing students with no programming experience to create and simulate neural networks. To facilitate the use of Neuronify in teaching, a set of premade common network motifs is provided, performing functions such as input summation, gain control by inhibition, and detection of direction of stimulus movement. Neuronify is developed in C++ and QML using the cross-platform application framework Qt and runs on smart phones (Android, iOS) and tablet computers as well personal computers (Windows, Mac, Linux).