Neuronify: An Educational Simulator for Neural Circuits
Open accessAbstract
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).
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PNNs around hippocampal PV neurons may attribute their relative higher propagation velocity of action potential with rare failure than principal neurons under comparable conditions.
“Indeed, PNNs around hippocampal PV neurons may attribute their relative higher propagation velocity of action potential with rare failure than that of principle neurons under comparable condition37.”
From Perineuronal nets decrease membrane capacitance of peritumoral fast spiking interneurons in a model of epilepsy (2018) · cites this paper as [37]
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- Authors
- Dragly, S.-A., Hobbi Mobarhan, M., Våvang Solbrå, A., Tennøe, S., Hafreager, A., Malthe-Sørenssen, A., Fyhn, M., Hafting, T., & Einevoll, G. T.
- Affiliations
- University of Oslo (NO)
- Corresponding author
- Einevoll, Gaute T.
- ORCID
- Venue
- eneuro
- Publisher
- Society for Neuroscience
- Published
- 2017-03
- Volume
- 4
- Issue
- 2
- Pages
- ENEURO.0022-17.2017
- ISSN
- 2373-2822 (ISSN-L)
- PMC
- PMC5355897
- OpenAlex
- W2592512818
- Cited by
- 16
- References
- 24
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 3 · 2023: 1 · 2022: 2 · 2021: 2 · 2020: 1 · 2019: 2 · 2018: 1
- FWCI
- 0.63
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- eNeuro (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Undergraduate Neuroscience Education and Research
- Physical Sciences › Engineering › Media Technology › Experimental Learning in Engineering
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- educational apps, neural circuit simulation, integrate-and-fire neurons, neural network model, network motifs, mobile application, Qt, QML
- MeSH terms
- Action Potentials, Animals, Electric Stimulation, Models, Neurological, Neural Inhibition, Synaptic Transmission, Neurons, Neurosciences, Periodicity, Touch, Vision, Ocular, Neural Networks, Computer, Mobile Applications
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