Neurosimulator NeuroNet 

Description NeuroNet is a neural simulator for building Spiking Neural Networks (SNNs), which are biologically inspired artificial neural networks.The application allows you to use SNNs to control the LEGO robot and Myo (EMG) Thalmic blacelet as an input. NeuroNet uses the LIF and Izhikevich’s models of neuron. The spikes between neurons propagate taking into account axonal delays. The effects of short-term and long-term synaptic plasticity are taken into account. The graphical user interface allows you to change the network configuration in a visual-interactive mode, as well as observe and record the characteristics of neurons and the SNN. In addition, tools for automatic generation of SNNs are provided, the statistical characteristics of which (the number of excitatory and inhibitory neurons; the number, value and distribution of connections) are set by the user.  Downloads To install just unzip the archive file to local folder. Run *.exe file. Enjoy ;). Package R56 (Apr. 27, 2023: imlementation of rewiring) Package R48 (Nov. 17, 2022: some fixes) Quick start guide SNNs files set_rewiring.zip

Publications with NeuroNet usage

• Lobov, S.A.; Berdnikova, E.S.; Zharinov, A.I.; Kurganov, D.P., Kazantsev, V.B. STDP driven rewiring in spiking neural networks under stimulus-induced and spontaneous activity. Biomimetics (submitted)
• Lobov, S.A.; Mikhaylov, A.N.; Berdnikova, E.S.; Makarov, V.A.; Kazantsev, V.B. Spatial Computing in Modular Spiking Neural Networks with a Robotic Embodiment. Mathematics 2023, 11 https://doi.org/10.3390/math11010234
• Lobov, S.A.; Zharinov, A.I.; Makarov, V.A.; Kazantsev, V.B. Spatial Memory in a Spiking Neural Network with Robot Embodiment. Sensors 2021, 21 https://doi.org/10.3390/s21082678
• Lobov, S.A.; Mikhaylov, A.N.; Shamshin, M.; Makarov, V.A.; Kazantsev, V.B. Spatial properties of STDP in a self-learning spiking neural network enable controlling a mobile robot. Front. Neurosci. 2020, 14, 88 https://doi.org/10.3389/fnins.2020.00088
• Lobov, S.A.; Chernyshov, A. V; Krilova, N.P.; Shamshin, M.O.; Kazantsev, V.B. Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier. Sensors 2020, 20 https://doi.org/10.3390/s20020500
• Lobov, S.A.; Zhuravlev, M.O.; Makarov, V.A.; Kazantsev, V.B. Noise Enhanced Signaling in STDP Driven Spiking-Neuron Network. Math. Model. Nat. Phenom. 2017, 12, 109–124 https://doi.org/10.1051/mmnp/201712409
• Lobov, S.; Simonov, A.; Kastalskiy, I.; Kazantsev, V. Network response synchronization enhanced by synaptic plasticity. Eur. Phys. J. Spec. Top. 2016, 225, 29–39 http://dx.doi.org/10.1140/epjst/e2016-02614-y