Network
CNeuroSim allows to implement different connectivity schemes by realistic models of NMDA, AMPA and GABA-A synapses. It also models G-protein coupled receptors for neuromodulatory (NM) signals.
Neurons
CneuroSim has two layers of processing for each neuron, an external and an internal layer. The internal layer stores information away from the horizontal network. Layers are coupled and exchange information when neurons are stimulated.
Neuromodulation
CNeuroSim allows to simulate neuromodulation (NM), such as by dopamine, serotonin, acetylcholine, opioids, by implementing NM control of synaptic strength and intrinsic excitability. NM signals result from a central brain area by network feedback, or from local release. NM affects internal signaling.
Input
Input can be directed at the whole network or specific neurons, and take the form of random background activity, rate-coded patterns, and/or spatio-temporal spike patterns.
Implementation
CNeuroSim is implemented in C for fast execution. Matlab-based visualization and analysis tools are also integrated.
Publications
Scheler G. Learning intrinsic excitability in medium spiny neurons. F1000Research.2013;2:88. doi:10.12688/f1000research.2-88.v2.
Scheler G. Neuromodulation influences synchronization and intrinsic read-out. F1000Res. 2018 Aug 14;7:1277. doi: 10.12688/f1000research.15804.2.
Scheler, G. Sketch of a novel approach to a neural model. arxiv:q-bio.NC 2209.06865.Jan 2023.