CNeuroSim simulates neurons and synaptic connections plus neuromodulation.


Neuron models are an ion channel based model, and a simplified two-dimensional dynamic model. The morphology of real neurons is not simulated. CNeuroSim implements parametrized heterogeneity of intrinsic excitability.


CNeuroSim allows to implement different connectivity schemes by realistic models of NMDA, AMPA and GABA-A synapses.


CNeuroSim allows to simulate modulation by neurochemicals, such as dopamine (neuromodulators, NM), by implementing NM control of synaptic strength and intrinsic excitability. A central NM signal can be controlled by the network to implement feedback.


Input can be directed at specific neurons, and take the form of random background activity, rate-coded patterns, and/or spatio-temporal spike patterns.


CNeuroSim scales for up to 10,000 neurons (1s simulation = 3.5s execution time, MacBookPro) and more. It is implemented in Matlab with a C core for faster execution. A great number of visualization and analysis tools are also integrated.


Scheler G. Learning intrinsic excitability in medium spiny neurons. F1000Research.2013;2:88. doi:10.12688/f1000research.2-88.v2.

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