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============================================================================================================= Network simulations of self-sustained activity in networks of adaptive exponential integrate and fire neurons ============================================================================================================= Demo files implemented using both NEURON and PyNN. demo_cx-lts ----------- Simulations of self-sustained AI states in a small N=500 network of excitatory and inhibitory neurons, described by Adaptive Exponential (Brette-Gerstner-Izhikevich) type neurons with exponential approach to threshold. The connectivity is random and there is a small proportion (5%) of LTS cells among the excitatory neurons. This simulation reproduces Fig. 7 of the paper below. demo_cx_up-down --------------- Simulations of Up-Down states in a two-layer cortical network, with one N=2000 network and a smaller N=500 network. Both networks have excitatory and inhibitory neurons described by Adaptative Exponential (Brette-Gerstner-Izhikevich) type neurons with exponential approach to threshold. The connectivity is random within each network as well as between them. In the N=500 network, there is a small proportion (5%) of LTS cells among the excitatory neurons. This simulation reproduces Fig. 13 of the paper below. See details in the following article: Destexhe, A. Self-sustained asynchronous irregular states and Up/Down states in thalamic, cortical and thalamocortical networks of nonlinear integrate-and-fire neurons. Journal of Computational Neuroscience 27: 493-506, 2009. arXiv preprint: http://arxiv.org/abs/0809.0654 Original NEURON implementation by Alain Destexhe destexhe@unic.cnrs-gif.fr http://cns.iaf.cnrs-gif.fr Converted to PyNN by Andrew Davison davison@unic.cnrs-gif.fr and Lyle Muller lyle.e.muller@gmail.com Usage (NEURON version): nrnivmodl nrngui <file.oc> Usage (Python version): python <file.py> <simulator> where <file.py> is one of the demo files, and <simulator> is one of neuron, nest, pcsim, brian, facets_hardware2, etc...