Firing patterns in the adaptive exponential integrate-and-fire model. Export

@article{citeulike:3574105, abstract = {For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.}, author = {Naud, Richard and Marcille, Nicolas and Clopath, Claudia and Gerstner, Wulfram}, citeulike-article-id = {3574105}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/s00422-008-0264-7}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/19011922}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=19011922}, citeulike-linkout-3 = {http://www.springerlink.com/content/uw514r4j6323x763}, day = {1}, doi = {10.1007/s00422-008-0264-7}, issn = {1432-0770}, journal = {Biological cybernetics}, keywords = {aeif, and, fire, integrate, model, neuron, patterns}, month = {November}, number = {4-5}, pages = {335--347}, posted-at = {2008-11-18 11:43:40}, priority = {2}, title = {Firing patterns in the adaptive exponential integrate-and-fire model.}, url = {http://dx.doi.org/10.1007/s00422-008-0264-7}, volume = {99}, year = {2008} }

TY - JOUR ID - citeulike:3574105 L3 - citeulike-article-id:3574105 N2 - For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations. IS - 4-5 JF - Biological cybernetics SN - 1432-0770 EP - 347 TI - Firing patterns in the adaptive exponential integrate-and-fire model. VL - 99 SP - 335 KW - aeif KW - and KW - fire KW - integrate KW - model KW - neuron KW - patterns AU - Naud, Richard AU - Marcille, Nicolas AU - Clopath, Claudia AU - Gerstner, Wulfram PY - 2008/11/01/ UR - http://dx.doi.org/10.1007/s00422-008-0264-7 ER -