000140445 001__ 140445
000140445 005__ 20180913055401.0
000140445 0247_ $$2doi$$a10.1007/s00422-008-0259-4
000140445 022__ $$a0340-1200
000140445 02470 $$2ISI$$a000260938100010
000140445 037__ $$aARTICLE
000140445 245__ $$aExtracting non-linear integrate-and-fire models from experimental data using dynamic I – V curves 
000140445 269__ $$a2008
000140445 260__ $$bSpringer Verlag$$c2008
000140445 336__ $$aJournal Articles
000140445 520__ $$aThe dynamic I–V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctuating synaptic drive. The resulting history-dependent, transmembrane current is then projected onto a one-dimensional current–voltage relation that provides the basis for a tractable non-linear integrate-and-fire model. An attractive feature of the method is that it can be used in spike-triggered mode to quantify the distinct patterns of post-spike refractoriness seen in different classes of cortical neuron. The method is first illustrated using a conductance-based model and is then applied experimentally to generate reduced models of cortical layer-5 pyramidal cells and interneurons, in injected-current and injected- conductance protocols. The resulting low-dimensional neuron models—of the refractory exponential integrate-and-fire type—provide highly accurate predictions for spike-times. The method therefore provides a useful tool for the construction of tractable models and rapid experimental classification of cortical neurons.
000140445 6531_ $$aIV curve
000140445 6531_ $$aExponential integrate-and-fire
000140445 6531_ $$aRefractoriness
000140445 700__ $$0240327$$aBadel, Laurent$$g119183
000140445 700__ $$0240431$$aLefort, Sandrine$$g161841
000140445 700__ $$aBerger, Thomas K.
000140445 700__ $$0243169$$aPetersen, Carl C. H.$$g157467
000140445 700__ $$0240007$$aGerstner, Wulfram$$g111732
000140445 700__ $$aRichardson, Magnus J. E.
000140445 773__ $$j99$$k4-5$$q361-370$$tBiological Cybernetics
000140445 8564_ $$uhttp://www.springerlink.com/content/l231321784j17157/?p=6640d593673e468dada7c0085c2b2d54&pi=9$$zURL
000140445 8564_ $$s548148$$uhttps://infoscience.epfl.ch/record/140445/files/Badel08.pdf$$yPublisher's version$$zn/a
000140445 909C0 $$0252006$$pLCN
000140445 909C0 $$0252149$$pLSENS$$xU10837
000140445 909CO $$ooai:infoscience.tind.io:140445$$pSV$$pIC$$particle
000140445 917Z8 $$x180892
000140445 937__ $$aLCN-ARTICLE-2009-007
000140445 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000140445 980__ $$aARTICLE