nips nips2005 nips2005-99 nips2005-99-reference knowledge-graph by maker-knowledge-mining
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Author: Renaud Jolivet, Alexander Rauch, Hans-rudolf Lüscher, Wulfram Gerstner
Abstract: Integrate-and-Fire-type models are usually criticized because of their simplicity. On the other hand, the Integrate-and-Fire model is the basis of most of the theoretical studies on spiking neuron models. Here, we develop a sequential procedure to quantitatively evaluate an equivalent Integrate-and-Fire-type model based on intracellular recordings of cortical pyramidal neurons. We find that the resulting effective model is sufficient to predict the spike train of the real pyramidal neuron with high accuracy. In in vivo-like regimes, predicted and recorded traces are almost indistinguishable and a significant part of the spikes can be predicted at the correct timing. Slow processes like spike-frequency adaptation are shown to be a key feature in this context since they are necessary for the model to connect between different driving regimes. 1
[1] Feng J. Neural Net. 14: 955–975, 2001.
[2] Maass W & Bishop C. Pulsed Neural Networks. MIT Press, Cambridge, 1998.
[3] Gerstner W & Kistler W. Spiking neurons models: single neurons, populations, plasticity. Cambridge Univ. Press, Cambridge, 2002.
[4] Rauch A, La Camera G, L¨ scher H, Senn W & Fusi S. J. Neurophysiol. 90: 1598–1612, 2003. u
[5] Keat J, Reinagel P, Reid R & Meister M. Neuron 30: 803-817, 2001.
[6] Mainen Z and Sejnowski T. Science 268: 1503–1506, 1995.
[7] Jolivet R, Lewis TJ & Gerstner W. J. Neurophysiol. 92: 959–976, 2004.
[8] Paninski L, Pillow J & Simoncelli E. Neural Comp. 16: 2533-2561, 2004.
[9] Brillinger D & Segundo J. Biol. Cyber. 35: 213-220, 1979.
[10] Benda J & Herz A. Neural Comp. 15: 2523-2564, 2003.
[11] La Camera G, Rauch A, L¨ scher H, Senn W & Fusi S. Neural Comp. 16: 2101-2124, 2004. u
[12] Jolivet R & Gerstner W. J. Physiol.-Paris 98: 442-451, 2004.
[13] Jolivet R, Rauch A, L¨ scher H & Gerstner W. Accepted in J. Comp. Neuro. u
[14] Wiener N. Nonlinear problems in random theory. MIT Press, Cambridge, 1958.
[15] Roth A & H¨ usser M. J. Physiol. 535: 445-472, 2001. a
[16] Kistler W, Gerstner W & van Hemmen J. Neural Comp. 9: 1015-1045, 1997.
[17] Jolivet R (2005). Effective minimal threshold models of neuronal activity. PhD thesis, EPFL, Lausanne.
[18] Arcas B & Fairhall A. Neural Comp. 15: 1789-1807, 2003.
[19] Brillinger D. Ann. Biomed. Engineer. 16: 3-16, 1988.
[20] Arcas B, Fairhall A & Bialek W. Neural Comp. 15: 1715-1749, 2003.
[21] Izhikevich E. IEEE Trans. Neural Net. 14: 1569-1572, 2003.
[22] Paninski L, Pillow J & Simoncelli E. Neurocomp. 65-66: 379-385, 2005.
[23] Robinson H & Kawai N. J. Neurosci. Meth. 49: 157-165, 1993.
[24] Arieli A, Sterkin A, Grinvald A & Aertsen A. Science 273: 1868–1871, 1996.
[25] De Weese M & Zador A. J. Neurosci. 23: 7940–7949, 2003.
[26] Stevens C & Zador A. In Proc. of the 5th Joint Symp. on Neural Comp., Inst. for Neural Comp., La Jolla, 1998.
[27] Destexhe A, Rudolph M & Par´ D. Nat. Rev. Neurosci. 4: 739-751, 2003. e
[28] Fourcaud-Trocm´ N, Hansel D, van Vreeswijk C & Brunel N. J. Neurosci. 23: 11628-11640, e 2003.