Adaptive exponential integrate-and-fire model as an effective description of neuronal activity

Journal of Neurophysiology

Volumn 94, Issue 5, 2005, Pages 3637-3642

  Brette, Romain ^a,b   Gerstner, Wulfram ^a  

^a EPFL   (Switzerland)

^b ECOLE NORMALE SUPÉRIEURE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ELECTROPHYSIOLOGY; IN VITRO STUDY; IN VIVO STUDY; MATHEMATICAL MODEL; NERVE CONDUCTION; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; SPIKE; SYNAPSE; THEORETICAL MODEL;

ACTION POTENTIALS; ADAPTATION, PHYSIOLOGICAL; ANIMALS; CELL MEMBRANE; COMPUTER SIMULATION; EXCITATORY POSTSYNAPTIC POTENTIALS; HUMANS; MEMBRANE POTENTIALS; MODELS, NEUROLOGICAL; NEURONAL PLASTICITY; SYNAPTIC TRANSMISSION;

EID: 27144498986     PISSN: 00223077     EISSN: None     Source Type: Journal    
DOI: 10.1152/jn.00686.2005     Document Type: Article

References (29)

1. Bower JM and Beeman D. The Book of GENESIS: Exploring Realistic Neural Models With the GEneral NEural Simulation System. New York: TELOS, Springer-Verlag, 1997.
2. Brette R and Guigon E. Reliability of spike timing is a general property of spiking model neurons. Neural Comput 15: 279-308, 2003.
3. Destexhe A, Contreras D, and Steriade M. Mechanisms underlying the synchronizing action of corticothalamic feedback through inhibition of thalamic relay cells. J Neurophysiol 79: 999-1016, 1998.
4. Destexhe A, Rudolph M, Fellous JM, and Sejnowski TJ. Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons. Neuroscience 107: 13-24, 2001.
5. Destexhe A, Rudolph M, and Pare D. The high-conductance state of neocortical neurons in vivo. Nat Rev Neurosci 4: 739-751, 2003.
6. Ermentrout B. Type I membranes, phase resetting curves, and synchrony. Neural Comput 8: 979-1001, 1996.
7. Fourcaud-Trocme N, Hansel D, van Vreeswijk C, and Brunei N. How spike generation mechanisms determine the neuronal response to fluctuating inputs. J Neurosci 23: 11628-11640, 2003.
8. Goldman MS, Golowasch J, Marder E, and Abbott LF. Global structure, robustness, and modulation of neuronal models. J Neurosci 21: 5229-5238, 2001.
9. Hille B. Ion Channels of Excitable Membranes. Sinauer Associates, Sunderland, MA, 2001.
10. Hines ML and Carnevale NT. The NEURON simulation environment. Neural Comput 9: 1179-1209, 1997.
11. Hodgkin A and Huxley A. A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 117: 500-544, 1952.
12. Izhikevich EM. Simple model of spiking neurons. IEEE Trans Neural Networks 14: 1569-1572, 2003.
13. Jolivet R, Lewis TJ, and Gerstner W. Generalized integrate-and-fire models of neuronal activity approximate spike trains of a detailed model to a high degree of accuracy. J Neurophysiol 92: 959-976, 2004.
14. Keat J, Reinagel P, Reid RC, and Meister M. Predicting every spike: a model for the responses of visual neurons. Neuron 30: 803-817, 2001.
15. Kistler WM, Gerstner W, and Leo van Hemmen J. Reduction of Hodgkin-Huxley equations to a single-variable threshold model. Neural Comput 9: 1015-1045, 1997.
16. Lapicque L. Recherches quantitatives sur l'excitation électrique des nerfs traitée comme une polarisation. J Physiol Pathol Gen 9: 620-635, 1907.
17. Latham PE, Richmond BJ, Nelson PG, and Nirenberg S. Intrinsic dynamics in neuronal networks. I. Theory. J Neurophysiol 83: 808-827, 2000.
18. Mainen Z and Sejnowski T. Reliability of spike timing in neocortical neurons. Science 268: 1503-1506, 1995.
19. McCormick DA, Wang Z, and Huguenard J. Neurotransmitter control of neocortical neuronal activity and excitability. Cereb Cortex 3: 387-398, 1993.
20. Paninski L, Pillow JW, and Simoncelli EP. Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model. Neural Comput 16: 2533-2561, 2004.
21. Pare D, Shink E, Gaudreau H, Destexhe A, and Lang EJ. Impact of spontaneous synaptic activity on the resting properties of cat neocortical pyramidal neurons in vivo. J Neurophysiol 79: 1450-1460, 1998.
22. Prinz AA, Billimoria CP, and Marder E. Alternative to hand-tuning conductance-based models: construction and analysis of databases of model neurons. J Neurophysiol 90: 3998-4015, 2003.
23. Richardson MJ, Brunei N, and Hakim V. From subthreshold to firing-rate resonance. J Neurophysiol 89: 2538-2554, 2003.
24. Roth A and Hausser M. Compartmental model of rat cerebellar Purkinje cells based on simultaneous somatic and dendritic patch-clamp recordings. J Physiol 535: 445-472, 2001.
25. Segev I, Fleshman JW, and Burke RE. Compartmental model of complex neurons. In: Methods in Neuronal Modeling, edited by Koch C and Segev I. Cambridge: MIT Press, 1989, p. 63-96.
26. Sharp AA, O'Neil MB, Abbott LF, and Marder E. The dynamic clamp: artificial conductances in biological neurons. Trends Neurosci 16: 389-394, 1993.
27. Stein RB. Some models of neuronal variability. Biophys J 7: 37-68, 1967.
28. Steriade M. Neocortical cell classes are flexible entities. Nat Rev Neurosci 5: 121-134, 2004.
29. Tuckwell H. Introduction to Theoretical Neurobiology, Vol. 1: Linear Cable Theory and Dendritic Structure. Cambridge: Cambridge University Press, 1988.