Effect of stimulation on the input parameters of stochastic leaky integrate-and-fire neuronal model

Journal of Physiology Paris

Volumn 104, Issue 3-4, 2010, Pages 160-166

  Lansky, Petr ^a   Sanda, Pavel ^a   He, Jufang ^b  

^a INSTITUTE OF PHYSIOLOGY   (Czech Republic)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Estimation of parameters; Interspike interval; Intracellular recording; Ornstein Uhlenbeck

Indexed keywords

ACTION POTENTIAL; ANIMAL CELL; ARTICLE; CONTROLLED STUDY; GUINEA PIG; INTRACELLULAR RECORDING; LEAKY INTEGRATE AND FIRE NEURONAL MODEL; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MEMBRANE DEPOLARIZATION; MEMBRANE POTENTIAL; MEMBRANE STEADY POTENTIAL; NERVE CELL MEMBRANE; NERVE FUNCTION; NONHUMAN; ORNSTEIN UHLENBECK NEURONAL MODEL; SPIKE WAVE; STATISTICAL MODEL; STIMULUS RESPONSE;

ACOUSTIC STIMULATION; ACTION POTENTIALS; ANIMALS; ELECTROENCEPHALOGRAPHY; GUINEA PIGS; MEMBRANE POTENTIALS; MODELS, NEUROLOGICAL; NEURAL PATHWAYS; NEURONS; REACTION TIME; SIGNAL PROCESSING, COMPUTER-ASSISTED; STOCHASTIC PROCESSES; TIME FACTORS;

EID: 77952548905     PISSN: 09284257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jphysparis.2009.11.019     Document Type: Article

References (23)

1. Bibbona E., Lansky P., Sacerdote L., Sirovich R. Errors in estimation of the input signal for integrate-and-fire neuronal models. Physical Review E 2008, 78:011918.
2. Brunel N., van Rossum M. Lapicque's 1907 paper: from frogs to integrate-and-fire. Biological Cybernectics 2007, 97:1-3.
3. Burkitt A. A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input. Biological Cybernetics 2006, 95:1-19.
4. Clopath C., Jolivet R., Rauch A., Lüscher H., Gerstner W. Predicting neuronal activity with simple models of the threshold type: adaptive exponential integrate-and-fire model with two compartments. Neurocomputing 2007, 70:1668-1673.
5. Dayan P., Abbott L. Theoretical Neuroscience 2001, MIT Press, Cambridge, CA.
6. Ditlevsen S., Lansky P. Estimation of the input parameters in the Ornstein-Uhlenbeck neuronal model. Physical Review E 2005, 71:11907.
7. Ditlevsen S., Lansky P. Estimation of the input parameters in the Feller neuronal model. Physical Review E 2006, 73:61910.
8. Ditlevsen S., Lansky P. Parameters of stochastic diffusion processes estimated from observations of first-hitting times: application to the leaky integrate-and-fire neuronal model. Physical Review E 2007, 76:41906.
9. Feigin P. Maximum likelihood estimation for continuous-time stochastic processes. Advances in Applied Probability 1976, 8:712-736.
10. Gerstner W., Kistler W. Spiking Neuron Models 2002, Cambridge University Press, New York.
11. Hampel D., Lansky P. On the estimation of refractory period. Journal of Neuroscience Methods 2008, 171:288-295.
12. He J. Slow oscillation in non-lemniscal auditory thalamus. Journal of Neuroscience 2003, 23:8281-8290.
13. Inoue J., Sato S., Ricciardi L. On the parameter estimation for diffusion models of single neuron's activities. Biological Cybernetics 1995, 73:209-221.
14. Jolivet R., Rauch A., Luscher H., Gerstner W. Integrate-and-fire models with adaptation are good enough: predicting spike times under random current injection. Advances in Neural Information Processing Systems 2006, Vol. 18:595-602. MIT Press, Cambridge MA.
15. Koyama S., Kass R. Spike train probability models for stimulus-driven leaky integrate-and-fire neurons. Neural Computation 2008, 20:1776-1795.
16. Lansky P., Ditlevsen S. A review of the methods for signal estimation in stochastic diffusion leaky integrate-and-fire neuronal models. Biological Cybernetics 2008, 99:253-262.
17. Lansky P., Sacerdote L. The Ornstein-Uhlenbeck neuronal model with signal-dependent noise. Physics Letters A 2001, 285:132-140.
18. Lansky P., Sanda P., He J. The parameters of the stochastic leaky integrate-and-fire neuronal model. Journal of Computational Neuroscience 2006, 21:211-223.
19. Mullowney P., Iyengar S. Parameter estimation for a leaky integrate-and-fire neuronal model from ISI data. Journal of Computational Neuroscience 2008, 24:179-194.
20. Shinomoto S., Sakai Y., Funahashi S. The Ornstein-Uhlenbeck process does not reproduce spiking statistics of neurons in prefrontal cortex. Neural Computation 1999, 11:935-951.
21. Tuckwell H. Introduction to Theoretical Neurobiology 1988, Cambridge University Press, New York.
22. Xiong Y., Yu Y., Fujimoto K., Chan Y., He J. An in vivo intracellular study of auditory thalamic neurons. Thalamus and Related Systems 2006, 2:253-260.
23. Yu Y., Xiong Y., Chan Y., He J. Corticofugal gating of auditory information in the thalamus: an in vivo intracellular recording study. Journal of Neuroscience 2004, 24:3060-3069.