Channel noise in excitable neuronal membranes

Advances in Neural Information Processing Systems

Volumn , Issue , 2000, Pages 143-149

  Manwani, Amit ^a   Steinmetz, Peter N ^a   Koch, Christof ^a  

^a CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; INTELLIGENT SYSTEMS; MEMBRANES; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; THRESHOLD VOLTAGE;

CHANNEL KINETICS; CRITICAL DETERMINANT; MEMBRANE VOLTAGE; MONTE-CARLO SIMULATIONS; NEURAL INFORMATION PROCESSING; NEURONAL MEMBRANES; STOCHASTIC FLUCTUATION; VOLTAGE GATED ION CHANNELS;

NEURONS;

EID: 84898997211     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. DeFelice L.J. (1981). Introduction to Membrane Noise. Plenum Press: New York, New York.
2. Strassberg A.F. & DeFelice L.J. (1993). Limitations of the Hodgkin-Huxley formalism: effect of single channel kinetics on transmembrane voltage dynamics. Neural Computation, 5:843-855.
3. Chow C. & White J. (1996). Spontaneous action potentials due to channel fluctuations. Biophy. J., 71:3013-3021.
4. Schneidman E., Freedman B. & Segev I. (1998). Ion-channel stochasticity may be critical in determining the reliability and precision of spike timing. Neural Computation, 10:1679-1703.
5. DeFelice L.J. & Isaac A. (1992). Chaotic states in a random world. J. Stat. Phys., 70:339-352.
6. White J.A., Budde T. & Kay A.R. (1995). A bifurcation analysis of neuronal subthreshold oscillations. Biophy. J., 69:1203-1217.
7. Manwani A. & Koch C. (1998). Synaptic transmission: An information-theoretic perspective. In: Jordan M., Kearns M.S. & Solla S.A., eds., Advances in Neural Information Processing Systems 10. pp 201-207. MIT Press: Cambridge, Massachusetts.
8. Manwani A. & Koch C. (1999). Detecting and estimating signals in noisy cable structures: I. Neuronal noise sources. Neural Computation. In press.
9. Manwani A. & Koch C. (1999). Detecting and estimating signals in noisy cable structures: II. Information-theoretic analysis. Neural Computation. In press.
10. Mainen Z.F. & Sejnowski T.J. (1995). Reliability of spike timing in neocortical neurons. Science, 268:1503-1506.
11. Johnston D. & Wu S.M. (1995). Foundations of Cellular Neurophysiology. MIT Press: Cambridge, Massachusetts.
12. Hodgkin A.L. & Huxley A.F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. (London), 117:500-544.
13. Skaugen E. & Wallce L. (1979). Firing behavior in a stochastic nerve membrane model based upon the Hodgkin-Huxley equations. Acta Physiol. Scand., 107:343-363.
14. Press W.H., Teukolsky S.A., Vetterling W.T. & Flannery B.P. (1992). Numerical Recipes in C: The Art of Scientific Computing. Cambridge University Press, second edn.
15. Mauro A., Conti F, Dodge F. & Schor R. (1970). Subthreshold behavior and phenomenological impedance of the squid giant axon. J Gen. Physiol., 55:497-523.
16. Koch C. (1984). Cable theory in neurons with active, linearized membranes. Biol. Cybern., 50:15-33.
17. Sabah N.H. & Leibovic K.N. (1972). The effect of membrane parameters on the properties of the nerve impulse. Biophys. J., 12:1132-44.
18. Shadlen M.N. & Newsome W.T. (1998). The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. J. NeuroscL, 18:3870-3896.
19. P. N. Steinmetz A. Manwani M.L & Koch C. (1999). Sub-threshold voltage noise due to channel fluctuations in active neuronal membranes. In preparation.