On the use of Bayesian methods for evaluating compartmental neural models

Journal of Computational Neuroscience

Volumn 5, Issue 3, 1998, Pages 285-314

  Baldi, Pierre ^a,b   Vanier, Michael C ^b   Bower, James M ^b  

^a Net ID Inc ^*  (United States)

^b CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Bayesian; Compartmental model; Model comparison

Indexed keywords

NEUROLOGY;

BAYESIAN; BAYESIAN APPROACHES; BAYESIAN METHODS; COMPARTMENTAL MODELLING; COMPUTATIONAL MODELLING; DEGREE OF CONFIDENCE; MODEL INFERENCE; MODEL SELECTION; MODELS COMPARISONS; NEURAL MODELLING;

BAYESIAN NETWORKS;

ARTICLE; BAYES THEOREM; CELL MEMBRANE POTENTIAL; COMPARTMENT MODEL; METHODOLOGY; NEUROANATOMY; NEUROPHYSIOLOGY; NEUROSCIENCE; PRIORITY JOURNAL; PROBABILITY; PYRAMIDAL NERVE CELL;

EID: 0031747899     PISSN: 09295313     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1008887028637     Document Type: Article

References (45)

1. Anderson CH (1995) Unifying perspectives on neuronal codes and processing. In Proceedings of the Nineteenth International Workshop on Condensed Matter Theories. Caracas, Venezuela.
2. Baldi P (1997). Probabilistic models of neuronal spike trains. In M Gori, ed. Lecture Notes in Artificial Intelligence: Adaptive Processing of Temporal Information. Springer Verlag, New York.
3. Baldi P, Brunak S (1998) Bioinformatics: The Machine Learning Approach. MIT Press, Cambridge, MA.
4. Barnett V (1982) Comparative Statistical Inference. Wiley, New York.
5. Berger JO (1985) Statistical Decision Theory and Bayesian Analysis. Springer Verlag, New York.
6. Besag J, Green P, Higdon D, Mengersen K (1995) Bayesian computation and stochastic systems. Statistical Science 10(1):3-66.
7. Bower JM (1992) Modeling the nervous system. Trends in Neurosci. 15(11):411-412.
8. Bower JM (1995) Reverse engineering the nervous system: An in vivo, in vitro, and in computo, approach to understanding the mammalian olfactory system. In: S Zornetzer, J Davis, C Lau, eds. An Introduction to Neural and Electronic Networks, 2nd ed. Academic Press, San Diego.
9. Bower JM (1996) What will save neuroscience? Neuroimage 4(3):S29-S33.
10. Bower JM, ed. (1997) Computational Neuroscience: Trends in Research 1997. Plenum Press, New York.
11. Bower JM, Beeman D (1995) The Book of Genesis. Springer Verlag, New York.
12. Bush PC, Sejnowski TJ (1993) Reduced compartmental models of neocortical pyramidal cells. J. Neurosci. Meth. 46:159-166.
13. Cheeseman P (1988) An inquiry into computer understanding. Comput. Intelligence 4:51-142.
14. Cox RT (1964) Probability, frequency and reasonable expectation. Am. J. Physics 14:1-13.
15. Dayan P, Hinton GE, Neal RM, Zemel RS (1995) The Helmholtz machine. Neural Comput. 7(5):889-904.
16. De Schutter E, Bower JM (1994a) An active membrane model of the cerebellar Purkinje cell. i. Simulation of current clamps in slice. J. Neurophysiol. 71:375-400.
17. De Schutter E, Bower JM (1994b) An active membrane model of the cerebellar Purkinje cell. ii. Simulation of synaptic responses. J. Neurophysiol. 71:401-419.
18. Gregory PC, Loredo TJ (1992) A new method for the detection of a periodic signal of unknown shape and period. Astrophysical J. 398:146-168.
19. Gull SF (1989) Developments in maximum entropy data analysis. In: J Skilling, ed. Maximum Entropy and Bayesian Methods. Kluwer. Dordrecht, pp. 53-71.
20. Hasselmo MH, Bower JM (1992) Cholinergic suppression specific to intrinsic not afferent fiber synapses in rat piriform (olfactory) cortex. J. Neurophysiol. 67(5):1222-1229.
21. Hille B (1992) Ionic Channels of Excitable Membranes, 2nd ed. Sinauer Associates, Sunderland, MA.
22. Hoel PG, Port SC, Stone CJ (1971) Introduction to Probability Theory. Houghton Mifflin, Boston.
23. Jaeger D, De Schutter E, Bower JM (1997) The role of synaptic and voltage-gated currents in the control of Purkinje-cell spiking: A modeling study. J. Neurosci. 17(1):91-106.
24. Jaynes ET (1986) Bayesian methods: General background. In: JH Justice, cd. Maximum Entropy and Bayesian Methods in Statistics. Cambridge University Press, Cambridge, pp. 1-25.
25. Jaynes ET (1995) Probability Theory: The Logic of Science. (in preparation)
26. Jeffreys WH, Berger JO (1992) Ockham's razor and Bayesian analysis. Am. Scientist 80:64-72.
27. Koch C, Segev I (1989) Methods in Neuronal Modeling. MIT Press, Cambridge, MA.
28. Koch C, Segev I (1997) Methods in Neuronal Modeling, 2nd ed. MIT Press, Cambridge, MA.
29. Lewicki MS (1994) Bayesian modeling and classification of neural signals. Neural Comput. 6(5):1005-1030.
30. MacKay DJC (1992a) Bayesian interpolation. Neural Comput. 4(3):415-447.
31. MacKay DJC (1992b) A practical Bayesian framework for back-propagation networks. Neural Comput. 4(3):448-472.
32. Mainen ZF, Sejnowski TJ (1995) Reliability of spike timing in neocortical neurons. Science 268:1503-1506.
33. McCormick DA, Connors BW, Lighthall JW, Prince DA (1985) Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex. J. Neurophysiol. 54(4):782-806.
34. Neal RM (1993) Probabilistic inference using Markov chain Monte Carlo methods. Technical Report, Department of Computer Science, University of Toronto, Canada.
35. Neal RM (1995) Bayesian learning for neural networks. Ph.D. Thesis, Department of Computer Science, University of Toronto, Canada.
36. Press SJ (1989) Bayesian Statistics: Principles, Models, and Applications. John Wiley, New York.
37. Press WH, Teukolsky SA, Vetterling WT, Flannery BP (1992) Numerical Recipes in C, 2nd ed. Cambridge University Press, New York.
38. Protopapas D, Bower JM (1997) Noradrenaline increases information without changing encoding in cortical neurons, (in preparation)
39. Shadlen M, Newsome W (1994) Noise, neural codes and cortical organization. Current Opinion in Neurobiol. 4:569-579.
40. Smith AFM (1991) Bayesian computational methods. Phil. Trans. Roy. Soc. Lond. A 337:369-386.
41. Smith AF, Roberts GO (1993) Bayesian computation via the Gibbs sampler and related Markov Chain Monte Carlo methods. J. Roy. Stat. Soc. 55(1):3-23.
42. Softky WR, Koch C (1993) The highly irregular firing of cortical-cells is inconsistent with temporal integration of random epsps. J. Neurosci. 13(1):334-350.
43. Traub RD, Wong RKS, Miles R, Michelson H (1991) A model of a CA3 hippocampal pyramidal neuron incorporating voltage-clamp data on intrinsic conductances. J. Neurophysiol. 66(2):635-650.
44. Vanier MC, Bower JM (1995) A comparison of automated parameter-searching methods for neural models. In: JM Bower, ed. Proceedings of the 1995 Computational Neuroscience Conference (CNS*95), Monterey (CA). Academic Press, San Diego, pp. 477-482.
45. Vanier MC, Bower JM (1997) A comparative survey of automated parameter-search methods for compartmental neural models. Submitted to Journal of Computational Neuroscience. In revision.