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AFSS International Conference on Fuzzy Systems

AFSS 2002: Advances in Soft Computing — AFSS 2002 pp 191–203Cite as

A Control Analysis of Neuronal Information Processing: A Study of Electrophysiological Experimentation and Non-equilibrium Information Theory

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2275))

Abstract

A model of information transmission across a neuron is delineated in terms of source (stimulus)-encoder-channel-decoder-behaviour (response). From cybernetic analysis of experimental data, we perform frequency/time domain and stability analyses and obtain the Bode, Nichols and Nyquist plots, Root locus plane, transfer function and response equation, all confirmed by data. We consider a new paradigm of information theory based on nonequilibrium dynamics of fluc-tuation, organization and information (Nicolis- Prigogine), that is the counterpart of Shannon-Boltzmann approach to information-entropy based on equilibrial dyna-mics. The Prigogine theorem of minimum entropy production and Rosen’s prin-ciple of optimum design were observed to characterize neural transmission in a particular test neuron operating near optimal sensitivity regime. Using Nyquist theorem and generalized temperature concept, we compute a non-equilibrial ent-ropy production and neurodynamic temperature equivalent during neural information processing. A trans-information/temperature plot implies an order-disorder Bose transition and zero neurodynamic entropy (near 00N) as informational analog of third law of thermodynamics (near 00K). Neural applications are explored.

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References

  1. Theunissen, F., et al:Information theoretic analysis, J. Neurophysiol. 75 (1996) 1345–1364

    Google Scholar 

  2. Clague, H., et al: Effects of adaptation on neural coding, J. Neurophysiol. 77 (1997) 207–220

    Article  Google Scholar 

  3. Dutta Majumder, D.: Cybernetics and systems: A unitary science, Kybernetes 8 (1979) 7–15

    Article  Google Scholar 

  4. Roy, P., Majumder, D.: A biothermodynamic study, J. Intelligent Systems 10 (2000) 57–104

    Google Scholar 

  5. Prigogine, I.: Nobel Lecture: Chemistry— 1977, Nobel Foundation, Stockholm (1978)

    Google Scholar 

  6. Nicolis, G., Prigogine, I.: Self-organization in non-equilibrium systems, Wiley, N.Y. (1977)

    Google Scholar 

  7. Zotin, A.: Thermodynamic bases of biological processes, W. de Gruyter, N. Y. (1990)

    Google Scholar 

  8. Little, W. Persistent states in the brain, Mathematical Biosciences, 19 (1974) 101–120

    Article  MATH  Google Scholar 

  9. Hofkirchner, H: The quest for unified theory of information, Gordon-Breach, London (1997)

    Google Scholar 

  10. Nicolis, J.: Information processing, In: Basar, E.: Synergetics of brain, Springer, NY (1983)

    Google Scholar 

  11. Avramescu, A.: Coherent informational energy, J. Documentation 36 (1980) 293–312

    Article  Google Scholar 

  12. Baddeley, R., Hancock, P.: Information theory and the brain, C.U.P., Cambridge (2000)

    Google Scholar 

  13. Stark, L: Neurological control systems analysis: Bio-engineering, Plenum, N.Y. (1978)

    Google Scholar 

  14. Pippard, Sir B.: Elements of Classical Thermodynamics, C.U.P., Cambridge (1991)

    Google Scholar 

  15. Pringle, J, Wilson, V: Response to harmonic stimulus, J. Exp. Biol. 29 (1952) 220–234

    Google Scholar 

  16. Mcfarland, D.: Feedback mechanisms in animal behaviour, Academic Press, London (1981)

    Google Scholar 

  17. Einstein, A.: Die molukular-kinetischen theorie, Annalen der Physik 17 (1905) 549–560

    Google Scholar 

  18. Dorf, R.: The electrical engineering handbook, CRC Press, Boca Raton (1993)

    MATH  Google Scholar 

  19. Halliday, D., Resnick, R.: Physics— Part I, Toppan-Wiley, Tokyo (1983)

    Google Scholar 

  20. Buckingham, M.: Noise in electronic devices and systems, Halstead Press, N. Y. (1995)

    Google Scholar 

  21. Herdan G.: The advanced theory of choice in language, Mouton, The Hague (1989)

    Google Scholar 

  22. Brillouin, L.: Science and information theory, Academic Press, New York (1966)

    Google Scholar 

  23. Mandelbrot, M: Thermostatistics, In: Cherry C: Information theory, Butterworths, NY (1976)

    Google Scholar 

  24. Flory, P.: Nobel Lecture: Chemistry— 1974, Nobel Foundation, Stockholm (1975)

    Google Scholar 

  25. Sarpeshkar, R.: Analog vs. digital neurobiology, Neural Computation 10 (1998) 1601–38

    Article  Google Scholar 

  26. Sataric, M.: Energy transfer mechanism involving soliton, Nanobiology 1 (1992) 445–56

    Google Scholar 

  27. Rasmussen, S.: Computational connectionism in neurones, Physica-D 42 (1990) 428–49

    Article  Google Scholar 

  28. Frohlich, H., Kremer, F: Coherent excitations in biological systems, Springer, Berlin (1983)

    Google Scholar 

  29. Davidov, A.: Quantum physics and biology, Springer, Berlin (1986)

    Google Scholar 

  30. Agrawal, G: High capacity Raman soliton systems, Optical Experiments, 9(2) (2001) 66–73

    Article  Google Scholar 

  31. Corney, J: Noise limit: Raman effect in soliton propagation, Opt.Comm.,140 (1997) 215–17

    Google Scholar 

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Author information

Authors and Affiliations

  1. Lishman Brain Unit, Maudsley Hospital, University of London, SE5 8AZ, London, UK

    Prasun K. Roy

  2. Centre for Computational Biology, Montana State University, MT-59717, Bozeman, USA

    John P. Miller

  3. Indian Statistical Institute,ECSU, 203 Barrackpore Trunk Road, 35, Calcutta, India

    Prasun K. Roy & D. Dutta Majumder

  4. Institute of Cybernetics Systems & Information Technology, 155 Asokgarh, 35, Calcutta, India

    D. Dutta Majumder

Authors
  1. Prasun K. Roy
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  2. John P. Miller
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  3. D. Dutta Majumder
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Editor information

Editors and Affiliations

  1. Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B.T. Road, 700108, Calcutta, India

    Nikhil R. Pal

  2. Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako, Japan

    Michio Sugeno

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© 2002 Springer-Verlag Berlin Heidelberg

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Roy, P.K., Miller, J.P., Majumder, D.D. (2002). A Control Analysis of Neuronal Information Processing: A Study of Electrophysiological Experimentation and Non-equilibrium Information Theory. In: Pal, N.R., Sugeno, M. (eds) Advances in Soft Computing — AFSS 2002. AFSS 2002. Lecture Notes in Computer Science(), vol 2275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45631-7_27

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  • DOI: https://doi.org/10.1007/3-540-45631-7_27

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43150-3

  • Online ISBN: 978-3-540-45631-5

  • eBook Packages: Springer Book Archive

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