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On the Complexity of Logic-Dynamics in Brain

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Complexity and Diversity
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Abstract

The complexity theory of interactions among functional levels in brain is developed. In particular, a possible interplay between the logical process and the sensory information processings is highlighted. In this respect, we deal with the transformation between a logical statement and a dynamical system, in relation with dynamics of neurons or neural assemblies. Both internal and external views for the threshold or the switching mechanism of neuron is discussed. An external view is generally represented by dynamical systems, which is assured here by the plausibility of conventional population dynamics. The internal view in the present context is assured by the existence of logical process of macromolecules in the pre- and/or post-synaptic membranes of neuron. Thus the internal view provides logic-based dynamics. There always exist two interpretations for the logic-based dynamics, which lead internal and external dynamics, respectively. The internal dynamics brings about the threshold-related characteristics of neuron, clue to its chaotic behaviors, whereas the external one provides a periodic behavior only. With this internal theory, we develop the hermeneutic theory for interfacial dynamics of different levels of neural assemblies, and for the notion of stability of self-description.

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References

  1. I. Tsuda and K. Tadaki, A Logic-Based Dynamical Theory for A Genesis of Biological Threshold, Biosystems (in press, 1997).

    Google Scholar 

  2. K. Matsuno, Protobiology: Physical Basis of Biology, CRC press, Boca Raton, Florida, 1989.

    Google Scholar 

  3. W. J. Freeman, Societies of Brains — A Study in The Neuroscience of Love and Hate, Lawrence Erlbaum Associates, Inc., Hillsdale, 1995.

    Google Scholar 

  4. G. Boole, An Investigation of The Laws of Thought, Dover Publications, Inc., New York, 1854.

    Google Scholar 

  5. I. Tsuda, A Hermeneutic Process of The Brain, Progress of Theoretical Physics, Supplement, Vol. 79, 1984, pp. 241–259.

    Article  ADS  Google Scholar 

  6. I. Tsuda, Chaotic Itinerancy as A Dynamical Basis of Hermeneutics in Brain and Mind, World Futures, Vol. 32, 1991, pp. 167–185.

    Article  Google Scholar 

  7. C. Murakami and K. Tomita, Giant Transitory Excitation — A Thermokinetic Model, Journal of Theoretical Biology, Vol. 79, 1979, pp. 203–222.

    Article  MathSciNet  Google Scholar 

  8. A. L. Hodgkin and A. F. Huxley, A Quantitative Description of Membrane Current and Its Application to Conduction and Excitation in Nerve, Journal of Physiology, Vol. 117. 1952, pp. 500–544.

    Google Scholar 

  9. R. Fitz Hugh, Impulses and Physiological States in Theoretical Models of Nerve Membrane, Biophysical Journal, Vol. 1, 1961, pp. 445–466.

    Article  ADS  Google Scholar 

  10. R. Fitz Hugh, Mathematical Models of Excitation and Propagation in Nerve, in Biological Engineering, ed. H. P. Schwan, McGraw-Hill, New York, 1969, pp. 1–85.

    Google Scholar 

  11. J. Nagumo, S. Arimoto, and S. Yoshizawa, An Active Pulse Transmission Line Stimulating Nerve Axon, Proc. Institute of Radio Engineering, Vol. 50, 1962, pp. 2061–2070.

    Google Scholar 

  12. N. Reseller, Many-Valued Logic, McGraw-Hill, New York, 1969.

    Google Scholar 

  13. L. A. Zadeh, Fuzzy Logic and Approximate Reasoning, Synthese, Vol. 30, 1975, pp. 407–428.

    Article  MATH  Google Scholar 

  14. P. Grim, Self-Reference and Chaos in Fuzzy Logic, IEEE Transaction on Fuzzy Systems, Vol. 1, 1993, pp. 237–253.

    Article  Google Scholar 

  15. J. L. Kaplan and J. A. Yorke, Chaotic Behavior of Multidimensional Difference Equations, Lecture Notes in Mathematics, Vol. 730, 1979, pp. 204–227.

    Article  MathSciNet  Google Scholar 

  16. C. Grebogi, E. Ott, S. Pelikan, and J. A. Yorke, Starange Attractors That Are Not Chaotic, Physica D, Vol 13, 1984, pp. 261–268.

    Article  MathSciNet  ADS  MATH  Google Scholar 

  17. O. E. Rössler, R. Wais, and R. Rössler, Singular-Continuous Weierstrass Function Attractors, In Proc. 2nd International Conference on Fuzzy Logic and Neural Networks, Fuzzy Logic Systems Institute, lizuka, Japan, 1992, pp. 909–912.

    Google Scholar 

  18. O. E. Rössler, J. L. Hudson, C. Knudsen and I. Tsuda, Nowhere-Differentiable Attractors, International Journal of Intelligent Systems, Vol. 10, 1995, pp. 15–23.

    Article  Google Scholar 

  19. O. E. Rössler and J. L. Hudson, A “Superfat” Attractor with A Singular-Continuous 2-D Weierstrass Function in A Cross Section, Zeitschrift für Naturforshung, Vol. 48a, pp. 673–678.

    Google Scholar 

  20. I. Tsuda, A New Type of Self-Organization Associated with Chaotic Dynamics in Neural Networks, International Journal of Neural Systems, Vol. 7, 1996, pp.451–459.

    Article  Google Scholar 

  21. L. Kay, K. Shimoide and W. J. Freeman, Comparison of EEG Time Series from Rat Olfactory System with Model Composed of Nonlinear Coupled Oscillators, International Journal of Bifurcation and Chaos, Vol. 5, pp. 849–858.

    Google Scholar 

  22. K. Ikeda, K. Otsuka and K. Matsumoto, Maxwell-Bloch Turbulence, Progress of Theoretical Physics, Supplement, Vol.99, 1989, pp. 295–327.

    Article  MathSciNet  ADS  Google Scholar 

  23. K. Kaneko, Clustering, Coding, Switching, Hierarchical Ordering, and Control in Network of Chaotic Elements, Physica D, Vol. 41, 1990, pp. 137–172.

    Article  MathSciNet  ADS  MATH  Google Scholar 

  24. I. Tsuda, Can Stochastic Renewal of Maps Be A Model for Cerebral Cortex? Physica D, Vol 75, 1994, pp. 165–178.

    Article  ADS  MATH  Google Scholar 

  25. I. Tsuda, Chaotic Neural Networks and Thesaurus, Neurocomputers and Attention I, eds., A. V. Holden and V. L Kryukov, Manchester University Press, Manchester, 1991, pp. 405–424.

    Google Scholar 

  26. I. Tsuda, Dynamic Link of Memories—Chaotic Memory Map in Nonequilibrium Neural Networks, Neural Networks, Vol. 5, 1992, pp. 313–326.

    Article  MathSciNet  Google Scholar 

  27. S. Nara and P. Davis, Chaotic Wandering and Search in A Cycle-Memory Neural Network, Progress of Theoretical Physics, Vol. 88, 1992, pp. 845–855.

    Article  ADS  Google Scholar 

  28. S. Nara, P. Davis, M. Kawachi and H. Totsuji, Chaotic Memory Dynamics in A Recurrent Neural Networks with Cycle Memories Embedded by Pseudo-Inverse Method, International Journal of Bifurcation and Chaos, Vol. 5, 1995, pp. 1205–1212.

    Article  MATH  Google Scholar 

  29. W. J. Freeman, Neural Mechanisms Underlying Destabilization of Cortex by Sensory Input, Physica D, Vol. 75, 1994, pp. 151–164.

    Article  ADS  MATH  Google Scholar 

  30. M. Adachi and K. Aihara, Association Dynamics in a Chaotic Neural Network, Neural Networks, (in press, 1997).

    Google Scholar 

  31. H. Okuda and I. Tsuda, A Coupled Chaotic System with Different Time Scales: Possible Implications of Observations by Dynamical Systems, International Journal of Bifurcation and Chaos, Vol. 4, 1994, pp.1011–1022.

    Article  MATH  Google Scholar 

  32. H. Dinse, A Temporal Structure of Cortical Information Processing, Concepts in Neuroscience, Vol. 1, 1990, pp. 199–238.

    Google Scholar 

  33. J. J. Eggermont, A. M. H. J. Aertsen, D. J. Hermes and P. I. M. Johannesma, Spectro-Temporal Characterization of Auditory Neurons: Redundant or Necessary? Hearing Research, Vol. 5, 1981, pp. 109–121.

    Article  Google Scholar 

  34. M. Tsukada, a private communication for his experimental findings in late 1970s on dynamic receptive field in cat retinal ganglion cells.

    Google Scholar 

  35. M. Heideggar, Sein und Zeit, Tübingen, 1927.

    Google Scholar 

  36. H. G. Gadamer, Philosophical Hermeneutics, translated and edited by D. E. Linge, University of California Press, 1976.

    Google Scholar 

  37. I. Tsuda, E. Korner and H. Shimizu, Memory Dynamics in Asynchronous Neural Networks, Progress of Theoretical Physics, Vol.78, 1987, pp.51–71.

    Article  ADS  Google Scholar 

  38. M. Tsukada, Theoretical Model of The Hippocampal-Cortical Memory System Motivated by Physiological Functions in The Hippocampus, Cybernetics and Systems: An International Journal, Vol. 25, 1994, pp.189–206.

    Article  MATH  Google Scholar 

  39. M. Tsukada, T. Aihara, M. Mizuno, H. Kato, and K. Ito, Temporal Pattern Sensitivity of Long-Term Potentiation in Hippocampal CAl Neurons, Biological Cybernetics, Vol. 70, 1994, pp.495–503.

    Article  Google Scholar 

  40. Y. Miyashita, Inferior Temporal Cortex: Where Visual Perception Meets Memory, Annual Review of Neuro science. Vol. 16, 1993, pp. 245–263.

    Article  Google Scholar 

  41. Y.-P. Gunji, Autonomous Life as The Proof of Incompleteness and Lawvere’s Theorem of Fixed Point, Applied Mathematics and Computation, Vol. 61, 1994, pp. 231–267.

    Article  MathSciNet  MATH  Google Scholar 

  42. Y.-P. Gunji, S. Toyoda and M. Migita, Tree and Loop as Moments for Measurement, Biosystems, Vol. 38, 1996, pp. 127–133.

    Article  Google Scholar 

  43. I. Tsuda, deus ex machina-Towards the Brain Theory from Chaos Theory (in Japanese), System and Control: Transaction of Japan Society of System Engineering, Vol. 31, 1987, pp. 180–188.

    Google Scholar 

  44. I. Tsuda, Kaosu-teki Noukan (Chaos Viewpoint of Brain)(m.Japanese), Science-sha, Publ., Inc., Tokyo, 1990.

    Google Scholar 

  45. K. Kaneko and I. Tsuda, Fukuzatsukei no Kaosu-teki Sinario (Chaos Scenarios of Complex Systems)(m Japanese), Asakura-shoten, Publ., Inc., Tokyo, 1996.

    Google Scholar 

  46. S. Smale, Differentiable Dynamical Systems, Bidletin of American Mathematical Soceity. Vol. 73, 1967, pp. 747–817.

    Article  MathSciNet  MATH  Google Scholar 

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© 1997 Springer-Verlag Tokyo

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Tsuda, I. (1997). On the Complexity of Logic-Dynamics in Brain. In: Nakamura, E.R., Kudo, K., Yamakawa, O., Tamagawa, Y. (eds) Complexity and Diversity. Springer, Tokyo. https://doi.org/10.1007/978-4-431-66862-6_4

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  • DOI: https://doi.org/10.1007/978-4-431-66862-6_4

  • Publisher Name: Springer, Tokyo

  • Print ISBN: 978-4-431-66864-0

  • Online ISBN: 978-4-431-66862-6

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