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Quantum Effects in Synaptic Neurons and Their Networks in the Brain

Received: 2 January 2017    Accepted: 10 January 2017    Published: 10 February 2017
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Abstract

This article describes small neurotransmitters as particles of a spinless quantum field. That is, the particles are Bosons that e.g. can occupy equal energy levels. In addition, we consider the particles of the presynaptic region before exocytosis occur as elements of a grand canonical ensemble that is in a thermodynamic equilibrium. Thus, the particles obey the Bose-Einstein statistics, which also determines the corresponding information entropy and the corresponding density matrix. When the release of neurotransmitters occur, the equilibrium collapses and the Bose-Einstein distribution transfers to the Poisson distribution. Moreover, the particles transmit as wave packets, with quantized energies and momenta, through the chemical synapses, where we also describe the effects of the quantum fluctuations. We mark this symmetry braking process that corresponds to a non-equilibrium phase transition by a threshold, which mainly depends on the mean of the particles number, with defined quanta. We model the connections of synaptic neurons of a population to a network by Hamiltonians that include both Bosons and Fermions and their interactions. Bosons are the carriers of messages (information) and Fermions are the switches, which forward these messages, with a modified content. The effects we observe in such a neural circuitry reveals a strong dependence of the solutions from the initial values and, more relevant, solutions with chaotic behavior exist. These circuitry-based ramifications together with possible internal malfunctioning of particular neurons (e.g. intermitted flow) of the network cause a sustainable reduction of the synaptic plasticity.

Published in European Journal of Biophysics (Volume 4, Issue 6)
DOI 10.11648/j.ejb.20160406.11
Page(s) 47-66
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Quantum Field of Bosons, Thermodynamics, Symmetry Braking, Quantum Fluctuations, Neural Quantum Circuitry

References
[1] Albers B, Johnson A, Lewis J, Raff M, Roberts K, Walter P (2008). Molecular Biology of the Cell. Fifth edition, New York, Garland Science.
[2] Bear F B, Connors B W, Paradiso M A, (2015). Neuroscience: Exploring the Brain. Fourth edition, Philadelphia, Wolters Kluwer.
[3] Beck F, Eccles J (2003). Quantum Processes in the Brain. Neural Basis of consciousness. Proc Natl. Acad. Sci. USA, Vol. 89, 11357-11361, December 1992 (49).
[4] Bjorken J. and Drell S, (1965). Relativistic Quantum Fields. New York, McGraw–Hill.
[5] Dyan P and Abbott L F (2005). Theoretical Neuroscience. Second edition, Cambridge, The MIT Press.
[6] Fermi E (1936). Thermodynamics. New York, Dover Publications, INC.
[7] Feynman R P and Hibbs A R (2005). Quantum Mechanics and Path Integrals. Emended edition, New York, Mc Graw-Hill.
[8] Gerstner W and Kistler W. (2011). Spiking Neuron Models. Second edition, Cambridge, Cambridge University Press.
[9] Gerstner W, Kistler W, Naud R, and Paninski L (2014). Neural Dynamics: From Single Neurons to Networks and Models of Cognition. Cambridge, Cambridge University Press.
[10] Hagan Sc, Hameroff St, and Tuszynski J (2014). Quantum Computation in Brain Microtubules: Decoherence and biological Feasibility. Physical Review E 65.6 (2002): 061901.
[11] Guckenheimer J, Holmes Ph (2002). Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields. Heidelberg, Springer-Verlag.
[12] Haken H (1985). Light and Matter II. Amsterdam, North Holland.
[13] Haken H (2006). Information and Self-Organization. Third edition, Heidelberg, Springer.
[14] Haken H, Levi P (2012). Synergetic Agents–Classical and Quantum. From Multi-Robot Systems to Molecular Robotics. Weinheim, Wiley-VCH.
[15] Huelga S F, Plenio M B (2011). Quantum Dynamics of bio-molecular Systems in noisy Environments. Twenty-twoth Solvay Conference in Chemistry, Procedia Chemistry 00(2011), 1-10, www.sciencedirect.com.
[16] Haynie D T (2001). Biological Thermodynamics. Cambridge, Cambridge University Press.
[17] Job G and Herrmann F (2006). Chemical Potential–a quantity in search of recognition, Eur. J. Phys. 27, 353-371.
[18] Kandel E R, Schwartz J H, Jessel Th M, Editors (2012). Principles of Neural Science. Fourth edition, New York, McGraw-Hill.
[19] Kittel Ch (2005). Introduction to Solid State Physics. Eighth edition, New Jersey, John Wiley & Sons.
[20] Lambert N, Chen YN, Li CM, Chen GY, Nori F (2013). Quantum Biology. Nature Physics 9, 10-18, doi: 10.138/nphys2474.
[21] Levi P (2015). Molecular Quantum Robotics: Particle and Wave Solutions, illustrated by “Leg-over-Leg” Walking along Microtubules. Frontiers in Neurorobotics, May 2015, Vol. 9, 1-16. doi: 10.3389/fnbot.2015.00002.
[22] Levi P (2016). A Quantum Field Based Approach to Describe the Global Molecular Dynamics of Neurotransmitter Cycles. European Journal of Biophysics, Vol. 4, No. 4, 22-41. doi: 10.11648/j.ejb.20160404.11.
[23] Lodish H, Berk A, Zipursky S L, Matsudaira P, Baltimore D, Darnell J. Molecular Cell Biology (2000). Fourth edition, New York, Freeman and Company.
[24] Lurié D (1968). Particles and Fields. New York, John Wiley & Sons.
[25] Weinberg S (2005). The Quantum Theory of Fields, Vol. I, II, III. Cambridge, Cambridge University Press.
[26] Weinberg S (2013). Lectures on Quantum Mechanics. Cambridge, Cambridge University Press.
[27] Wiggins S (1990). Introduction to Applied Nonlinear Dynamical Systems and Chaos. Heidelberg, Springer-Verlag.
[28] Zaslavsky G M (2007). The Physics of Chaos in Hamiltonian Systems. Second edition, London, Imperial College Press.
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    Paul Levi. (2017). Quantum Effects in Synaptic Neurons and Their Networks in the Brain. European Journal of Biophysics, 4(6), 47-66. https://doi.org/10.11648/j.ejb.20160406.11

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    Paul Levi. Quantum Effects in Synaptic Neurons and Their Networks in the Brain. Eur. J. Biophys. 2017, 4(6), 47-66. doi: 10.11648/j.ejb.20160406.11

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    AMA Style

    Paul Levi. Quantum Effects in Synaptic Neurons and Their Networks in the Brain. Eur J Biophys. 2017;4(6):47-66. doi: 10.11648/j.ejb.20160406.11

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  • @article{10.11648/j.ejb.20160406.11,
      author = {Paul Levi},
      title = {Quantum Effects in Synaptic Neurons and Their Networks in the Brain},
      journal = {European Journal of Biophysics},
      volume = {4},
      number = {6},
      pages = {47-66},
      doi = {10.11648/j.ejb.20160406.11},
      url = {https://doi.org/10.11648/j.ejb.20160406.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ejb.20160406.11},
      abstract = {This article describes small neurotransmitters as particles of a spinless quantum field. That is, the particles are Bosons that e.g. can occupy equal energy levels. In addition, we consider the particles of the presynaptic region before exocytosis occur as elements of a grand canonical ensemble that is in a thermodynamic equilibrium. Thus, the particles obey the Bose-Einstein statistics, which also determines the corresponding information entropy and the corresponding density matrix. When the release of neurotransmitters occur, the equilibrium collapses and the Bose-Einstein distribution transfers to the Poisson distribution. Moreover, the particles transmit as wave packets, with quantized energies and momenta, through the chemical synapses, where we also describe the effects of the quantum fluctuations. We mark this symmetry braking process that corresponds to a non-equilibrium phase transition by a threshold, which mainly depends on the mean of the particles number, with defined quanta. We model the connections of synaptic neurons of a population to a network by Hamiltonians that include both Bosons and Fermions and their interactions. Bosons are the carriers of messages (information) and Fermions are the switches, which forward these messages, with a modified content. The effects we observe in such a neural circuitry reveals a strong dependence of the solutions from the initial values and, more relevant, solutions with chaotic behavior exist. These circuitry-based ramifications together with possible internal malfunctioning of particular neurons (e.g. intermitted flow) of the network cause a sustainable reduction of the synaptic plasticity.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Quantum Effects in Synaptic Neurons and Their Networks in the Brain
    AU  - Paul Levi
    Y1  - 2017/02/10
    PY  - 2017
    N1  - https://doi.org/10.11648/j.ejb.20160406.11
    DO  - 10.11648/j.ejb.20160406.11
    T2  - European Journal of Biophysics
    JF  - European Journal of Biophysics
    JO  - European Journal of Biophysics
    SP  - 47
    EP  - 66
    PB  - Science Publishing Group
    SN  - 2329-1737
    UR  - https://doi.org/10.11648/j.ejb.20160406.11
    AB  - This article describes small neurotransmitters as particles of a spinless quantum field. That is, the particles are Bosons that e.g. can occupy equal energy levels. In addition, we consider the particles of the presynaptic region before exocytosis occur as elements of a grand canonical ensemble that is in a thermodynamic equilibrium. Thus, the particles obey the Bose-Einstein statistics, which also determines the corresponding information entropy and the corresponding density matrix. When the release of neurotransmitters occur, the equilibrium collapses and the Bose-Einstein distribution transfers to the Poisson distribution. Moreover, the particles transmit as wave packets, with quantized energies and momenta, through the chemical synapses, where we also describe the effects of the quantum fluctuations. We mark this symmetry braking process that corresponds to a non-equilibrium phase transition by a threshold, which mainly depends on the mean of the particles number, with defined quanta. We model the connections of synaptic neurons of a population to a network by Hamiltonians that include both Bosons and Fermions and their interactions. Bosons are the carriers of messages (information) and Fermions are the switches, which forward these messages, with a modified content. The effects we observe in such a neural circuitry reveals a strong dependence of the solutions from the initial values and, more relevant, solutions with chaotic behavior exist. These circuitry-based ramifications together with possible internal malfunctioning of particular neurons (e.g. intermitted flow) of the network cause a sustainable reduction of the synaptic plasticity.
    VL  - 4
    IS  - 6
    ER  - 

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Author Information
  • Institute for Parallel and Distributed Systems (IPVS), Faculty for Informatics, Electrical Engineering and Information Technology, University Stuttgart, Stuttgart, Germany

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