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Book Publisher International (a part of SCIENCEDOMAIN International)

Study on the Quantum Effects in Synaptic Neurons and Their Networks in the Brain

Paul A. Levi

Published Jul 23, 2021• 0 citations
Publisher

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 occurs, 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.

DOI
10.9734/bpi/nupsr/v12/3191f

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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.

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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 occurs, 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.
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.
Descriptions of neurotransmitter cycles in chemical synapses are generally accomplished in the field of macroscopic molecular biology. This paper proposes a new theoretical approach to model these cycles with methods of the non-relativistic quantum field theory (QFT) which is applicable on small neurotransmitters of nano size like amino acids or amines. The whole cycle is subdivided into the standard five phases: uptake, axonal transport, release and reception. Our ansatz is concentrated to quantum effects, which are relevant in molecular processes. Examples are quantization of momentums and energies of all small transmitters, definition of the density-based quantum information, quantization of molecular currents, because densities of them generate quantized particles. Our model of the neurotransmitter cycle of chemical synapses was created by the emphasis of possible essential quantum effects; therefore, we neglect many additional molecular aspects that do not lead us to quantum impacts. We elucidate the ramification of our quantum-based approach by the definition of particular Hamiltonians for each of the five phases of the neurotransmitter cycles and by the calculation of the corresponding molecular dynamics. The transformation from the particle representation to usual wave functions yields the probability to find at the same time neurotransmitters of different energy states at different positions. Our results have far-reaching implications and may initiate animated discussions. The validation or the disconfirmation of our hypothesis is still open.
Descriptions of neurotransmitter cycles in chemical synapses are generally accomplished in the field of macroscopic molecular biology. This paper proposes a new theoretical approach to model these cycles with methods of the non-relativistic quantum field theory (QFT) which is applicable on small neurotransmitters of nano size like amino acids or amines. The whole cycle is subdivided into the standard five phases: uptake, axonal transport, release and reception. Our ansatz is concentrated to quantum effects, which are relevant in molecular processes. Examples are quantization of momentums and energies of all small transmitters, definition of the density based quantum information; quantization of molecular currents because densities of generate them quantized particles. Our model of the neurotransmitter cycle of chemical synapses was created by the emphasis of possible essential quantum effects; therefore, we neglect many additional molecular aspects that do not lead us to quantum impacts. We elucidate the ramification of our quantum-based approach by the definition of particular Hamiltonians for each of the five phases and by the calculation of the corresponding molecular dynamics. The transformation from the particle representation to usual wave functions yields the probability to find at the same time n neurotransmitters of different energy states at different positions. Our results have far-reaching implications and may initiate animated discussions. The validation or the disconfirmation of our hypothesis is still open.
If non-material mental events, such as the intention to carry out an action, are to have an effective action on neural events in the brain, it has to be at the most subtle and plastic level of these events. In the first stage of our enquiry an introduction to conventional synaptic theory leads on to an account of the manner of operation of the ultimate synaptic units. These units are the synaptic boutons that, when excited by an all-or-nothing nerve impulse, deliver the total contents of a single synaptic vesicle, not regularly, but probabilistically. This quantal emission of the synaptic transmitter molecules (about 5000-10 000) is the elementary unit of the transmission process from one neuron to another. In the second stage this refined physiological analysis leads on to an account of the ultrastructure of the synapse, which gives clues as to the manner of its unitary probabilistic operation. The essential feature is that the effective structure of each bouton is a paracrystalline presynaptic vesicular grid with about 50 vesicles, which acts probabilistically in vesicular (quantal) release. In the third stage it is considered how a non-material mental event, such as an intention to move, could influence the subtle probabilistic operations of synaptic boutons. On the biological side, attention is focused on the paracrystalline presynaptic vesicular grids as the targets for non-material mental events. On the physical side, attention is focused on the probabilistic fields of quantum mechanics which carry neither mass nor energy, but which nevertheless can exert effective action at microsites. The new light on the mind-brain problem came from the hypothesis that the non-material mental events, the 'World 2' of Popper, relate to the neural events of the brain (the 'World 1' of matter and energy) by actions in conformity with quantum theory. This hypothesis that mental events act on probabilistic synaptic events in a manner analogous to the probability fields of quantum mechanics seems to open up an immense field of scientific investigation both in quantum physics and in neuroscience.
A probabilistic model of Synapse is proposed. In concrete, synapse is proposed as a Bayesian probability that requires the quantum probabilities for both: the interaction of Calcium 2+ in axon area, and the releasing of neurotransmitters. In this way, all available interactions that are carry out at axon zone, are dictated by quantum events. Once neurotransmitters are released from synaptic vesicles, their dynamics might be dictated by quantum probabilities based in a Hamiltonian. The diverse scenarios and their respective distribution of probabilities are simulated. From proposed theory, it is suggested that synapse would have a notable dependence on the accumulation of electric charges before and after the pass of neurotransmitters from a neuron to adjacent one. From the results, it is possible to argue that synapse is more than a biological phenomenon, a multidisciplinary event, that emphasizes the importance of transporting of electric charges with a potential dependence on probabilities, more than trivial determinism.
Abstract Motivated by recent advances in neuroscience, in this work, we explore the emergent behaviour of quantum systems with a dynamical biologically-inspired qubits interaction. We use a minimal model of two interacting qubits with an activity-dependent dynamic interplay as in classical dynamic synapses that induces the so-called synaptic depression, that is, synapses that present synaptic fatigue after heavy presynaptic stimulation. Our study shows that in absence of synaptic depression the two-qubits quantum system shows typical Rabi oscillations whose frequency decreases when synaptic depression is introduced, so one can trap excitations for a large period of time. This creates a population imbalance between the qubits even though the Hamiltonian is Hermitian. This imbalance can be sustained in time by introducing a small energy shift between the qubits. In addition, we report that long time entanglement between the two qubits raises naturally in the presence of synaptic depression. Moreover, we propose and analyse a plausible experimental setup of our two-qubits system which demonstrates that these results are robust and can be experimentally obtained in a laboratory.