An important clarification: I intentionally exaggerate some aspects and simplify some facts, for the sake of simplicity of perception of the idea.

When the reflex is strengthened by repetitions, one can speak about the refinement and amplification of the transmission in the direction for each segment. This concept leads to the conclusion that if we divide the entire bark into similar segments, we will observe in each a certain orientation in the direction with varying accuracy and strength. Each segment will be part of some reflex arc of a conditional or unconditioned reflex. Presumably, this orientation in the learning process can be refined or changed.

If you turn to the neural paradigm, then it does not provide for orientation in the direction. We have a membrane and dendrites that receive signals and an axon, through which the signal is passed on to other cells after space-time summation, that is, the signal is transmitted in one direction along the axon to its endings. But in doing so, we still observe the formation of directed propagation of excitation in the brain, with the formation of conditioned reflexes.

If we consider not a single cell as a functional unit of directed commutation, but a small cell region, then one can see that the cells and their processes are very tightly interlaced, and in different directions. This gives an element of directional communication with a multitude of inputs and outputs in different directions.

The shape of the neuron is due to evolutionary changes. The shape of the cell was formed in nervous systems, in which only the simplest functional of nervous activity was realized. When the development of life on Earth required the addition of the formation of culinary reflexes to the set of functions of the nervous system, evolution proceeded along the path of not rebuilding the cell, but increasing their number and densely interlacing their dendrites and axons.

Thus, the property of directional commutation is distributed in groups of neurons, in the change in the strength of their synapses. The model neuron is a functional unit in modeling, and therefore an analogue in biology for it is a group of neurons, for which the phenomenon of directional commutation will be expressed.

We found out that the direction of excitation propagation is important for us, but how this direction is determined for each functional element. It is known that excitation seeks to spread to another source of excitation, and a stronger and larger focus of excitement attracts weaker ones (the conclusion of Academician Ivan Pavlov). If the functional element gets excited, then somehow it must determine the direction that will subsequently form and remain in its structure.

In my work on modeling, I started from the idea of the electromagnetic interaction of nerve cells, and this idea gave answers to many puzzles about the brain, gave a theory and a model explaining many aspects of the work of the nervous system.

Direct research on this topic has been done little, this is due to the fact that labor-intensive work is required to register changes in neurons under the influence of external electric fields. For example, an experiment conducted by neurophysiologists from the California Institute of Technology (C.A. Anastassiou, R. Perin, H. Markram, C. Koch (2011) Ephartic communication in cortical neurons — Nature Neuroscience [Abstract], [PDF]), showed that extracellular electric fields generated by neurons change the characteristics of the action potentials of other neurons.

Despite the fact that the neuron has many contacts with the neighbors’ cells, the radius of its action is limited in comparison with the scale of the nervous system as a whole. It becomes unclear how the neuron commutation takes place in the formation of simple conditioned reflexes, since the distances between different representations of these or those reflexes can be counted up to hundreds of millimeters.

I.P. Pavlov explains the mechanism of formation of conditioned reflexes in the following way: If two foci of excitation arise in the central nervous system, the stronger one of them “attracts” excitation from the less powerful one. If such an interaction of the strong and weak foci of excitation is combined repeatedly several times, a conditioned reflex can form.

Transmission of excitation in the nervous system is always accompanied by a change in electromagnetic fields. It is natural to assume that the nature of the “Pavlovsky attraction” has an electromagnetic character. Of course, there are hypotheses that neurons can interact at a certain quantum level, but the nature of these interactions is not clear, the development of quantum models should be postponed until the advent of quantum computers.

If we follow the Pavlovian ideas, then each activated neuron must determine in which direction the strongest focus of excitation exists and, subsequently, transmit excitation in the right direction. The neuron can memorize this direction and use it in the future. Here the neuron is represented as a certain commutator. The network of such switches forms a reflex arc, like an electrical circuit that can be formed, strengthened, rebuilt and destroyed. Of course, the functions of the adder are stored behind the neuron, which extends the capabilities of such a self-organized system.

To test the hypothesis, I developed a model in which a neuron, like a cellular automaton, conducts its internal calculations independently of the system, only on the basis of the collected information. First, when the neuron excitation is received, its variable q (charge) begins to change at a frequency of 0.01 c, depending on the given array of numbers characterizing the law of charge change on the surface of its membrane. A total of sixteen values, after which the neuron does not react to irritation for a short period of time.

For demonstration, we present four variants of the law of charge change, mainly differing in the value of the negative trace potential. It is believed that the undershoot are only a consequence of the repolarization of the neuron. In my work on the models I came to the conclusion that the undershoot is of great importance for the communication of neurons.