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Electrostimulation of inhibition

DOI 10.18127/j19998554-201810-03

Keywords:

B.V. Zhuravlev – Dr.Sc. (Med.), Professor, Chief Research Scientist,  Head of Laboratory of General Physiology of Functional Systems, P.K. Anokhin Institute of Normal Physiology (Moscow)
E-mail: b.zhuravlerb@nphys.ru
N.Yu. Trifonova – Junior Research Scientist, Laboratory of General Physiology of Functional Systems, P.K. Anokhin Institute of Normal Physiology (Moscow)
E-mail: natrish@bk.ru
A.V. Savelyev – Ph.D. (Philos.), Senior Research Scientist, Director of the Patent agency «©Uniquely honest patenting» (Moscow)
E-mail: gmkristo@rambler.ru


The aim of the study was to simulate the activity "silent" neurons, which is well illustrated by the developed specialized neu-roprocessor of the "silent" neuron, supported by the patent RU 1436720. In addition the it`s application for the new generation stimulatiors – Inhibition stimulator. The article presents the results of a study on the activities of the so-called "Silent" neurons in terms of their participation in the processes of nonspecific inhibition. The questions of detailed modeling of their activity based on the use of numerous neurophysiological data are considered. A number of schemes of neuroelectrostimulators are proposed to activate the inhibition processes without the adverse effects on the professional activity, during its fulfillment. When generating a bundle of spikes, hyperpolarization increases and, the faster, the more the frequency of spikes generated under the exposure to the external stimuli is the threshold exceeds the total stimulating effect from the output of the block 6. Also, when the stimulation stops, the signal at the output of the accumulator 16 and, accordingly, at the output of the device, the increased threshold value persists for a long time, gradually decreasing as the capacitor of the accumulator self-discharges, and since the signal level on it is summed and considerably exceeds the level of the signal with a single discharge of the neuron, then the period of restoration of the initial state is much longer than that of the real "silent" neuron (before a few minutes). The scheme of the device (algorithm) developed can be used as a transcranial electrostimulator of silent neurons, which provides among other things, one of the components of the complex inhibition mechanism. Moreover, the morphological activation of silent neurons can only be mediated indirectly by the general neurochemical inhibition processes caused by the appropriate mediators (GABA, dopamine, glycine, norepinephrine, taurine, adonosine, etc.). This means that the activation of silent neurons with the help of the devices proposed used as the neurostimulators with a complex organization according to the signal proposed by the algorithm, makes it possible to activate the processes of neuro-inhibition without inhibiting cognitive functions. This, in turn, is extremely important for resting sensory and other cognitive brain systems directly involved in the process of labor and social activity, for example, air operators, sea, land-based vehicles, etc. without disconnecting from work. Thus, an algorithm that implements the operation of a "silent" neuron can be included in artificial neural networks, which will increase their stability and noise immunity, prevent self-excitation, and improve the accuracy of calculations by eliminating unwanted nonlinear oscillations. In addition, the device patented can serve as an electrostimulator, which provides the transmission of the output signal into the neocortex. This can be make invasively on the electrodes injected directly into the brain, for example, in neurosurgical operations, or in the form of modulation of traditional transcranial magnetic, or electrical, or electromagnetic stimulation. In the latter case, the levels of the affected signals decrease significantly (by a factor of three orders of magnitude or more), which in turn, causes, no side effects, which are often observed when the traditional methods of exposure to the brain are used.
This work was financially supported by RHSF in grant № 15-03-00519а «Post-non-classic paradigm of artificial intellect».

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