Design of Nano-Scale Devices Affecting Synapses: The New Approach to Artificial Intelligence and Brain Interface

Design of Nano-Scale Devices Affecting Synapses: The New Approach to Artificial Intelligence and Brain Interface

Rinat Galiautdinov (Independent Researcher, Italy)
Copyright: © 2019 |Pages: 13
DOI: 10.4018/IJANR.2019070104
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Abstract

The research describes the nano scale devices, their general architecture, and how they affect the synapses. Such devices, based on the new approach in artificial intelligence, will play a significant role in many spheres. The research also describes the architecture of the programming neuron built on the basis of a biological one. Unlike existing technical devices for implementing a neuron based on classical nodes oriented to binary processing, the proposed path is based on bit-parallel processing of numerical data (synapses) for obtaining result. The proposed approach of implementing a neuron can serve as a new elementary basis for the construction of neuron-based computers with a higher processing speed of biological information and good survivability.
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Introduction

Nowadays the sphere of Artificial Intelligence is based on the simplified programmable model of a neuron which becomes a basis of different topologies‘ neural-networks (Galiautdinov, R., 2019). Such the approach however does not seem to be able to fully resolve many problems and build fully functional Artificial Intelligence (Lee, H. et al., 2009 A). At the same time many different spheres have a demand of being able to connect neural activity of biological creatures and technical devices. The solution could be applied in medicine, military sphere, education, etc (Galiautdinov, R. & Mkrttchian, V., 2019 A).

The major trend in such the work was based on measuring of the electrical activity of the brain. Most of the researches in this sphere use the data received with the help of encephalogram adopting this data into some visible result (Lee, S.H. et al., 2017). The recent activity of some other researchers is based on injection of the small electrodes into the brain providing some kind of result based on human interpretation of the spikes (the data of the electrical activity of the brain). As we can see there is no significant difference. Moreover, such the approach leads to dead-end simply because of the two major factors:

  • The size of the electrode can’t be reduced more than it’s reduced now, because it would effect on the quality of the received signal (Ford, L. et al., 2019);

  • The work of the brain is based on electro-chemical transfer of a signal and not just on the electrical signal (Hawkins, R.D. & Kandel, E.R., 2019). The electrical signal might be translated as “do something” and “stop doing something” and the researchers do not take this into consideration.

The approach suggested here is based on nano-scale devices which effect on the synapses and the whole interpretation of the neural activity requires the introduction of another type of the programming neuron based on the biological one which should become a new direction in the sphere of Artificial Intelligence (Galiautdinov, R. & Mkrttchian, V., 2019 B).

The new type of programming neuron (BN) could also become a basis in development of the computers.

The problem of remote control and monitoring of biochemical processes at the molecular and nanoscale level is extremely important and is significant in various fields of science and technology (Rayman, J.B. & Kandel, E.R., 2017). Nanotechnology offers a number of new approaches for this, in particular, the use of composite magnetic nanoparticles activated by an external low-frequency non-heating magnetic field with a frequency of <1 kHz (Mkrttchian, V., Gamidullaeva, L. & Galiautdinov, R., 2019). In this case, magnetic nanoparticles act as mediators that convert the energy of an external magnetic field into mechanical stimuli that transform into a controlled deformation of the surrounding macromolecules and macromolecular systems, thereby changing their structure, properties and biochemical activity.

This approach has significant potential for the selective management of biochemical reactions (regulation of kinetics, yield ratios, cell survival) and the creation of new generation chemical molecular technologies, in particular, for solving nanomedicine problems with molecular locality, selectivity and targeted therapeutic effect (Asok, A. et al., 2018).

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