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Integration technology for replacing damaged brain areas with artificial neuronal networks

Authors :
Andrey A. Mironov
Victor B. Kazantsev
Polina Bardina
Mikhail A. Mishchenko
Zoia Zhuravleva
A.V. Lebedeva
Alexey Mikhaylo
Alexander N. Pisarchik
S. A. Gerasimova
Anastasiya Fedulina
Source :
2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR).
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

We present a novel integration technology for replacing damaged microcircuits in the rat brain with electronic neuronal networks. This technology will allow simulating important brain functions, such as memory, through the adaptive stimulating effects of neural interfaces at cellular and neuronal network levels. The proposed system includes electronic devices to register and process neuronal signals and to adaptively stimulate damaged brain areas according to the online algorithm decoding the registered neuronal activity. The stimulation algorithm is implemented in hardware neural network with memristive connections that allows both network learning and adaptive re-learning.The basic idea is to develop components of hardware neural network with memristive connections for adaptive generation of electrical signals to stimulate particular brain areas. Moreover, the uniqueness of the system is adaptive closed-loop connection between two hippocampal neuronal networks. Such a system is very promising for restoring functionality of damaged areas in the human brain to replace lost functions in patients with brain pathologies or trauma.

Details

Database :
OpenAIRE
Journal :
2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR)
Accession number :
edsair.doi...........fb00768ecdc707369091a8d87d07df3b
Full Text :
https://doi.org/10.1109/dcnair50402.2020.9216941