Investigation of the functioning of a neurohybrid system based on the FitzHugh–Nagumo radio generator and mouse hippocampal neurons

Abstract

Currently, in the treatment of neurodegenerative diseases that are difficult to respond to drug therapy, electrical stimulation of the brain is performed through invasive intervention in damaged structures of the nervous tissue. The development and development of invasive technologies of closed-loop neural interfaces have made it possible to achieve great success in restoring neural connections, since they have finer and more precise stimulation settings that respond to changes in the physiological state, which is important in the process of restoring the functions of the nervous tissue. Advances in these areas open up prospects for the treatment of a wide range of diseases of the motor system and neurodegenerative diseases of the brain. In this study, a neurohybrid closed system was used, consisting of a FitzHugh-Nagumo radio generator and live surviving slices of the mouse brain hippocampus. For the preparation of surviving slices of the hippocampus, sexually mature males aged 2-3 months of the C57BL/6 mouse line were used. For the preparation and incubation of slices of the hippocampus, a solution of artificial cerebrospinal fluid (ACSF) was used, composition in (mM): 126 NaCl; 3.5 KCl; 1.2 KH2PO4; 26 NaHCO3; 1.3 MgCl * 6H2O; 2 CaCl2 * 6H2O; 10 D-glucose at constant carbogen saturation (95% O2 and 5% CO2). Registration of the electrical activity of brain neurons was carried out using optical and electrophysiological methods. In experiments on pairing a neuron-like FitzHugh-Nagumo generator and biological nerve cells in a closed circuit, an effect was obtained when the activity of brain nerve cells switched the generator to a self-oscillating mode. The evoked oscillations in the neuron-like generator provided an effective stimulus for the activation of nerve fibers in the perforant pathway of the hippocampus. As a result, it was possible to fix a decrease in the frequency of the generator impulses, which was provoked by the responses of living neurons to the incoming stimulus from the neuron-like generator. These results show the ability of live neural networks to control an artificial signal by adjusting its parameters by changing their own activity and confirm the efficiency of using closed loop systems when combining live and artificial neurons. The present study requires further experiments to create more physiological conditions for the functioning of the proposed neurohybrid system. In addition, this neurohybrid system will be improved and have adaptive properties through the use of memristive devices. Advances in this direction will help solve the urgent problem of restoring lost brain functions at the cellular and network levels.