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Research in artificial neural networks the role of temporal parameters of inhibition in the local synchronization of activity in the cortex


V. G. Marchenko, E. D. Bark, K. A. Saltykov

On a simulation model of local neural network we investigated the role of temporal parameters of inhibition of cortical neurons in the generation of slow epileptiform potentials. To create a neural network model we used the program "Neuroimitator" version 4. 2. The model imagines matrix of 20-69 at the same level of formal neurons that are not directly related to each other. Parameters of formal neurons corresponded to the parameters of real cortical neurons. In the model of local neural network at a sufficiently long period of time we were able to get the synchronous activity of neurons at the oscillation frequency 0.7 Hz. For network operation mode, when the number of simultaneously active neurons at twice the equivalent noise (the number of neurons with relatively unexpressed rhythm), you must have a network of at least 75% of the neurons with the above mentioned parameters. Exactly the same activity was observed in the real local neural networks of the cortex during blockade of GABAA receptors. It appeared to be essential that the neurons that make the greatest contribution to the generation of synchronous activity had the duration of the inhibitory pause in the range from 100 to 150 ms and 300 ms. Coincidence of activity at the output of the model and in animal experiments give grounds to assert that the processes simulated in the model are similar to the processes occurring in the brain. Based on the results obtained on the model, we can as-sume that the synchronization observed during epileptiform discharges in local networks of the cortex is due to inhibition mainly related to GABAB receptors.
June 24, 2020
May 29, 2020

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