Simulating Small Neural Circuits with a Discrete Computational Model.

Simulating Small Neural Circuits with a Discrete Computational Model.
Biol Cybern. 2020 Mar 13;:
Authors: Bazenkov NI, Boldyshev BA, Dyakonova V, Kuznetsov OP
Abstract
Simulations of neural activity are commonly based on differential equations. We address the question what can be achieved with a simplified discrete model. The proposed model resembles artificial neural networks enriched with additional biologically inspired features. A neuron has several states, and the state transitions follow endogenous patterns which roughly correspond to firing behavior observed in biological neurons: oscillatory, tonic, plateauing, etc. Neural interactions consist of two components: synaptic connections and extrasynaptic emission of neurotransmitters. The dynamics is asynchronous and event-based; the events correspond to the changes in neurons activity. This model is innovative in introducing discrete framework for modeling neurotransmitter interactions which play the important role in neuromodulation. We simulate rhythmic activity of small neural ensembles like central pattern generators (CPG). The modeled examples include: the biphasic rhythm generated by the half-center mechanism with the post-inhibitory rebound (like the leech heartbeat CPG), the triphasic rhythm (like in pond snail feeding CPG) and the pattern switch in the system of several neurons (like the switch between ingestion and egestion in Aplysia feeding CPG). The asynchronous dyn...

Source: Biological Cybernetics - March 12, 2020 Category: Science Authors: Bazenkov NI, Boldyshev BA, Dyakonova V, Kuznetsov OP Tags: Biol Cybern Source Type: research