Multiplier-less digital implementation of neuronastrocyte signalling on FPGA
Experimental observations have shown that astrocytes are active partner in neural information processing which are mainly carried out by neurons. In this research, we investigate this issue and provide a computationally efficient digital circuit for neuronastrocyte interactions. The firing dynamics of the neuron is described by Izhikevich model (spiking and bursting activities) and the calcium dynamics of a single astrocyte explained by a proposed model adapted from a functional model introduced by Postnov and colleagues. The new linear model makes it possible to design an efficient multiplier-less hardware architecture for digital implementation of neuronastrocyte interaction on field-programmable gate array (FPGA). Using the proposed neuronastrocyte circuit and based on the results of MATLAB simulation, hardware synthesis and FPGA implementation, it is demonstrated that the proposed digital astrocyte is able to change the neuron spiking frequency through bidirectional signaling. This circuit may represent a fundamental computational unit for the development of artificial neuronastrocyte networks, opening new perspectives in pattern recognition tasks.
digital implementation fpga neuronastrocyte interactions neuromorphic circuit