A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations

Abstract

Neurophysiological observations are clarifying how astrocytes can actively participate in information processing and how they can encode information through frequency and amplitude modulation of intracellular Ca2+signals. Consequently, the efficient digital realization of astrocytes is important for developing next generation of bio-inspired computing systems. In this paper, astrocytic calcium oscillations and firing dynamics of the neuron are described by Li-Rinzel and Integrated and Fire models, respectively. Considering highly nonlinear equations of the astrocyte model, linear approximation and single constant multiply (SCM) techniques are employed for efficient hardware realization while maintaining the dynamic of the original models. Next, a low-cost architecture for hardware realization of the astrocyte model is presented which is able to show the essential features of different types of Ca2+modulation including amplitude modulation (AM), frequency modulation (FM) or both modes (AFM). To show good agreement between the results of original model simulated in MATLAB and the proposed digital circuits executed on FPGA, quantitative and qualitative analysis are done. This new neuromorphic circuit of astrocytes successfully is able to demonstrate AM/FM/AFM calcium modulation in its real operation on FPGA and has a wide range of applications from neuroscience to bio-robotics.