Silicon neuron with programmable ion channel kinematics for bioelectronic applications

Abstract

Bioelectronic medicine is driving the need to design low-power circuits for interfacing biological neurons to electronic neural processing systems, and for implementing real-time close-loop interactions with the biological tissue. This interaction would benefit from congruent features between the biological and artificial systems, such as their working frequency and temporal dynamics. Neuromorphic engineering provides design solutions for building circuits capable of emulating biological neural processing systems faithfully. However, very few, albeit notable, attempts have been made so far to provide accurate models of action potential generation mechanisms with time-constants and dynamics that resemble those of real neurons. This paper presents a design of a silicon neuron, based on a generalized Hodgkin-Huxley model with programmable slopes for each ion channel model, that provide a robust method for matching accurately the silicon neural dynamics to those of target neuron types in biological systems. The parameters of the ion channel dynamics are controlled by a circuit comprising multiple Differential Pairs. This can be used to shape the membrane voltage profile of the silicon neuron. We use this feature to emulate biological neurons involved in respiratory Central Pattern Generator responsible for the stimulation of the vagus nerve for the activation of the heart chamber pacing. The novelty introduced in our approach is to provide a step further toward the development of a silicon neuron able to reproduce the response of biological cells and to interact with them in real-time, with the aim to design low power Brain-Machine-Interface.