A memristor-based circuit approximation of the Hindmarsh–Rose model

Abstract Neuron models exist in different levels of complexity and biological modeling depth. The Hindmarsh–Rose model offers a rich repertoire neuronal dynamics while being moderately mathematically complex. Existing circuit realizations this neuron model, however, require large amount operational amplifiers due to the model’s quadratic cubic nonlinearity. In contrast hardware simpler models, leads higher power consumption. work, is approximated by an ideal electrical that relies mostly on passive elements thus reduces For purpose, we analyze flows equivalent replace several nonlinear constant ones. Moreover, approximate nonlinearity three memristors combination with negative impedance converter. This converter represents only active element required for complete circuit, leading increased energy efficiency compared existing realizations. Simulations verify circuit’s ability generate spiking bursting comparable original model. Graphic abstract