Tabular Data for experimental measurements and numerical simulations describing spiking patterns in a three-neuron circuit composed of diffusive memristors

The stochastic dynamics of a three-neuron circuit composed of diffusive memristors is investigated. This circuit simulates synaptic convergence where two primary neurons synapse onto a single secondary neuron. Experimental measurements and numerical simulations are performed to study how applying input voltages V₁ and V₂ onto the primary neurons 1 and 2 respectively influence spiking behavior in the neuromorphic circuit. We reveal input voltage combinations leading to different spiking patterns (i.e. spiking of one, two or three memristors) depending on resistances and noise applied. These findings enable the design of large-scale reconfigurable neuromorphic circuits which combine the responses of functional neuromorphic blocks.fig6a: experimental file shows the experimental measurements of spiking patterns observed for load resistors R_L = 55 kΩ and 60 kΩ applied to artificial primary neurons 1 and 2 respectively with input voltages V_1,2 ϵ [0,3.6] and voltage step 0.2V.fig6b: theory file shows spiking patterns observed for parameters 2k_Bη₁ = 10⁻⁴, 2k_Bη₂ = 10⁻³ and 2k_Bη₃ = 2.9×10⁻⁴ with V_1,2 ϵ [0,400] (voltage step 20V) and randomized potential using derived governing equations that characterize the neuromorphic circuit's spiking dynamics.Qualitative spiking behavior observed in numerical simulations match experimental measurements.© the authors