Biologically Relevant Dynamical Behaviors Realized in an Ultra-Compact Neuron Model

Abstract

We demonstrate a variety of biologically relevant dynamical behaviors building on a recently introduced ultra-compact neuron (UCN) model. We provide the detailed circuits which all share a common basic block that realizes the leaky-integrate-andfire (LIF) spiking behavior. All circuits have a small number of active components and the basic block has only three, two transistors and a silicon controlled rectifier (SCR). We also demonstrate that numerical simulations can faithfully represent the variety of spiking behavior and can be used for further exploration of dynamical behaviors. Taking Izhikevich's set of biologically relevant behaviors as a reference, our work demonstrates that a circuit of a LIF neuron model can be used as a basis to implement a large variety of relevant spiking patterns. These behaviors may be useful to construct neural networks that can capture complex brain dynamics or may also be useful for artificial intelligence applications. Our UCN model can therefore be considered the electronic circuit counterpart of Izhikevich's (2003) mathematical neuron model, sharing its two seemingly contradicting features, extreme simplicity and rich dynamical behavior.

Implementation of a Minimal Recurrent Spiking Neural Network in a Solid-State Device

“…We next briefly describe the basic features of the UCN circuit; further details can be found in Refs. [12,13]. In Fig.…”

“…Different biologically relevant models were implemented as variations of the UCN circuit in Ref. [13]. In the Supplemental Material [14], we consider the effect of excitatory recursion in two such models to illustrate this point.…”

“…The spiking neuron circuit, or ultracompact neuron (UCN) can be likened to Lego blocks for the construction of networks [12]. It can also be easily extended to realize a multitude of biologically relevant spiking behaviors [13]. Here, we shall adopt the recently introduced circuit of a leaky-integrate-and-fire UCN and supplement it with a self-synaptic connection that produces a self-feedback effect [Fig.…”

A Functional Spiking Neural Network of Ultra Compact Neurons

“…We shall next briefly describe the basic behavior of the UCN, for the sake of completeness. Further details can be found in Rozenberg et al (2019), Stoliar et al (2020).…”

“…However, the SCR present the advantage that they are available off-the-shelf to implement artificial neurons (Rozenberg et al, 2019), avoiding the need to deal with the complexities of Mott quantum material fabrication and control. We should also mention that the UCN is not restricted to the LIF model as it can be easily extended to realize a large variety of biologically relevant spiking neuron models (Stoliar et al, 2020).…”