In recent years, the insulator-to-metal transition in Vanadium Dioxide (VO₂) micro-resistors has been harnessed to design spiking, sensitive neurons [1-6], implemented through compact circuits with minimal components number. VO₂ micro-resistors feature "S-shaped" I-V characteristics with a negative-differential resistance (NDR). Using a current source, the current flowing through the micro-resistor can be set within this region, sot that the device enters an astable regime and quickly oscillates between its metallic and insulating phases, producing voltage spikes.

These sensitive neurons can encode various stimuli including temperature, pressure, RF signals, or visible light into the spikes rate. The transduction is realized either by (1) a dedicated sensor whose current output is fed to the VO₂ device [1-2] or (2) the modulation of the VO₂ device electrical characteristics by the stimulus [3-6], both options affecting the spike rate. However, so far, all proposed sensory neurons – including our previous work [6] – function in an "always spiking" fashion, producing continuous spike trains where information is solely encoded into the time period of consecutive spikes. These sensors are meant to be interfaced with Spiking Neural Networks (SNNs): when using such encoding, the sensing/processing system does not benefit from the full energy saving potential SNNs can offer when activated in a sparse fashion [7]. In addition, plain rate-coding is only one of the many neural codes observed in biological neurons [8], meaning present implementations of VO₂ sensitive neurons do not reproduce this complexity.

In this work, we propose a temperature-sensitive VO₂ neuron operating just below the limit of its spiking regime, in which temperature is encoded into several characteristics of spike bursts rather than continuous spike trains. This bursting phenomenon could be attributed to a combination of noise sources, both external and intrinsic to the VO₂ device. In our case, the current is set right under the NDR region of the device, using a NMOS transistor in saturation regime (making the sensory neuron a 1T-1R system). The VO₂ micro-resistor will then sporadically enter spiking regime, through stochastic resonance with external or internal noise (e.g. on the transistor current, supply voltage, or thermal noise on the resistor), triggering the start of a spike burst. After a few spikes, the burst terminates: this could be due to intrinsic cycle-to-cycle variations in the VO₂ electrical characteristics (modeled and observed in previous work [6][9][10]).

We study the evolution of several bursts characteristics over the 42 – 45°C range: bursts duration, inter-burst intervals, spike count per burst, frequency of burst occurrence, inter-spike interval (ISI) in burst, and mean firing rate. For the four last parameters, we find trends similar to those observed in biological thermoreceptors of insects. Indeed, such receptors switch from regular to bursty spiking in certain noxious temperature ranges; their burst frequency, spike count per burst and mean firing rate increase with temperature, while their ISI decreases [11][12]. In VO₂ neurons, this can be explained by the modulation of the I-V characteristics with temperature: the S-shaped region moves closer to the fixed current, making the device more likely to enter spiking regime upon current fluctuations.

This bursting behavior takes place in a narrow temperature range: above a certain threshold temperature, the VO₂ neuron enters back into the always-spiking regime, in which temperature is solely encoded into the period of continuous spikes. We measure 10 different VO₂ devices and find that this threshold temperature varied from up to several degrees from neuron to neuron, a disparity which is also observed among biological neurons in single specimens [11].

Our findings pave the way for a new type of more biologically plausible, energy efficient sparse encoding of stimuli into phase-transition neurons.