A Six-Transistor Integrate-and-Fire Neuron Enabling Chaotic Dynamics.

Abstract

Integrate-and-fire (I&F) neurons used in neuromorphic systems are traditionally optimized for low energy-per-spike and high density, often excluding the complex dynamics of biological neurons. Limited dynamics cause missed opportunities in applications such as modeling time-varying physical systems, where using a small number of neurons with rich nonlinearities can enhance network performance, even when rich neurons incur a marginally higher cost. By adding additional coupling into the gate of one transistor within an I&F neuron, we parsimoniously achieve a highly nonlinear system capable of exhibiting rich dynamics and chaos. The dynamics of this novel neuron include regular spiking, fast spiking, and chaotic chattering, and can be tuned via the neuron parameters and input current. We implement and experimentally demonstrate the behavior of our chaotic neuron and its subcircuits on a 350 nm field-programmable analog array. Experimental insights inform a compact simulation model, which validates experimental results and confirms that the additional coupling incites chaos. Results are corroborated with comparisons to traditional I&F neurons. Our chaotic circuit achieves the lowest area (0.0025 mm²), power draw (1.1-2.6 μW), and transistor count (6T) of any nondriven chaotic system in integrated CMOS thus far. We also demonstrate the utility of our neuron for neuroscience exploration and hardware security.