A spiking neural model of the basal ganglia performing action selection, implementing the direct and indirect pathways through StrD1, StrD2, STN, GPe, and GPi nuclei. Drop-in subnetwork: feed in a utility vector, read out a one-hot selection signal.

A 3D recurrent ensemble that implements a 2D oscillator whose angular speed is gated by the third dimension. A separate input ensemble drives that speed, demonstrating how one neural population can control the dynamic regime of another.

A spiking neural model of the lamprey locomotion control module from the Neural Engineering Framework. A 3D damped-oscillator central pattern generator (CPG) drives 10D muscle tensions through a basis-function decoding, producing the traveling-wave swimming pattern characteristic of lamprey undulation.

A Legendre Memory Unit in Nengo — a recurrent layer that optimally represents a sliding window of a continuous-time signal using Legendre polynomials. Demonstrated learning a fixed-time-delay function via PES on a downstream spiking ensemble.

A spiking neural implementation of the Lorenz "butterfly" chaotic attractor. A single 3D ensemble with recurrent connections implements the differential equations of the canonical Lorenz system, producing the characteristic two-lobe trajectory.

A convolutional spiking network trained on MNIST with NengoDL and deployed on Loihi. Demonstrates training a TensorFlow-defined network inside Nengo, then running the trained spiking network on Loihi neuromorphic hardware.