James C. Knight

This paper proposes a model explaining how desert ants control Learning Walks (LWs) through a mismatch between path integration and visual cues, showing it reproduces LW dynamics and transitions to foraging.

The paper develops and tests computational models of TSDN circuits in hoverflies to explain how background motion modulates target responses, finding that simple inhibition from LPTCs explains facilitation and suppression.

This paper uses an anatomically constrained model to show that the bilateral structure of the insect brain can implicitly encode higher-order visual features used in navigation, without requiring explicit computation.

This paper develops a spiking neural network model of the insect central complex to estimate heading direction using visual cues and demonstrates its ability to track heading in natural scenes.

The paper studies how target-tuned neurons in male hoverflies respond to reconstructed pursuit trajectories, finding that individual neurons respond to specific parts of the pursuit while the population covers a larger proportion.

This paper introduces GPU-accelerated spiking neural network simulations that procedurally generate connectivity in real-time, enabling large-scale brain modeling on single GPUs.