Published paper in Neural Computation: Spiking Elementary Motion Detector in Neuromorphic Systems

The Neuromorphic Behaving Systems Group is proud that a paper co-authored by Elisabetta Chicca is published in the journal Neural Computation.

In the paper titled "Spiking Elementary Motion Detector in Neuromorphic Systems" the authors investigate the dynamics of a novel asynchronous circuit inspired by the Hassenstein-Reichardt Detector for elementary motion. By using an event-based vision sensor and its output spikes, the authors show that they can encode the time an object's image needs to travel across the retina into a burst of spikes. A fast but imprecise estimate of the time-to-travel can already be obtained from the first two spikes of a burst and refined by subsequent interspike intervals. The latter encoding scheme is possible due to an adaptive nonlinear synaptic efficacy scaling.

The VLSI implementation of this spiking Elementary Motion Detector (sEMD) can be used to compute a collision avoidance direction in the context of robotic navigation in a cluttered outdoor environment. The proposed computational principle constitutes a generic spiking temporal correlation detector that can be applied to other sensory modalities (e.g., sound localization), and it provides a novel perspective to gating information in spiking neural networks. It is a first step toward a novel bioinspired vision processing approach suitable for robotics as well as various embedded systems.