An Analysis of a Ring Attractor Model for Cue Integration [chapter]

Xuelong Sun, Michael Mangan, Shigang Yue
2018 Lecture Notes in Computer Science  
Animals and robots must constantly make sense of multiple streams of noisy information gathered from the environment, and combine them appropriately to make improved decisions. Recently, it has been proposed that animals might combine conflicting cues optimally using a ring attractor network architecture inspired by the head direction system in rats and augmented with a dynamic re-weighting mechanism. In this work we report that an older and simpler ring attractor network architecture,
more » ... no re-weighting property combines cues according to their certainty for small to moderate cue conflicts but converges on the most certain cue for larger conflicts. These results are consistent with observations in animal experiments that show sub-optimal cue integration and switching from cue integration to cue selection strategies. This work therefore demonstrates an alternative architecture for those seeking neural correlates of sensory integration in animals. In addition, performance is shown robust to noise and miniaturization and thus provides an efficient solution for artificial systems.
doi:10.1007/978-3-319-95972-6_49 fatcat:iflz3rwmjfdbrgqqdbmhoh3avy