| In the biological retina, the feedback and lateral pathways among retinal neurons construct a complicated network that contributes to motion sensing in the retina. When these complex pathways and diverse retinal cell types collaborate, the retina effectively extracts useful information from the visual scene and communicates it to the brain. A silicon retina with motion sensing may be useful for service robots, autonomous vehicles and other applications that require processing dynamic visual information in real time. Implementing motion sensing in a silicon retina presents many challenges. For engineers trying to model the motion sensing functions of a silicon retina, connectivity is one of the most significant engineering challenges that have to be considered.;For this dissertation research, we implement a portion of the starburst amacrine cell (SAC) and differential motion detection model. We also investigate the importance of the feedback and lateral connections in implementing these motion sensing functions in silicon circuit. To validate the importance of the feedback and lateral pathways in the silicon retina, we first build a portion of a retinal network from photoreceptors to ganglion cells that maintains a hierarchical structure similar to that of the biological retina. Lateral connections with horizontal cells and amacrine cells are implemented, along with feedback within the inner and outer plexiform layers of the retina. We then perform demonstrations by comparing the silicon retina tested to one altered by removing these pathways and observing how the behaviors in the silicon retina are changed. We also compare some of our simulation results with biological data. In this research, we showed that some functions cannot be achieved or performances degrade without feedback and lateral connections. Hence, we concluded that incorporating feedback and lateral connections in the artificial retina helps the performance even though it complicates the retinal network. |
