Dynamic computation in a recurrent network of heterogeneous silicon neurons

Abstract—We describe a neuromorphic chip with a twolayer excitatory-inhibitory recurrent network of spiking neurons that exhibits localized clusters of neural activity. Unlike other recurrent networks, the clusters in our network are pinned to certain locations due to transistor mismatch introduced in fabrication. As described in previous work, our pinned clusters respond selectively to oriented stimuli and the neurons’ preferred orientations are distributed similar to the visual cortex. Here we show that orientation computation is rapid when activity alternates between layers (staccato-like), dislodging pinned clusters, which promotes fast cluster diffusion. I. PATTERN-FORMING RECURRENT NETWORKS A 2-D recurrent network of spiking neurons with Mexican hat connectivity (local excitation and distal inhibition) can exhibit clusters of activity when the feedback is sufficiently strong. These clusters are an emergent property of the network and are identified by contiguous regions of ...

• Type: Conference
• Year: 2006
• Where: ISCAS
• Authors: Paul Merolla, Kwabena Boahen
• Keywords: Excitatory-inhibitory Recurrent Network, ISCAS 2006, Neurons, Recurrent Network