Orientation-selective aVLSI spiking neurons

We describe a programmable multi-chip VLSI neuronal system that can be used for exploring spike-based information processing models. The system consis ts of a silicon retina, a PIC microcontroller, and a transceiver chip whose integrate-and-fire neurons are connected in a soft winner-take-all archite cture. The circuit on this multi-neuron chip approximates a cortical microc ircuit. The neurons can be configured for different computational propertie s by the virtual connections of a selected set of pixels on the silicon ret ina. The virtual wiring between the different chips is effected by an event -driven communication protocol that uses asynchronous digital pulses, simil ar to spikes in a neuronal system. We used the multi-chip spike-based syste m to synthesize orientation-tuned neurons using both a feedforward model an d a feedback model. The performance of our analog hardware spiking model ma tched the experimental observations and digital simulations of continuous-v alued neurons. The multi-chip VLSI system has advantages over computer neur onal models in that it is real-time, and the computational time does not sc ale with the size of the neuronal network. (C) 2001 Elsevier Science Ltd. A ll rights reserved.