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 consists of a silicon retina, a PIC microcontroller, and a transceiver chip whose integrate-and-fire neurons are connected in a soft winner-take-all architecture. The circuit on this multi-neuron chip approximates a cortical microcircuit. The neurons can be configured for different computational properties by the virtual connections of a selected set of pixels on the silicon retina. The virtual wiring between the different chips is effected by an event-driven communication protocol that uses asynchronous digital pulses, similar to spikes in a neuronal system. We used the multi-chip spike-based system to synthesize orientation-tuned neurons using both a feedforward model and a feedback model. The performance of our analog hardware spiking model matched the experimental observations and digital simulations of continuous-valued neurons. The multi-chip VLSI system has advantages over computer neuronal models in that it is real-time, and the computational time does not scale with the size of the neuronal network.
Liu
S C
SC
Institute of Neuroinformatics, ETH/UNIZ, Zurich, Switzerland.
Kramer
J
J
Indiveri
G
G
Delbrück
T
T
Burg
T
T
Douglas
R
R
D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D005246:Feedback / Q000502:physiology; D006801:Humans; D008838:Microcomputers; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D010364:Pattern Recognition, Visual / Q000502:physiology*; D012160:Retina / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*