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??An integrated circuit with on-chip photoreceptors is described, that computes the bi-directional velocity of a visual stimulus moving along a given axis in the focal plane by measuring the time delay of its detection at two positions. Due to the compactness of the circuit, a dense array of such motion-sensing elements can be monolithically integrated to(More)
We fabricated an improved version of an imager reported earlier [1], primarily by using better pixel circuit and layout principles. The new imager functions over 5 decades of background illumination and has much more symmetrical ON and OFF responses. This imager achieves massive redundancy reduction by temporally differentiating the image contrast. The(More)
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(More)
We present three diierent architectures that make use of analog VLSI velocity sensors for detecting the focus of expansion, time to contact and motion dis-continuities respectively. For each of the architectures proposed we describe the functionality of their component modules and their principles of operation. Data measurements obtained f r om the VLSI(More)
Christof Koch We describe two parallel analog VLSI architectures that integrate optical flow data obtained from arrays of elementary velocity sensors to estimate heading direction and time-to-contact. For heading direction computation, we performed simulations to evaluate the most important qualitative properties of the optical flow field and determine the(More)
We present a biophysically constrained cerebellar model of classical conditioning, implemented using a neuromorphic analog VLSI (aVLSI) chip. Like its biological counterpart, our cerebellar model is able to control adaptive behavior by predicting the precise timing of events. Here we describe the functionality of the chip and present its learning(More)
We couple a previously studied, biologically inspired neurotrophic model of activity-dependent competitive synaptic plasticity and neuronal development to a neuromorphic retina chip. Using this system, we examine the development and refinement of a topographic mapping between an array of afferent neurons (the retinal ganglion cells) and an array of target(More)
A neurotrophic model for the co-development of topography and ocular dominance columns in the primary visual cortex has recently been proposed. In the present work, we test this model by driving it with the output of a pair of neuronal vision sensors stimulated by disparate moving patterns. We show that the temporal correlations in the spike trains(More)
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