Ralph Etienne-Cummings

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Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this(More)
An 80 x 60 pixels arbitrated address-event imager has been designed and fabricated in a 0.6µm CMOS process. The value of the intensity is inversely proportional to the inter-spike interval and the read-out of each spike is initiated by the pixel. The available output bandwidth is allocated according to the pixel's demand, favoring brighter pixels and(More)
In biological systems, the task of computing a gait trajectory is shared between the biomechanical and nervous systems. We take the perspective that both of these seemingly different computations are examples of physical computation. Here we describe the progress that has been made toward building a minimal biped system that illustrates this idea. We embed(More)
The biological foundation of most natural locomotory systems is the Central Pattern Generator (CPG). The CPG is a set of neural circuits found in the spinal cord, arranged to produce oscillatory periodic waveforms that activate muscles in a coordinated manner. A 2 nd generation VLSI CPG emulator chip ⎯ with more and improved neurons, enhanced flexibility,(More)
We present a multichip, mixed-signal VLSI system for spike-based vision processing. The system consists of an 80 x 60 pixel neuromorphic retina and a 4800 neuron silicon cortex with 4,194,304 synapses. Its functionality is illustrated with experimental data on multiple components of an attention-based hierarchical model of cortical object recognition,(More)
As development toward multi-fingered dexterous prosthetic hands continues, there is a growing need for more flexible and intuitive control schemes. Through the use of generalized electrode placement and well-established methods of pattern recognition, we have developed a basis for asynchronous decoding of finger positions. With the present method,(More)
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