Reid R. Harrison

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In the past decade, neuroscientists and clinicians have begun to use implantable MEMS multielectrode arrays (e.g., [1]) to observe the simultaneous activity of many neurons in the brain. By observing the action potentials, or “spikes,” of many neurons in a localized region of the brain it is possible to gather enough information to predict hand trajectories(More)
We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6- mum 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902-928 MHz(More)
Locusts possess an identified neuron, the descending contralateral movement detector (DCMD), conveying visual information about impending collision from the brain to thoracic motor centers. We built a telemetry system to simultaneously record, in freely behaving animals, the activity of the DCMD and of motoneurons involved in jump execution. Cocontraction(More)
Arthropods exhibit highly efficient solutions to sensorimotor navigation problems. They thus provide a source of inspiration and ideas to robotics researchers. At the same time, attempting to re-engineer these mechanisms in robot hardware and software provides useful insights into how the natural systems might work. This paper reviews three examples of(More)
We have designed and tested a single-chip analog VLSI sensor that detects imminent collisions by measuring radially expanding optic flow. The design of the chip is based on a model proposed to explain leg-extension behavior in flies during landing approaches. We evaluated a detailed version of this model in simulation using a library of 50 test movies taken(More)
Extracellular electrode arrays can reveal the neuronal network correlates of behavior with single-cell, single-spike, and sub-millisecond resolution. However, implantable electrodes are inherently invasive, and efforts to scale up the number and density of recording sites must compromise on device size in order to connect the electrodes. Here, we report on(More)
We compare the performance of algorithms for automatic spike detection in neural recording applications. Each algorithm sets a threshold based on an estimate of the background noise level. The adaptive spike detection algorithm is suitable for implementation in analog VLSI; results from a proof-of-concept chip using neural data are presented. We also(More)
The neural computations underlying sensory-guided behaviors can best be understood in view of the sensory stimuli to be processed under natural conditions. This input is often actively shaped by the movements of the animal and its sensory receptors. Little is known about natural sensory scene statistics taking into account the concomitant movement of(More)
We have developed miniature telemetry systems that capture neural, EMG, and acceleration signals from a freely moving insect or other small animal and transmit the data wirelessly to a remote digital receiver. The systems are based on custom low-power integrated circuits (ICs) that amplify, filter, and digitize four biopotential signals using low-noise(More)