Ryan J. Kier

Wireless Neural Recording With Single Low-Power Integrated Circuit

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 frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor.

HermesC: Low-Power Wireless Neural Recording System for Freely Moving Primates

Neural prosthetic systems have the potential to restore lost functionality to amputees or patients suffering from neurological injury or disease. Current systems have primarily been designed for immobile patients, such as tetraplegics functioning in a rather static, carefully tailored environment. However, an active patient such as amputee in a normal dynamic, everyday environment may be quite different in terms of the neural control of movement. In order to study motor control in a more unconstrained natural setting, we seek to develop an animal model of freely moving humans. Therefore, we have developed and tested HermesC-INI3, a system for recording and wirelessly transmitting neural data from electrode arrays implanted in rhesus macaques who are freely moving. This system is based on the integrated neural interface (INI3) microchip which amplifies, digitizes, and transmits neural data across a ~ 900 MHz wireless channel. The wireless transmission has a range of ~ 4 m in free space. All together this device consumes 15.8 mA and 63.2 mW. On a single 2 A-hr battery pack, this device runs contiguously for approximately six days. The smaller size and power consumption of the custom IC allows for a smaller package (51 times 38 times 38 mm3) than previous primate systems. The HermesC-INI3 system was used to record and telemeter one channel of broadband neural data at 15.7 kSps from a monkey performing routine daily activities in the home cage.

Wireless Neural/EMG Telemetry Systems for Small Freely Moving Animals

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 circuits. One of the chips also digitizes three acceleration signals from an off-chip microelectromechanical-system accelerometer. All information is transmitted over a wireless ~ 900-MHz telemetry link. The first unit, using a custom chip fabricated in a 0.6- μm BiCMOS process, weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts as well as transdermal potentials in weakly swimming electric fish. The second unit, using a custom chip fabricated in a 0.35-μ m complementary metal-oxide semiconductor CMOS process, weighs 0.17 g and runs for five hours on a single 1.5-V battery. This system has been used to monitor neural potentials in untethered perching dragonflies.

HermesC: RF wireless low-power neural recording system for freely behaving primates

Neural prosthetics for motor systems is a rapidly growing field with the potential to provide treatment for amputees or patients suffering from neurological injury and disease. To determine whether a physically active patient such as an amputee can take advantage of these systems, we seek to develop an animal model of freely moving humans. Therefore, we have developed and tested HermesC, a system for recording neural activity from electrode arrays implanted in rhesus monkeys and transmitting this data wirelessly. This system is based on the integrated neural interface (INI) microchip, which amplifies, digitizes, and transmits neural data across a ~900 MHz wireless channel. The wireless transmission has a range of ~4 m in free space. All together, this device consumes 11.7 mA from a 4.0 V lithium ion battery pack for a total of 46.8 mW. To test the performance, the device was used to record and telemeter one channel of broadband neural data at 15.7 kSps from one monkey doing various physical activities in a home cage, such as eating, climbing and swinging. The in-band noise of the recorded neural signal is 34 muVrms, which is low enough to allow the detection of neural units on an active electrode. This system can be readily upgraded to use future generations of the INI chip, with circuits providing 96 channels of programmable threshold crossing event data.

Design and implementation of multipattern generators in analog VLSI

In recent years, computational biologists have shown through simulation that small neural networks with fixed connectivity are capable of producing multiple output rhythms in response to transient inputs. It is believed that such networks may play a key role in certain biological behaviors such as dynamic gait control. In this paper, we present a novel method for designing continuous-time recurrent neural networks (CTRNNs) that contain multiple embedded limit cycles, and we show that it is possible to switch the networks between these embedded limit cycles with simple transient inputs. We also describe the design and testing of a fully integrated four-neuron CTRNN chip that is used to implement the neural network pattern generators. We provide two example multipattern generators and show that the measured waveforms from the chip agree well with numerical simulations.

A wireless neural/EMG telemetry system for freely moving insects

We have developed a miniature telemetry system that captures neural, EMG, and acceleration signals from a freely moving insect and transmits the data wirelessly to a remote digital receiver. The system is based on a custom low-power integrated circuit that amplifies and digitizes four biopotential signals as well as three acceleration signals from an off-chip MEMS accelerometer, and transmits this information over a wireless 920-MHz telemetry link. The unit weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts.

A wireless neural interface for chronic recording

A primary goal of the integrated neural interface project (INIP) is to develop a wireless, implantable device capable of recording neural activity from 100 micromachined electrodes. The heart of this recording system is a low-power integrated circuit that amplifies 100 weak neural signals, detects spikes with programmable threshold-crossing circuits, and returns these data via digital radio telemetry. The chip receives power, clock, and command signals through a coil-to-coil inductive link. Here we report that the isolated integrated circuit successfully recorded and wirelessly transmitted digitized electrical activity from peripheral nerve and cortex at 15.7 kS/s. The chip also simultaneously performed accurate on-chip spike detection and wirelessly transmitted the spike threshold-crossing data. We also present preliminary successful results from full system integration and packaging.

Wireless neural signal acquisition with single low-power integrated circuit

We present experimental results from an integrated circuit designed for wireless neural recording applications. The chip, which was fabricated in a 0.6-mum 2P3M BiCMOS process, contains 100 amplifiers and a 10-bit ADC and 902-928 MHz FSK transmitter. Neural signals from one amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power receive coil and a 100-nF capacitor.

Power minimization of a 433-MHz LC VCO for an implantable neural recording system

This paper presents a new random-search based integrated inductor optimization algorithm. The algorithm provides the designer with valuable information about design tradeoffs. It is used to design an inductor to minimize power dissipation in an LC VCO. The measured results show that a 53:1 power savings can be achieved over VCOs using inductors optimized only for maximum Q. Six 433-MHz VCOs were fabricated and measured. The VCO using the optimal inductor design has a measured minimum power dissipation of 1.2 mW in a 0.5-mum three-metal CMOS process

An MDAC synapse for analog neural networks

Efficient weight storage and multiplication are important design challenges which must be addressed in analog neural network implementations. Many schemes which treat storage and multiplication separately have been previously reported for implementation of synapses. We present a synapse circuit that integrates the weight storage and multiplication into a single, compact multiplying digital-to-analog converter (MDAC) circuit. The circuit has a small layout area (5400 /spl mu/m/sup 2/ in a 1.5-/spl mu/m process) and exhibits good linearity over its entire input range. We have fabricated several synapses and characterize their responses. Average maximum INL and DNL values of 0.2 LSB and 0.4 LSB, respectively, have been measured. We also report on the performance of an analogue neural network which uses these synapses.