R.J. Kier

Bio: R.J. Kier is an academic researcher from University of Utah. The author has contributed to research in topics: Low-power electronics & Amplifier. The author has an hindex of 11, co-authored 14 publications receiving 1520 citations.

A Low-Power Integrated Circuit for a Wireless 100-Electrode Neural Recording System

Abstract: Recent work in field of neuroprosthetics has demonstrated that by observing the simultaneous activity of many neurons in specific regions of the brain, it is possible to produce control signals that allow animals or humans to drive cursors or prosthetic limbs directly through thoughts. As neuroprosthetic devices transition from experimental to clinical use, there is a need for fully-implantable amplification and telemetry electronics in close proximity to the recording sites. To address these needs, we developed a prototype integrated circuit for wireless neural recording from a 100-channel microelectrode array. The design of both the system-level architecture and the individual circuits were driven by severe power constraints for small implantable devices; chronically heating tissue by only a few degrees Celsius leads to cell death. Due to the high data rate produced by 100 neural signals, the system must perform data reduction as well. We use a combination of a low-power ADC and an array of "spike detectors" to reduce the transmitted data rate while preserving critical information. The complete system receives power and commands (at 6.5 kb/s) wirelessly over a 2.64-MHz inductive link and transmits neural data back at a data rate of 330 kb/s using a fully-integrated 433-MHz FSK transmitter. The 4.7times5.9 mm2 chip was fabricated in a 0.5-mum 3M2P CMOS process and consumes 13.5 mW of power. While cross-chip interference limits performance in single-chip operation, a two-chip system was used to record neural signals from a Utah Electrode Array in cat cortex and transmit the digitized signals wirelessly to a receiver

Wireless Neural Recording With Single Low-Power Integrated Circuit

Abstract: 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

Abstract: 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

Abstract: 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

Abstract: 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.

Neural Mechanisms for Interacting with a World Full of Action Choices

Abstract: The neural bases of behavior are often discussed in terms of perceptual, cognitive, and motor stages, defined within an information processing framework that was originally inspired by models of human abstract problem solving. Here, we review a growing body of neurophysiological data that is difficult to reconcile with this influential theoretical perspective. As an alternative foundation for interpreting neural data, we consider frameworks borrowed from ethology, which emphasize the kinds of real-time interactive behaviors that animals have engaged in for millions of years. In particular, we discuss an ethologically-inspired view of interactive behavior as simultaneous processes that specify potential motor actions and select between them. We review how recent neurophysiological data from diverse cortical and subcortical regions appear more compatible with this parallel view than with the classical view of serial information processing stages.

A Low-Power Integrated Circuit for a Wireless 100-Electrode Neural Recording System

Abstract: Recent work in field of neuroprosthetics has demonstrated that by observing the simultaneous activity of many neurons in specific regions of the brain, it is possible to produce control signals that allow animals or humans to drive cursors or prosthetic limbs directly through thoughts. As neuroprosthetic devices transition from experimental to clinical use, there is a need for fully-implantable amplification and telemetry electronics in close proximity to the recording sites. To address these needs, we developed a prototype integrated circuit for wireless neural recording from a 100-channel microelectrode array. The design of both the system-level architecture and the individual circuits were driven by severe power constraints for small implantable devices; chronically heating tissue by only a few degrees Celsius leads to cell death. Due to the high data rate produced by 100 neural signals, the system must perform data reduction as well. We use a combination of a low-power ADC and an array of "spike detectors" to reduce the transmitted data rate while preserving critical information. The complete system receives power and commands (at 6.5 kb/s) wirelessly over a 2.64-MHz inductive link and transmits neural data back at a data rate of 330 kb/s using a fully-integrated 433-MHz FSK transmitter. The 4.7times5.9 mm2 chip was fabricated in a 0.5-mum 3M2P CMOS process and consumes 13.5 mW of power. While cross-chip interference limits performance in single-chip operation, a two-chip system was used to record neural signals from a Utah Electrode Array in cat cortex and transmit the digitized signals wirelessly to a receiver

Design and Optimization of Printed Spiral Coils for Efficient Transcutaneous Inductive Power Transmission

Abstract: The next generation of implantable high-power neuroprosthetic devices such as visual prostheses and brain computer interfaces are going to be powered by transcutaneous inductive power links formed between a pair of printed spiral coils (PSC) that are batch-fabricated using micromachining technology. Optimizing the power efficiency of the wireless link is imperative to minimize the size of the external energy source, heating dissipation in the tissue, and interference with other devices. Previous design methodologies for coils made of 1-D filaments are not comprehensive and accurate enough to consider all geometrical aspects of PSCs with planar 3-D conductors as well as design constraints imposed by implantable device application and fabrication technology. We have outlined the theoretical foundation of optimal power transmission efficiency in an inductive link, and combined it with semi-empirical models to predict parasitic components in PSCs. We have used this foundation to devise an iterative PSC design methodology that starts with a set of realistic design constraints and ends with the optimal PSC pair geometries. We have executed this procedure on two design examples at 1 and 5 MHz achieving power transmission efficiencies of 41.2% and 85.8%, respectively, at 10-mm spacing. All results are verified with simulations using a commercial field solver (HFSS) as well as measurements using PSCs fabricated on printed circuit boards.

Design and Optimization of a 3-Coil Inductive Link for Efficient Wireless Power Transmission

Abstract: Inductive power transmission is widely used to energize implantable microelectronic devices (IMDs), recharge batteries, and energy harvesters. Power transfer efficiency (PTE) and power delivered to the load (PDL) are two key parameters in wireless links, which affect the energy source specifications, heat dissipation, power transmission range, and interference with other devices. To improve the PTE, a 4-coil inductive link has been recently proposed. Through a comprehensive circuit-based analysis that can guide a design and optimization scheme, we have shown that despite achieving high PTE at larger coil separations, the 4-coil inductive links fail to achieve a high PDL. Instead, we have proposed a 3-coil inductive power transfer link with comparable PTE over its 4-coil counterpart at large coupling distances, which can also achieve high PDL. We have also devised an iterative design methodology that provides the optimal coil geometries in a 3-coil inductive power transfer link. Design examples of 2-, 3-, and 4-coil inductive links have been presented, and optimized for a 13.56-MHz carrier frequency and 12-cm coupling distance, showing PTEs of 15%, 37%, and 35%, respectively. At this distance, the PDL of the proposed 3-coil inductive link is 1.5 and 59 times higher than its equivalent 2- and 4-coil links, respectively. For short coupling distances, however, 2-coil links remain the optimal choice when a high PDL is required, while 4-coil links are preferred when the driver has large output resistance or small power is needed. These results have been verified through simulations and measurements.

Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity

Abstract: We consider the problem of extracting smooth, low-dimensional neural trajectories that summarize the activity recorded simultaneously from tens to hundreds of neurons on individual experimental trials. Current methods for extracting neural trajectories involve a two-stage process: the data are first "denoised" by smoothing over time, then a static dimensionality reduction technique is applied. We first describe extensions of the two-stage methods that allow the degree of smoothing to be chosen in a principled way, and account for spiking variability that may vary both across neurons and across time. We then present a novel method for extracting neural trajectories, Gaussian-process factor analysis (GPFA), which unifies the smoothing and dimensionality reduction operations in a common probabilistic framework. We applied these methods to the activity of 61 neurons recorded simultaneously in macaque premotor and motor cortices during reach planning and execution. By adopting a goodness-of-fit metric that measures how well the activity of each neuron can be predicted by all other recorded neurons, we found that GPFA provided a better characterization of the population activity than the two-stage methods.