A Wireless Neural Stimulator IC for Cortical Visual Prosthesis.

We propose a 0.25 × 0.25 × 0.3 mm (~0.02 mm3) optically powered mote for visual cortex stimulation to restore vision. Up to 1024 implanted motes can be individually addressed. The complete StiMote system was confirmed fully functional when optically powered and cortex stimulation was confirmed in-vivo with a live rat brain.

A 21.4 pW Subthreshold Voltage Reference with 0.020 %/V Line Sensitivity Using DIBL Compensation.

This paper presents an ultra-low-power voltage reference designed in 180 nm CMOS technology. To achieve near-zero line sensitivity, a two-transistor (2-T) voltage reference is biased with a current source to cancel the drain-induced barrier-lowering (DIBL) effect of the 2-T core, thus improving the line sensitivity. This compensation circuit achieves a Monte-Carlo-simulated line sensitivity of 0.035 %/V in a supply range of 0.6 to 1.8 V, while generating a reference voltage of 307.8 mV, with 21.4 pW power consumption. The simulated power supply rejection ratio (PSRR) is -54 dB at 100 Hz. It also achieves a temperature coefficient of 24.8 ppm/°C in a temperature range of -20 to 80 °C, with a projected area of 0.003 mm2.

A Light-Tolerant Wireless Neural Recording IC for Motor Prediction With Near-Infrared-Based Power and Data Telemetry.

Miniaturized and wireless near-infrared (NIR) based neural recorders with optical powering and data telemetry have been introduced as a promising approach for safe long-term monitoring with the smallest physical dimension among state-of-the-art standalone recorders. However, a main challenge for the NIR based neural recording ICs is to maintain robust operation in the presence of light-induced parasitic short circuit current from junction diodes. This is especially true when the signal currents are kept small to reduce power consumption. In this work, we present a light-tolerant and low-power neural recording IC for motor prediction that can fully function in up to 300 µW/mm2 of light exposure. It achieves best-in-class power consumption of 0.57 µW at 38° C with a 4.1 NEF pseudo-resistorless amplifier, an on-chip neural feature extractor, and individual mote level gain control. Applying the 20-channel pre-recorded neural signals of a monkey, the IC predicts finger position and velocity with correlation coefficient up to 0.870 and 0.569, respectively, with individual mote level gain control enabled. In addition, wireless measurement is demonstrated through optical power and data telemetry using a custom PV/LED GaAs chip wire bonded to the proposed IC.

A low-power communication scheme for wireless, 1000 channel brain-machine interfaces.

Objective. Brain-machine interfaces (BMIs) have the potential to restore motor function but are currently limited by electrode count and long-term recording stability. These challenges may be solved through the use of free-floating 'motes' which wirelessly transmit recorded neural signals, if power consumption can be kept within safe levels when scaling to thousands of motes. Here, we evaluated a pulse-interval modulation (PIM) communication scheme for infrared (IR)-based motes that aims to reduce the wireless data rate and system power consumption.Approach. To test PIM's ability to efficiently communicate neural information, we simulated the communication scheme in a real-time closed-loop BMI with non-human primates. Additionally, we performed circuit simulations of an IR-based 1000-mote system to calculate communication accuracy and total power consumption.Main results. We found that PIM at 1 kb/s per channel maintained strong correlations with true firing rate and matched online BMI performance of a traditional wired system. Closed-loop BMI tests suggest that lags as small as 30 ms can have significant performance effects. Finally, unlike other IR communication schemes, PIM is feasible in terms of power, and neural data can accurately be recovered on a receiver using 3 mW for 1000 channels.Significance.These results suggest that PIM-based communication could significantly reduce power usage of wireless motes to enable higher channel-counts for high-performance BMIs.

Bridging the"Last Millimeter" Gap of Brain-Machine Interfaces via Near-Infrared Wireless Power Transfer and Data Communications.

Arrays of floating neural sensors with high channel count that cover an area of square centimeters and larger would be transformative for neural engineering and brain-machine interfaces. Meeting the power and wireless data communications requirements within the size constraints for each neural sensor has been elusive due to the need to incorporate sensing, computing, communications, and power functionality in a package of approximately 100 micrometers on a side. In this work, we demonstrate a near infrared optical power and data communication link for a neural recording system that satisfies size requirements to achieve dense arrays and power requirements to prevent tissue heating. The optical link is demonstrated using an integrated optoelectronic device consisting of a tandem photovoltaic cell and microscale light emitting diode. End-to-end functionality of a wireless neural link within system constraints is demonstrated using a pre-recorded neural signal between a self-powered CMOS integrated circuit and single photon avalanche photodiode.

A Light Tolerant Neural Recording IC for Near-Infrared-Powered Free Floating Motes.

A key challenge for near-infrared (NIR) powered neural recording ICs is to maintain robust operation in the presence of parasitic short circuit current from junction diodes when exposed to light. This is especially so when intentional currents are kept small to reduce power consumption. We present a neural recording IC that is tolerant up to 300 µW/mm2 light exposure (above tissue limit) and consumes 0.57 µW at 38°C, making it lowest power among standalone motes while incorporating on-chip feature extraction and individual gain control.

A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain-machine interfaces.

The large power requirement of current brain-machine interfaces is a major hindrance to their clinical translation. In basic behavioural tasks, the downsampled magnitude of the 300-1,000 Hz band of spiking activity can predict movement similarly to the threshold crossing rate (TCR) at 30 kilo-samples per second. However, the relationship between such a spiking-band power (SBP) and neural activity remains unclear, as does the capability of using the SBP to decode complicated behaviour. By using simulations of recordings of neural activity, here we show that the SBP is dominated by local single-unit spikes with spatial specificity comparable to or better than that of the TCR, and that the SBP correlates better with the firing rates of lower signal-to-noise-ratio units than the TCR. With non-human primates, in an online task involving the one-dimensional decoding of the movement of finger groups and in an offline two-dimensional cursor-control task, the SBP performed equally well or better than the TCR. The SBP may enhance the decoding performance of neural interfaces while enabling substantial cuts in power consumption.

A 380pW Dual Mode Optical Wake-up Receiver with Ambient Noise Cancellation.

We present a sub-nW optical wake-up receiver for wireless sensor nodes. The wake-up receiver supports dual mode operation for both ultra-low standby power and high data rates, while canceling ambient in-band noise. In 0.18µm CMOS the receiver consumes 380pW in always-on wake-up mode and 28.1µW in fast RX mode at 250kbps.

A 99nW 70.4kHz Resistive Frequency Locking On-Chip Oscillator with 27.4ppm/°C Temperature Stability.

We present a low power on-chip oscillator for system-on-chip designs. The oscillator introduces a resistive frequency locking loop topology where the equivalent resistance of a switched-capacitor is matched to a temperature-compensated resistor. The approach eliminates the traditional comparator from the oscillation loop, which consumes significant power and limits temperature stability in conventional relaxation oscillators. The oscillator is fabricated in 0.18µm CMOS and exhibits 27.4ppm/°C and <7ppm long-term stability while consuming 99.4nW at 70.4 kHz.