A multichannel wireless sEMG sensor endowing a 0.13 μm CMOS mixed-signal SoC

This paper presents a wireless multichannel surface electromyography (sEMG) sensor which features a custom 0.13μm CMOS mixed-signal system-on-chip (SoC) analog frontend circuit. The proposed sensor includes 10 sEMG recording channels with tunable bandwidth (BW) and analog-to-digital converter (ADC) resolution. The SoC includes 10x bioamplifiers, 10x 3 rd order ΔΣ MASH 1-1-1 ADC, and 10x on-chip decimation filters (DF). This SoC provides the sEMG samples data through a serial peripheral interface (SPI) bus to a microcontroller unit (MCU) that then transfers the data to a wireless transceiver. We report sEMG waveforms acquired using a custom multichannel electrode module, and a comparison with a commercial grade system. Results show that the proposed integrated wireless SoC-based system compares well with the commercial grade sEMG recording system. The sensor has an input-referred noise of 2.5 μVrms (BW of 10-500 Hz), an input-dynamic range of 6 mVpp, a programmable sampling rate of 2 ksps, for sEMG, while consuming only 7.1 μW/Ch for the SoC (w/ ADC & DF) and 21.8 mW of power for the sensor (Transceiver, MCU, etc.). The system lies on a 1.5 × 2.0 cm 2 printed circuit board and weights <; 1 g

Outan: An On-Head System for Driving micro-LED Arrays Implanted in Freely Moving Mice

In the intact brain, neural activity can be recorded using sensing electrodes and manipulated using light stimulation. Silicon probes with integrated electrodes and micro-LEDs enable the detection and control of neural activity using a single implanted device. Miniaturized solutions for recordings from small freely moving animals are commercially available, but stimulation is driven by large, stationary current sources. We designed and fabricated a current source chip and integrated it into a headstage PCB that weighs 1.37 g. The proposed system provides 10-bit resolution current control for 32 channels, driving micro-LEDs with up to 4.6 V and sourcing up to 0.9 mA at a refresh rate of 5 kHz per channel. When calibrated against a micro-LED probe, the system allows linear control of light output power, up to 10 micro-W per micro-LED. To demonstrate the capabilities of the system, synthetic sequences of neural spiking activity were produced by driving multiple micro-LEDs implanted in the hippocampal CA1 area of a freely moving mouse. The high spatial, temporal, and amplitude resolution of the system provides a rich variety of stimulation patterns. Combined with commercially available sampling headstages, the system provides an easy to use back-end, fully utilizing the bi-directional potential of integrated opto-electronic arrays.Comment: 11 pages, 9 figure

Bidirectional Neural Interface Circuits with On-Chip Stimulation Artifact Reduction Schemes

Bidirectional neural interfaces are tools designed to “communicate” with the brain via recording and modulation of neuronal activity. The bidirectional interface systems have been adopted for many applications. Neuroscientists employ them to map neuronal circuits through precise stimulation and recording. Medical doctors deploy them as adaptable medical devices which control therapeutic stimulation parameters based on monitoring real-time neural activity. Brain-machine-interface (BMI) researchers use neural interfaces to bypass the nervous system and directly control neuroprosthetics or brain-computer-interface (BCI) spellers. In bidirectional interfaces, the implantable transducers as well as the corresponding electronic circuits and systems face several challenges. A high channel count, low power consumption, and reduced system size are desirable for potential chronic deployment and wider applicability. Moreover, a neural interface designed for robust closed-loop operation requires the mitigation of stimulation artifacts which corrupt the recorded signals. This dissertation introduces several techniques targeting low power consumption, small size, and reduction of stimulation artifacts. These techniques are implemented for extracellular electrophysiological recording and two stimulation modalities: direct current stimulation for closed-loop control of seizure detection/quench and optical stimulation for optogenetic studies. While the two modalities differ in their mechanisms, hardware implementation, and applications, they share many crucial system-level challenges. The first method aims at solving the critical issue of stimulation artifacts saturating the preamplifier in the recording front-end. To prevent saturation, a novel mixed-signal stimulation artifact cancellation circuit is devised to subtract the artifact before amplification and maintain the standard input range of a power-hungry preamplifier. Additional novel techniques have been also implemented to lower the noise and power consumption. A common average referencing (CAR) front-end circuit eliminates the cross-channel common mode noise by averaging and subtracting it in analog domain. A range-adapting SAR ADC saves additional power by eliminating unnecessary conversion cycles when the input signal is small. Measurements of an integrated circuit (IC) prototype demonstrate the attenuation of stimulation artifacts by up to 42 dB and cross-channel noise suppression by up to 39.8 dB. The power consumption per channel is maintained at 330 nW, while the area per channel is only 0.17 mm2. The second system implements a compact headstage for closed-loop optogenetic stimulation and electrophysiological recording. This design targets a miniaturized form factor, high channel count, and high-precision stimulation control suitable for rodent in-vivo optogenetic studies. Monolithically integrated optoelectrodes (which include 12 µLEDs for optical stimulation and 12 electrical recording sites) are combined with an off-the-shelf recording IC and a custom-designed high-precision LED driver. 32 recording and 12 stimulation channels can be individually accessed and controlled on a small headstage with dimensions of 2.16 x 2.38 x 0.35 cm and mass of 1.9 g. A third system prototype improves the optogenetic headstage prototype by furthering system integration and improving power efficiency facilitating wireless operation. The custom application-specific integrated circuit (ASIC) combines recording and stimulation channels with a power management unit, allowing the system to be powered by an ultra-light Li-ion battery. Additionally, the µLED drivers include a high-resolution arbitrary waveform generation mode for shaping of µLED current pulses to preemptively reduce artifacts. A prototype IC occupies 7.66 mm2, consumes 3.04 mW under typical operating conditions, and the optical pulse shaping scheme can attenuate stimulation artifacts by up to 3x with a Gaussian-rise pulse rise time under 1 ms.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147674/1/mendrela_1.pd

Physical principles for scalable neural recording

Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power–bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices