A Miniaturized 256-Channel Neural Recording Interface with Area-Efficient Hybrid Integration of Flexible Probes and CMOS Integrated Circuits

Modeling and Analysis of Environmental Electromagnetic Interference in Multiple-Channel Neural Recording Systems for High Common-Mode Interference Rejection Performance

Environmental electromagnetic interference (EMI) has always been a major interference source for multiple-channel neural recording systems, and little theoretical work has been attempted to address it. In this paper, equivalent circuit models are proposed to model both electromagnetic interference sources and neural signals in such systems, and analysis has been performed to generate the design guidelines for neural probes and the subsequent recording circuit towards higher common-mode interference (CMI) rejection performance while maintaining the recorded neural action potential (AP) signal quality. In vivo animal experiments with a configurable 32-channel neural recording system are carried out to validate the proposed models and design guidelines. The results show the power spectral density (PSD) of environmental 50 Hz EMI interference is reduced by three orders from 4.43 × 10-3 V2/Hz to 4.04 × 10-6 V2/Hz without affecting the recorded AP signal quality in an unshielded experiment environment.

Self-Assembled Origami Neural Probes for Scalable, Multifunctional, Three-Dimensional Neural Interface

Flexible intracortical neural probes have drawn attention for their enhanced longevity in high-resolution neural recordings due to reduced tissue reaction. However, the conventional monolithic fabrication approach has met significant challenges in: (i) scaling the number of recording sites for electrophysiology; (ii) integrating of other physiological sensing and modulation; and (iii) configuring into three-dimensional (3D) shapes for multi-sided electrode arrays. We report an innovative self-assembly technology that allows for implementing flexible origami neural probes as an effective alternative to overcome these challenges. By using magnetic-field-assisted hybrid self-assembly, multiple probes with various modalities can be stacked on top of each other with precise alignment. Using this approach, we demonstrated a multifunctional device with scalable high-density recording sites, dopamine sensors and a temperature sensor integrated on a single flexible probe. Simultaneous large-scale, high-spatial-resolution electrophysiology was demonstrated along with local temperature sensing and dopamine concentration monitoring. A high-density 3D origami probe was assembled by wrapping planar probes around a thin fiber in a diameter of 80∼105 μm using optimal foldable design and capillary force. Directional optogenetic modulation could be achieved with illumination from the neuron-sized micro-LEDs (μLEDs) integrated on the surface of 3D origami probes. We could identify angular heterogeneous single-unit signals and neural connectivity 360° surrounding the probe. The probe longevity was validated by chronic recordings of 64-channel stacked probes in behaving mice for up to 140 days. With the modular, customizable assembly technologies presented, we demonstrated a novel and highly flexible solution to accommodate multifunctional integration, channel scaling, and 3D array configuration.

Power-Efficient LFP-Adaptive Dynamic Zoom-and-Track Incremental ΔΣ Front-End for Dual-Band Subcortical Recordings

We report a power-efficient analog front-end integrated circuit (IC) for multi-channel, dual-band subcortical recordings. In order to achieve high-resolution multi-channel recordings with low power consumption, we implemented an incremental ΔΣ ADC (IADC) with a dynamic zoom-and-track scheme. This scheme continuously tracks local field potential (LFP) and adaptively adjusts the input dynamic range (DR) into a zoomed sub-LFP range to resolve tiny action potentials. Thanks to the reduced DR, the oversampling rate of the IADC can be reduced by 64.3% compared to the conventional approach, leading to significant power reduction. In addition, dual-band recording can be easily attained because the scheme continuously tracks LFPs without additional on-chip hardware. A prototype four-channel front-end IC has been fabricated in 180 nm standard CMOS processes. The IADC achieved 11.3-bit ENOB at 6.8 μW, resulting in the best Walden and SNDR FoMs, 107.9 fJ/c-s and 162.1 dB, respectively, among two different comparison groups: the IADCs reported up to date in the state-of-the-art neural recording front-ends; and the recent brain recording ADCs using similar zooming or tracking techniques to this work. The intrinsic dual-band recording feature reduces the post-processing FPGA resources for subcortical signal band separation by >45.8%. The front-end IC with the zoom-and-track IADC showed an NEF of 5.9 with input-referred noise of 8.2 μVrms, sufficient for subcortical recording. The performance of the whole front-end IC was successfully validated through in vivo animal experiments.

A CMOS-based highly scalable flexible neural electrode interface

Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. However, existing electrophysiological devices are limited by their scalability in capturing this cortex-wide activity. Here, we developed an electrode connector based on an ultra-conformable thin-film electrode array that self-assembles onto silicon microelectrode arrays enabling multithousand channel counts at a millimeter scale. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed Flex2Chip. Capillary-assisted assembly drives the pads to deform toward the chip surface, and van der Waals forces maintain this deformation, establishing Ohmic contact. Flex2Chip arrays successfully measured extracellular action potentials ex vivo and resolved micrometer scale seizure propagation trajectories in epileptic mice. We find that seizure dynamics in absence epilepsy in the Scn8a+/- model do not have constant propagation trajectories.

Emerging Penetrating Neural Electrodes: In Pursuit of Large Scale and Longevity

Penetrating neural electrodes provide a powerful approach to decipher brain circuitry by allowing for time-resolved electrical detections of individual action potentials. This unique capability has contributed tremendously to basic and translational neuroscience, enabling both fundamental understandings of brain functions and applications of human prosthetic devices that restore crucial sensations and movements. However, conventional approaches are limited by the scarce number of available sensing channels and compromised efficacy over long-term implantations. Recording longevity and scalability have become the most sought-after improvements in emerging technologies. In this review, we discuss the technological advances in the past 5-10 years that have enabled larger-scale, more detailed, and longer-lasting recordings of neural circuits at work than ever before. We present snapshots of the latest advances in penetration electrode technology, showcase their applications in animal models and humans, and outline the underlying design principles and considerations to fuel future technological development.

Electrochemical and electrophysiological considerations for clinical high channel count neural interfaces

Electrophysiological recording and stimulation are the gold standard for functional mapping during surgical and therapeutic interventions as well as capturing cellular activity in the intact human brain. A critical component probing human brain activity is the interface material at the electrode contact that electrochemically transduces brain signals to and from free charge carriers in the measurement system. Here, we summarize state-of-the-art electrode array systems in the context of translation for use in recording and stimulating human brain activity. We leverage parametric studies with multiple electrode materials to shed light on the varied levels of suitability to enable high signal-to-noise electrophysiological recordings as well as safe electrophysiological stimulation delivery. We discuss the effects of electrode scaling for recording and stimulation in pursuit of high spatial resolution, channel count electrode interfaces, delineating the electrode-tissue circuit components that dictate the electrode performance. Finally, we summarize recent efforts in the connectorization and packaging for high channel count electrode arrays and provide a brief account of efforts toward wireless neuronal monitoring systems.

A Wireless Headstage System Based on Neural-Recording Chip Featuring 315 nW Kickback-Reduction SAR ADC

Wireless neural-recording instruments eliminate the bulky cables in multi-channel signal transmission, while the system size should be reduced to mitigate the impact on freely-moving animals. As the battery usually dominates the system size, the neural-recording chip should be low power to minimize the battery in long-termly monitoring. In general, a neural-recording chip consists of an analog front end (AFE) and an 8 bit -10 bit analog-to-digital converter (ADC), while it's challenging to design an ADC with an 8 -10 effective number of bits (ENOB) and sub- μ W power consumption due to the kickback noise. In this work, we propose a kickback-reduction technique for a successive-approximation-register (SAR) ADC based on neural-recording chip. Fabricated in 65 nm CMOS process, the proposed technique reduce the ADC power to 315 nW, resulting in an 8-channel neural-recording chip with 249 μW in total. Measured results show that the chip achieves an ADC ENOB of 9.73 bits, as well as an AFE gain of 43.3 dB and input-referred noise (IRN) of 9.68 μV_rms in a bandwidth of 0.9 Hz -7.2 kHz. Combined with a BLE chip and a PCB antenna, the chip is implemented into a 2.6 g wireless headstage system (w/o battery), and an in-vivo demonstration is conducted on a male Sprague-Dawley rat with Parkinson's disease. The headstage system transfers the in-vivo neural signals to a commodity smartphone through BLE, and the miniature size induces little impact on freely-moving activities.

A 3.1-5.2GHz, Energy-Efficient Single Antenna, Cancellation-Free, Bitwise Time-Division Duplex Transceiver for High Channel Count Optogenetic Neural Interface

We report an energy-efficient, cancellation-free, bit-wise time-division duplex (B-TDD) transceiver (TRX) for real-time closed-loop control of high channel count neural interfaces. The proposed B-TDD architecture consists of a duty-cycled ultra-wide band (UWB) transmitter (3.1-5 GHz) and a switching U-NII band (5.2 GHz) receiver. An energy-efficient duplex is realized in a single antenna without power-hungry self-interference cancellation circuits which are prevalently used in the conventional full-duplex, single antenna transceivers. To suppress the interference between up- and down-links and enhance the isolation between the two, we devised a fast-switching scheme in a low noise amplifier and used 5× oversampling with a built-in winner-take-all voting in the receiver. The B-TDD transceiver was fabricated in 65 nm CMOS RF process, achieving low energy consumption of 0.32 nJ/b at 10 Mbps in the receiver and 9.7 pJ/b at 200 Mbps in the transmitter, respectively. For validation, the B-TDD TRX has been integrated with a μLED optoelectrode and a custom analog frontend integrated circuit in a prototype wireless bidirectional neural interface system. Successful in-vivo operation for simultaneously recording broadband neural signals and optical stimulation was demonstrated in a transgenic rodent.