Devices such as keyboards and touchscreens allow humans to communicate with machines. Neural interfaces, which can provide a direct, electrical bridge between analogue nervous systems and digital man-made systems, could provide a more efficient route to future information exchange. Here we review the development of electronic neural interfaces. The interfaces typically consist of three modules — a tissue interface, a sensing interface, and a neural signal processing unit — and based on technical milestones in the development of the electronic sensing interface, we group and analyse the interfaces in four generations: the patch clamp technique, multi-channel neural interfaces, implantable/wearable neural interfaces and integrated neural interfaces. We also consider key circuit and system challenges in the design of neural interfaces and explore the opportunities that arise with the latest technology This Review Article examines the development of neural interfaces, which can provide a direct, electrical bridge between analogue human nervous systems and digital man-made devices, considering challenges and opportunities created with such technology.

Electronic neural interfaces

This article presents a Gm-C-based continuous-time delta–sigma modulator (CTDSM) for artifact-tolerant neural recording interfaces. We propose the feedback-assisted Gm linearization technique, which is applied to the first Gm-C integrator by using a resistive feedback digital-to-analog converter (DAC) in parallel to the degeneration resistor of the input Gm. This enables the input Gm to process the quantization noise, thereby improving the input range and linearity of the Gm-C-based CTDSM, significantly. An energy-efficient second-order loop filter is realized by using a voltage-controlled oscillator (VCO) as the second integrator and a phase quantizer. A proportional–integral (PI) transfer function is employed at the first integrator, which minimizes the output swing while maintaining loop stability. Fabricated in a 110-nm CMOS process, the prototype CTDSM achieves a high input impedance, 300-mVpp linear input range, 80.4-dB signal-to-noise and distortion ratio (SNDR), 81-dB dynamic range (DR), and 76-dB common-mode rejection ratio (CMRR) and consumes only 6.5 $\mu \text{W}$ with a signal bandwidth of 10 kHz. This corresponds to a figure of merit (FoM) of 172.3 dB, which is the state of the art among the neural recording ADCs. This work is also validated through the in vivo experiment.

A 6.5- μ W 10-kHz BW 80.4-dB SNDR G m -C-Based CT ∆∑ Modulator With a Feedback-Assisted G m Linearization for Artifact-Tolerant Neural Recording

A single-chip, bidirectional brain–computer interface (BBCI) enables neuromodulation through simultaneous neural recording and stimulation. This article presents a prototype BBCI application-specified integrated circuit (ASIC) consisting of a 64-channel time-multiplexed recording front-end, an area-optimized four-channel high-voltage compliant stimulator, and electronics to support the concurrent multi-channel stimulus artifact cancellation. Stimulator power generation is integrated on a chip, providing ±11-V compliance from low-voltage supplies with a resonant charge pump. High-frequency (~3 GHz) self-resonant clocking is used to reduce the pumping capacitor area while suppressing the associated switching losses. A 32-tap least mean square (LMS)-based digital adaptive filter achieves 60-dB artifact suppression, enabling simultaneous neural stimulation and recording. The entire chip occupies 4 mm2 in a 65-nm low power (LP) process and is powered by 2.5-/1.2-V supplies, dissipating $205~\mu \text{W}$ in recording and $142~\mu \text{W}$ in the stimulation and cancellation back-ends. The stimulation output drivers achieve 31% dc–dc efficiency at a maximum output power of 24 mW.

A Single-Chip Bidirectional Neural Interface With High-Voltage Stimulation and Adaptive Artifact Cancellation in Standard CMOS

The bidirectional neural interface is essential to realize the closed-loop neuromodulation, which is the core of next-generation neurological devices. For the bidirectional neural interface, a recording circuit with a high dynamic range (DR) is required to record the neural signal while stimulating the neuronal cells simultaneously. This article presents a voltage-controlled oscillator (VCO)-based neural-recording IC, which directly quantizes the input signal and achieves a large DR to process the small-amplitude neural signal in the presence of the large-amplitude stimulation artifact (SA). A feedback-controlled source degeneration is applied to the input transconductor circuit ( $G_{\mathrm {m, in}}$ ) by using a resistor digital-to-analog converter (R-DAC). It mitigates the circuit nonlinearity, resulting in a large signal-to-noise-and-distortion ratio (SNDR) and a high input impedance ( $Z_{\mathrm {in}}$ ). The implemented neural-recording IC achieves 81.3-dB SNDR over 200-Hz signal bandwidth and 200-mVpp maximum allowable input range with consuming 3.9 $\mu \text{W}$ per channel. The in-vitro measurement with prerecorded neural signal demonstrates that the original neural signal is well preserved in the presence of the large-amplitude artifact without any saturation or significant distortion.

A High DR, DC-Coupled, Time-Based Neural-Recording IC With Degeneration R-DAC for Bidirectional Neural Interface

Flexible electronics are compatible with film substrates that are soft and stretchable, resulting in conformal integration with human body. Integrated with various sensors and communication ICs, wearable flexible electronics are able to effectively track human vital signs without affecting the body activities. Such a wearable flexible system contains a sensor, a front-end amplifier (FEA), an analog-to-digital converter (ADC), a micro-controller unit (MCU), a radio, a power management unit (PMU), where the radio is the design bottleneck due to its high power consumption. Different from conventional wireless communications, body channel communication (BCC) uses the human body surface as the signal transmission medium resulting in less signal loss and low power consumption. However, there are some design challenges in BCC, including body channel model, backward loss, variable contact impedance, stringent spectral mask, crystalless design, body antenna effect, etc. In this paper, we conduct a survey on BCC transceiver, and analyze its potential role and challenges in wearable flexible electronics.

The Role and Challenges of Body Channel Communication in Wearable Flexible Electronics

This paper presents a direct-digital-conversion biopotential-recording front-end with 92.3dB dynamic range at an input range of $360\text{mV}_{\text{pp}}$. The proposed front-end is a capacitively - coupled 3rd-order Gm-C CT $\Delta\Sigma \text{M}$ with a 5-bit SAR quantizer. The capacitively-coupled summing circuit increases linearity of the $\Delta\Sigma \text{M}$, and a 3rd-order Gm-C loop filter and a 5-bit SAR ADC reduces quantization noise level. The proposed front-end is fabricated in $0.18\mu \text{m}$ CMOS, and achieves 91.3dB SNDR and $1.8\mu \text{V}_{\text{rms}}$ input-referred noise over 100Hz BW. Also, an in-vitro LFP recording is performed to verify the front-end.

6.5µW 92.3DB-DR Biopotential-Recording Front-End with 360MV PP Linear Input Range

Despite rapid advancements in our electronics industry, connecting our minds to machines (e.g., robots and computers) through brain-machine interface (BMI) technologies remains an unfulfilled human ambition. Voice-free interaction with unplugged holographic displays, controlling a computer mouse hands free, downloading our minds onto artificial intelligence chips, and uploading knowledge or skills into our brain still reside in the realm of research or imagination.

Plugging Electronics Into Minds: Recent Trends and Advances in Neural Interface Microsystems

A galvanically-coupled body-channel communication (GCBCC) transceiver (TRX) is proposed for bionic arms, offering robust communication and human-body safety. The GC-BCC mitigates the influence from the environmental changes and disturbances. A simple termination at the RX input widens the channel bandwidth (BW), enabling 100Mb/s communication. The implantable TX guarantees the user’s safety by employing a current-regulating channel driver, a charge-balancing scheme, and a biphasic waveform generated by bipolar RZ (BRZ) encoding. The TRX IC fabricated in 0.18 mm CMOS, achieves a low bit-error rate (BER) of 10-9 with excellent TX and RX energy efficiencies of 4.75pJ/b and 26.8pJ/b, respectively.

A 100Mb/s Galvanically-Coupled Body-Channel-Communication Transceiver with 4.75pJ/b TX and 26.8 pJ/b RX for Bionic Arms

The capacitively coupled instrumentation amplifier (CCIA) is broadly used for neural signal acquisition. Although it is suitable for various biopotential recording applications, the CCIA is vulnerable to capacitor mismatches, which degrades the common-mode rejection ratio (CMRR). The neural signals with small amplitude can be easily contaminated by large-amplitude common-mode (CM) interferences due to the degraded CMRR. This brief presents a CMRR enhancement circuit for the CCIA, with which the capacitor mismatches can be compensated in a power-efficient manner. In the proposed CCIA, the gains of a pair of output stages are controlled separately to reject the output signals generated by the CM interferers in the presence of capacitor mismatches. Employing the proposed CMRR enhancement scheme, the implemented CCIA achieves a CMRR over 90 dB from 10 Hz to 1 kHz and 3.4- $\mu \text{V}_{\mathrm{ rms}}$ integrated input-referred noise (IRN) while only consuming $1.5~\mu \text{W}$ per channel.

Hyuntak Jeon

Papers

A High DR, DC-Coupled, Time-Based Neural-Recording IC With Degeneration R-DAC for Bidirectional Neural Interface

6.5µW 92.3DB-DR Biopotential-Recording Front-End with 360MV PP Linear Input Range

Plugging Electronics Into Minds: Recent Trends and Advances in Neural Interface Microsystems

A 100Mb/s Galvanically-Coupled Body-Channel-Communication Transceiver with 4.75pJ/b TX and 26.8 pJ/b RX for Bionic Arms

A CMRR Enhancement Circuit Employing Gₘ-Controllable Output Stages for Capacitively Coupled Instrumentation Amplifiers