Stimulation and Artifact-Suppression Techniques for In Vitro High-Density Microelectrode Array Systems

Brain Feature Extraction With an Artifact-Tolerant Multiplexed Time-Encoding Neural Frontend for True Real-Time Closed-Loop Neuromodulation

Closed-loop neuromodulation is emerging as a more effective and targeted solution for the treatment of neurological symptoms compared to traditional open-loop stimulation. The majority of the present designs lack the ability to continuously record brain activity during electrical stimulation; hence they cannot fully monitor the treatment's effectiveness. This is due to the large stimulation artifacts that can saturate the sensitive readout circuits. To overcome this challenge, this work presents a rapid-artifact-recovery time-multiplexed neural readout frontend in combination with backend linear interpolation to reconstruct the artifact-corrupted local field potentials' (LFP) features. Our hybrid technique is an alternative approach to avoid power-hungry large-dynamic-range readout architectures or large and complex artifact template subtraction circuits. We discuss the design and measurements of a prototype implementation of the proposed readout frontend in 180-nm CMOS. It combines time multiplexing and time-domain conversion in a novel 13-bit incremental ADC, requiring only 0.0018 mm2/channel of readout area despite the large 180-nm CMOS process used, while consuming only 4.51 μW/channel. This is the smallest reported area for stimulation-voltage-compatible technologies (i.e. ≥ 65 nm). The frontend also yields a best-in-class peak total harmonic distortion of -72.6 dB @2.5-mVpp input, thanks to its implicit DAC mismatch-error shaping property. We employ the chip to measure brain LFP signals corrupted with artifacts, then perform linear interpolation and feature extraction on the measured signals and evaluate the reconstruction quality, using a set of sixteen commonly used features and three stimulation scenarios. The results show relative accuracies above 95% with respect to the situation without artifacts. This work is an ideal candidate for integration in high-channel-count true closed-loop neuromodulation systems.

Anti-artifacts techniques for neural recording front-ends in closed-loop brain-machine interface ICs

In recent years, thanks to the development of integrated circuits, clinical medicine has witnessed significant advancements, enabling more efficient and intelligent treatment approaches. Particularly in the field of neuromedical, the utilization of brain-machine interfaces (BMI) has revolutionized the treatment of neurological diseases such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. The BMI acquires neural signals via recording circuits and analyze them to regulate neural stimulator circuits for effective neurological treatment. However, traditional BMI designs, which are often isolated, have given way to closed-loop brain-machine interfaces (CL-BMI) as a contemporary development trend. CL-BMI offers increased integration and accelerated response speed, marking a significant leap forward in neuromedicine. Nonetheless, this advancement comes with its challenges, notably the stimulation artifacts (SA) problem inherent to the structural characteristics of CL-BMI, which poses significant challenges on the neural recording front-ends (NRFE) site. This paper aims to provide a comprehensive overview of technologies addressing artifacts in the NRFE site within CL-BMI. Topics covered will include: (1) understanding and assessing artifacts; (2) exploring the impact of artifacts on traditional neural recording front-ends; (3) reviewing recent technological advancements aimed at addressing artifact-related issues; (4) summarizing and classifying the aforementioned technologies, along with an analysis of future trends.

Multiphysics simulation of magnetoelectric micro core-shells for wireless cellular stimulation therapy via magnetic temporal interference

This paper presents an innovative approach to wireless cellular stimulation therapy through the design of a magnetoelectric (ME) microdevice. Traditional electrophysiological stimulation techniques for neural and deep brain stimulation face limitations due to their reliance on electronics, electrode arrays, or the complexity of magnetic induction. In contrast, the proposed ME microdevice offers a self-contained, controllable, battery-free, and electronics-free alternative, holding promise for targeted precise stimulation of biological cells and tissues. The designed microdevice integrates core shell ME materials with remote coils which applies magnetic temporal interference (MTI) signals, leading to the generation of a bipolar local electric stimulation current operating at low frequencies which is suitable for precise stimulation. The nonlinear property of the magnetostrictive core enables the demodulation of remotely applied high-frequency electromagnetic fields, resulting in a localized, tunable, and manipulatable electric potential on the piezoelectric shell surface. This potential, triggers electrical spikes in neural cells, facilitating stimulation. Rigorous computational simulations support this concept, highlighting a significantly high ME coupling factor generation of 550 V/m·Oe. The high ME coupling is primarily attributed to the operation of the device in its mechanical resonance modes. This achievement is the result of a carefully designed core shell structure operating at the MTI resonance frequencies, coupled with an optimal magnetic bias, and predetermined piezo shell thickness. These findings underscore the potential of the engineered ME core shell as a candidate for wireless and minimally invasive cellular stimulation therapy, characterized by high resolution and precision. These results open new avenues for injectable material structures capable of delivering effective cellular stimulation therapy, carrying implications across neuroscience medical devices, and regenerative medicine.

Programmable Electrochemical Stimulation on a Large-Scale CMOS Microelectrode Array

In this paper we present spatio-temporally controlled electrochemical stimulation of aqueous samples using an integrated CMOS microelectrode array with 131,072 pixels. We demonstrate programmable gold electrodeposition in arbitrary spatial patterns, controllable electrolysis to produce microscale hydrogen bubbles, and spatially targeted electrochemical pH modulation. Dense spatially-addressable electrochemical stimulation is important for a wide range of bioelectronics applications.

Overcoming temporal dispersion for measurement of activity-related impedance changes in unmyelinated nerves

Objective.Fast neural electrical impedance tomography is an imaging technique that has been successful in visualising electrically evoked activity of myelinated fibres in peripheral nerves by measurement of the impedance changes (dZ) accompanying excitation. However, imaging of unmyelinated fibres is challenging due to temporal dispersion (TP) which occurs due to variability in conduction velocities of the fibres and leads to a decrease of the signal below the noise with distance from the stimulus. To overcome TP and allow electrical impedance tomography imaging in unmyelinated nerves, a new experimental and signal processing paradigm is required allowing dZ measurement further from the site of stimulation than compound neural activity is visible. The development of such a paradigm was the main objective of this study.Approach.A finite element-based statistical model of TP in porcine subdiaphragmatic nerve was developed and experimentally validatedex-vivo. Two paradigms for nerve stimulation and processing of the resulting data-continuous stimulation and trains of stimuli, were implemented; the optimal paradigm for recording dispersed dZ in unmyelinated nerves was determined.Main results.While continuous stimulation and coherent spikes averaging led to higher signal-to-noise ratios (SNRs) at close distances from the stimulus, stimulation by trains was more consistent across distances and allowed dZ measurement at up to 15 cm from the stimulus (SNR = 1.8 ± 0.8) if averaged for 30 min.Significance.The study develops a method that for the first time allows measurement of dZ in unmyelinated nerves in simulation and experiment, at the distances where compound action potentials are fully dispersed.

A Charge Balanced Neural Stimulator Silicon Chip for Human-Machine Interface

This paper proposes a neural stimulator silicon chip design with an improved charge balancing technology. The proposed neural stimulation integrated circuit (IC) uses two charge balancing modules including synchronous charge detection module and short-time pulse insertion module. The synchronous charge detection module is designed based on a current splitter with ultra-small output current and an integrator circuit for neural stimulation pulse width control, which greatly reduces the residual charge remained on the electrode-tissue interface. The short-time pulse insertion module is designed based on the electrode voltage detection and compensation current control, which further reduces the accumulated residual charge and keeps the electrode voltage within a safety range of ±25 mV during multiple stimulation cycles. Finally, this neural stimulator is implemented in TSMC 0.18-μm CMOS process technology, and the chip function is tested and verified in both experiments with the electrode-tissue RC model and the PBS saline solution environment. The measurement result shows the neural stimulator chip achieves improved charge balancing with the residual charge smaller than 0.95 nC, which is the lowest compared to the traditional neural stimulator chips.

A Closed-Loop Neuromodulation Chipset With 2-Level Classification Achieving 1.5-Vpp CM Interference Tolerance, 35-dB Stimulation Artifact Rejection in 0.5ms and 97.8%-Sensitivity Seizure Detection

This work presents an 8-channel closed-loop neuromodulation chipset with 2-level seizure classification. The power-consuming fine classifier is only enabled when the coarse classifier in the frontend chip judges the patient's status as "suspected seizure". This scheme can reduce the overall power consumption extensively since seizure usually occurs with very low possibility. In the capacitive-coupled instrument amplifier (CCIA) of the front-end IC, a feedback based common-mode (CM) cancellation circuit is proposed to suppress large-scale CM interferences and the stimulation artifacts are suppressed by a mixed-signal loop with fast response. An auto-zero based pre- charge path is adopted to boost the input impedance, while the electrode DC offset is canceled by a DC servo loop with very-large and accurate time constant. The 2.32-mm² front-end chip and 3.51-mm² DSP chip implemented in 0.18 μm CMOS are applied in a deep-brain stimulation (DBS) neuromodulator. Measurement results show that the CCIA can suppress 1.5-Vpp CM interference, and achieve an accurate high-pass corner frequency as low as 0.1 Hz and an input impedance greater than 2.2 GΩ. The overall classifier achieves 97.8% sensitivity and consumes only 1.16-μW average power for the CHB-MIT database test. The chipset has been verified by in vivo measurement, showing that the stimulation artifact can be suppressed by 35 dB within 0.5 ms.

Thermoplastic microfluidic bioreactors with integrated electrodes to study tumor treating fields on yeast cells

Tumor-treating fields (TTFields) are alternating electrical fields of intermediate frequency and low intensity that can slow or inhibit tumor growth by disrupting mitosis division of cancerous cells through cell cycle proteins. In this work, for the first time, an in-house fabricated cyclo-olefin polymer made microfluidic bioreactors are integrated with Cr/Au interdigitated electrodes to test TTFields on yeast cells with fluorescent protein:Nop56 gene. A small gap between electrodes (50 μm) allows small voltages (<150 mV) to be applied on the cells; hence, uninsulated gold electrodes are used in the non-faradaic region without causing any electrochemical reaction at the electrode-medium interface. Electrochemical modeling as well as impedance characterization and analysis of the electrodes are done using four different cell nutrient media. The experiments with yeast cells are done with 150 mV, 150 kHz and 30 mV, 200 kHz sinusoidal signals to generate electrical field magnitudes of 6.58 V/cm and 1.33 V/cm, respectively. In the high electrical field experiment, the cells go through electroporation. In the experiment with the low electrical field magnitude for TTFields, the cells have prolonged mitosis from typical 80-90 min to 200-300 min. Our results confirm the validity of the electrochemical model and the importance of applying a correct magnitude of the electrical field. Compared to the so far reported alternatives with insulated electrodes, the here developed thermoplastic microfluidic bioreactors with uninsulated electrodes provide a new, versatile, and durable platform for in vitro cell studies toward the improvement of anti-cancer therapies including personalized treatment.