Wireless Multichannel Neural Recording With a 128-Mbps UWB Transmitter for an Implantable Brain-Machine Interfaces

DualSort: online spike sorting with a running neural network

Objective.Spike sorting, i.e. the detection and separation of measured action potentials from different extracellularly recorded neurons, remains one of the bottlenecks in deciphering the brain. In recent years, the application of neural networks (NNs) for spike sorting has garnered significant attention. Most methods focus on specific sub-problems within the conventional spike sorting pipeline, such as spike detection or feature extraction, and attempt to solve them with complex network architectures. This paper presents DualSort, a simple NN that gets combined with downstream post-processing for real-time spike sorting. It shows high efficiency, low complexity, and requires a comparatively small amount of human interaction.Approach.Synthetic and experimentally obtained extracellular single-channel recordings were utilized to train and evaluate the proposed NN. For training, spike waveforms were labeled with respect to their associated neuron and position in the signal, allowing the detection and categorization of spikes in unison. DualSort classifies a single spike multiple times in succession, as it runs over the signal in a step-by-step manner and uses a post-processing algorithm that transmits the network output into spike trains. Main results.With the used datasets, DualSort was able to detect and distinguish different spike waveforms and separate them from background activity. The post-processing algorithm significantly strengthened the overall performance of the model, making the system more robust as a whole. Although DualSort is an end-to-end solution that efficiently transforms filtered signals into spike trains, it competes with contemporary state-of-the-art technologies that exclusively target single sub-problems in the conventional spike sorting pipeline.Significance.This work demonstrates that even under high noise levels, complex NNs are not necessary by any means to achieve high performance in spike detection and sorting. The utilization of data augmentation on a limited quantity of spikes could substantially decrease hand-labeling compared to other studies. Furthermore, the proposed framework can be utilized without human interaction when combined with an unsupervised technique that provides pseudo labels for DualSort. Due to the low complexity of our network, it works efficiently and enables real-time processing on basic hardware. The proposed approach is not limited to spike sorting, as it may also be used to process different signals, such as electroencephalogram (EEG), which needs to be investigated in future research.

An Energy-Efficient and High-Data-Rate IR-UWB Transmitter for Intracortical Neural Sensing Interfaces

This paper presents an implantable impulse-radio ultra-wideband (IR-UWB) wireless telemetry system for intracortical neural sensing interfaces. A 3-dimensional (3-D) hybrid impulse modulation that comprises phase shift keying (PSK), pulse position modulation (PPM) and pulse amplitude modulation (PAM) is proposed to increase modulation order without significantly increasing the demodulation requirement, thus leading to a high data rate of 1.66 Gbps and an increased air-transmission range. Operating in 6 - 9 GHz UWB band, the presented transmitter (TX) supports the proposed hybrid modulation with a high energy efficiency of 5.8 pJ/bit and modulation quality (EVM< -21 dB). A low-noise injection-locked ring oscillator supports 8-PSK with a phase error of 2.6°. A calibration free delay generator realizes a 4-PPM with only 115 μW and avoids potential cross-modulation between PPM and PSK. A switch-cap power amplifier with an asynchronous pulse-shaping performs 4-PAM with high energy efficiency and linearity. The TX is implemented in 28 nm CMOS technology, occupying 0.155mm² core area. The wireless module including a printed monopole antenna has a module area of only 1.05 cm². The transmitter consumes in total 9.7 mW when transmitting -41.3 dBm/MHz output power. The wireless telemetry module has been validated ex-vivo with a 15-mm multi-layer porcine tissue, and achieves a communication (air) distance up to 15 cm, leading to at least 16× improvement in distance-moralized energy efficiency of 45 pJ/bit/meter compared to state-of-the-art.

“Natural Laboratory Complex” for novel primate neuroscience

We propose novel strategies for primate experimentation that are ethically valuable and pragmatically useful for cognitive neuroscience and neuropsychiatric research. Specifically, we propose Natural Laboratory Complex or Natural Labs, which are a combination of indoor-outdoor structures for studying free moving and socially housed primates in natural or naturalistic environment. We contend that Natural Labs are pivotal to improve primate welfare, and at the same time to implement longitudinal and socio-ecological studies of primate brain and behavior. Currently emerging advanced technologies and social systems (including recent COVID-19 induced “remote” infrastructures) can speed-up cognitive neuroscience approaches in freely behaving animals. Experimental approaches in natural(istic) settings are not in competition with conventional approaches of laboratory investigations, and could establish several benefits at the ethical, experimental, and economic levels.

Melatonin Decreases Acute Inflammatory Response to Neural Probe Insertion

Neural electrode insertion trauma impedes the recording and stimulation capabilities of numerous diagnostic and treatment avenues. Implantation leads to the activation of inflammatory markers and cell types, which is detrimental to neural tissue health and recording capabilities. Oxidative stress and inflammation at the implant site have been shown to decrease with chronic administration of antioxidant melatonin at week 16, but its effects on the acute landscape have not been studied. To assess the effect of melatonin administration in the acute phase, specifically the first week post-implantation, we utilized histological and q-PCR methods to quantify cellular and molecular indicators of inflammation and oxidative stress in the tissue surrounding implanted probes in C57BL/6 mice as well as two-photon microscopy to track the microglial responses to the probes in real-time in transgenic mice expressing GFP with CX3CR1 promotor. Histological results indicate that melatonin effectively maintained neuron density surrounding the electrode, inhibited accumulation and activation of microglia and astrocytes, and reduced oxidative tissue damage. The expression of the pro-inflammatory cytokines, TNF-α and IL-6, were significantly reduced in melatonin-treated animals. Additionally, microglial encapsulation of the implant surface was inhibited by melatonin as compared to control animals following implantation. Our results combined with previous research suggest that melatonin is a particularly suitable drug for modulating inflammatory activity around neural electrode implants both acutely and chronically, translating to more stable and reliable interfaces.

Evolution of Biotelemetry in Medical Devices: From Radio Pills to mm-Scale Implants

The advent of semiconductor technology in the mid-20th century created unprecedented opportunities to develop a new generation of small-scale wireless medical sensing devices that can support remote monitoring of patients' vital signs. The first radio pills were developed as early as the 1950's using only a few transistors. These swallowable capsules could sense and wirelessly transmit vital parameters from inside the human body. Since then we have witnessed the rapid progress of medical devices driven by the evolution of semiconductor technology, from single-transistor oscillators to complex mixed-signal multi-channel and multi-modal systems. This paper retraces the evolution of biotelemetry devices from their very early inception to the smart miniaturized systems of modern days, focusing on semiconductor-enabled sensing methods and circuits developed over the last six decades. The paper also includes the author's perspective on current and future trends in the development of CMOS-based biotelemeters, focusing on concepts of implant modularity, miniaturization and hybrid energy harvesting solutions.

A 0.43 g Wireless Battery-Less Neural Recorder With On-Chip Microelectrode Array and Integrated Flexible Antenna

This work presents a single-chip battery-less neural recorder with 12 on-die microelectrodes. It can be powered wirelessly up to 16 cm away from a horn antenna at 915 MHz and only consumes 104 μW dc power for accessing 10 enabled recording sites simultaneously, transmitting at 5 Mbps. The implantable device integrated with a flexible antenna weighs only 0.43 gram. In vivo measurements on an unrestricted mouse have been successfully conducted, showing response to visual stimuli.

A Direct Digitizing Chopped Neural Recorder Using a Body-Induced Offset Based DC Servo Loop

This article presents a direct digitizing neural recorder that uses a body-induced offset based DC servo loop to cancel electrode offset (EDO) on-chip. The bulk of the input pair is used to create an offset, counteracting the EDO. The architecture does not require AC coupling capacitors which enables the use of chopping without impedance boosting while maintaining a large input impedance of 238 M Ω over the whole 10 kHz bandwidth. Implemented in a 180 nm HV-CMOS process, the prototype occupies a silicon area of only 0.02 mm² while consuming 12.8 μW and achieving 1.82 μV[Formula: see text] of input-referred noise in the local field potential (LFP) band and a NEF of 5.75.

A Neuromorphic CMOS Circuit With Self-Repairing Capability

Neurophysiological observations confirm that the brain not only is able to detect the impaired synapses (in brain damage) but also it is relatively capable of repairing faulty synapses. It has been shown that retrograde signaling by astrocytes leads to the modulation of synaptic transmission and thus bidirectional collaboration of astrocyte with nearby neurons is an important aspect of self-repairing mechanism. Specifically, the retrograde signaling via astrocyte can increase the transmission probability of the healthy synapses linked to the neuron. Motivated by these findings, in the present research, a CMOS neuromorphic circuit with self-repairing capabilities is proposed based on astrocyte signaling. In this way, the computational model of self-repairing process is hired as a basis for designing a novel analog integrated circuit in the 180-nm CMOS technology. It is illustrated that the proposed analog circuit is able to successfully recompense the damaged synapses by appropriately modifying the voltage signals of the remaining healthy synapses in the wide range of frequency. The proposed circuit occupies 7500- [Formula: see text] silicon area and its power consumption is about [Formula: see text]. This neuromorphic fault-tolerant circuit can be considered as a key candidate for future silicon neuronal systems and implementation of neurorobotic and neuro-inspired circuits.

Ionic communication for implantable bioelectronics

Implanted bioelectronic devices require data transmission through tissue, but ionic conductivity and inhomogeneity of this medium complicate conventional communication approaches. Here, we introduce ionic communication (IC) that uses ions to effectively propagate megahertz-range signals. We demonstrate that IC operates by generating and sensing electrical potential energy within polarizable media. IC was tuned to transmit across a range of biologically relevant tissue depths. The radius of propagation was controlled to enable multiline parallel communication, and it did not interfere with concurrent use of other bioelectronics. We created a fully implantable IC-based neural interface device that acquired and noninvasively transmitted neurophysiologic data from freely moving rodents over a period of weeks with stability sufficient for isolation of action potentials from individual neurons. IC is a biologically based data communication that establishes long-term, high-fidelity interactions across intact tissue.

An Energy-Efficient ASK Demodulator Robust to Power-Carrier-Interference for Inductive Power and Data Telemetry

Wireless power and datatelemetry based on amplitude-shift keying (ASK) modulation over dual inductive links has been widely adopted in biomedical implants. Due to the mutual inductance between the power and data links, the large power-carrier-interference (PCI) will inevitably cause low signal-to-interference ratio (SIR) of the received signal, thereby increasing the bit-error-rate (BER) of the ASK demodulation. In this paper, an innovative high energy-efficient ASK demodulator robust to PCI has been proposed. Thanks to the proposed sampling-and-subtraction (SAS) architecture, the demodulator is capable of withstanding PCI with an amplitude up to 2.5 times as the data carrier without the need for any high-order filters. The prototype has been implemented with 180 nm standard CMOS process, occupying a core area of 0.51 mm ². The experimental results show that with 1 Mbps data rate and 13.56 MHz carrier frequency, the typical BER is less than 1.3×10 ^-3, while the energy efficiency is 280 pJ/bit, showing 7.5× improvement compared to the prior works. The energy-efficient robustness to PCI demonstrates the potential of the technique to be applied to retina prostheses as well as various kinds of ultra-low-power implantable biomedical devices.

A Neural Recording and Stimulation Chip with Artifact Suppression for Biomedical Devices

This paper presents chip implementation of the integrated neural recording and stimulation system with stimulation-induced artifact suppression. The implemented chip consists of low-power neural recording circuits, stimulation circuits, and action potential detection circuits. These circuits constitute a closed-loop simultaneous neural recording and stimulation system for biomedical devices, and a proposed artifact suppression technique is used in the system. Moreover, this paper also presents the measurement and experiment results of the implemented 4-to-4 channel neural recording and stimulation chip with 0.18 µm CMOS technology. The function and efficacy of simultaneous neural recording and stimulation is validated in both in vivo and animal experiments.

Advances in Neural Recording and Stimulation Integrated Circuits

In the past few decades, driven by the increasing demands in the biomedical field aiming to cure neurological diseases and improve the quality of daily lives of the patients, researchers began to take advantage of the semiconductor technology to develop miniaturized and power-efficient chips for implantable applications. The emergence of the integrated circuits for neural prosthesis improves the treatment process of epilepsy, hearing loss, retinal damage, and other neurological diseases, which brings benefits to many patients. However, considering the safety and accuracy in the neural prosthesis process, there are many research directions. In the process of chip design, designers need to carefully analyze various parameters, and investigate different design techniques. This article presents the advances in neural recording and stimulation integrated circuits, including (1) a brief introduction of the basics of neural prosthesis circuits and the repair process in the bionic neural link, (2) a systematic introduction of the basic architecture and the latest technology of neural recording and stimulation integrated circuits, (3) a summary of the key issues of neural recording and stimulation integrated circuits, and (4) a discussion about the considerations of neural recording and stimulation circuit architecture selection and a discussion of future trends. The overview would help the designers to understand the latest performances in many aspects and to meet the design requirements better.

Neural Spike Sorting Using Binarized Neural Networks

This article presents the design and efficient hardware implementation of binarized neural networks (BNNs) for brain-implantable neural spike sorting. In contrast to the conventional artificial neural networks (ANNs), in which the weights and activation functions of neurons are represented using real values, the BNNs utilize binarized weights and activation functions to dramatically reduce the memory requirement and computational complexity of the ANNs. The designed BNN is trained using several realistic neural datasets to verify its accuracy for neural spike sorting. The application-specific integrated circuit (ASIC) implementation of the designed BNN in a standard 0.18- [Formula: see text] CMOS process occupies 0.33 mm ² of silicon area. Power consumption estimation of the ASIC layout shows that the BNN dissipates [Formula: see text] of power from a 1.8 V supply while operating at 24 kHz. The designed BNN-based spike sorting system is also implemented on a field-programmable gate array and is shown to reduce the required on-chip memory by 89% compared to those of the alternative state-of-the-art spike sorting systems. To the best of our knowledge, this is the first work employing BNNs for real-time in vivo neural spike sorting.

Soft, Wireless and subdermally implantable recording and neuromodulation tools

Progress in understanding neuronal interaction and circuit behavior of the central and peripheral nervous system strongly relies on the advancement of tools that record and stimulate with high fidelity and specificity. Currently, devices used in exploratory research predominantly utilize cables or tethers to provide pathways for power supply, data communication, stimulus delivery and recording, which constrains the scope and use of such devices. In particular, the tethered connection, mechanical mismatch to surrounding soft tissues and bones frustrate the interface leading to irritation and limitation of motion of the subject, which in the case of fundamental and preclinical studies, impacts naturalistic behaviors of animals and precludes the use in experiments involving social interaction and ethologically relevant three-dimensional environments, limiting the use of current tools to mostly rodents and exclude species such as birds and fish. This review explores the current state-of-the-art in wireless, subdermally implantable tools that quantitively expand capabilities in analysis and perturbation of the central and peripheral nervous system by removing tethers and externalized features of implantable neuromodulation and recording tools. Specifically, the review explores power harvesting strategies, wireless communication schemes, and soft materials and mechanics that enable the creation of such devices and discuss their capabilities in the context of freely-behaving subjects. Highlights of this class of devices includes wireless battery-free and fully implantable operation with capabilities in cell specific recording, multimodal neural stimulation and electrical, optogenetic and pharmacological neuromodulation capabilities. We conclude with discussion on translation of such technologies which promises routes towards broad dissemination.

Electrophysiology Read-Out Tools for Brain-on-Chip Biotechnology

Brain-on-Chip (BoC) biotechnology is emerging as a promising tool for biomedical and pharmaceutical research applied to the neurosciences. At the convergence between lab-on-chip and cell biology, BoC couples in vitro three-dimensional brain-like systems to an engineered microfluidics platform designed to provide an in vivo-like extrinsic microenvironment with the aim of replicating tissue- or organ-level physiological functions. BoC therefore offers the advantage of an in vitro reproduction of brain structures that is more faithful to the native correlate than what is obtained with conventional cell culture techniques. As brain function ultimately results in the generation of electrical signals, electrophysiology techniques are paramount for studying brain activity in health and disease. However, as BoC is still in its infancy, the availability of combined BoC-electrophysiology platforms is still limited. Here, we summarize the available biological substrates for BoC, starting with a historical perspective. We then describe the available tools enabling BoC electrophysiology studies, detailing their fabrication process and technical features, along with their advantages and limitations. We discuss the current and future applications of BoC electrophysiology, also expanding to complementary approaches. We conclude with an evaluation of the potential translational applications and prospective technology developments.

Using Low-Power, Low-Cost IoT Processors in Clinical Biosignal Research: an In-depth Feasibility Check

Research on biosignal (ExG) analysis is usually performed with expensive systems requiring connection with external computers for data processing. Consumer-grade low-cost wearable systems for bio-potential monitoring and embedded processing have been presented recently, but are not considered suitable for medical-grade analyses. This work presents a detailed quantitative comparative analysis of a recently presented fully-wearable low-power and low-cost platform (BioWolf) for ExG acquisition and embedded processing with two researchgrade acquisition systems, namely, ANTNeuro (EEG) and the Noraxon DTS (EMG). Our preliminary results demonstrate that BioWolf offers competitive performance in terms of electrical properties and classification accuracy. This paper also highlights distinctive features of BioWolf, such as real-time embedded processing, improved wearability, and energy-efficiency, which allows devising new types of experiments and usage scenarios for medical-grade biosignal processing in research and future clinical studies.

A Chip Integrity Monitor for Evaluating Moisture/Ion Ingress in mm-Sized Single-Chip Implants

For mm-sized implants incorporating silicon integrated circuits, ensuring lifetime operation of the chip within the corrosive environment of the body still remains a critical challenge. For the chip's packaging, various polymeric and thin ceramic coatings have been reported, demonstrating high biocompatibility and barrier properties. Yet, for the evaluation of the packaging and lifetime prediction, the conventional helium leak test method can no longer be applied due to the mm-size of such implants. Alternatively, accelerated soak studies are typically used instead. For such studies, early detection of moisture/ion ingress using an in-situ platform may result in a better prediction of lifetime functionality. In this work, we have developed such a platform on a CMOS chip. Ingress of moisture/ions would result in changes in the resistance of the interlayer dielectrics (ILD) used within the chip and can be tracked using the proposed system, which consists of a sensing array and an on-chip measurement engine. The measurement system uses a novel charge/discharge based time-mode resistance sensor that can be implemented using simple yet highly robust circuitry. The sensor array is implemented together with the measurement engine in a standard 0.18  μm 6-metal CMOS process. The platform was validated through a series of dry and wet measurements. The system can measure the ILD resistance with values of up to 0.504 peta-ohms, with controllable measurement steps that can be as low as 0.8 M Ω. The system works with a supply voltage of 1.8 V, and consumes 4.78 mA. Wet measurements in saline demonstrated the sensitivity of the platform in detecting moisture/ion ingress. Such a platform could be used both in accelerated soak studies and during the implant's life-time for monitoring the integrity of the chip's packaging.

Investigating on the Interferences on Human Body Communication System Induced by Other Wearable Devices

Human body communication (HBC) has become one of the most energy-efficient candidates for wireless body area network (WBAN) as it uses higher conductivity of human body as transmission media to reduce transmission loss. The use of medical electrodes instead of bulky antennas makes it suitable for biomedical sensors. The IEEE 802.15.6 standard has reserved only one communication channel for HBC centering at 21 MHz with 5.25 MHz bandwidth, which enlarges the probability of the collision and interference when multiple wearable devices locate on the human body. As a result, the error vector magnitude (EVM) of HBC will be affected by the various states of the interference sources. However, none of the previous works has studied the effects of interferences in HBC. In this paper, the interference factors in HBC WBAN systems assisted by actual measurement on human body are investigated. The HBC signal EVM under different interference states are studied, including frequency, power, modulation scheme, symbol rate, and apart distance between interference source and receiver of HBC. Based on the result and analysis, we propose a possible communication scheme for other body nodes to avoid the collision with HBC.

Future of Neural Interfaces

The technological ability to capture electrophysiological activity of populations of cortical neurons through chronic implantable devices has led to significant advancements in the field of brain-computer interfaces. Recent progress in the field has been driven by developments in integrated microelectronics, wireless communications, materials science, and computational neuroscience. Here, we review major device development landmarks in the arena of neural interfaces from FDA-approved clinical systems to prototype head-mounted and fully implantable wireless systems for multi-channel neural recording. Additionally, we provide an outlook toward next-generation, highly miniaturized technologies for minimally invasive, vastly parallel neural interfaces for naturalistic, closed-loop neuroprostheses.

BioWolf: A Sub-10-mW 8-Channel Advanced Brain-Computer Interface Platform With a Nine-Core Processor and BLE Connectivity

Advancements in digital signal processing (DSP) and machine learning techniques have boosted the popularity of brain-computer interfaces (BCIs), where electroencephalography is a widely accepted method to enable intuitive human-machine interaction. Nevertheless, the evolution of such interfaces is currently hampered by the unavailability of embedded platforms capable of delivering the required computational power at high energy efficiency and allowing for a small and unobtrusive form factor. To fill this gap, we developed BioWolf, a highly wearable (40 mm × 20 mm × 2 mm) BCI platform based on Mr. Wolf, a parallel ultra low power system-on-chip featuring nine RISC-V cores with DSP-oriented instruction set extensions. BioWolf also integrates a commercial 8-channel medical-grade analog-to-digital converter, and an ARM-Cortex M4 microcontroller unit (MCU) with bluetooth low-energy connectivity. To demonstrate the capabilities of the system, we implemented and tested a BCI featuring canonical correlation analysis (CCA) of steady-state visual evoked potentials. The system achieves an average information transfer rate of 1.46 b/s (aligned with the state-of-the-art of bench-top systems). Thanks to the reduced power envelope of the digital computational platform, which consumes less than the analog front-end, the total power budget is just 6.31 mW, providing up to 38 h operation (65 mAh battery). To our knowledge, our design is the first to explore the significant energy boost of a parallel MCU with respect to single-core MCUs for CCA-based BCI.

A 25 Mbps, 12.4 pJ/b DQPSK Backscatter Data Uplink for the NeuroDisc Brain-Computer Interface

Wireless brain-computer interfaces (BCIs) are used to study neural activity in freely moving non-human primates (NHPs). However, the high energy consumption of conventional active radios is proving to be an obstacle as research drives for wireless BCIs that can provide continuous high-rate data uplinks for longer durations (i.e. multiple days). We present a differential quadrature phase shift keying (DQPSK) backscatter uplink for the NeuroDisc BCI as an alternative to active radios. The uplink achieves a 25 Mbps throughput while operating in the 915 MHz industrial, scientific, and medical (ISM) band. The DQPSK backscatter modulator was measured to have an error-vector magnitude (EVM) of 9.7% and a measured power consumption of 309  μW during continuous, full-rate transmissions, yielding an analog communication efficiency of 12.4 pJ/bit. The NeuroDisc is capable of recording 16 channels of neural data with 16-bit resolution at up to 20 kSps per channel with a measured input-referred noise of 2.35  μV. In previous work, we demonstrated the DQPSK backscatter uplink, but bandwidth constraints in the signal chain limited the uplink rate to 6.25 Mbps and the neural sampling rate to 5 kSps. This work provides new innovations to increase the bandwidth of the system, including an ultra-high frequency (UHF) antenna design with a -10 dB return loss bandwidth of 12.5 MHz and a full-duplex receiver with an average self-jammer cancellation of 89 dB. We present end-to-end characterization of the NeuroDisc and validate the backscatter uplink using pre-recorded neural data as well as in vivo recordings from a pigtail macaque.

An Energy Efficient Multi-User Asynchronous Wireless Transmitter for Biomedical Signal Acquisition

The paper presents a novel transmitter architecture for short-range asynchronous wireless communication, applicable to simultaneous multi-user wireless acquisition of biological signals. The analog signal, provided from an analog biosensor, is transformed to time information using an Integral Pulse Frequency Modulator (IPFM) as a Time-Encoding Machine. The IPFM generates a time-encoded unipolar pulse train, maintaining the linear dependence of the output pulse distance on analog input voltage. The system enables continuous acquisition of the signals from multiple sensors in which each transmitter has unique feedback loop delay used for multi-user coding. IPFM pulses trigger the Impulse Radio Ultra-Wideband pulse generator directly, providing two ultra-wideband (UWB) pulses per each IPFM pulse. Due to the lack of internal clock signal and microprocessor-free multi-user coding, the circuitry satisfies the requirements of multi-user coding energy efficiency and size reduction, which are crucial demands in biomedical applications. The proposed Time-Encoded UWB (TE-UWB) transmitter is implemented in 0.18 [Formula: see text] CMOS technology. Measurement results of the IPFM transfer function for input voltage ranging from 0.15 to 1.5 V are presented, providing the dependence of the IPFM pulse time distance on analog input voltage and power consumption dependence on the input voltage level. For continuous monitoring operation, total power consumption of the transmitter circuitry for the maximum input voltage is 10.8 [Formula: see text], while for the lowest input voltage it increases to 40.48 [Formula: see text]. The circuit occupies 0.14 [Formula: see text].

An ASIC for Recording and Stimulation in Stacked Microchannel Neural Interfaces

This paper presents an active microchannel neural interface (MNI) using seven stacked application specific integrated circuits (ASICs). The approach provides a solution to the present problem of interconnect density in three-dimensional (3-D) MNIs. The 4 mm² ASIC is implemented in 0.35 μm high-voltage CMOS technology. Each ASIC is the base for seven microchannels each with three electrodes in a pseudo-tripolar arrangement. Multiplexing allows stimulating or recording from any one of 49 channels, across seven ASICs. Connections to the ASICs are made with a five-line parallel bus. Current controlled biphasic stimulation from 5 to 500 μA has been demonstrated with switching between channels and ASICs. The high-voltage technology gives a compliance of 40 V for stimulation, appropriate for the high impedances within microchannels. High frequency biphasic stimulation, up to 40 kHz is achieved, suitable for reversible high frequency nerve blockades. Recording has been demonstrated with mV level signals; common-mode inputs are differentially distorted and limit the CMRR to 40 dB. The ASIC has been used in vitro in conjunction with an oversize (2 mm diameter) microchannel in phosphate buffered saline, demonstrating attenuation of interference from outside the microchannel and tripolar recording of signals from within the microchannel. By using five-lines for 49 active microchannels the device overcomes limitations when connecting many electrodes in a 3-D miniaturized nerve interface.

A Five-Tissue-Layer Human Body Communication Circuit Model Tunable to Individual Characteristics

Human body communication (HBC) has several advantages over traditional wireless communications due to the high conductivity of human body. An accurate body channel model plays a vital role in optimizing the performance and power of HBC transceivers. In this paper, we present a body channel model with three distinct features. First, it takes into account all five body tissue layers resulting better accuracy; second, it adapts to different individuals with the proposed layer thickness estimation technique; third, it counts in the variation of backward coupling capacitance versus different postures. These new features significantly improve the model accuracy. Measurement results show that the proposed model achieves a maximum error of 2.21% in path loss for different human subjects.

A Time-Domain Analog Spatial Compressed Sensing Encoder for Multi-Channel Neural Recording

A time-domain analog spatial compressed sensing encoder for neural recording applications is proposed. Owing to the advantage of MEMS technologies, the number of channels on a silicon neural probe array has doubled in 7.4 years, and therefore, a greater number of recording channels and higher density of front-end circuitry is required. Since neural signals such as action potential (AP) have wider signal bandwidth than that of an image sensor, a data compression technique is essentially required for arrayed neural recording systems. In this paper, compressed sensing (CS) is employed for data reduction, and a novel time-domain analog CS encoder is proposed. A simpler and lower power circuit than conventional analog or digital CS encoders can be realized by using the proposed CS encoder. A prototype of the proposed encoder was fabricated in a 180 nm 1P6M CMOS process, and it achieved an active area of 0.0342 mm 2 / ch . and an energy efficiency of 25.0 pJ / ch . · conv .

An Investigation on Ground Electrodes of Capacitive Coupling Human Body Communication

Utilizing the body surface as the signal transmission medium, capacitive coupling human body communication (CC-HBC) can achieve a much higher energy efficiency than conventional wireless communications in future wireless body area network (WBAN) applications. Under the CC-HBC scheme, the body surface serves as the forward signal path, whereas the backward path is formed by the capacitive coupling between the ground electrodes (GEs) of transmitter (TX) and receiver (RX). So the type of communication benefits from a low forward loss, while the backward loss depending on the GE coupling strength dominates the total transmission loss. However, none of the previous works have shown a complete research on the effects of GEs. In this paper, all kinds of GE effects on CC-HBC are investigated by both finite element method (FEM) analysis and human body measurement. We set the TX GE and RX GE at different heights, separation distances, and dimensions to study the corresponding influence on the overall signal transmission path loss. In addition, we also investigate the effects of GEs with different shapes and different TX-to-RX relative angles. Based on all the investigations, an analytical model is derived to evaluate the GE related variations of channel loss in CC-HBC.

Workshops of the Sixth International Brain-Computer Interface Meeting: brain-computer interfaces past, present, and future

The Sixth International Brain-Computer Interface (BCI) Meeting was held 30 May-3 June 2016 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 28 workshops covering topics in BCI and brain-machine interface research. Topics included BCI for specific populations or applications, advancing BCI research through use of specific signals or technological advances, and translational and commercial issues to bring both implanted and non-invasive BCIs to market. BCI research is growing and expanding in the breadth of its applications, the depth of knowledge it can produce, and the practical benefit it can provide both for those with physical impairments and the general public. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and highlighting important issues and calls for action to support future research and development.

Feasibility of an ultra-low power digital signal processor platform as a basis for a fully implantable brain-computer interface system

A fully implantable brain-computer interface (BCI) can be a practical tool to restore independence to those affected by spinal cord injury. We envision that such a BCI system will invasively acquire brain signals (e.g. electrocorticogram) and translate them into control commands for external prostheses. The feasibility of such a system was tested by implementing its benchtop analogue, centered around a commercial, ultra-low power (ULP) digital signal processor (DSP, TMS320C5517, Texas Instruments). A suite of signal processing and BCI algorithms, including (de)multiplexing, Fast Fourier Transform, power spectral density, principal component analysis, linear discriminant analysis, Bayes rule, and finite state machine was implemented and tested in the DSP. The system's signal acquisition fidelity was tested and characterized by acquiring harmonic signals from a function generator. In addition, the BCI decoding performance was tested, first with signals from a function generator, and subsequently using human electroencephalogram (EEG) during eyes opening and closing task. On average, the system spent 322 ms to process and analyze 2 s of data. Crosstalk (<;-65 dB) and harmonic distortion (~1%) were minimal. Timing jitter averaged 49 μs per 1000 ms. The online BCI decoding accuracies were 100% for both function generator and EEG data. These results show that a complex BCI algorithm can be executed on an ULP DSP without compromising performance. This suggests that the proposed hardware platform may be used as a basis for future, fully implantable BCI systems.