Recent advances in neural recording microsystems

Recent Advancements in Graphene-Based Implantable Electrodes for Neural Recording/Stimulation

Implantable electrodes represent a groundbreaking advancement in nervous system research, providing a pivotal tool for recording and stimulating human neural activity. This capability is integral for unraveling the intricacies of the nervous system's functionality and for devising innovative treatments for various neurological disorders. Implantable electrodes offer distinct advantages compared to conventional recording and stimulating neural activity methods. They deliver heightened precision, fewer associated side effects, and the ability to gather data from diverse neural sources. Crucially, the development of implantable electrodes necessitates key attributes: flexibility, stability, and high resolution. Graphene emerges as a highly promising material for fabricating such electrodes due to its exceptional properties. It boasts remarkable flexibility, ensuring seamless integration with the complex and contoured surfaces of neural tissues. Additionally, graphene exhibits low electrical resistance, enabling efficient transmission of neural signals. Its transparency further extends its utility, facilitating compatibility with various imaging techniques and optogenetics. This paper showcases noteworthy endeavors in utilizing graphene in its pure form and as composites to create and deploy implantable devices tailored for neural recordings and stimulations. It underscores the potential for significant advancements in this field. Furthermore, this paper delves into prospective avenues for refining existing graphene-based electrodes, enhancing their suitability for neural recording applications in in vitro and in vivo settings. These future steps promise to revolutionize further our capacity to understand and interact with the neural research landscape.

Data Compression Versus Signal Fidelity Tradeoff in Wired-OR Analog-to-Digital Compressive Arrays for Neural Recording

Future high-density and high channel count neural interfaces that enable simultaneous recording of tens of thousands of neurons will provide a gateway to study, restore and augment neural functions. However, building such technology within the bit-rate limit and power budget of a fully implantable device is challenging. The wired-OR compressive readout architecture addresses the data deluge challenge of a high channel count neural interface using lossy compression at the analog-to-digital interface. In this article, we assess the suitability of wired-OR for several steps that are important for neuroengineering, including spike detection, spike assignment and waveform estimation. For various wiring configurations of wired-OR and assumptions about the quality of the underlying signal, we characterize the trade-off between compression ratio and task-specific signal fidelity metrics. Using data from 18 large-scale microelectrode array recordings in macaque retina ex vivo, we find that for an event SNR of 7-10, wired-OR correctly detects and assigns at least 80% of the spikes with at least 50× compression. The wired-OR approach also robustly encodes action potential waveform information, enabling downstream processing such as cell-type classification. Finally, we show that by applying an LZ77-based lossless compressor (gzip) to the output of the wired-OR architecture, 1000× compression can be achieved over the baseline recordings.

An iEEG Recording and Adjustable Shunt-Current Conduction Platform for Epilepsy Treatment

This paper proposes a compact bioelectronics sensing platform, including a multi-channel electrode, intracranial electroencephalogram (iEEG) recorder, adjustable galvanometer, and shunt-current conduction circuit pathway. The developed implantable electrode made of polyurethane-insulated stainless-steel materials is capable of recording iEEG signals and shunt-current conduction. The electrochemical impedance of the conduction, ground/reference, and working electrode were characterized in phosphate buffer saline solution, revealing in vitro results of 517.2 Ω@1 kHz (length of 0.1 mm, diameter of 0.8 mm), 1.374 kΩ@1 kHz (length of 0.3 mm, diameter of 0.1 mm), and 3.188 kΩ@1 kHz (length of 0.1 mm, diameter of 0.1 mm), respectively. On-bench measurement of the system revealed that the input noise of the system is less than 2 μVrms, the signal frequency bandwidth range is 1 Hz~10 kHz, and the shunt-current detection range is 0.1~3000 μA with an accuracy of above 99.985%. The electrode was implanted in the CA1 region of the right hippocampus of rats for the in vivo experiments. Kainic acid (KA)-induced seizures were detected through iEEG monitoring, and the induced shunt-current was successfully measured and conducted out of the brain through the designed circuit-body path, which verifies the potential of current conduction for the treatment of epilepsy.

Ultra-compact dual-band smart NEMS magnetoelectric antennas for simultaneous wireless energy harvesting and magnetic field sensing

Ultra-compact wireless implantable medical devices are in great demand for healthcare applications, in particular for neural recording and stimulation. Current implantable technologies based on miniaturized micro-coils suffer from low wireless power transfer efficiency (PTE) and are not always compliant with the specific absorption rate imposed by the Federal Communications Commission. Moreover, current implantable devices are reliant on differential recording of voltage or current across space and require direct contact between electrode and tissue. Here, we show an ultra-compact dual-band smart nanoelectromechanical systems magnetoelectric (ME) antenna with a size of 250 × 174 µm² that can efficiently perform wireless energy harvesting and sense ultra-small magnetic fields. The proposed ME antenna has a wireless PTE 1–2 orders of magnitude higher than any other reported miniaturized micro-coil, allowing the wireless IMDs to be compliant with the SAR limit. Furthermore, the antenna’s magnetic field detectivity of 300–500 pT allows the IMDs to record neural magnetic fields.

Wireless implantable medical devices (IMDs) are hamstrung by both size and efficiency required for wireless power transfer. Here, Zaeimbashi et al. present a magnetoelectric nano-electromechanical systems that can harvest energy and sense weak magnetic fields like those arising from neural activity.

Developing Precision Invasive Neuromodulation for Psychiatry

Psychiatric conditions are common and often disabling. Although great strides have been made in alleviating symptoms with pharmacotherapy and psychotherapeutic approaches, many patients continue to have severe disease burden despite the best therapies available. One of the pervasive challenges to improving treatment is that present diagnostic and therapeutic strategies lag behind our modern conceptualization of the pathophysiology of these disorders. Psychiatric symptoms manifest through activity in specific neural circuits; thus, therapies capable of modulating these circuits are attractive. The investigators reviewed recent advances that facilitate treating medically refractory psychiatric disorders with intracranial neuromodulation in a way that intervenes more directly with the underlying pathophysiology. Specifically, they reviewed the prospects for using intracranial multielectrode arrays to record brain activity with high spatiotemporal resolution and identify circuit-level electrophysiological correlates of symptoms. A causal relationship of circuit electrophysiology to symptoms could then be established by modulating the circuits to disrupt the symptoms. Personalized therapeutic neuromodulation strategies can then proceed in a rational manner with stimulation protocols informed by the underlying circuit-based pathophysiology of the most bothersome symptoms. This strategy would enhance current methods in neurotherapeutics by identifying individualized anatomical targets with symptom-specific precision, circumventing many of the limitations inherent in modern psychiatric nosology and treatment.

A Multi-Channel Neural Recording System with Adaptive Electrode Selection for High-Density Neural Interface

There is an increasing demand for real-time neural signal monitoring from a large number of electrode contacts to provide adequate spatial and temporal resolution for brain mapping and high-resolution neural interface. This paper proposes a novel multi-channel neural recording system that records neural signals from a large number of electrodes with a smaller number of recording channels. The system utilizes an adaptive electrode selection technique to automatically scan the electrode arrays and record from selected electrodes where neural spikes are detected. The proposed neural recording IC was fabricated in CMOS 180 nm process and tested with in vitro environments. Experiment results with pre-recorded neural data indicate that neural spikes can be separated and amplified with the proposed system and counted in real-time.

Low power switched-resistor band-pass filter for neural recording channels in 130nm CMOS

In this work, we present a low-power 2^nd order band-pass filter for neural recording applications. The central frequency of the passband is set to 375Hz and the quality factor to 5 to properly process the neural signals related to the onset of epileptic seizure, and to strongly attenuate all the out of band biological signals and electrical disturbances. The biquad filter is based on a fully differential Tow Thomas architecture in which high-valued resistors are implemented through switched high-resistivity polysilicon resistors. A supply voltage as low as 0.8V and MOS transistors operating in the sub-threshold region are exploited to achieve a power consumption as low as 170nW, when driving a 1pF load capacitance. The filter exhibits a tuning range of the resonance frequency from 200Hz to 400Hz, and an area footprint of only 0.021 mm². Very low power consumption and area occupation are key specifications for integrated, multiple-sensors, neural recording systems.

Multi-Channel Neural Recording Implants: A Review

The recently growing progress in neuroscience research and relevant achievements, as well as advancements in the fabrication process, have increased the demand for neural interfacing systems. Brain-machine interfaces (BMIs) have been revealed to be a promising method for the diagnosis and treatment of neurological disorders and the restoration of sensory and motor function. Neural recording implants, as a part of BMI, are capable of capturing brain signals, and amplifying, digitizing, and transferring them outside of the body with a transmitter. The main challenges of designing such implants are minimizing power consumption and the silicon area. In this paper, multi-channel neural recording implants are surveyed. After presenting various neural-signal features, we investigate main available neural recording circuit and system architectures. The fundamental blocks of available architectures, such as neural amplifiers, analog to digital converters (ADCs) and compression blocks, are explored. We cover the various topologies of neural amplifiers, provide a comparison, and probe their design challenges. To achieve a relatively high SNR at the output of the neural amplifier, noise reduction techniques are discussed. Also, to transfer neural signals outside of the body, they are digitized using data converters, then in most cases, the data compression is applied to mitigate power consumption. We present the various dedicated ADC structures, as well as an overview of main data compression methods.

An Unsupervised Compressed Sensing Algorithm for Multi-Channel Neural Recording and Spike Sorting

We propose an unsupervised compressed sensing (CS)-based framework to compress, recover, and cluster neural action potentials. This framework can be easily integrated into high-density multi-electrode neural recording VLSI systems. Embedding spectral clustering and group structures in dictionary learning, we extend the proposed framework to unsupervised spike sorting without prior label information. Additionally, we incorporate group sparsity concepts in the dictionary learning to enable the framework for multi-channel neural recordings, as in tetrodes. To further improve spike sorting success rates in the CS framework, we embed template matching in sparse coding to jointly predict clusters of spikes. Our experimental results demonstrate that the proposed CS-based framework can achieve a high compression ratio (8:1 to 20:1), with a high quality reconstruction performance (>8 dB) and a high spike sorting accuracy (>90%).

Online Artifact Cancelation in Same-Electrode Neural Stimulation and Recording Using a Combined Hardware and Software Architecture

Advancing studies of neural network dynamics and developments of closed-loop neural interfaces requires the ability to simultaneously stimulate and record the neural cells. Recording adjacent to or at the stimulation site produces artifact signals that are orders of magnitude larger than the neural responses of interest. These signals often saturate the recording amplifier causing distortion or loss of short-latency evoked responses. This paper proposes a method to cancel the artifact in simultaneous neural recording and stimulation on the same electrode. By combining a novel hardware architecture with concurrent software processing, the design achieves neural signal recovery in a wide range of conditions. The proposed system uniquely demonstrates same-electrode stimulation and recording, with neural signal recovery in presence of stimulation artifact 100 dB larger in magnitude than the underlying signals. The system is tested both in vitro and in vivo, during concurrent stimulation and recording on the same electrode. In vivo results in a rodent model are compared to recordings made by a commercial neural amplifier system connected in parallel.

Sub 100 nW Volatile Nano-Metal-Oxide Memristor as Synaptic-Like Encoder of Neuronal Spikes

Advanced neural interfaces mediate a bioelectronic link between the nervous system and microelectronic devices, bearing great potential as innovative therapy for various diseases. Spikes from a large number of neurons are recorded leading to creation of big data that require online processing under most stringent conditions, such as minimal power dissipation and on-chip space occupancy. Here, we present a new concept where the inherent volatile properties of a nano-scale memristive device are used to detect and compress information on neural spikes as recorded by a multielectrode array. Simultaneously, and similarly to a biological synapse, information on spike amplitude and frequency is transduced in metastable resistive state transitions of the device, which is inherently capable of self-resetting and of continuous encoding of spiking activity. Furthermore, operating the memristor in a very high resistive state range reduces its average in-operando power dissipation to less than 100 nW, demonstrating the potential to build highly scalable, yet energy-efficient on-node processors for advanced neural interfaces.

Towards miniaturized closed-loop optogenetic stimulation devices

OBJECTIVE

Electrical brain stimulation provides therapeutic benefits for patients with drug-resistant neurological disorders. It, however, has restricted access to cell-type selectivity which limits its treatment effectiveness. Optogenetics, in contrast, enables precise targeting of a specific cell type which can address the issue with electrical brain stimulation. It, nonetheless, disregards real-time brain responses in delivering optimized stimulation to target cells. Closed-loop optogenetics, on the other hand, senses the difference between normal and abnormal states of the brain, and modulates stimulation parameters to achieve the desired stimulation outcome. Current review articles on closed-loop optogenetics have focused on its theoretical aspects and potential benefits. A review of the recent progress in miniaturized closed-loop optogenetic stimulation devices is thus needed.

APPROACH

This paper presents a comprehensive study on the existing miniaturized closed-loop optogenetic stimulation devices and their internal components.

MAIN RESULTS

Hardware components of closed-loop optogenetic stimulation devices including electrode, light-guiding mechanism, optical source, neural recorder, and optical stimulator are discussed. Next, software modules of closed-loop optogenetic stimulation devices including feature extraction, classification, control, and stimulation parameter modulation are described. Then, the existing devices are categorized into open-loop and closed-loop groups, and the combined operation of their neural recorder, optical stimulator, and control approach is discussed. Finally, the challenges in the design and implementation of closed-loop optogenetic stimulation devices are presented, suggestions on how to tackle these challenges are given, and future directions for closed-loop optogenetics are stated.

SIGNIFICANCE

A generic architecture for closed-loop optogenetic stimulation devices involving both hardware and software perspectives is devised. A comprehensive investigation into the most current miniaturized and tetherless closed-loop optogenetic stimulation devices is given. A detailed comparison of the closed-loop optogenetic stimulation devices is presented.

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 .

A hybrid hardware and software approach for cancelling stimulus artifacts during same-electrode neural stimulation and recording

Recovering neural responses from electrode recordings is fundamental for understanding the dynamics of neural networks. This effort is often obscured by stimulus artifacts in the recordings, which result from stimuli injected into the electrode-tissue interface. Stimulus artifacts, which can be orders of magnitude larger than the neural responses of interest, can mask short-latency evoked responses. Furthermore, simultaneous neural stimulation and recording on the same electrode generates artifacts with larger amplitudes compared to a separate electrode setup, which inevitably overwhelm the amplifier operation and cause unrecoverable neural signal loss. This paper proposes an end-to-end system combining hardware and software techniques for actively cancelling stimulus artifacts, avoiding amplifier saturation, and recovering neural responses during current-controlled in-vivo neural stimulation and recording. The proposed system is tested in-vitro under various stimulation settings by stimulating and recording on the same electrode with a superimposed pre-recorded neural signal. Experimental results show that neural responses can be recovered with minimal distortion even during stimulus artifacts that are several orders greater in magnitude.

A Multi-Functional Microelectrode Array Featuring 59760 Electrodes, 2048 Electrophysiology Channels, Stimulation, Impedance Measurement and Neurotransmitter Detection Channels

Biological cells are characterized by highly complex phenomena and processes that are, to a great extent, interdependent. To gain detailed insights, devices designed to study cellular phenomena need to enable tracking and manipulation of multiple cell parameters in parallel; they have to provide high signal quality and high spatiotemporal resolution. To this end, we have developed a CMOS-based microelectrode array system that integrates six measurement and stimulation functions, the largest number to date. Moreover, the system features the largest active electrode array area to date (4.48×2.43 mm2) to accommodate 59,760 electrodes, while its power consumption, noise characteristics, and spatial resolution (13.5 μm electrode pitch) are comparable to the best state-of-the-art devices. The system includes: 2,048 action-potential (AP, bandwidth: 300 Hz to 10 kHz) recording units, 32 local-field-potential (LFP, bandwidth: 1 Hz to 300 Hz) recording units, 32 current recording units, 32 impedance measurement units, and 28 neurotransmitter detection units, in addition to the 16 dual-mode voltage-only or current/voltage-controlled stimulation units. The electrode array architecture is based on a switch matrix, which allows for connecting any measurement/stimulation unit to any electrode in the array and for performing different measurement/stimulation functions in parallel.

Biology-inspired microphysiological system approaches to solve the prediction dilemma of substance testing

The recent advent of microphysiological systems - microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro - is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various dedicated research programs in Europe and Asia have led recently to the first cutting-edge achievements of human single-organ and multi-organ engineering based on microphysiological systems. The expectation is that test systems established on this basis would model various disease stages, and predict toxicity, immunogenicity, ADME profiles and treatment efficacy prior to clinical testing. Consequently, this technology could significantly affect the way drug substances are developed in the future. Furthermore, microphysiological system-based assays may revolutionize our current global programs of prioritization of hazard characterization for any new substances to be used, for example, in agriculture, food, ecosystems or cosmetics, thus, replacing laboratory animal models used currently. Thirty-six experts from academia, industry and regulatory bodies present here the results of an intensive workshop (held in June 2015, Berlin, Germany). They review the status quo of microphysiological systems available today against industry needs, and assess the broad variety of approaches with fit-for-purpose potential in the drug development cycle. Feasible technical solutions to reach the next levels of human biology in vitro are proposed. Furthermore, key organ-on-a-chip case studies, as well as various national and international programs are highlighted. Finally, a roadmap into the future is outlined, to allow for more predictive and regulatory-accepted substance testing on a global scale.

A Smart Cage With Uniform Wireless Power Distribution in 3D for Enabling Long-Term Experiments With Freely Moving Animals

This paper presents a novel experimental chamber with uniform wireless power distribution in 3D for enabling long-term biomedical experiments with small freely moving animal subjects. The implemented power transmission chamber prototype is based on arrays of parallel resonators and multicoil inductive links, to form a novel and highly efficient wireless power transmission system. The power transmitter unit includes several identical resonators enclosed in a scalable array of overlapping square coils which are connected in parallel to provide uniform power distribution along x and y. Moreover, the proposed chamber uses two arrays of primary resonators, facing each other, and connected in parallel to achieve uniform power distribution along the z axis. Each surface includes 9 overlapped coils connected in parallel and implemented into two layers of FR4 printed circuit board. The chamber features a natural power localization mechanism, which simplifies its implementation and ease its operation by avoiding the need for active detection and control mechanisms. A single power surface based on the proposed approach can provide a power transfer efficiency (PTE) of 69% and a power delivered to the load (PDL) of 120 mW, for a separation distance of 4 cm, whereas the complete chamber prototype provides a uniform PTE of 59% and a PDL of 100 mW in 3D, everywhere inside the chamber with a size of 27×27×16 cm(3).

Flexible, Polarization-Diverse UWB Antennas for Implantable Neural Recording Systems

Implanted antennas for implant-to-air data communications must be composed of material compatible with biological tissues. We design single and dual-polarization antennas for wireless ultra-wideband neural recording systems using an inhomogeneous multi-layer model of the human head. Antennas made from flexible materials are more easily adapted to implantation; we investigate both flexible and rigid materials and examine performance trade-offs. The proposed antennas are designed to operate in a frequency range of 2-11 GHz (having S11 below -10 dB) covering both the 2.45 GHz (ISM) band and the 3.1-10.6 GHz UWB band. Measurements confirm simulation results showing flexible antennas have little performance degradation due to bending effects (in terms of impedance matching). Our miniaturized flexible antennas are 12 mm×12 mm and 10 mm×9 mm for single- and dual-polarizations, respectively. Finally, a comparison is made of four implantable antennas covering the 2-11 GHz range: 1) rigid, single polarization, 2) rigid, dual polarization, 3) flexible, single polarization and 4) flexible, dual polarization. In all cases a rigid antenna is used outside the body, with an appropriate polarization. Several advantages were confirmed for dual polarization antennas: 1) smaller size, 2) lower sensitivity to angular misalignments, and 3) higher fidelity.

A PWM Buck Converter With Load-Adaptive Power Transistor Scaling Scheme Using Analog-Digital Hybrid Control for High Energy Efficiency in Implantable Biomedical Systems

We report a pulse width modulation (PWM) buck converter that is able to achieve a power conversion efficiency (PCE) of > 80% in light loads 100 μA) for implantable biomedical systems. In order to achieve a high PCE for the given light loads, the buck converter adaptively reconfigures the size of power PMOS and NMOS transistors and their gate drivers in accordance with load currents, while operating at a fixed frequency of 1 MHz. The buck converter employs the analog-digital hybrid control scheme for coarse/fine adjustment of power transistors. The coarse digital control generates an approximate duty cycle necessary for driving a given load and selects an appropriate width of power transistors to minimize redundant power dissipation. The fine analog control provides the final tuning of the duty cycle to compensate for the error from the coarse digital control. The mode switching between the analog and digital controls is accomplished by a mode arbiter which estimates the average of duty cycles for the given load condition from limit cycle oscillations (LCO) induced by coarse adjustment. The fabricated buck converter achieved a peak efficiency of 86.3% at 1.4 mA and > 80% efficiency for a wide range of load conditions from 45 μA to 4.1 mA, while generating 1 V output from 2.5-3.3 V supply. The converter occupies 0.375 mm(2) in 0.18 μm CMOS processes and requires two external components: 1.2 μF capacitor and 6.8 μH inductor.

A Low Noise Amplifier for Neural Spike Recording Interfaces

This paper presents a Low Noise Amplifier (LNA) for neural spike recording applications. The proposed topology, based on a capacitive feedback network using a two-stage OTA, efficiently solves the triple trade-off between power, area and noise. Additionally, this work introduces a novel transistor-level synthesis methodology for LNAs tailored for the minimization of their noise efficiency factor under area and noise constraints. The proposed LNA has been implemented in a 130 nm CMOS technology and occupies 0.053 mm-sq. Experimental results show that the LNA offers a noise efficiency factor of 2.16 and an input referred noise of 3.8 μVrms for 1.2 V power supply. It provides a gain of 46 dB over a nominal bandwidth of 192 Hz–7.4 kHz and consumes 1.92 μW. The performance of the proposed LNA has been validated through in vivo experiments with animal models.

A Wireless Optogenetic Headstage with Multichannel Electrophysiological Recording Capability

We present a small and lightweight fully wireless optogenetic headstage capable of optical neural stimulation and electrophysiological recording. The headstage is suitable for conducting experiments with small transgenic rodents, and features two implantable fiber-coupled light-emitting diode (LED) and two electrophysiological recording channels. This system is powered by a small lithium-ion battery and is entirely built using low-cost commercial off-the-shelf components for better flexibility, reduced development time and lower cost. Light stimulation uses customizable stimulation patterns of varying frequency and duty cycle. The optical power that is sourced from the LED is delivered to target light-sensitive neurons using implantable optical fibers, which provide a measured optical power density of 70 mW/mm² at the tip. The headstage is using a novel foldable rigid-flex printed circuit board design, which results into a lightweight and compact device. Recording experiments performed in the cerebral cortex of transgenic ChR2 mice under anesthetized conditions show that the proposed headstage can trigger neuronal activity using optical stimulation, while recording microvolt amplitude electrophysiological signals.

A High Performance Delta-Sigma Modulator for Neurosensing

Recorded neural data are frequently corrupted by large amplitude artifacts that are triggered by a variety of sources, such as subject movements, organ motions, electromagnetic interferences and discharges at the electrode surface. To prevent the system from saturating and the electronics from malfunctioning due to these large artifacts, a wide dynamic range for data acquisition is demanded, which is quite challenging to achieve and would require excessive circuit area and power for implementation. In this paper, we present a high performance Delta-Sigma modulator along with several design techniques and enabling blocks to reduce circuit area and power. The modulator was fabricated in a 0.18-μm CMOS process. Powered by a 1.0-V supply, the chip can achieve an 85-dB peak signal-to-noise-and-distortion ratio (SNDR) and an 87-dB dynamic range when integrated over a 10-kHz bandwidth. The total power consumption of the modulator is 13 μW, which corresponds to a figure-of-merit (FOM) of 45 fJ/conversion step. These competitive circuit specifications make this design a good candidate for building high precision neurosensors.

Wireless gigabit data telemetry for large-scale neural recording

Implantable wireless neural recording from a large ensemble of simultaneously acting neurons is a critical component to thoroughly investigate neural interactions and brain dynamics from freely moving animals. Recent researches have shown the feasibility of simultaneously recording from hundreds of neurons and suggested that the ability of recording a larger number of neurons results in better signal quality. This massive recording inevitably demands a large amount of data transfer. For example, recording 2000 neurons while keeping the signal fidelity ( > 12 bit, > 40 KS/s per neuron) needs approximately a 1-Gb/s data link. Designing a wireless data telemetry system to support such (or higher) data rate while aiming to lower the power consumption of an implantable device imposes a grand challenge on neuroscience community. In this paper, we present a wireless gigabit data telemetry for future large-scale neural recording interface. This telemetry comprises of a pair of low-power gigabit transmitter and receiver operating at 60 GHz, and establishes a short-distance wireless link to transfer the massive amount of neural signals outward from the implanted device. The transmission distance of the received neural signal can be further extended by an externally rendezvous wireless transceiver, which is less power/heat-constraint since it is not at the immediate proximity of the cortex and its radiated signal is not seriously attenuated by the lossy tissue. The gigabit data link has been demonstrated to achieve a high data rate of 6 Gb/s with a bit-error-rate of 10(-12) at a transmission distance of 6 mm, an applicable separation between transmitter and receiver. This high data rate is able to support thousands of recording channels while ensuring a low energy cost per bit of 2.08 pJ/b.

BER performance of implant-to-air high-speed UWB data communications for neural recording systems

Implant-to-air ultra-wideband communication systems are interesting for neural recording systems due to their low power consumption and high data-rates. In this paper we investigate the performance of an implant-to-air wireless link using a realistic model of the biological channel for neural recording systems. We propose an optimized fifth-derivative Gaussian pulse as a transmitted waveform for different modulations: binary phase shift keying (BPSK), on-off keying (OOK) and differential phase shift keying (DPSK). Monitoring of neural responses with high resolution in the brain requires a high data rate link as the number of electrodes is increased. Each electrode needs a data rate around 800 kb/s to support its neural channel. As we target more than 512 electrodes, we require a data link higher than 400 Mbps.

Capacity of UWB wireless channel for neural recording systems

Ultra wide-band (UWB) short-range communication systems are valuable in medical technology, particularly for implanted devices, due to their low-power consumption, low cost, small size and high data rates. Monitoring of neural responses in the brain requires high data rate if we target a system supporting a large number of sensors. In this work, we are interested in the evaluation of the capacity of the ultra wide-band (UWB) channel that we could exploit using a realistic model of the biological channel. The channel characteristics are examined under two scenarios that are related to TX antenna placements. Using optimal power spectrum allocation (OPSA) at the transmitter side, we have computed this capacity by taking into account the fading characteristics of the channel. The results show the pertinence of the optimal power spectrum allocation for this type of channel. An improvement by a factor of 2 to 3 over a uniform power spectrum allocation (UPSA) when the SNR <; 0 dB was obtained. When the SNR is > 40 dB, both approaches give similar results. Antennas placement is examined under two scenarios having contrasting power constraints.

Revealing neuronal function through microelectrode array recordings

Microelectrode arrays and microprobes have been widely utilized to measure neuronal activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate neurons at multiple sites simultaneously. However, unlike the single-cell or single-channel resolution of intracellular recording, microelectrodes detect signals from all possible sources around every sensor. Here, we review the current understanding of microelectrode signals and the techniques for analyzing them. We introduce the ongoing advancements in microelectrode technology, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry. We show how recent advanced microelectrode array measurement methods facilitate the understanding of single neurons as well as network function.

A functional model and simulation of spinal motor pools and intrafascicular recordings of motoneuron activity in peripheral nerve

Decoding motor intent from recorded neural signals is essential for the development of effective neural-controlled prostheses. To facilitate the development of online decoding algorithms we have developed a software platform to simulate neural motor signals recorded with peripheral nerve electrodes, such as longitudinal intrafascicular electrodes (LIFEs). The simulator uses stored motor intent signals to drive a pool of simulated motoneurons with various spike shapes, recruitment characteristics, and firing frequencies. Each electrode records a weighted sum of a subset of simulated motoneuron activity patterns. As designed, the simulator facilitates development of a suite of test scenarios that would not be possible with actual data sets because, unlike with actual recordings, in the simulator the individual contributions to the simulated composite recordings are known and can be methodically varied across a set of simulation runs. In this manner, the simulation tool is suitable for iterative development of real-time decoding algorithms prior to definitive evaluation in amputee subjects with implanted electrodes. The simulation tool was used to produce data sets that demonstrate its ability to capture some features of neural recordings that pose challenges for decoding algorithms.

A CMOS IC-based multisite measuring system for stimulation and recording in neural preparations in vitro

In this report, we describe the system integration of a complementary metal oxide semiconductor (CMOS) integrated circuit (IC) chip, capable of both stimulation and recording of neurons or neural tissues, to investigate electrical signal propagation within cellular networks in vitro. The overall system consisted of three major subunits: a 5.0 × 5.0 mm CMOS IC chip, a reconfigurable logic device (field-programmable gate array, FPGA), and a PC. To test the system, microelectrode arrays (MEAs) were used to extracellularly measure the activity of cultured rat cortical neurons and mouse cortical slices. The MEA had 64 bidirectional (stimulation and recording) electrodes. In addition, the CMOS IC chip was equipped with dedicated analog filters, amplification stages, and a stimulation buffer. Signals from the electrodes were sampled at 15.6 kHz with 16-bit resolution. The measured input-referred circuitry noise was 10.1 μ V root mean square (10 Hz to 100 kHz), which allowed reliable detection of neural signals ranging from several millivolts down to approximately 33 μ Vpp. Experiments were performed involving the stimulation of neurons with several spatiotemporal patterns and the recording of the triggered activity. An advantage over current MEAs, as demonstrated by our experiments, includes the ability to stimulate (voltage stimulation, 5-bit resolution) spatiotemporal patterns in arbitrary subsets of electrodes. Furthermore, the fast stimulation reset mechanism allowed us to record neuronal signals from a stimulating electrode around 3 ms after stimulation. We demonstrate that the system can be directly applied to, for example, auditory neural prostheses in conjunction with an acoustic sensor and a sound processing system.

Biological channel modeling and implantable UWB antenna design for neural recording systems

Ultrawideband (UWB) short-range communication systems have proved to be valuable in medical technology, particularly for implanted devices, due to their low-power consumption, low cost, small size, and high data rates. Neural activity monitoring in the brain requires high data rate (800 kb/s per neural sensor), and we target a system supporting a large number of sensors, in particular, aggregate transmission above 430 Mb/s (∼512 sensors). Knowledge of channel behavior is required to determine the maximum allowable power to 1) respect ANSI guidelines for avoiding tissue damage, and 2) respect FCC guidelines on unlicensed transmissions. We utilize a realistic model of the biological channel to inform the design of antennas for the implanted transmitter and the external receiver under these requirements. Antennas placement is examined under two scenarios having contrasting power constraints. Performance of the system within the biological tissues is examined via simulation and experiment. Our miniaturized antennas, 12 mm ×12 mm, need worst-case receiver sensitivities of -38 and -30.5 dBm for the first and second scenarios, respectively. These sensitivities allow us to successfully detect signals transmitted through tissues in the 3.1-10.6-GHz UWB band.

Rodent scope: a user-configurable digital wireless telemetry system for freely behaving animals

This paper describes the design and implementation of a wireless neural telemetry system that enables new experimental paradigms, such as neural recordings during rodent navigation in large outdoor environments. RoSco, short for Rodent Scope, is a small lightweight user-configurable module suitable for digital wireless recording from freely behaving small animals. Due to the digital transmission technology, RoSco has advantages over most other wireless modules of noise immunity and online user-configurable settings. RoSco digitally transmits entire neural waveforms for 14 of 16 channels at 20 kHz with 8-bit encoding which are streamed to the PC as standard USB audio packets. Up to 31 RoSco wireless modules can coexist in the same environment on non-overlapping independent channels. The design has spatial diversity reception via two antennas, which makes wireless communication resilient to fading and obstacles. In comparison with most existing wireless systems, this system has online user-selectable independent gain control of each channel in 8 factors from 500 to 32,000 times, two selectable ground references from a subset of channels, selectable channel grounding to disable noisy electrodes, and selectable bandwidth suitable for action potentials (300 Hz-3 kHz) and low frequency field potentials (4 Hz-3 kHz). Indoor and outdoor recordings taken from freely behaving rodents are shown to be comparable to a commercial wired system in sorting for neural populations. The module has low input referred noise, battery life of 1.5 hours and transmission losses of 0.1% up to a range of 10 m.

A low-power current-reuse dual-band analog front-end for multi-channel neural signal recording

Thoroughly studying the brain activity of freely moving subjects requires miniature data acquisition systems to measure and wirelessly transmit neural signals in real time. In this application, it is mandatory to simultaneously record the bioelectrical activity of a large number of neurons to gain a better knowledge of brain functions. However, due to limitations in transferring the entire raw data to a remote base station, employing dedicated data reduction techniques to extract the relevant part of neural signals is critical to decrease the amount of data to transfer. In this work, we present a new dual-band neural amplifier to separate the neuronal spike signals (SPK) and the local field potential (LFP) simultaneously in the analog domain, immediately after the pre-amplification stage. By separating these two bands right after the pre-amplification stage, it is possible to process LFP and SPK separately. As a result, the required dynamic range of the entire channel, which is determined by the signal-to-noise ratio of the SPK signal of larger bandwidth, can be relaxed. In this design, a new current-reuse low-power low-noise amplifier and a new dual-band filter that separates SPK and LFP while saving capacitors and pseudo resistors. A four-channel dual-band (SPK, LFP) analog front-end capable of simultaneously separating SPK and LFP is implemented in a TSMC 0.18 μm technology. Simulation results present a total power consumption per channel of 3.1 μw for an input referred noise of 3.28 μV and a NEF for 2.07. The cutoff frequency of the LFP band is fc=280 Hz, and fL=725 Hz and fL=11.2 KHz for SPK, with 36 dB gain for LFP band 46 dB gain for SPK band.

Electromagnetic limits to radiofrequency (RF) neuronal telemetry

The viability of a radiofrequency (RF) telemetry channel for reporting individual neuron activity wirelessly from an embedded antenna to an external receiver is determined. Comparing the power at the transmitting antenna required for the desired Channel Capacity, to the maximum power that this antenna can dissipate in the body without altering or damaging surrounding tissue reveals the severe penalty incurred by miniaturization of the antenna. Using both Specific Absorption Rate (SAR) and thermal damage limits as constraints, and 300 Kbps as the required capacity for telemetry streams 100 ms in duration, the model shows that conventional antennas smaller than 0.1 mm could not support human neuronal telemetry to a remote receiver (1 m away.) Reducing the antenna to 10 microns in size to enable the monitoring of single human neuron signals to a receiver at the surface of the head would require operating with a channel capacity of only 0.3 bps.

A wideband dual-antenna receiver for wireless recording from animals behaving in large arenas

A low-noise wideband receiver (Rx) is presented for a multichannel wireless implantable neural recording (WINeR) system that utilizes time-division multiplexing of pulse width modulated (PWM) samples. The WINeR-6 Rx consists of four parts: 1) RF front end; 2) signal conditioning; 3) analog output (AO); and 4) field-programmable gate array (FPGA) back end. The RF front end receives RF-modulated neural signals in the 403-490 MHz band with a wide bandwidth of 18 MHz. The frequency-shift keying (FSK) PWM demodulator in the FPGA is a time-to-digital converter with 304 ps resolution, which converts the analog pulse width information to 16-bit digital samples. Automated frequency tracking has been implemented in the Rx to lock onto the free-running voltage-controlled oscillator in the transmitter (Tx). Two antennas and two parallel RF paths are used to increase the wireless coverage area. BCI-2000 graphical user interface has been adopted and modified to acquire, visualize, and record the recovered neural signals in real time. The AO module picks three demultiplexed channels and converts them into analog signals for direct observation on an oscilloscope. One of these signals is further amplified to generate an audio output, offering users the ability to listen to ongoing neural activity. Bench-top testing of the Rx performance with a 32-channel WINeR-6 Tx showed that the input referred noise of the entire system at a Tx-Rx distance of 1.5 m was 4.58 μV rms with 8-bit resolution at 640 kSps. In an in vivo experiment, location-specific receptive fields of hippocampal place cells were mapped during a behavioral experiment in which a rat completed 40 laps in a large circular track. Results were compared against those acquired from the same animal and the same set of electrodes by a commercial hardwired recording system to validate the wirelessly recorded signals.

A portable system for recording neural activity in indoor and outdoor environments

We present a self-contained portable USB based device that can amplify and record small bioelectric signals from insects and animals. The system combines a purpose built low noise amplifier with off the shelf components to provide a low cost low power system for recording electrophysiological signals. Using open source software the system is programmed as a simple USB device and can be connected to any USB capable computer for recording data. This simple and universal interface provides the ability to connect to a variety of systems. Open source acquisition software was also written to record signals under the linux operating system. Performance analysis shows that our device is able to record good quality signals both indoors and outdoors and delivers this performance at a very low cost. Compared to larger systems our device provides the additional advantage of portability given that it can fit into a pocket and costs a fraction of large systems used in electrophysiology labs.

Realistic modeling of the biological channel for the design of implantable wireless UWB communication systems

Several emerging medical applications require that a miniature data acquisition device be implanted into the head to extract and wirelessly communicate brain activity to other devices. Designing a reliable communication link for such an application requires a realistic model of the surrounding biological tissues. This paper exploits a realistic model of the biological channel to design a suitable wireless ultra wideband communication link in a brain monitoring application. Two scenarios for positioning the implanted transmitting antenna are considered. The 1(st) scenario places the antenna under the skull, whereas the 2(nd) scenario places the antenna under the skin, above the skull. The propagation characteristics of the signal through the tissues of the human head have been determined with full-wave electromagnetic simulation based on Finite Element Method. The implantable antenna and the external antenna are key components to establish an electromagnetic link between an implanted transmitter and an external receiver. The average specific absorption rate (ASAR) of the implantable antennas are evaluated and compared for the two proposed scenarios. Moreover, the maximum available power from the implanted antenna is evaluated to characterize the performance of the communication link established between the implantable antenna and the external antenna, with respect to spectrum and safety regulations. We show how sensitive the receiver must be in order to implement a reliable telemetry link based on the proposed model of the channel.

Topography and coating of platinum improve the electrochemical properties and neuronal guidance

To improve neuronal-electrode interfaces, we analyzed the influence of surface topographies combined with coating on the electrochemistry of platinum and neuronal differentiation of PC-12 cells. Surface structuring on nanoscale was realized by femtosecond laser ablation. Additional coating with laminin (LA), collagen type I (COL) or poly-d-lysine (PDL) did not change the produced topography. We further demonstrated that impedance could be improved in all cases. The pre-requisites of differentiation - viability and attachment - were fulfilled on the topography. Cell attachment of non-differentiated and differentiated cells and their formation of focal adhesion complexes were even enhanced compared to unstructured platinum. However, without the nerve growth factor (NGF) no cellular outgrowth and differentiation were possible. The topography enabled cell elongation and reduced the amount of rounded cells, but less effective than coating. Differentiation was either comparable or increased on the structures when compared with unstructured coatings. For instance, microtubule associated protein (MAP2) was detected most on the topography alone. But a combination of surface structuring and coating had the strongest impact on differentiation: the usage of COL provoked best cell elongation and beta III tubulin expression, PDL best synaptophysin. LA-coating had no noteworthy effect. These findings point out that innovative electronic devices like cochlear implants include two aspects: (a) nanotopography to improve the transmission of electrical signals and neuronal attachment; and (b) an additional coating to stimulate neuronal differentiation.

A multichannel integrated circuit for electrical recording of neural activity, with independent channel programmability

Since a few decades, micro-fabricated neural probes are being used, together with microelectronic interfaces, to get more insight in the activity of neuronal networks. The need for higher temporal and spatial recording resolutions imposes new challenges on the design of integrated neural interfaces with respect to power consumption, data handling and versatility. In this paper, we present an integrated acquisition system for in vitro and in vivo recording of neural activity. The ASIC consists of 16 low-noise, fully-differential input channels with independent programmability of its amplification (from 100 to 6000 V/V) and filtering (1-6000 Hz range) capabilities. Each channel is AC-coupled and implements a fourth-order band-pass filter in order to steeply attenuate out-of-band noise and DC input offsets. The system achieves an input-referred noise density of 37 nV/√Hz, a NEF of 5.1, a CMRR > 60 dB, a THD < 1% and a sampling rate of 30 kS/s per channel, while consuming a maximum of 70 μA per channel from a single 3.3 V. The ASIC was implemented in a 0.35 μm CMOS technology and has a total area of 5.6 × 4.5 mm². The recording system was successfully validated in in vitro and in vivo experiments, achieving simultaneous multichannel recordings of cell activity with satisfactory signal-to-noise ratios.

A transcutaneous power transfer interface based on a multicoil inductive link

This paper presents a transcutaneous power transfer link based on a multicoil structure. Multicoil inductive links using 4-coil or 3-coil topologies have shown significant improvement over conventional 2-coil structures for transferring power transcutaneously across larger distances and with higher efficiency. However, such performance comes at the cost of additional inductors and capacitor in the system, which is not convenient in implantable applications. This paper presents a transcutaneous power transfer interface that takes advantage on a 3-coils inductive topology to achieve wide separation distances and high power transfer efficiency without increasing the size of the implanted device compared to a conventional 2-coil structure. In the proposed link, a middle coil is placed outside the body to act as a repeater between an external transmitting coil and an implanted receiving coil. The proposed structure allows optimizing the link parameters after implantation by changing the characteristics of the repeater coil. Simulation with a multilayer model of the biological tissues and measured results are presented for the proposed link.