Long-term Neural Recording Research Articles

Mechanically adaptive and deployable intracortical probes enable long-term neural electrophysiological recordings

Flexible intracortical probes offer important opportunities for stable neural interfaces by reducing chronic immune responses, but their advances usually come with challenges of difficult implantation and limited recording span. Here, we reported a mechanically adaptive and deployable intracortical probe, which features a foldable fishbone-like structural design with branching electrodes on a temperature-responsive shape memory polymer (SMP) substrate. Leveraging the temperature-triggered soft-rigid phase transition and shape memory characteristic of SMP, this probe design enables direct insertion into brain tissue with minimal footprint in a folded configuration while automatically softening to reduce mechanical mismatches with brain tissue and deploying electrodes to a broader recording span under physiological conditions. Experimental and numerical studies on the material softening and structural folding-deploying behaviors provide insights into the design, fabrication, and operation of the intracortical probes. The chronically implanted neural probe in the rat cortex demonstrates that the proposed neural probe can reliably detect and track individual units for months with stable impedance and signal amplitude during long-term implantation. The work provides a tool for stable neural activity recording and creates engineering opportunities in basic neuroscience and clinical applications.

Tentacle Microelectrode Arrays Uncover Soft Boundary Neurons in Hippocampal CA1.

Hippocampal CA1 neurons show intense firing at specific spatial locations, modulated by isolated landmarks. However, the impact of real-world scene transitions on neuronal activity remains unclear. Moreover, long-term neural recording during movement challenges device stability. Conventional rigid-based electrodes cause inflammatory responses, restricting recording durations. Inspired by the jellyfish tentacles, the multi-conductive layer ultra-flexible microelectrode arrays (MEAs) are developed. The tentacle MEAs ensure stable recordings during movement, thereby enabling the discovery of soft boundary neurons. The soft boundary neurons demonstrate high-frequency firing that aligns with the boundaries of scene transitions. Furthermore, the localization ability of soft boundary neurons improves with more scene transition boundaries, and their activity decreases when these boundaries are removed. The innovation of ultra-flexible, high-biocompatible tentacle MEAs improves the understanding of neural encoding in spatial cognition. They offer the potential for long-term in vivo recording of neural information, facilitating breakthroughs in the understanding and application of brain spatial navigation mehanisms.

Short-Term Effects of Gamma Stimulation on Neuroinflammation at the Tissue-Electrode Interface in Motor Cortex

ObjectivesThe reliability of long-term neural recordings as therapeutic interventions for motor and sensory disorders is hampered by the brain tissue response. Previous work showed that flickering light at gamma frequencies (ie, 20–50 Hz) causes enhanced microglial recruitment in the visual cortex. The effects of gamma stimulation on glial cells surrounding implanted neural electrodes are not well understood. We hypothesized that invasive stimulation in the gamma frequency band increases microglial recruitment in the short term and reduces astrogliosis at the tissue-electrode interface. Materials and MethodsMale Long Evans rats were implanted with dual-shank silicon microelectrode arrays into the motor cortex. After implantation, rats received one hour of 40-Hz stimulation at a constant current of 10 μA using charge-balanced, biphasic pulses on one shank, and the other shank served as the nonstimulated control. Postmortem, tissue sections were stained with ectodermal dysplasia 1 (ED1) for activated microglia, glial fibrillary acidic protein (GFAP) for astrocytes, and 4′,6-diamidino-2-phenylindole (DAPI) for nonspecific nuclei. Fluorescent intensity and cell number as a function of distance from the tissue-electrode interface were used to quantify all stained sections. ResultsFluorescent intensity for ED1 was nearly 40% lower for control than for stimulated sites (0–500 μm away from the implant), indicating increased microglial recruitment to the stimulated site (p < 0.05). Fluorescent intensity for GFAP was >67% higher for control than for stimulated sites (0–500 μm away from the implant), indicating reduced astrogliosis at the stimulated site (p < 0.05). No differences were observed in DAPI-stained sections between conditions. ConclusionsThese results suggest that short-term gamma stimulation modulates glial recruitment in the immediate vicinity of the microelectrode. Future studies will investigate the long-term effects of gamma stimulation on glial recruitment at the tissue-electrode interface as a strategy to improve long-term recording reliability.

Self-assembled ultraflexible probes for long-term neural recordings and neuromodulation.

Ultraflexible microelectrode arrays (MEAs) that can stably record from a large number of neurons after their chronic implantation offer opportunities for understanding neural circuit mechanisms and developing next-generation brain-computer interfaces. The implementation of ultraflexible MEAs requires their reliable implantation into deep brain tissues in a minimally invasive manner, as well as their precise integration with optogenetic tools to enable the simultaneous recording of neural activity and neuromodulation. Here, we describe the process for the preparation of elastocapillary self-assembled ultraflexible MEAs, their use in combination with adeno-associated virus vectors carrying opsin genes and promoters to form an optrode probe and their in vivo experimental use in the brains of rodents, enabling electrophysiological recordings and optical modulation of neuronal activity over long periods of time (on the order of weeks to months). The procedures, including device fabrication, probe assembly and implantation, can be completed within 3 weeks. The protocol is intended to facilitate the applications of ultraflexible MEAs for long-term neuronal activity recording and combined electrophysiology and optogenetics. The protocol requires users with expertise in clean room facilities for the fabrication of ultraflexible MEAs.

Modeling and inference methods for switching regime-dependent dynamical systems with multiscale neural observations

Objective. Realizing neurotechnologies that enable long-term neural recordings across multiple spatial-temporal scales during naturalistic behaviors requires new modeling and inference methods that can simultaneously address two challenges. First, the methods should aggregate information across all activity scales from multiple recording sources such as spiking and field potentials. Second, the methods should detect changes in the regimes of behavior and/or neural dynamics during naturalistic scenarios and long-term recordings. Prior regime detection methods are developed for a single scale of activity rather than multiscale activity, and prior multiscale methods have not considered regime switching and are for stationary cases. Approach. Here, we address both challenges by developing a switching multiscale dynamical system model and the associated filtering and smoothing methods. This model describes the encoding of an unobserved brain state in multiscale spike-field activity. It also allows for regime-switching dynamics using an unobserved regime state that dictates the dynamical and encoding parameters at every time-step. We also design the associated switching multiscale inference methods that estimate both the unobserved regime and brain states from simultaneous spike-field activity. Main results. We validate the methods in both extensive numerical simulations and prefrontal spike-field data recorded in a monkey performing saccades for fluid rewards. We show that these methods can successfully combine the spiking and field potential observations to simultaneously track the regime and brain states accurately. Doing so, these methods lead to better state estimation compared with single-scale switching methods or stationary multiscale methods. Also, for single-scale linear Gaussian observations, the new switching smoother can better generalize to diverse system settings compared to prior switching smoothers. Significance. These modeling and inference methods effectively incorporate both regime-detection and multiscale observations. As such, they could facilitate investigation of latent switching neural population dynamics and improve future brain-machine interfaces by enabling inference in naturalistic scenarios where regime-dependent multiscale activity and behavior arise.

Anti-fouling peptide functionalization of ultraflexible neural probes for long-term neural activity recordings in the brain

Implantable neural probes constitute an essential tool for neuronal activity recordings in basic neuroscience and also hold great promise for the development of neuroprosthesis to restore lost motor or sensory functions of the body. However, conventional neural probes are susceptible to biofouling because of their physicochemical mismatch with neural tissues, resulting in signal degradation in chronic studies. Here, we describe an ultraflexible neural probe (uFNP) with anti-fouling zwitterionic peptide modification for long-term stable neural activity recordings. The anti-fouling zwitterionic peptide consists of two parts: negatively charged glutamic acid (E) and positively charged lysine (K) formed EKEKEK (EK) head to create a hydration layer that resists protein adsorption on the microelectrodes, and a fragment of laminin formed IKVAV tail to increase the adhesion of the microelectrodes to neuronal cells. We demonstrate that EK-IKVAV modified uFNPs can allow for stable neuronal activity recordings over 16 weeks. Immunohistological studies confirm that EK-IKVAV functionalized uFNPs could induce greatly reduced neuronal cell loss. Collectively, these results suggest that the anti-fouling zwitterionic peptide functionalization of uFNPs provide a promising route to construct biocompatible and stable neural interfaces.

Micro-wrinkle strategy for stable soft neural interface with optimized electroplated PEDOT:PSS

A highly reliable neural interface is required in long-term neural signal recording in vivo for neuroscience research and the treatment of neurological disorders. Organic poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT:PSS) is a promising candidate for a next-generation neural interface material due to its better faradaic charge transfer and capacitive charge coupling than metal electrodes such as Au or Pt. However, its weak adhesion to underlying metallic layers impedes its application with significant cracks or delamination. Here, a MEMS-compatible strategy is proposed to obtain wrinkled microelectrodes based on oil-pretreated elastomer substrate to improve the electrochemical performance and stability of electroplated PEDOT:PSS coating. To discover the optimized electroplating parameters, the galvanostatic electroplating method is applied with incremental time from 0 to 500 s. The modified wrinkled microelectrodes with electroplating time of 300 s permits 10 000 cyclic voltammetry scanning cycles without cracks nor significant change in charge storage capacity or electrochemical impedance, whereas the cracks and delamination appear when the electroplating time increases to 500 s.

Estimation of dispersive properties of encapsulation tissue surrounding deep brain stimulation electrodes in the rat.

The aim of this study was to estimate the electrical properties of the encapsulation tissue surrounding chronically implanted electrodes for deep brain stimulation in the rat. The impedance spectrum of a concentric bipolar microelectrode implanted in the rat brain was measured immediately following surgery and after 8 weeks of implantation. The experimental impedance data were used in combination with a finite element model of the rat brain using a parametric sweep method to estimate the electrical properties of the tissue surrounding the electrode in acute and chronic conditions. In the acute case, the conductivity and relative permittivity of the peri-electrode space were frequency independent with an estimated conductivity of 0.38 S/m and relative permittivity of 123. The electrical properties of the encapsulation tissue in the chronic condition were fitted to a dispersive Cole-Cole model. The estimated conductivity and relative permittivity in the chronic condition at 1 kHz were 0.028 S/m and 2×105, respectively. The estimated tissue properties can be used in combination with computational modeling as a basis for optimization of chronically implanted electrodes to increase the efficacy of long-term neural recording and stimulation.

Sequential Neural Activity in Primary Motor Cortex during Sleep.

Sequential firing of neurons during sleep is thought to play a role in the consolidation of learning. However, direct evidence for such sequence replay is limited to only a few brain areas and sleep states mainly in rodents. Using a custom-designed wearable neural data logger and chronically implanted electrodes, we made long-term recordings of neural activity in the primary motor cortex of two female nonhuman primates during free behavior and natural sleep. We used the local field potential (LFP) spectrogram to characterize sleep cycles, and examined firing rates, correlations, and sequential firing of neurons at different frequency bands through the cycle. Slow-wave sleep (SWS) was characterized by low neural firing rates and high synchrony, reflecting slow oscillations between cortical down and up states. However, the order in which neurons entered up states was similar to the sequence of neural activity observed at low frequencies during waking behavior. In addition, we found evidence of brief bursts of theta oscillation, associated with non-SWS states, during which neurons fired in strikingly regular sequential order phase-locked to the LFP. Theta sequences were preserved between waking and sleep, but appeared not to resemble the order of neural activity observed at lower frequencies. The sequential firing of neurons during slow oscillations and theta bursts may contribute to the consolidation of procedural memories during sleep.SIGNIFICANCE STATEMENT Replay of sequential neural activity during sleep is believed to support consolidation of daytime learning. Despite a wealth of studies investigating sequential replay in association with episodic and spatial memory, it is unknown whether similar sequences occur in motor areas during sleep. Within long-term neural recordings from monkey motor cortex, we found two distinct patterns of sequential activity during different phases of the natural sleep cycle. Slow-wave sleep was associated with delta-band sequences that resembled low-frequency activity during movement, while occasional brief bursts of theta oscillation were associated with a different order of sequential firing. Our results are the first report of sequential sleep replay in the motor cortex, which may play an important role in consolidation of procedural learning.

Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis

Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it remains a formidable challenge to extract unbiased and interpretable descriptions of how rapid single-trial circuit dynamics change slowly over many trials to mediate learning. We demonstrate a simple tensor component analysis (TCA) can meet this challenge by extracting three interconnected, low-dimensional descriptions of neural data: neuron factors, reflecting cell assemblies; temporal factors, reflecting rapid circuit dynamics mediating perceptions, thoughts, and actions within each trial; and trial factors, describing both long-term learning and trial-to-trial changes in cognitive state. We demonstrate the broad applicability of TCA by revealing insights intodiverse datasets derived from artificial neural networks, large-scale calcium imaging of rodent prefrontal cortex during maze navigation, and multielectrode recordings of macaque motor cortex during brain machine interface learning.

Fluidic Microactuation of Flexible Electrodes for Neural Recording.

Soft and conductive nanomaterials like carbon nanotubes, graphene, and nanowire scaffolds have expanded the family of ultraflexible microelectrodes that can bend and flex with the natural movement of the brain, reduce the inflammatory response, and improve the stability of long-term neural recordings. However, current methods to implant these highly flexible electrodes rely on temporary stiffening agents that temporarily increase the electrode size and stiffness thus aggravating neural damage during implantation, which can lead to cell loss and glial activation that persists even after the stiffening agents are removed or dissolve. A method to deliver thin, ultraflexible electrodes deep into neural tissue without increasing the stiffness or size of the electrodes will enable minimally invasive electrical recordings from within the brain. Here we show that specially designed microfluidic devices can apply a tension force to ultraflexible electrodes that prevents buckling without increasing the thickness or stiffness of the electrode during implantation. Additionally, these "fluidic microdrives" allow us to precisely actuate the electrode position with micron-scale accuracy. To demonstrate the efficacy of our fluidic microdrives, we used them to actuate highly flexible carbon nanotube fiber (CNTf) microelectrodes for electrophysiology. We used this approach in three proof-of-concept experiments. First, we recorded compound action potentials in a soft model organism, the small cnidarian Hydra. Second, we targeted electrodes precisely to the thalamic reticular nucleus in brain slices and recorded spontaneous and optogenetically evoked extracellular action potentials. Finally, we inserted electrodes more than 4 mm deep into the brain of rats and detected spontaneous individual unit activity in both cortical and subcortical regions. Compared to syringe injection, fluidic microdrives do not penetrate the brain and prevent changes in intracranial pressure by diverting fluid away from the implantation site during insertion and actuation. Overall, the fluidic microdrive technology provides a robust new method to implant and actuate ultraflexible neural electrodes.

A portable platform to collect and review behavioral data simultaneously with neurophysiological signals.

This paper presents a portable platform to collect and review behavioral data simultaneously with neurophysiological signals. The whole system is comprised of four parts: a sensor data acquisition interface, a socket server for real-time data streaming, a Simulink system for real-time processing and an offline data review and analysis toolbox. A low-cost microcontroller is used to acquire data from external sensors such as accelerometer and hand dynamometer. The micro-controller transfers the data either directly through USB or wirelessly through a bluetooth module to a data server written in C++ for MS Windows OS. The data server also interfaces with the digital glove and captures HD video from webcam. The acquired sensor data are streamed under User Datagram Protocol (UDP) to other applications such as Simulink/Matlab for real-time analysis and recording. Neurophysiological signals such as electroencephalography (EEG), electrocorticography (ECoG) and local field potential (LFP) recordings can be collected simultaneously in Simulink and fused with behavioral data. In addition, we developed a customized Matlab Graphical User Interface (GUI) software to review, annotate and analyze the data offline. The software provides a fast, user-friendly data visualization environment with synchronized video playback feature. The software is also capable of reviewing long-term neural recordings. Other featured functions such as fast preprocessing with multithreaded filters, annotation, montage selection, power-spectral density (PSD) estimate, time-frequency map and spatial spectral map are also implemented.

A novel bio-mimicking, planar nano-edge microelectrode enables enhanced long-term neural recording.

Our inability to accurately monitor individual neurons and their synaptic activity precludes fundamental understanding of brain function under normal and various pathological conditions. However, recent breakthroughs in micro- and nano-scale fabrication processes have advanced the development of neuro-electronic hybrid technology. Among such devices are three-dimensional and planar electrodes, offering the advantages of either high fidelity or longer-term recordings respectively. Here, we present the next generation of planar microelectrode arrays with “nano-edges” that enable long-term (≥1 month) and high fidelity recordings at a resolution 15 times higher than traditional planar electrodes. This novel technology enables better understanding of brain function and offers a tremendous opportunity towards the development of future bionic hybrids and drug discovery devices.

Flexible, Penetrating Brain Probes Enabled by Advances in Polymer Microfabrication.

The acquisition of high-fidelity, long-term neural recordings in vivo is critically important to advance neuroscience and brain–machine interfaces. For decades, rigid materials such as metal microwires and micromachined silicon shanks were used as invasive electrophysiological interfaces to neurons, providing either single or multiple electrode recording sites. Extensive research has revealed that such rigid interfaces suffer from gradual recording quality degradation, in part stemming from tissue damage and the ensuing immune response arising from mechanical mismatch between the probe and brain. The development of “soft” neural probes constructed from polymer shanks has been enabled by advancements in microfabrication; this alternative has the potential to mitigate mismatch-related side effects and thus improve the quality of recordings. This review examines soft neural probe materials and their associated microfabrication techniques, the resulting soft neural probes, and their implementation including custom implantation and electrical packaging strategies. The use of soft materials necessitates careful consideration of surgical placement, often requiring the use of additional surgical shuttles or biodegradable coatings that impart temporary stiffness. Investigation of surgical implantation mechanics and histological evidence to support the use of soft probes will be presented. The review concludes with a critical discussion of the remaining technical challenges and future outlook.

Chronic intracortical neural recordings using microelectrode arrays coated with PEDOT–TFB

Microelectrode arrays have been extensively utilized to record extracellular neuronal activity for brain–machine interface applications. Modifying the microelectrodes with conductive polymers such as poly(3,4-ethylenedioxythiophene) (PEDOT) has been reported to be advantageous because it increases the effective surface area of the microelectrodes, thereby decreasing impedance and enhancing charge transfer capacity. However, the long term stability and integrity of such coatings for chronic recordings remains unclear. Previously, our group has demonstrated that use of the smaller counter ion tetrafluoroborate (TFB) during electrodeposition increased the stability of the PEDOT coatings in vitro compared to the commonly used counter ion poly(styrenesulfonate) (PSS). In the current work, we examined the long-term in vivo performance of PEDOT–TFB coated microelectrodes. To do so, we selectively modified half of the microelectrodes on NeuroNexus single shank probes with PEDOT–TFB while the other half of the microelectrodes were modified with gold as a control. The modified probes were then implanted into the primary motor cortex of rats. Single unit recordings were observed on both PEDOT–TFB and gold control microelectrodes for more than 12weeks. Compared to the gold-coated microelectrodes, the PEDOT–TFB coated microelectrodes exhibited an overall significantly lower impedance and higher number of units per microelectrode specifically for the first four weeks. The majority of PEDOT–TFB microelectrodes with activity had an impedance magnitude lower than 400kΩ at 1kHz. Our equivalent circuit modeling of the impedance data suggests stability in the polymer-related parameters for the duration of the study. In addition, when comparing PEDOT–TFB microelectrodes with and without long-term activity, we observed a distinction in certain circuit parameters for these microelectrodes derived from equivalent circuit modeling prior to implantation. This observation may prove useful in qualifying PEDOT–TFB microelectrodes with a greater likelihood of registering long-term activity. Overall, our findings confirm that PEDOT–TFB is a chronically stable coating for microelectrodes to enable neural recording. Statement of significanceMicroelectrode arrays have been extensively utilized to record extracellular neuronal activity for brain–machine interface applications. Poly(3,4-ethylenedioxythiophene) (PEDOT) has gained interest because of its unique electrochemical characteristics and its excellent intrinsic electrical conductivity. However, the long-term stability of the PEDOT film, especially for chronic neural applications, is unclear. In this manuscript, we report for the first time the use of highly stable PEDOT doped with tetrafluoroborate (TFB) for long-term neural recordings. We show that PEDOT–TFB coated microelectrodes on average register more units compared to control gold microelectrodes for at least first four weeks post implantation. We collected the in vivo impedance data over a wide frequency spectrum and developed an equivalent circuit model which helped us determine certain parameters to distinguish between PEDOT–TFB microelectrodes with and without long-term activity. Our findings suggest that PEDOT–TFB is a chronically stable coating for neural recording microelectrodes. As such, PEDOT–TFB could facilitate chronic recordings with ultra-small and high-density neural arrays.

Towards a large-scale recording system: demonstration of polymer-based penetrating array for chronic neural recording.

The brain is a massively interconnected network of specialized circuits. Even primary sensory areas, once thought to support relatively simple, feed-forward processing, are now known to be parts of complex feedback circuits. All brain functions depend on millisecond timescale interactions across these brain networks. Current approaches cannot measure or manipulate such large-scale interactions. Here we demonstrate that polymer-based, penetrating, micro-electrode arrays can provide high quality neural recordings from awake, behaving animals over periods of months. Our results indicate that polymer electrodes are a viable substrate for the development of systems that can record from thousands of channels across months to years. This is our first step towards developing a 1000+ electrode system capable of providing high-quality, long-term neural recordings.

Magnetically Inserted Neural Electrodes: Tissue Response and Functional Lifetime.

Neural recording and stimulation have great clinical potential. Long-term neural recording remains a challenge, however, as implantable electrodes eventually fail due to the adverse effects of the host tissue response to the indwelling implant. Astrocytes and microglia attempt to engulf the electrode, increasing the electrical impedance between the electrode and neurons, and possibly pushing neurons away from the recording site. Faster insertion speed, finer tip geometry, smaller size, and lower material stiffness all seem to decrease damage caused by insertion and reduce the intensity of the tissue response. However, electrodes that are too small result in buckling, making insertion impossible. In this paper, we assess the viability of high-speed (27.8 m/s) deployment of 25 μm, ferromagnetic microelectrodes into rat brain. To characterize functionality of magnetically inserted electrodes, 4 Long-Evans rats were implanted for 31 days with impedance measurements and neural recordings taken daily. Performance was compared to 150 μm diameter PlasticsOne electrodes since 25 μm electrodes buckled during "slow speed" insertion. Platinum-iron magnetically inserted electrodes resolved single unit activity throughout the duration of the study in one rat, and saw no significant change (p=0.970) in impedance (4.54% increase) from day 0 (Z0 ≈ 144 kΩ,Z31 ≈ 150 kΩ). These findings provide a proof-of-concept for magnetic insertion as a viable insertion method that enables nonbuckling implantation of small (25 μm) microelectrodes, with potential for neural recording applications.

A carbon-fiber electrode array for long-term neural recording

Objective. Chronic neural recording in behaving animals is an essential method for studies of neural circuit function. However, stable recordings from small, densely packed neurons remains challenging, particularly over time-scales relevant for learning. Approach. We describe an assembly method for a 16-channel electrode array consisting of carbon fibers (<5 µm diameter) individually insulated with Parylene-C and fire-sharpened. The diameter of the array is approximately 26 µm along the full extent of the implant. Main results. Carbon fiber arrays were tested in HVC (used as a proper name), a song motor nucleus, of singing zebra finches where individual neurons discharge with temporally precise patterns. Previous reports of activity in this population of neurons have required the use of high impedance electrodes on movable microdrives. Here, the carbon fiber electrodes provided stable multi-unit recordings over time-scales of months. Spike-sorting indicated that the multi-unit signals were dominated by one, or a small number of cells. Stable firing patterns during singing confirmed the stability of these clusters over time-scales of months. In addition, from a total of 10 surgeries, 16 projection neurons were found. This cell type is characterized by sparse stereotyped firing patterns, providing unambiguous confirmation of single cell recordings. Significance. Carbon fiber electrode bundles may provide a scalable solution for long-term neural recordings of densely packed neurons.

A New System Architecture for Future Long-Term High-Density Neural Recording

This brief presents a new system architecture for neural recording to allow higher recording density and more tolerance to interface degeneration and artifacts. Compared with its conventional counterpart, the proposed architecture has a frequency-dependent gain stage that inherently rejects dc offset and attenuates low-frequency interferences. In the digital domain, frequency compensation is used to restore the signals “seen” by an electrode. Powered by a switched-capacitor design, the proposed architecture can lead to major improvements on system performance metrics, including input impedance, distortion, and dynamic range. In simulations with different electrode sizes and degeneration levels, the proposed architecture consistently gives high-fidelity recording data. We argue that the proposed architecture is more suitable for long-term high-density invasive brain-computer interface experiments as a replacement to better support a mimicked “Moore's Law” on recording density.

Design of Wireless Links to Implanted Brain–Machine Interface Microelectronic Systems

This letter presents a monolithic integration of an antenna with an array of neural recording electrodes on a flexible thin film. The structure was designed for long-term neural recording in a wireless brain-machine interface system. The implant-on-body antenna pair is optimized for maximal link power efficiency to maximize the battery life of a portable outside-body control unit. We provide guidelines for the design of the sub-skin-depth implant antenna and validate the antenna simulation model with wireless link measurements in air. We propose a new computational analysis of both the power and voltage delivery to the battery-free implant under design variations to guarantee efficient on-chip RF-to-dc conversion.