Intracortical Brain-Machine Interfaces Advance Sensorimotor Neuroscience

Depletion of complement factor 3 delays the neuroinflammatory response to intracortical microelectrodes

The neuroinflammatory response to intracortical microelectrodes (IMEs) used with brain-machine interfacing (BMI) applications is regarded as the primary contributor to poor chronic performance. Recent developments in high-plex gene expression technologies have allowed for an evolution in the investigation of individual proteins or genes to be able to identify specific pathways of upregulated genes that may contribute to the neuroinflammatory response. Several key pathways that are upregulated following IME implantation are involved with the complement system. The complement system is part of the innate immune system involved in recognizing and eliminating pathogens - a significant contributor to the foreign body response against biomaterials. Specifically, we have identified Complement 3 (C3) as a gene of interest because it is the intersection of several key complement pathways. In this study, we investigated the role of C3 in the IME inflammatory response by comparing the neuroinflammatory gene expression at the microelectrode implant site between C3 knockout (C3-/-) and wild-type (WT) mice. We have found that, like in WT mice, implantation of intracortical microelectrodes in C3-/- mice yields a dramatic increase in the neuroinflammatory gene expression at all post-surgery time points investigated. However, compared to WT mice, C3 depletion showed reduced expression of many neuroinflammatory genes pre-surgery and 4 weeks post-surgery. Conversely, depletion of C3 increased the expression of many neuroinflammatory genes at 8 weeks and 16 weeks post-surgery, compared to WT mice. Our results suggest that C3 depletion may be a promising therapeutic target for acute, but not chronic, relief of the neuroinflammatory response to IME implantation. Additional compensatory targets may also be required for comprehensive long-term reduction of the neuroinflammatory response for improved intracortical microelectrode performance.

The effect of a Mn(III)tetrakis(4-benzoic acid)porphyrin (MnTBAP) coating on the chronic recording performance of planar silicon intracortical microelectrode arrays

Intracortical microelectrode arrays (MEAs) are used to record neural activity. However, their implantation initiates a neuroinflammatory cascade, involving the accumulation of reactive oxygen species, leading to interface failure. Here, we coated commercially-available MEAs with Mn(III)tetrakis(4-benzoic acid)porphyrin (MnTBAP), to mitigate oxidative stress. First, we assessed the in vitro cytotoxicity of modified sample substrates. Then, we implanted 36 rats with uncoated, MnTBAP-coated ("Coated"), or (3-Aminopropyl)triethoxysilane (APTES)-coated devices - an intermediate step in the coating process. We assessed electrode performance during the acute (1-5 weeks), sub-chronic (6-11 weeks), and chronic (12-16 weeks) phases after implantation. Three subsets of animals were euthanized at different time points to assess the acute, sub-chronic and chronic immunohistological responses. Results showed that MnTBAP coatings were not cytotoxic in vitro, and their implantation in vivo improved the proportion of electrodes during the sub-chronic and chronic phases; APTES coatings resulted in failure of the neural interface during the chronic phase. In addition, MnTBAP coatings improved the quality of the signal throughout the study and reduced the neuroinflammatory response around the implant as early as two weeks, an effect that remained consistent for months post-implantation. Together, these results suggest that MnTBAP coatings are a potentially useful modification to improve MEA reliability.

Differential expression of genes involved in the chronic response to intracortical microelectrodes

Brain-Machine Interface systems (BMIs) are clinically valuable devices that can provide functional restoration for patients with spinal cord injury or improved integration for patients requiring prostheses. Intracortical microelectrodes can record neuronal action potentials at a resolution necessary for precisely controlling BMIs. However, intracortical microelectrodes have a demonstrated history of progressive decline in the recording performance with time, inhibiting their usefulness. One major contributor to decreased performance is the neuroinflammatory response to the implanted microelectrodes. The neuroinflammatory response can lead to neurodegeneration and the formation of a glial scar at the implant site. Historically, histological imaging of relatively few known cellular and protein markers has characterized the neuroinflammatory response to implanted microelectrode arrays. However, neuroinflammation requires many molecular players to coordinate the response - meaning traditional methods could result in an incomplete understanding. Taking advantage of recent advancements in tools to characterize the relative or absolute DNA/RNA expression levels, a few groups have begun to explore gene expression at the microelectrode-tissue interface. We have utilized a custom panel of ∼813 neuroinflammatory-specific genes developed with NanoString for bulk tissue analysis at the microelectrode-tissue interface. Our previous studies characterized the acute innate immune response to intracortical microelectrodes. Here we investigated the gene expression at the microelectrode-tissue interface in wild-type (WT) mice chronically implanted with nonfunctioning probes. We found 28 differentially expressed genes at chronic time points (4WK, 8WK, and 16WK), many in the complement and extracellular matrix system. Further, the expression levels were relatively stable over time. Genes identified here represent chronic molecular players at the microelectrode implant sites and potential therapeutic targets for the long-term integration of microelectrodes. STATEMENT OF SIGNIFICANCE: Intracortical microelectrodes can record neuronal action potentials at a resolution necessary for the precise control of Brain-Machine Interface systems (BMIs). However, intracortical microelectrodes have a demonstrated history of progressive declines in the recording performance with time, inhibiting their usefulness. One major contributor to the decline in these devices is the neuroinflammatory response against the implanted microelectrodes. Historically, neuroinflammation to implanted microelectrode arrays has been characterized by histological imaging of relatively few known cellular and protein markers. Few studies have begun to develop a more in-depth understanding of the molecular pathways facilitating device-mediated neuroinflammation. Here, we are among the first to identify genetic pathways that could represent targets to improve the host response to intracortical microelectrodes, and ultimately device performance.

Clinical neuroscience and neurotechnology: An amazing symbiosis

In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.

High-Density, Actively Multiplexed µECoG Array on Reinforced Silicone Substrate

Simultaneous interrogation of electrical signals from wide areas of the brain is vital for neuroscience research and can aid in understanding the mechanisms of brain function and treatments for neurological disorders. There emerges a demand for development of devices with highly conformal interfaces that can span large cortical regions, have sufficient spatial resolution, and chronic recording capability while keeping a small implantation footprint. In this work, we have designed 61 channel and 48 channel high-density, cortical, micro-electrocorticographic electrode arrays with 400 μm pitch on an ultra-soft but durable substrate. We have also developed a custom multiplexing integrated circuit (IC), methods for packaging the IC in a water-tight liquid crystal polymer casing, and a micro-bonding method for attaching the electronics package to the electrode array. With the integrated multiplexer, the number of external wire connections can be reduced to 16 wires, thereby diminishing the invasive footprint of the device. Both the electrode array and IC were tested in vivo in a rat model to demonstrate the ability to sense finely-localized electrophysiological signals.

Investigation of the Feasibility of Ventricular Delivery of Resveratrol to the Microelectrode Tissue Interface

(1) Background: Intracortical microelectrodes (IMEs) are essential to basic brain research and clinical brain-machine interfacing applications. However, the foreign body response to IMEs results in chronic inflammation and an increase in levels of reactive oxygen and nitrogen species (ROS/RNS). The current study builds on our previous work, by testing a new delivery method of a promising antioxidant as a means of extending intracortical microelectrodes performance. While resveratrol has shown efficacy in improving tissue response, chronic delivery has proven difficult because of its low solubility in water and low bioavailability due to extensive first pass metabolism. (2) Methods: Investigation of an intraventricular delivery of resveratrol in rats was performed herein to circumvent bioavailability hurdles of resveratrol delivery to the brain. (3) Results: Intraventricular delivery of resveratrol in rats delivered resveratrol to the electrode interface. However, intraventricular delivery did not have a significant impact on electrophysiological recordings over the six-week study. Histological findings indicated that rats receiving intraventricular delivery of resveratrol had a decrease of oxidative stress, yet other biomarkers of inflammation were found to be not significantly different from control groups. However, investigation of the bioavailability of resveratrol indicated a decrease in resveratrol accumulation in the brain with time coupled with inconsistent drug elution from the cannulas. Further inspection showed that there may be tissue or cellular debris clogging the cannulas, resulting in variable elution, which may have impacted the results of the study. (4) Conclusions: These results indicate that the intraventricular delivery approach described herein needs further optimization, or may not be well suited for this application.

Online control of reach accuracy in mice

Reaching movements, as a basic yet complex motor behavior, are a foundational model system in neuroscience. In particular, there has been a significant recent expansion of investigation into the neural circuit mechanisms of reach behavior in mice. Nevertheless, quantification of mouse reach kinematics remains lacking, limiting comparison to the primate literature. In this study, we quantitatively demonstrate the homology of mouse reach kinematics to primate reach and also discover novel late-phase correlational structure that implies online control. Overall, our results highlight the decelerative phase of reach as important in driving successful outcome. Specifically, we develop and implement a novel statistical machine-learning algorithm to identify kinematic features associated with successful reaches and find that late-phase kinematics are most predictive of outcome, signifying online reach control as opposed to preplanning. Moreover, we identify and characterize late-phase kinematic adjustments that are yoked to midflight position and velocity of the limb, allowing for dynamic correction of initial variability, with head-fixed reaches being less dependent on position in comparison to freely behaving reaches. Furthermore, consecutive reaches exhibit positional error correction but not hot-handedness, implying opponent regulation of motor variability. Overall, our results establish foundational mouse reach kinematics in the context of neuroscientific investigation, characterizing mouse reach production as an active process that relies on dynamic online control mechanisms.NEW & NOTEWORTHY Mice use reaching movements to grasp and manipulate objects in their environment, similar to primates. To better establish mouse reach as a model for motor control, we implement several analytical frameworks, from basic kinematic relationships to statistical machine learning, to quantify mouse reach, finding many canonical features of primate reaches are conserved in mice, as well as evidence for midflight course corrections, expanding the utility of mouse reach paradigms for motor control studies.

Toward Standardization of Electrophysiology and Computational Tissue Strain in Rodent Intracortical Microelectrode Models

Progress has been made in the field of neural interfacing using both mouse and rat models, yet standardization of these models' interchangeability has yet to be established. The mouse model allows for transgenic, optogenetic, and advanced imaging modalities which can be used to examine the biological impact and failure mechanisms associated with the neural implant itself. The ability to directly compare electrophysiological data between mouse and rat models is crucial for the development and assessment of neural interfaces. The most obvious difference in the two rodent models is size, which raises concern for the role of device-induced tissue strain. Strain exerted on brain tissue by implanted microelectrode arrays is hypothesized to affect long-term recording performance. Therefore, understanding any potential differences in tissue strain caused by differences in the implant to tissue size ratio is crucial for validating the interchangeability of rat and mouse models. Hence, this study is aimed at investigating the electrophysiological variances and predictive device-induced tissue strain. Rat and mouse electrophysiological recordings were collected from implanted animals for eight weeks. A finite element model was utilized to assess the tissue strain from implanted intracortical microelectrodes, taking into account the differences in the depth within the cortex, implantation depth, and electrode geometry between the two models. The rat model demonstrated a larger percentage of channels recording single unit activity and number of units recorded per channel at acute but not chronic time points, relative to the mouse model Additionally, the finite element models also revealed no predictive differences in tissue strain between the two rodent models. Collectively our results show that these two models are comparable after taking into consideration some recommendations to maintain uniform conditions for future studies where direct comparisons of electrophysiological and tissue strain data between the two animal models will be required.

Channel Projection-Based CCA Target Identification Method for an SSVEP-Based BCI System of Quadrotor Helicopter Control

The brain-computer interface (BCI) plays an important role in assisting patients with amyotrophic lateral sclerosis (ALS) to enable them to participate in communication and entertainment. In this study, a novel channel projection-based canonical correlation analysis (CP-CCA) target identification method for steady-state visual evoked potential- (SSVEP-) based BCI system was proposed. The single-channel electroencephalography (EEG) signals of multiple trials were recorded when the subject is under the same stimulus frequency. The CCAs between single-channel EEG signals of multiple trials and sine-cosine reference signals were obtained. Then, the optimal reference signal of each channel was utilized to estimate the test EEG signal. To validate the proposed method, we acquired the training dataset with two testing conditions including the optimal time window length and the number of the trial of training data. The offline experiments conducted a comparison of the proposed method with the traditional canonical correlation analysis (CCA) and power spectrum density analysis (PSDA) method using a 5-class SSVEP dataset that was recorded from 10 subjects. Based on the training dataset, the online 3D-helicopter control experiment was carried out. The offline experimental results showed that the proposed method outperformed the CCA and the PSDA methods in terms of classification accuracy and information transfer rate (ITR). Furthermore, the online experiments of 3-DOF helicopter control achieved an average accuracy of 87.94 ± 5.93% with an ITR of 21.07 ± 4.42 bit/min.

Volitional control of single-electrode high gamma local field potentials by people with paralysis

Intracortical brain-computer interfaces (BCIs) can enable individuals to control effectors, such as a computer cursor, by directly decoding the user's movement intentions from action potentials and local field potentials (LFPs) recorded within the motor cortex. However, the accuracy and complexity of effector control achieved with such "biomimetic" BCIs will depend on the degree to which the intended movements used to elicit control modulate the neural activity. In particular, channels that do not record distinguishable action potentials and only record LFP modulations may be of limited use for BCI control. In contrast, a biofeedback approach may surpass these limitations by letting the participants generate new control signals and learn strategies that improve the volitional control of signals used for effector control. Here, we show that, by using a biofeedback paradigm, three individuals with tetraplegia achieved volitional control of gamma LFPs (40-400 Hz) recorded by a single microelectrode implanted in the precentral gyrus. Control was improved over a pair of consecutive sessions up to 3 days apart. In all but one session, the channel used to achieve control lacked distinguishable action potentials. Our results indicate that biofeedback LFP-based BCIs may potentially contribute to the neural modulation necessary to obtain reliable and useful control of effectors. NEW & NOTEWORTHY Our study demonstrates that people with tetraplegia can volitionally control individual high-gamma local-field potential (LFP) channels recorded from the motor cortex, and that this control can be improved using biofeedback. Motor cortical LFP signals are thought to be both informative and stable intracortical signals and, thus, of importance for future brain-computer interfaces.

Nano-Architectural Approaches for Improved Intracortical Interface Technologies

Intracortical microelectrodes (IME) are neural devices that initially were designed to function as neuroscience tools to enable researchers to understand the nervous system. Over the years, technology that aids interfacing with the nervous system has allowed the ability to treat patients with a wide range of neurological injuries and diseases. Despite the substantial success that has been demonstrated using IME in neural interface applications, these implants eventually fail due to loss of quality recording signals. Recent strategies to improve interfacing with the nervous system have been inspired by methods that mimic the native tissue. This review focusses on one strategy in particular, nano-architecture, a term we introduce that encompasses the approach of roughening the surface of the implant. Various nano-architecture approaches have been hypothesized to improve the biocompatibility of IMEs, enhance the recording quality, and increase the longevity of the implant. This review will begin by introducing IME technology and discuss the challenges facing the clinical deployment of IME technology. The biological inspiration of nano-architecture approaches will be explained as well as leading fabrication methods used to create nano-architecture and their limitations. A review of the effects of nano-architecture surfaces on neural cells will be examined, depicting the various cellular responses to these modified surfaces in both in vitro and pre-clinical models. The proposed mechanism elucidating the ability of nano-architectures to influence cellular phenotype will be considered. Finally, the frontiers of next generation nano-architecture IMEs will be identified, with perspective given on the future impact of this interfacing approach.

Quantitative simulation of extracellular single unit recording from the surface of cortex

OBJECTIVE

Neural recording is important for a wide variety of clinical applications. Until recently, recording from the surface of the brain, even when using micro-electrocorticography (μECoG) arrays, was not thought to enable recording from individual neurons. Recent results suggest that when the surface electrode contact size is sufficiently small, it may be possible to record single neurons from the brain's surface. In this study, we use computational techniques to investigate the ability of surface electrodes to record the activity of single neurons.

APPROACH

The computational model included the rat head, μECoG electrode, two existing multi-compartmental neuron models, and a novel multi-compartmental neuron model derived from patch clamp experiments in layer 1 of the cortex.

MAIN RESULTS

Using these models, we reproduced single neuron recordings from μECoG arrays, and elucidated their possible source. The model resembles the experimental data when spikes originate from layer 1 neurons that are less than 60 μm from the cortical surface. We further used the model to explore the design space for surface electrodes. Although this model does not include biological or thermal noise, the results indicate the electrode contact area should be 100 μm² or smaller to maintain a detectable waveform amplitude. Furthermore, the model shows the width of lateral insulation could be reduced, which may reduce scar formation, while retaining 95% of signal amplitude.

SIGNIFICANCE

Overall, the model suggests single-unit surface recording is limited to neurons in layer 1 and further improvement in electrode design is needed.

Effect of Different Movement Speed Modes on Human Action Observation: An EEG Study

Action observation (AO) generates event-related desynchronization (ERD) suppressions in the human brain by activating partial regions of the human mirror neuron system (hMNS). The activation of the hMNS response to AO remains controversial for several reasons. Therefore, this study investigated the activation of the hMNS response to a speed factor of AO by controlling the movement speed modes of a humanoid robot's arm movements. Since hMNS activation is reflected by ERD suppressions, electroencephalography (EEG) with BCI analysis methods for ERD suppressions were used as the recording and analysis modalities. Six healthy individuals were asked to participate in experiments comprising five different conditions. Four incremental-speed AO tasks and a motor imagery (MI) task involving imaging of the same movement were presented to the individuals. Occipital and sensorimotor regions were selected for BCI analyses. The experimental results showed that hMNS activation was higher in the occipital region but more robust in the sensorimotor region. Since the attended information impacts the activations of the hMNS during AO, the pattern of hMNS activations first rises and subsequently falls to a stable level during incremental-speed modes of AO. The discipline curves suggested that a moderate speed within a decent inter-stimulus interval (ISI) range produced the highest hMNS activations. Since a brain computer/machine interface (BCI) builds a path-way between human and computer/mahcine, the discipline curves will help to construct BCIs made by patterns of action observation (AO-BCI). Furthermore, a new method for constructing non-invasive brain machine brain interfaces (BMBIs) with moderate AO-BCI and motor imagery BCI (MI-BCI) was inspired by this paper.

Implantation of Neural Probes in the Brain Elicits Oxidative Stress

Clinical implantation of intracortical microelectrodes has been hindered, at least in part, by the perpetual inflammatory response occurring after device implantation. The neuroinflammatory response observed after device implantation has been correlated to oxidative stress that occurs due to neurological injury and disease. However, there has yet to be a definitive link of oxidative stress to intracortical microelectrode implantation. Thus, the objective of this study is to give direct evidence of oxidative stress following intracortical microelectrode implantation. This study also aims to identify potential molecular targets to attenuate oxidative stress observed postimplantation. Here, we implanted adult rats with silicon non-functional microelectrode probes for 4 weeks and compared the oxidative stress response to no surgery controls through postmortem gene expression analysis and qualitative histological observation of oxidative stress markers. Gene expression analysis results at 4 weeks postimplantation indicated that EH domain-containing 2, prion protein gene (Prnp), and Stearoyl-Coenzyme A desaturase 1 (Scd1) were all significantly higher for animals implanted with intracortical microelectrode probes compared to no surgery control animals. To the contrary, NADPH oxidase activator 1 (Noxa1) relative gene expression was significantly lower for implanted animals compared to no surgery control animals. Histological observation of oxidative stress showed an increased expression of oxidized proteins, lipids, and nucleic acids concentrated around the implant site. Collectively, our results reveal there is a presence of oxidative stress following intracortical microelectrode implantation compared to no surgery controls. Further investigation targeting these specific oxidative stress linked genes could be beneficial to understanding potential mechanisms and downstream therapeutics that can be utilized to reduce oxidative stress-mediated damage following microelectrode implantation.

Sensory percepts induced by microwire array and DBS microstimulation in human sensory thalamus

BACKGROUND

Microstimulation in human sensory thalamus (ventrocaudal, VC) results in focal sensory percepts in the hand and arm which may provide an alternative target site (to somatosensory cortex) for the input of prosthetic sensory information. Sensory feedback to facilitate motor function may require simultaneous or timed responses across separate digits to recreate perceptions of slip as well as encoding of intensity variations in pressure or touch.

OBJECTIVES

To determine the feasibility of evoking sensory percepts on separate digits with variable intensity through either a microwire array or deep brain stimulation (DBS) electrode, recreating "natural" and scalable percepts relating to the arm and hand.

METHODS

We compared microstimulation within ventrocaudal sensory thalamus through either a 16-channel microwire array (∼400 kΩ per channel) or a 4-channel DBS electrode (∼1.2 kΩ per contact) for percept location, size, intensity, and quality sensation, during thalamic DBS electrode placement in patients with essential tremor.

RESULTS

Percepts in small hand or finger regions were evoked by microstimulation through individual microwires and in 5/6 patients sensation on different digits could be perceived from stimulation through separate microwires. Microstimulation through DBS electrode contacts evoked sensations over larger areas in 5/5 patients, and the apparent intensity of the perceived response could be modulated with stimulation amplitude. The perceived naturalness of the sensation depended both on the pattern of stimulation as well as intensity of the stimulation.

CONCLUSIONS

Producing consistent evoked perceptions across separate digits within sensory thalamus is a feasible concept and a compact alternative to somatosensory cortex microstimulation for prosthetic sensory feedback. This approach will require a multi-element low impedance electrode with a sufficient stimulation range to evoke variable intensities of perception and a predictable spread of contacts to engage separate digits.

Should We Stop Saying 'Glia' and 'Neuroinflammation'?

Central nervous system (CNS) therapeutics based on the theoretical framework of neuroinflammation have only barely succeeded. We argue that a problem may be the wrong use of the term 'neuroinflammation' as a distinct nosological entity when, based on recent evidence, it may not explain CNS disease pathology. Indeed, the terms 'neuroinflammation' and 'glia' could be obsolete. First, unbiased molecular profiling of CNS cell populations and individual cells reveals striking phenotypic heterogeneity in health and disease. Second, astrocytes, microglia, oligodendrocytes, and NG2 cells may contribute to higher-brain functions by performing actions beyond housekeeping. We propose that CNS diseases be viewed as failed circuits caused in part by disease-specific dysfunction of cells traditionally called 'glia', and hence, favor therapies promoting their functional recovery.

Hybrid EEG-fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control

In this paper, a hybrid electroencephalography–functional near-infrared spectroscopy (EEG–fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain–computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG–fNIRS interface.