Motor neuroprosthesis implanted with neurointerventional surgery improves capacity for activities of daily living tasks in severe paralysis: first in-human experience

Advances in endovascular brain computer interface: Systematic review and future implications

BACKGROUND

Brain-computer interfaces (BCIs) translate neural activity into real-world commands. While traditional invasive BCIs necessitate craniotomy, endovascular BCIs offer a minimally invasive alternative using the venous system for electrode placement.

NEW METHOD

This systematic review evaluates the technical feasibility, safety, and clinical outcomes of endovascular BCIs, discussing their future implications. A systematic review was conducted per PRISMA guidelines. The search spanned PubMed, Web of Science, and Scopus databases using keywords related to neural interfaces and endovascular approaches. Studies were included if they reported on endovascular BCIs in preclinical or clinical settings. Dual independent screening and extraction focused on electrode material, recording capabilities, safety parameters, and clinical efficacy.

RESULTS

From 1385 initial publications, 26 met the inclusion criteria. Seventeen studies investigated the Stentrode device. Among the 24 preclinical studies, 16 used ovine or rodent models, and 9 addressed engineering or simulation aspects. Two clinical studies reported six ALS patients successfully using an endovascular BCI for digital communication. Preclinical data established the endovascular ovine model, demonstrating stable neural recordings and vascular changes with long-term implantation. Key challenges include thrombosis risk, long-term electrode stability, and anatomical variability.

COMPARISON WITH EXISTING METHODS

Endovascular BCI reduced invasiveness, improved safety profiles, with comparable neural recording fidelity to invasive methods, and promising preliminary clinical outcomes in severely paralyzed patients.

CONCLUSIONS

Early results are promising, but clinical data remain scarce. Further research is needed to optimize signal processing, enhance electrode biocompatibility, and refine endovascular procedures for broader clinical applications.

Decoding cortical responses from visual input using an endovascular brain-computer interface

Objective.Implantable neural interfaces enable recording of high-quality brain signals that can improve our understanding of brain function. This work examined the feasibility of using a minimally invasive endovascular neural interface (ENI) to record interpretable cortical activity from the visual cortex.Approach. A sheep model (n= 5) was used to record and decode visually evoked potentials from the cortex both with an ENI and a subdural electrode grid. Sets of distinct experimental visual stimuli were presented to attempt decoding from the recorded cortical potentials, using perceptual categories of colour, contrast, movement direction orientation, spatial frequency and temporal frequency. Decoding performances are presented as accuracy scores from K-fold cross-validation of a stratified random forest classification model. The study compared the signal quality and decoding performance between the ENI and electrocorticography (ECoG) electrodes.Main results. Recordings from the ENI array resulted in lower decoding performances than the ECoG array, but the classification scores were significantly above chance in the stimuli categories of colour, contrast, direction and temporal frequency. This study is the first report of visually evoked neural activity using a minimally-invasive ENI.Significance. Overall, the results show that implantable macro-electrodes yield sufficient neural signal definition to discern primary visual percepts, using both endo-vascular and intracranial surgical placements.

Continuous operation of battery-free implants enables advanced fracture recovery monitoring

Substantial hurdles in achieving a digitally connected body with seamless, chronic, high-fidelity organ interfaces include challenges of sourcing energy and ensuring reliable connectivity. Operation is currently limited by batteries that occupy large volumes. Wireless, battery-free operation is therefore paramount, requiring a system-level solution that enables seamless connection of wearable and implantable devices. Here, we present a technological framework that enables wireless, battery-free implant operation in freely moving subjects, with streaming of high-fidelity information from low-displacement, battery-free implants with little user interaction. This is accomplished using at-distance wirelessly recharged, wearable biosymbiotic devices for powering and communication with fully implantable NFC-enabled implants. We demonstrate this capability with osseosurface electronics that stream bone health insight. Eleven-month-long large animal studies highlight the ability of implants to relay information on bone health without negative impact on the subjects. Clinical translatability is shown through fracture healing studies that demonstrate biomarkers of bone union.

An Interventional Brain-Computer Interface for Long-Term EEG Collection and Motion Classification of a Quadruped Mammal

Brain-computer interfaces (BCI) acquire electroencephalogram (EEG) signals to effectively address postoperative motor dysfunction in stroke patients by discerning their motor intentions during significant movements. Traditionally, noninvasive BCIs have been constrained by limitations in their usage environments; whereas, invasive BCIs damage neural permanently. Therefore, we proposed a novel interventional BCI, in which electrodes are implanted along the veins into the brain to acquire intracerebral EEG signals without an open craniotomy. We collect EEG signals from the primary motor cortex in the superior sagittal sinus of sheep during three different significant movements: laying down; standing; and walking. The first three month data are used to train the neural network, and The fourth month of data were used to validate. The deep learning model achieved an 86% accuracy rate in classifying motion states in validation. Furthermore, the results of the power spectral density (PSD) show that the signal power in the main frequency band did not decrease over a period of five months, which demonstrates that the interventional BCI has the ability to effectively capture EEG signals over long periods of time.

Trans-arterial approach for neural recording and stimulation: Present and future

Neural recording and stimulation are fundamental techniques used for brain computer interfaces (BCIs). BCIs have significant potential for use in a range of brain disorders. However, for most BCIs, electrode implantation requires invasive craniotomy procedures, which have a risk of infection, hematoma, and immune responses. Such drawbacks may limit the extensive application of BCIs. There has been a rapid increase in the development of endovascular technologies and devices. Indeed, in a clinical trial, stent electrodes have been endovascularly implanted via a venous approach and provided an effective endovascular BCI to help disabled patients. Several authors have reviewed the use of endovascular recordings or endovascular BCIs. However, there is limited information on the use of trans-arterial BCIs. Herein, we reviewed the literature on the use of trans-arterial neural recording and stimulation for BCIs, and discuss their potential in terms of anatomical features, device innovations, and clinical applications. Although the use of trans-arterial recording and stimulation in the brain remains challenging, we believe it has high potential for both scientists and physicians.

Non-Surgical, In-Stent Membrane Bioelectronics for Long-Term Intracranial Pressure Monitoring

Traditional intracranial pressure (ICP) monitoring methods, using intraventricular catheters, face significant limitations, including high invasiveness, discrete data, calibration complexities, and drift issues, which hinder long-term and stable monitoring. Here, a non-surgical, in-stent membrane bioelectronic system is presented for continuous and reliable ICP monitoring. This platform integrates a capacitive thin-film sensor with a stent, enabling precise real-time detection of pressure fluctuations directly within the dural venous sinus without requiring skull penetration or frequent recalibration. The sensor demonstrates a high sensitivity of 0.052%/mmHg and a broad, readable pressure range of 3-30 mmHg while maintaining calibration-free and drift-free performance. A series of in vivo studies highlight the system's superior sensitivity, rapid sampling rate, and long-term stability compared to conventional microcatheters. Statistical analyses reveal a strong agreement between the device and clinical reference, underscoring its potential to revolutionize ICP monitoring. These advancements pave the way for broader clinical applications, minimizing complications and improving patient outcomes in neurocritical care.

Lessons Learned and Challenges Ahead in the Translation of Implantable Microscale Sensors and Actuators

Microscale sensors and actuators have been widely explored by the scientific community to augment the functionality of conventional medical implants. However, despite the many innovative concepts proposed, a negligible fraction has successfully made the leap from concept to clinical translation. This shortfall is primarily due to the considerable disparity between academic research prototypes and market-ready products. As such, it is critically important to examine the lessons learned in successful commercialization efforts to inform early-stage translational research efforts. Here, we review the regulatory prerequisites for market approval and provide a comprehensive analysis of commercially available microimplants from a device design perspective. Our objective is to illuminate both the technological advances underlying successfully commercialized devices and the key takeaways from the commercialization process, thereby facilitating a smoother pathway from academic research to clinical impact.

Acoustic Inspired Brain-to-Sentence Decoder for Logosyllabic Language

Recent advances in brain-computer interfaces (BCIs) have demonstrated the potential to decode language from brain activity into sound or text, which has predominantly focused on alphabetic languages, such as English. However, logosyllabic languages, such as Mandarin Chinese, present marked challenges for establishing decoders that cover all characters, due to its unique syllable structures, extended character sets (e.g., over 50,000 characters for Mandarin Chinese), and complex mappings between characters and syllables, thus hindering practical applications. Here, we leverage the acoustic features of Mandarin Chinese syllables, constructing prediction models for syllable components (initials, tones, and finals), and decode speech-related stereoelectroencephalography (sEEG) signals into coherent Chinese sentences. The results demonstrate a high sentence-level offline decoding performance with a median character accuracy of 71.00% over the full spectrum of characters in the best participant. We also verified that incorporating acoustic-related features into the design of prediction models substantially enhances the accuracy of initials, tones, and finals. Moreover, our findings revealed that effective speech decoding also involves subcortical structures like the thalamus in addition to traditional language-related brain regions. Overall, we established a brain-to-sentence decoder for logosyllabic languages over full character set with a large intracranial electroencephalography dataset.

Clinical indications and patient outcomes of intracranial venous sinus stenting beyond overt idiopathic intracranial hypertension: a scoping review

BACKGROUND

Intracranial venous sinus stenting (VSS) was initially developed as an alternative approach to addressing venous outflow obstruction in the context of idiopathic intracranial hypertension (IIH). In recent years, the technique has been increasingly used for other conditions involving venous compromise beyond overt IIH. The aim of this study was to describe the nature and volume of literature considering clinical applications and efficacy of VSS.

METHODS

A scoping review was conducted using MEDLINE, EMBASE, Scopus, The Cochrane Library, and various grey literature sources. Articles published since the introduction of VSS in 2002 were included. Independent screening of articles occurred in two stages: title-and-abstract and full-text screening. Relevant data was extracted and evidence mapping with narrative synthesis followed.

RESULTS

The search strategy yielded 1814 articles, of which 165 were included in this review. A total of 27 additional clinical indications of VSS beyond overt IIH were identified, spanning a diverse range of neurological pathology. Most evidence came from case reports, with the United States being the commonest study origin. Focal stenotic lesions and stenting locations were distributed throughout the dural sinus anatomy. An outline of patient outcomes reported by VSS providers is presented, with pulsatile tinnitus and visual impairment showing the greatest likelihood of clinical resolution.

CONCLUSION

This scoping review demonstrates the wider clinical utility and therapeutic potential of VSS beyond overt IIH. We also highlight the need for further studies to assess efficacy for each respective indication and clinical standardisation of VSS practice.

5-year follow-up of a fully implanted brain-computer interface in a spinal cord injury patient

Spinal cord injury (SCI) affects over 250 000 individuals in the US. Brain-computer interfaces (BCIs) may improve quality of life by controlling external devices. Invasive intracortical BCIs have shown promise in clinical trials but degrade in the chronic period and tether patients to acquisition hardware. Alternatively, electrocorticography (ECoG) records data from electrodes on the cortex,and studies evaluating fully implanted BCI-ECoG systems are scarce. Objective. We seek to address this need using a fully implanted ECoG-based BCI that allows for home use in SCI.Approach.The patient used a long-term BCI system, initially controlling an functional electrical stimulation orthosis in the lab and later using an external mechanical orthosis at home. To evaluate its long-term viability, electrode contact impedance, signal quality, and decoder performance were measured. Signal quality was assessed using signal-to-noise ratio and maximum bandwidth of the signal. Decoder performance was monitored using the area under the receiver operator characteristic curve (AUROC).Main results.The study analyzed data from the patient's home environment over 54 months, revealing that the device was used at home for 38 ± 24 min on average daily. After six months, we observed stable event-related desynchronization that aided in determining the onset of motor intention. The decoder's average AUROC across months was 0.959. Importantly, 40 months of the data collected was gather from the subject's home or community environment. The results indicate long-term ECoG recordings were stable for motor-imagery classification and motor control in the community environment in a case of an individual with SCI.Significance.This study presents the long-term feasibility and viability of an ECoG-based BCI system that persists in the home environment in a case of SCI. Future research should explore larger electrode counts with more participants to confirm this stability. Understanding these trends is crucial for clinical utility and chronic viability in broader patient populations.

Comparing a BCI communication system in a patient with Multiple System Atrophy, with an animal model

Paralysis affects many people worldwide, and the people affected often suffer from impaired communication. We developed a microelectrode-based Brain-Computer Interface (BCI) for enabling communication in patients affected by paralysis, and implanted it in a patient with Multiple System Atrophy (MSA), a neurodegenerative disease that causes widespread neural symptoms including paralysis. To verify the effectiveness of the BCI system, it was also tested by implanting it in a non-human primate (NHP). Data from the human and NHP were used to train binary classifiers two different types of machine learning models: a Linear Discriminant Analysis (LDA) model, and a Long Short-Term Memory (LSTM)-based Artificial Neural Network (ANN). The LDA model performed at up to 72.7 % accuracy for binary decoding in the human patient, however, performance was highly variable and was much lower on most recording days. The BCI system was able to accurately decode movement vs non-movement in the NHP (accuracy using LDA: 82.7 ± 3.3 %, LSTM: 83.7 ± 2.2 %, 95 % confidence intervals), however it was not able to with recordings from the human patient (accuracy using LDA: 47.0 ± 5.1 %, LSTM: 44.6 ± 9.9 %, 95 % confidence intervals). We discuss how neurodegenerative diseases such as MSA can impede BCI-based communication, and postulate on the mechanisms by which this may occur.

Motor activity in gamma and high gamma bands recorded with a Stentrode from the human motor cortex in two people with ALS

Objective.This study examined the strength and stability of motor signals in low gamma and high gamma bands of vascular electrocorticograms (vECoG) recorded with endovascular stent-electrode arrays (Stentrodes) implanted in the superior sagittal sinus of two participants with severe paralysis due to amyotrophic lateral sclerosis.Approach.vECoG signals were recorded from two participants in the COMMAND trial, an Early Feasibility Study of the Stentrode brain-computer interface (BCI) (NCT05035823). The participants performed attempted movements of their ankles or hands. The signals were band-pass filtered to isolate low gamma (30-70 Hz) and high gamma (70-200 Hz) components. The strength of vECoG motor activity was measured as signal-to-noise ratio (SNR) and the percentage change in signal amplitude between the rest and attempted movement epochs, which we termed depth of modulation (DoM). We trained and tested classifiers to evaluate the accuracy and stability of detecting motor intent.Main results.Both low gamma and high gamma were modulated during attempted movements. For Participant 1, the average DoM across channels and sessions was 125.41 ± 17.53% for low gamma and 54.23 ± 4.52% for high gamma, with corresponding SNR values of 6.75 ± 0.37 dB and 3.69 ± 0.28 dB. For Participant 2, the average DoM was 22.77 ± 4.09% for low gamma and 22.53 ± 2.04% for high gamma, with corresponding SNR values of 1.72 ± 0.25 dB and 1.73 ± 0.13 dB. vECoG amplitudes remained significantly different between rest and move periods over the 3 month testing period, with >90% accuracy in discriminating attempted movement from rest epochs for both participants. For Participant 1, the average DoM was strongest during attempted movements of both ankles, while for Participant 2, the DoM was greatest for attempted movement of the right hand. The overall classification accuracy was 91.43% for Participant 1 and 70.37% for Participant 2 in offline decoding of multiple attempted movements and rest conditions.Significance.By eliminating the need for open brain surgery, the Stentrode offers a promising BCI alternative, potentially enhancing access to BCIs for individuals with severe motor impairments. This study provides preliminary evidence that the Stentrode can detect discriminable signals indicating motor intent, with motor signal modulation observed over the 3 month testing period reported here.

Stakeholder's perspective on brain-computer interfaces for children and young adults with cerebral palsy

Communication Brain-Computer Interfaces (cBCIs) are a promising tool for people with motor and speech impairment, in particular for children and young adults with communication impairments, for example due to cerebral palsy (CP). Here we aimed to create a solid basis for the user-centered design of cBCIs for children and young adults with severe CP by investigating the perspectives of their parents/caregivers and health care professionals on communication and cBCIs. We conducted an online survey on 1) current communication problems and usability of used aids, 2) interest in cBCIs, and 3) preference for specific types of cBCIs. A total of 19 parents/caregivers and 36 health care professionals who interacted directly with children and young adults (8-25 years old) with severe CP, corresponding to Gross Motor Function Classification System level IV or V, participated. Both groups of respondents indicated that motor impairment occurred the most frequently and had the greatest impact on communication. The currently used communication aids included mainly no/low-tech aids and high-tech aids. The majority of health care professionals and parents/caregivers reported an interest in cBCIs, with a slight preference for implanted electrodes over non-implanted ones, and no preference for either of the two proposed mental BCI control strategies. Results indicate that cBCIs should be considered for a subpopulation of children and young adults with severe CP, and that in the development of cBCIs for this group both visual stimuli and sensorimotor rhythms, as well as the use of implanted electrodes, should be considered.

Direct 3D rotational venography: Insights in optimizing visualization

IntroductionThree-dimensional rotational venography (3D-RV) expands on three-dimensional rotational angiography to provide high-quality venous anatomy details, complementing traditional two-dimensional digital subtraction angiography and supporting the diagnosis and treatment of venous pathologies. This article presents a series of patients who underwent advanced 3D-RV for the evaluation of idiopathic intracranial hypertension (IIH).MethodsIn this single-center retrospective case series, we analyzed 13 patients with IIH who underwent direct 3D-RV from June 2023 to May 2024. Access was obtained by placing a 6-Fr or larger guide catheter in the rostral internal jugular vein, with a Zoom 35 microcatheter advanced to the middle third of the superior sagittal sinus. A descriptive analysis was performed based on the demographic and radiation metrics.ResultsSixteen direct 3D-RV procedures were performed on 13 patients with IIH (mean age 42.06 ± 13.13 years), including 10 females and three males. General anesthesia was administered for interventions (12 cases) and monitored anesthesia care for manometry (four cases). Venous access was obtained via upper extremity veins in 13 cases (81.25%) and the right common femoral vein in three cases (18.75%). Mean fluoroscopy time was 42.0 ± 29.8 min, contrast dose 92.2 ± 34.2 mL, dose area product (DAP) 18.6 ± 10.5 Gy·cm², and air kerma 1.3 ± 0.56 Gy, with a mean procedure time of 71.3 ± 42.0 min. The 3D-RV procedure contributed an additional 1.86 ± 0.6 Gy to DAP and 0.072 ± 0.021 Gy to air kerma, representing an extra 6.26% and 10.59% of the skin dose, respectively. No procedure-related or in-hospital complications occurred.ConclusionsThe 3D-RV procedure is reliable and safe, offering improved accuracy in assessing venous anatomy and stents without significantly impacting procedure time or radiation dose.

Overcoming failure: improving acceptance and success of implanted neural interfaces

Implanted neural interfaces are electronic devices that stimulate or record from neurons with the purpose of improving the quality of life of people who suffer from neural injury or disease. Devices have been designed to interact with neurons throughout the body to treat a growing variety of conditions. The development and use of implanted neural interfaces is increasing steadily and has shown great success, with implants lasting for years to decades and improving the health and quality of life of many patient populations. Despite these successes, implanted neural interfaces face a multitude of challenges to remain effective for the lifetime of their users. The devices are comprised of several electronic and mechanical components that each may be susceptible to failure. Furthermore, implanted neural interfaces, like any foreign body, will evoke an immune response. The immune response will differ for implants in the central nervous system and peripheral nervous system, as well as over time, ultimately resulting in encapsulation of the device. This review describes the challenges faced by developers of neural interface systems, particularly devices already in use in humans. The mechanical and technological failure modes of each component of an implant system is described. The acute and chronic reactions to devices in the peripheral and central nervous system and how they affect system performance are depicted. Further, physical challenges such as micro and macro movements are reviewed. The clinical implications of device failures are summarized and a guide for determining the severity of complication was developed and provided. Common methods to diagnose and examine mechanical, technological, and biological failure modes at various stages of development and testing are outlined, with an emphasis on chronic in vivo characterization of implant systems. Finally, this review concludes with an overview of some of the innovative solutions developed to reduce or resolve the challenges faced by implanted neural interface systems.

The state-of-the-art of invasive brain-computer interfaces in humans: a systematic review and individual patient meta-analysis

Objective.Invasive brain-computer interfaces (iBCIs) have evolved significantly since the first neurotrophic electrode was implanted in a human subject three decades ago. Since then, both hardware and software advances have increased the iBCI performance to enable tasks such as decoding conversations in real-time and manipulating external limb prostheses with haptic feedback. In this systematic review, we aim to evaluate the advances in iBCI hardware, software and functionality and describe challenges and opportunities in the iBCI field.Approach.Medline, EMBASE, PubMed and Cochrane databases were searched from inception until 13 April 2024. Primary studies reporting the use of iBCI in human subjects to restore function were included. Endpoints extracted include iBCI electrode type, iBCI implantation, decoder algorithm, iBCI effector, testing and training methodology and functional outcomes. Narrative synthesis of outcomes was done with a focus on hardware and software development trends over time. Individual patient data (IPD) was also collected and an IPD meta-analysis was done to identify factors significant to iBCI performance.Main results.93 studies involving 214 patients were included in this systematic review. The median task performance accuracy for cursor control tasks was 76.00% (Interquartile range [IQR] = 21.2), for motor tasks was 80.00% (IQR = 23.3), and for communication tasks was 93.27% (IQR = 15.3). Current advances in iBCI software include use of recurrent neural network architectures as decoders, while hardware advances such as intravascular stentrodes provide a less invasive alternative for neural recording. Challenges include the lack of standardized testing paradigms for specific functional outcomes and issues with portability and chronicity limiting iBCI usage to laboratory settings.Significance.Our systematic review demonstrated the exponential rate at which iBCIs have evolved over the past two decades. Yet, more work is needed for widespread clinical adoption and translation to long-term home-use.

Master classes of the tenth international brain-computer interface meeting: showcasing the research of BCI trainees

The Tenth International brain-computer interface (BCI) meeting was held June 6-9, 2023, in the Sonian Forest in Brussels, Belgium. At that meeting, 21 master classes, organized by the BCI Society's Postdoc & Student Committee, supported the Society's goal of fostering learning opportunities and meaningful interactions for trainees in BCI-related fields. Master classes provide an informal environment where senior researchers can give constructive feedback to the trainee on their chosen and specific pursuit. The topics of the master classes span the whole gamut of BCI research and techniques. These include data acquisition, neural decoding and analysis, invasive and noninvasive stimulation, and ethical and transitional considerations. Additionally, master classes spotlight innovations in BCI research. Herein, we discuss what was presented within the master classes by highlighting each trainee and expert researcher, providing relevant background information and results from each presentation, and summarizing discussion and references for further study.

Bio-inspired electronics: Soft, biohybrid, and "living" neural interfaces

Neural interface technologies are increasingly evolving towards bio-inspired approaches to enhance integration and long-term functionality. Recent strategies merge soft materials with tissue engineering to realize biologically-active and/or cell-containing living layers at the tissue-device interface that enable seamless biointegration and novel cell-mediated therapeutic opportunities. This review maps the field of bio-inspired electronics and discusses key recent developments in tissue-like and regenerative bioelectronics, from soft biomaterials and surface-functionalized bioactive coatings to cell-containing 'biohybrid' and 'all-living' interfaces. We define and contextualize key terminology in this emerging field and highlight how biological and living components can bridge the gap to clinical translation.

Designing an online BCI forum: insights from researchers and end-users

Objective.Brain-computer interfaces (BCIs) can support non-muscular communication and device control for severely paralyzed people. However, efforts that directly involve potential or actual end-users and address their individual needs are scarce, demonstrating a translational gap. An online BCI forum supported by the BCI Society could initiate and sustainably strengthen interactions between BCI researchers and end-users to bridge this gap.Approach.We interviewed six severely paralyzed individuals and surveyed 121 BCI researchers to capture their opinions and wishes concerning an online BCI forum. Data were analyzed with a mixed-method quantitative and qualitative content analysis.Main results.All end-users and most researchers (83%) reported an interest in participating in an online BCI forum. Rating questions and open comments to identify design aspects included what should be featured most prominently, how people would get engaged in the online BCI forum, and which pitfalls should be considered.Significance.Responses support establishing an online BCI forum to serve as a meaningful resource for the entire BCI community.

Non-Invasive Brain-Computer Interfaces: State of the Art and Trends

Brain-computer interface (BCI) is a rapidly evolving technology that has the potential to widely influence research, clinical and recreational use. Non-invasive BCI approaches are particularly common as they can impact a large number of participants safely and at a relatively low cost. Where traditional non-invasive BCIs were used for simple computer cursor tasks, it is now increasingly common for these systems to control robotic devices for complex tasks that may be useful in daily life. In this review, we provide an overview of the general BCI framework as well as the various methods that can be used to record neural activity, extract signals of interest, and decode brain states. In this context, we summarize the current state-of-the-art of non-invasive BCI research, focusing on trends in both the application of BCIs for controlling external devices and algorithm development to optimize their use. We also discuss various open-source BCI toolboxes and software, and describe their impact on the field at large.

A 10-year journey towards clinical translation of an implantable endovascular BCI a keynote lecture given at the BCI society meeting in Brussels

In the rapidly evolving field of brain-computer interfaces (BCIs), a novel modality for recording electrical brain signals has quietly emerged over the past decade. The technology is endovascular electrocorticography (ECoG), an innovation that stands alongside well-established methods such as electroencephalography, traditional ECoG, and single/multi-unit activity recording. This system was inspired by advancements in interventional cardiology, particularly the integration of electronics into various medical interventions. The breakthrough led to the development of the Stentrode system, which employs stent-mounted electrodes to record electrical brain activity for applications in a motor neuroprosthesis. This perspective explores four key areas in our quest to bring the Stentrode BCI to market: the critical patient need for autonomy driving our efforts, the hurdles and achievements in assessing BCI performance, the compelling advantages of our unique endovascular approach, and the essential steps for clinical translation and product commercialization.

Next generation bioelectronic medicine: making the case for non-invasive closed-loop autonomic neuromodulation

The field of bioelectronic medicine has advanced rapidly from rudimentary electrical therapies to cutting-edge closed-loop systems that integrate real-time physiological monitoring with adaptive neuromodulation. Early innovations, such as cardiac pacemakers and deep brain stimulation, paved the way for these sophisticated technologies. This review traces the historical and technological progression of bioelectronic medicine, culminating in the emerging potential of closed-loop devices for multiple disorders of the brain and body. We emphasize both invasive techniques, such as implantable devices for brain, spinal cord and autonomic regulation, while we introduce new prospects for non-invasive neuromodulation, including focused ultrasound and newly developed autonomic neurography enabling precise detection and titration of inflammatory immune responses. The case for closed-loop non-invasive autonomic neuromodulation (incorporating autonomic neurography and splenic focused ultrasound stimulation) is presented through its applications in conditions such as sepsis and chronic inflammation, illustrating its capacity to revolutionize personalized healthcare. Today, invasive or non-invasive closed-loop systems have yet to be developed that dynamically modulate autonomic nervous system function by responding to real-time physiological and molecular signals; it represents a transformative approach to therapeutic interventions and major opportunity by which the bioelectronic field may advance. Knowledge gaps remain and likely contribute to the lack of available closed loop autonomic neuromodulation systems, namely, (1) significant exogenous and endogenous noise that must be filtered out, (2) potential drift in the signal due to temporal change in disease severity and/or therapy induced neuroplasticity, and (3) confounding effects of exogenous therapies (e.g., concurrent medications that dysregulate autonomic nervous system functions). Leveraging continuous feedback and real-time adjustments may overcome many of these barriers, and these next generation systems have the potential to stand at the forefront of precision medicine, offering new avenues for individualized and adaptive treatment.

Prospectively identifying risks and controls for advanced brain-computer interfaces: A Networked Hazard Analysis and Risk Management System (Net-HARMS) approach

The introduction of advanced digital technologies continues to increase system complexity and introduce risks, which must be proactively identified and managed to support system resilience. Brain-computer interfaces (BCIs) are one such technology; however, the risks arising from broad societal use of the technology have yet to be identified and controlled. This study applied a structured systems thinking-based risk assessment method to prospectively identify risks and risk controls for a hypothetical future BCI system lifecycle. The application of the Networked Hazard Analysis and Risk Management System (Net-HARMS) method identified over 800 risks throughout the BCI system lifecycle, from BCI development and regulation through to BCI use, maintenance, and decommissioning. High-criticality risk themes include the implantation and degradation of unsafe BCIs, unsolicited brain stimulation, incorrect signals being sent to safety-critical technologies, and insufficiently supported BCI users. Over 600 risk controls were identified that could be implemented to support system safety and performance resilience. Overall, many highly-impactful BCI system safety and performance risks may arise throughout the BCI system lifecycle and will require collaborative efforts from a wide range of BCI stakeholders to adequately control. Whilst some of the identified controls are practical, work is required to develop a more systematic set of controls to best support the design of a resilient sociotechnical BCI system.

A Method to Extract Task-Related EEG Feature Based on Lightweight Convolutional Neural Network

Unlocking task-related EEG spectra is crucial for neuroscience. Traditional convolutional neural networks (CNNs) effectively extract these features but face limitations like overfitting due to small datasets. To address this issue, we propose a lightweight CNN and assess its interpretability through the fully connected layer (FCL). Initially tested with two tasks (Task 1: open vs closed eyes, Task 2: interictal vs ictal stage), the CNN demonstrated enhanced spectral features in the alpha band for Task 1 and the theta band for Task 2, aligning with established neurophysiological characteristics. Subsequent experiments on two brain-computer interface tasks revealed a correlation between delta activity (around 1.55 Hz) and hand movement, with consistent results across pericentral electroencephalogram (EEG) channels. Compared to recent research, our method stands out by delivering task-related spectral features through FCL, resulting in significantly fewer trainable parameters while maintaining comparable interpretability. This indicates its potential suitability for a wider array of EEG decoding scenarios.

Superior cortical venous anatomy for endovascular device implantation: a systematic review

Endovascular electrode arrays provide a minimally invasive approach to access intracranial structures for neural recording and stimulation. These arrays are currently used as brain-computer interfaces (BCIs) and are deployed within the superior sagittal sinus (SSS), although cortical vein implantation could improve the quality and quantity of recorded signals. However, the anatomy of the superior cortical veins is heterogenous and poorly characterised. MEDLINE and Embase databases were systematically searched from inception to December 15, 2023 for studies describing the anatomy of the superior cortical veins. A total of 28 studies were included: 19 cross-sectional imaging studies, six cadaveric studies, one intraoperative anatomical study and one review. There was substantial variability in cortical vein diameter, length, confluence angle, and location relative to the underlying cortex. The mean number of SSS branches ranged from 11 to 45. The vein of Trolard was most often reported as the largest superior cortical vein, with a mean diameter ranging from 2.1 mm to 3.3 mm. The mean vein of Trolard was identified posterior to the central sulcus. One study found a significant age-related variability in cortical vein diameter and another identified myoendothelial sphincters at the base of the cortical veins. Cortical vein anatomical data are limited and inconsistent. The vein of Trolard is the largest tributary vein of the SSS; however, its relation to the underlying cortex is variable. Variability in cortical vein anatomy may necessitate individualized pre-procedural planning of training and neural decoding in endovascular BCI. Future focus on the relation to the underlying cortex, sulcal vessels, and vessel wall anatomy is required.

A leadless power transfer and wireless telemetry solutions for an endovascular electrocorticography

Objective. Endovascular brain-computer interfaces (eBCIs) offer a minimally invasive way to connect the brain to external devices, merging neuroscience, engineering, and medical technology. Currently, solutions for endovascular electrocorticography (ECoG) include a stent in the brain with sensing electrodes, a chest implant to accommodate electronic components to provide power and data telemetry, and a long (tens of centimeters) cable travel through vessels with a set of wires in between. Removing this long cable is the key to the clinical viability of eBCIS as it carries risks and limitations, especially for patients with fragile vasculature.Approach. This work introduces a wireless and leadless telemetry and power transfer solution for ECoG. The proposed solution includes an optical telemetry module and a focused ultrasound (FUS) power transfer system. The proposed system can be miniaturised to fit in an endovascular stent, removing the need for long, intrusive cables.Main results. The optical telemetry achieves data transmission speeds of over 2 Mbit/s, capable of supporting 41 ECoG channels at a 2 kHz sampling rate with 24-bit resolution. The FUS power transfer system delivers up to 10 mW of power to the implant through the scalp(6 mm), skull(10 mm), and subdural space(5 mm), adhering to safety limits. Testing on bovine tissue (10 mm thick bone, 7 mm thick skin) confirmed the system's efficacy.Significance. This leadless and wireless solution eliminates the need for long cables and auxiliary implants, potentially reducing complications and enhancing the clinical applicability of eBCIs. The proposed system represents a step forward in enabling safer and more effective ECoG for a broader range of patients.

Implanted cortical neuroprosthetics for speech and movement restoration

Implanted cortical neuroprosthetics (ICNs) are medical devices developed to replace dysfunctional neural pathways by creating information exchange between the brain and a digital system which can facilitate interaction with the external world. Over the last decade, researchers have explored the application of ICNs for diverse conditions including blindness, aphasia, and paralysis. Both transcranial and endovascular approaches have been used to record neural activity in humans, and in a laboratory setting, high-performance decoding of the signals associated with speech intention has been demonstrated. Particular progress towards a device which can move into clinical practice has been made with ICNs focussed on the restoration of speech and movement. This article provides an overview of contemporary ICNs for speech and movement restoration, their mechanisms of action and the unique ethical challenges raised by the field.

Caregivers in implantable brain-computer interface research: a scoping review

Introduction

While the ethical significance of caregivers in neurological research has increasingly been recognized, the role of caregivers in brain-computer interface (BCI) research has received relatively less attention.

Objectives

This report investigates the extent to which caregivers are mentioned in publications describing implantable BCI (iBCI) research for individuals with motor dysfunction, communication impairment, and blindness.

Methods

The scoping review was conducted in June 2024 using the PubMed and Web of Science bibliographic databases. The articles were systematically searched using query terms for caregivers, family members, and guardians, and the results were quantitatively and qualitatively analyzed.

Results

Our search yielded 315 unique studies, 78 of which were included in this scoping review. Thirty-four (43.6%) of the 78 articles mentioned the study participant's caregivers. We sorted these into 5 categories: Twenty-two (64.7%) of the 34 articles thanked caregivers in the acknowledgement section, 6 (17.6%) articles described the caregiver's role with regard to the consent process, 12 (35.3%) described the caregiver's role in the technical maintenance and upkeep of the BCI system or in other procedural aspects of the study, 9 (26.5%) discussed how the BCI enhanced participant communication and goal-directed behavior with the help of a caregiver, and 3 (8.8%) articles included general comments that did not fit into the other categories but still related to the importance of caregivers in the lives of the research participants.

Discussion

Caregivers were mentioned in less than half of BCI studies in this review. The studies that offered more robust discussions of caregivers provide valuable insight into the integral role that caregivers play in supporting the study participants and the research process. Attention to the role of caregivers in successful BCI research studies can help guide the responsible development of future BCI study protocols.

Gustatory interface for operative assessment and taste decoding in patients with tongue cancer

Taste, a pivotal sense modality, plays a fundamental role in discerning flavors and evaluating the potential harm of food, thereby contributing to human survival, physical and mental health. Patients with tongue cancer may experience a loss of taste following extensive surgical resection with flap reconstruction. Here, we designed a gustatory interface that enables the non-invasive detection of tongue electrical activities for a comprehensive operative assessment. Moreover, it decodes gustatory information from the reconstructed tongue without taste buds. Our gustatory interface facilitates the recording and analysis of electrical activities on the tongue, yielding an electrical mapping across the entire tongue surface, which delineates the safe margin for surgical management and assesses flap viability for postoperative structure monitoring and prompt intervention. Furthermore, the gustatory interface helps patients discern tastes with an accuracy of 97.8%. Our invention offers a promising approach to clinical assessment and management and holds potential for improving the quality of life for individuals with tongue cancer.

10. Three Embodied Dimensions of Communication

In the last chapter, Janna van Grunsven, Caroline Bollen and Bouke van Balen show how the phenomenology of communication can inform the field of augmented or alternative communication technology (AAC-tech). AAC-tech is a set of technologies developed for people who are unable to use some of their bodily expressive resources due to congenital or acquired disability. This inability often makes it very difficult for those people to communicate. Developers of AAC-tech often take a cognitivist starting-point, thereby missing out on the subtle ways in which embodiment shapes communication. The phenomenological description of the lived experiences of these people offers a fruitful starting-point for recognizing the often forgotten embodied dimension of communication, and enables to formulate desiderata for how AAC-tech should be developed: AAC-tech should take into account (1) embodied address, (2) embodied enrichment, and (3) embodied diversity. Focusing on the lived experience of potential users of AAC-tech has, according to van Grunsven, Bollen, and van Balen, not only direct practical applications for technology development but also can inform phenomenology methodologically: focusing on a limit case as the one discussed in this chapter makes visible that communication takes place in a wide variety of ways and that it is not the task of the phenomenologist to lay bare a general or essential structure of communication that can be taken as a standard.

DO NOT LOSE SLEEP OVER IT: IMPLANTED BRAIN-COMPUTER INTERFACE FUNCTIONALITY DURING NIGHTTIME IN LATE-STAGE AMYOTROPHIC LATERAL SCLEROSIS

Background and objectives

Brain-computer interfaces (BCIs) hold promise as augmentative and alternative communication technology for people with severe motor and speech impairment (locked-in syndrome) due to neural disease or injury. Although such BCIs should be available 24/7, to enable communication at all times, feasibility of nocturnal BCI use has not been investigated. Here, we addressed this question using data from an individual with amyotrophic lateral sclerosis (ALS) who was implanted with an electrocorticography-based BCI that enabled the generation of click-commands for spelling words and call-caregiver signals.

Methods

We investigated nocturnal dynamics of neural signal features used for BCI control, namely low (LFB: 10-30Hz) and high frequency band power (HFB: 65-95Hz). Additionally, we assessed the nocturnal performance of a BCI decoder that was trained on daytime data by quantifying the number of unintentional BCI activations at night. Finally, we developed and implemented a nightmode decoder that allowed the participant to call a caregiver at night, and assessed its performance.

Results

Power and variance in HFB and LFB were significantly higher at night than during the day in the majority of the nights, with HFB variance being higher in 88% of nights. Daytime decoders caused 245 unintended selection-clicks and 13 unintended caregiver-calls per hour when applied to night data. The developed nightmode decoder functioned error-free in 79% of nights over a period of ±1.5 years, allowing the user to reliably call the caregiver, with unintended activations occurring only once every 12 nights.

Discussion

Reliable nighttime use of a BCI requires decoders that are adjusted to sleep-related signal changes. This demonstration of a reliable BCI nightmode and its long-term use by an individual with advanced ALS underscores the importance of 24/7 BCI reliability.

Trial registration

This trial is registered in clinicaltrials.gov under number NCT02224469 (https://clinicaltrials.gov/study/NCT02224469?term=NCT02224469&rank=1). Date of submission to registry: August 21, 2014. Enrollment of first participant: September 7, 2015.

The pioneering past and cutting-edge future of interventional neuroradiology

This review provides a thorough understanding of the developments in the field of interventional neuroradiology (INR). A concise overview of the pioneering past and current state of this field is presented first, followed by a greater emphasis on its future. Five main aspects predicted to undergo significant developments are identified and discussed. These include changes in 'education and training', 'clinical practice and logistics', 'devices and equipment', 'techniques and procedures', and 'relevant diagnostic imaging'. INR is at the crossroads of neuroradiology, neurosurgery, neurology, and the neurosciences. To progress we must value the uniqueness and vitality of this multidisciplinary aspect. While minimal access techniques offer very good anatomical accessibility to treat multiple pathologies of the central nervous system, it is also important to recognise its limitations. Medical, surgical, and radiosurgery modalities retain an important role in the management of some complex neuropathology. This review is certainly not exhaustive of all ongoing and predicted developments, but it is an important update for INR specialists and other interested professionals.

Longevity of a Brain-Computer Interface for Amyotrophic Lateral Sclerosis

The durability of communication with the use of brain-computer interfaces in persons with progressive neurodegenerative disease has not been extensively examined. We report on 7 years of independent at-home use of an implanted brain-computer interface for communication by a person with advanced amyotrophic lateral sclerosis (ALS), the inception of which was reported in 2016. The frequency of at-home use increased over time to compensate for gradual loss of control of an eye-gaze-tracking device, followed by a progressive decrease in use starting 6 years after implantation. At-home use ended when control of the brain-computer interface became unreliable. No signs of technical malfunction were found. Instead, the amplitude of neural signals declined, and computed tomographic imaging revealed progressive atrophy, which suggested that ALS-related neurodegeneration ultimately rendered the brain-computer interface ineffective after years of successful use, although alternative explanations are plausible. (Funded by the National Institute on Deafness and Other Communication Disorders and others; ClinicalTrials.gov number, NCT02224469.).

The speech neuroprosthesis

Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by directly decoding speech from intact cortical activity has the potential to restore natural communication and self-expression. Recent discoveries have defined how key features of speech production are facilitated by the coordinated activity of vocal-tract articulatory and motor-planning cortical representations. In this Review, we highlight such progress and how it has led to successful speech decoding, first in individuals implanted with intracranial electrodes for clinical epilepsy monitoring and subsequently in individuals with paralysis as part of early feasibility clinical trials to restore speech. We discuss high-spatiotemporal-resolution neural interfaces and the adaptation of state-of-the-art speech computational algorithms that have driven rapid and substantial progress in decoding neural activity into text, audible speech, and facial movements. Although restoring natural speech is a long-term goal, speech neuroprostheses already have performance levels that surpass communication rates offered by current assistive-communication technology. Given this accelerated rate of progress in the field, we propose key evaluation metrics for speed and accuracy, among others, to help standardize across studies. We finish by highlighting several directions to more fully explore the multidimensional feature space of speech and language, which will continue to accelerate progress towards a clinically viable speech neuroprosthesis.

Detecting and Eliminating Cardiac Artifact from Endovascular EEG Signals

Paralysis is a debilitating condition that affects more than 5.4 million people in the U.S. In severe cases, the paralyzed patient is incapable of communication. Restoring this communication is a primary goal of caretakers and is critical to improving the patient's quality of life. Brain-computer interfaces (BCIs) that directly access signals from the motor cortex are a promising method of circumventing the condition causing paralysis, typically using machine learning (ML) to predict motor intent from brain signals. However, BCIs are highly invasive and subjects have primarily been limited to patients with mild to moderate paralysis. The Stentrode is a novel technology that records electroencephalographic (EEG) signals via an electrode array placed endovascularly in the superior sagittal sinus. The first clinical trials of this technology aim to enable digital communication for severely paralyzed patients, translating brain signals from attempted movements into computer control inputs like mouse clicks. However, recordings of EEG are often contaminated with artifacts, including biopotentials arising from other excitable tissues, such as the heart and skeletal muscle. This study characterizes the electrocardiographic (ECG) artifact detected in the Stentrode recordings and proposes an automated Independent Component Analysis (ICA) method for removing this artifact. We compare the effectiveness of this method to previous methods for removal. Quantifying and eliminating the cardiac artifact is critical to accurately decode signals from the motor cortex and restore patients' ability to communicate.

Venous Sinus Stent to Treat Paralysis

Transvenous treatment of paralysis is a concept less than a decade old. The Stentrode (Synchron, Inc, New York, USA) is a novel electrode on stent device intended to be implanted in the superior sagittal sinus adjacent to the motor cortex. Initial animal studies in sheep demonstrated the safety of the implant as well as its accuracy in detecting neural signals at both short and long term. Early human trials have shown the safety of the device and demonstrated the use of the Stentrode system in facilitating patients with paralysis to carry out daily activities such as texting, email, and personal finance. This is an emerging technology with promise, although certainly more research is required to better understand the capabilities and limitations of the device.

The ethical significance of user-control in AI-driven speech-BCIs: a narrative review

AI-driven brain-computed interfaces aimed at restoring speech for individuals living with locked-in-syndrome are paired with ethical implications for user's autonomy, privacy and responsibility. Embedding options for sufficient levels of user-control in speech-BCI design has been proposed to mitigate these ethical challenges. However, how user-control in speech-BCIs is conceptualized and how it relates to these ethical challenges is underdetermined. In this narrative literature review, we aim to clarify and explicate the notion of user-control in speech-BCIs, to better understand in what way user-control could operationalize user's autonomy, privacy and responsibility and explore how such suggestions for increasing user-control can be translated to recommendations for the design or use of speech-BCIs. First, we identified types of user control, including executory control that can protect voluntariness of speech, and guidance control that can contribute to semantic accuracy. Second, we identified potential causes for a loss of user-control, including contributions of predictive language models, a lack of ability for neural control, or signal interference and external control. Such a loss of user control may have implications for semantic accuracy and mental privacy. Third we explored ways to design for user-control. While embedding initiation signals for users may increase executory control, they may conflict with other aims such as speed and continuity of speech. Design mechanisms for guidance control remain largely conceptual, similar trade-offs in design may be expected. We argue that preceding these trade-offs, the overarching aim of speech-BCIs needs to be defined, requiring input from current and potential users. Additionally, conceptual clarification of user-control and other (ethical) concepts in this debate has practical relevance for BCI researchers. For instance, different concepts of inner speech may have distinct ethical implications. Increased clarity of such concepts can improve anticipation of ethical implications of speech-BCIs and may help to steer design decisions.

Feasibility of endovascular stimulation of the femoral nerve using a stent-mounted electrode array

Objective.Electrical stimulation of peripheral nerves has long been a treatment option to restore impaired neural functions that cannot be restored by conventional pharmacological therapies. Endovascular neurostimulation with stent-mounted electrode arrays is a promising and less invasive alternative to traditional implanted electrodes, which typically require invasive implantation surgery. In this study, we investigated the feasibility of endovascular stimulation of the femoral nerve using a stent-mounted electrode array and compared its performance to that of a commercially available pacing catheter.Approach.In acute animal experiments, a pacing catheter was implanted unilaterally in the femoral artery to stimulate the femoral nerve in a bipolar configuration. Electromyogram of the quadriceps and electroneurogram of a distal branch of the femoral nerve were recorded. After retrieval of the pacing catheter, a bipolar stent-mounted electrode array was implanted in the same artery and the recording sessions were repeated.Main Results.Stimulation of the femoral nerve was feasible with the stent-electrode array. Although the threshold stimulus intensities required with the stent-mounted electrode array (at 100-500µs increasing pulse width, 2.17 ± 0.87 mA-1.00 ± 0.11 mA) were more than two times higher than the pacing catheter electrodes (1.05 ± 0.48 mA-0.57 ± 0.28 mA), we demonstrated that, by reducing the stimulus pulse width to 100µs, the threshold charge per phase and charge density can be reduced to 0.22 ± 0.09µC and 24.62 ± 9.81µC cm-2, which were below the tissue-damaging limit, as defined by the Shannon criteria.Significance.The present study is the first to reportin vivofeasibility and efficiency of peripheral nerve stimulation using an endovascular stent-mounted electrode array.

The Promise of Endovascular Neurotechnology: A Brain-Computer Interface to Restore Autonomy to People With Motor Impairment

ABSTRACT

This Joel A. DeLisa Lecture on endovascular brain-computer interfaces was presented by Dr Thomas Oxley on February 23, 2023, at the Association of Academic Physiatrists Annual Scientific Meeting. The lecture described how brain-computer interfaces replace lost physiological function to enable direct communication between the brain and external digital devices, such as computers, smartphones, and robotic limbs. Specifically, the potential of a novel endovascular brain-computer interface technology was discussed. The brain-computer interface uses a stent-electrode array delivered via the jugular vein and is permanently implanted in a vein adjacent to the motor cortex. In a first-in-human clinical trial, participants with upper limb paralysis who received the endovascular brain-computer interface could use the system independently and at home to operate laptop computers for various instrumental activities of daily living. A Food and Drug Administration-approved trial of the endovascular brain-computer interface in the United States is in progress. Future development of the system will provide recipients with continuous autonomy through digital access with minimal caregiver assistance. Physiatrists and occupational therapists will have a vital role in helping people with paralysis achieve the potential of implantable brain-computer interfaces.

Invasive Brain Computer Interface for Motor Restoration in Spinal Cord Injury: A Systematic Review

STUDY DESIGN

Systematic review of the literature.

OBJECTIVES

In recent years, brain-computer interface (BCI) has emerged as a potential treatment for patients with spinal cord injury (SCI). This is the first systematic review of the literature on invasive closed-loop BCI technologies for the treatment of SCI in humans.

MATERIALS AND METHODS

A comprehensive search of PubMed MEDLINE, Web of Science, and Ovid EMBASE was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

RESULTS

Of 8316 articles collected, 19 studies met all the inclusion criteria. Data from 21 patients were extracted from these studies. All patients sustained a cervical SCI and were treated using either a BCI with intracortical microelectrode arrays (n = 18, 85.7%) or electrocorticography (n = 3, 14.3%). To decode these neural signals, machine learning and statistical models were used: support vector machine in eight patients (38.1%), linear estimator in seven patients (33.3%), Hidden Markov Model in three patients (14.3%), and other in three patients (14.3%). As the outputs, ten patients (47.6%) underwent noninvasive functional electrical stimulation (FES) with a cuff; one (4.8%) had an invasive FES with percutaneous stimulation, and ten (47.6%) used an external device (neuroprosthesis or virtual avatar). Motor function was restored in all patients for each assigned task. Clinical outcome measures were heterogeneous across all studies.

CONCLUSIONS

Invasive techniques of BCI show promise for the treatment of SCI, but there is currently no technology that can restore complete functional autonomy in patients with SCI. The current techniques and outcomes of BCI vary greatly. Because invasive BCIs are still in the early stages of development, further clinical studies should be conducted to optimize the prognosis for patients with SCI.

Detection of Blood Clots Using a Whole Stent as an Active Implantable Biosensor

Many cardiovascular problems stem from blockages that form within the vasculature and often treatment includes fitting a stent through percutaneous coronary intervention. This offers a minimally invasive therapy but re-occlusion through restenosis or thrombosis formation often occurs post-deployment. Research is ongoing into the creation of smart stents that can detect the occurrence of further problems. In this study, it is shown that selectively metalizing a non-conductive stent can create a set of electrodes that are capable of detecting a build-up of material around the stent. The associated increase in electrical impedance across the electrodes is measured, testing the stent with blood clot to mimic thrombosis. It is shown that the device is capable of sensing different amounts of occlusion. The stent can reproducibly sense the presence of clot showing a 16% +/-3% increase in impedance which is sufficient to reliably detect the clot when surrounded by explanted aorta (one sample t-test, p = 0.009, n = 9). It is demonstrated that this approach can be extended beyond the 3D printed prototypes by showing that it can be applied to a commercially available stent and it is believed that it can be further utilized by other types of medical implants.

Text and image generation from intracranial electroencephalography using an embedding space for text and images

Objective.Invasive brain-computer interfaces (BCIs) are promising communication devices for severely paralyzed patients. Recent advances in intracranial electroencephalography (iEEG) coupled with natural language processing have enhanced communication speed and accuracy. It should be noted that such a speech BCI uses signals from the motor cortex. However, BCIs based on motor cortical activities may experience signal deterioration in users with motor cortical degenerative diseases such as amyotrophic lateral sclerosis. An alternative approach to using iEEG of the motor cortex is necessary to support patients with such conditions.Approach. In this study, a multimodal embedding of text and images was used to decode visual semantic information from iEEG signals of the visual cortex to generate text and images. We used contrastive language-image pretraining (CLIP) embedding to represent images presented to 17 patients implanted with electrodes in the occipital and temporal cortices. A CLIP image vector was inferred from the high-γpower of the iEEG signals recorded while viewing the images.Main results.Text was generated by CLIPCAP from the inferred CLIP vector with better-than-chance accuracy. Then, an image was created from the generated text using StableDiffusion with significant accuracy.Significance.The text and images generated from iEEG through the CLIP embedding vector can be used for improved communication.

Online speech synthesis using a chronically implanted brain-computer interface in an individual with ALS

Brain-computer interfaces (BCIs) that reconstruct and synthesize speech using brain activity recorded with intracranial electrodes may pave the way toward novel communication interfaces for people who have lost their ability to speak, or who are at high risk of losing this ability, due to neurological disorders. Here, we report online synthesis of intelligible words using a chronically implanted brain-computer interface (BCI) in a man with impaired articulation due to ALS, participating in a clinical trial (ClinicalTrials.gov, NCT03567213) exploring different strategies for BCI communication. The 3-stage approach reported here relies on recurrent neural networks to identify, decode and synthesize speech from electrocorticographic (ECoG) signals acquired across motor, premotor and somatosensory cortices. We demonstrate a reliable BCI that synthesizes commands freely chosen and spoken by the participant from a vocabulary of 6 keywords previously used for decoding commands to control a communication board. Evaluation of the intelligibility of the synthesized speech indicates that 80% of the words can be correctly recognized by human listeners. Our results show that a speech-impaired individual with ALS can use a chronically implanted BCI to reliably produce synthesized words while preserving the participant's voice profile, and provide further evidence for the stability of ECoG for speech-based BCIs.

Improving auditory attention decoding by classifying intracranial responses to glimpsed and masked acoustic events

Listeners with hearing loss have trouble following a conversation in multitalker environments. While modern hearing aids can generally amplify speech, these devices are unable to tune into a target speaker without first knowing to which speaker a user aims to attend. Brain-controlled hearing aids have been proposed using auditory attention decoding (AAD) methods, but current methods use the same model to compare the speech stimulus and neural response, regardless of the dynamic overlap between talkers which is known to influence neural encoding. Here, we propose a novel framework that directly classifies event-related potentials (ERPs) evoked by glimpsed and masked acoustic events to determine whether the source of the event was attended. We present a system that identifies auditory events using the local maxima in the envelope rate of change, assesses the temporal masking of auditory events relative to competing speakers, and utilizes masking-specific ERP classifiers to determine if the source of the event was attended. Using intracranial electrophysiological recordings, we showed that high gamma ERPs from recording sites in auditory cortex can effectively decode the attention of subjects. This method of AAD provides higher accuracy, shorter switch times, and more stable decoding results compared with traditional correlational methods, permitting the quick and accurate detection of changes in a listener's attentional focus. This framework also holds unique potential for detecting instances of divided attention and inattention. Overall, we extend the scope of AAD algorithms by introducing the first linear, direct-classification method for determining a listener's attentional focus that leverages the latest research in multitalker speech perception. This work represents another step toward informing the development of effective and intuitive brain-controlled hearing assistive devices.

The digital motor output: a conceptual framework for a meaningful clinical performance metric for a motor neuroprosthesis

In recent years, the majority of the population has become increasingly reliant on continuous and independent control of smart devices to conduct activities of daily living. Upper extremity movement is typically required to generate the motor outputs that control these interfaces, such as rapidly and accurately navigating and clicking a mouse, or activating a touch screen. For people living with tetraplegia, these abilities are lost, significantly compromising their ability to interact with their environment. Implantable brain computer interfaces (BCIs) hold promise for restoring lost neurologic function, including motor neuroprostheses (MNPs). An implantable MNP can directly infer motor intent by detecting brain signals and transmitting the motor signal out of the brain to generate a motor output and subsequently control computer actions. This physiological function is typically performed by the motor neurons in the human body. To evaluate the use of these implanted technologies, there is a need for an objective measurement of the effectiveness of MNPs in restoring motor outputs. Here, we propose the concept of digital motor outputs (DMOs) to address this: a motor output decoded directly from a neural recording during an attempted limb or orofacial movement is transformed into a command that controls an electronic device. Digital motor outputs are diverse and can be categorized as discrete or continuous representations of motor control, and the clinical utility of the control of a single, discrete DMO has been reported in multiple studies. This sets the stage for the DMO to emerge as a quantitative measure of MNP performance.

Post-trial access to implantable neural devices: an exploratory international survey

Objectives

Clinical trials of innovative neural implants are rapidly increasing and diversifying, but little is known about participants' post-trial access to the device and ongoing clinical care. This exploratory study examines common practices in the planning and coordination of post-trial access to neurosurgical devices. We also explore the perspectives of trial investigators on the barriers to post-trial access and ongoing care, as well as ethical questions related to the responsibilities of key stakeholder groups.

Design setting and participants

Trial investigators (n=66) completed a survey on post-trial access in the most recent investigational trial of a surgically implanted neural device they had conducted. Survey respondents predominantly specialized in neurosurgery, neurology and psychiatry, with a mean of 14.8 years of experience working with implantable neural devices.

Main outcome measures

Outcomes of interest included rates of device explantation during or at the conclusion of the trial (pre-follow-up) and whether plans for post-trial access were described in the study protocol. Outcomes also included investigators' greatest 'barrier' and 'facilitator' to providing research participants with post-trial access to functional implants and perspectives on current arrangements for the sharing of post-trial responsibilities among key stakeholders.

Results

Trial investigators reported either 'all' (64%) or 'most' (33%) trial participants had remained implanted after the end of the trial, with 'infection' and 'non-response' the most common reasons for explantation. When asked to describe the main barriers to facilitating post-trial access, investigators described limited funding, scarcity of expertise and specialist clinical infrastructure and difficulties maintaining stakeholder relationships. Notwithstanding these barriers, investigators overwhelmingly (95%) agreed there is an ethical obligation to provide post-trial access when participants individually benefit during the trial.

Conclusions

On occasions when devices were explanted during or at the end of the trial, this was done out of concern for the safety and well-being of participants. Further research into common practices in the post-trial phase is needed and essential to ethical and pragmatic discussions regarding stakeholder responsibilities.

Future Directions and Innovations in Venous Sinus Stenting

This review explores the future role of venous sinus stenting (VSS) in the management of idiopathic intracranial hypertension and pulsatile tinnitus. Despite its favorable safety profile and clinical outcomes compared with traditional treatments, VSS is not yet the standard of care for these conditions, lacking high-level evidence data and guidelines for patient selection and indications. Current and recently completed clinical trials are expected to provide data to support the adoption of VSS as a primary treatment option. Additionally, VSS shows potential in treating other conditions, such as dural arteriovenous fistula and cerebral venous sinus thrombosis, and it is likely that the procedure will continue to see an expansion of its approved indications. The current lack of dedicated venous stenting technology is being addressed with promising advancements, which may improve procedural ease and patient outcomes. VSS also offers potential for expansion into modulation of brain electrophysiology via endovascular routes, offering exciting possibilities for neurodiagnostics and treatment of neurodegenerative disorders.

The evolution of neuromodulation for chronic stroke: From neuroplasticity mechanisms to brain-computer interfaces

Stroke is one of the most common and debilitating neurological conditions worldwide. Those who survive experience motor, sensory, speech, vision, and/or cognitive deficits that severely limit remaining quality of life. While rehabilitation programs can help improve patients' symptoms, recovery is often limited, and patients frequently continue to experience impairments in functional status. In this review, invasive neuromodulation techniques to augment the effects of conventional rehabilitation methods are described, including vagus nerve stimulation (VNS), deep brain stimulation (DBS) and brain-computer interfaces (BCIs). In addition, the evidence base for each of these techniques, pivotal trials, and future directions are explored. Finally, emerging technologies such as functional near-infrared spectroscopy (fNIRS) and the shift to artificial intelligence-enabled implants and wearables are examined. While the field of implantable devices for chronic stroke recovery is still in a nascent stage, the data reviewed are suggestive of immense potential for reducing the impact and impairment from this globally prevalent disorder.

Haemodynamics of stent-mounted neural interfaces in tapered and deformed blood vessels

The endovascular neural interface provides an appealing minimally invasive alternative to invasive brain electrodes for recording and stimulation. However, stents placed in blood vessels have long been known to affect blood flow (haemodynamics) and lead to neointimal growth within the blood vessel. Both the stent elements (struts and electrodes) and blood vessel wall geometries can affect the mechanical environment on the blood vessel wall, which could lead to unfavourable vascular remodelling after stent placement. With increasing applications of stents and stent-like neural interfaces in venous blood vessels in the brain, it is necessary to understand how stents affect blood flow and tissue growth in veins. We explored the haemodynamics of a stent-mounted neural interface in a blood vessel model. Results indicated that blood vessel deformation and tapering caused a substantial change to the lumen geometry and the haemodynamics. The neointimal proliferation was evaluated in sheep implanted with an endovascular neural interface. Analysis showed a negative correlation with the mean Wall Shear Stress pattern. The results presented here indicate that the optimal stent oversizing ratio must be considered to minimise the haemodynamic impact of stenting.