Objective: The 10th International brain computer interface (BCI) Society Meeting, 'Balancing Innovation and Translation', was held from the 6th to 9th of June 2023 in Brussels, Belgium. This report provides a summary of the workshop 'Building Consensus on Clinical Outcome Assessments (COAs) for BCI Devices'. This workshop was intended to give participants an overview of the current state of BCI, future opportunities, and how different countries and regions provide regulatory oversight to support the BCI community to develop safe and effective devices for patients.Approach: Five presentations and a panel discussion including representatives from regulators, industry, and clinical research stakeholders focused on how various stakeholders and the BCI community might best work together to ensure studies provide data that is useful for evaluating safety and effectiveness, including reaching consensus on COAs that represent clinically meaningful benefits and support regulatory and payor requirements. This report focuses on the regulatory and reimbursement requirements for medical devices and how to best measure safety and effectiveness and summarizes the presentations from five experts and the discussion between the panel and the audience.Main results: Consensus was reached on the following items specifically related to BCI: (i) the importance of and need for a new generation of COAs, (ii) the challenges facing the development of appropriate clinical outcome assessments, and (iii) that improvements in COAs should demonstrate obvious and clinically meaningful benefit(s). There was discussion on: (i) clinical trial design for BCIs and (ii) considerations for payor reimbursement and other funding.Significance: Whilst the importance of building community consensus on COAs was apparent, further collaboration will be required to reach consensus on which specific current and/or novel COAs could be used for the BCI field to evolve from research to market.

BACKGROUND:Intracortical microstimulation (ICMS) of the somatosensory cortex activates neurons around the stimulating electrodes and can elicit tactile sensations. OBJECTIVE:It is not clear how the direct activation of cortical neurons influences their ability to process additional tactile inputs originating from the skin. METHODS:In a human implanted with chronic microelectrode arrays in both left and right somatosensory cortices, we presented mechanical vibration to the skin while simultaneously delivering ICMS and quantified the effects of combined mechanical and electrical stimulation on tactile perception. RESULTS:We found that subthreshold ICMS enhanced sensitivity to touch on the skin, as evidenced by a reduction in vibrotactile detection thresholds (median: 1.5 dB), but subthreshold vibration did not systematically impact the detectability of ICMS. Suprathreshold vibration led to an increase in ICMS thresholds (median: 2.4 dB) but suprathreshold ICMS had little impact on vibrotactile thresholds. The ICMS-induced enhancement of vibrotactile sensitivity was location dependent with the effect size decreasing as the projected field of the stimulating electrode and the locus of vibratory stimulation became farther apart. CONCLUSION:These results demonstrate that targeted microstimulation of cortex alone can focally enhance tactile sensitivity, potentially enabling restoration or strengthening of retained tactile sensations after injury.

Invasive brain-machine interfaces can help restore function through the control of external devices while the addition of intracortical microstimulation (ICMS) can elicit sensations of touch and help provide further benefits for individuals living with sensorimotor deficits. However, the extent of tactile information that can be conveyed through ICMS has not been fully explored. In a human participant with spinal cord injury and chronically implanted microelectrode arrays, we used ICMS to the somatosensory cortex to provide grip force feedback in the hands during grasping of objects with varying stiffness with a robotic arm. Using only ICMS-evoked touch sensations, the participant was able to identify between two and three objects with an accuracy of 92% and 67%, respectively. In a compliant grasping task with the goal of grasping a delicate object without crushing it, objects were deformed on average only 2.8 mm with ICMS-based touch feedback compared to 8.7 mm without. These results demonstrate that ICMS-evoked touch sensations to the hands can be used to provide force-based feedback for perceiving object properties and enable more precise grasping during closed-loop control of a robotic limb through a cortical interface.

Complete sensorimotor integration and user acceptance of a neural prosthesis relies on system embodiment the incorporation of an external system into one's own body schema and representation. Embodiment of neural prostheses is an ambiguous concept with limited approaches for quantifying human and machine integration in a meaningful way. In an attempt to understand human sensory integration with external systems, we measured neural activity in the somatosensory cortex of a participant with chronically implanted microelectrode arrays during sensory events tied to either a virtual robotic hand touching an object or a virtual lamp lighting up. Sensory stimulation was delivered using either skin vibration or intracortical microstimulation (ICMS) and was mapped to the virtual systems. Through the brain-machine interface, we observed quantifiable cortical activity corresponding to tactile sensations perceived during the virtual tasks and even during instances when neural stimulation was expected but not delivered, demonstrating the presence of sensory-related neural activity even in the absence of tactile stimulation. Evoked sensory expectation signals were also observed in the motor cortex, although at reduced amplitudes. Evoked cortical activity corresponding to expectation of a sensory input could serve as objective cortical markers for better understanding sensorimotor integration and perceptual experiences when connecting humans with external systems.

Objective Intuitively providing touch feedback from artificial hands to users with sensory loss remains a challenge. Although localized fingertip sensations can be evoked via intracortical microstimulation (ICMS), feedback is generally optimized using psychometric tasks rather than mimicking the cortical response to touch. Approach We created an anatomically-informed and participant-specific model of the human somatosensory cortex (S1) region with an implanted microelectrode array (MEA). We performed simultaneous stimulation-and-recording from the study participant S1 region to characterize cortical responses elicited by single ICMS pulses. Pulses were delivered to a set of pre-selected electrodes mapped to tactile receptive fields. We next performed a 2D (i.e., in the plane of the MEA probe tips) current source density (CSD) analysis of recorded cortical responses to inform cortical network model parameters on how ICMS activates neurons and lateral synaptic connections in the area of the S1 sampled by MEA electrodes. Using information from planar CSD profiles obtained from ground truth data, we reconstructed lateral connections in the S1 model needed to produce the desired responses to single ICMS pulses. The effect of multiple ICMS was then simulated in the biologically realistic cortical model and the results were validated against ground truth cortical responses from the study participant. Main results A high-resolution cortical network model, calibrated to produce the known cortical responses to single ICMS pulses delivered to individual electrodes, predicted with a reasonable accuracy the cortical response to ICMS pulses delivered simultaneously to multiple electrodes. Significance These preliminary results suggest that high-resolution biologically realistic cortical network models can potentially be reliable predictors of cortical response to a given pattern of ICMS presentations and therefore useful in designing biomimetic stimulation patterns.

Background: Intracortical microstimulation (ICMS) of somatosensory cortex can partially restore the sense of touch. Though ICMS bypasses much of the neuraxis, prior studies have found that conscious detection of touch elicited by ICMS lags behind the detection of cutaneous vibration. These findings may have been influenced by mismatched stimulus intensities, which can impact temporal perception. Objective: Evaluate the relative latency at which intensity-matched vibration and ICMS are perceived by a human participant. Methods: One person implanted with microelectrode arrays in somatosensory cortex performed reaction time and temporal order judgment (TOJ) tasks. To measure reaction time, the participant reported when he perceived vibration or ICMS. In the TOJ task, vibration and ICMS were sequentially presented and the participant reported which stimulus occurred first. To verify that the participant could distinguish between stimuli, he also performed a modality discrimination task, in which he indicated if he felt vibration, ICMS, or both. Results: When vibration was matched in perceived intensity to high-amplitude ICMS, vibration was perceived, on average, 48 ms faster than ICMS. However, in the TOJ task, both sensations arose at comparable latencies, with points of subjective simultaneity not significantly different from zero. The participant could discriminate between tactile modalities above chance level but was more inclined to report feeling vibration than ICMS. Conclusions: The latencies of ICMS-evoked percepts are slower than their mechanical counterparts. However, differences in latencies are small, particularly when stimuli are matched for intensity, implying that ICMS-based somatosensory feedback is rapid enough to be effective in neuroprosthetic applications. (C) 2022 The Authors. Published by Elsevier Inc.

BACKGROUND AND OBJECTIVES:The restoration of touch to fingers and fingertips is critical to achieving dexterous neuroprosthetic control for individuals with sensorimotor dysfunction. However, localized fingertip sensations have not been evoked via intracortical microstimulation (ICMS).METHODS:Using a novel intraoperative mapping approach, we implanted electrode arrays in the finger areas of left and right somatosensory cortex and delivered ICMS over a 2-year period in a human participant with spinal cord injury.RESULTS:Stimulation evoked tactile sensations in 8 fingers, including fingertips, spanning both hands. Evoked percepts followed expected somatotopic arrangements. The subject was able to reliably identify up to 7 finger-specific sites spanning both hands in a finger discrimination task. The size of the evoked percepts was on average 33% larger than a finger pad, as assessed via manual markings of a hand image. The size of the evoked percepts increased modestly with increased stimulation intensity, growing 21% as pulse amplitude increased from 20 to 80 µA. Detection thresholds were estimated on a subset of electrodes, with estimates of 9.2 to 35 µA observed, roughly consistent with prior studies.DISCUSSION:These results suggest that ICMS can enable the delivery of consistent and localized fingertip sensations during object manipulation by neuroprostheses for individuals with somatosensory deficits.CLINICALTRIALSGOV IDENTIFIER:NCT03161067.

Advances in intelligent robotic systems and brain-machine interfaces (BMI) have helped restore functionality and independence to individuals living with sensorimotor deficits; however, tasks requiring bimanual coordination and fine manipulation continue to remain unsolved given the technical complexity of controlling multiple degrees of freedom (DOF) across multiple limbs in a coordinated way through a user input. To address this challenge, we implemented a collaborative shared control strategy to manipulate and coordinate two Modular Prosthetic Limbs (MPL) for performing a bimanual self-feeding task. A human participant with microelectrode arrays in sensorimotor brain regions provided commands to both MPLs to perform the self-feeding task, which included bimanual cutting. Motor commands were decoded from bilateral neural signals to control up to two DOFs on each MPL at a time. The shared control strategy enabled the participant to map his four-DOF control inputs, two per hand, to as many as 12 DOFs for specifying robot end effector position and orientation. Using neurally-driven shared control, the participant successfully and simultaneously controlled movements of both robotic limbs to cut and eat food in a complex bimanual self-feeding task. This demonstration of bimanual robotic system control via a BMI in collaboration with intelligent robot behavior has major implications for restoring complex movement behaviors for those living with sensorimotor deficits.

Understanding the cortical representations of movements and their stability can shed light on improved brain-machine interface (BMI) approaches to decode these representations without frequent recalibration. Here, we characterize the spatial organization (somatotopy) and stability of the bilateral sensorimotor map of forearm muscles in an incomplete-high spinal-cord injury study participant implanted bilaterally in the primary motor and sensory cortices with Utah microelectrode arrays (MEAs). We built representation maps by recording bilateral multiunit activity (MUA) and surface electromyography (EMG) as the participant executed voluntary contractions of the extensor carpi radialis (ECR), and attempted motions in the flexor carpi radialis (FCR), which was paralytic. To assess stability, we repeatedly mapped and compared left- and right-wrist-extensor-related activity throughout several sessions, comparing somatotopy of active electrodes, as well as neural signals both at the within-electrode (multiunit) and cross-electrode (network) levels. Wrist motions showed significant activation in motor and sensory cortical electrodes. Within electrodes, firing strength stability diminished as the time increased between consecutive measurements (hours within a session, or days across sessions), with higher stability observed in sensory cortex than in motor, and in the contralateral hemisphere than in the ipsilateral. However, we observed no differences at network level, and no evidence of decoding instabilities for wrist EMG, either across timespans of hours or days, or across recording area. While map stability differs between brain area and hemisphere at multiunit/electrode level, these differences are nullified at ensemble level.

Defining eloquent cortex intraoperatively, traditionally performed by neurosurgeons to preserve patient function, can now help target electrode implantation for restoring function. Brain-machine interfaces (BMIs) have the potential to restore upper-limb motor control to paralyzed patients but require accurate placement of recording and stimulating electrodes to enable functional control of a prosthetic limb. Beyond motor decoding from recording arrays, precise placement of stimulating electrodes in cortical areas associated with finger and fingertip sensations allows for the delivery of sensory feedback that could improve dexterous control of prosthetic hands. In this study, the authors demonstrated the use of a novel intraoperative online functional mapping (OFM) technique with high-density electrocorticography to localize finger representations in human primary somatosensory cortex. In conjunction with traditional pre- and intraoperative targeting approaches, this technique enabled accurate implantation of stimulating microelectrodes, which was confirmed by postimplantation intracortical stimulation of finger and fingertip sensations. This work demonstrates the utility of intraoperative OFM and will inform future studies of closed-loop BMIs in humans.

Advances in brain-machine interfaces have helped restore function and independence for individuals with sensorimotor deficits; however, providing efficient and effective sensory feedback remains challenging. Intracortical microstimulation (ICMS) of sensorimotor brain regions is a promising technique for providing bioinspired sensory feedback. In a human participant with chronically-implanted microelectrode arrays, we provided ICMS to the primary somatosensory cortex to generate tactile percepts in his hand. In a 3-choice object identification task, the participant identified virtual objects using tactile sensory feedback and no visual information. We evaluated three different stimulation paradigms, each with a different weighting of the grip force and its derivative, to explore the potential benefits of a more bioinspired stimulation strategy. In all paradigms, the participant's ability to identify the objects was above-chance, with object identification accuracy reaching 80% correct when using only sustained grip force feedback and 76.7% when using equal weighting of both sustained grip force and its derivative. These results demonstrate that bioinspired ICMS can provide sensory feedback that is functionally beneficial in sensorimotor tasks. Designing more efficient stimulation paradigms is important because it will allow us to 1) provide safer stimulation delivery methods that reduce overall injected charge without sacrificing function and 2) more effectively transmit sensory information to promote intuitive integration and usage by the human body.

The complex nature of neural connections throughout the cerebral cortex has led to broad interest in understanding cortical functional networks of tactile perception and sensorimotor integration. Cortico-cortical evoked potentials (CCEPs) can be used as physiological markers to study and map cerebral networks in the brain. In a human participant with bi-hemispheric microelectrode array implants in sensorimotor regions of the brain, we found that intracortical microstimulation (ICMS) of the primary somatosensory cortex can lead to evoked responses in the motor cortex in the same hemisphere, indicating connectivity between these sensorimotor regions. Single ICMS pulses were not consciously perceived, but elicited a rapid evoked potential approximately 20 ms after stimulus onset. Multi-pulse ICMS trains, perceived as tactile sensations in the thumb, sustained over an approximately 33 ms period, led to a delayed evoked response roughly 80 ms after stimulus onset. This work is important not only for better understanding the functional relationship between cortical areas, specifically somatosensory and motor cortices, but also to provide insight on pathways where neuromodulation techniques could be employed for rehabilitation or mitigation of sensorimotor neurodegenerative effects.

The restoration of cutaneous sensation to fingers and fingertips is critical to achieving dexterous prosthesis control for individuals with sensorimotor dysfunction. However, localized and reproducible fingertip sensations in humans have not been reported via intracortical microstimulation (ICMS) in humans. Here, we show that ICMS in a human participant was capable of eliciting percepts in 7 fingers spanning both hands, including 6 fingertip regions (i.e., 3 on each hand). Median percept size was estimated to include 1.40 finger or palmar segments (e.g., one segment being a fingertip or the section of upper palm below a finger). This was corroborated with a more sensitive manual marking technique where median percept size corresponded to roughly 120% of a fingertip segment. Percepts showed high intra-day consistency, including high performance (99%) on a blinded finger discrimination task. Across days, there was more variability in percepts, with 75.8% of trials containing the modal finger or palm region for the stimulated electrode. These results suggest that ICMS can enable the delivery of localized fingertip sensations during object manipulation by neuroprostheses. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Trial NCT03161067 ### Funding Statement This research was developed with funding from the Defense Advanced Research Projects Agency's (DARPA; Arlington, VA) Revolutionizing Prosthetics program (contract number N66001-10-C-4056). Development of experimental setup and support for regulatory submissions associated with this study were provided by a grant from the Alfred E. Mann Foundation. Study software infrastructure and study preparation were developed with internal funding from Johns Hopkins University Applied Physics Laboratory and Johns Hopkins University. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was conducted under Investigational Device Exemption (IDE, 170010) by the Food and Drug Administration (FDA) for the purpose of evaluating bilateral sensory and motor capabilities of microelectrode array implants. The study protocol was approved by the FDA, the Johns Hopkins Institutional Review Board (JH IRB) and NIWC Pacific IRB. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Data is not publicly available at this time.

ABSTRACT Most daily tasks require simultaneous control of both hands. Here we demonstrate simultaneous classification of gestures in both hands using multi-unit activity recorded from bilateral motor and somatosensory cortices of a tetraplegic participant. Attempted gestures were classified using hierarchical linear discriminant models trained separately for each hand. In an online experiment, gestures were continuously classified and used to control two robotic arms in a center-out movement task. Bimanual trials that required keeping one hand still resulted in the best performance (70.6%), followed by symmetric movement trials (50%) and asymmetric movement trials (22.7%). Our results indicate that gestures can be simultaneously decoded in both hands using two independently trained hand models concurrently, but online control using this approach becomes more difficult with increased complexity of bimanual gesture combinations. This study demonstrates the potential for restoring simultaneous control of both hands using a bilateral intracortical brain-machine interface.

Despite advances in the capabilities of robotic limbs, their clinical use by patients with motor disabilities is limited because of inadequate levels of user control. Our Johns Hopkins University Applied Physics Laboratory (APL) team and collaborators designed an augmented reality (AR) control interface that accepts multiple levels of user inputs to a robotic limb using noninvasive eye tracking technology to enhance user control. Our system enables either direct control over 3-D endpoint, gripper orientation, and aperture or supervisory control over several common tasks leveraging computer vision and intelligent route-planning algorithms. This system enables automation of several high-frequency movements (e.g., grabbing an object) that are typically time consuming and require high degrees of precision. Supervisory control can increase movement accuracy and robustness while decreasing the demands on user inputs. We conducted a pilot study in which three subjects with Duchenne muscular dystrophy completed a pick-and-place motor task with the AR interface using both traditional direct and newer supervisory control strategies. The pilot study demonstrated the effectiveness of AR interfaces and the utility of supervisory control for reducing completion time and cognitive burden for certain necessary, repeatable prosthetic control tasks. Future goals include generalizing the supervisory control modes to a wider variety of objects and activities of daily living and integrating the capability into wearable headsets with mixed reality capabilities.

Brain-machine interface (BMI) researchers have traditionally focused on modeling endpoint reaching tasks to provide the control of neurally driven prosthetic arms. Most previous research has focused on achieving an endpoint control through a Cartesian-coordinate-centered approach. However, a joint-centered approach could potentially be used to intuitively control a wide range of limb movements. We systematically investigated the feasibility of discriminating between flexion and extension of different upper limb joints using electrocorticography(ECoG) recordings from sensorimotor cortex. Four subjects implanted with macro-ECoG (10-mm spacing), high-density ECoG (5-mm spacing), and/or micro-ECoG arrays (0.9-mm spacing and 4 mm × 4 mm coverage), performed randomly cued flexions or extensions of the fingers, wrist, or elbow contralateral to the implanted hemisphere. We trained a linear model to classify six movements using averaged high-gamma power (70-110 Hz) modulations at different latencies with respect to movement onset, and within a time interval restricted to flexion or extension at each joint. Offline decoding models for each subject classified these movements with accuracies of 62%-83%. Our results suggest that the widespread ECoG coverage of sensorimotor cortex could allow a whole limb BMI to sample native cortical representations in order to control flexion and extension at multiple joints.

SEE CORRESPONDING ARTICLE ON PAGE 466 Mechanisms of Antidepressant Response to Electroconvulsive Therapy Studied With Perfusion Magnetic Resonance ImagingBiological PsychiatryVol. 85Issue 6PreviewConverging evidence suggests that electroconvulsive therapy (ECT) induces neuroplasticity in patients with severe depression, though how this relates to antidepressant response is less clear. Arterial spin-labeled functional magnetic resonance imaging tracks absolute changes in cerebral blood flow (CBF) linked with brain function and offers a potentially powerful tool when observing neurofunctional plasticity with functional magnetic resonance imaging. Full-Text PDF

SEE CORRESPONDING ARTICLE ON PAGE 28 Prospective Validation That Subgenual Connectivity Predicts Antidepressant Efficacy of Transcranial Magnetic Stimulation SitesBiological PsychiatryVol. 84Issue 1PreviewThe optimal target in the dorsolateral prefrontal cortex for treating depression with repetitive transcranial magnetic stimulation (rTMS) remains unknown. Better efficacy has been associated with stimulation sites that are 1) more anterior and lateral and 2) more functionally connected to the subgenual cingulate. Here we prospectively test whether these factors predict response in individual patients. Full-Text PDF

Background Neuropsychiatric disorders are a leading source of disability and require novel treatments that target mechanisms of disease. As such disorders are thought to result from aberrant neuronal circuit activity, neuromodulation approaches are of increasing interest given their potential for manipulating circuits directly. Low intensity transcranial electrical stimulation (tES) with direct currents (transcranial direct current stimulation, tDCS) or alternating currents (transcranial alternating current stimulation, tACS) represent novel, safe, well-tolerated, and relatively inexpensive putative treatment modalities. Objective This report seeks to promote the science, technology and effective clinical applications of these modalities, identify research challenges, and suggest approaches for addressing these needs in order to achieve rigorous, reproducible findings that can advance clinical treatment. Methods The National Institute of Mental Health (NIMH) convened a workshop in September 2016 that brought together experts in basic and human neuroscience, electrical stimulation biophysics and devices, and clinical trial methods to examine the physiological mechanisms underlying tDCS/tACS, technologies and technical strategies for optimizing stimulation protocols, and the state of the science with respect to therapeutic applications and trial designs. Results Advances in understanding mechanisms, methodological and technological improvements (e.g., electronics, computational models to facilitate proper dosing), and improved clinical trial designs are poised to advance rigorous, reproducible therapeutic applications of these techniques. A number of challenges were identified and meeting participants made recommendations made to address them. Conclusions These recommendations align with requirements in NIMH funding opportunity announcements to, among other needs, define dosimetry, demonstrate dose/response relationships, implement rigorous blinded trial designs, employ computational modeling, and demonstrate target engagement when testing stimulation-based interventions for the treatment of mental disorders.