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Purpose of Review: While wearable robotics is expanding within clinical settings, particularly for neurological rehabilitation, there is still a lack of consensus on how to effectively assess the performance of these devices. This review focuses on the most common metrics, whose selection and design are crucial for optimizing treatment outcomes and potentially improve the standard care., Recent Findings: The literature reveals that while wearable robots are equipped with various embedded sensors, most studies still rely on traditional, nontechnological methods for assessment. Recent studies have shown that, although quantitative data from embedded sensors are available (e.g., kinematics), these are underutilized in favor of qualitative assessments. A trend toward integrating automatic assessments from the devices themselves is emerging, with a few notable studies pioneering this approach., Summary: Our analysis suggests a critical need for developing standardized metrics that leverage the data from embedded sensors in wearable robots. This shift could enhance the accuracy of patient assessments and the effectiveness of rehabilitation strategies, ultimately leading to better patient outcomes in neurological rehabilitation., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

The clinical applications of neurotechnology are rapidly expanding, and the combination of different approaches could be more effective and precise to treat brain disorders. This Perspective discusses the potential and challenges of "multimodal neuromodulation," which combines modalities such as electrical, magnetic, and ultrasound stimulation., Competing Interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: GF is co-founder and shareholder of Neuronika S.p.A. (Italy), which develops and commercializes products for deep brain stimulation and transcranial direct current stimulation, and of Neurek SL (Spain), which develops and commercializes products for transcranial static magnetic field stimulation. SM is co-founder and shareholder of Sensars Neurotechnology, which develops neuromodulation devices for pain management and of Action Potential Neurotechnology, which develops neuromodulation devices for sensory and motor function restoration., (Copyright: © 2024 Micera, Foffani. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Traditional microelectrode arrays (MEAs) are limited to measuring electrophysiological activity in two dimensions, failing to capture the complexity of three-dimensional (3D) tissues such as neural organoids and spheroids. Here, we introduce a flower-shaped MEA (e-Flower) that can envelop submillimeter brain spheroids following actuation by the sole addition of the cell culture medium. Inspired by soft microgrippers, its actuation mechanism leverages the swelling properties of a polyacrylic acid hydrogel grafted to a polyimide substrate hosting the electrical interconnects. Compatible with standard electrophysiology recording systems, the e-Flower does not require additional equipment or solvents and is ready to use with preformed 3D tissues. We designed an e-Flower achieving a curvature as low as 300 micrometers within minutes, a value tunable by the choice of reswelling media and hydrogel cross-linker concentration. Furthermore, we demonstrate the ability of the e-Flower to detect spontaneous neural activity across the spheroid surface, demonstrating its potential for comprehensive neural signal recording.

Objective: This study explored intraneural stimulation of the right thoracic vagus nerve (VN) in sexually mature male minipigs to modulate safe heart rate and blood pressure response., Material and Methods: We employed an intraneural electrode designed for the VN of pigs to perform VN stimulation (VNS). This was delivered using different numbers of contacts on the electrode and different stimulation parameters (amplitude, frequency, and pulse width), identifying the most suitable stimulation configuration. All the parameter ranges had been selected from a computational cardiovascular system model., Results: Clinically relevant responses were observed when stimulating with low current intensities and relatively low frequencies delivered with a single contact. Selecting a biphasic, charge-balanced square wave for VNS with a current amplitude of 500 μA, frequency of 10 Hz, and pulse width of 200 μs, we obtained heart rate reduction of 7.67 ± 5.19 beats per minute, systolic pressure reduction of 5.75 ± 2.59 mmHg, and diastolic pressure reduction of 3.39 ± 1.44 mmHg., Conclusion: Heart rate modulation was obtained without inducing any observable adverse effects, underlining the high selectivity of the intraneural approach., Competing Interests: Conflict of Interest The authors reported no conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The human hand, with its intricate sensory capabilities, plays a pivotal role in our daily interactions with the world. This remarkable organ possesses a wide range of natural sensors that enrich our experiences, enabling us to perceive touch, position, and temperature. These natural sensors work in concert to provide us with a rich sensory experience, enabling us to distinguish between various textures, gauge the force of our grip, determine the position of our fingers without needing to see them, perceive the temperature of objects we come into contact with or detect if a cloth is wet or dry. This complex sensory system is fundamental to our ability to manipulate objects, explore our surroundings, and interact with the world and people around us. In this article, we summarize the research performed in our laboratories over the years and our findings to restore both touch, position, and temperature modalities. The combination of intraneural stimulation, sensory substitution, and wearable technology opens new possibilities for enhancing sensory feedback in prosthetic hands, promising improved functionality and a closer approximation to natural sensory experiences for individuals with limb differences., (© 2024 The Author(s). Artificial Organs published by International Center for Artificial Organ and Transplantation (ICAOT) and Wiley Periodicals LLC.)

Implantable neural interfaces with the central and peripheral nervous systems are currently used to restore sensory, motor, and cognitive functions in disabled people with very promising results. They have also been used to modulate autonomic activities to treat diseases such as diabetes or hypertension. Here, this study proposes to extend the use of these technologies to (re-)establish the connection between new (transplanted or artificial) organs and the nervous system in order to increase the long-term efficacy and the effective biointegration of these solutions. In this perspective paper, some clinically relevant applications of this approach are briefly described. Then, the choices that neural engineers must implement about the type, implantation location, and closed-loop control algorithms to successfully realize this approach are highlighted. It is believed that these new "organ neuroprostheses" are going to become more and more valuable and very effective solutions in the years to come., (© 2024 The Authors. Advanced Healthcare Materials published by Wiley‐VCH GmbH.)

Background and Objectives: Lower-limb wearable devices can significantly improve the quality of life of subjects suffering from debilitating conditions, such as amputations, neurodegenerative disorders, and stroke-related impairments. Current control approaches, limited to forward walking, fall short of replicating the complexity of human locomotion in complex environments, such as uneven terrains or crowded places. Here we propose a high-level controller based on two Support Vector Machines exploiting four surface electromyography (EMG) signals of the thigh muscles to detect the onset (Toe-off intention decoder) and the direction (Directional EMG decoder) of the upcoming step., Methods and Materials: We validated a preliminary version of the approach by acquiring EMG signals from ten healthy subjects, performing steps in four directions (forward, backward, right, and left), in three different settings (ground-level walking, stairs, and ramps), and in both steady-state and static conditions. Both the Toe-off intention and Directional EMG decoders have been tested with a 5-fold cross-validation repeated five times, using linear and radial-basis-function kernels, and by changing the classification output timing, from 200 ms before to 50 ms after the toe-off., Results: The Toe-off intention decoder reached a median accuracy of 83.34 % (interquartile range (IQR): 6.48) and specificity of 92.72 % (IQR: 3.62) in its radial-basis-function version, while the Directional EMG decoder's median accuracy ranged between 73.92 % (IQR: 5.8), 200 ms before the toe-off, to 92.91 % (IQR: 4.11), 50 ms after the toe-off, with the radial-basis-function kernel implementation. For both the Toe-off intention and Directional EMG decoders the radial-basis-function version achieved better performances than the linear one (Wilcoxon signed rank test, p < 0.05)., Conclusions and Significance: The combination of the two decoders proved to be a promising solution to detect the step initiation and classify its direction, paving the way for wearable devices with a broader range of movements and more degrees of freedom, ultimately promoting usability in uncontrolled settings and better reactions to external perturbations. Additionally, the encumbrance of the setup is limited to the thigh of the leg of interest, which simplifies the implementation in compact devices, concurrently limiting the sensors worn by the subject., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Peripheral neural interfaces facilitate bidirectional communication between the nervous system and external devices, enabling precise control for prosthetic limbs, sensory feedback systems, and therapeutic interventions in the field of Bioelectronic Medicine. Intraneural interfaces hold great promise since they ensure high selectivity in communicating only with the desired nerve fascicles. Despite significant advancements, challenges such as chronic immune response, signal degradation over time, and lack of long-term biocompatibility remain critical considerations in the development of such devices. Here we report on the development and benchtop characterization of a novel design of an intraneural interface based on carbon fiber bundles. Carbon fibers possess low impedance, enabling enhanced signal detection and stimulation efficacy compared to traditional metal electrodes. We provided a 3D-stabilizing structure for the carbon fiber bundles made of PEDOT:PSS hydrogel, to enhance the biocompatibility between the carbon fibers and the nervous tissue. We further coated the overall bundles with a thin layer of elastomeric material to provide electrical insulation. Taken together, our results demonstrated that our electrode possesses adequate structural and electrochemical properties to ensure proper stimulation and recording of peripheral nerve fibers and a biocompatible interface with the nervous tissue., (© 2024. The Author(s).)

Acoustic, lexical, and syntactic information are simultaneously processed in the brain requiring complex strategies to distinguish their electrophysiological activity. Capitalizing on previous works that factor out acoustic information, we could concentrate on the lexical and syntactic contribution to language processing by testing competing statistical models. We exploited electroencephalographic recordings and compared different surprisal models selectively involving lexical information, part of speech, or syntactic structures in various combinations. Electroencephalographic responses were recorded in 32 participants during listening to affirmative active declarative sentences. We compared the activation corresponding to basic syntactic structures, such as noun phrases vs. verb phrases. Lexical and syntactic processing activates different frequency bands, partially different time windows, and different networks. Moreover, surprisal models based on part of speech inventory only do not explain well the electrophysiological data, while those including syntactic information do. By disentangling acoustic, lexical, and syntactic information, we demonstrated differential brain sensitivity to syntactic information. These results confirm and extend previous measures obtained with intracranial recordings, supporting our hypothesis that syntactic structures are crucial in neural language processing. This study provides a detailed understanding of how the brain processes syntactic information, highlighting the importance of syntactic surprisal in shaping neural responses during language comprehension., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The objective of this study was to characterize hemodynamic changes during trans-vascular stimulation of the renal nerve and their dependence on stimulation parameters. We employed a stimulation catheter inserted in the right renal artery under fluoroscopic guidance, in pigs. Systolic, diastolic and pulse blood pressure and heart rate were recorded during stimulations delivered at different intravascular sites along the renal artery or while varying stimulation parameters (amplitude, frequency, and pulse width). Blood pressure changes during stimulation displayed a pattern more complex than previously described in literature, with a series of negative and positive peaks over the first two minutes, followed by a steady state elevation during the remainder of the stimulation. Pulse pressure and heart rate only showed transient responses, then they returned to baseline values despite constant stimulation. The amplitude of the evoked hemodynamic response was roughly linearly correlated with stimulation amplitude, frequency, and pulse width., (© 2024 The Authors.)

Background: Cortical excitation/inhibition dynamics have been suggested as a key mechanism occurring after stroke. Their supportive or maladaptive role in the course of recovery is still not completely understood. Here, we used transcranial magnetic stimulation (TMS)-electroencephalography coupling to study cortical reactivity and intracortical GABAergic inhibition, as well as their relationship to residual motor function and recovery longitudinally in patients with stroke., Methods: Electroencephalography responses evoked by TMS applied to the ipsilesional motor cortex were acquired in patients with stroke with upper limb motor deficit in the acute (1 week), early (3 weeks), and late subacute (3 months) stages. Readouts of cortical reactivity, intracortical inhibition, and complexity of the evoked dynamics were drawn from TMS-evoked potentials induced by single-pulse and paired-pulse TMS (short-interval intracortical inhibition). Residual motor function was quantified through a detailed motor evaluation., Results: From 76 patients enrolled, 66 were included (68.2±13.2 years old, 18 females), with a Fugl-Meyer score of the upper extremity of 46.8±19. The comparison with TMS-evoked potentials of healthy older revealed that most affected patients exhibited larger and simpler brain reactivity patterns ( P <0.05). Bayesian ANCOVA statistical evidence for a link between abnormally high motor cortical excitability and impairment level. A decrease in excitability in the following months was significantly correlated with better motor recovery in the whole cohort and the subgroup of recovering patients. Investigation of the intracortical GABAergic inhibitory system revealed the presence of beneficial disinhibition in the acute stage, followed by a normalization of inhibitory activity. This was supported by significant correlations between motor scores and the contrast of local mean field power and readouts of signal dynamics.cluster <0.05). Bayesian ANCOVA statistical evidence for a link between abnormally high motor cortical excitability and impairment level. A decrease in excitability in the following months was significantly correlated with better motor recovery in the whole cohort and the subgroup of recovering patients. Investigation of the intracortical GABAergic inhibitory system revealed the presence of beneficial disinhibition in the acute stage, followed by a normalization of inhibitory activity. This was supported by significant correlations between motor scores and the contrast of local mean field power and readouts of signal dynamics., Conclusions: The present results revealed an abnormal motor cortical reactivity in patients with stroke, which was driven by perturbations and longitudinal changes within the intracortical inhibition system. They support the view that disinhibition in the ipsilesional motor cortex during the first-week poststroke is beneficial and promotes neuronal plasticity and recovery., Competing Interests: Disclosures Dr Hummel serves as a board member for Novartis Foundation for Medical-Biological Research. Dr Blanke is a cofounder and a shareholder of Metaphysiks Engineering Société Anonyme, a company that develops immersive technologies, including applications of the robotic induction of presence hallucinations that are not related to the diagnosis, prognosis, or treatment in medicine. Dr Blanke is a member of the board and a shareholder of Mindmaze Société Anonyme.

Background: Neurological disorders, such as stroke and chronic pain syndromes, profoundly impact independence and quality of life, especially when affecting upper extremity (UE) function. While conventional physical therapy has shown effectiveness in providing some neural recovery in affected individuals, there remains a need for improved interventions. Virtual reality (VR) has emerged as a promising technology-based approach for neurorehabilitation to make the patient's experience more enjoyable. Among VR-based rehabilitation paradigms, those based on fully immersive systems with headsets have gained significant attention due to their potential to enhance patient's engagement., Methods: This scoping review aims to investigate the current state of research on the use of immersive VR for UE rehabilitation in individuals with neurological diseases, highlighting benefits and limitations. We identified thirteen relevant studies through comprehensive searches in Scopus, PubMed, and IEEE Xplore databases. Eligible studies incorporated immersive VR for UE rehabilitation in patients with neurological disorders and evaluated participants' neurological and motor functions before and after the intervention using clinical assessments., Results: Most of the included studies reported improvements in the participants rehabilitation outcomes, suggesting that immersive VR represents a valuable tool for UE rehabilitation in individuals with neurological disorders. In addition, immersive VR-based interventions hold the potential for personalized and intensive training within a telerehabilitation framework. However, further studies with better design are needed for true comparison with traditional therapy. Also, the potential side effects associated with VR head-mounted displays, such as dizziness and nausea, warrant careful consideration in the development and implementation of VR-based rehabilitation programs., Conclusion: This review provides valuable insights into the application of immersive VR in UE rehabilitation, offering the foundation for future research and clinical practice. By leveraging immersive VR's potential, researchers and rehabilitation specialists can design more tailored and patient-centric rehabilitation strategies, ultimately improving the functional outcome and enhancing the quality of life of individuals with neurological diseases., (© 2024. The Author(s).)

Objective: Brain-body interfaces (BBIs) have emerged as a very promising solution for restoring voluntary hand control in people with upper-limb paralysis. The BBI module decoding motor commands from brain signals should provide the user with intuitive, accurate, and stable control. Here, we present a preliminary investigation in a monkey of a brain decoding strategy based on the direct coupling between the activity of intrinsic neural ensembles and output variables, aiming at achieving ease of learning and long-term robustness. Results: We identified an intrinsic low-dimensional space (called manifold) capturing the co-variation patterns of the monkey's neural activity associated to reach-to-grasp movements. We then tested the animal's ability to directly control a computer cursor using cortical activation along the manifold axes. By daily recalibrating only scaling factors, we achieved rapid learning and stable high performance in simple, incremental 2D tasks over more than 12 weeks of experiments. Finally, we showed that this brain decoding strategy can be effectively coupled to peripheral nerve stimulation to trigger voluntary hand movements. Conclusions: These results represent a proof of concept of manifold-based direct control for BBI applications., Competing Interests: EL, SS, and SM are founders of Action Potential Neurotechnology, a company that develops implantable neuroprostheses. The remaining authors declare no competing interests., (© 2024 The Authors.)

Background: Cuff electrodes target various nerves throughout the body, providing neuromodulation therapies for motor, sensory, or autonomic disorders. However, when using standard, thick silicone cuffs, fabricated in discrete circular sizes, complications may arise, namely cuff displacement or nerve compression, due to a poor adaptability to variable nerve shapes and sizes encountered in vivo. Improvements in cuff design, materials, closing mechanism and surgical approach are necessary to overcome these issues., Methods: In this work, we propose a microfabricated multi-channel silicone-based soft cuff electrode with a novel easy-to-implant and size-adaptable design and evaluate a number of essential features such as nerve-cuff contact, nerve compression, cuff locking stability, long-term integration and stimulation selectivity. We also compared performance to that of standard fixed-size cuffs., Results: The belt-like cuff made of 150 μm thick silicone membranes provides a stable and pressure-free conformal contact, independently of nerve size variability, combined with a straightforward implantation procedure. The adaptable design and use of soft materials lead to limited scarring and demyelination after 6-week implantation. In addition, multi-contact designs, ranging from 6 to 16 electrodes, allow for selective stimulation in models of rat and pig sciatic nerve, achieving targeted activation of up to 5 hindlimb muscles., Conclusion: These results suggest a promising alternative to classic fixed-diameter cuffs and may facilitate the adoption of soft, adaptable cuffs in clinical settings., (© 2024. The Author(s).)

Lower urinary tract dysfunction, such as incontinence or urinary retention, is one of the leading consequences of neurological diseases. This significantly impacts the quality of life for those affected, with implications extending not only to humans but also to clinical veterinary care. Having motor and sensory fibers, the pudendal nerve is an optimal candidate for neuromodulation therapies using bidirectional intraneural prostheses, paving the way towards the restoration of a more physiological urination cycle: bladder state can be detected from recorded neural signals, then an electrical current can be injected to the nerve based on the real-time need of the bladder. To develop such prostheses and investigate this novel approach, animal studies are still required since the morphology of the target nerve is fundamental to optimizing the prosthesis design. This study aims to describe the porcine pudendal nerve as a model for neuromodulation studies aiming at restoring lower urinary tract dysfunction. Five male farm pigs were involved in the study. First, a surgical procedure to access the porcine pudendal nerve without muscle resection was developed. Then, an intraneural interface was implanted to confirm the presence of fibers innervating the external urethral sphincter by measuring its electromyographic activity. Finally, the morphophysiology of the porcine pudendal nerve at the level of surgical exposure was described by using histological and immunohistochemical characterization. This analysis confirmed the fasciculate nature of the nerve and the presence of mixed fibers with a spatial and functional organization. These achievements pave the way for further pudendal neuromodulation studies by using a clinically relevant animal model with the potential for translating the findings into clinical applications.

Background: The impact of acute unilateral injury on spontaneous electrical activity in both vagus nerves at the heart level is poorly understood. We investigated the immediate neuroelectrical response after right or left cardiac vagal nerve transection (VNTx) by recording spiking activity of each heart vagus nerve (VN)., Methods: Fourteen male Göttingen minipigs underwent sternotomy. Multi-electrode cuffs were implanted below the cut level to record vagal electroneurographic signals during electrocardiographic and hemodynamic monitoring, before and immediately after cardiac VNTx (left: L-cut, n = 6; right: R-cut, n = 8)., Results: Left cardiac VNTx significantly reduced multi-unit electrical activity (MUA) firing rate in the vagal stump (-30.7% vs pre-cut) and intact right VN (-21.8% vs pre-cut) at the heart level, without affecting heart rate, heart rate variability, or hemodynamics. In contrast, right cardiac VNTx did not acutely alter MUA in either VN but slightly increased (p < 0.022) the root mean square of successive RR interval differences (rMSSD), an index of parasympathetic outflow, without affecting hemodynamics., Conclusions: Our study reveals an early left-lateralized pattern in vagal spiking activity following unilateral cardiac vagotomy. These findings enhance understanding of the neuroelectrical response to vagal injury and provide insights into preserving vagal outflow after unilateral cardiac vagotomy. Importantly, monitoring spiking activity of the cardiac right VN may predict onset of left vagal pathway injury, which is detrimental to cardiac patients and can occur as a complication of catheter ablation for atrial fibrillation., (Copyright © 2023. Published by Elsevier B.V.)

With the brain, the spinal cord forms the central nervous system. Initially considered a passive relay between the brain and the periphery, the spinal cord is now recognized as being active and plastic. Yet, it remains largely overlooked by the human neuroscience community, in stark contrast with the wealth of research investigating the brain. In this review, we argue that fMRI, traditionally used to image cerebral function, can be extended beyond the brain to help unravel spinal mechanisms involved in human behaviors. To this end, we first outline strategies that have been proposed to tackle the challenges inherent to spinal cord fMRI. Then, we discuss how they have been utilized to provide insights into the functional organization of spinal sensorimotor circuits, highlighting their potential to address fundamental and clinical questions. By summarizing guidelines and applications of spinal cord fMRI, we hope to stimulate and support further research into this promising yet underexplored field., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Neuroprosthetic devices used for the treatment of lower urinary tract dysfunction, such as incontinence or urinary retention, apply a pre-set continuous, open-loop stimulation paradigm, which can cause voiding dysfunctions due to neural adaptation. In the literature, conditional, closed-loop stimulation paradigms have been shown to increase bladder capacity and voiding efficacy compared to continuous stimulation. Current limitations to the implementation of the closed-loop stimulation paradigm include the lack of robust and real-time decoding strategies for the bladder fullness state. We recorded intraneural pudendal nerve signals in five anesthetized pigs. Three bladder-filling states, corresponding to empty, full, and micturition, were decoded using the Random Forest classifier. The decoding algorithm showed a mean balanced accuracy above 86.67% among the three classes for all five animals. Our approach could represent an important step toward the implementation of an adaptive real-time closed-loop stimulation protocol for pudendal nerve modulation, paving the way for the design of an assisted-as-needed neuroprosthesis., Competing Interests: The authors have no conflicts to disclose., (© 2023 Author(s).)

Background: Around 25% of patients who have had a stroke suffer from severe upper-limb impairment and lack effective rehabilitation strategies. The AVANCER proof-of-concept clinical trial (NCT04448483) tackles this issue through an intensive and personalized-dosage cumulative intervention that combines multiple non-invasive neurotechnologies., Methods: The therapy consists of two sequential interventions, lasting until the patient shows no further motor improvement, for a minimum of 11 sessions each. The first phase involves a brain-computer interface governing an exoskeleton and multi-channel functional electrical stimulation enabling full upper-limb movements. The second phase adds anodal transcranial direct current stimulation of the motor cortex of the lesioned hemisphere. Clinical, electrophysiological, and neuroimaging examinations are performed before, between, and after the two interventions (T0, T1, and T2). This case report presents the results from the first patient of the study., Findings: The primary outcome (i.e., 4-point improvement in the Fugl-Meyer assessment of the upper extremity) was met in the first patient, with an increase from 6 to 11 points between T0 and T2. This improvement was paralleled by changes in motor-network structure and function. Resting-state and transcranial magnetic stimulation-evoked electroencephalography revealed brain functional changes, and magnetic resonance imaging (MRI) measures detected structural and task-related functional changes., Conclusions: These first results are promising, pointing to feasibility, safety, and potential efficacy of this personalized approach acting synergistically on the nervous and musculoskeletal systems. Integrating multi-modal data may provide valuable insights into underlying mechanisms driving the improvements and providing predictive information regarding treatment response and outcomes., Funding: This work was funded by the Wyss-Center for Bio and Neuro Engineering (WCP-030), the Defitech Foundation, PHRT-#2017-205, ERA-NET-NEURON (Discover), and SNSF (320030L&#95;197899, NiBS-iCog)., Competing Interests: Declaration of interests A.E. works for the Wyss Center for Bio and Neuroengineering, sponsor of the clinical trial., (Copyright © 2023 Elsevier Inc. All rights reserved.)

High-density surface electromyography (HDsEMG) allows noninvasive muscle monitoring and disease diagnosis. Clinical translation of current HDsEMG technologies is hampered by cost, limited scalability, low usability, and minimal spatial coverage. Here, this study presents, validates, and demonstrates the broad clinical applicability of dry wearable MXene HDsEMG arrays (MXtrodes) fabricated from safe and scalable liquid-phase processing of Ti 3 C 2 T x . The fabrication scheme allows easy customization of array geometry to match subject anatomy, while the gel-free and minimal skin preparation enhance usability and comfort. The low impedance and high conductivity of the MXtrode arrays allow detection of the activity of large muscle groups at higher quality and spatial resolution than state-of-the-art wireless electromyography  sensors, and in realistic clinical scenarios. To demonstrate the clinical applicability of MXtrodes in the context of neuromuscular diagnostics and rehabilitation, simultaneous HDsEMG and biomechanical mapping of muscle groups across the whole calf during various tasks, ranging from controlled contractions to walking is shown. Finally, the integration of HDsEMG acquired with MXtrodes with a machine learning pipeline and the accurate prediction of the phases of human gait are shown. The results underscore the advantages and translatability of MXene-based wearable bioelectronics for studying neuromuscular function and disease, as well as for precision rehabilitation., (© 2022 Wiley-VCH GmbH.)

Planning and execution of voluntary movement depend on the contribution of distinct classes of neurons in primary motor and premotor areas. However, timing and pattern of activation of GABAergic cells during specific motor behaviors remain only partly understood. Here, we directly compared the response properties of putative pyramidal neurons (PNs) and GABAergic fast-spiking neurons (FSNs) during spontaneous licking and forelimb movements in male mice. Recordings centered on the face/mouth motor field of the anterolateral motor cortex (ALM) revealed that FSNs fire longer than PNs and earlier for licking, but not for forelimb movements. Computational analysis revealed that FSNs carry vastly more information than PNs about the onset of movement. While PNs differently modulate their discharge during distinct motor acts, most FSNs respond with a stereotyped increase in firing rate. Accordingly, the informational redundancy was greater among FSNs than PNs. Finally, optogenetic silencing of a subset of FSNs reduced spontaneous licking movement. These data suggest that a global rise of inhibition contributes to the initiation and execution of spontaneous motor actions. SIGNIFICANCE STATEMENT Our study contributes to clarifying the causal role of fast-spiking neurons (FSNs) in driving initiation and execution of specific, spontaneous movements. Within the face/mouth motor field of mice premotor cortex, FSNs fire before pyramidal neurons (PNs) with a specific activation pattern: they reach their peak of activity earlier than PNs during the initiation of licking, but not of forelimb, movements; duration of FSNs activity is also greater and exhibits less selectivity for the movement type, as compared with that of PNs. Accordingly, FSNs appear to carry more redundant information than PNs. Optogenetic silencing of FSNs reduced spontaneous licking movement, suggesting that FSNs contribute to the initiation and execution of specific spontaneous movements, possibly by sculpting response selectivity of nearby PNs., (Copyright © 2023 Giordano, Alia et al.)

Objective. Syntax involves complex neurobiological mechanisms, which are difficult to disentangle for multiple reasons. Using a protocol able to separate syntactic information from sound information we investigated the neural causal connections evoked by the processing of homophonous phrases, i.e. with the same acoustic information but with different syntactic content. These could be either verb phrases (VP) or noun phrases. Approach . We used event-related causality from stereo-electroencephalographic recordings in ten epileptic patients in multiple cortical and subcortical areas, including language areas and their homologous in the non-dominant hemisphere. The recordings were made while the subjects were listening to the homophonous phrases. Main results. We identified the different networks involved in the processing of these syntactic operations (faster in the dominant hemisphere) showing that VPs engage a wider cortical and subcortical network. We also present a proof-of-concept for the decoding of the syntactic category of a perceived phrase based on causality measures. Significance . Our findings help unravel the neural correlates of syntactic elaboration and show how a decoding based on multiple cortical and subcortical areas could contribute to the development of speech prostheses for speech impairment mitigation., (Creative Commons Attribution license.)

Objective. Powered lower-limb prostheses relying on decoding motor intentions from non-invasive sensors, like electromyographic (EMG) signals, can significantly improve the quality of life of amputee subjects. However, the optimal combination of high decoding performance and minimal set-up burden is yet to be determined. Here we propose an efficient decoding approach obtaining high decoding performance by observing only a fraction of the gait duration with a limited number of recording sites. Approach. Thirteen transfemoral amputee subjects performed five motor tasks while recording EMG signals from four muscles and inertial signals from the prosthesis. A support-vector-machine-based algorithm decoded the gait modality selected by the patient from a finite set. We investigated the trade-off between the robustness of the classifier's accuracy and the minimization of (i) the duration of the observation window, (ii) the number of EMG recording sites, (iii) the computational load of the procedure, measured the complexity of the algorithm. Main results. When including pre-foot-strike data in the decoding, the combination of three EMG recording sites and the inertial signals led to correct rates above 94% at the 20% of the gait cycle, showing the best trade-off between invasiveness of the setup and accuracy of the classifier. The complexity of the algorithm proved to be significantly higher when applying a polynomial kernel compared to a linear one, while the correct rate of the classifier generally showed no differences between the two approaches. The proposed algorithm led to high performance with a minimal EMG set-up and using only a fraction of the gait duration. Significance . These results pave the way for efficient control of powered lower-limb prostheses with minimal set-up burden and a rapid classification output., (© 2023 IOP Publishing Ltd.)

Young children and adults process spatial information differently: the former use their bodies as primary reference, while adults seem capable of using abstract frames. The transition is estimated to occur between the 6th and the 12th year of age. The mechanisms underlying spatial encoding in children and adults are unclear, as well as those underlying the transition. Here, we investigated the role of the subjective straight-ahead (SSA), the body antero-posterior half-plane mental model, in spatial encoding before and after the expected transition. We tested 6-7-year-old and 10-11-year-old children, and adults on a spatial alignment task in virtual reality, searching for differences in performance when targets were placed frontally or sideways. The performance differences were assessed both in a naturalistic baseline condition and in a test condition that discouraged using body-centered coordinates through a head-related visuo-motor conflict. We found no differences in the baseline condition, while all groups showed differences between central and lateral targets (SSA effect) in the visuo-motor conflict condition, and 6-7-year-old children showed the largest effect. These results confirm the expected transition timing; moreover, they suggest that children can abstract from the body using their SSA and that the transition underlies the maturation of a world-centered reference frame., (© 2023. The Author(s).)

Objective. The optic nerve is a good location for a visual neuroprosthesis. It can be targeted when a subject cannot receive a retinal prosthesis and it is less invasive than a cortical implant. The effectiveness of an electrical neuroprosthesis depends on the combination of the stimulation parameters which must be optimized, and an optimization strategy might be performing closed-loop stimulation using the evoked cortical response as feedback. However, it is necessary to identify target cortical activation patterns and to associate the cortical activity with the visual stimuli present in the visual field of the subjects. Visual stimuli decoding should be performed on large areas of the visual cortex, and with a method as translational as possible to shift the study to human subjects in the future. The aim of this work is to develop an algorithm that meets these requirements and can be leveraged to automatically associate a cortical activation pattern with the visual stimulus that generated it. Approach. Three mice were presented with ten different visual stimuli, and their primary visual cortex response was recorded using wide-field calcium imaging. Our decoding algorithm relies on a convolutional neural network (CNN), trained to classify the visual stimuli from the correspondent wide-field images. Several experiments were performed to identify the best training strategy and investigate the possibility of generalization. Main results. The best classification accuracy was 75.38% ± 4.77%, obtained pre-training the CNN on the MNIST digits dataset and fine-tuning it on our dataset. Generalization was possible pre-training the CNN to classify Mouse 1 dataset and fine-tuning it on Mouse 2 and Mouse 3, with accuracies of 64.14% ± 10.81% and 51.53% ± 6.48% respectively. Significance. The combination of wide-field calcium imaging and CNNs can be used to classify the cortical responses to simple visual stimuli and might be a viable alternative to existing decoding methodologies. It also allows us to consider the cortical activation as reliable feedback in future optic nerve stimulation experiments., (Creative Commons Attribution license.)

Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by the user as belonging to their own body. Robotic limbs can convey information about the environment with higher precision than biological limbs, but their actual performance is substantially limited by current technologies for the interfacing of the robotic devices with the body and for transferring motor and sensory information bidirectionally between the prosthesis and the user. In this Perspective, we argue that direct skeletal attachment of bionic devices via osseointegration, the amplification of neural signals by targeted muscle innervation, improved prosthesis control via implanted muscle sensors and advanced algorithms, and the provision of sensory feedback by means of electrodes implanted in peripheral nerves, should all be leveraged towards the creation of a new generation of high-performance bionic limbs. These technologies have been clinically tested in humans, and alongside mechanical redesigns and adequate rehabilitation training should facilitate the wider clinical use of bionic limbs., (© 2021. Springer Nature Limited.)

The epileptic brain is the result of a sequence of events transforming normal neuronal populations into hyperexcitable networks supporting recurrent seizure generation. These modifications are known to induce fundamental alterations of circuit function and, ultimately, of behavior. However, how hyperexcitability affects information processing in cortical sensory circuits is not yet fully understood. Here, we investigated interlaminar alterations in sensory processing of the visual cortex in a mouse model of focal epilepsy. We found three main circuit dynamics alterations in epileptic mice: (i) a spreading of visual contrast-driven gamma modulation across layers, (ii) an increase in firing rate that is layer-unspecific for excitatory units and localized in infragranular layers for inhibitory neurons, and (iii) a strong and contrast-dependent locking of firing units to network activity. Altogether, our data show that epileptic circuits display a functional disruption of layer-specific organization of visual sensory processing, which could account for visual dysfunction observed in epileptic subjects. Understanding these mechanisms paves the way to circuital therapeutic interventions for epilepsy., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The brain is an ultra-soft viscoelastic matrix. Sub-kPa hydrogels match the brain's mechanical properties but are challenging to manipulate in an implantable format. We propose a simple fabrication and processing sequence, consisting of de-hydration, patterning, implantation, and re-hydration steps, to deliver brain-like hydrogel implants into the nervous tissue. We monitored in real-time the ultra-soft hydrogel re-swelling kinetics in vivo using microcomputed tomography, achieved by embedding gold nanoparticles inside the hydrogel for contrast enhancement. We found that re-swelling in vivo strongly depends on the implant geometry and water availability at the hydrogel-tissue interface. Buckling of the implant inside the brain occurs when the soft implant is tethered to the cranium. Finite-element and analytical models reveal how the shank geometry, modulus and anchoring govern in vivo buckling. Taken together, these considerations on re-swelling kinetics of hydrogel constructs, implant geometry and soft implant-tissue mechanical interplay can guide the engineering of biomimetic brain implants., Competing Interests: Declaration of competing interest The authors declare no competing interest., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective . This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach . EEG recordings of 17 healthy controls (HCs), 56 subjective cognitive decline (SCD) and 45 mild cognitive impairment (MCI) subjects were acquired at resting state. After preprocessing, we selected sections corresponding to eyes-closed condition. Five different datasets were created by extracting delta, theta, alpha, beta and delta-to-theta frequency bands using bandpass filters. To classify SCD vs MCI and HC vs SCD vs MCI, we propose a framework based on the transformer architecture, which uses multi-head attention to focus on the most relevant parts of the input signals. We trained and validated the model on each dataset with a leave-one-subject-out cross-validation approach, splitting the signals into 10 s epochs. Subjects were assigned to the same class as the majority of their epochs. Classification performances of the transformer were assessed for both epochs and subjects and compared with other DL models. Main results . Results showed that the delta dataset allowed our model to achieve the best performances for the discrimination of SCD and MCI, reaching an Area Under the ROC Curve (AUC) of 0.807, while the highest results for the HC vs SCD vs MCI classification were obtained on alpha and theta with a micro-AUC higher than 0.74. Significance . We demonstrated that DL approaches can support the adoption of non-invasive and economic techniques as EEG to stratify patients in the clinical population at risk for AD. This result was achieved since the attention mechanism was able to learn temporal dependencies of the signal, focusing on the most discriminative patterns, achieving state-of-the-art results by using a deep model of reduced complexity. Our results were consistent with clinical evidence that changes in brain activity are progressive when considering early stages of AD., (Creative Commons Attribution license.)

Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

In recent years, our group and others have reported multiple cases of consistent neurological recovery in people with spinal cord injury (SCI) following a protocol that integrates locomotion training with brain machine interfaces (BMI). The primary objective of this pilot study was to compare the neurological outcomes (motor, tactile, nociception, proprioception, and vibration) in both an intensive assisted locomotion training (LOC) and a neurorehabilitation protocol integrating assisted locomotion with a noninvasive brain-machine interface (L + BMI), virtual reality, and tactile feedback. We also investigated whether individuals with chronic-complete SCI could learn to perform leg motor imagery. We ran a parallel two-arm randomized pilot study; the experiments took place in São Paulo, Brazil. Eight adults sensorimotor-complete (AIS A) (all male) with chronic (> 6 months) traumatic spinal SCI participated in the protocol that was organized in two blocks of 14 weeks of training and an 8-week follow-up. The participants were allocated to either the LOC group (n = 4) or L + BMI group (n = 4) using block randomization (blinded outcome assessment). We show three important results: (i) locomotion training alone can induce some level of neurological recovery in sensorimotor-complete SCI, and (ii) the recovery rate is enhanced when such locomotion training is associated with BMI and tactile feedback (∆Mean Lower Extremity Motor score improvement for LOC =  + 2.5, L + B =  + 3.5; ∆Pinprick score: LOC =  + 3.75, L + B =  + 4.75 and ∆Tactile score LOC =  + 4.75, L + B =  + 9.5). (iii) Furthermore, we report that the BMI classifier accuracy was significantly above the chance level for all participants in L + B group. Our study shows potential for sensory and motor improvement in individuals with chronic complete SCI following a protocol with BMIs and locomotion therapy. We report no dropouts nor adverse events in both subgroups participating in the study, opening the possibility for a more definitive clinical trial with a larger cohort of people with SCI.Trial registration: http://www.ensaiosclinicos.gov.br/ identifier RBR-2pb8gq., (© 2022. The Author(s).)

Task-specific training constitutes a core element for evidence-based rehabilitation strategies targeted at improving upper extremity activity after stroke. Its combination with additional treatment strategies and neurotechnology-based solutions could further improve patients' outcomes. Here, we studied the effect of gamified robot-assisted upper limb motor training on motor performance, skill learning, and transfer with respect to a non-gamified control condition with a group of chronic stroke survivors. The results suggest that a gamified training strategy results in more controlled motor performance during the training phase, which is characterized by a higher accuracy (lower deviance), higher smoothness (lower jerk), but slower speed. The responder analyses indicated that mildly impaired patients benefited most from the gamification approach. In conclusion, gamified robot-assisted motor training, which is personalized to the individual capabilities of a patient, constitutes a promising investigational strategy for further improving motor performance after a stroke., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)

Despite recent improvements, complete motor recovery occurs in <15% of stroke patients. To improve the therapeutic outcomes, there is a strong need to tailor treatments to each individual patient. However, there is a lack of knowledge concerning the precise neuronal mechanisms underlying the degree and course of motor recovery and its individual differences, especially in the view of brain network properties despite the fact that it became more and more clear that stroke is a network disorder. The TiMeS project is a longitudinal exploratory study aiming at characterizing stroke phenotypes of a large, representative stroke cohort through an extensive, multi-modal and multi-domain evaluation. The ultimate goal of the study is to identify prognostic biomarkers allowing to predict the individual degree and course of motor recovery and its underlying neuronal mechanisms paving the way for novel interventions and treatment stratification for the individual patients. A total of up to 100 patients will be assessed at 4 timepoints over the first year after the stroke: during the first (T1) and third (T2) week, then three (T3) and twelve (T4) months after stroke onset. To assess underlying mechanisms of recovery with a focus on network analyses and brain connectivity, we will apply synergistic state-of-the-art systems neuroscience methods including functional, diffusion, and structural magnetic resonance imaging (MRI), and electrophysiological evaluation based on transcranial magnetic stimulation (TMS) coupled with electroencephalography (EEG) and electromyography (EMG). In addition, an extensive, multi-domain neuropsychological evaluation will be performed at each timepoint, covering all sensorimotor and cognitive domains. This project will significantly add to the understanding of underlying mechanisms of motor recovery with a strong focus on the interactions between the motor and other cognitive domains and multimodal network analyses. The population-based, multi-dimensional dataset will serve as a basis to develop biomarkers to predict outcome and promote personalized stratification toward individually tailored treatment concepts using neuro-technologies, thus paving the way toward personalized precision medicine approaches in stroke rehabilitation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Fleury, Koch, Wessel, Bonvin, San Millan, Constantin, Vuadens, Adolphsen, Cadic Melchior, Brügger, Beanato, Ceroni, Menoud, De Leon Rodriguez, Zufferey, Meyer, Egger, Harquel, Popa, Raffin, Girard, Thiran, Vaney, Alvarez, Turlan, Mühl, Léger, Morishita, Micera, Blanke, Van De Ville and Hummel.)

The continuous stream of multisensory information between the brain and the body during body-environment interactions is crucial to maintain the updated representation of the perceived dimensions of body parts (metric body representation) and the space around the body (the peripersonal space). Such flow of multisensory signals is often limited by upper limb sensorimotor deficits after stroke. This would suggest the presence of systematic distortions of metric body representation and peripersonal space in chronic patients with persistent sensorimotor deficits. We assessed metric body representation and peripersonal space representation in 60 chronic stroke patients with unilateral upper limb motor deficits, in comparison with age-matched healthy controls. We also administered a questionnaire capturing explicit feelings towards the affected limb. These novel measures were analysed with respect to patients' clinical profiles and brain lesions to investigate the neural and functional origin of putative deficits. Stroke patients showed distortions in metric body representation of the affected limb, characterized by an underestimation of the arm length and an alteration of the arm global shape. A descriptive lesion analysis (subtraction analysis) suggests that these distortions may be more frequently associated with lesions involving the superior corona radiata and the superior frontal gyrus. Peripersonal space representation was also altered, with reduced multisensory facilitation for stimuli presented around the affected limb. These deficits were more common in patients reporting pain during motion. Explorative lesion analyses (subtraction analysis, disconnection maps) suggest that the peripersonal space distortions would be more frequently associated with lesions involving the parietal operculum and white matter frontoparietal connections. Moreover, patients reported altered feelings towards the affected limb, which were associated with right brain damage, proprioceptive deficits and a lower cognitive profile. These results reveal implicit and explicit distortions involving metric body representation, peripersonal space representation and the perception of the affected limb in chronic stroke patients. These findings might have important clinical implications for the longitudinal monitoring and the treatments of often-neglected deficits in body perception and representation., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Objective. Intrafascicular peripheral nerve implants are key components in the development of bidirectional neuroprostheses such as touch-enabled bionic limbs for amputees. However, the durability of such interfaces is hindered by the immune response following the implantation. Among the causes linked to such reaction, the mechanical mismatch between host nerve and implant is thought to play a decisive role, especially in chronic settings. Approach. Here we focus on modeling mechanical stresses induced on the peripheral nerve by the implant's micromotion using finite element analysis. Through multiple parametric sweeps, we analyze the role of the implant's material, geometry (aspect-ratio and shape), and surface coating, deriving a set of parameters for the design of better-integrated implants. Main results. Our results indicate that peripheral nerve implants should be designed and manufactured with smooth edges, using materials at most three orders of magnitude stiffer than the nerve, and with innovative geometries to redistribute micromotion-associated loads to less delicate parts of the nerve such as the epineurium. Significance. Overall, our model is a useful tool for the peripheral nerve implant designer that is mindful of the importance of implant mechanics for long term applications., (Creative Commons Attribution license.)

Functional magnetic resonance imaging (fMRI) has been widely employed to study stroke pathophysiology. In particular, analyses of fMRI signals at rest were directed at quantifying the impact of stroke on spatial features of brain networks. However, brain networks have intrinsic time features that were, so far, disregarded in these analyses. In consequence, standard fMRI analysis failed to capture temporal imbalance resulting from stroke lesions, hence restricting their ability to reveal the interdependent pathological changes in structural and temporal network features following stroke. Here, we longitudinally analyzed hemodynamic-informed transient activity in a large cohort of stroke patients (n = 103) to assess spatial and temporal changes of brain networks after stroke. Metrics extracted from the hemodynamic-informed transient activity were replicable within- and between-individuals in healthy participants, hence supporting their robustness and their clinical applicability. While large-scale spatial patterns of brain networks were preserved after stroke, their durations were altered, with stroke subjects exhibiting a varied pattern of longer and shorter network activations compared to healthy individuals. Specifically, patients showed a longer duration in the lateral precentral gyrus and anterior cingulum, and a shorter duration in the occipital lobe and in the cerebellum. These temporal alterations were associated with white matter damage in projection and association pathways. Furthermore, they were tied to deficits in specific behavioral domains as restoration of healthy brain dynamics paralleled recovery of cognitive functions (attention, language and spatial memory), but was not significantly correlated to motor recovery. These findings underscore the critical importance of network temporal properties in dissecting the pathophysiology of brain changes after stroke, thus shedding new light on the clinical potential of time-resolved methods for fMRI analysis., Competing Interests: Declaration of competing Interests The authors declare no competing interests., (Copyright © 2022. Published by Elsevier Inc.)

Effective, patient-tailored rehabilitation to restore upper-limb motor function in severely impaired stroke patients is still missing. If suitably combined and administered in a personalized fashion, neurotechnologies offer a large potential to assist rehabilitative therapies to enhance individual treatment effects. AVANCER (clinicaltrials.gov NCT04448483) is a two-center proof-of-concept trial with an individual based cumulative longitudinal intervention design aiming at reducing upper-limb motor impairment in severely affected stroke patients with the help of multiple neurotechnologies. AVANCER will determine feasibility, safety, and effectivity of this innovative intervention. Thirty chronic stroke patients with a Fugl-Meyer assessment of the upper limb (FM-UE) <20 will be recruited at two centers. All patients will undergo the cumulative personalized intervention within two phases: the first uses an EEG-based brain-computer interface to trigger a variety of patient-tailored movements supported by multi-channel functional electrical stimulation in combination with a hand exoskeleton. This phase will be continued until patients do not improve anymore according to a quantitative threshold based on the FM-UE. The second interventional phase will add non-invasive brain stimulation by means of anodal transcranial direct current stimulation to the motor cortex to the initial approach. Each phase will last for a minimum of 11 sessions. Clinical and multimodal assessments are longitudinally acquired, before the first interventional phase, at the switch to the second interventional phase and at the end of the second interventional phase. The primary outcome measure is the 66-point FM-UE, a significant improvement of at least four points is hypothesized and considered clinically relevant. Several clinical and system neuroscience secondary outcome measures are additionally evaluated. AVANCER aims to provide evidence for a safe, effective, personalized, adjuvant treatment for patients with severe upper-extremity impairment for whom to date there is no efficient treatment available., Competing Interests: MC and AE is employed by the Wyss Center acting as the sponsor of this study. MC is employed by confinis AG. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bigoni, Zandvliet, Beanato, Crema, Coscia, Espinosa, Henneken, Hervé, Oflar, Evangelista, Morishita, Wessel, Bonvin, Turlan, Birbaumer and Hummel.)

Functional magnetic resonance imaging (fMRI) has revolutionized the investigation of brain function. Similar approaches can be translated to probe spinal mechanisms. However, imaging the spinal cord remains challenging, notably due to its size and location. Technological advances are gradually tackling these issues, though there is yet no consensus on optimal acquisition protocols. In this study, we assessed the performance of three sequences during a simple motor task and at rest, in 15 healthy humans. Building upon recent literature, we selected three imaging protocols: a sequence integrating outer volume suppression (OVS) and two sequences implementing inner field-of-view imaging (ZOOMit) with different spatial and temporal resolutions. Images acquired using the OVS sequence appeared more prone to breathing-induced signal fluctuations, though they exhibited a higher temporal signal-to-noise ratio than ZOOMit sequences. Conversely, the spatial signal-to-noise ratio was higher for the two ZOOMit schemes. In spite of these differences in signal properties, all sequences yielded comparable performance in detecting group-level task-related activity, observed in the expected spinal levels. Nevertheless, our results suggest a superior sensitivity and robustness of patterns imaged using the OVS acquisition scheme. To analyze the data acquired at rest, we deployed a dynamic functional connectivity framework, SpiCiCAP, and we evaluated the ability of the three acquisition schemes to disentangle intrinsic spinal signals. We demonstrated that meaningful subdivisions of the spinal cord's functional architecture could be uncovered for all three sequences, with similar spatio-temporal properties across acquisition parameters. Cleaner and more stable components were, however, obtained using ZOOMit sequences. This study emphasizes the potential of fMRI as a robust tool to image spinal activity in vivo and it highlights specificities and similarities of three acquisition methods. This represents a key step towards the establishment of standardized spinal cord fMRI protocols., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Numerous neurorehabilitative, neuroprosthetic, and repair interventions aim to address the consequences of upper limb impairments after neurological disorders. Although these therapies target widely different mechanisms, they share the common need for a preclinical platform that supports the development, assessment, and understanding of the therapy. Here, we introduce a neurorobotic platform for rats that meets these requirements. A four-degree-of-freedom end effector is interfaced with the rat's wrist, enabling unassisted to fully assisted execution of natural reaching and retrieval movements covering the entire body workspace. Multimodal recording capabilities permit precise quantification of upper limb movement recovery after spinal cord injury (SCI), which allowed us to uncover adaptations in corticospinal tract neuron dynamics underlying this recovery. Personalized movement assistance supported early neurorehabilitation that improved recovery after SCI. Last, the platform provided a well-controlled and practical environment to develop an implantable spinal cord neuroprosthesis that improved upper limb function after SCI.

Precise control of bionic limbs relies on robust decoding of motor commands from nerves or muscles signals and sensory feedback from artificial limbs to the nervous system by interfacing the afferent nerve pathways. Implantable devices for bidirectional communication with bionic limbs have been developed in parallel with research on physiological alterations caused by an amputation. In this perspective article, we question whether increasing our effort on bridging these technologies with a deeper understanding of amputation pathophysiology and human motor control may help to overcome pressing stalls in the next generation of bionic limbs., (Creative Commons Attribution license.)

Objective. Motor neuroprostheses require the identification of stimulation protocols that effectively produce desired movements. Manual search for these protocols can be very time-consuming and often leads to suboptimal solutions, as several stimulation parameters must be personalized for each subject for a variety of target motor functions. Here, we present an algorithm that efficiently tunes peripheral intraneural stimulation protocols to elicit functionally relevant distal limb movements. Approach. We developed the algorithm using Bayesian optimization (BO) with multi-output Gaussian Processes (GPs) and defined objective functions based on coordinated muscle recruitment. We applied the algorithm offline to data acquired in rats for walking control and in monkeys for hand grasping control and compared different GP models for these two systems. We then performed a preliminary online test in a monkey to experimentally validate the functionality of our method. Main results. Offline, optimal intraneural stimulation protocols for various target motor functions were rapidly identified in both experimental scenarios. Using the model that performed best, the algorithm converged to stimuli that evoked functionally consistent movements with an average number of actions equal to 20% of the search space size in both the rat and monkey animal models. Online, the algorithm quickly guided the observations to stimuli that elicited functional hand gestures, although more selective motor outputs could have been achieved by refining the objective function used. Significance. These results demonstrate that BO can reliably and efficiently automate the tuning of peripheral neurostimulation protocols, establishing a translational framework to configure peripheral motor neuroprostheses in clinical applications. The proposed method can also potentially be applied to optimize motor functions using other stimulation modalities., (Creative Commons Attribution license.)

Introduction/aims: The hand is a sophisticated tool which allows humans to interact with the external world mainly via the sense of touch. Previous evidences demonstrated that electrical stimulations of the nerve trunks governing the hand are able to restore touch perception in transradial amputees. The aim of this study was to evaluate the neurological correlates of restored perception by the evaluation of network characteristics of the brain connectome via EEG recordings in amputees utilizing a fully sensorized bionic hand., Methods: A 48-year-old female with a left wrist traumatic disarticulation incurred 23 years prior to the study was enrolled for 6 months, during which experimental sessions were randomized. The control group included 12 healthy subjects performing a similar protocol., Results: Results showed that in both amputee and control group, a trend of SW in delta and beta 1 is recognizable (Delta and Beta 1 opposite spread) selectively in the hemisphere contralateral to the stimulus., Discussion: Delta increases (less orderly network) while Beta 1 decreases (more ordered network). It could be seen as a sign of higher attention and concentration of subjects to understand the perception and this monolateral modulation is similar to the bilateral attention given to the mathematical task difficulty's increment., (© 2021. Fondazione Società Italiana di Neurologia.)

Restoring dexterous hand control is critical for people with paralysis. Approaches based on surface or intramuscular stimulation provide limited finger control, generate insufficient force to recover functional movements, and require numerous electrodes. Here, we show that intrafascicular peripheral electrodes could produce functional grasps and sustained forces in three monkeys. We designed an intrafascicular implantable electrode targeting the motor fibers of the median and radial nerves. Our interface selectively and reliably activated extrinsic and intrinsic hand muscles, generating multiple functional grips, hand opening, and sustained contraction forces for up to 2 months. We extended those results to a behaving monkey with transient hand paralysis and used intracortical signals to control simple stimulation protocols that enabled this animal to perform a functional grasping task. Our findings show that just two intrafascicular electrodes can generate a rich portfolio of dexterous and functional hand movements with important implications for clinical applicability.

Objective. Stereo-electroencephalography (SEEG) has recently gained importance in analyzing brain functions. Its high temporal resolution and spatial specificity make it a powerful tool to investigate the strength, direction, and spectral content of brain networks interactions, especially when these connections are stimulus-evoked. However, choosing the best approach to evaluate the flow of information is not trivial, due to the lack of validated methods explicitly designed for SEEG. Approach. We propose a novel non-parametric statistical test for event-related causality (ERC) assessment on SEEG recordings. Here, we refer to the ERC as the causality evoked by a particular part of the stimulus (a response window (RW)). We also present a data surrogation method to evaluate the performance of a causality estimation algorithm. We finally validated our pipeline using surrogate SEEG data derived from an experimentally collected dataset, and compared the most used and successful measures to estimate effective connectivity, belonging to the Geweke-Granger causality framework. Main results. Here we show that our workflow correctly identified all the directed connections in the RW of the surrogate data and prove the robustness of the procedure against synthetic noise with amplitude exceeding physiological-plausible values. Among the causality measures tested, partial directed coherence performed best. Significance. This is the first non-parametric statistical test for ERC estimation explicitly designed for SEEG datasets. The pipeline, in principle, can also be applied to the analysis of any type of time-varying estimator, if there exists a clearly defined RW., (Creative Commons Attribution license.)

The acquisition of postural control is an elaborate process, which relies on the balanced integration of multisensory inputs. Current models suggest that young children rely on an 'en-block' control of their upper body before sequentially acquiring a segmental control around the age of 7, and that they resort to the former strategy under challenging conditions. While recent works suggest that a virtual sensory environment alters visuomotor integration in healthy adults, little is known about the effects on younger individuals. Here we show that this default coordination pattern is disrupted by an immersive virtual reality framework where a steering role is assigned to the trunk, which causes 6- to 8-year-olds to employ an ill-adapted segmental strategy. These results provide an alternate trajectory of motor development and emphasize the immaturity of postural control at these ages., (© 2021. The Author(s).)