An Investigation of Manifold-Based Direct Control for a Brain-to-Body Neural Bypass.

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.

Implementation of an epicardial implantable MEMS sensor for continuous and real-time postoperative assessment of left ventricular activity in adult minipigs over a short- and long-term period.

The sensing of left ventricular (LV) activity is fundamental in the diagnosis and monitoring of cardiovascular health in high-risk patients after cardiac surgery to achieve better short- and long-term outcome. Conventional approaches rely on noninvasive measurements even if, in the latest years, invasive microelectromechanical systems (MEMS) sensors have emerged as a valuable approach for precise and continuous monitoring of cardiac activity. The main challenges in designing cardiac MEMS sensors are represented by miniaturization, biocompatibility, and long-term stability. Here, we present a MEMS piezoresistive cardiac sensor capable of continuous monitoring of LV activity over time following epicardial implantation with a pericardial patch graft in adult minipigs. In acute and chronic scenarios, the sensor was able to compute heart rate with a root mean square error lower than 2 BPM. Early after up to 1 month of implantation, the device was able to record the heart activity during the most important phases of the cardiac cycle (systole and diastole peaks). The sensor signal waveform, in addition, closely reflected the typical waveforms of pressure signal obtained via intraventricular catheters, offering a safer alternative to heart catheterization. Furthermore, histological analysis of the LV implantation site following sensor retrieval revealed no evidence of myocardial fibrosis. Our results suggest that the epicardial LV implantation of an MEMS sensor is a suitable and reliable approach for direct continuous monitoring of cardiac activity. This work envisions the use of this sensor as a cardiac sensing device in closed-loop applications for patients undergoing heart surgery.

Toward the Development of User-Centered Neurointegrated Lower Limb Prostheses.

The last few years witnessed radical improvements in lower-limb prostheses. Researchers have presented innovative solutions to overcome the limits of the first generation of prostheses, refining specific aspects which could be implemented in future prostheses designs. Each aspect of lower-limb prostheses has been upgraded, but despite these advances, a number of deficiencies remain and the most capable limb prostheses fall far short of the capabilities of the healthy limb. This article describes the current state of prosthesis technology; identifies a number of deficiencies across the spectrum of lower limb prosthetic components with respect to users' needs; and discusses research opportunities in design and control that would substantially improve functionality concerning each deficiency. In doing so, the authors present a roadmap of patients related issues that should be addressed in order to fulfill the vision of a next-generation, neurally-integrated, highly-functional lower limb prosthesis.

Cardiovascular response to closed-loop intraneural stimulation of the right vagus nerve: a proof-of-concept study.

Vagus nerve stimulation (VNS) is an FDA-approved technique for the neuromodulation of the autonomic nervous system. There are many therapeutic applications where VNS could be used as a therapy, such as cardiovascular diseases, epilepsy, depression, and inflammatory conditions. Cardiovascular applications are particularly relevant, since cardiovascular diseases are the top causes of death worldwide. VNS clinical trials have been performed in the last 15 years for the treatment of heart failure (HF), achieving controversial results. Typically VNS is applied with a cuff electrode placed around the nerve, in an open-loop or cardiac synchronized design. The effectiveness of this approach is hindered by the multifunctional nature of the VN, which is involved in a variety of homeostatic controls. When a high current is applied, adverse effects arise from the stimulation of undesired fibers. An alternative strategy is represented by intraneural stimulation, which can guarantee higher selectivity. Moreover, closed-loop modalities allow the delivery of electrical current inside the nerves only if needed, with a reduced risk of untargeted nerve activation and lower energy consumption. Here we propose a closed-loop intraneural stimulation of the right cervical VN in a clinically relevant animal model. The intraneural was designed according to the internal structure of the VN. A threshold-based closed-loop algorithm was developed using HR as a control variable to produce a chronotropic effect.Clinical Relevance-This work analyzes the closed-loop intraneural VNS for the treatment of cardiovascular disorders, and supports the possibility of developing fully implantable devices with a high degree of selectivity in stimulation and prolonged lifespan.

Neural Stimulation Hardware for the Selective Intrafascicular Modulation of the Vagus Nerve.

The neural stimulation of the vagus nerve is able to modulate various functions of the parasympathetic response in different organs. The stimulation of the vagus nerve is a promising approach to treating inflammatory diseases, obesity, diabetes, heart failure, and hypertension. The complexity of the vagus nerve requires highly selective stimulation, allowing the modulation of target-specific organs without side effects. Here, we address this issue by adapting a neural stimulator and developing an intraneural electrode for the particular modulation of the vagus nerve. The neurostimulator parameters such as amplitude, pulse width, and pulse shape were modulated. Single-, and multi-channel stimulation was performed at different amplitudes. For the first time, a polyimide thin-film neural electrode was designed for the specific stimulation of the vagus nerve. In vivo experiments were performed in the adult minipig to validate to elicit electrically evoked action potentials and to modulate physiological functions, validating the spatial selectivity of intraneural stimulation. Electrochemical tests of the electrode and the neurostimulator showed that the stimulation hardware was working correctly. Stimulating the porcine vagus nerve resulted in spatially selective modulation of the vagus nerve. ECAP belonging to alpha and beta fibers could be distinguished during single- and multi-channel stimulation. We have shown that the here presented system is able to activate the vagus nerve and can therefore modulate the heart rate, diastolic pressure, and systolic pressure. The here presented system may be used to restore the cardiac loop after denervation by implementing biomimetic stimulation patterns. Presented methods may be used to develop intraneural electrodes adapted for various applications.

Decoding bladder state from pudendal intraneural signals in pigs.

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.

EMG Data Augmentation for Grasp Classification Using Generative Adversarial Networks.

Electromyography (EMG) has been used as an interface for the control of robotic hands for decades but with the improvement of embedded electronics and decoding algorithms, many applications are now envisaged by companies. Deep learning has shown the possibility to increase decoding performance but it requires large amounts of data to show its full capabilities. However, recording such amounts of EMG signals face several issues since recording hours of data from patients is very time-consuming and can result in muscle fatigue. We explore a deep learning data augmentation strategy using generative adversarial networks (GANs) to create high-quality synthetic data to increase the performance of grasp classification.

Bidirectional bionic limbs: a perspective bridging technology and physiology.

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.

Bayesian optimization of peripheral intraneural stimulation protocols to evoke distal limb movements.

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.

Combining robotics with enhanced serotonin-driven cortical plasticity improves post-stroke motor recovery.

Despite recent progresses in robotic rehabilitation technologies, their efficacy for post-stroke motor recovery is still limited. Such limitations might stem from the insufficient enhancement of plasticity mechanisms, crucial for functional recovery. Here, we designed a clinically relevant strategy that combines robotic rehabilitation with chemogenetic stimulation of serotonin release to boost plasticity. These two approaches acted synergistically to enhance post-stroke motor performance. Indeed, mice treated with our combined therapy showed substantial functional gains that persisted beyond the treatment period and generalized to non-trained tasks. Motor recovery was associated with a reduction in electrophysiological and neuroanatomical markers of GABAergic neurotransmission, suggesting disinhibition in perilesional areas. To unveil the translational potentialities of our approach, we specifically targeted the serotonin 1A receptor by delivering Buspirone, a clinically approved drug, in stroke mice undergoing robotic rehabilitation. Administration of Buspirone restored motor impairments similarly to what observed with chemogenetic stimulation, showing the immediate translational potential of this combined approach to significantly improve motor recovery after stroke.

Cortical connectivity and spectral perturbations underlying TENS stimulation of hand nerves: a case study.

The major challenge in upper limbs neuroprosthetic improvement is the implementation of effective sensory feedback. Transcutaneous electrical nerve stimulation (TENS) of the median and ulnar nerves confirmed, with electroencephalographic (EEG) recordings, the presence of appropriate responses in relevant cortical areas with induced sensation successfully located in the innervation regions of each nerve. The characterization of these elicited responses could be used to recreate precise somatotopic feedback from hand protheses. Using TENS and EEG, the purpose of this study was to detect distinctions in time-frequency cortical dynamics and connectivity occurring after stimulation of hand nerves. Region of interest (ROI) were selected according to topographical distributions and Somatosensory Evoked Potentials (SEP) localization and were named Contralateral Parietal (Cont P), Central Frontal (Cent F) and Superior Parietal (Sup P). The analysis of cortical oscillations showed spectral inflections in theta [4-7 Hz] and alpha [7.5-12.5 Hz] band which occurred at 60 ms in Cont P and 300 ms in Sup P and prominent for the ulnar condition over the median one. The beta band decrease [16-30 Hz] which occurred in the same ROIs was especially significant after ulnar stimulation too. Effective connectivity measures did not differ significantly across conditions but exhibited some slight difference in the alpha-band causal flow coming from Cent F in direction to Cont P and Sup P. Although pending completion of multiple-subjects study, these results already suggest magnitude differences in somatosensory spectral fluctuations and sensorimotor interactions flows.

Direct activation of zebrafish neurons by ultrasonic stimulation revealed by whole CNS calcium imaging.

OBJECTIVE: Ultrasounds (US) use in neural engineering is so far mainly limited to ablation through high intensity focused ultrasound, but interesting preliminary results show that low intensity low frequency ultrasound could be used instead to modulate neural activity. However, the extent of this modulatory ability of US is still unclear, as in in vivo studies it is hard to disentangle the contribution to neural responses of direct activation of the neuron by US stimulation and indirect activation due either to sensory response to mechanical stimulation associated to US, or to propagation of activity from neighboring areas. Here, we aim to show how to separate the three effects and assess the presence of direct response to US stimulation in zebrafish. APPROACH: We observed in zebrafish larvae brain-wide US-induced activity patterns through calcium imaging microscopy. Sensory response to mechanical stimulation was assessed with a US shield. Activity propagation was assessed with inter-area latency evaluation. MAIN RESULTS: We prove that in selected brain regions the zebrafish's neural response is mainly due to direct activation, later spreading to the other regions. Shielding the neurons from direct US stimulation resulted in a significantly attenuated response, showing that sensory stimulation does not play a prominent role. SIGNIFICANCE: US non-invasive neuromodulatory approach might lead to novel ways to test and control neural activity, and hence to novel neuromodulatory therapies. Future studies will focus on the biophysical structure of directly responsive neurons to capture the mechanisms of US induced activity.

Cortical plasticity after hand prostheses use: Is the hypothesis of deafferented cortex "invasion" always true?

OBJECTIVE: To study motor cortex plasticity after a period of training with a new prototype of bidirectional hand prosthesis in three left trans-radial amputees, correlating these changes with the modification of Phantom Limb Pain (PLP) in the same period. METHODS: Each subject underwent a brain motor mapping with Transcranial Magnetic Stimulation (TMS) and PLP evaluation with questionnaires during a six-month training with a prototype of bidirectional hand prosthesis. RESULTS: The baseline motor maps showed in all three amputees a smaller area of muscles representation of the amputated side compared to the intact limb. After training, there was a partial reversal of the baseline asymmetry. The two subjects affected by PLP experienced a statistically significant reduction of pain. CONCLUSIONS: Two apparently opposite findings, the invasion of the "deafferented" cortex by neighbouring areas and the "persistence" of neural structures after amputation, could vary according to different target used for measurement. Our results do not support a correlation between PLP and motor cortical changes. SIGNIFICANCE: The selection of the target and of the task is essential for studies investigating motor brain plasticity. This study boosts against a direct and unique role of motor cortical changes on PLP genesis.

Characterization of multi-channel intraneural stimulation in transradial amputees.

Although peripheral nerve stimulation using intraneural electrodes has been shown to be an effective and reliable solution to restore sensory feedback after hand loss, there have been no reports on the characterization of multi-channel stimulation. A deeper understanding of how the simultaneous stimulation of multiple electrode channels affects the evoked sensations should help in improving the definition of encoding strategies for bidirectional prostheses. We characterized the sensations evoked by simultaneous stimulation of median and ulnar nerves (multi-channel configuration) in four transradial amputees who had been implanted with four TIMEs (Transverse Intrafascicular Multichannel Electrodes). The results were compared with the characterization of single-channel stimulation. The sensations were characterized in terms of location, extent, type, and intensity. Combining two or more single-channel configurations caused a linear combination of the sensation locations and types perceived with such single-channel stimulations. Interestingly, this was also true when two active sites from the same nerve were stimulated. When stimulating in multi-channel configuration, the charge needed from each electrode channel to evoke a sensation was significantly lower than the one needed in single-channel configuration (sensory facilitation). This result was also supported by electroencephalography (EEG) recordings during nerve stimulation. Somatosensory potentials evoked by multi-channel stimulation confirmed that sensations in the amputated hand were perceived by the subjects and that a perceptual sensory facilitation occurred. Our results should help the future development of more efficient bidirectional prostheses by providing guidelines for the development of more complex stimulation approaches to effectively restore multiple sensations at the same time.

A versatile robotic platform for the design of natural, three-dimensional reaching and grasping tasks in monkeys.

OBJECTIVE: Translational studies on motor control and neurological disorders require detailed monitoring of sensorimotor components of natural limb movements in relevant animal models. However, available experimental tools do not provide a sufficiently rich repertoire of behavioral signals. Here, we developed a robotic platform that enables the monitoring of kinematics, interaction forces, and neurophysiological signals during user-defined upper limb tasks for monkeys. APPROACH: We configured the platform to position instrumented objects in a three-dimensional workspace and provide an interactive dynamic force-field. MAIN RESULTS: We show the relevance of our platform for fundamental and translational studies with three example applications. First, we study the kinematics of natural grasp in response to variable interaction forces. We then show simultaneous and independent encoding of kinematic and forces in single unit intra-cortical recordings from sensorimotor cortical areas. Lastly, we demonstrate the relevance of our platform to develop clinically relevant brain computer interfaces in a kinematically unconstrained motor task. SIGNIFICANCE: Our versatile control structure does not depend on the specific robotic arm used and allows for the design and implementation of a variety of tasks that can support both fundamental and translational studies of motor control.

Optimal integration of intraneural somatosensory feedback with visual information: a single-case study.

Providing somatosensory feedback to amputees is a long-standing objective in prosthesis research. Recently, implantable neural interfaces have yielded promising results in this direction. There is now considerable evidence that the nervous system integrates redundant signals optimally, weighting each signal according to its reliability. One question of interest is whether artificial sensory feedback is combined with other sensory information in a natural manner. In this single-case study, we show that an amputee with a bidirectional prosthesis integrated artificial somatosensory feedback and blurred visual information in a statistically optimal fashion when estimating the size of a hand-held object. The patient controlled the opening and closing of the prosthetic hand through surface electromyography, and received intraneural stimulation proportional to the object's size in the ulnar nerve when closing the robotic hand on the object. The intraneural stimulation elicited a vibration sensation in the phantom hand that substituted the missing haptic feedback. This result indicates that sensory substitution based on intraneural feedback can be integrated with visual feedback and make way for a promising method to investigate multimodal integration processes.

External sensory-motor cues while managing unexpected slippages can violate the planar covariation law.

This study was aimed at investigating the intersegmental coordination of six older adults while managing unexpected slippages delivered during steady walking, and wearing an Active Pelvis Orthosis (APO). The APO was setup either to assist volunteers at the hip levels during balance loss or to be transparent. The Planar Covariation Law (PCL) of the lower limb elevation angles was the main tool used to assess the intersegmental coordination of both limbs (i.e., the perturbed and unperturbed ones). Results revealed that, after the onset of the perturbation, elevation angles of both limbs do not covary, a part from the robot-mediated assistance. These new evidences suggest that external sensory-motor cues can alter the temporal synchronization of elevation angles, thus violating the PCL.

Pre-impact detection algorithm to identify lack of balance due to tripping-like perturbations.

This study investigates the performance of an updated version of our pre-impact detection algorithm while parsing out hip kinematics in order to identify unexpected tripping-like perturbations during walking. This approach grounds on the hypothesis that due to unexpected gait disturbances, the cyclic features of hip kinematics are suddenly altered thus promptly highlighting that the balance is challenged. To achieve our goal, hip angles of eight healthy young subjects were recorded while they were managing unexpected tripping trials delivered during the steady locomotion. Results showed that the updated version of our pre-impact detection algorithm allows for identifying a lack of balance due to tripping-like perturbations, after a suitable tuning of the algorithm parameters. The best performance is represented by a mean detection time ranging within 0.8-0.9 s with a low percentage of false alarms (i.e., lower than 10%). Accordingly, we can conclude that the proposed strategy is able to detect lack of balance due to different kinds of gait disturbances (e.g., slippages, tripping) and that it could be easily implemented in lower limb orthoses/prostheses since it only relies on joint angles.

Evaluation of time-frequency features as detectors of lack of balance due to tripping-like perturbations.

Unbalancing events during gait can end up in falls and, thus, injury. Detecting events that could bring to fall and consequently activating fall prevention systems before the impact may help to mitigate related injuries. However, there is uncertainty about signals and methods that could offer the best performance. In this paper we investigated a novel trip detection method based on time-frequency features to evaluate the performances of these features as trip detectors. Hip angles of eight healthy young subjects were recorded while performing unexpected tripping trials delivered during steady locomotion. Then the Short-Time Fourier Transform (STFT) of the hip angle was estimated. Median frequency, power, centroidal frequency as well as frequency dispersion were computed for each time sliced power spectrum. These features were used as input for a trip detection algorithm. We assessed detection time (Tdetect), specificity (Spec) and sensitivity (Sens) for each feature. Performances obtained with median frequencies over time(Tdetect 0.91 ± 0.47 s; Sens 0.96) were better than those obtained using the hip angle signal in time domain (Tdetect 1.19 ± 0.27 s; Sens 0.83). Other features did not show significant results. Thus, median frequency over time expected to achieve effective real-time event detection systems, with the aim of a future on-board application concerning detection and prevention measures.

Comparison of linear frequency and amplitude modulation for intraneural sensory feedback in bidirectional hand prostheses.

Recent studies have shown that direct nerve stimulation can be used to provide sensory feedback to hand amputees. The intensity of the elicited sensations can be modulated using the amplitude or frequency of the injected stimuli. However, a comprehensive comparison of the effects of these two encoding strategies on the amputees' ability to control a prosthesis has not been performed. In this paper, we assessed the performance of two trans-radial amputees controlling a myoelectric hand prosthesis while receiving grip force sensory feedback encoded using either linear modulation of amplitude (LAM) or linear modulation of frequency (LFM) of direct nerve stimulation (namely, bidirectional prostheses). Both subjects achieved similar and significantly above-chance performance when they were asked to exploit LAM or LFM in different tasks. The feedbacks allowed them to discriminate, during manipulation through the robotic hand, objects of different compliances and shapes or different placements on the prosthesis. Similar high performances were obtained when they were asked to apply different levels of force in a random order on a dynamometer using LAM or LFM. In contrast, only the LAM strategy allowed the subjects to continuously modulate the grip pressure on the dynamometer. Furthermore, when long-lasting trains of stimulation were delivered, LFM strategy generated a very fast adaptation phenomenon in the subjects, which caused them to stop perceiving the restored sensations. Both encoding approaches were perceived as very different from the touch feelings of the healthy limb (natural). These results suggest that the choice of specific sensory feedback encodings can have an effect on user performance while grasping. In addition, our results invite the development of new approaches to provide more natural sensory feelings to the users, which could be addressed by a more biomimetic strategy in the future.