Characterization of Machine Learning-Based Surrogate Models of Neural Activation Under Electrical Stimulation.

Electrical stimulation of peripheral nerves via implanted electrodes has been shown to be a promising approach to restore sensation, movement, and autonomic functions across a wide range of illnesses and injuries. While in principle computational models of neuromodulation can allow the exploration of large parameter spaces and the automatic optimization of stimulation devices and strategies, their high time complexity hinders their use on a large scale. We recently proposed the use of machine learning-based surrogate models to estimate the activation of nerve fibers under electrical stimulation, producing a considerable speed-up with respect to biophysically accurate models of fiber excitation while retaining good predictivity.

A computational model to design wide field-of-view optic nerve neuroprostheses.

Retinal stimulation (RS) allows restoring vision in blind patients, but it covers only a narrow region of the visual field. Optic nerve stimulation (ONS) has the potential to produce visual perceptions spanning the whole visual field, but it produces very irregular phosphenes. We introduced a geometrical model converting retinal and optic nerve firing rates into visual perceptions and vice versa and a method to estimate the best perceptions elicitable through an electrode configuration.

Combining external physical stimuli and nanostructured materials for upregulating pro-regenerative cellular pathways in peripheral nerve repair.

Peripheral nerve repair remains a major clinical challenge, particularly in the pursuit of therapeutic approaches that ensure adequate recovery of patient's activity of daily living. Autografts are the gold standard in clinical practice for restoring lost sensorimotor functions nowadays. However, autografts have notable drawbacks, including dimensional mismatches and the need to sacrifice one function to restore another.

Wide-angle simulated artificial vision enhances spatial navigation and object interaction in a naturalistic environment.

. Vision restoration approaches, such as prosthetics and optogenetics, provide visual perception to blind individuals in clinical settings. Yet their effectiveness in daily life remains a challenge.

Immersive VR for upper-extremity rehabilitation in patients with neurological disorders: a scoping review.

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.

Beyond the limiting gap length: peripheral nerve regeneration through implantable nerve guidance conduits.

Peripheral nerve damage results in the loss of sensorimotor and autonomic functions, which is a significant burden to patients. Furthermore, nerve injuries greater than the limiting gap length require surgical repair. Although autografts are the preferred clinical choice, their usage is impeded by their limited availability, dimensional mismatch, and the sacrifice of another functional donor nerve.

An actor-model framework for visual sensory encoding.

A fundamental challenge in neuroengineering is determining a proper artificial input to a sensory system that yields the desired perception. In neuroprosthetics, this process is known as artificial sensory encoding, and it holds a crucial role in prosthetic devices restoring sensory perception in individuals with disabilities. For example, in visual prostheses, one key aspect of artificial image encoding is to downsample images captured by a camera to a size matching the number of inputs and resolution of the prosthesis.

Swine Pudendal Nerve as a Model for Neuromodulation Studies to Restore Lower Urinary Tract Dysfunction.

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.

Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients.

Background: Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanisms depend on the time after stroke is yet to be assessed.

Aim: We investigated the response to an intensive protocol of robot-assisted rehabilitation in sub-acute and chronic stroke patients, by analyzing the underlying changes in clinical scores, electroencephalography (EEG) and end-effector kinematics.

Predicting party switching through machine learning and open data.

Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such prediction.

Early decoding of walking tasks with minimal set of EMG channels.

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.

The role of the visual field size in artificial vision.

. Artificial vision has been and still is the subject of intense research. The ultimate goal is to help blind people in their daily life.

Conformable neural interface based on off-stoichiometry thiol-ene-epoxy thermosets.

Off-stoichiometry thiol-ene-epoxy (OSTE+) thermosets show low permeability to gases and little absorption of dissolved molecules, allow direct low-temperature dry bonding without surface treatments, have a low Young's modulus, and can be manufactured via UV polymerisation. For these reasons, OSTE+ thermosets have recently gained attention for the rapid prototyping of microfluidic chips. Moreover, their compatibility with standard clean-room processes and outstanding mechanical properties make OSTE+ an excellent candidate as a novel material for neural implants.

Wearable High-Density MXene-Bioelectronics for Neuromuscular Diagnostics, Rehabilitation, and Assistive Technologies.

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 C T .

A method to establish functional vagus nerve topography from electro-neurographic spontaneous activity.

Bioelectronic medicine is an emerging approach to treat many types of diseases via electrical stimulation of the autonomic nervous system (ANS). Because the vagus nerve (VN) is one of the most important nerves controlling several ANS functions, stimulation protocols based on knowledge of the functional organization of the VN are particularly interesting. Here, we proposed a method to localize different physiological VN functions by exploiting electro-neurographic signals recorded during spontaneous VN fibers activity.

Neurocognitive and motor-control challenges for the realization of bionic augmentation.

Robotic fingers and arms that augment the motor abilities of non-disabled individuals are increasingly feasible yet face neurocognitive barriers and hurdles in efferent motor control.

A lightweight learning-based decoding algorithm for intraneural vagus nerve activity classification in pigs.

Bioelectronic medicine is an emerging field that aims at developing closed-loop neuromodulation protocols for the autonomic nervous system (ANS) to treat a wide range of disorders. When designing a closed-loop protocol for real time modulation of the ANS, the computational execution time and the memory and power demands of the decoding step are important factors to consider. In the context of cardiovascular and respiratory diseases, these requirements may partially explain why closed-loop clinical neuromodulation protocols that adapt stimulation parameters on patient's clinical characteristics are currently missing.

POLYRETINA restores light responses in vivo in blind Göttingen minipigs.

Retinal prostheses hold the potential for artificial vision in blind people affected by incurable diseases of the outer retinal layer. Available technologies provide only a small field of view: a significant limitation for totally blind people. To overcome this problem, we recently proposed a large and high-density photovoltaic epiretinal device, known as POLYRETINA.

A modular strategy for next-generation upper-limb sensory-motor neuroprostheses.

Neuroprosthetics is a discipline that aims at restoring lost functions to people affected by a variety of neurological disorders or neurotraumatic lesions. It combines the expertise of computer science and electrical, mechanical, and micro/nanotechnology with cellular, molecular, and systems neuroscience. Rapid breakthroughs in the field during the past decade have brought the hope that neuroprostheses can soon become a clinical reality, in particular-as we will detail in this review-for the restoration of hand functions.

Three-dimensional multilayer concentric bipolar electrodes restrict spatial activation in optic nerve stimulation.

Intraneural nerve interfaces often operate in a monopolar configuration with a common and distant ground electrode. This configuration leads to a wide spreading of the electric field. Therefore, this approach is suboptimal for intraneural nerve interfaces when selective stimulation is required.

Preclinical upper limb neurorobotic platform to assess, rehabilitate, and develop therapies.

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.