Quantitative Kinematic Characterization of Reaching Impairments in Mice After a Stroke

Background and Objective. Kinematic analysis of reaching movements is increasingly used to evaluate upper extremity function after cerebrovascular insults in humans and has also been applied to rodent models. Such analyses can require time-consuming frame-by-frame inspections and are affected by the experimenter's bias. In this study, we introduce a semi-automated algorithm for tracking forepaw movements in mice. This methodology allows us to calculate several kinematic measures for the quantitative assessment of performance in a skilled reaching task before and after a focal cortical stroke. Methods. Mice were trained to reach for food pellets with their preferred paw until asymptotic performance was achieved. Photothrombosis was then applied to induce a focal ischemic injury in the motor cortex, contralateral to the trained limb. Mice were tested again once a week for 30 days. A high frame rate camera was used to record the movements of the paw, which was painted with a nontoxic dye. An algorithm was then applied off-line to track the trajectories and to compute kinematic measures for motor performance evaluation. Results. The tracking algorithm proved to be fast, accurate, and robust. A number of kinematic measures were identified as sensitive indicators of poststroke modifications. Based on end-point measures, ischemic mice appeared to improve their motor performance after 2 weeks. However, kinematic analysis revealed the persistence of specific trajectory adjustments up to 30 days poststroke, indicating the use of compensatory strategies. Conclusions. These results support the use of kinematic analysis in mice as a tool for both detection of poststroke functional impairments and tracking of motor improvements following rehabilitation. Similar studies could be performed in parallel with human studies to exploit the translational value of this skilled reaching analysis

A machine learning framework to optimize optic nerve electrical stimulation for vision restoration

Optic nerve electrical stimulation is a promising technique to restore vision in blind subjects. Machine learning methods can be used to select effective stimulation protocols, but they require a model of the stimulated system to generate enough training data. Here, we use a convolutional neural network (CNN) as a model of the ventral visual stream. A genetic algorithm drives the activation of the units in a layer of the CNN representing a cortical region toward a desired pattern, by refining the activation imposed at a layer representing the optic nerve. To simulate the pattern of activation elicited by the sites of an electrode array, a simple point-source model was introduced and its optimization process was investigated for static and dynamic scenes. Psychophysical data confirm that our stimulation evolution framework produces results compatible with natural vision. Machine learning approaches could become a very powerful tool to optimize and personalize neuroprosthetic systems

Progress and challenges of implantable neural interfaces based on nature-derived materials

Neural interfaces are bioelectronic devices capable of stimulating a population of neurons or nerve fascicles and recording electrical signals in a specific area. Despite their success in restoring sensory-motor functions in people with disabilities, their long-term exploitation is still limited by poor biocompatibility, mechanical mismatch between the device and neural tissue and the risk of a chronic inflammatory response upon implantation. In this context, the use of nature-derived materials can help address these issues. Examples of these materials, such as extracellular matrix proteins, peptides, lipids and polysaccharides, have been employed for decades in biomedical science. Their excellent biocompatibility, biodegradability in the absence of toxic compound release, physiochemical properties that are similar to those of human tissues and reduced immunogenicity make them outstanding candidates to improve neural interface biocompatibility and long-term implantation safety. The objective of this review is to highlight progress and challenges concerning the impact of nature-derived materials on neural interface design. The use of these materials as biocompatible coatings and as building blocks of insulation materials for use in implantable neural interfaces is discussed. Moreover, future perspectives are presented to show the increasingly important uses of these materials for neural interface fabrication and their possible use for other applications in the framework of neural engineering

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. (C) 2019 Elsevier Ltd. All rights reserved

Polysaccharide Layer-by-Layer Coating for Polyimide-Based Neural Interfaces

: Implantable flexible neural interfaces (IfNIs) are capable of directly modulating signals of the central and peripheral nervous system by stimulating or recording the action potential. Despite outstanding results in acute experiments on animals and humans, their long-term biocompatibility is hampered by the effects of foreign body reactions that worsen electrical performance and cause tissue damage. We report on the fabrication of a polysaccharide nanostructured thin film as a coating of polyimide (PI)-based IfNIs. The layer-by-layer technique was used to coat the PI surface due to its versatility and ease of manufacturing. Two different LbL deposition techniques were tested and compared: dip coating and spin coating. Morphological and physiochemical characterization showed the presence of a very smooth and nanostructured thin film coating on the PI surface that remarkably enhanced surface hydrophilicity with respect to the bare PI surface for both the deposition techniques. However, spin coating offered more control over the fabrication properties, with the possibility to tune the coating's physiochemical and morphological properties. Overall, the proposed coating strategies allowed the deposition of a biocompatible nanostructured film onto the PI surface and could represent a valid tool to enhance long-term IfNI biocompatibility by improving tissue/electrode integration

Soft Embodiment for Engineering Artificial Limbs

We highlight two alternative, yet complementary, solutions for harnessing available neural resources for improving integration of artificial limbs (ALs) through embodiment. ‘Hard’ embodiment exploits neural and cognitive body mechanisms by closely mimicking their original biological functions. ‘Soft’ embodiment exploits these same mechanisms by recycling them to support a different function altogether

Polysaccharide Layer-by-Layer Coating for Polyimide-Based Neural Interfaces

Implantable flexible neural interfaces (IfNIs) are capable of directly modulating signals of the central and peripheral nervous system by stimulating or recording the action potential. Despite outstanding results in acute experiments on animals and humans, their long-term biocompatibility is hampered by the effects of foreign body reactions that worsen electrical performance and cause tissue damage. We report on the fabrication of a polysaccharide nanostructured thin film as a coating of polyimide (PI)-based IfNIs. The layer-by-layer technique was used to coat the PI surface due to its versatility and ease of manufacturing. Two different LbL deposition techniques were tested and compared: dip coating and spin coating. Morphological and physiochemical characterization showed the presence of a very smooth and nanostructured thin film coating on the PI surface that remarkably enhanced surface hydrophilicity with respect to the bare PI surface for both the deposition techniques. However, spin coating offered more control over the fabrication properties, with the possibility to tune the coating’s physiochemical and morphological properties. Overall, the proposed coating strategies allowed the deposition of a biocompatible nanostructured film onto the PI surface and could represent a valid tool to enhance long-term IfNI biocompatibility by improving tissue/electrode integration

Nanotopography induced contact guidance of the F11 cell line during neuronal differentiation: a neuronal model cell line for tissue scaffold development.

The F11 hybridoma, a dorsal root ganglion-derived cell line, was used to investigate the response of nociceptive sensory neurons to nanotopographical guidance cues. This established this cell line as a model of peripheral sensory neuron growth for tissue scaffold design. Cells were seeded on substrates of cyclic olefin copolymer (COC) films imprinted via nanoimprint lithography (NIL) with a grating pattern of nano-scale grooves and ridges. Different ridge widths were employed to alter the focal adhesion formation, thereby changing the cell/substrate interaction. Differentiation was stimulated with forskolin in culture medium consisting of either 1 or 10% fetal bovine serum (FBS). Per medium condition, similar neurite alignment was achieved over the four day period, with the 1% serum condition exhibiting longer, more aligned neurites. Immunostaining for focal adhesions found the 1% FBS condition to also have fewer, less developed focal adhesions. The robust response of the F11 to guidance cues further builds on the utility of this cell line as a sensory neuron model, representing a useful tool to explore the design of regenerative guidance tissue scaffolds

Wearable Robotics for Impaired Upper-Limb Assistance and Rehabilitation: State of the Art and Future Perspectives

Despite more than thirty-five years of research on wearable technologies to assist the upper-limb and a multitude of promising preliminary results, the goal of restoring pre-impairment quality of life of people with physical disabilities has not been fully reached yet. Whether it is for rehabilitation or for assistance, nowadays robotics is still only used in a few high-tech clinics and hospitals, limiting the access to a small amount of people. This work provides a description of the three major 'revolutions' occurred in the field (end-effector robots, rigid exoskeletons, and soft exosuits), reviewing forty-eight systems for the upper-limb (excluding hand-only devices) used in eighty-nine studies enrolling a clinical population before June 2022. The review critically discusses the state of the art, analyzes the different technologies, and compares the clinical outcomes, with the goal of determine new potential directions to follow

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. 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