The HTT gene influences plasma neurofilament light chain and brain metabolism in prodromal Alzheimer's disease.

Objective: HTT, encoding a protein involved in axonal trafficking, contains a key region of CAG repeats. When expanded beyond 39 repeats, this region leads to Huntington's disease (HD). However, several studies have suggested that increasing the number of CAG repeats below the pathological threshold may confer functional advantages by enhancing HTT activity.

Biophysical characterization of the recording of unmyelinated and myelinated fiber activity with peripheral interfaces.

Unmyelinated fibers account for a remarkable fraction of the peripheral nervous system and their activity is linked to many autonomic and somatic functions. While electrical recording of such activity from human-sized peripheral nerves holds significant potential for neuroengineering applications, it has been shown only in acute settings via microneurography. This leaves unclear whether current implantable electrodes could achieve the same outcome.

Millimetre-scale bioresorbable optoelectronic systems for electrotherapy.

Temporary pacemakers are essential for the care of patients with short-lived bradycardia in post-operative and other settings. Conventional devices require invasive open-heart surgery or less invasive endovascular surgery, both of which are challenging for paediatric and adult patients. Other complications include risks of infections, lacerations and perforations of the myocardium, and of displacements of external power supplies and control systems.

Low intensity trans-spinal focused ultrasound reduces mechanical sensitivity and suppresses spinal microglia activation in rats with chronic constriction injury.

Low intensity, trans-spinal focused ultrasound (tsFUS) is a noninvasive neuromodulation approach that has been shown to modulate spinal circuit excitability in healthy rats. Here, we evaluated the potential of tsFUS for alleviating neuropathic pain by testing it in a chronic constriction injury (CCI) model. Male rats underwent CCI of the left sciatic nerve and then received tsFUS (2 kHz pulse repetition frequency; 40% duty cycle) or sham stimulation, targeted at spinal segment level L5 for 3 min daily over three days.

Effect of Medication and Freezing of Gait on Rambling and Trembling in Quiet Standing in Individuals With Parkinson's Disease.

Background: Individuals with Parkinson's disease (PD) with freezing of gait (FoG) exhibit difficulty with changes in sensory input, indicating a potential sensorimotor integration deficit. Understanding how levodopa impacts balance particularly in FoG, is critical. As traditional postural sway measures may not fully capture the complexity of balance control, rambling and trembling decomposition of the center of pressure allows a more detailed assessment of postural control by distinguishing between supraspinal and spinal contributions, offering insights into sensorimotor integration deficits.

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 Novel and Accurate BiLSTM Configuration Controller for Modular Soft Robots with Module Number Adaptability.

Modular soft robots (MSRs) exhibit greater potential for sophisticated tasks compared with single-module robots. However, the modular structure incurs the complexity of accurate control and necessitates a control strategy specifically for modular robots. In this article, we introduce a data collection strategy tailored for MSR and a bidirectional long short-term memory (biLSTM) configuration controller capable of adapting to varying module numbers.

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.

Assessment of wearable robotics performance in patients with neurological conditions.

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.

Brain and grammar: revealing electrophysiological basic structures with competing statistical models.

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.

Dysphagia in primary progressive aphasia: Clinical predictors and neuroanatomical basis.

Background And Purpose: Dysphagia is an important feature of neurodegenerative diseases and potentially life-threatening in primary progressive aphasia (PPA) but remains poorly characterized in these syndromes. We hypothesized that dysphagia would be more prevalent in nonfluent/agrammatic variant (nfv)PPA than other PPA syndromes, predicted by accompanying motor features, and associated with atrophy affecting regions implicated in swallowing control.

Methods: In a retrospective case-control study at our tertiary referral centre, we recruited 56 patients with PPA (21 nfvPPA, 22 semantic variant [sv]PPA, 13 logopenic variant [lv]PPA).

Effect of disease, freezing of gait, and dopaminergic medication in the biomechanics of trunk and upper limbs in the gait of Parkinson's disease.

Introduction: Parkinson's disease (PD) causes gait abnormalities that may be associated with an arm swing reduction. Medication and freezing of gait (FoG) may influence gait characteristics. However, these comparisons do not consider differences in gait speed and clinical characteristics in individuals with PD.

FetalBrainAwareNet: Bridging GANs with anatomical insight for fetal ultrasound brain plane synthesis.

Over the past decade, deep-learning (DL) algorithms have become a promising tool to aid clinicians in identifying fetal head standard planes (FHSPs) during ultrasound (US) examination. However, the adoption of these algorithms in clinical settings is still hindered by the lack of large annotated datasets. To overcome this barrier, we introduce FetalBrainAwareNet, an innovative framework designed to synthesize anatomically accurate images of FHSPs.

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.

Organ Neuroprosthetics: Connecting Transplanted and Artificial Organs with the Nervous System.

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.

Stroke Recovery-Related Changes in Cortical Reactivity Based on Modulation of Intracortical Inhibition.

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.

On the use of contrastive learning for standard-plane classification in fetal ultrasound imaging.

Background: To investigate the effectiveness of contrastive learning, in particular SimClr, in reducing the need for large annotated ultrasound (US) image datasets for fetal standard plane identification.

Methods: We explore SimClr advantage in the cases of both low and high inter-class variability, considering at the same time how classification performance varies according to different amounts of labels used. This evaluation is performed by exploiting contrastive learning through different training strategies.

Automatic Spontaneous Speech Analysis for the Detection of Cognitive Functional Decline in Older Adults: Multilanguage Cross-Sectional Study.

Background: The rise in life expectancy is associated with an increase in long-term and gradual cognitive decline. Treatment effectiveness is enhanced at the early stage of the disease. Therefore, there is a need to find low-cost and ecological solutions for mass screening of community-dwelling older adults.

A soft, scalable and adaptable multi-contact cuff electrode for targeted peripheral nerve modulation.

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.

Finite-element modeling of neuromodulation via controlled delivery of potassium ions using conductive polymer-coated microelectrodes.

. The controlled delivery of potassium is an interesting neuromodulation modality, being potassium ions involved in shaping neuron excitability, synaptic transmission, network synchronization, and playing a key role in pathological conditions like epilepsy and spreading depression. Despite many successful examples of pre-clinical devices able to influence the extracellular potassium concentration, computational frameworks capturing the corresponding impact on neuronal activity are still missing.

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.

Real-Time Laryngeal Cancer Boundaries Delineation on White Light and Narrow-Band Imaging Laryngoscopy with Deep Learning.

Objective: To investigate the potential of deep learning for automatically delineating (segmenting) laryngeal cancer superficial extent on endoscopic images and videos.

Methods: A retrospective study was conducted extracting and annotating white light (WL) and Narrow-Band Imaging (NBI) frames to train a segmentation model (SegMENT-Plus). Two external datasets were used for validation.

Placental vessel segmentation and registration in fetoscopy: Literature review and MICCAI FetReg2021 challenge findings.

Fetoscopy laser photocoagulation is a widely adopted procedure for treating Twin-to-Twin Transfusion Syndrome (TTTS). The procedure involves photocoagulation pathological anastomoses to restore a physiological blood exchange among twins. The procedure is particularly challenging, from the surgeon's side, due to the limited field of view, poor manoeuvrability of the fetoscope, poor visibility due to amniotic fluid turbidity, and variability in illumination.