Cortico-thalamic tremor circuits and their associations with deep brain stimulation effects in essential tremor.

Essential tremor (ET) is one of the most common movement disorders in adults. Deep brain stimulation (DBS) of the ventralis intermediate nucleus (VIM) of the thalamus and/or the posterior subthalamic area (PSA) has been shown to provide significant tremor suppression in patients with ET, but with significant inter-patient variability and habituation to the stimulation. Several non-invasive neuromodulation techniques targeting other parts of the central nervous system, including cerebellar, motor cortex, or peripheral nerves, have also been developed for treating ET, but the clinical outcomes remain inconsistent.

HDE-Array: Development and Validation of a New Dry Electrode Array Design to Acquire HD-sEMG for Hand Position Estimation.

This paper aims to introduce HDE-Array (High-Density Electrode Array), a novel dry electrode array for acquiring High-Density surface electromyography (HD-sEMG) for hand position estimation through RPC-Net (Recursive Prosthetic Control Network), a neural network defined in a previous study. We aim to demonstrate the hypothesis that the position estimates returned by RPC-Net using HD-sEMG signals acquired with HDE-Array are as accurate as those obtained from signals acquired with gel electrodes. We compared the results, in terms of precision of hand position estimation by RPC-Net, using signals acquired by traditional gel electrodes and by HDE-Array.

Auditory cues modulate the short timescale dynamics of STN activity during stepping in Parkinson's disease.

Background: Gait impairment has a major impact on quality of life in patients with Parkinson's disease (PD). It is believed that basal ganglia oscillatory activity at β frequencies (15-30 Hz) may contribute to gait impairment, but the precise dynamics of this oscillatory activity during gait remain unclear. Additionally, auditory cues are known to lead to improvements in gait kinematics in PD.

Evaluation of 3D C-Arm Fluoroscopy versus Diagnostic CT for Deep Brain Stimulation Stereotactic Registration and Post-Operative Lead Localization.

Introduction: DBS efficacy depends on accuracy. CT-MRI fusion is established for both stereotactic registration and electrode placement verification. The desire to streamline DBS workflows, reduce operative time, and minimize patient transfers has increased interest in portable imaging modalities such as the Medtronic O-arm® and mobile CT.

Developing RPC-Net: Leveraging High-Density Electromyography and Machine Learning for Improved Hand Position Estimation.

Objective: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand position with high accuracy and computational efficiency.

Methods: RPC-Net uses a regression-based approach to convert forearm electromyographic signals into hand kinematics. We tested the adaptability of the algorithm to different conditions and compared its performance with that of solutions from the academic literature.

Seeing Is Believing: Photon Counting Computed Tomography Clearly Images Directional Deep Brain Stimulation Lead Segments and Markers After Implantation.

Background And Objectives: Directional deep brain stimulation (DBS) electrodes are increasingly used, but conventional computed tomography (CT) is unable to directly image segmented contacts owing to physics-based resolution constraints. Postoperative electrode segment orientation assessment is necessary because of the possibility of significant deviation during or immediately after insertion. Photon-counting detector (PCD) CT is a relatively novel technology that enables high resolution imaging while addressing several limitations intrinsic to CT.

Identification of motor progression in Parkinson's disease using wearable sensors and machine learning.

Wearable devices offer the potential to track motor symptoms in neurological disorders. Kinematic data used together with machine learning algorithms can accurately identify people living with movement disorders and the severity of their motor symptoms. In this study we aimed to establish whether a combination of wearable sensor data and machine learning algorithms with automatic feature selection can estimate the clinical rating scale and whether it is possible to monitor the motor symptom progression longitudinally, for people with Parkinson's Disease.

Antiparkinsonian medication masks motor signal progression in de novo patients.

Patients not yet receiving medication provide insight to drug-naïve early physiology of Parkinson's Disease (PD). Wearable sensors can measure changes in motor features before and after introduction of antiparkinsonian medication. We aimed to identify features of upper limb bradykinesia, postural stability, and gait that measurably progress in de novo PD patients prior to the start of medication, and determine whether these features remain sensitive to progression in the period after commencement of antiparkinsonian medication.

Closed-loop parameter optimization for patient-specific phrenic nerve stimulation.

Background: Ventilator-induced diaphragm dysfunction occurs rapidly following the onset of mechanical ventilation and has significant clinical consequences. Phrenic nerve stimulation has shown promise in maintaining diaphragm function by inducing diaphragm contractions. Non-invasive stimulation is an attractive option as it minimizes the procedural risks associated with invasive approaches.

Decomposition into dynamic features reveals a conserved temporal structure in hand kinematics.

The human hand is a unique and highly complex effector. The ability to describe hand kinematics with a small number of features suggests that complex hand movements are composed of combinations of simpler movements. This would greatly simplify the neural control of hand movements.

Parkinson's disease deficits in time perception to auditory as well as visual stimuli - A large online study.

Cognitive deficits are common in Parkinson's disease (PD) and range from mild cognitive impairment to dementia, often dramatically reducing quality of life. Physiological models have shown that attention and memory are predicated on the brain's ability to process time. Perception has been shown to be increased or decreased by activation or deactivation of dopaminergic neurons respectively.

Computation of Activating Fields for Approximation of the Orientation-Specific Neural Response to Electrical Stimulation.

Computational methods of determining the response of neural tissue to electrical stimulation have demonstrated value for the development of novel devices and the programming of neuromodulation therapies. Detailed biophysical models are excessively computationally intensive for many applications; simple metrics to approximate activation can speed up progress in this area. The activating function provides such a useful metric.

Longitudinal Monitoring of Progressive Supranuclear Palsy using Body-Worn Movement Sensors.

Background: We have previously shown that wearable technology and machine learning techniques can accurately discriminate between progressive supranuclear palsy (PSP), Parkinson's disease, and healthy controls. To date these techniques have not been applied in longitudinal studies of disease progression in PSP.

Objectives: We aimed to establish whether data collected by a body-worn inertial measurement unit (IMU) network could predict clinical rating scale scores in PSP and whether it could be used to track disease progression.

Oculomotor deficits in Parkinson's disease: Increasing sensitivity using multivariate approaches.

Parkinson's disease (PD) affects several domains of neurological function, from lower-level motor programs to higher cognitive processing. As certain types of eye movements (saccades) are fast, non-fatiguing, and can be measured objectively and non-invasively, they are a promising candidate for quantifying motor and cognitive dysfunction in PD, as well as other movement disorders. In this pilot study, we evaluate the latency (reaction time), damping (resistance to oscillation), and amplitude of saccadic movements in two tasks performed by 25 PD patients with mild to moderate disease and 26 age-matched healthy controls.

Deep Brain Stimulation and Levodopa Affect Gait Variability in Parkinson Disease Differently.

Background: Both dopaminergic medication and subthalamic nucleus (STN) deep brain stimulation (DBS) can improve the amplitude and speed of gait in Parkinson disease (PD), but relatively little is known about their comparative effects on gait variability. Gait irregularity has been linked to the degeneration of cholinergic neurons in the pedunculopontine nucleus (PPN).

Objectives: The STN and PPN have reciprocal connections, and we hypothesized that STN DBS might improve gait variability by modulating PPN function.

Non-invasive phrenic nerve stimulation to avoid ventilator-induced diaphragm dysfunction in critical care.

Background: Diaphragm muscle atrophy during mechanical ventilation begins within 24 h and progresses rapidly with significant clinical consequences. Electrical stimulation of the phrenic nerves using invasive electrodes has shown promise in maintaining diaphragm condition by inducing intermittent diaphragm muscle contraction. However, the widespread application of these methods may be limited by their risks as well as the technical and environmental requirements of placement and care.

Spatial and Temporal Distribution of Information Processing in the Human Dorsal Anterior Cingulate Cortex.

The dorsal anterior cingulate cortex (dACC) is a key node in the human salience network. It has been ascribed motor, pain-processing and affective functions. However, the dynamics of information flow in this complex region and how it responds to inputs remain unclear and are difficult to study using non-invasive electrophysiology.

Longitudinal changes of early motor and cognitive symptoms in progressive supranuclear palsy: the OxQUIP study.

Background: Progressive supranuclear palsy (PSP) is a rare neurodegenerative condition characterised by a range of motor and cognitive symptoms. Very little is known about the longitudinal change in these symptoms over time. Moreover, the effectiveness of clinical scales to detect early changes in PSP is still a matter of debate.

Paired Acute Invasive/Non-invasive Stimulation (PAINS) study: A phase I/II randomized, sham-controlled crossover trial in chronic neuropathic pain.

Background: Dorsal root ganglion (DRG) stimulation, an invasive method of neuromodulation, and transcranial direct current stimulation (tDCS), a non-invasive method of altering cortical excitability, have both proven effective in relieving chronic pain.

Objective: We employed a randomized, sham-controlled crossover study design to investigate whether single-session tDCS would have an additive therapeutic effect alongside DRG stimulation (DRGS) in the treatment of chronic pain.

Methods: Sixteen neuropathic pain patients who were previously implanted with DRG stimulators were recruited.

Pallido-putaminal connectivity predicts outcomes of deep brain stimulation for cervical dystonia.

Cervical dystonia is a non-degenerative movement disorder characterized by dysfunction of both motor and sensory cortico-basal ganglia networks. Deep brain stimulation targeted to the internal pallidum is an established treatment, but its specific mechanisms remain elusive, and response to therapy is highly variable. Modulation of key dysfunctional networks via axonal connections is likely important.