Rigidity in Parkinson's Disease: The Objective Effect of Levodopa.

Background: Quantitative evidence of levodopa-induced beneficial effects on parkinsonian rigidity in Parkinson's disease (PD) is lacking. Recent research has demonstrated the velocity-dependent nature of objective rigidity in PD and revealed its neural underpinning.

Objective: The present study aimed to examine the effect of levodopa on objective rigidity in PD.

Cohort analysis of novel variants in SPG4 patients and implementation of and studies to identify the pathogenic mechanism caused by splicing mutations.

Introduction: Pure hereditary spastic paraplegia (SPG) type 4 (SPG4) is caused by mutations of gene. This study aimed to analyze variants in SPG4 patients to highlight the occurrence of splicing mutations and combine functional studies to assess the relevance of these variants in the molecular mechanisms of the disease.

Methods: We performed an NGS panel in 105 patients, analysis for splicing mutations, and minigene assay.

Effects of deep brain stimulation of the subthalamic nucleus on patients with Parkinson's disease: a machine-learning voice analysis.

Introduction: Deep brain stimulation of the subthalamic nucleus (STN-DBS) can exert relevant effects on the voice of patients with Parkinson's disease (PD). In this study, we used artificial intelligence to objectively analyze the voices of PD patients with STN-DBS.

Materials And Methods: In a cross-sectional study, we enrolled 108 controls and 101 patients with PD.

Pain-motor integration in chronic pain: A neurophysiological study.

Objective: Chronic pain may lead to functional changes in several brain regions, including the primary motor cortex (M1). Our neurophysiological study aimed to probe M1 plasticity, through a non-invasive transcranial magnetic stimulation protocol, in a cohort of patients with chronic pain.

Methods: Twenty patients with chronic pain (age ± SD: 62.

Acoustic analysis in stuttering: a machine-learning study.

Background: Stuttering is a childhood-onset neurodevelopmental disorder affecting speech fluency. The diagnosis and clinical management of stuttering is currently based on perceptual examination and clinical scales. Standardized techniques for acoustic analysis have prompted promising results for the objective assessment of dysfluency in people with stuttering (PWS).

Robust and language-independent acoustic features in Parkinson's disease.

Introduction: The analysis of vocal samples from patients with Parkinson's disease (PDP) can be relevant in supporting early diagnosis and disease monitoring. Intriguingly, speech analysis embeds several complexities influenced by speaker characteristics (e.g.

Rigidity in Parkinson's disease: evidence from biomechanical and neurophysiological measures.

Although rigidity is a cardinal motor sign in patients with Parkinson's disease (PD), the instrumental measurement of this clinical phenomenon is largely lacking, and its pathophysiological underpinning remains still unclear. Further advances in the field would require innovative methodological approaches able to measure parkinsonian rigidity objectively, discriminate the different biomechanical sources of muscle tone (neural or visco-elastic components), and finally clarify the contribution to 'objective rigidity' exerted by neurophysiological responses, which have previously been associated with this clinical sign (i.e.

Artificial Intelligence-Based Voice Assessment of Patients with Parkinson's Disease Off and On Treatment: Machine vs. Deep-Learning Comparison.

Parkinson's Disease (PD) is one of the most common non-curable neurodegenerative diseases. Diagnosis is achieved clinically on the basis of different symptoms with considerable delays from the onset of neurodegenerative processes in the central nervous system. In this study, we investigated early and full-blown PD patients based on the analysis of their voice characteristics with the aid of the most commonly employed machine learning (ML) techniques.

Parkinsonism Is Associated with Altered SMA-Basal Ganglia Structural and Functional Connectivity in Frontotemporal Degeneration.

Background: Patients with frontotemporal degeneration (FTD) often manifest parkinsonism, which likely results from cortical and subcortical degeneration of brain structures involved in motor control. We used a multimodal magnetic resonance imaging (MRI) approach to investigate possible structural and/or functional alterations in FTD patients with and without parkinsonism (Park+ and Park-).

Methods: Thirty FTD patients (12 Park+, 18 Park-) and 30 healthy controls were enrolled and underwent 3T MRI scanning.

Machine Learning and Wearable Sensors for the Early Detection of Balance Disorders in Parkinson's Disease.

Dynamic posturography combined with wearable sensors has high sensitivity in recognizing subclinical balance abnormalities in patients with Parkinson's disease (PD). However, this approach is burdened by a high analytical load for motion analysis, potentially limiting a routine application in clinical practice. In this study, we used machine learning to distinguish PD patients from controls, as well as patients under and not under dopaminergic therapy (i.

Assessing the interaction between L-dopa and γ-transcranial alternating current stimulation effects on primary motor cortex plasticity in Parkinson's disease.

L-dopa variably influences transcranial magnetic stimulation (TMS) parameters of motor cortex (M1) excitability and plasticity in Parkinson's disease (PD). In patients OFF dopaminergic medication, impaired M1 plasticity and defective GABA-A-ergic inhibition can be restored by boosting gamma (γ) oscillations via transcranial alternating current stimulation (tACS) during intermittent theta-burst stimulation (iTBS). However, it is unknown whether L-dopa modifies the beneficial effects of iTBS-γ-tACS on M1 in PD.

Handwriting Declines With Human Aging: A Machine Learning Study.

Background: Handwriting is an acquired complex cognitive and motor skill resulting from the activation of a widespread brain network. Handwriting therefore may provide biologically relevant information on health status. Also, handwriting can be collected easily in an ecological scenario, through safe, cheap, and largely available tools.

Decipher non-canonical SPAST splicing mutations with the help of functional assays in patients affected by spastic paraplegia 4 (SPG4).

Flowchart showing the molecular approach used to decipher the non-canonical splicing mutations.

Voice in Parkinson's Disease: A Machine Learning Study.

Introduction: Parkinson's disease (PD) is characterized by specific voice disorders collectively termed hypokinetic dysarthria. We here investigated voice changes by using machine learning algorithms, in a large cohort of patients with PD in different stages of the disease, OFF and ON therapy.

Methods: We investigated 115 patients affected by PD (mean age: 68.

Wearable Electrochemical Sensors in Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disorder associated with widespread aggregation of α-synuclein and dopaminergic neuronal loss in the substantia nigra pars compacta. As a result, striatal dopaminergic denervation leads to functional changes in the cortico-basal-ganglia-thalamo-cortical loop, which in turn cause most of the parkinsonian signs and symptoms. Despite tremendous advances in the field in the last two decades, the overall management (i.

Transcranial magnetic stimulation as a tool to induce and explore plasticity in humans.

Activity-dependent synaptic plasticity is the main theoretical framework to explain mechanisms of learning and memory. Synaptic plasticity can be explored experimentally in animals through various standardized protocols for eliciting long-term potentiation and long-term depression in hippocampal and cortical slices. In humans, several non-invasive protocols of repetitive transcranial magnetic stimulation and transcranial direct current stimulation have been designed and applied to probe synaptic plasticity in the primary motor cortex, as reflected by long-term changes in motor evoked potential amplitudes.

Long-term changes in short-interval intracortical facilitation modulate motor cortex plasticity and L-dopa-induced dyskinesia in Parkinson's disease.

Background: Abnormal glutamatergic neurotransmission in the primary motor cortex (M1) contributes to Parkinson's disease (PD) pathophysiology and is related to l-dopa-induced dyskinesia (LID). We previously showed that short-term treatment with safinamide, a monoamine oxidase type-B inhibitor with anti-glutamatergic properties, improves abnormally enhanced short-interval intracortical facilitation (SICF) in PD patients.

Objective: To examine whether a long-term SICF modulation has beneficial effects on clinical measures, including LID severity, and whether these changes parallel improvement in cortical plasticity mechanisms in PD.

Cortical mechanisms underlying variability in intermittent theta-burst stimulation-induced plasticity: A TMS-EEG study.

Objective: To test the hypothesis that intermittent theta burst stimulation (iTBS) variability depends on the ability to engage specific neurons in the primary motor cortex (M1).

Methods: In a sham-controlled interventional study on 31 healthy volunteers, we used concomitant transcranial magnetic stimulation (TMS) and electroencephalography (EEG). We compared baseline motor evoked potentials (MEPs), M1 iTBS-evoked EEG oscillations, and resting-state EEG (rsEEG) between subjects who did and did not show MEP facilitation following iTBS.

Acute-onset binocular diplopia in neurological unit: Aetiological factors and diagnostic assessment.

Objectives: To investigate the aetiology of acute-onset binocular diplopia (AOBD) in neurological units and identify the key diagnostic procedures in this setting.

Materials And Methods: Clinico-demographic data from patients hospitalized for AOBD from 2008 to 2019 were retrospectively reviewed. AOBD due to an underlying neurological disorder known to cause diplopia was addressed as secondary diplopia.

The effect of gamma oscillations in boosting primary motor cortex plasticity is greater in young than older adults.

Objective: In healthy subjects, the long-term potentiation (LTP)-like plasticity of the primary motor cortex (M1) induced by intermittent theta-burst stimulation (iTBS) can be boosted by modulating gamma (γ) oscillations through transcranial alternating current stimulation (tACS). γ-tACS also reduces short-interval intracortical inhibition (SICI). We tested whether the effects of γ-tACS differ between young (YA) and older adults (OA).

Voice Analysis with Machine Learning: One Step Closer to an Objective Diagnosis of Essential Tremor.

Background: Patients with essential tremor have upper limb postural and action tremor often associated with voice tremor. The objective of this study was to objectively examine voice tremor and its response to symptomatic pharmacological treatment in patients with essential tremor using voice analysis consisting of power spectral analysis and machine learning.

Methods: We investigated 58 patients (24 men; mean age ± SD, 71.