Neurology

Cortico-basal oscillations index naturalistic movements during deep brain stimulation.

The basal ganglia and sensorimotor cortex are essential nodes of a network that supports motor control. In Parkinson's disease, disruptions in this network lead to rigidity and slowness during movement execution. Deep brain stimulation (DBS) of the basal ganglia has proved effective in alleviating Parkinson's disease-related hypokinetic symptoms, and sensing-enabled neurostimulators now afford the...

External Validation of a Machine Learning Model for the Early Prediction of Upper-Limb Recovery After Stroke.

BACKGROUND: Reliable prediction of upper-limb recovery after stroke can support rehabilitation planning, yet few prognostic models have been tested beyond their development cohorts. External validation is essential to establish the clinical reliability of these methods. OBJECTIVE: To externally validate a previously developed machine learning model for predicting 6-month upper-limb capacity after ...

Addressing the Global Disparities in Access to Treatment in Spinal Muscular Atrophy.

The advent of novel disease-modifying therapeutics for spinal muscular atrophy (SMA) increased life expectancy with better motor function and potentia...

Automatic sleep staging and atonia detection in RBD using single-channel chin EMG.

Study ObjectivesThe diagnosis of rapid eye movement (REM) sleep behavior disorder (RBD) is of clinical interest, as there is a high rate of future con...

Retinal and Choroidal Vascular Metrics Predict Cerebral Atrophy and Cognitive Impairment in Noninfarcted Large Artery Stenosis.

PURPOSE: Large artery stenosis (LAS) can drive cognitive impairment and neurodegeneration even without overt infarction, yet scalable biomarkers for c...

Adaptive cascading artificial intelligence for Alzheimer's disease assessment: a clinically oriented narrative review and implementation framework.

Artificial intelligence (AI) has achieved remarkable success in the diagnosis of Alzheimer's disease (AD) in the literature, where many of the models ...

Functional outcome prediction after traumatic cervical spinal cord injury using ensemble machine learning: a three‑center validation study.

BACKGROUND: Traumatic cervical spinal cord injury (TCSCI) often causes severe neurological dysfunction. Accurate prediction of functional recovery is ...

Neurons Die Not by One Hit, but by Signaling Convergence.

There is an emerging understanding of neurodegenerative diseases as complex diseases with a combination of multiple interrelated signaling pathways as...

Assessing a reduced-channel algorithm for end-to-end seizure detection on multiday EEG using inter-rater agreement with epileptologists.

Automated electrographic seizure detection software often rely on the high channel counts of traditional electroencephalography (EEG) recording system...

Validation of a deep learning-based system for sleep staging, arousal detection, and respiratory event scoring in atrial fibrillation patients.

PURPOSE: Obstructive sleep apnea is a common yet underdiagnosed sleep disorder in patients with atrial fibrillation (AF). Although polysomnography (PS...

Biomarker-Conditioned Vision Transformers with Deformable Biomarker Attention for Alzheimer's Disease Classification.

Alzheimer's disease (AD) classification from structural magnetic resonance imaging (MRI) remains challenging, particularly when distinguishing mild co...

Intron retention in health and amyotrophic lateral sclerosis.

Intron retention (IR) is the molecular phenomenon by which introns, historically thought to represent non-coding 'junk', remain unspliced within pre-m...

MRI-based oxygen extraction fraction mapping using qBOLD, QSM, and hybrid QSM-qBOLD methods: Methodological advances, validation, and clinical applications.

Oxygen extraction fraction (OEF) is a physiological parameter reflecting the fraction of delivered arterial oxygen extracted by cerebral tissue, provi...

EEG-fMRI fusion-based source localization for the identification and mechanistic elucidation of paroxysmal kinesigenic dyskinesia.

UNLABELLED: Paroxysmal kinesigenic dyskinesia is a rare neurological disorder characterized by brief, recurrent motor attacks that significantly impai...

Leveraging pretrained vision transformers for classifying alcohol use disorder using raw resting-state EEG.

Alcohol Use Disorder (AUD) is a prevalent neuropsychiatric condition affecting about 28 million adults in the USA, with few objective biomarkers to as...

From machine learning to deep learning in attention deficit hyperactivity disorder diagnosis: A bibliometric analysis of global trends (2011-2024).

BACKGROUND: The diagnosis of attention deficit hyperactivity disorder (ADHD) has traditionally relied on subjective clinical interviews. Recent years ...

Leveraging machine learning with real-world data for hypothesis generation by identifying exposomic predictors in Parkinson's disease among farmers.

BackgroundMachine learning offers new avenues for complementing traditional epidemiological approaches by analyzing routinely collected, population-ba...

Genome-wide analysis of subcortical aging identifies a spatially structured pattern of genetic associations.

Local brain age (LBA) is a spatially resolved biomarker of brain aging that captures regional deviations from chronological age, yet its genetic archi...

A network approach with motion sequencing reveals hidden patterns of repetitive behavior in a pre-clinical model of epilepsy.

Epilepsy is the 4th most prevalent neurological condition with 50 million cases worldwide. Patients with epilepsy bare a disproportionate burden of co...

Enhancing the Capability and Accuracy of Motor Imagery Classification: A Deep Neural Network-Powered Multifaceted Strategy Model.

Motor imagery (MI) is a popular noninvasive brain computer interface (BCI) paradigm, yet its decoding accuracy remains hindered by the inherent nonsta...