Neurology

Glymphatic-meningeal lymphatic dysfunction in epilepsy: Novel mechanistic insights and therapeutic avenues.

Despite advances in pharmacotherapy, approximately one-third of individuals with epilepsy develop drug-resistant epilepsy (DRE), accounting for a disproportionate share of the global disease burden. Emerging evidence implicates dysfunction of the meningeal lymphatic system-a critical regulator of waste clearance and immune surveillance-in the pathogenesis of DRE. This suggests that impaired lympha...

Clinical relevance of intracranial stenosis as false-positive findings of a deep learning algorithm trained to detect large vessel occlusions: a retrospective cohort study of a supraregional stroke centre.

OBJECTIVES: This study aims to explore the ability to identify high-grade intracranial arterial stenosis (ICAS) by an artificial intelligence (AI) designed to detect large vessel occlusions (LVO) and the clinical relevance of these 'false positive' findings. DESIGN: We are presenting a retrospective cohort study. SETTING: The study was conducted at a supraregional stroke centre of an urban tertiar...

Multimodal assessment of minimally conscious state and cognitive motor dissociation in neurocritical care: A critical review.

Minimally conscious state (MCS) is characterized by inconsistent but clearly discernible clinical and behavioral evidence of consciousness. Cognitive ...

Deep Learning-Guided Retinal Vascular Morphometric Quantification in Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy Mouse Models.

PURPOSE: To develop and validate an explainable deep learning-guided workflow to localize and quantify focal retinal luminal pathology on fundus fluor...

Oscillatory edge connectivity in pain-related regions supports machine learning identification of migraine.

BACKGROUND: Objective and interpretable brain signatures for migraine diagnosis and phenotyping remain limited. Edge-centric connectivity treats inter...

Denoising of ASL Data Using Deep Learning Priors Generated From Distribution Remapping.

PURPOSE: To develop an effective deep learning (DL)-based method to denoise arterial spin labeling (ASL) data. METHODS: Conventional DL-based ASL deno...

Masked autoencoder pretraining for peripheral nerve segmentation in ultrasound images.

Despite recent advances in medical image segmentation, deep learning applications in musculoskeletal ultrasound remain limited by small labeled datase...

The entropic brain today.

Introduced in 2014 and revised in 2018, the entropic brain hypothesis has accrued a wealth of supportive evidence. The hypothesis states that-along a ...

Accuracy of Machine Learning to Predict Upper-Limb Outcome Within the First 72 Hours Poststroke.

BACKGROUND: Timely and accurate prediction of poststroke motor outcome is important for efficient rehabilitation planning and resource allocation. Exi...

Streetview greenspace types and dementia risk in older adults: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Greenspace has been associated with lower dementia risk but most studies have used satellite-derived measures that cannot distinguish vege...

Developmental circuit instability in amyotrophic lateral sclerosis: from hyperexcitability to network collapse.

Amyotrophic lateral sclerosis (ALS) is traditionally viewed as a late-onset motor neuron disease, yet how cortical dysfunction originates and contribu...

An Interpretable Machine Learning Model for Predicting Intellectual Disability in Children With Cerebral Palsy.

BACKGROUND: Intellectual disability (ID) affects approximately 45% of children with cerebral palsy (CP), yet early identification is frequently hinder...

Identifing two distinct cortical progression subtypes of Parkinson's disease through multimodal neuroimaging.

PURPOSE: To investigate whether distinct patterns of cortical involvement exist in Parkinson's disease (PD) and to characterize their potential progre...

Domain Adaptation for IMU Data to Enhance Objective Assessment of Friedreich Ataxia.

Friedreich Ataxia (FRDA) is an uncommon progressive neurodegenerative disorder of the nervous system that primarily affects motor coordination. Measur...

Supervised autoencoder for gradient and BCG artifact removal in EEG during simultaneous EEG-fMRI.

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide complementary views of brain function, but MRI-indu...

QSM vs dopamine transporter PET: χ+ Mapping Shows Stronger Longitudinal Associations with Nigral Degeneration than Conventional QSM in Parkinson's Disease.

BACKGROUND: Iron accumulation in the substantia nigra (SN) is a hallmark of Parkinson's disease (PD). Quantitative susceptibility mapping (QSM) includ...

A comprehensive survey on diagnosis and assessment of Parkinson's disease via plantar pressure analysis.

Parkinson's disease (PD) is a progressive neurodegenerative disorder. Its motor symptoms include bradykinesia, rigidity, and postural instability, whi...

A Dataset of Microelectrode Recordings from Deep Brain Stimulation Procedures.

Precise intraoperative localisation of subcortical brain structures remains a critical challenge in deep brain stimulation, yet openly available micro...

Hetairos is a histology-based artificial intelligence model for predicting central nervous system tumor methylation subtypes.

Molecular testing is essential for classifying central nervous system (CNS) tumors, with methylation profiling providing the highest diagnostic granul...

Transformer-based emotion recognition in interactive art: A multimodal neural approach.

Understanding how interactive digital art affects emotional states is essential to advance research into the interface between affective neuroscience ...