Neurology

Age-related metabolomic signatures and stroke susceptibility in a population-based cohort.

Aging-related metabolic dysregulation and vascular vulnerability contribute substantially to stroke susceptibility, yet subtype-specific metabolic signatures remain incompletely characterized. Employing a nested case-control design within the Taizhou Longitudinal Study, we quantified 296 lipoprotein parameters and 54 metabolites in 1208 stroke-control pairs using nuclear magnetic resonance. Logist...

Focused Ultrasound System Design Considerations Based on the Applications for the Peripheral Nervous System.

OBJECTIVE: This paper provides a review of design considerations crucial to Focused ultrasound (FUS) systems for achieving effective therapeutic outcomes in peripheral nervous system (PNS) applications, with an emphasis on linking application requirements to hardware realizability. METHODS: We reviewed the literature on FUS used primarily in the PNS and extracted treatment parameters, transducers,...

Cross-Level Topological Framework: Learning Explainable Region-Channel Representations from EEG Signals for Emotional Decoding.

Constructing functional connectivity networks from electroencephalogram (EEG) channels and using graph neural networks for emotion recognition have em...

AAPM Consensus Guidelines on Neuromodulation Technologies and Neurocomputer Interfaces for Pain Management and Functional Recovery.

OBJECTIVE: To provide an evidence-based framework for healthcare professionals to use neuromodulation technologies to restore neuromuscular function a...

MindGrab: A Spectrally-Motivated Architecture for Accessible Deep Learning in Neuroimaging.

Deployment complexity and specialized hardware requirements hinder the adoption of deep learning models in neuroimaging. We present MindGrab, a lightw...

A blood transcriptomic signature anchored to central nervous system pathology enables noninvasive detection of multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) lacks noninvasive biomarkers anchored to central nervous system (CNS) pathology. This study aimed to identify a bl...

Alzheimer's disease risk prediction from clinical and social determinants of health: a machine learning cohort study in UK Biobank.

OBJECTIVES: Social determinants of health (SDOH) may improve Alzheimer's disease (AD) risk prediction by capturing upstream contextual risk beyond rou...

Diagnostic yield of electroencephalographyin the emergency department: protocol for the EMINENCE-M multicentre retrospective observational study.

INTRODUCTION: Emergency EEG (emEEG) is increasingly used in the emergency department (ED), but its diagnostic yield remains uncertain. This protocol d...

Low-intensity transcranial ultrasound stimulation improves motor behavior and modulates cortical functional network connectivity in mice with ischemic stroke.

The recovery of motor function in patients with ischemic stroke is closely related to the plastic remodeling of cortical functional networks. Low-inte...

A cloud-based miniscope for neurosurveillance of brain health and disease in freely behaving animals.

Miniaturized microscopes or 'miniscopes' for neuroimaging in freely behaving animals mostly operate over short durations (<2 h) and image either neuro...

Cross-attention guided explainable deep transformer model for multi-level classification of rare neurological disorders using MRI images.

Neurological disorders (ND) impact a significant number of the population all over the world, affecting the brain, spinal cord, and peripheral nerves....

Burden trajectories of stroke attributable to lipid-glucose dysfunction and biomarker validation: evidence from the global burden of disease (GBD) 2023 and the China health and retirement longitudinal study (CHARLS).

BACKGROUND: Metabolic dysfunction is an important contributor to stroke burden and may also help identify individuals at higher future risk of stroke....

Applications of electromyography in Amyotrophic Lateral Sclerosis: A systematic review.

This systematic review examined the use of surface electromyography (sEMG) for the neuromuscular assessment of individuals with Amyotrophic Lateral Sc...

Evaluating multi-level membership inference risk in federated EEG learning.

Electroencephalography (EEG) records electrical brain activity from the scalp and is widely used in brain-computer interface (BCI) systems for communi...

Machine learning-based prediction model for long-term mortality after ischemic stroke.

Stroke, a leading cause of death, requires precise predictions of life expectancy. Traditional scores focused on short-term outcomes and required labo...

Clinical pathways matter for multimodal deep learning in early Alzheimer's disease detection.

Identifying individuals at risk of Alzheimer's disease (AD), particularly in the preclinical and early stages, remains challenging. Although deep lear...

Precision neuroprotection in cardiac surgery: a structured narrative review of multimodal, data-driven perioperative care.

Neurological injury remains a major contributor to morbidity, mortality, and long-term cognitive decline in patients undergoing cardiac surgery, despi...

Machine learning identification of neuroimaging signatures in young and middle-aged male patients with obstructive sleep apnea: a multimodal MRI study.

OBJECTIVES: This study aimed to develop and validate an integrated neuroimaging-based model for identifying severe obstructive sleep apnea (OSA) with ...

Increasing the Reliability of Functional Connectivity by Predicting Long-Scan Functional Connectivity based on Short-Scan Functional Connectivity: Model Exploration, Explanation, Validation, and Application.

Functional connectivity (FC) is a widely used metric in functional magnetic resonance imaging (fMRI) research. However, its reliability has long been ...

Diagnosis of ADHD in children from EEG signals using amplitude modulation features.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children and accurate diagnosis of this disorde...