Neurology

TMNRED, A Chinese Language EEG Dataset for Fuzzy Semantic Target Identification in Natural Reading Environments.

Semantic understanding is central to advanced cognitive functions, and the mechanisms by which the brain processes language information are still being explored. Existing EEG datasets often lack natural reading data specific to Chinese, limiting research on Chinese semantic decoding and natural language processing. This study aims to construct a Chinese natural reading EEG dataset, TMNRED, for sem...

Developmental coordination disorder and cerebral visual impairment: What is the association?

INTRODUCTION: Children with Developmental Coordination Disorder (DCD) experience impairments beyond motor planning, affecting visual perceptual and visual-motor integration abilities, similar to children with Cerebral Visual Impairment (CVI), making it challenging to distinguish between the two conditions. This study aimed to identify convergences and divergences in the clinical, neuropsychologica...

Generative artificial intelligence, integrative bioinformatics, and single-cell analysis reveal Alzheimer's genetic and immune landscape.

The research aims to understand Alzheimer's genetic and immune landscapes using the amalgamation of three technologies: artificial intelligence (GenAI...

Enhanced EEG-based Alzheimer's disease detection using synchrosqueezing transform and deep transfer learning.

The most prevalent type of dementia and a progressive neurodegenerative disease, Alzheimer's disease has a major influence on day-to-day functioning d...

A review of multimodal fusion-based deep learning for Alzheimer's disease.

Alzheimer's Disease (AD) as one of the most prevalent neurodegenerative disorders worldwide, characterized by significant memory and cognitive decline...

perfDSA: Automatic Perfusion Imaging in Cerebral Digital Subtraction Angiography.

PURPOSE: Cerebral digital subtraction angiography (DSA) is a standard imaging technique in image-guided interventions for visualizing cerebral blood f...

EEG-based epilepsy detection using CNN-SVM and DNN-SVM with feature dimensionality reduction by PCA.

This study focuses on epilepsy detection using hybrid CNN-SVM and DNN-SVM models, combined with feature dimensionality reduction through PCA. The goal...

SS-EMERGE - self-supervised enhancement for multidimension emotion recognition using GNNs for EEG.

Self-supervised learning (SSL) is a potent method for leveraging unlabelled data. Nonetheless, EEG signals, characterised by their low signal-to-noise...

Decoding of lexical items and grammatical features in EEG: A cross-linguistic study.

Diverse evidence supports the theory that bilingual language users have language-invariant representations of concepts and grammatical forms such as a...

Predictive Analysis of Amyotrophic Lateral Sclerosis Progression and Mortality in a Clinic Cohort From Singapore.

INTRODUCTION: There is currently no comprehensive Amyotrophic Lateral Sclerosis (ALS) patient database in Singapore comparable to those available in E...

Burnout Among Physicians Treating Patients with Multiple Sclerosis in the United States: A Podcast.

Physician burnout, a growing crisis in the healthcare system of the United States of America (USA), is characterized by long-term job-related stress t...

Challenges and Opportunities: Nanomaterials in Epilepsy Diagnosis.

Epilepsy is a common neurological disorder characterized by a significant rate of disability. Accurate early diagnosis and precise localization of the...

HATNet: EEG-Based Hybrid Attention Transfer Learning Network for Train Driver State Detection.

Electroencephalography (EEG) is widely utilized for train driver state detection due to its high accuracy and low latency. However, existing methods f...

Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention.

The neural activity patterns of localized brain regions are crucial for recognizing brain intentions. However, existing electroencephalogram (EEG) dec...

AdamGraph: Adaptive Attention-Modulated Graph Network for EEG Emotion Recognition.

The underlying time-variant and subject-specific brain dynamics lead to inconsistent distributions in electroencephalogram (EEG) topology and represen...

Torg-Pavlov ratio qualification to diagnose developmental cervical spinal stenosis based on HRViT neural network.

BACKGROUND: Developing computer-assisted methods to measure the Torg-Pavlov ratio (TPR), defined as the ratio of the sagittal diameter of the cervical...

Integrating WGCNA and SVM-RFE identifies hub molecular biomarkers driving ischemic stroke progression.

BACKGROUND: Stroke is the second most common cause of death worldwide and the leading cause of long-term severe disability with neurological impairmen...

Radiomics-based analysis of choroid plexus abnormalities in neuromyelitis optica spectrum disorders and multiple sclerosis and their clinical implications.

BACKGROUND: The choroid plexus (CP) is closely linked to inflammation in multiple sclerosis (MS). While the CP volume is enlarged in MS compared with ...

Cerebrospinal fluid inflammatory cytokines as prognostic indicators for cognitive decline across Alzheimer's disease spectrum.

BackgroundNeuroinflammation actively contributes to the pathophysiology of Alzheimer's disease (AD); however, the value of neuroinflammatory biomarker...

Post-stroke spontaneous motor recovery in mice can be predicted from acute-phase local field potential using machine learning.

Stroke remains a leading cause of long-term disability, underscoring the urgent need for effective predictors of motor recovery. Understanding the ele...