CIGNN: A Causality-Informed and Graph Neural Network Based Framework for Cuffless Continuous Blood Pressure Estimation

CIGNN: A Framework for Cuffless Continuous Blood Pressure Estimation Based on Causality and Graph Neural Networks Background Introduction According to data from the World Health Organization (WHO), approximately 1.13 billion people globally are affected by hypertension, and this number is expected to increase to 1.5 billion by 2025. Hypertension is...

Graph-based Conditional Generative Adversarial Networks for Major Depressive Disorder Diagnosis with Synthetic Functional Brain Network Generation

Graph-based Conditional Generative Adversarial Networks for Major Depressive Disorder Diagnosis with Synthetic Functional Brain Network Generation

Graph-Based Conditional Generative Adversarial Network for Generating Synthetic Functional Brain Networks to Diagnose Major Depressive Disorder Research Background: Major Depressive Disorder (MDD) is a widespread mental disorder that affects millions of people’s lives and poses a significant threat to global health. Studies have shown that function...

Decreased Thalamocortical Connectivity in Resolved Rolandic Epilepsy

Decreased Thalamocortical Connectivity in Resolved Rolandic Epilepsy

Thalamocortical Connectivity Reduction in Rolandic Epilepsy Rolandic Epilepsy (RE), also known as self-limited epilepsy with centrotemporal spikes (SELECTS), is the most common localized developmental epileptic encephalopathy. This type of epilepsy is typically accompanied by transient mild to severe cognitive symptoms, sleep-related rolandic spike...

Functional Connectivity Changes in Mild Cognitive Impairment: A Meta-Analysis of M/EEG Studies

Changes in Functional Connectivity in Mild Cognitive Impairment: A Meta-Analysis of M/EEG Studies Background and Objectives Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by memory loss and cognitive impairment. AD is the leading cause of cognitive disorders in the elderly, accounting for approximately 60% to 80% of global c...

Investigation of the Impact of Cross-Frequency Coupling on the Assessment of Depression Severity through the Analysis of Resting State EEG Signals

Background Depression, particularly Major Depressive Disorder (MDD), is a widespread and debilitating psychological disease often described as the “common cold” of mental health. Many people with MDD experience symptoms such as persistent sadness, hopelessness, cognitive impairment, and loss of motivation for daily activities, severely affecting pe...

Distinguishing Parkinsonian Rest Tremor from Voluntary Hand Movements through Subthalamic and Cortical Activity

Parkinson’s disease (PD) is a common neurodegenerative disorder characterized mainly by resting tremor, bradykinesia, and rigidity. Deep Brain Stimulation (DBS) has been widely used to treat the motor symptoms of PD (Krauss et al., 2021). However, DBS treatment also has significant side effects, most of which are caused by the extension of stimulat...

Early Prediction of Drug-Resistant Epilepsy Using Clinical and EEG Features Based on Convolutional Neural Network

Research Background and Purpose Epilepsy is a spontaneous and severe neurological disorder characterized by recurrent seizures, affecting approximately 50 million people worldwide [1]. Despite recent advances in anti-seizure medications (ASMs), drug-resistant epilepsy (DRE) still affects 20% to 30% of epilepsy patients [1-3]. DRE patients face sign...

Single-Subject Cortical Morphological Brain Networks: Phenotypic Associations and Neurobiological Substrates

This paper is a study on the phenotypic associations and neurobiological bases of single-subject morphological brain networks. Combining multimodal and multiscale data, this study reveals the differences in morphological brain networks between genders, their potential as individual-specific markers, and their relationships with gene expression, lay...

Networked Information Interactions in Schizophrenia Magnetoencephalograms based on Permutation Transfer Entropy

Study of Network Information Interactions in Schizophrenia Magnetoencephalograms Based on Permutation Transfer Entropy Academic Background Schizophrenia (SCZ) is a mental disorder characterized by persistent delusions and hallucinations, disorganized thinking, and inconsistent behavior, often leading to significant impairment in the perception of r...

Functional Brain Network Based on Improved Ensemble Empirical Mode Decomposition of EEG for Anxiety Analysis and Detection

Brain Functional Network for Anxiety Analysis and Detection Based on Improved Ensemble Empirical Mode Decomposition Academic Background and Research Objectives With the increasing stress of modern life, anxiety, a common neurological disorder, has become an urgent issue in global public health. Anxiety not only manifests as mental disorders but als...