Knowledge Graph Completion by Jointly Learning Structural Features and Soft Logical Rules

In recent years, Knowledge Graphs (KG) have been widely used in many artificial intelligence tasks. Knowledge graphs represent entities and their relationships using triplets consisting of a head entity, a relation, and a tail entity. For example, the triplet (h = Paris, r = capital_of, t = France) represents a common-sense fact about the real worl...

Deep Relational Graph Infomax for Knowledge Graph Completion

Knowledge Graph (KG) embedding technology is an important research topic in the field of artificial intelligence, mainly used for knowledge acquisition and extension of knowledge graphs. In recent years, although many graph embedding methods have been proposed, these methods typically focus only on the semantic information of the knowledge graph, i...

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...

Epilepsy Surgery for Dominant-Side Mesial Temporal Lobe Epilepsy without Hippocampal Sclerosis

Evaluation of Efficacy of Epilepsy Surgery for Dominant Mesial Temporal Lobe Epilepsy without Hippocampal Sclerosis Original Research | Journal of Clinical Neuroscience 111 (2023) 16-21 Introduction Approximately 0.5%-1% of the global population suffers from epilepsy (Fiest et al. 2017), with about 30% of these patients being refractory to medicati...

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...

Pupillometry Reveals Resting State Alpha Power Correlates with Individual Differences in Adult Auditory Language Comprehension

Study on the Correlation between Adult Auditory Language Comprehension and Resting-State Alpha Wave Power Academic Background and Research Question Although individual differences in adult language processing have been documented in literature, the neural basis largely remains to be explored. Existing research primarily focuses on how general cogni...

Salivary Testosterone Levels and Pain Perception Exhibit Sex-Specific Association in Healthy Adults but Not in Patients with Migraine

The Level of Salivary Testosterone and Pain Perception Show Sex-Specific Associations in Healthy Adults, But Not in Migraine Patients Introduction Understanding the complexity of pain and the role gender plays in pain perception is of significant importance in medical research. Pain is an unpleasant sensory and emotional experience associated with ...

Bridging Stories and Science: An fNIRS-based Hyperscanning Investigation into Child Learning in STEM

Bridging Stories and Science: An fNIRS-based Hyperscanning Investigation into Child Learning in STEM

Academic News Report In Volume 285 of “Neuroimage” (2024), there is a published article entitled “Bridging Stories and Science: An fNIRS-Based Hyperscanning Investigation into Child Learning in STEM”. This article was co-authored by Juan Zhang and others, with the research team hailing from the Faculty of Education, Faculty of Health Sciences, and ...

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...