Identifying Oscillatory Brain Networks with Hidden Gaussian Graphical Spectral Models of MEEG

Identifying Oscillatory Brain Networks with Hidden Gaussian Graphical Spectral Models of MEEG

Research Background and Objectives With the continuous development of neuroscience, identifying indirectly observed processes related to functional networks has become an important research direction. Researchers attempt to estimate the activity of these functional networks through electrophysiological signals such as EEG and MEG. However, this pro...

Increases in Pre-Stimulus Theta and Alpha Oscillations Precede Successful Encoding of Crossmodal Associations

Enhancement of Theta and Alpha Oscillations Prior to Crossmodal Memory Encoding Background Episodic memory is a crucial component of human memory, with one of its core mechanisms being the formation of associations through stimuli from different sensory channels. Current theories suggest that during crossmodal associative encoding, the phase and po...

Macroscale Intrinsic Dynamics are Associated with Microcircuit Function in Focal and Generalized Epilepsies

Macroscale Intrinsic Dynamics are Associated with Microcircuit Function in Focal and Generalized Epilepsies

Study on the Relationship between Macroscopic Intrinsic Dynamics and Microcircuit Functions in Epilepsy Research Background Epilepsy is a group of neurological disorders characterized by abnormal spontaneous brain activity, involving multi-scale changes in brain functional organization. However, it remains unclear to what extent epilepsy-related sp...

An EEG Study on Artistic and Engineering Mindsets in Students in Creative Processes

A Study on EEG Activities in Artistic and Engineering Thinking during the Creative Process Background and Research Motivation Creativity is universally regarded as the ability to imagine new and valuable things. Researchers have identified two types of creative thinking: growth mindset and fixed mindset. Growth mindset creativity can improve skills...

Analysis of Reading-Task-Based Brain Connectivity in Dyslexic Children Using EEG Signals

Brain Connectivity Analysis Based on Reading Tasks in Children with Dyslexia (Using EEG Signals) Dyslexia is a neurodevelopmental disorder that affects the normal reading ability, even though children with normal intelligence may still be affected. This paper investigates the differences in brain connectivity between children with dyslexia and norm...

Development of Complemented Comprehensive Networks for Rapid Screening of Repurposable Drugs Applicable to New Emerging Disease Outbreaks

Research on Network Construction and Application of Novel Drug Repositioning Strategies Background During the COVID-19 pandemic, researchers and pharmaceutical companies have been dedicated to developing treatments and vaccines. Drug repositioning, due to its shortcut, is considered a rapid and effective response strategy. Drug repositioning attemp...

Potential Biomarker for Early Detection of ADHD Using Phase-Based Brain Connectivity and Graph Theory

Research Report on Potential Biomarkers for Early Detection of ADHD: Phase-Based Functional Brain Connectivity and Graph Theory Analysis This is a research report titled “Potential Biomarkers for Early Detection of ADHD: Using Phase-Based Functional Brain Connectivity and Graph Theory Analysis”. This study was conducted by Farhad Abedinzadeh Torgha...

The Neural Mechanism of Knowledge Assembly in the Human Brain Inspires Artificial Intelligence Algorithm

The Neural Mechanism of Knowledge Assembly in the Human Brain Inspires Artificial Intelligence Algorithm

Brain Science Research Inspires AI Algorithms: Neural Mechanisms of Knowledge Assembly Background Introduction When new information enters the brain, human pre-existing knowledge of the world can quickly change through a process called “knowledge assembly.” Recently, in a study conducted by Nelli et al., the neural correlates of knowledge assembly ...

Asthma Prediction via Affinity Graph Enhanced Classifier: A Machine Learning Approach Based on Routine Blood Biomarkers

Asthma Prediction Enhanced by Affinity Graph-Based Classifier: A Machine Learning Approach Using Routine Blood Biomarkers Background Asthma is a chronic respiratory disease that affects approximately 235 million people worldwide. According to the World Health Organization (WHO), the main characteristic of asthma is airway inflammation, leading to s...

Identification of Autism Spectrum Disorder Using Multiple Functional Connectivity-Based Graph Convolutional Network

The title of this paper is “Identification of Autism Spectrum Disorder Using Multiple Functional Connectivity-based Graph Convolutional Network,” published in the journal “Medical & Biological Engineering & Computing,” volume 62, pages 2133-2144, in 2024. This paper proposes a multiple functional connectivity-based graph convolutional network (mfc-...