Deep-Learning-Based Motor Imagery EEG Classification by Exploiting the Functional Connectivity of Cortical Source Imaging

Deep-learning-based Motor Imagery EEG Classification by Exploiting the Functional Connectivity of Cortical Source Imaging Research Background and Motivation A brain-computer interface (BCI) is a system that directly decodes and outputs brain activity information without relying on related neural pathways and muscles, thereby achieving communication...

Study on Different Brain Activation Rearrangement during Cognitive Workload from ERD/ERS and Coherence Analysis

Study on Different Brain Activation Reorganization during Cognitive Load: ERD/ERS and Coherence Analysis Academic Background When humans engage in imagination, movement, or cognitive tasks, their brain functional activity patterns and activated regions differ. These pattern changes are also reflected in changes in brain electrical activity, which c...

Physiological Data for Affective Computing: The Affect-HRI Dataset

Application of Physiological Data in Human-Robot Interaction with Anthropomorphic Service Robots: Affect-HRI Dataset Background and Significance In interactions between humans and humans, as well as humans and robots, the interacting entity can influence human emotional states. Unlike humans, robots inherently cannot exhibit empathy and thus cannot...

Speech-Induced Suppression During Natural Dialogues

During human communication, the brain processes self-generated speech and others’ speech differently, a phenomenon known as the Speech-Induced Suppression (SIS) mechanism. This mechanism involves the motor efference copy in the perception pathway, functioning similar to an “echo” that helps filter internally generated signals to avoid confusing the...

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...