Overview and Report: Application of GRU-CNN Model Based on Microstate and Recurrence Quantification Analysis in Auditory Attention Detection Background and Research Motivation Attention, as a cognitive ability, plays a crucial role in the perception process, helping humans to focus on specific objects while ignoring other distractions in a complex ...

Deep Learning Model Reveals Mechanisms of Semantic Satiation Semantic satiation, the phenomenon where a word or phrase loses its meaning after being repeated many times, is a well-known psychological phenomenon. However, the micro-neural computational principles underlying this mechanism remain unknown. This paper uses a continuous coupled neural n...

“Internal Speech Representation by Single Neurons in Human Supramarginal Gyrus” Scientific Report Background In recent years, Brain-Machine Interfaces (BMIs) technology has made significant advancements in the field of speech decoding. BMIs enable those who have lost the ability to speak due to disease or injury to communicate again by converting b...

Topographical Map of the 1/f Index in the Whole Brain for Parkinson’s Disease Authors: Pascal Helson, Daniel Lundqvist, Per Svenningsson, Mikkel C. Vinding, Arvind Kumar Research Background Parkinson’s Disease (PD) is a progressive and debilitating brain disorder primarily characterized by motor dysfunction but also affecting perceptual and cogniti...

Scientific Data Report | K-emophone: A Mobile and Wearable Dataset with On-site Emotion, Stress, and Attention Labels Background With the proliferation of low-cost mobile and wearable sensors, numerous studies have leveraged these devices to track and analyze human mental health, productivity, and behavioral patterns. However, despite the developme...

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 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...

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...

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...

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...