brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Academic report: brainlife.io: A decentralized and open-source cloud platform supporting neuroscience research Background and Motivation Neuroscience research is rapidly developing, and the advancement of data standardization, management, and processing tools has made research more rigorous and transparent. However, this also brings about complex d...

Prediction error processing and sharpening of expected information

Prediction error processing and sharpening of expected information

Scientific Report Background Introduction Perception and neuronal processing of sensory information are largely influenced by prior expectations. Perception is not merely passive reception, but an active inferential process by combining existing sensory information with prior information based on past experience and current context. The combination...

A GRU-CNN Model for Auditory Attention Detection using Microstate and Recurrence Quantification Analysis

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 ...

Revealing the Mechanisms of Semantic Satiation with Deep Learning Models

Revealing the Mechanisms of Semantic Satiation with Deep Learning Models

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...

Representation of Internal Speech by Single Neurons in Human Supramarginal Gyrus

“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...

Cortex-wide Topography of 1/f-exponent in Parkinson’s Disease

Cortex-wide Topography of 1/f-exponent in Parkinson’s Disease

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...

k-emophone: a mobile and wearable dataset with in-situ emotion, stress, and attention labels

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

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...