Differentiation of schizophrenia by combining the spatial EEG brain network patterns of rest and task P300

F Li, J Wang, Y Liao, C Yi, Y Jiang, Y Si… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
The P300 is regarded as a psychosis endophenotype of schizophrenia and a putative
biomarker of risk for schizophrenia. However, the brain activity (ie, P300 amplitude) during …

Altered default mode network causal connectivity patterns in autism spectrum disorder revealed by Liang information flow analysis

J Cong, W Zhuang, Y Liu, S Yin, H Jia, C Yi… - Human Brain …, 2023 - Wiley Online Library
Autism spectrum disorder (ASD) is a pervasive developmental disorder with severe
cognitive impairment in social communication and interaction. Previous studies have …

A survey of brain network analysis by electroencephalographic signals

C Luo, F Li, P Li, C Yi, C Li, Q Tao, X Zhang, Y Si… - Cognitive …, 2022 - Springer
Brain network analysis is one efficient tool in exploring human brain diseases and can
differentiate the alterations from comparative networks. The alterations account for time …

[HTML][HTML] Inter-subject P300 variability relates to the efficiency of brain networks reconfigured from resting-to task-state: evidence from a simultaneous event-related …

F Li, Q Tao, W Peng, T Zhang, Y Si, Y Zhang, C Yi… - NeuroImage, 2020 - Elsevier
The P300 event-related potential (ERP) varies across individuals, and exploring this
variability deepens our knowledge of the event, and scope for its potential applications …

Predicting individual decision-making responses based on the functional connectivity of resting-state EEG

Y Si, L Jiang, Q Tao, C Chen, F Li, Y Jiang… - Journal of Neural …, 2019 - iopscience.iop.org
Objective. Despite increasing evidence revealing the relationship between task-related
brain activity and decision-making, the association between resting-state functional …

Identification and analysis of autism spectrum disorder via large‐scale dynamic functional network connectivity

W Zhuang, H Jia, Y Liu, J Cong, K Chen… - Autism …, 2023 - Wiley Online Library
Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with severe
cognitive impairment. Several studies have reported that brain functional network …

L1-norm based time-varying brain neural network and its application to dynamic analysis for motor imagery

P Li, C Li, JC Bore, Y Si, F Li, Z Cao… - Journal of Neural …, 2022 - iopscience.iop.org
Objective. Electroencephalogram (EEG)-based motor imagery (MI) brain-computer interface
offers a promising way to improve the efficiency of motor rehabilitation and motor skill …

Constructing large-scale cortical brain networks from scalp EEG with Bayesian nonnegative matrix factorization

C Yi, C Chen, Y Si, F Li, T Zhang, Y Liao, Y Jiang… - Neural Networks, 2020 - Elsevier
A large-scale network provides a high hierarchical level for understanding the adaptive
adjustment of the human brain during cognition processes. Since high spatial resolution is …

Analysis of dynamic network reconfiguration in adults with attention-deficit/hyperactivity disorder based multilayer network

X Cui, C Ding, J Wei, J Xue, X Wang, B Wang… - Cerebral …, 2021 - academic.oup.com
Attention-deficit/hyperactivity disorder (ADHD) has been reported exist abnormal topology
structure in the brain network. However, these studies often treated the brain as a static …

Large-scale cortical network analysis and classification of MI-BCI tasks based on Bayesian nonnegative matrix factorization

S Yu, B Mao, Y Zhou, Y Liu, C Yi, F Li… - … on Neural Systems …, 2024 - ieeexplore.ieee.org
Motor imagery (MI) is a high-level cognitive process that has been widely applied to clinical
rehabilitation and brain-computer interfaces (BCIs). However, the decoding of MI tasks still …