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Current status, trends, and recommendations of EEG microstates research

Current Psychology 2025年 1-14页

作者： Han, Shangfeng Su, Wenxiu Li, Wenwen Ma, Yankun Luo, Yuejia Department of Psychology Center for Brain and Cognitive Sciences School of Education Guangzhou University Guangzhou China The State Key Lab of Cognitive and Learning Faculty of Psychology Beijing Normal University Beijing China Institute for Neuropsychological Rehabilitation University of Health and Rehabilitation Sciences Qingdao China School of Psychology Shenzhen University Shenzhen China Faculty of Psychology Beijing Normal University No. 19 Xinjiekouwai St Haidian District Beijing 100875 China School of Education Guangzhou University No. 230 Waihuanxi Ave. Panyu District Guangzhou 510006 China

EEG microstates provides a unique perspective on the dynamic functional organization of the brain, has attracted considerable attention. This study conducted a bibliometric analysis of 441 articles retrieved from the Web of Science database using CiteSpace. The analysis focused on four key areas of EEG microstates: The academic network, classification and function, reliability of parameter, and primary research topics. Results revealed a steady increase in annual publications within this field. The academic network was dominated by the countries (including Switzerland, the United states, and China), the journal NeuroImage, and prominent researchers such as Koenig, Michel, and Lehmann. Determining the optimal number and the functions of EEG microstate classes were attributed to the clustering algorithms and validation criteria. The reliability of EEG microstate parameters varied, with mean duration demonstrating high reliability while the lower reliability was observed for transition probabilities (TP). Primary research topics that showed the trends in microstate studies encompassed cognitive function exploration, developmental changes, psychiatric disorder diagnosis, and emotion recognition. We recommend that future research focus on promoting international collaboration and establishing standardized labeling systems for EEG microstate classes. Greater attention should be directed towards employing robust metrics, such as mean duration (MD), while adopting a cautious approach to the use of TP. Furthermore, advancing task-based investigations and prioritizing clinical applications are essential for driving progress and fostering meaningful developments in EEG microstate research. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Biomarkers CiteSpace EEG microstates Resting-state networks

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NEURO-cognitive MECHANISMS UNDERLYING THE EMOTIONAL MODULATION OF WORD READING

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Chinese Science Bulletin 2006年第4期51卷 377-384页

作者： PENG Danling HU Zhiguo LIU Hongyan LIU Conghui DING Guosheng State Key Lab of Cognitive Neuroscience and Learning Beijing Normal University Beijing 100875 China

A novel neural model for emotional modulation of word reading is proposed. This model has four principal hypotheses: the dominant activa-tion region hypothesis, the emotional modulation hypothesis, the attentional level hypothesis, and the interaction hypothesis. Four lines of research were reviewed to provide evidence for these hypotheses: (1) neuro-cognitive studies on the mechanisms of word reading (i.e., neural networks for reading); (2) studies on the influence of words’ emotional valence on word reading; (3) studies of the effect of attention on word reading; and (4) studies on emotional modulation of word reading under different attentional levels.

关键词：文字阅读情绪调节认知机制神经模型注意力

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Variable-frame CNNLSTM for Breast Nodule Classification using Ultrasound Videos

arXiv

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arXiv 2025年

作者： Cui, Xiangxiang Li, Zhongyu Fan, Xiayue Huang, Peng Wang, Ying Yang, Meng Chang, Shi Zhu, Jihua The State Key Lab of Cognitive Neuroscience and Learning Beijing Normal University China School of Software Engineering Xi’an Jiaotong University China Center for Immunological and Metabolic Diseases The First Affiliated Hospital of Xi’an Jiaotong University China Department of General Surgery Xiangya Hospital Central South University China Co. Ltd China Department of general surgery The Second Hospital of Hebei Medical University China

Purpose: The intersection of medical imaging and artificial intelligence has become an important research direction in intelligent medical treatment, and deep learning can analyze and calculate medical images and participate in clinical diagnosis. In order to improve the dataset utilization, the method supporting the training of variable frame datasets and the automatic extraction of ultrasonic features combined with deep learning is designed to improve the dataset utilization rate, which has important research value in ultrasound classification diagnosis. There is no extraction of time series features for the existing keyframe classification method. The ultrasonic video classification work based on three-dimensional convolution requires the same number of video frames for different patients, and the efficiency of extracting features and the classification performance of the model are poor. In this work, We designed the ultrasound video classification method, realizes the training of ultrasound datasets with different video frame numbers, which increases the utilization rate of datasets, optimizes Spatio-temporal feature extraction, and improves classification accuracy. Methods: This paper proposed video classification methods based on CNN and LSTM. Moreover, to support variable-frame training, we introduce the processing scheme of long and short sentences in NLP into video classification for the first time. We reduce the dimension of the CNN extracted image features to 1x512 and then sort and compress the feature vectors and input them into LSTM for training. Specifically, the feature vectors are sorted by the number of patient video frames and populated with padding value 0 to form a variable batch. The invalid padding values in the batch are compressed and then entered into LSTM for training, saving computing resources. To calculate subsequent indicators, it is necessary to restore the output dimension to the input dimension by padding filling. To summarize, the

关键词： Convolutional neural networks

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Effects of violent and non-violent computer video games on explicit and implicit aggression

Journal of Software

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Journal of Software 2010年第9期5卷 1014-1021页

作者： Zhang, Xuemin Liu, Chang Wang, Langlang Piao, Qiuhong Beijing Normal University School of Psychology State Key Lab of Cognitive Neuroscience and Learning Beijing 100875 China

The effect of violent media on aggression has always been highly concerned by the public. The effect of violent video game has been studied by researchers for many years, while how the interaction (competition and cooperation) work during video game play is still little known. In present study, the effect of non-violent video games on aggression was tested by experimental design. Participants were assigned to 6 groups to play a violent video game or a nonviolent video game, and he or she played competitively or cooperatively with another participant, or played the game alone. Competitive Reaction Time Task was used to test aggressive behavior. EAST task and SHS scale were used to test aggressive cognition and affect. The results indicated both violent content and competition can arouse aggressive cognition and aggressive behavior. Only violent content can arouse aggressive affect. Cooperation has little effect on explicit and implicit aggression. © 2010 Academy Publisher.

关键词： Human computer interaction

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Comparison of three group ICA methods for multi-subject fMRI data analysis

Comparison of three group ICA methods for multi-subject fMRI...

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2011 International Conference on Information Science and Technology, ICIST 2011

作者： Hui, Mingqi Yao, Li Long, Zhiying State Key Lab. of Cognitive Neuroscience and Learning Beijing Normal University Beijing China State Key Lab. of Cognitive Neuroscience and Learning School of Information Science and Technology Beijing Normal University Beijing China

ISBN: (纸本)9781424494408

Since spatial independent component analysis (sICA) was introduced to fMRI data analysis of single subject by Mckeown (1998), several group ICA approaches including subject-specific ICA, across-subject averaging, temporal/spatial concatenation and tensor probabilistic ICA (PICA) have been proposed to generate group inference over a group of subjects. By far, the subject-specific ICA, temporal concatenation method and tensor PICA have been applied to fMRI data analysis. Among the three methods, both temporal concatenation method and tensor PICA are the most widely used. However, there hasn't been any comparison of subject-specific ICA, temporal concatenation method and tensor PICA. The current study aims at comparing the three group ICA methods at various noise levels. Simulated experiment based on human resting fMRI data revealed that tensor PICA provided the best overall performance due to the highest spatial detection power and relatively more accurate estimation of time course. Temporal concatenation method provided moderate performance in terms of relatively higher spatial detection power and simpler algorithm. Subject-specific method showed the worst spatial detection power and was the most time consuming in component selection. © 2011 IEEE.

关键词： Independent component analysis

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Effects of action video game on attention distribution: A cognitive study

Effects of action video game on attention distribution: A co...

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作者： Zhang, Xuemin Yan, Bin Shu, Hua School of Psychology State Key Lab of Cognitive Neuroscience and Learning Beijing Normal University Beijing 100875 China

ISBN: (纸本)9783642105111

Based on the previous researches, Flanker compatibility effect paradigm was applied to explore the degree where people process the visual information presented on to-be-ignored locations. In present study, this paradigm was used to investigate attention distribution of Video Game Players (VGPs) and Non Video Game Players (NVGPs). The results suggested, under low perceptual load, VGPs tried to focus their attention on the task at-hand whereas the NVGPs tried to explore the adjacent locations with the left-over resources from the research task;however, under high perceptual load, the players would process the visual information at the adjacent locations of the target with the left-over resources, because they had comparatively greater attention capability, whereas the non-players focused their attention on the target locations to finish the search task. To conclude, the present study suggested that action video game play could not only enhance the attention capacity but also cause a different way of attention distribution in different perceptual load situations. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Location

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RETRACTED ARTICLE: Effect of gaze direction and face expression on visual reflexive attention

RETRACTED ARTICLE: Effect of gaze direction and face express...

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2009 2nd International Conference on Education Technology and Training, ETT 2009

作者： Guan, Xin Wang, Qi Zhang, Ji Zhang, Xue-Min Beijing Normal University School of Psychology State Key Lab. of Cognitive Neuroscience and Learning Beijing 100875 China

ISBN: (纸本)9780769539362

As important social clues, gaze direction and expression usually influence people's social interaction in their communication, and facial cognition is also a hot topic in social cognitive study. In our studies, by comparing facial cognition in upright and inverted face, considering both gaze direction and expression, we tried to explore the mechanism of gaze and expression processing by the method of Posner, and explored sex difference in it. Results indicated that gaze direction could act as a central cue and brought out benefit effect and cost effect only when face is upright. While negative expression would act as an abstractor and prolonged the reflexive attention to target also only in upright face, which means expression and gaze direction were both processed by holistic with the face. What's more, we found sex difference in these two processing. © 2009 IEEE.

关键词： Expression Gaze direction Holistic hypothesis Inversion effect Reflexive attention

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Object category classification of fMRI data using support vector machine combined with deactivation voxel selection

Object category classification of fMRI data using support ve...

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Conference on Medical Imaging - Biomedical Applications in Molecular, Structural and Functional Imaging

作者： Yan, Caifeng Song, Sutao Yao, Li Guo, Xiaojuan Beijing Normal Univ Coll Informat Sci & Technol Beijing 100875 Peoples R China Beijing Normal Univ State Key Lab Cognitive Nuerosci & Learning Beijing Peoples R China

ISBN: (纸本)9780819489661

Support Vector Machine (SVM) is an accurate pattern recognition method which has been widely used in functional MRI (fMRI) data classification. Voxel selection is a very important part in classification. In general, voxel selection is based on brain regions associated with activation caused by different experiment conditions or stimulations. However, negative blood oxygenation level-dependent responses (deactivation) which have also been found in humans or animals contribute to the classification of different cognitive tasks. Different from traditional studies which focused merely on the activation voxel selection methods, our aim is to investigate the deactivation voxel selection methods in the classification of fMRI data using SVM. In this study, three different voxel selection methods (deactivation, activation, the combination of deactivation and activation) are applied to decide which voxel is included in SVM classifier with linear kernel in classifying 4-category objects on fMRI data. The average accuracies of deactivation classification were 73.36%(house vs. face), 60.34%(house vs. car), 60.94%(house vs. cat), 71.43%(face vs. car), 63.17%(face vs. cat) and 61.61%(car vs. cat). The classification results of deactivation were significantly above the chance level which implies the deactivation is informative. The accuracies of combination of activation and deactivation method were close to that of activation method, and it was even better for some representative subjects. These results suggest deactivation provides useful information in the object category classification on fMRI data and the method of voxel selection based on both activation and deactivation will be a significant method in classification in the future.

关键词： deactivation feature selection classification fMRI SVM

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Effect of multiplayer interactive violent video games on players' explicit and implicit aggression

Effect of multiplayer interactive violent video games on pla...

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2012 International Workshops on Web-Based learning, ICWL 2012 - KMEL, SciLearn, and CCSTED

作者： Liu, Chang Zhang, Xuemin Sun, Fawei Wang, Langlang Fu, Xinyuan Zhao, Xia School of Psychology Beijing Key Lab. of Applied Experimental Psychology Beijing Normal University Beijing 100875 China State Key Lab. of Cognitive Neuroscience and Learning Beijing Normal University Beijing 100875 China

ISBN: (纸本)9783662434536

While violent video games are of great concern to the public for their potential impact of inducing aggression, recent changes in the dynamics of gaming has rendered study of such phenomena quite challenging. The impact of interpersonal factors on players' aggression has not yet to be fully understood. The present experiment was designed to test explicit and implicit aggression caused by multiplayer interactive violent games. 56 male participants were randomly assigned to three groups (four-player group, double-player group and solo-play group). Extrinsic Affective Simon Task (EAST) and words evaluation task (WET) were used to test implicit and explicit aggressive cognition respectively. Competitive Reaction Time Task (CRT) was for measuring explicit aggressive behavior. Results showed: (1) Participants with low-trait aggression were more aggressive in implicit aggressive cognition when playing in four-player group than in other two groups. (2) Explicit aggressive cognition was affected by both interactive modes and trait aggression without interaction. The solo-play group was more explicitly aggressive than the four-player group. High-trait aggression group was more aggressive than low-trait group. (3) Participants' aggressive behavior decreased as the number of players increased. Factors that affect violent video games' impact on players' aggression were discussed. © 2014 Springer-Verlag.

关键词： Human computer interaction

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Applications of Psychological Principles and Fatigue Feedback-learning Technique in E-learning

Applications of Psychological Principles and Fatigue Feedbac...

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ETT and GRS International Education Technology and Training, and International Workshop on Geoscience and Remote Sensing

作者： Xuemin Zhang Xiaonan Liu Pan Lian Bing Liu Bin Yang Beijing Normal University State Key Lab of Cognitive Neuroscience and Learning Beijing China Shuang Liao City State Key Lab of Cognitive Neuroscience and Learning Jinlin China

As the rapid development of information technology, the learning style has been changing tremendously. E-learning as the result of this technology development, it has been changing our work, life and learning. The essential part of e-learning is Internet and other digital device, Internet has played an important role in global education and training. As a important work, life and learning style, e-learning has its special feature and function. However, during the e-learning process, physiological and psychological fatigue caused by human computer interaction and learning process becomes an important problems, it is also one of the most obstacles to efficient learning working. So, how to overcome this problem is the focus of e-learning. In present paper, we discuss fatigue feedback technique used in e-learning and its application in e-learning process.

关键词： Psychology Fatigue Electronic learning Computer science education Internet Information technology Mobile computing Educational technology Geoscience and remote sensing Neuroscience

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