Article
Neurosciences
Shudong Zhang, Jingjing Zhou, Jian Cui, Zhifang Zhang, Rui Liu, Yuan Feng, Lei Feng, Yun Wang, Xiongying Chen, Hang Wu, Yuening Jin, Yuan Zhou, Gang Wang
Summary: This study explored the effects of antidepressants on brain networks and individual differences in response. Patients with major depressive disorder (MDD) were scanned before and after a 12-week treatment with escitalopram. Results showed that the decreased subcortical network-ventral attention network connectivity increased after treatment, but within-network connectivity abnormalities persisted. The strength of subcortical network-ventral attention network connectivity at baseline predicted the reduction rate of depression scores.
HUMAN BRAIN MAPPING
(2023)
Article
Clinical Neurology
Jiang Zhang, Hongjie Cui, Huadong Yang, Yuanyuan Li, Dundi Xu, Tianyu Zhao, Huawang Wu, Zhengcong Du, Wei Huang, Chong Wang, Ai Chen, Jiaojian Wang
Summary: This study utilized sliding window method and litekmeans algorithm to investigate the dynamic functional network connectivity in MDD, revealing increased mean dwell time and correlation with depression symptom load in state #5, as well as significantly reduced FNC within FPN in state #7 for MDD patients compared to healthy controls. This new approach of determining optimal window length and number of clusters may facilitate future studies on functional dynamics and provide new evidence to better understand the neuropathology of MDD.
PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY
(2021)
Article
Psychology, Clinical
Mayron Piccolo, Emily L. Belleau, Laura M. Holsen, Madhukar H. Trivedi, Ramin V. Parsey, Patrick J. McGrath, Myrna M. Weissman, Diego A. Pizzagalli, Kristin N. Javaras
Summary: This study found that hyperphagic MDD may be associated with altered activity and connectivity between interoceptive and reward regions.
PSYCHOLOGICAL MEDICINE
(2023)
Article
Neurosciences
Lan Mei, Yuting Wang, Chunyang Liu, Jingping Mou, Yizhi Yuan, Lihua Qiu, Qiyong Gong
Summary: Some important clinical characteristics of major depressive disorder (MDD) differ between sexes. This study explored abnormal brain activity in MDD patients and its relationship to clinical manifestations in male and female patients. The results suggest that sex-specific abnormal brain activity might be a potential pathomechanism contributing to different symptoms in male and female MDD patients.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Clinical Neurology
Aron T. Hill, Reza Zomorrodi, Itay Hadas, Faranak Farzan, Daphne Voineskos, Alanah Throop, Paul B. Fitzgerald, Daniel M. Blumberger, Zafiris J. Daskalakis
Summary: Magnetic seizure therapy (MST) is emerging as a safe and effective experimental intervention for treatment resistant major depressive disorder (MDD) with minimal cognitive side-effects. Resting-state brain dynamics show widespread changes following MST in MDD patients, with theta connectivity potentially serving as a physiological marker of treatment response. Future prospective studies are needed to confirm these initial findings.
PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY
(2021)
Article
Engineering, Biomedical
Bingtao Zhang, Guanghui Yan, Zhifei Yang, Yun Su, Jinfeng Wang, Tao Lei
Summary: By constructing brain functional networks based on resting state EEG, alterations in brain synchronization in different brain regions of MDD patients were identified, and potential biomarkers were discovered with a highest classification accuracy of 93.31%. The findings also suggest a random trend in the brain function network of MDD patients and a weakening of small world characteristics.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2021)
Article
Medicine, General & Internal
Shu-Hsien Chu, Keshab K. Parhi, Melinda Westlund Schreiner, Christophe Lenglet, Bryon A. Mueller, Bonnie Klimes-Dougan, Kathryn R. Cullen
Summary: The study investigated brain changes in functional connectivity and functional network topology after 8-week SSRI treatments in unmedicated adolescents with MDD. Changes were observed in frontal-limbic, temporal, and default mode networks, with topological analysis showing decreased clustering coefficient and smallworldness after treatment. Regional changes were observed in specific brain regions, and frequency dependence was observed in limbic-cortical connectivity changes.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Neuroimaging
Guoshi Li, Yujie Liu, Yanting Zheng, Ye Wu, Danian Li, Xinyu Liang, Yaoping Chen, Ying Cui, Pew-Thian Yap, Shijun Qiu, Han Zhang, Dinggang Shen
Summary: This study demonstrates that major depressive disorder is primarily characterized by abnormal circuit interactions in the executive-limbic network rather than the default mode-salience network. Reduced frontoparietal effective connectivity in the former network potentially contributes to hypoactivity in the dorsolateral prefrontal cortex, while decreased intrinsic inhibition combined with increased excitation in the superior parietal cortex leads to amygdala hyperactivity. This activation imbalance in the PFC-amygdala circuit is prevalent in major depressive disorder.
NEUROIMAGE-CLINICAL
(2021)
Article
Behavioral Sciences
P. M. Briley, L. Webster, C. Boutry, W. J. Cottam, D. P. Auer, P. F. Liddle, R. Morriss
Summary: This systematic review explores the differences in resting-state brain connectivity associated with comorbid anxiety in individuals with MDD. The findings suggest that dysconnectivity between the amygdala and other brain networks, as well as abnormalities in default mode network connectivity, may play a role in the co-occurrence of anxiety and MDD.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2022)
Article
Neuroimaging
Xueling Zhu, Fulai Yuan, Gaofeng Zhou, Jilin Nie, Dongcui Wang, Ping Hu, Lirong Ouyang, Lingyu Kong, Weihua Liao
Summary: This study suggests that cross-network interaction can serve as an effective biomarker for the clinical diagnosis of MDD, potentially revealing the underlying pathological mechanism for major depression. It also confirms the reliable application of MVPA in discriminating MDD patients from healthy controls.
BRAIN IMAGING AND BEHAVIOR
(2021)
Article
Neurosciences
Shuting Sun, Peng Yang, Huayu Chen, Xuexiao Shao, Shanling Ji, Xiaowei Li, Gongying Li, Bin Hu
Summary: This study found that ECT treatment can alter the topology organization of functional brain networks in patients with depression, and these changes are associated with clinical remission.
FRONTIERS IN HUMAN NEUROSCIENCE
(2022)
Article
Neurosciences
Lijun Song, Xu Liu, Wenbo Yang, Qian Chen, Han Lv, Zhenghan Yang, Wenhu Liu, Hao Wang, Zhenchang Wang
Summary: This study investigated the network characteristics of the resting-state functional network in patients with stage 5 chronic kidney disease (CKD5 ND) and the underlying pathological mechanism. The results showed that all CKD5 ND patients exhibited changes in functional network properties and were closely associated with mild cognitive impairment. The topological property changes in CKD5 ND patients were dominated by basal ganglia areas, which may help understand the underlying pathological mechanisms of cognitive impairment in CKD5 ND.
Article
Neurosciences
Uwe Riedmann, Andreas Fink, Bernhard Weber, Karl Koschutnig
Summary: Grey matter volume reductions were observed in the right superior temporal gyrus (rSTG) in young adults who learned to ride a unicycle, possibly indicating brain tissue reorganization for automated and efficient coordination of postural control. The study applied graph theory to examine changes in the functional brain network and found that after three weeks of unicycle training, the local efficiency of the rSTG significantly increased, suggesting an increase in fault tolerance and decentralization of specific functions. This increased local efficiency may indicate improved task efficiency through decentralization of crucial balance functions.
Article
Neurosciences
Serafeim Loukas, Lara Lordier, Djalel-Eddine Meskaldji, Manuela Filippa, Joana Sa de Almeida, Dimitri Van de Ville, Petra S. Hueppi
Summary: Research indicates that even during the newborn period, familiar music and unfamiliar music are processed differently by the brain. After music listening, functional connectivity between brain regions in all newborns is modulated. Premature infants exposed to music experience enhanced functional connectivity between brain regions after listening to music.
HUMAN BRAIN MAPPING
(2022)
Article
Neurosciences
Gui Zhang, Qian Xiao, Chun Wang, Weijia Gao, Linyan Su, Guangming Lu, Yuan Zhong
Summary: This study aimed to investigate the differences in clinical, cognitive function, and intrinsic brain networks between pediatric bipolar disorder patients with first-episode depression and first-episode mania. The results showed differences in cognitive functions such as attention and visual memory between first-episode depression and mania, as well as differences in brain activation in specific regions. These findings shed light on the different developmental paths of bipolar disorder.
Article
Automation & Control Systems
Tong Chen, Xing-Cong Zhao, Hang Zhou, Guang-Yuan Liu
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2016)
Article
Neurosciences
Guangjie Yuan, Guangyuan Liu, Dongtao Wei, Gaoyuan Wang, Qiang Li, Mingming Qi, Shifu Wu
HUMAN BRAIN MAPPING
(2018)
Article
Computer Science, Artificial Intelligence
Wanhui Wen, Guangyuan Liu, Zhi-Hong Mao, Wenjin Huang, Xu Zhang, Hui Hu, Jiemin Yang, Wenyan Jia
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2020)
Article
Automation & Control Systems
Yong Liao, Xuewu Dai, Guangyuan Liu, Yang Yang, Shizhong Yang
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2013)
Article
Computer Science, Artificial Intelligence
Tong Chen, Peter Yuen, Mark Richardson, Guangyuan Liu, Zhishun She
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2014)
Article
Computer Science, Artificial Intelligence
Wanhui Wen, Guangyuan Liu, Nanpu Cheng, Jie Wei, Pengchao Shangguan, Wenjin Huang
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2014)
Article
Neurosciences
Liang Shi, Roger E. Beaty, Qunlin Chen, Jiangzhou Sun, Dongtao Wei, Wenjing Yang, Jiang Qiu
Article
Neurosciences
Qiang Li, Guangyuan Liu, Dongtao Wei, Ying Liu, Guangjie Yuan, Gaoyuan Wang
Article
Mathematical & Computational Biology
Jin Zhang, Guangjie Yuan, Huan Lu, Guangyuan Liu
Summary: The study utilized ECG signals to capture the ILFS emotion, achieving an identification accuracy of 69.07% through feature extraction and classifier recognition. ECG signals can reflect the participant's desire for romance, helping to determine the right partner.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2021)
Article
Neurosciences
Guangjie Yuan, Wenguang He, Guangyuan Liu
Summary: This study provides early evidence for the recognition of initial romantic attraction (IRA) based on EEG signals. The best classification accuracy of 85.2% was achieved using feature vectors that mainly included the asymmetry features in the alpha, beta, and theta rhythms.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Engineering, Biomedical
Jialan Xie, Ping Lan, Shiyuan Wang, Yutong Luo, Guangyuan Liu
Summary: This study investigates whether there are differences in brain activation states for six basic emotions between VR-3D and Screen-2D modalities. The results show that happiness and surprise have greater differences in brain frequency bands in the VR-3D modality, while sadness, fear, disgust, and anger have greater differences in the frontal and occipital regions. Additionally, the power feature subsets of brain activation states can classify the six emotions accurately in both modalities. Overall, there are significant differences in the induction of discrete emotions in VR-3D and Screen-2D modalities, with greater brain activation in the VR-3D modality.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Donghui Li, Xingcong Zhao, Guangjie Yuan, Ying Liu, Guangyuan Liu
Summary: Facial expression recognition, an important part of human-computer interactions, has seen significant progress with the development of capsule network (CapsNet) in comparison to traditional convolutional neural networks (CNN) and fully convolutional networks (FCN). Capsules in CapsNet can learn posture information, enhancing the robustness of facial expression recognition in complex real-world environments.
APPLIED INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Shanbin Zhang, Guangyuan Liu, Xiangwei Lai
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS
(2015)
Article
Computer Science, Information Systems
Zhaofang Yang, Guangyuan Liu
JOURNAL OF INTERNET TECHNOLOGY
(2015)