Article
Neurosciences
Yutong Zhang, Ziwen Wang, Jiarong Du, Jixin Liu, Tao Xu, Xiao Wang, Mingsheng Sun, Yi Wen, Dehua Li, Huaqiang Liao, Yu Zhao, Ling Zhao
Summary: Acupuncture is beneficial in treating menstrual migraine without aura patients by improving emotional symptoms and clinical manifestations. True acupuncture has a better effect on reducing migraine attack frequency compared to sham acupuncture, with distinct modulation effects on emotional disorders and pain perception by targeting different brain regions.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Clinical Neurology
Zhaoxia Qin, Hang Qu, Huai-Bin Liang, Qichen Zhou, Wei Wang, Min Wang, Jian-Ren Liu, Xiaoxia Du
Summary: A study using resting-state functional magnetic resonance imaging found differences in effective connectivity among regions in the trigeminal vascular system between patients with migraine without aura (MWoA) and healthy controls. These results provide further evidence of the involvement of disturbed trigeminovascular nociceptive pathways in the pathophysiology of migraine.
Article
Clinical Neurology
Shanshan Liu, Shilei Luo, Tianwei Yan, Wen Ma, Xiangyu Wei, Yilei Chen, Songhua Zhan, Bo Wang
Summary: The study found that patients with migraine had lower ReHo values in the cerebellum, which increased after acupuncture therapy. Long-term acupuncture significantly improved migraine symptoms and mood, with effects lasting for at least 6 months. After 12 acupuncture sessions, there were significant increases in cerebellum and angular gyrus activation in the migraine group.
FRONTIERS IN NEUROLOGY
(2021)
Article
Clinical Neurology
Yansong Li, Guoliang Chen, Jing Lv, Lei Hou, Zhao Dong, Rongfei Wang, Min Su, Shengyuan Yu
Summary: This study examined EEG microstates in migraine patients and found that microstate classes B and D had higher time coverage and occurrence in migraine patients compared to healthy controls, while microstate class C exhibited lower time coverage and occurrence. The duration of microstate class C was negatively correlated with headache-related disability in migraine patients. Microstate syntax analysis also revealed significant differences in transition probabilities between the two groups.
JOURNAL OF HEADACHE AND PAIN
(2022)
Article
Clinical Neurology
Xiaobin Huang, Di Zhang, Peng Wang, Cunnan Mao, Zhengfei Miao, Chunmei Liu, Chenjie Xu, Xindao Yin, Xinying Wu
Summary: Granger causality analysis (GCA) was used to investigate the directional effective connectivity of the amygdala in migraine patients, revealing altered connectivity patterns related to disease duration. The findings suggest that neurolimbic pain networks contribute to abnormalities in multisensory integration and pain modulation deficits in migraine without aura (MwoA) patients.
JOURNAL OF HEADACHE AND PAIN
(2021)
Article
Behavioral Sciences
Maryam Tabiee, Ahmad Azhdarloo, Mohammad Azhdarloo
Summary: This study aimed to compare executive functions in children with ADHD with or without RD by monitoring brain connectivity patterns. The findings revealed that children with ADHD and comorbid RD showed more abnormal brain connectivity patterns, which can serve as a useful marker for better recognizing ADHD and comorbid disabilities.
BRAIN AND BEHAVIOR
(2023)
Article
Clinical Neurology
Coralie Mignot, Vanda Faria, Thomas Hummel, Marie Frost, Christoph. M. M. Michel, Gudrun Gossrau, Antje Haehner
Summary: This study investigated the central nervous processing of olfactory and trigeminal stimuli in migraine patients with and without aura. It found that patients with aura had higher event-related potentials amplitudes for trigeminal and olfactory stimulations, as well as higher neural activity in brain areas related to trigeminal and visual processing. Patients with aura also showed decreased neural activity in secondary olfactory structures after olfactory stimulations. The study suggests that there may be hypersensitivity and deficits in engaging secondary olfactory-related structures in patients with aura.
JOURNAL OF HEADACHE AND PAIN
(2023)
Article
Anesthesiology
Kun Liu, Jinming Cheng, Yungang Cao, Keyang Chen, Yan Li, Xi Zhang, LiPeng Dong, Zhihong Wang, Xiaozheng Liu
Summary: This study used a Granger causality analysis-based approach to investigate the resting-state effective connectivity of the bilateral periaqueductal gray (PAG) in migraine patients without aura (MwoA). The results showed increased effective connectivity from the left PAG to the left anterior cingulate gyrus and right postcentral gyrus, as well as increased effective connectivity from the right PAG to the left precentral gyrus. Additionally, there was increased effective connectivity from the left caudate and right middle occipital gyrus to the right PAG. These abnormal effective connectivity patterns may play a crucial role in the neuropathological features, perception, and affection of MwoA.
CLINICAL JOURNAL OF PAIN
(2023)
Article
Neurosciences
Kimberly L. Ray, Nicholas R. Griffin, Jason Shumake, Alexandra Alario, John J. B. Allen, Christopher G. Beevers, David M. Schnyer
Summary: Individuals with remitted depression present abnormal EEG power and connectivity compared to healthy adults and individuals with depression, suggesting potential biomarkers for future depression risk. This study enhances our understanding of resting-state neural correlates in depression and bridges the gap between EEG power and network connectivity dynamics. The examination of remitted depression is crucial for identifying brain-based biomarkers for those at high risk of subsequent depression.
Article
Radiology, Nuclear Medicine & Medical Imaging
Xiaobin Huang, Yujia Gao, Tong Fu, Tongxing Wang, Jun Ren, Di Zhang, Lindong Liu, Shuangqing Deng, Xindao Yin, Xinying Wu
Summary: This study found that patients with menstrual migraine without aura (MRM) have altered resting-state functional networks and directional functional connectivity. These alterations involve brain regions associated with cognitive processes, emotional perception, and migraine attack. These findings are important for understanding the neuro-mechanism of menstrually-related migraine.
QUANTITATIVE IMAGING IN MEDICINE AND SURGERY
(2023)
Review
Medicine, General & Internal
Franz Riederer, Johannes Beiersdorf, Adrian Scutelnic, Christoph J. Schankin, Elena R. Lebedeva
Summary: Approximately one-third of migraine patients experience migraine with aura, which is characterized by visual disturbance, sensory abnormalities, speech problems, or paresis along with the headache attack. This type of migraine is associated with a higher risk of stroke, epilepsy, and anxiety disorder. EEG and MRI findings during migraine auras have been examined to understand the underlying pathophysiology of this condition. EEG studies show no consistent abnormalities during visual auras, while significant EEG abnormalities have been observed in familial hemiplegic migraine and migraine with brain stem aura. MRI studies have revealed changes in perfusion and the appearance of dilated veins in susceptibility-weighted imaging. Detecting cortical spreading depression, a possible cause of migraine aura, is challenging using non-invasive methods. Further research is needed to explore this area.
Review
Clinical Neurology
XiaoGuang Lin, ZhongQuan Yi, XueLing Zhang, QinQin Liu, Hui Zhang, RuYuan Cai, ChaoChun Chen, HongJie Zhang, PanWen Zhao, PingLei Pan
Summary: Migraine is a common disabling disease that can lead to abnormalities in the brain and retina. A meta-analysis showed that RNFL thickness reduction in migraine patients was significant, especially in those with aura, suggesting a potential role for RNFL thickness measurement in differentiating migraine patients from healthy controls.
NEUROLOGICAL SCIENCES
(2021)
Article
Anesthesiology
Li-Ling Hope Pan, Wei-Ta Chen, Yen-Feng Wang, Shih-Pin Chen, Kuan-Lin Lai, Hung-Yu Liu, Fu-Jung Hsiao, Shuu-Jiun Wang
Summary: This study explored the association between cortical oscillations and treatment outcome in patients with chronic migraine. The findings suggest that nonresponsive patients exhibited elevated occipital alpha activity, and changes in migraine attack frequency were associated with baseline occipital alpha power. The study provides insights for developing personalized migraine treatment plans.
Article
Neurosciences
Zilei Tian, Yaoguang Guo, Tao Yin, Qingqing Xiao, Guodong Ha, Jiyao Chen, Shuo Wang, Lei Lan, Fang Zeng
Summary: This retrospective study analyzed resting-state functional connectivity in patients with migraine to identify abnormal pain processing patterns in the brain. The study found significantly different functional connectivity patterns in migraine patients compared to healthy controls, mainly in regions related to pain processing. Acupuncture treatment was shown to partially restore the abnormal functional connectivity patterns and correlate with clinical symptoms.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Clinical Neurology
Xiaolin Wang, Weinan Na, Ying Yang, Wenwen Zhang, Junxia Zhao, Tingting Zhang, Yuanji Zhou, Hua Liu, Dong Zhao, Shengyuan Yu
Summary: In this study, 1444 female patients with migraine without aura (MWA) were divided into three groups (J1, J2, and J3) based on the association of MWA onset with menarche and childbirth. The J1 and J2 groups showed more typical migraine features compared to the J3 group, while the J3 group had higher rates of emotional and sleep disorders, weight management issues, frequent migraine attacks, and medication overuse. This study provides a basis for further understanding and treatment of MWA.
JOURNAL OF HEADACHE AND PAIN
(2023)
Article
Computer Science, Artificial Intelligence
Xiaofei Wang, Hsiang-Ting Chen, Yu-Kai Wang, Chin-Teng Lin
Summary: This article investigates the application of ErrP-based BCI paradigm to control robot movements with implicit commands. ErrP is a neural signal automatically evoked when the machine's behavior deviates from the observer's expectations. The proposed robotic design allows humans to continuously evaluate the robot's intentions and intervene earlier, if necessary before the robot commits an error, addressing the limitations of ErrP-based BCI.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Akshansh Gupta, Dhirendra Kumar, Hanuman Verma, M. Tanveer, Andreu Perez Javier, Chin-Teng Lin, Mukesh Prasad
Summary: This paper presents a novel method for mental task classification using EEG signals. The method includes a unique feature representation technique combining statistical, uncertainty, and memory-based coefficients. The proposed method outperforms existing work in mental task classification.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Zehong Cao, Chin-Teng Lin
Summary: This study investigates the use of global information to accelerate the learning process and increase the cumulative rewards in reinforcement learning (RL) for competition tasks. The proposed RLHC algorithm introduces multiple cooperative critics from a hierarchical framework, allowing agents to access value information from local and global critics. The results show that RLHC outperforms the benchmark algorithm in various competitive tasks.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Chemistry, Multidisciplinary
Alka Rachel John, Zehong Cao, Hsiang-Ting Chen, Kaylena Ehgoetz Martens, Matthew Georgiades, Moran Gilat, Hung T. Nguyen, Simon J. G. Lewis, Chin-Teng Lin
Summary: This study utilized EEG signals to distinguish between the onset of freezing of gait (FOG) and voluntary stopping in patients with advanced Parkinson's disease (PD). By employing a convolutional neural network (CNN), the researchers achieved a high classification accuracy in identifying the transition to FOG from normal walking and voluntary stopping.
APPLIED SCIENCES-BASEL
(2023)
Article
Clinical Neurology
Po-Tso Lin, Yen-Feng Wang, Shu-Shya Hseu, Jong-Ling Fuh, Jiing-Feng Lirng, Jr-Wei Wu, Shu-Ting Chen, Shih-Pin Chen, Wei-Ta Chen, Shuu-Jiun Wang
Summary: This study developed and validated a scoring system to predict the response to the first epidural blood patching in patients with spontaneous intracranial hypotension. Multivariable logistic regression modeling identified factors associated with the response, and a scoring system was developed. The findings were verified in an independent validation cohort.
Article
Psychiatry
Jun-Ding Zhu, Yung-Fu Wu, Shih-Jen Tsai, Ching-Po Lin, Albert C. C. Yang
Summary: Brain-age prediction models were constructed using multimodal MRI, and deviations in aging trajectories in different brain regions of participants with schizophrenia were examined. The results showed accelerated aging in most gray matter regions, especially in the frontal lobe, temporal lobe, and insula. Deviations in aging trajectories were also observed in some white matter tracts. However, no accelerated brain aging was found in functional connectivity maps. These findings provide insights into the neuropathology of schizophrenia.
TRANSLATIONAL PSYCHIATRY
(2023)
Article
Computer Science, Artificial Intelligence
Chin-Teng Lin, Jia Liu, Chieh-Ning Fang, Shih-Ying Hsiao, Yu-Cheng Chang, Yu-Kai Wang
Summary: A new multistream 3-D CNN model with parameter sharing is proposed for EEG analysis, which effectively extracts significant features from EEG data and reduces the risk of overfitting and the number of parameters through a sharing mechanism.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Article
Nanoscience & Nanotechnology
Shaikh Nayeem Faisal, Tien-Thong Nguyen Do, Tasauf Torzo, Daniel Leong, Aiswarya Pradeepkumar, Chin-Teng Lin, Francesca Iacopi
Summary: Three-dimensional micropatterned sensors based on graphene can detect EEG signals from the occipital region of the scalp, enabling the implementation of brain-machine interfaces. These sensors show efficient on-skin contact and comparable signal-to-noise ratios to wet sensors.
ACS APPLIED NANO MATERIALS
(2023)
Article
Geriatrics & Gerontology
Chia-Fen Tsai, Mao-Hsuan Huang, Yung-Shuan Lin, Chun-Yu Chen, Jong-Ling Fuh
Summary: This study validated the Taiwanese version of the MBI-C and found that the total score and subdomains of the MBI-C were associated with decreased health-related quality of life among individuals without dementia.
INTERNATIONAL JOURNAL OF GERIATRIC PSYCHIATRY
(2023)
Article
Dentistry, Oral Surgery & Medicine
K. L. Bindels, M. C. Verhoeff, N. Su, F. V. Knijn, G. Aarab, J. L. Fuh, C. -s. Lin, F. Lobbezoo
Summary: This study investigated the factors associated with swallowing performance in older adults, including cognitive function, neuroanatomical factors, and demographical factors. It found that a thinner cortex of the right supramarginal gyrus and being an older female were associated with poorer swallowing performance. Additionally, cortical volume was found to differ more frequently between individuals with and without cognitive impairment compared to cortical thickness.
JOURNAL OF ORAL REHABILITATION
(2023)
Article
Clinical Neurology
Wei-Chia Huang, Chia-Yueh Hsu, Chia-Ming Chang, Albert C. Yang, Shih-Cheng Liao, Shu-Sen Chang, Chi-Shin Wu
Summary: No previous studies have investigated the association between psychiatrist density and suicide, accounting for individual- and area-level characteristics. This study found that increased psychiatrist density was associated with decreased suicide risk.
PSYCHIATRY AND CLINICAL NEUROSCIENCES
(2023)
Article
Anesthesiology
Chun-Ning Ho, Pei-Han Fu, Kuo-Chuan Hung, Li-Kai Wang, Yao-Tsung Lin, Albert C. Yang, Chung-Han Ho, Jia-Hui Chang, Jen-Yin Chen
Summary: This study developed a prediction model using the Insomnia Severity Index (ISI), heart rate variability (HRV), and other factors to predict the likelihood of higher postoperative pain. The results showed that higher ISI scores and parasympathetic activity, as well as loss of fractal dynamics, were associated with higher pain scores, while laparoscopic surgery was associated with lower pain scores. A multiple logistic model was constructed to predict the severity of postoperative pain.
Review
Computer Science, Artificial Intelligence
Rahul Sharma, Tripti Goel, M. Tanveer, C. T. Lin, R. Murugan
Summary: This article provides a detailed review of automated early AD diagnosis using DL methods published from 2009 to 2022. It introduces popular imaging modalities, discusses early biomarkers for AD diagnosis using neuroimaging scans, reviews the popular online available data sets widely used, systematically describes the various DL algorithms for accurate and early assessment of AD, discusses the advantages and limitations of the DL-based model for AD diagnosis, and provides an outlook toward future trends derived from critical assessment.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Quang Manh Doan, Tran Hiep Dinh, Nguyen Linh Trung, Diep N. Nguyen, Avinash Kumar Singh, Chin-Teng Lin
Summary: This paper introduces a smoothing filter method for EEG signal processing, which can remove noise while preserving important features. By using the UDR technique to process the signal in the image domain, the CUDR method exhibits superior performance in dealing with noisy signals.
2023 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP, SSP
(2023)
Proceedings Paper
Automation & Control Systems
Qiao Wang, Dikai Liu, Marc G. Carmichael, Chin-Teng Lin
Summary: This research proposes a trust-based method for role arbitration in human-robot collaboration and presents a TSC model to measure robot trust and self-confidence. Human-in-the-loop experiments with a collaborative robot confirm that the proposed method can improve human-robot combined performance, reduce human co-workers' workload, and enhance subjective preference.
2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2023)
(2023)
