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2023 international Conference on Fuzzy Theory and Its Applications, iFUZZY 2023

作者： Fan, Zuo-Cian Lin, Ro-Wei Tsai, Ching-Shu Chou, Wen-Jiun Li, Chia-Jung Huang, Zih-Jun Shih, Bin-Yu Wang, Liang-Jen Ko, Li-Wei Department of Biological Science & Technology Hsinchu300 Taiwan National Yang Ming Chiao Tung University International Ph.D. Program in Interdisciplinary Neuroscience Hsinchu300 Taiwan Kaohsiung Chang Gung Memorial Hospit Department of Child and Adolescent Psychiatry National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Department of Electronics and Electrical Engineering Hsinchu300 Taiwan

ISBN: (纸本)9798350305791

We sought to revolutionize the classification of Attention-deficit/Hyperactivity disorder (AdHd) by pioneering an innovative approach that seamlessly integrated auditory and visual tests with electroencephalogram (EEG) coherence analysis, forming the foundation for our Support Vector Machine (SVM) models. Our primary objective was to achieve precise differentiation between individuals with AdHd and those without, aiming to reshape the landscape of AdHd diagnosis and early intervention. We constructed an SVM model based on CATA coherence, incorporating a carefully selected set of 180 features, and another grounded in CPT coherence with 70 features. Astonishingly, our exploration uncovered that a model incorporating CATA's coherence and Power Spectral density (PSd) as features achieved an astounding accuracy rate of 97.7%, using only half the number of features. This revelation hints at untapped potential for multivariate advancements in the realm of AdHd classification. The landscape of AdHd diagnosis and intervention is perpetually evolving, most notably with the FdA's approval of game therapy for AdHd. Leveraging the transformative power of our findings, we envision the development of user-friendly game therapies for in-home use, empowering both clinicians and parents alike. This marks a paradigm shift in the realm of AdHd intervention, offering objective, data-driven tools for the early management of AdHd. Gamified therapy not only enhances accessibility but also fosters engagement and compliance, all of which are pivotal in the long-term care of individuals with AdHd. In summary, our study represents a significant advancement in our comprehension and classification of AdHd. By fusing auditory and visual tests with EEG coherence analysis, fortified by state-of-the-art machine learning techniques, we have achieved an unprecedented level of accuracy in identifying individuals with AdHd. Our findings, aligned with the FdA-approved game therapy, offer a glimpse into a

关键词： Electroencephalography

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Equilibrative nucleoside transporter 3 supports microglial functions and protects against the progression of Huntington's disease in the mouse model

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Brain, Behavior, and Immunity 2024年 120卷 413-429页

作者： Lu, Ying-Sui Hung, Wei-Chien Hsieh, Yu-Ting Tsai, Pei-Yuan Tsai, Tsai-Hsien Fan, Hsiu-Han Chang, Ya-Gin Cheng, Hui-Kuei Huang, Shen-Yan Lin, Hsin-Chuan Lee, Yan-Hua Shen, Tzu-Hsiang Hung, Bing-Yu Tsai, Jin-Wu dzhagalov, Ivan Cheng, Irene Han-Juo Lin, Chun-Jung Chern, Yijuang Hsu, Chia-Lin Institute of Microbiology and Immunology National Yang Ming Chiao Tung University Taipei Taiwan Taiwan International Graduate Program in Molecular Medicine National Yang Ming Chiao Tung University and Academia Sinica Taipei Taiwan Institute of Brain Science National Yang Ming Chiao Tung University Taipei Taiwan Institute of Biomedical Sciences Academia Sinica Taipei Taiwan Taiwan International Graduate Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University and Academia Sinica Taipei Taiwan Biomedical Industry Ph.D. Program National Yang Ming Chiao Tung University Taipei Taiwan Brain Research Center National Yang Ming Chiao Tung University Taipei Taiwan School of Pharmacy College of Medicine National Taiwan University Taipei Taiwan

Huntington's disease (Hd) is a hereditary neurodegenerative disorder characterized by involuntary movements, cognitive deficits, and psychiatric symptoms. Currently, there is no cure, and only limited treatments are available to manage the symptoms and to slow down the disease's progression. The molecular and cellular mechanisms of Hd's pathogenesis are complex, involving immune cell activation, altered protein turnover, and disturbance in brain energy homeostasis. Microglia have been known to play a dual role in Hd, contributing to neurodegeneration through inflammation but also enacting neuroprotective effects by clearing mHTT aggregates. However, little is known about the contribution of microglial metabolism to Hd progression. This study explores the impact of a microglial metabolite transporter, equilibrative nucleoside transporter 3 (ENT3), in Hd. Known as a lysosomal membrane transporter protein, ENT3 is highly enriched in microglia, with its expression correlated with Hd severity. Using the R6/2 ENT3^−/− mouse model, we found that the deletion of ENT3 increases microglia numbers yet worsens Hd progression, leading to mHTT accumulation, cell death, and disturbed energy metabolism. These results suggest that the delicate balance between microglial metabolism and function is crucial for maintaining brain homeostasis and that ENT3 has a protective role in ameliorating neurodegenerative processes. © 2024 The Authors

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Evaluation of Fatigue and Attention Levels in Multi-target Scenario using CNN

Evaluation of Fatigue and Attention Levels in Multi-target S...

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2020 international Computer Symposium, ICS 2020

作者： Sandeep Vara Sankar, d Ko, Li-Wei National Chiao Tung University International Ph.D Program in Interdisciplinary Neuroscience Dept. of Biological Science and Technology Hsinchu Taiwan National Chiao Tung University Center for Intelligent Drug Systems and Smart Bio-Devices Department of Biological Science and Technology Hsinchu Taiwan

ISBN: (纸本)9781728192550

Fatigue is a behavioral phenomenon that occurs when a user conducts focused mental activity for a prolonged duration resulting in performance errors or lapse. This paper presents an electroencephalogram (EEG)-based fatigue and attention level detection using 2-dimensional convolutional neural networks (2d-CNN). The experimental paradigm was designed to identify and detect a target object from a multi- target scenario. The results show that our proposed model provides a classification accuracy of 86.12%, which is ~18%, ~16% and ~10% higher than the Bayesian linear discriminant analysis (BLdA), support vector machine (SVM) and bootstrap aggregating (bagging tree) algorithms. Further, the decreased session-wise accuracy levels observed for each subject after the 4th experimental session postulates cognitive state disparities were caused due to increased fatigue and dropped attention levels. These biomarkers were assessed by comparing the resting theta and alpha band powers with the rapid serial visual presentation (RSVP) performance of the later sessions (sessions 5 to 7). The results show an inverse relationship between the RSVP classification performance and the resting EEG power, validating that the subjects' performance is affected by the physiological state biomarkers like fatigue and attention for prolonged brain-computer interface (BCI) experiments. Our findings demonstrate that the resting theta and alpha band powers can be considered as indicative measures to interpret mental fatigue and attention deficit problems. © 2020 IEEE.

关键词： Brain computer interface

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diversity and Suitability of the State-of-the-Art Wearable and Wireless EEG Systems Review

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IEEE Journal of Biomedical and Health Informatics 2023年第8期27卷 3830-3843页

作者： He, Congying Chen, Yu-Yi phang, Chun-Ren Stevenson, Cory Chen, I-Ping Jung, Tzyy-Ping Ko, Li-Wei Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Applied Arts National Yang Ming Chiao Tung University Hsinchu30010 Taiwan International Ph.D. Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute for Neural Computation and Institute of Engineering in Medicine University of California San DiegoCA90093 United States National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Electrical and Control Engineering Department of Electronics and Electrical Engineering Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Biomedical Science and Environment Biology Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung80708 Taiwan

Wireless electroencephalography (EEG) systems have been attracting increasing attention in recent times. Both the number of articles discussing wireless EEG and their proportion relative to general EEG publications have increased over years. These trends indicate that wireless EEG systems could be more accessible to researchers and the research community has recognized the potential of wireless EEG systems. To explore the development and diverse applications of wireless EEG systems, this review highlights the trends in wearable and wireless EEG systems over the past decade and compares the specifications and research applications of the major wireless systems marketed by 16 companies. For each product, five parameters (number of channels, sampling rate, cost, battery life, and resolution) were assessed for comparison. Currently, these wearable and portable wireless EEG systems have three main application areas: consumer, clinical, and research. To address this multitude of options, the article also discussed the thought process to find a suitable device that meets personalization and use cases specificities. These investigations suggest that low-price and convenience are key factors for consumer applications, wireless EEG systems with FdA or CE-certification may be more suitable for clinical settings, and devices that provide raw EEG data with high-density channels are important for laboratory research. This article presents an overview of the current state of the wireless EEG systems specifications and possible applications and serves as a guide point as it is expected that more influential and novel research will cyclically promote the development of such EEG systems. © 2023 IEEE.

关键词： Electroencephalography

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Evaluation of Fatigue and Attention Levels in Multi-target Scenario using CNN

Evaluation of Fatigue and Attention Levels in Multi-target S...

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international Computer Symposium (ICS)

作者： d Sandeep Vara Sankar Li-Wei Ko International Ph.D Program in Interdisciplinary Neuroscience National Chiao Tung University Hsinchu Taiwan Center for Intelligent Drug Systems and Smart Bio-Devices National Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9781728192550

ISBN: (纸本)9781728192567

Fatigue is a behavioral phenomenon that occurs when a user conducts focused mental activity for a prolonged duration resulting in performance errors or lapse. This paper presents an electroencephalogram (EEG)-based fatigue and attention level detection using 2-dimensional convolutional neural networks (2d-CNN). The experimental paradigm was designed to identify and detect a target object from a multi- target scenario. The results show that our proposed model provides a classification accuracy of 86.12%, which is ~18%, ~16% and ~10% higher than the Bayesian linear discriminant analysis (BLdA), support vector machine (SVM) and bootstrap aggregating (bagging tree) algorithms. Further, the decreased session-wise accuracy levels observed for each subject after the 4 th experimental session postulates cognitive state disparities were caused due to increased fatigue and dropped attention levels. These biomarkers were assessed by comparing the resting theta and alpha band powers with the rapid serial visual presentation (RSVP) performance of the later sessions (sessions 5 to 7). The results show an inverse relationship between the RSVP classification performance and the resting EEG power, validating that the subjects' performance is affected by the physiological state biomarkers like fatigue and attention for prolonged brain-computer interface (BCI) experiments. Our findings demonstrate that the resting theta and alpha band powers can be considered as indicative measures to interpret mental fatigue and attention deficit problems.

关键词： Support vector machines Biomarkers Fatigue Brain modeling Classification algorithms Task analysis Bagging

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A nigroincertal projection mediates aversion and enhances coping responses to potential threat

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FASEB Journal 2023年第12期37卷 e23322-e23322页

作者： Ho, Ping-Chen Hsiao, Fu-Yun Chiu, Shi-Hong Lee, Syun-Ruei Yau, Hau-Jie The Laboratory for Neural Circuits and Behaviors Graduate Institute of Brain and Mind Sciences National Taiwan University Taipei Taiwan School of Medicine National Taiwan University Taipei Taiwan Neurobiology and Cognitive Science Center National Taiwan University Taipei Taiwan Taiwan International Graduate Program in Interdisciplinary Neuroscience National Taiwan University and Academia Sinica Taipei Taiwan Ph.D. Program in Translational Medicine National Taiwan University and Academia Sinica Taipei Taiwan

Recent studies have shown that the non-dA neurons in the ventral tegmental area (VTA) and substantia nigra (SN) not only modulate motivational behaviors but also regulate defensive behaviors. While zona incerta (ZI) is a threat-responsive substrate and receives innervations from the ventral midbrain, the function of the ventral midbrain-to-ZI connection remains poorly defined. Here, we demonstrate that the ZI receives heterogenous innervations from the ventral midbrain. By utilizing a retrograde AAV preferentially labeling non-dA neurons in the ventral midbrain, we found that ZI-projecting non-dA cells in the ventral midbrain are activated by restraint stress. We focused on the SN and found that SN-to-ZI GABAergic input is engaged by a predatory odor. Sustained pan-neuronal SN-to-ZI activation results in aversion and enhances defensive behaviors, likely through a disinhibition mechanism to recruit downstream brain regions that regulate defensive behaviors. Collectively, our results reveal a novel role of nigroincertal projection in mediating negative valence and regulating defensive behaviors. © 2023 Federation of American Societies for Experimental Biology.

关键词： defensive behavior stress substantia nigra ventral tegmental area zona increta

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Unveiling Multivariate EEG Features: A Novel Approach to Enhancing AdHd diagnosis Through Visual and Auditory Attention Tests

Unveiling Multivariate EEG Features: A Novel Approach to Enh...

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international Conference on Fuzzy Theory and it's Applications (iFUZZY)

作者： Zuo-Cian Fan Ro-Wei Lin Ching-Shu Tsai Wen-Jiun Chou Chia-Jung Li Zih-Jun Huang Bin-Yu Shih Liang-Jen Wang Li-Wei Ko Department of Biological Science & Technology Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B) College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan International Ph.D. Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Child and Adolescent Psychiatry Kaohsiung Chang Gung Memorial Hospit Department of Electronics and Electrical Engineering Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

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Integration of MRI and somatosensory evoked potentials facilitate diagnosis of spinal cord compression

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Scientific Reports 2023年第1期13卷 1-12页

作者： Sun, Shu-Pin phang, Chun-Ren Tzou, Shey-Cherng Chen, Chang-Mu Ko, Li-Wei International Ph.D. Program in Interdisciplinary Neuroscience (UST) College of Biological Science and Technology National Yang Ming Chiao Tung University 734 Engineering Bldg. 5 1001 Daxue Road Hsinchu 30010 Taiwan Department of Medical Research National Taiwan University Hospital Hsin-Chu Branch Hsinchu 300 Taiwan Institute of Molecular Medicine and Bioengineering National Yang Ming Chiao Tung University Hsinchu 300 Taiwan Department of Surgery College of Medicine and Hospital National Taiwan University No. 7 Zhongshan South Road Taipei 10002 Taiwan Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B) College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu 300 Taiwan Institute of Electrical and Control Engineering Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu 300 Taiwan Department of Biomedical Science and Environment Biology and the Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung 807 Taiwan

This study aimed to integrate magnetic resonance imaging (MRI) and related somatosensory evoked potential (SSEP) features to assist in the diagnosis of spinal cord compression (SCC). MRI scans were graded from 0 to 3 according to the changes in the subarachnoid space and scan signals to confirm differences in SCC levels. The amplitude, latency, and time–frequency analysis (TFA) power of preoperative SSEP features were extracted and the changes were used as standard judgments to detect neurological function changes. Then the patient distribution was quantified according to the SSEP feature changes under the same and different MRI compression grades. Significant differences were found in the amplitude and TFA power between MRI grades. We estimated three degrees of amplitude anomalies and power loss under each MRI grade and found the presence or absence of power loss occurs after abnormal changes in amplitude only. For SCC, few integrated approach combines the advantages of both MRI and evoked potentials. However, integrating the amplitude and TFA power changes of SSEP features with MRI grading can help in the diagnosis and speculate progression of SCC. © 2023, The Author(s).

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Time synchronization between parietal–frontocentral connectivity with MRCP and gait in post-stroke bipedal tasks

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Journal of NeuroEngineering and Rehabilitation 2024年第1期21卷 101页

作者： phang, Chun-Ren Su, Kai-Hsiang Cheng, Yuan-Yang Chen, Chia-Hsin Ko, Li-Wei International Ph.D. Program in Interdisciplinary Neuroscience (UST) College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B) College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biological Science and Technology College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Physical Medicine and Rehabilitation Taichung Veterans General Hospital Taichung Taiwan Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan School of Medicine National Yang Ming Chiao Tung University Taipei Taiwan Department of Physical Medicine and Rehabilitation Kaohsiung Medical University Hospital Kaohsiung Taiwan School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Regenerative Medicine and Cell Therapy Research Center Kaohsiung Medical University Kaohsiung Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Science and Environment Biology Kaohsiung Medical University Kaohsiung Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung Taiwan

Background: In post-stroke rehabilitation, functional connectivity (FC), motor-related cortical potential (MRCP), and gait activities are common measures related to recovery outcomes. However, the interrelationship between FC, MRCP, gait activities, and bipedal distinguishability have yet to be investigated. Methods: Ten participants were equipped with EEG devices and inertial measurement units (IMUs) while performing lower limb motor preparation (MP) and motor execution (ME) tasks. MRCP, FCs, and bipedal distinguishability were extracted from the EEG signals, while the change in knee degree during the ME phase was calculated from the gait data. FCs were analyzed with pairwise Pearson’s correlation, and the brain-wide FC was fed into support vector machine (SVM) for bipedal classification. Results: Parietal–frontocentral connectivity (PFCC) dysconnection and MRCP desynchronization were related to the MP and ME phases, respectively. Hemiplegic limb movement exhibited higher PFCC strength than nonhemiplegic limb movement. Bipedal classification had a short-lived peak of 75.1% in the pre-movement phase. These results contribute to a better understanding of the neurophysiological functions during motor tasks, with respect to localized MRCP and nonlocalized FC activities. The difference in PFCCs between both limbs could be a marker to understand the motor function of the brain of post-stroke patients. Conclusions: In this study, we discovered that PFCCs are temporally dependent on lower limb gait movement and MRCP. The PFCCs are also related to the lower limb motor performance of post-stroke patients. The detection of motor intentions allows the development of bipedal brain-controlled exoskeletons for lower limb active rehabilitation. © The Author(s) 2024.

关键词： Brain–computer interface Functional connectivity Motor execution Motor preparation Post-stroke

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