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196 – Fronto-parietal dysfunction during spatial working memory task in subjects at high clinical-risk for schizophrenia

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Schizophrenia Research 2008年 98卷 114-114页

作者： Park, J.Y. Kang, D.H. Choi, J.S. Jung, M.H. Jung, W.H. Choi, C.H. Shin, N.Y. Kwon, J.S. Interdisciplinary Program in Cognitive and Brain Science Seoul National University Seoul Republic of Korea Department of Psychiatry Seoul National University College of Medicine Seoul Republic of Korea Clinical Cognitive Neuroscience Center Neuroscience Institute SNU-MRC Seoul Republic of Korea Department of Radiology National Medical Center Seoul Republic of Korea

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Corrigendum to “Switching strategy underlies phonemic verbal fluency impairment in obsessive-compulsive disorder” [J. Obsessive-Compuls. Relat. Disord. 1 (2012) 221–227]

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Journal of Obsessive-Compulsive and Related Disorders 2016年 10卷 99-99页

作者： Shin, Ye Seul Shin, Na Young Jang, Joon Hwan Shim, Geumsook Park, Hye Yoon Shin, Min-Sup Kwon, Jun Soo Department of Brain & Cognitive Sciences World Class University Program College of Natural Sciences Seoul National University Seoul Republic of Korea Interdisciplinary Cognitive Science Program Seoul National University Seoul Republic of Korea Department of Psychiatry & Behavioral Sciences Seoul National University College of Medicine Seoul Republic of Korea Department of Child-Adolescent Psychiatry Seoul National University College of Medicine Seoul Republic of Korea

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Altered connectivity in focal epilepsy

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International Journal of Epilepsy 2016年第1期3卷 46-46页

作者： Chun Kee Chung Department of Neurosurgery Seoul National University Hospital Seoul Republic of Korea Interdisciplinary Program in Neuroscience Seoul National University College of Natural Science Seoul Republic of Korea Department of Neurosurgery Seoul National University College of MedicineSeoul Republic of Korea Department of Brain and Cognitive Sciences Seoul National University College of Natural Sciences Seoul Republic of Korea

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Multi-stream deep learning framework to predict mild cognitive impairment with Rey Complex Figure Test

arXiv

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arXiv 2024年

作者： Park, Junyoung Seo, Eun Hyun Kim, Sunjun Yi, SangHak Lee, Kun Ho Won, Sungho Department of Neurology and Neurological Sciences Stanford University School of Medicine StanfordCA94305 United States RexSoft Inc Seoul08826 Korea Republic of Gwangju Alzheimer's & Related Dementia Cohort Research Center Chosun University Gwangju61452 Korea Republic of Premedical Science College of Medicine Chosun University Gwangju61452 Korea Republic of Neurozen Inc. Seoul06160 Korea Republic of Department of Neurology Wonkwang University Hospital Wonkwang University School of Medicine Iksan15865 Korea Republic of Department of Biomedical Science Chosun University Gwangju61452 Korea Republic of Korea Brain Research Institute Daegu41068 Korea Republic of Department of Public Health Sciences Graduate School of Public Health Seoul National University Seoul08826 Korea Republic of Interdisciplinary Program in Bioinformatics Seoul National University Seoul08826 Korea Republic of Institute of Health and Environment Seoul National University Seoul08826 Korea Republic of

Drawing tests like the Rey Complex Figure Test (RCFT) are widely used to assess cognitive functions such as visuospatial skills and memory, making them valuable tools for detecting mild cognitive impairment (MCI). Despite their utility, existing predictive models based on these tests often suffer from limitations like small sample sizes and lack of external validation, which undermine their reliability. We developed a multi-stream deep learning framework that integrates two distinct processing streams: a multi-head self-attention based spatial stream using raw RCFT images and a scoring stream employing a previously developed automated scoring system. Our model was trained on data from 1,740 subjects in the Korean cohort and validated on an external hospital dataset of 222 subjects from Korea. The proposed multi-stream model demonstrated superior performance over baseline models (AUC = 0.872, Accuracy = 0.781) in external validation. The integration of both spatial and scoring streams enables the model to capture intricate visual details from the raw images while also incorporating structured scoring data, which together enhance its ability to detect subtle cognitive impairments. This dual approach not only improves predictive accuracy but also increases the robustness of the model, making it more reliable in diverse clinical settings. Our model has practical implications for clinical settings, where it could serve as a cost-effective tool for early MCI screening. © 2024, CC BY.

关键词： Convolutional neural networks

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROscience 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Strategic brain areas for cognitive decline in subcortical vascular cognitive impairment: A diffusion-tensor imaging and PET study

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Alzheimer's & Dementia 2013年第4期9卷 P583-P584页

作者： Min-Jeong Kim Kyoung-Min Lee Young-Don Son Hyeon-Ae Jeon Sejin Yoo Young-Bo Kim Zang-Hee Cho Department of Neurology Seoul National University Hospital Healthcare System Gangnam Center Seoul South Korea Seoul National University Hospital Seoul South Korea Neuroscience Research Institute Gachon Medical School Incheon South Korea Department of Neuropsychology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany Interdisciplinary Program in Cognitive Science Seoul National University Seoul South Korea

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186 – Inefficient neural network during spatial working memory task in subjects at high genetic-risk for schizophrenia

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Schizophrenia Research 2008年 98卷 110-110页

作者： Han, J.Y. Park, J.Y. Kang, D.H. Choi, J.S. Jung, M.H. Choi, C.H. Jung, Y.S. Lee, J.M. Kwon, J.S. Interdisciplinary Program in Cognitive and Brain Science Seoul National University Seoul Republic of Korea Department of Psychiatry Seoul National University College of Medicine Seoul Republic of Korea Clinical Cognitive Neuroscience Center Neuroscience Institute SNU-MRC Seoul Republic of Korea Department of Radiology National Medical Center Seoul Republic of Korea Department of Biomedical Engineering Hanyang University School of Medicine Seoul Republic of Korea

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Author Correction: Predicting the efficiency of prime editing guide RNAs in human cells

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Nature biotechnology 2024年第3期42卷 529页

作者： Hui Kwon Kim Goosang Yu Jinman Park Seonwoo Min Sungtae Lee Sungroh Yoon Hyongbum Henry Kim Department of Pharmacology Yonsei University College of Medicine Seoul Republic of Korea. Brain Korea 21 Plus Project for Medical Sciences Yonsei University College of Medicine Seoul Republic of Korea. Center for Nanomedicine Institute for Basic Science (IBS) Seoul Republic of Korea. Graduate Program of Nano Biomedical Engineering (NanoBME) Advanced Science Institute Yonsei University Seoul Republic of Korea. Electrical and Computer Engineering Seoul National University Seoul Republic of Korea. Interdisciplinary Program in Bioinformatics Seoul National University Seoul Republic of Korea. Graduate School of Data Science Seoul National University Seoul Republic of Korea. Department of Pharmacology Yonsei University College of Medicine Seoul Republic of Korea. hkim1@yuhs.ac. Brain Korea 21 Plus Project for Medical Sciences Yonsei University College of Medicine Seoul Republic of Korea. hkim1@yuhs.ac. Center for Nanomedicine Institute for Basic Science (IBS) Seoul Republic of Korea. hkim1@yuhs.ac. Graduate Program of Nano Biomedical Engineering (NanoBME) Advanced Science Institute Yonsei University Seoul Republic of Korea. hkim1@yuhs.ac. Severance Biomedical Science Institute Yonsei University College of Medicine Seoul Republic of Korea. hkim1@yuhs.ac. Graduate Program of NanoScience and Technology Yonsei University Seoul Republic of Korea. hkim1@yuhs.ac.

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Correction: Astrocytic water channel aquaporin-4 modulates brain plasticity in both mice and humans: a potential gliogenetic mechanism underlying language-associated learning

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Molecular psychiatry 2021年第12期26卷 7853页

作者： J Woo J E Kim J J Im J Lee H S Jeong S Park S- Y Jung H An S Yoon S M Lim S Lee J Ma E Y Shin Y- E Han B Kim E H Lee L Feng H Chun B- E Yoon I Kang S R Dager I K Lyoo C J Lee Center for Neural Science and Functional Connectomics Korea Institute of Science and Technology (KIST) Seoul Republic of Korea. Neuroscience Program University of Science and Technology (UST) Daejeon Republic of Korea. Department of Brain and Cognitive Sciences Scranton College Ewha Womans University Seoul Republic of Korea. Ewha Brain Institute Ewha Womans University Seoul Republic of Korea. Interdisciplinary Program in Neuroscience College of Natural Sciences Seoul National University Seoul Republic of Korea. Division of Functional Food Research Korea Food Research Institute Seongnam Republic of Korea. Department of Radiology Incheon St. Mary's Hospital College of Medicine The Catholic University of Korea Seoul Republic of Korea. KU-KIST Graduate School of Converging Science and Technology Korea University145 Anam-ro Seongbuk-gu Seoul 02841 Republic of Korea. Department of Radiology College of Medicine Ewha Womans University Seoul Republic of Korea. Green Cross Laboratories Yongin Republic of Korea. Department of Nanobiomedical Science Dankook University Cheonan Republic of Korea. Department of Radiology University of Washington Seattle WA USA. Department of Bioengineering University of Washington Seattle WA USA. Department of Brain and Cognitive Sciences Scranton College Ewha Womans University Seoul Republic of Korea. inkylyoo@ewha.ac.kr. Ewha Brain Institute Ewha Womans University Seoul Republic of Korea. inkylyoo@ewha.ac.kr. Graduate School of Pharmaceutical Sciences Ewha Womans University Seoul Republic of Korea. inkylyoo@ewha.ac.kr. Center for Neural Science and Functional Connectomics Korea Institute of Science and Technology (KIST) Seoul Republic of Korea. cjl@kist.re.kr. Neuroscience Program University of Science and Technology (UST) Daejeon Republic of Korea. cjl@kist.re.kr. KU-KIST Graduate School of Converging Science and Technology Korea University145 Anam-ro Seongbuk-gu Seoul 02841 Republic of Korea. cjl@kist.re.kr.

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Proceedings of the 16th Annual UT-KBRIN Bioinformatics Summit 2016: bioinformatics

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BMC Bioinformatics 2017年第9期18卷 1-9页

作者： Eric C. Rouchka Juw Won Park Julia H. Chariker David A. Tieri Shreedharkumar Rajurkar Vikas Singh Nishchal K. Verma Yan Cui Mark Farman Bradford Condon Jolanta Jaromczyk Neil Moore Jerzy Jaromczyk Daniel Harris Patrick Calie Eun Kyong Shin Robert L. Davis Arash Shaban-Nejad Joshua M. Mitchell Hunter N. B. Moseley Robert M. Flight Qing Jun Wang Richard M. Higashi Teresa W-M Fan Andrew N. Lane Liangqun Lu Bernie J Daigle Jr. Xi Chen Andrey Smelter Jerzy W. Jaromczyk Bailey K. Phan Nathaniel J. Serpico Ethan G. Toney Li Chen Caroline E. Melton Jennifer R. Mandel Bernie J. Daigle Jr. Hao Chen Kazi I. Zaman Ramin Homayouni Patrick J. Trainor Andrew P. DeFilippis Samantha M. Carlisle Shesh N. Rai Department of Computer Engineering and Computer Science University of Louisville Duthie Center for Engineering Louisville KY 40292 USA Kentucky Biomedical Research Infrastructure (KBRIN) Bioinformatics Core 522 East Gray Street Louisville KY 40292 USA Department of Psychological and Brain Sciences University of Louisville Louisville KY 40292 USA Department of Anatomical Sciences and Neurobiology University of Louisville Louisville KY 40292 USA Department of Electrical Engineering IIT Kanpur India Department of Microbiology Immunology and Biochemistry University of Tennessee Health Science Center Memphis TN 38103 USA Center for Integrative and Translational Genomics University of Tennessee Health Science Center Memphis TN 38103 USA Department of Plant Pathology University of Kentucky Lexington KY 40546 USA UK Healthcare Genomics University of Kentucky Lexington KY 40536 USA Department of Entomology & Plant Pathology University of Tennessee Knoxville TN 37996 USA Department of Forestry University of Kentucky Lexington KY 40506 USA Department of Computer Science University of Kentucky Lexington KY 40506 USA Department of Computer Science University of Kentucky Lexington KY 40508 USA Department of Biological Sciences Eastern Kentucky University Richmond KY 40475 USA University of Tennessee Health Science Center – Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics Department of Pediatrics Memphis TN 38103 USA Department of Molecular & Cellular Biochemistry University of Kentucky Lexington KY 40536 USA Markey Cancer Center University of Kentucky Lexington KY 40536 USA Center for Environmental and Systems Biochemistry University of Kentucky Lexington KY 40536 USA Institute for Biomedical Informatics University of Kentucky Lexington KY 40536 USA Department of Molecular and Cellular Biochemistry University of Kentucky Lexington KY 40536 USA Department of Statistics University of Kentucky Louisville KY

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