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研究

RESEARCH Principles underlying the input-dependent formation and organization of memories Juliane Herpich 1,2 and Christian Tetzlaff1,2 1Department of Computational Neuroscience, Third Institute of PhysicsBiophysics, Georg-August-University, Göttingen, Germany 2Bernstein Center for Computational Neuroscience, Georg-August-University, Göttingen, Germany Keywords: Synaptic plasticity, 记忆, Memory interaction, Synaptic scaling, Inhibition a n o p e n a c c e s s j o u r n a l

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方法

METHODS Guided graph spectral embedding: Application to the C. elegans connectome Miljan Petrovic 1,2 , Thomas A. 瓦. Bolton , Maria Giulia Preti 1,2 Raphaël Liégeois , and Dimitri Van De Ville 1,2 1,2 , 1,2 1Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Campus Biotech, 日内瓦, Switzerland 2Department of Radiology and Medical Informatics, University of Geneva, 日内瓦, Switzerland Keywords: Spectral graph domain, Graph embedding,

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方法

METHODS Network structural dependency in the human connectome across the life-span Markus D. Schirmer 1,2,3∗ , Ai Wern Chung4∗ , 磷. Ellen Grant4, and Natalia S. Rost1 1Stroke Division & Massachusetts General Hospital, J. Philip Kistler Stroke Research Center, 哈佛医学院, 波士顿, 嘛, USA 2Computer Science and Artificial Intelligence Lab, 麻省理工学院, 剑桥, 嘛, USA 3Department of Population Health Sciences, German Centre

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焦点功能:

焦点功能: Topological Neuroscience Topological exploration of artificial neuronal network dynamics Jean-Baptiste Bardin 1 , Gard Spreemann 1 1 , and Kathryn Hess 1Laboratory for Topology and Neuroscience, Brain Mind Institute, École Polytechnique Fédérale de Lausanne, 洛桑, Switzerland Keywords: Network dynamics, Topological data analysis, Persistent homology, Artificial neural network, Spike train, machine learning a n o p e n a c c e s s

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研究

RESEARCH Psychological resilience correlates with EEG source-space brain network flexibility Véronique Paban 1 , Julien Modolo 2 , Ahmad Mheich 2 , and Mahmoud Hassan 2 1Aix Marseille University, 法国国家科学研究中心, LNSC, Marseille, France 2University of Rennes, INSERM, LTSI-U1099, F-35000 Rennes, France Keywords: EEG source connectivity, Psychological resilience, Resting state, Flexibility ABSTRACT We aimed at identifying the potential relationship between the dynamical properties of the human

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研究

RESEARCH Changes in structural network topology correlate with severity of hallucinatory behavior in Parkinson’s disease 1,2 Julie M. Hall Joseph R. Phillips 1,2 , Claire O’Callaghan 2,3 2 , Alana J. 穆勒 , Ahmed A. Moustafa , Simon J. G. Lewis 1,4 , Kaylena A. Ehgoetz Martens 2 , and James M. Shine 2 , 2 a n o p e n a c c

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研究

RESEARCH Spatial and spectral trajectories in typical neurodevelopment from childhood to middle age Benjamin A. 乙. 打猎 1,2, Simeon M. 黄 1,2, Marlee M. Vandewouw1,2, Matthew J. Brookes3, Benjamin T. Dunkley1,2,5, and Margot J. Taylor1,2,4,5 1Department of Diagnostic Imaging, The Hospital for Sick Children, 多伦多, Canada 2Neurosciences and Mental Health Program, The Hospital for Sick Children Research Institute, 多伦多, Canada 3The Sir Peter Mansfield Imaging

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焦点功能:

焦点功能: Topological Neuroscience Replays of spatial memories suppress topological fluctuations in cognitive map 1 Andrey Babichev , Dmitriy Morozov 2 , and Yuri Dabaghian 1,3 1Department of Computational and Applied Mathematics, Rice University, Houston, TX, USA 2Lawrence Berkeley National Laboratory, 伯克利, CA, USA Department of Neurology, The University of Texas McGovern Medical School, Houston, TX, 美国 3 关键词: Learning and memory, Hippocampal replays, Transient

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研究

RESEARCH Distance-dependent consensus thresholds for generating group-representative structural brain networks Richard F. Betzel1,2,3,4, Alessandra Griffa5, Patric Hagmann6, and Bratislav Miši´c7 1Department of Psychological and Brain Sciences, 印第安纳大学, 布卢明顿, 在, USA 2Cognitive Science Program, 印第安纳大学, 布卢明顿, 在, USA 3Program in Neuroscience, 印第安纳大学, 布卢明顿, 在, USA 4Network Science Institute, 印第安纳大学, 布卢明顿, 在, USA 5Dutch Connectome Lab, Department of Complex Trait Genetics, Center for

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方法

METHODS Connectome sorting by consensus clustering increases separability in group neuroimaging studies Javier Rasero Daniele Marinazzo , Ibai Diez , Jesus M. 科尔特斯 , and Sebastiano Stramaglia 7 1 2,3,4 1,5,6 , 8,9,10 1Biocruces Health Research Institute, Hospital Universitario de Cruces, Barakaldo, Spain 2Functional Neurology Research Group, 神经内科, Massachusetts General Hospital, 哈佛医学院, 波士顿, 嘛, USA 3Gordon Center, Department of Nuclear Medicine,

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研究

RESEARCH Centralized and distributed cognitive task processing in the human connectome Enrico Amico1,2, Alex Arenas 3, and Joaquín Goñi1,2,4 1School of Industrial Engineering, Purdue University, West-Lafayette, 在, USA 2Purdue Institute for Integrative Neuroscience, Purdue University, West-Lafayette, 在, USA 3Departament d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona, Spain 4Weldon School of Biomedical Engineering, Purdue University, West-Lafayette, 在, USA Keywords: Brain connectomics, Functional connectivity, 网络

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研究

RESEARCH Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity David M. Lydon-Staley 1, Rastko Ciric 2, Theodore D. Satterthwaite 2, and Danielle S. Bassett 1,3,4,5 1Department of Bioengineering, 宾夕法尼亚大学, 费城, PA, USA 2Department of Psychiatry, Perelman School of Medicine, 宾夕法尼亚大学, 费城, PA, USA 3Department of Electrical and

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研究

RESEARCH Dynamic properties of simulated brain network models and empirical resting-state data Amrit Kashyap1 and Shella Keilholz 1 1Department of Biomedical Engineering, Georgia Tech and Emory University, 亚特兰大, 遗传算法, USA Keywords: Resting-state fMRI, Brain network modeling, Dynamics, Dynamic functional connectivity ABSTRACT Brain network models (BNMs) have become a promising theoretical framework for simulating signals that are representative of whole-brain activity such as resting-state fMRI. 然而,

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研究

RESEARCH Computation is concentrated in rich clubs of local cortical networks Samantha P. Faber 1, Nicholas M. Timme 2, 约翰·M. Beggs 3, and Ehren L. 纽曼 1 1Department of Psychological and Brain Sciences, Indiana University Bloomington, 布卢明顿, 在, USA 2Department of Psychology, Indiana University-Purdue University Indianapolis, 印第安纳波利斯, 在, USA 3Department of Physics, Indiana University Bloomington, 布卢明顿, 在, USA Keywords: Cortical networks; Effective connectivity; Neural

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研究

RESEARCH High-accuracy individual identification using a “thin slice” of the functional connectome Lisa Byrge and Daniel P. Kennedy Department of Psychological and Brain Sciences, 印第安纳大学, 布卢明顿, 在, USA Keywords: Functional connectivity MRI, Individual differences, Single-subject fMRI, Resting state, Within-subject reliability ABSTRACT Connectome fingerprinting—a method that uses many thousands of functional connections in aggregate to identify individuals—holds promise for individualized neuroimaging. A better characterization of

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研究

RESEARCH Functional connectivity-based subtypes of individuals with and without autism spectrum disorder Amanda K. Easson1,2, Zainab Fatima3, and Anthony R. McIntosh1,2 1Rotman Research Institute, Baycrest Hospital, 多伦多, 在, Canada 2Department of Psychology, 多伦多大学, 多伦多, 在, Canada 3Department of Psychology, Faculty of Health, Sherman Health Sciences Centre, 约克大学, 多伦多, 在, Canada a n o p e n a c c e s s

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研究

RESEARCH High-resolution data-driven model of the mouse connectome Joseph E. Knox1,2, Kameron Decker Harris Hongkui Zeng 1, 朱莉A. Harris1, Eric Shea-Brown 1,2, and Stefan Mihalas 2,3, Nile Graddis1, Jennifer D. Whitesell 1,2 1, 1Allen Institute for Brain Science, Seattle, 华盛顿, USA 2Applied Mathematics, 华盛顿大学, Seattle, 华盛顿, USA 3Computer Science and Engineering, 华盛顿大学, Seattle, 华盛顿, USA Keywords: Connectome, Whole-brain, Mouse a

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研究

RESEARCH Cooperative contributions of structural and functional connectivity to successful memory in aging Simon W. 戴维斯 1,2, Amanda Szymanski1,2, Homa Boms1, Thomas Fink1, and Roberto Cabeza 1 1Center for Cognitive Neuroscience, 杜克大学, 达勒姆, NC, USA 2Department of Neurology, Duke University School of Medicine, 达勒姆, NC, USA Keywords: 老化, 结构连接, Functional connectivity, Episodic memory, Task-related connectivity, SEM a n o p e n a

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