RESEARCH Dynamic large-scale network synchronization from perception to action Jonni Hirvonen 1,2 , Simo Monto 1,† 1 , 盛华. 王 1 , J. 马蒂亚斯·帕尔瓦 1 , and Satu Palva 1Helsinki Institute for Life Sciences, 神经科学中心, 赫尔辛基大学, Finland 2BioMag Laboratory, HUS医学影像中心, 赫尔辛基大学中心医院, Finland †Present affiliation: 跨学科脑研究中心, 心理学系, 大学

焦点功能: New Trends in Connectomics ADHD and attentional control: Impaired segregation of task positive and task negative brain networks 1 Brian D. 米尔斯 1 , Oscar Miranda-Dominguez , Sarah L. Karalunas 1 Julia Painter 1 , 凯瑟琳·L. 米尔斯 , Joel T. Nigg 3,1 3,1 , Eric Earl 1 1 , Michaela Cordova 1,2,3 , , and Damien A. Fair l D o w

RESEARCH Frequency-based brain networks: From a multiplex framework to a full multilayer description Javier M. Buldú1,2 and Mason A. Porter3,4,5 1Laboratory of Biological Networks, Center for Biomedical Technology (UPM), Pozuelo de Alarcón, Madrid, Spain 2Complex Systems Group & G.I.S.C., Universidad Rey Juan Carlos, Móstoles, Madrid, Spain 3Department of Mathematics, University of California Los Angeles, 天使们, CA, USA 4Oxford Centre for Industrial and Applied Mathematics,

RESEARCH Ensemble stacking mitigates biases in inference of synaptic connectivity Brendan Chambers1, Maayan Levy1, Joseph B. Dechery1, and Jason N. MacLean1,2 1Committee on Computational Neuroscience, 芝加哥大学, 芝加哥, 伊尔, USA 2Department of Neurobiology, 芝加哥大学, 芝加哥, 伊尔, USA Keywords: Network analysis, Network motifs, Simulation and modeling, Synaptic connectivity, Information theory, Ensemble learning a n o p e n a c c e s

RESEARCH Local connectome phenotypes predict social, 健康, and cognitive factors Michael A. 鲍威尔 1 , Javier O. 加西亚 , Fang-Cheng Yeh 2,3 Jean M. Vettel , and Timothy Verstynen 2,3,6 4,5 , 7 1Department of Mathematical Sciences, United States Military Academy, 西点, 纽约, USA 2U.S. Army Research Laboratory, Aberdeen Proving Ground, 医学博士, USA 3Department of Bioengineering, 宾夕法尼亚大学, 费城, PA, USA 4Department of

RESEARCH Cognition and connectomes in nondementia idiopathic Parkinson’s disease 1 Luis M. Colon-Perez 2 , Jared J. Tanner 5 托马斯·H. Mareci , Michelle Couret 2 , and Catherine C. Price 3 4 , Shelby Goicochea , 1 Department of Psychiatry, University of Florida, Gainesville, FL, USA 2Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA 3Department of Medicine, 哥伦比亚大学, 新的

METHODS Network dynamics in the healthy and epileptic developing brain Richard Rosch1,2, Torsten Baldeweg2, Friederike Moeller3, and Gerold Baier4 1Wellcome Trust Centre for Neuroimaging, 伦敦大学学院, United Kingdom 2Developmental Neurosciences Programme, UCL Great Ormond Street Institute of Child Health, 伦敦大学学院, United Kingdom 3Department of Clinical Neurophysiology, Great Ormond Street Hospital, 伦敦, United Kingdom 4Cell and Developmental Biology, 伦敦大学学院, 英国

RESEARCH Sensitivity analysis of human brain structural network construction Kuang Wei 1,2 3 , Matthew Cieslak 4 , Clint Greene , Scott T. Grafton 3 , and Jean M. 卡尔森 2 1Department of Physics, 芝加哥大学, 芝加哥, 伊尔, USA 2Department of Physics, 加州大学, 圣巴巴拉, CA, USA 3Department of Psychological and Brain Sciences, 加州大学, 圣巴巴拉, CA, USA 4Department of

PERSPECTIVE Switching between internal and external modes: A multiscale learning principle 1 克里斯托弗·J. 蜂蜜 , Ehren L. 纽曼 2 , and Anna C. Schapiro 3 1Department of Psychological and Brain Sciences, Johns Hopkins University, 巴尔的摩, 医学博士, USA 2Department of Psychological and Brain Sciences, 印第安纳大学, 布卢明顿, 在, USA Department of Psychiatry, Beth Israel Deaconess Medical Center / 哈佛医学院, 波士顿, 嘛, 美国 3

RESEARCH High-energy brain dynamics during anesthesia-induced unconsciousness James R. Riehl 1 , Ben J. Palanca 3,4 , and ShiNung Ching 1,2,4 1Department of Electrical and Systems Engineering, Washington University in St. 路易斯, 英石. 路易斯, MO, USA 2Department of Biomedical Engineering, Washington University in St. 路易斯, 英石. 路易斯, MO, USA 3Department of Anesthesiology, Washington University School of Medicine, 英石. 路易斯, MO, USA 4Division of Biology and

RESEARCH Optimized connectome architecture for sensory-motor integration Jacob C. Worrell1, Jeffrey Rumschlag2, Richard F. Betzel3, Olaf Sporns1, and Bratislav Miši´c4 1Department of Psychological and Brain Sciences, 印第安纳大学, 布卢明顿, 印第安纳州, USA 2Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, CA, USA 3Department of Bioengineering, 宾夕法尼亚大学, 费城, PA, USA 4Montréal Neurological Institute, 麦吉尔大学, 蒙特利尔, Canada Keywords: Connectome, Brain, Spreading, Drosophila

焦点功能: New Trends in Connectomics The network architecture of value learning Marcelo G. Mattar 1,2 , Sharon L. Thompson-Schill 1 , and Danielle S. Bassett 2,3 1心理学系, 宾夕法尼亚大学, 费城, PA, USA 2Department of Bioengineering, 宾夕法尼亚大学, 费城, PA, USA 3Department of Electrical and Systems Engineering, 宾夕法尼亚大学, 费城, PA, USA Keywords: Functional connectivity, Cognitive systems, Brain networks, Behavioral

PERSPECTIVE Dynamical networks: Finding, measuring, and tracking neural population activity using network science Mark D. Humphries Faculty of Biology, 药品, 和健康, 曼彻斯特大学, 曼彻斯特, United Kingdom Keywords: Graph theory, Network theory, Systems neuroscience, Calcium imaging, Multineuron recordings, Neural ensembles a n o p e n a c c e s s j o u r n a l ABSTRACT l D o w

METHODS Nonparametric test for connectivity detection in multivariate autoregressive networks and application to multiunit activity data M. Gilson 1 , A. 陶斯特·坎波 1,2 , X. 陈 3 3 , A. Thiele , and G. 德科 1,4 1Computational Neuroscience Group, Departament de Tecnologies de la Informació i les Comunicacions, Universitat Pompeu Fabra, 巴塞罗那, Spain 2Epilepsy Monitoring Unit, 神经内科, Hospital del Mar Medical Research

RESEARCH The graphical brain: Belief propagation and active inference Karl J. 弗里斯顿 1 1 , Thomas Parr , and Bert de Vries 2,3 1Wellcome Trust Centre for Neuroimaging, Institute of Neurology, 伦敦大学学院, United Kingdom 2Eindhoven University of Technology, Department of Electrical Engineering, Eindhoven, The Netherlands GN Hearing, Eindhoven, 荷兰人 3 关键词: Bayesian, Neuronal, Connectivity, Factor graphs, Free energy, Belief propagation, Message passing

METHODS Consensus clustering approach to group brain connectivity matrices Javier Rasero 1,2,3 , Mario Pellicoro 6 Daniele Marinazzo 2 , Leonardo Angelini , and Sebastiano Stramaglia 2,3,4 , Jesus M. 科尔特斯 2,3,4 1,5 , 1Biocruces Health Research Institute. Hospital Universitario de Cruces, Barakaldo, Spain 2Dipartimento di Fisica, Università degli Studi Aldo Moro, Bari, Italy 3Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Italy 4TIRES-Center of

RESEARCH Structural covariance networks across the life span, 从 6 到 94 年龄 1 Elizabeth DuPre 1 和R. Nathan Spreng 1Laboratory of Brain and Cognition, Human Neuroscience Institute, Department of Human Development, 康奈尔大学, 伊萨卡岛, 纽约, USA Keywords: 网络, Structural covariance, Gray matter, 发展, 老化, MRI ABSTRACT Structural covariance examines covariation of gray matter morphology between brain regions and across individuals. 尽管

METHODS Large-scale DCMs for resting-state fMRI 1,2,3 Adeel Razi , Mohamed L. Seghier , Yuan Zhou , Peter McColgan , Peter Zeidman 7 Hae-Jeong Park 8 , 奥拉夫·斯波恩斯 , Geraint Rees , and Karl J. 弗里斯顿 1,9 1 1,4 1,5 6 1 , 4 1The Wellcome Trust Centre for Neuroimaging, 伦敦大学学院, 伦敦, United Kingdom 2Monash Biomedical Imaging and Monash Institute of Cognitive