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焦点功能:
焦点功能: Connectivity, 认识, and Consciousness It’s about time: Linking dynamical systems with human neuroimaging to understand the brain Yohan J. John1, Kayle S. Sawyer2,3,4,5, Karthik Srinivasan6, Eli J. Müller7, Brandon R. Munn7, and James M. Shine7 1Neural Systems Laboratory, 健康科学系, 波士顿大学, 波士顿, 嘛, USA 2Departments of Anatomy and Neurobiology, 波士顿大学, 波士顿大学, 波士顿, 嘛, USA 3Department of Radiology, 马萨诸塞州
方法
METHODS NeuMapper: A scalable computational framework for multiscale exploration of the brain’s dynamical organization Caleb Geniesse1,2*, Samir Chowdhury2*, and Manish Saggar2 1Biophysics Program, 斯坦福大学, 斯坦福大学, CA, USA 2Department of Psychiatry and Behavioral Sciences, 斯坦福大学, 斯坦福大学, CA, USA *Equal contribution. 关键词: TDA, Mapper, Optimal transport, Multitask fMRI, Ongoing cognition, NeuroSynth a n o p e n a c c e s s j o
研究
RESEARCH An application of neighbourhoods in digraphs to the classification of binary dynamics Pedro Conceição1, Dejan Govc2, Jānis Lazovskis3, Ran Levi1 , Henri Riihimäki5, and Jason P. Smith4 1Institute of Mathematics, University of Aberdeen, Aberdeen, UK 2Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia 3Riga Business School, Riga Technical University, Riga, Latvia 4Department of Mathematics and Physics, Nottingham Trent University, Nottingham, UK 5Department
焦点功能:
焦点功能: Biomarkers in Network Neuroscience Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis Shanna D. Kulik1* , Ilse M. Nauta2*, Prejaas Tewarie2,3, Ismail Koubiyr4, Edwin van Dellen5, Aurelie Ruet4,6, Kim A. Meijer1, Brigit A. de Jong2, Cornelis J. Stam2,3, Arjan Hillebrand3, Jeroen J. G. Geurts1, Linda Douw1, and Menno M. Schoonheim1 1Department of Anatomy and Neurosciences, Amsterdam UMC,
焦点功能:
焦点功能: Biomarkers in Network Neuroscience Network-level permutation entropy of resting-state MEG recordings: A novel biomarker for early-stage Alzheimer’s disease? Elliz P. Scheijbeler1,2, 安妮·M. van Nifterick1,2, Cornelis J. Stam2, Arjan Hillebrand2, Alida A. Gouw1,2, and Willem de Haan1,2 1Alzheimer Center Amsterdam, 神经内科, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 阿姆斯特丹, Netherlands 2Department of Clinical Neurophysiology and MEG Center, 神经内科, Amsterdam Neuroscience, Vrije
方法
METHODS More than the sum of its parts: Merging network psychometrics and network neuroscience with application in autism Joe Bathelt1,2 , Hilde M. Geurts2 , and Denny Borsboom2 1Department of Psychology, Royal Holloway, 伦敦大学, Egham, Surrey, UK 2Department of Psychology, University of Amsterdam, 阿姆斯特丹, the Netherlands Keywords: 网络, 方法, Psychometrics, Neuroimaging, Autism a n o p e n a c c e s
研究
RESEARCH Connectomic analysis of Alzheimer’s disease using percolation theory Parker Kotlarz1 , Juan C. Nino1* , and Marcelo Febo2* 1Department of Materials Science and Engineering, University of Florida, Gainesville, FL, USA 2Department of Psychiatry, University of Florida, Gainesville, FL, USA *J. Nino and M. Febo are co-senior authors. 关键词: 阿尔茨海默氏病, Connectomics, Percolation theory, Biomarker, 功能磁共振成像, Graph theory a n o p e n a
方法
METHODS Inferring excitation-inhibition dynamics using a maximum entropy model unifying brain structure and function Igor Fortel1 Anastasios Sidiropoulos6, Yichao Wu7, Ira Driscoll2, Dan Schonfeld1,8, and Alex Leow1,5 , Mitchell Butler1, Laura E. Korthauer2,3, Liang Zhan4, Olusola Ajilore5, 1Department of Bioengineering, University of Illinois at Chicago, 芝加哥, 伊尔, USA 2Department of Psychology, University of Wisconsin–Milwaukee, Milwaukee, WI, USA 3Warren Alpert Medical School, Brown University, Providence, RI,
研究
RESEARCH Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference Rodrigo Echeveste1 , Enzo Ferrante1* , Diego H. Milone1* , and Inés Samengo2* 1Research Institute for Signals, 系统, and Computational Intelligence sinc(我) (FICH-UNL/CONICET), 圣达菲, Argentina 2Medical Physics Department and Balseiro Institute (CNEA-UNCUYO/CONICET), Bariloche, Argentina *These authors contributed equally to this work. a n o p e n a c c
方法
METHODS Structure supports function: Informing directed and dynamic functional connectivity with anatomical priors David Pascucci1,2 , Maria Rubega3, Joan Rué-Queralt2,4, Sebastien Tourbier4, Patric Hagmann4, and Gijs Plomp2 1Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), 洛桑, Switzerland 2Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland 3Department of Neurosciences, University of Padova, Padova, Italy 4Connectomics Lab, 放射科, University Hospital of Lausanne and University
研究
RESEARCH Functional connectivity–based prediction of global cognition and motor function in riluzole-naive amyotrophic lateral sclerosis patients Luqing Wei1, Chris Baeken2,3,4, Daihong Liu5, Jiuquan Zhang5, and Guo-Rong Wu6 1School of Psychology, Jiangxi Normal University, Nanchang, China 2Ghent Experimental Psychiatry Lab, Department of Head and Skin, UZ Gent/ Universiteit Gent, Ghent, Belgium 3Department of Psychiatry, UZ Brussel/ Free University of Brussels, 布鲁塞尔, Belgium 4Department of Electrical Engineering,
研究
RESEARCH Probing the association between resting-state brain network dynamics and psychological resilience Dominik Kraft1 and Christian J. Fiebach1,2 1Department of Psychology, Goethe University Frankfurt, 法兰克福, Germany 2Brain Imaging Center, Goethe University Frankfurt, Frankfurt am Main, Germany Keywords: Resting-state, Time-varying connectivity, Multilayer modularity, Psychological resilience, Network reconfigurations, Node flexibility, Node promiscuity, Node degree a n o p e n a c c e s s j
研究
RESEARCH Test-retest reliability of regression dynamic causal modeling Stefan Frässle1 and Klaas E. Stephan1,2 1Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland 2Max Planck Institute for Metabolism Research, Cologne, Germany Keywords: Regression dynamic causal modeling, rDCM, Generative model, Effective connectivity, Connectomics, Test-retest reliability a n o p e n a c c e s s j o
方法
METHODS A regression framework for brain network distance metrics Chal E. Tomlinson1 , Paul J. Laurienti2,3, Robert G. Lyday2,3, and Sean L. Simpson2,4 1Department of Biostatistics, University of North Carolina at Chapel Hill, 教堂山, NC, USA 2Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, NC, USA 3Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA 4Department of Biostatistics and
研究
RESEARCH Adaptive rewiring in nonuniform coupled oscillators MohamamdHossein Manuel Haqiqatkhah1,2 and Cees van Leeuwen1,3 1Brain and Cognition Research Unit, KU Leuven, Leuven, Belgium 2Department of Methodology and Statistics, Utrecht University, 乌得勒支, The Netherlands 3Center for Cognitive Science, TU Kaiserslautern, Kaiserslautern, Germany Keywords: Evolving neural networks, Neural oscillators, Dynamical systems, Complexity a n o p e n a c c e s s j o u
研究
RESEARCH Quantifying brain state transition cost via Schrödinger Bridge Genji Kawakita1, Shunsuke Kamiya1, Shuntaro Sasai2,3, Jun Kitazono1, and Masafumi Oizumi1 1Graduate School of Arts and Sciences, University of Tokyo, 东京, Japan 2Araya Inc., 东京, Japan 3University of Wisconsin–Madison, 麦迪逊, WI, USA Keywords: Brain state transition, Network control theory, Functional MRI, Information theory, Schrödinger Bridge a n o p e n a c c e s
PERSPECTIVE
PERSPECTIVE Feeding the machine: Challenges to reproducible predictive modeling in resting-state connectomics Andrew Cwiek1,2 , Sarah M. Rajtmajer3,4 , Bradley Wyble1 , Vasant Honavar3,5 , Emily Grossner1,2, and Frank G. Hillary1,2 1Department of Psychology, Pennsylvania State University, 大学园, PA, USA 2Social Life and Engineering Sciences Imaging Center, Pennsylvania State University, 大学园, PA, USA 3College of Information Sciences and Technology, Pennsylvania State University, 大学
研究
RESEARCH Disruption of large-scale electrophysiological networks in stroke patients with visuospatial neglect Tomas Ros1,2 , Abele Michela1, Anaïs Mayer3, Anne Bellmann3, Philippe Vuadens3, Victorine Zermatten4, Arnaud Saj1,5, and Patrik Vuilleumier1 1Department of Neuroscience, University of Geneva, 日内瓦, Switzerland 2CIBM Center for Biomedical Imaging, Geneva University Hospitals, 日内瓦, Switzerland 3Romand Clinic of Readaptation, SUVA, Sion, Switzerland 4Rehabilitation Clinic Valais de Coeur, Sion, Switzerland 5Department of Neurology,