FUNCIÓN DE ENFOQUE: Connectivity, Cognición, 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, Department of Health Sciences, Boston University, Bostón, MAMÁ, USA 2Departments of Anatomy and Neurobiology, Boston University, Boston University, Bostón, MAMÁ, USA 3Department of Radiology, Massachusetts

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, Universidad Stanford, stanford, California, USA 2Department of Psychiatry and Behavioral Sciences, Universidad Stanford, stanford, California, USA *Equal contribution. Palabras clave: TDA, Mapper, Optimal transport, Multitask fMRI, Ongoing cognition, NeuroSynth a n o p e n a c c e s s j o

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

FUNCIÓN DE ENFOQUE: 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. GRAMO. Geurts1, Linda Douw1, and Menno M. Schoonheim1 1Department of Anatomy and Neurosciences, Amsterdam UMC,

FUNCIÓN DE ENFOQUE: 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, Anne M. van Nifterick1,2, Cornelis J. Stam2, Arjan Hillebrand2, Alida A. Gouw1,2, and Willem de Haan1,2 1Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Ámsterdam, Netherlands 2Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije

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, University of London, Egham, Surrey, UK 2Department of Psychology, University of Amsterdam, Ámsterdam, the Netherlands Keywords: Red, Métodos, Psychometrics, Neuroimaging, Autism a n o p e n a c c e s

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, Florida, USA 2Department of Psychiatry, University of Florida, Gainesville, Florida, USA *J. Nino and M. Febo are co-senior authors. Palabras clave: Alzheimer’s disease, Connectomics, Teoría de la percolación, Biomarker, resonancia magnética funcional, Graph theory a n o p e n a

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, chicago, IL, USA 2Department of Psychology, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin, USA 3Warren Alpert Medical School, Universidad marrón, Providencia, Rhode Island,

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, Sistemas, and Computational Intelligence sinc(i) (FICH-UNL/CONICET), Santa Fe, 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

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), Lausanne, Switzerland 2Perceptual Networks Group, University of Fribourg, Fribourg, Switzerland 3Department of Neurosciences, University of Padova, Padova, Italy 4Connectomics Lab, Department of Radiology, University Hospital of Lausanne and University

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, Bruselas, Belgium 4Department of Electrical Engineering,

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, Frankfurt, 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

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

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, Chapel Hill, CAROLINA DEL NORTE, USA 2Laboratory for Complex Brain Networks, Wake Forest School of Medicine, Winston-Salem, CAROLINA DEL NORTE, USA 3Department of Radiology, Wake Forest School of Medicine, Winston-Salem, CAROLINA DEL NORTE, USA 4Department of Biostatistics and

RESEARCH Adaptive rewiring in nonuniform coupled oscillators MohamamdHossein Manuel Haqiqatkhah1,2 and Cees van Leeuwen1,3 1Brain and Cognition Research Unit, KU Lovaina, Lovaina, Belgium 2Department of Methodology and Statistics, Universidad de Utrecht, Utrecht, 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

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, Tokio, Japan 2Araya Inc., Tokio, Japan 3University of Wisconsin–Madison, Madison, Wisconsin, 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 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, Universidad Estatal de Pensilvania, University Park, Pensilvania, USA 2Social Life and Engineering Sciences Imaging Center, Universidad Estatal de Pensilvania, University Park, Pensilvania, USA 3College of Information Sciences and Technology, Universidad Estatal de Pensilvania, Universidad

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, Geneva, Switzerland 2CIBM Center for Biomedical Imaging, Geneva University Hospitals, Geneva, Switzerland 3Romand Clinic of Readaptation, SUVA, Sion, Switzerland 4Rehabilitation Clinic Valais de Coeur, Sion, Switzerland 5Department of Neurology,