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1. Anatomo-functional correspondence in the voice-selective regions of human prefrontal cortex

Author

Mélina Cordeau, Ihsane Bichoutar, David Meunier, Kep-Kee Loh, Isaure Michaud, Olivier Coulon, Guillaume Auzias, and Pascal Belin

Subjects
Human, fMRI, Voice perception, Individual variability, Sulcal anatomy, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Group level analyses of functional regions involved in voice perception show evidence of 3 sets of bilateral voice-sensitive activations in the human prefrontal cortex, named the anterior, middle and posterior Frontal Voice Areas (FVAs). However, the relationship with the underlying sulcal anatomy, highly variable in this region, is still unknown. We examined the inter-individual variability of the FVAs in conjunction with the sulcal anatomy. To do so, anatomical and functional MRI scans from 74 subjects were analyzed to generate individual contrast maps of the FVAs and relate them to each subject's manually labeled prefrontal sulci. We report two major results. First, the frontal activations for the voice are significantly associated with the sulcal anatomy. Second, this correspondence with the sulcal anatomy at the individual level is a better predictor than coordinates in the MNI space. These findings offer new perspectives for the understanding of anatomical-functional correspondences in this complex cortical region. They also shed light on the importance of considering individual-specific variations in subject's anatomy.

Published
2023
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2. NeuroPycon: An open-source python toolbox for fast multi-modal and reproducible brain connectivity pipelines

Author

David Meunier, Annalisa Pascarella, Dmitrii Altukhov, Mainak Jas, Etienne Combrisson, Tarek Lajnef, Daphné Bertrand-Dubois, Vanessa Hadid, Golnoush Alamian, Jordan Alves, Fanny Barlaam, Anne-Lise Saive, Arthur Dehgan, and Karim Jerbi

Subjects
Magnetoencephalography (MEG), Electroencephalography (EEG), Electrophysiology, MRI, Functional connectivity, Graph theory, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Recent years have witnessed a massive push towards reproducible research in neuroscience. Unfortunately, this endeavor is often challenged by the large diversity of tools used, project-specific custom code and the difficulty to track all user-defined parameters. NeuroPycon is an open-source multi-modal brain data analysis toolkit which provides Python-based template pipelines for advanced multi-processing of MEG, EEG, functional and anatomical MRI data, with a focus on connectivity and graph theoretical analyses. Importantly, it provides shareable parameter files to facilitate replication of all analysis steps. NeuroPycon is based on the NiPype framework which facilitates data analyses by wrapping many commonly-used neuroimaging software tools into a common Python environment. In other words, rather than being a brain imaging software with is own implementation of standard algorithms for brain signal processing, NeuroPycon seamlessly integrates existing packages (coded in python, Matlab or other languages) into a unified python framework. Importantly, thanks to the multi-threaded processing and computational efficiency afforded by NiPype, NeuroPycon provides an easy option for fast parallel processing, which critical when handling large sets of multi-dimensional brain data. Moreover, its flexible design allows users to easily configure analysis pipelines by connecting distinct nodes to each other. Each node can be a Python-wrapped module, a user-defined function or a well-established tool (e.g. MNE-Python for MEG analysis, Radatools for graph theoretical metrics, etc.). Last but not least, the ability to use NeuroPycon parameter files to fully describe any pipeline is an important feature for reproducibility, as they can be shared and used for easy replication by others. The current implementation of NeuroPycon contains two complementary packages: The first, called ephypype, includes pipelines for electrophysiology analysis and a command-line interface for on the fly pipeline creation. Current implementations allow for MEG/EEG data import, pre-processing and cleaning by automatic removal of ocular and cardiac artefacts, in addition to sensor or source-level connectivity analyses. The second package, called graphpype, is designed to investigate functional connectivity via a wide range of graph-theoretical metrics, including modular partitions. The present article describes the philosophy, architecture, and functionalities of the toolkit and provides illustrative examples through interactive notebooks. NeuroPycon is available for download via github (https://github.com/neuropycon) and the two principal packages are documented online (https://neuropycon.github.io/ephypype/index.html, and https://neuropycon.github.io/graphpype/index.html). Future developments include fusion of multi-modal data (eg. MEG and fMRI or intracranial EEG and fMRI). We hope that the release of NeuroPycon will attract many users and new contributors, and facilitate the efforts of our community towards open source tool sharing and development, as well as scientific reproducibility.

Published
2020
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3. Visbrain: A Multi-Purpose GPU-Accelerated Open-Source Suite for Multimodal Brain Data Visualization

Author

Etienne Combrisson, Raphael Vallat, Christian O'Reilly, Mainak Jas, Annalisa Pascarella, Anne-lise Saive, Thomas Thiery, David Meunier, Dmitrii Altukhov, Tarek Lajnef, Perrine Ruby, Aymeric Guillot, and Karim Jerbi

Subjects
visualization, neuroscience, python, open-source, brain, OpenGL, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

We present Visbrain, a Python open-source package that offers a comprehensive visualization suite for neuroimaging and electrophysiological brain data. Visbrain consists of two levels of abstraction: (1) objects which represent highly configurable neuro-oriented visual primitives (3D brain, sources connectivity, etc.) and (2) graphical user interfaces for higher level interactions. The object level offers flexible and modular tools to produce and automate the production of figures using an approach similar to that of Matplotlib with subplots. The second level visually connects these objects by controlling properties and interactions through graphical interfaces. The current release of Visbrain (version 0.4.2) contains 14 different objects and three responsive graphical user interfaces, built with PyQt: Signal, for the inspection of time-series and spectral properties, Brain for any type of visualization involving a 3D brain and Sleep for polysomnographic data visualization and sleep analysis. Each module has been developed in tight collaboration with end-users, i.e., primarily neuroscientists and domain experts, who bring their experience to make Visbrain as transparent as possible to the recording modalities (e.g., intracranial EEG, scalp-EEG, MEG, anatomical and functional MRI). Visbrain is developed on top of VisPy, a Python package providing high-performance 2D and 3D visualization by leveraging the computational power of the graphics card. Visbrain is available on Github and comes with a documentation, examples, and datasets (http://visbrain.org).

Published
2019
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4. Could LC-NE-Dependent Adjustment of Neural Gain Drive Functional Brain Network Reorganization?

Author

Carole Guedj, David Meunier, Martine Meunier, and Fadila Hadj-Bouziane

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

The locus coeruleus-norepinephrine (LC-NE) system is thought to act at synaptic, cellular, microcircuit, and network levels to facilitate cognitive functions through at least two different processes, not mutually exclusive. Accordingly, as a reset signal, the LC-NE system could trigger brain network reorganizations in response to salient information in the environment and/or adjust the neural gain within its target regions to optimize behavioral responses. Here, we provide evidence of the co-occurrence of these two mechanisms at the whole-brain level, in resting-state conditions following a pharmacological stimulation of the LC-NE system. We propose that these two mechanisms are interdependent such that the LC-NE-dependent adjustment of the neural gain inferred from the clustering coefficient could drive functional brain network reorganizations through coherence in the gamma rhythm. Via the temporal dynamic of gamma-range band-limited power, the release of NE could adjust the neural gain, promoting interactions only within the neuronal populations whose amplitude envelopes are correlated, thus making it possible to reorganize neuronal ensembles, functional networks, and ultimately, behavioral responses. Thus, our proposal offers a unified framework integrating the putative influence of the LC-NE system on both local- and long-range adjustments of brain dynamics underlying behavioral flexibility.

Published
2017
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5. The neural bases of disgust for cheese: an fMRI study

Author

Jean-Pierre ROYET, David Meunier, Nicolas Torquet, Anne-Marie Mouly, and Tao Jiang

Subjects
Basal Ganglia, fMRI, liking, wanting, Food Aversion, reward circuit, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

The study of food aversion in humans by the induction of illness is ethically unthinkable, and it is difficult to propose a type of food that is disgusting for everybody. However, although cheese is considered edible by most people, it can also be perceived as particularly disgusting to some individuals. As such, the perception of cheese constitutes a good model to study the cerebral processes of food disgust and aversion. In this study, we show that a higher percentage of people are disgusted by cheese than by other types of food. Functional magnetic resonance imaging then reveals that the internal and external globus pallidus and the substantia nigra belonging to the basal ganglia are more activated in participants who dislike or diswant to eat cheese (Anti) than in other participants who like to eat cheese, as revealed following stimulation with cheese odors and pictures. We suggest that the aforementioned basal ganglia structures commonly involved in reward are also involved in the aversive motivated behaviors. Our results further show that the ventral pallidum, a core structure of the reward circuit, is deactivated in Anti subjects stimulated by cheese in the wanting task, highlighting the suppression of motivation-related activation in subjects disgusted by cheese.

Published
2016
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6. Disrupted modularity and local connectivity of brain functional networks in childhood-onset schizophrenia

Author

Aaron F Alexander-Bloch, Nitin eGogtay, David Meunier, Rasmus eBirn, Liv Clasen, Francois eLalonde, Rhoshel eLenroot, Jay eGiedd, and Edward T Bullmore

Subjects
Brain, Schizophrenia, fMRI, network, modularity, clustering, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Modularity is a fundamental concept in systems neuroscience, referring to the formation of local cliques or modules of densely intra-connected nodes that are sparsely inter-connected with nodes in other modules. Topological modularity of brain functional networks can quantify theoretically anticipated abnormality of brain network community structure--so called dysmodularity--in developmental disorders such as childhood-onset schizophrenia (COS). We used graph theory to investigate topology of networks derived from resting-state fMRI data on 13 COS patients and 19 healthy volunteers. We measured functional connectivity between each pair of 100 regional nodes, focusing on wavelet correlation in the frequency interval 0.05-0.1 Hz, then applied global and local thresholding rules to construct graphs from each individual association matrix over the full range of possible connection densities. We show how local thresholding based on the minimum spanning tree facilitates group comparisons of networks by forcing the connectedness of sparse graphs. Threshold-dependent graph theoretical results are compatible with the results of a k-means unsupervised learning algorithm and a multi-resolution (spin glass) approach to modularity, both of which also find community structure but do not require thresholding of the association matrix. In general modularity of brain functional networks was significantly reduced in COS, due to a relatively reduced density of intra-modular connections between neighboring regions. Other network measures of local organization such as clustering were also decreased, while complementary measures of global efficiency and robustness were increased, in the COS group. The group differences in complex network properties were mirrored by differences in simpler statistical properties of the data, such as the variability of the global time series and the internal homogeneity of the time series within anatomical regions of interest.

Published
2010
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7. Hierarchical modularity in human brain functional networks

Author

David Meunier, Renaud Lambiotte, Alex Fornito, Karen Ersche, and Edward T Bullmore

Subjects
Brain, network, hierarchy, information, modularity, graph theory, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules”) decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

Published
2009
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8. CamBAfx: workflow design, implementation and application for neuroimaging

Author

Cinly Ooi, Edward T Bullmore, Alle-Meije Wink, Levent Sendur, Anna Barnes, Sophie Achard, John Aspden, Sanja Abbott, Shigang Yue, Manfred Kitzbichler, David Meunier, Voichita Maxim, Raymond Salvador, Julian Henty, Roger Tait, Naresh Subramaniam, and John Suckling

Subjects
open source, batch processing, camba, eclipse, pipeline, rich client platform, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

CamBAfx is a workflow application designed for both researchers who use workflows to process data (consumers) and those who design them (designers). It provides a front-end (user interface) optimized for data processing designed in a way familiar to consumers. The back-end uses a pipeline model to represent workflows since this is a common and useful metaphor used by designers and is easy to manipulate compared to other representations like programming scripts. As an Eclipse Rich Client Platform application, CamBAfx's pipelines and functions can be bundled with the software or downloaded post-installation. The user interface contains all the workflow facilities expected by consumers. Using the Eclipse Extension Mechanism designers are encouraged to customize CamBAfx for their own pipelines. CamBAfx wraps a workflow facility around neuroinformatics software without modification. CamBAfx's design, licensing and Eclipse Branding Mechanism allow it to be used as the user interface for other software, facilitating exchange of innovative computational tools between originating labs.

Published
2009
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19. Is Migraine Associated to Brain Anatomical Alterations? New Data and Coordinate-Based Meta-analysis

Author

Rémy Masson, David Meunier, Salem Hannoun, Aurélie Bidet-Caulet, Geneviève Demarquay, Yohana Lévêque, Anne Caclin, Centre de recherche en neurosciences de Lyon (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon, Hospices Civils de Lyon (HCL), American University of Beirut Faculty of Medicine and Medical Center (AUB), Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), American University of Beirut [Beyrouth] (AUB), Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), ANR-11-LABX-0042,CORTEX,Construction, Fonction Cognitive et Réhabilitation du Cerveau(2011), ANR-10-LABX-0060,CeLyA,Lyon Acoustics Centre(2010), ANR-16-IDEX-0005,IDEXLYON,IDEXLYON(2016), Otten, Lisa, Construction, Fonction Cognitive et Réhabilitation du Cerveau - - CORTEX2011 - ANR-11-LABX-0042 - LABX - VALID, Lyon Acoustics Centre - - CeLyA2010 - ANR-10-LABX-0060 - LABX - VALID, and IDEXLYON - - IDEXLYON2016 - ANR-16-IDEX-0005 - IDEX - VALID

Subjects
Aura, tractbased spatial statistics, coordinate-based meta-analysis, Migraine Disorders, computer.software_genre, 050105 experimental psychology, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, Voxel, medicine, voxel-based morphometry, Humans, migraine, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Gray Matter, Gyrification, Left superior longitudinal fasciculus, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0303 health sciences, Radiological and Ultrasound Technology, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, 05 social sciences, Brain, Voxel-based morphometry, Anatomy, Sulcus, medicine.disease, Magnetic Resonance Imaging, White Matter, surface-based morphometry, Diffusion Tensor Imaging, medicine.anatomical_structure, Neurology, Migraine, Meta-analysis, Neurology (clinical), business, computer, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, 030217 neurology & neurosurgery, Diffusion MRI
Abstract

A growing number of studies investigate brain anatomy in migraine using voxel-(VBM) and surface-based morphometry (SBM), as well as diffusion tensor imaging (DTI). The purpose of this article is to identify consistent patterns of anatomical alterations associated with migraine. First, 19 migraineurs without aura and 19 healthy participants were included in a brain imaging study. T1-weighted MRIs and DTI sequences were acquired and analyzed using VBM, SBM and tract-based spatial statistics. No significant alterations of gray matter (GM) volume, cortical thickness, cortical gyrification, sulcus depth and white-matter tract integrity could be observed. However, migraineurs displayed decreased white matter (WM) volume in the left superior longitudinal fasciculus. Second, a systematic review of the literature employing VBM, SBM and DTI was conducted to investigate brain anatomy in migraine. Meta-analysis was performed using Seed-based d Mapping via permutation of subject images (SDM-PSI) on GM volume, WM volume and cortical thickness data. Alterations of GM volume, WM volume, cortical thickness or white-matter tract integrity were reported in 72%, 50%, 56% and 33% of published studies respectively. Spatial distribution and direction of the disclosed effects were highly inconsistent across studies. The SDM-PSI analysis revealed neither significant decrease nor significant increase of GM volume, WM volume or cortical thickness in migraine. Overall there is to this day no strong evidence of specific brain anatomical alterations reliably associated to migraine. Possible explanations of this conflicting literature are discussed.Trial registration numberNCT02791997, registrated February 6th, 2015.

Published
2021
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22. Sex differences in brain modular organization in chronic pain

Author

Kasey S. Hemington, Camille Fauchon, Rachael L. Bosma, Junseok A. Kim, Joshua C. Cheng, Karen D. Davis, Robert D. Inman, Natalie R. Osborne, Anton Rogachov, Peter Shih-Ping Hung, David Meunier, University Health Network, Institut de Neurosciences de la Timone (INT), and Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Cingulate cortex, medicine.medical_specialty, Ankylosing spondylitis, medicine.diagnostic_test, business.industry, Chronic pain, Arthritis, Magnetic resonance imaging, medicine.disease, 03 medical and health sciences, Functional brain, 0302 clinical medicine, Anesthesiology and Pain Medicine, Physical medicine and rehabilitation, medicine.anatomical_structure, Neurology, 030202 anesthesiology, [SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], medicine, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurology (clinical), business, 030217 neurology & neurosurgery, Default mode network, Anterior cingulate cortex
Abstract

International audience; Men and women can exhibit different pain sensitivities, and many chronic pain conditions are more prevalent in one sex. Although there is evidence of sex differences in the brain, it is not known whether there are sex differences in the organization of large-scale functional brain networks in chronic pain. Here, we used graph theory with modular analysis and machine-learning of resting-state-functional magnetic resonance imaging data from 220 participants: 155 healthy controls and 65 individuals with chronic low back pain due to ankylosing spondylitis, a form of arthritis. We found an extensive overlap in the graph partitions with the major brain intrinsic systems (ie, default mode, central, visual, and sensorimotor modules), but also sex-specific network topological characteristics in healthy people and those with chronic pain. People with chronic pain exhibited higher cross-network connectivity, and sex-specific nodal graph properties changes (ie, hub disruption), some of which were associated with the severity of the chronic pain condition. Females exhibited atypically higher functional segregation in the mid cingulate cortex and subgenual anterior cingulate cortex and lower connectivity in the network with the default mode and frontoparietal modules, whereas males exhibited stronger connectivity with the sensorimotor module. Classification models on nodal graph metrics could classify an individual's sex and whether they have chronic pain with high accuracies (77%-92%). These findings highlight the organizational abnormalities of resting-state-brain networks in people with chronic pain and provide a framework to consider sex-specific pain therapeutics.

Published
2020
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25. Toward next-generation primate neuroscience: A collaboration-based strategic plan for integrative neuroimaging

Author

David C. Van Essen, Caspar M. Schwiedrzik, Takuro Ikeda, Shaomin Zhang, Marcello G. P. Rosa, Ning Liu, Aidan Murphy, Li Min Chen, Pinglei Bao, Julia Lehman, Yuki Hori, Pengcheng Li, Julien Vezoli, Peter H. Rudebeck, Yao Meng, Julian 'Bene' Ramirez, Pierre Pouget, Guillermo Gallardo, Rogier B. Mars, Charles E. Schroeder, Minqing Jiang, Steve Frey, Michael P. Milham, Mohammad Hadi Aarabi, Pascal Belin, Patrick Friedrich, Bichan Wu, Hector Figueroa, Ye He, Charles L. Wilson, Melanie Wilke, Eunha Baeg, Fadila Hadj-Bouziane, Danny Garside, Marco Pagani, Ting-Yat Wong, Igor Kagan, Abdelhadi Essamlali, Bharat B. Biswal, Wasana Ediri Arachchi, Julio Villalon, Zheng Wang, Kacie Dougherty, Neo Sunhang Shi, Luciano Simone, Roberto Toro, Benjamin Jung, Masaki Fukunaga, Zhanguang Zuo, Loïc Magrou, Xiaowei Song, Kadharbatcha S. Saleem, Michele A. Basso, Eduardo A. Garza-Villarreal, Chihiro Yokoyama, Aaron Tanenbaum, Brian E. Russ, Alexandre Rosa Franco, Alison R. Weiss, Isabel Restrepo, Alan C. Evans, Lixia Gao, Nobuyuki Kimura, Augix Guohua Xu, Piotr Majka, Colline Poirier, Justine Cléry, Bassem Hiba, Alessandro Gozzi, Xiaojie Wang, Nick Upright, Stan Colcombe, Yang Gao, Won Mok Shim, Eduardo Rojas Hortelano, Takuya Hayashi, Anna S. Mitchell, Andrew F. Rossi, Itamar Kahn, Jorge Jaramillo, Henry C. Evrard, Xin Yumeng, Gregory Kiar, Sean Froudist-Walsh, Elise Roger, Roberto A. Gulli, Yufan Wang, Damien A. Fair, Yuguang Zhao, Stephen J. Sawiak, Boris C. Bernhardt, Ulysse Klatzmann, Ashkan Alvand, Kep Kee Loh, David Schaeffer, Virginie Sivan, Daniel S. Margulies, Carly M. Drzewiecki, Tomoko Sakai, Ting Xu, Cirong Liu, Essa Yacoub, Theresa M. Desrochers, Seok-Jun Hong, Sethu Boopathy, Reza Azadi, Lu Yuheng, Aarit Ahuja, Zhifeng Liang, Elena Borra, Fernanda Ponce, Robert Dahnke, Julien Sein, Li Deying, Jitendra Sharma, A.J. Mitchell, Roger Little, Luqi Cheng, Du Xiao, Choong-Wan Woo, Xinhui Li, Chris Petkov, Ruiliang Bai, D Zaldivar, Sheyla Mejia, Haidong D. Lu, Nikoloz Sirmpilatze, Diego Emanuel Ortuzar Martinez, Suzanne N. Haber, Catherine Elorette, Yue Cui, Michael Hawrylycz, Jerome Sallet, Wim Vanduffel, Daniel R. Glen, Ralph Adolphs, Dongrong Xu, Simon Clavagnier, Rakshit Dadarwal, Marzio Gerbella, Hannah Doyle, Ningrong Ye, Xiaojin Liu, Xinyu Liu, Quansheng He, Christopher R. Madan, Vikas Pareek, James Cavanaugh, Sze Chai Kwok, Zhang Ying, Sam Vickery, Xiaoguang Tian, Zhou Xufeng, Bevil R. Conway, Mark Postans, Wei-an Sheng, Gianfranco Chavez, Rober Boshra, Yuki Kikuchi, Michael Ortiz-Rios, Céline Amiez, Felix Hoffstaedter, Elizabeth A. Buffalo, Amy Howard, Hsin-Yi Lai, Marianne Duyck, Samy Rima, Froesel Mathilda, Towela Mvula, Guilherme Freches, Alfonso Fajardo, Maria de la Iglesia-Vaya, Ana Rita Ribeiro Gomes, Xiongjie Yu, Afonso C. Silva, Andrew S. Fox, Long Cao, Anna W. Roe, Meizhen Qian, David Meunier, Erika Raven, Nicola Palomero-Gallagher, Jordy Tasserie, Joonas A. Autio, Francois Chouinard-Decorte, Hank P. Jedema, Shasha Yue, Xinjian Li, Xiaodong Chen, Kathleen Rockland, Satoka Hashimoto Fujimoto, Amiez Celine, Melina Cordeau, Olivier Coulon, Ravi S. Menon, Sandra Gonzalez Torrecilla, Bjørg Elisabeth Kilavik, Adam Messinger, Hecheng Jin, Steven Giavasis, Pierce Perkins, Conor Liston, Yujie Hou, Jakob Seidlitz, Kelly Shen, Yvonne Bennett, Franck Lamberton, Maxime Gaudet-Trafit, Suliann Ben Hamed, Chris Klink, Sabine Kastner, Lucas R. Trambaiolli, Lucija Jankovic-Rapan, Atsushi Fujimoto, Nadira Yusif Rodriguez, Maeva Gacoin, Amir Shmuel, Katja Heuer, Austin K. Behel, Susann Boretius, Paul A. Taylor, Child Mind Institute, Institute of Neurosciences and Psychology [Glasgow], University of Glasgow, Institut des sciences cognitives Marc Jeannerod - Centre de neuroscience cognitive - UMR5229 (ISC-MJ), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), University of Tübingen, Oregon Health and Science University [Portland] (OHSU), New York University [New York] (NYU), NYU System (NYU), Princeton Neuroscience Institute [Princeton], Consortium, PRIMatE Data and Resource Exchange (PRIME-DRE) Global Collaboration Workshop and, Institut des sciences cognitives Marc Jeannerod - Centre de neuroscience cognitive - UMR5229 (CNC), Nathan S. Kline Institute for Psychiatric Research (NKI), New York State Office of Mental Health, Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Nencki Institute of Experimental Biology, Polska Akademia Nauk = Polish Academy of Sciences (PAN), Monash University [Clayton], Wellcome Trust Centre for Integrative Neuroimaging (WIN - FMRIB), University of Oxford, Donders Institute for Brain, Cognition and Behaviour, Radboud University [Nijmegen], National Institute of Mental Health (NIMH), Newcastle University [Newcastle], McConnell Brain Imaging Centre (MNI), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Laboratorium voor Neuro- en Psychofysiologie, Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), and Washington University in Saint Louis (WUSTL)

Subjects
Strategic planning, 0303 health sciences, Open science, biology, Action, intention, and motor control, Resource exchange, [SCCO.NEUR]Cognitive science/Neuroscience, Neuroscience(all), General Neuroscience, Nonhuman primate, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, biology.animal, Primate, Beacon - Precision Imaging, ddc:610, Psychology, Neuroscience, ComputingMilieux_MISCELLANEOUS, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Contains fulltext : 239574.pdf (Publisher’s version ) (Closed access) Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience. 5 p.

Published
2022
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26. Centering inclusivity in the design of online conferences - An OHBM - Open Science perspective

Author

Elizabeth Levitis, Cassandra Doris Gould van Praag, Remi Gau, Stephan Heunis, Elizabeth DuPre, Greg Kiar, Katherine L Bottenhorn, Tristan Glatard, Aki Nikolaidis, Kirstie Jane Whitaker, Matteo Mancini, Guiomar Niso, Soroosh Afyouni, Eva Alonso Ortiz, Stefan Appelhoff, Aurina Arnatkeviciute, Melvin Selim ATAY, Tibor Auer, Giulia Baracchini, Johanna Margarete Marianne Bayer, Michael J. S. Beauvais, Janine Diane Bijsterbosch, Isil Poyraz Bilgin, Saskia Bollmann, Steffen Bollmann, Rotem Botvinik-Nezer, Molly G Bright, Vince D Calhoun, Xiao Chen, Sidhant Chopra, Hu Chuan-Peng, Thomas Close, Savannah Cookson, Cameron Craddock, Alejandro De La Vega, Benjamin De Leener, Damion Demeter, Paola Di Maio, Erin W Dickie, Simon B Eickhoff, Oscar Esteban, Karolina Finc, Matteo Frigo, Saampras Ganesan, Melanie Ganz, Kelly Garner, Eduardo A. Garza-Villarreal, Gabriel Gonzalez-Escamilla, Rohit Goswami, John David Griffiths, Tijl Grootswagers, Samuel Guay, Olivia Guest, Daniel A. Handwerker, Peer Herholz, Katja Heuer, Dorien Huijser, Vittorio Iacovella, Michael Joseph, Agah Karakuzu, David Keator, Xenia Kobeleva, Manoj Kumar, Angie Laird, Linda J. Larson-Prior, Alexandra Lautarescu, Alberto Lazari, Jon Haitz Legarreta Gorroño, Jeff jeffers, Jinglei Lv, Sina Mansour L., David Meunier, Dustin Moraczewski, Tulika Nandi, Samuel A. Nastase, Matthias Nau, Stephanie Noble, Martin Norgaard, Johnes Obungoloch, Robert Oostenveld, Edwina R Orchard, Ana Luísa Pinho, Russell Poldrack, Anqi Qiu, Pradeep Reddy Raamana, Ariel Rokem, Saige Rutherford, Malvika Sharan, Thomas Shaw, Warda T Syeda, Meghan M. Testerman, Roberto Toro, Sofie L. Valk, Sofie Van Den Bossche, Gael P. Varoquaux, Frantisek Vasa, Michele Veldsman, Jakub Vohryzek, Adina Svenja Wagner, Reubs J Walsh, Tonya White, null zuxfoucault, Xihe Xie, Chao-Gan Yan, Yu-Fang Yang, Yohan Yee, Gaston E Zanitti, Ana Van Gulick, Eugene Duff, Camille MAUMET, National Institute of Mental Health (NIMH), University College of London [London] (UCL), University of Oxford, Université Catholique de Louvain = Catholic University of Louvain (UCL), Eindhoven University of Technology [Eindhoven] (TU/e), McGill University = Université McGill [Montréal, Canada], Florida International University [Miami] (FIU), Concordia University [Montreal], Child Mind Institute, The Alan Turing Institute, University of Sussex, Cardiff University, École Polytechnique de Montréal (EPM), Indiana University [Bloomington], Indiana University System, Universidad Politécnica de Madrid (UPM), Max Planck Institute for Human Development, Max-Planck-Gesellschaft, Monash University [Melbourne], Middle East Technical University [Ankara] (METU), University of Surrey (UNIS), Montreal Neurological Institute and Hospital, University of Melbourne, Orygen Youth Health Research Centre [Melbourne], Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), University of Reading (UOR), University of Queensland [Brisbane], Dartmouth College [Hanover], Northwestern University [Evanston], Georgia State University, University System of Georgia (USG), Institute of Psychology [Beijing], Chinese Academy of Sciences [Changchun Branch] (CAS), University of Chinese Academy of Sciences [Beijing] (UCAS), Nanjing Normal University (NNU), The University of Sydney, University of California (UC), University of Texas at Austin [Austin], CHU Sainte Justine [Montréal], Institute for Globally Distributed Open Research and Education (IGDORE ), Centre for Addiction and Mental Health [Toronto] (CAMH), University of Toronto, Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf], Jülich Research Centre, Université de Lausanne = University of Lausanne (UNIL), Nicolaus Copernicus University [Toruń], Université Côte d'Azur (UCA), Computational Imaging of the Central Nervous System (ATHENA), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Rigshospitalet [Copenhagen], Copenhagen University Hospital, University of Copenhagen = Københavns Universitet (UCPH), University of Birmingham [Birmingham], Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU), University of Iceland [Reykjavik], Indian Institute of Technology Kanpur (IIT Kanpur), Western Sydney University, Université de Montréal (UdeM), Radboud University [Nijmegen], Centre de Recherche Interdisciplinaire / Center for Research and Interdisciplinarity [Paris, France] (CRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Erasmus University Rotterdam, Universiteit Leiden, University of Trento [Trento], Université du Québec à Montréal = University of Québec in Montréal (UQAM), University Hospital Bonn, German Research Center for Neurodegenerative Diseases - Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Princeton University, University of Arkansas for Medical Sciences (UAMS), Arkansas Children's Research Institute, King‘s College London, Université de Sherbrooke (UdeS), Aarhus University [Aarhus], Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Yale University [New Haven], Stanford University, Mbarara University of Science and Technology [Mbarara] (MUST), Karolinska Institutet [Stockholm], Université Paris-Saclay, National University of Singapore (NUS), Johns Hopkins University (JHU), University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), University of Washington [Seattle], Radboud University Medical Center [Nijmegen], University of Michigan [Ann Arbor], University of Michigan System, Institut Pasteur [Paris] (IP), Universiteit Gent = Ghent University (UGENT), Vrije Universiteit Amsterdam [Amsterdam] (VU), Department of Public Health, Erasmus University Medical Centre, Rotterdam, Erasmus University Medical Centre, Rotterdam, Academia Sinica, Weill Medical College of Cornell University [New York], Chinese Academy of Sciences [Beijing] (CAS), University of Würzburg, The Hospital for sick children [Toronto] (SickKids), Carnegie Mellon University [Pittsburgh] (CMU), Neuroimagerie: méthodes et applications (Empenn), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), R25-DA051675, National Institutes of Health, 1631325, National Science Foundation, 5R21MH118556-02, National Institute of Mental Health, BB/S008314/1, Biotechnology and Biological Sciences Research Council, G036716N, Fonds Wetenschappelijk Onderzoek, University of Oxford [Oxford], University of California, University of Lausanne (UNIL), University of Copenhagen = Københavns Universitet (KU), Universidad Nacional Autónoma de México (UNAM), Johannes Gutenberg - Universität Mainz (JGU), Radboud university [Nijmegen], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Leiden University, Institut Pasteur [Paris], Universiteit Gent = Ghent University [Belgium] (UGENT), Empenn, Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), and Maumet, Camille

Subjects
SDG 16 - Peace, collaborative events, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, SDG 16 - Peace, Justice and Strong Institutions, Review, Justice and Strong Institutions, online conferences, diversity, World Wide Web, inclusivity, open science, ddc:610, Sociology
Abstract

As the global health crisis unfolded throughout the world, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical and legal barriers and effectively enabled many individuals who have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g. caregiving responsibilities. Yet, the mere existence of online conferences is unfortunately no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the setup of the conference can provide more visibility to well-established researchers and reduce opportunities for early career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design.Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to: attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

Published
2021
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28. NeuroPycon: An open-source python toolbox for fast multi-modal and reproducible brain connectivity pipelines

Author

Tarek Lajnef, Dmitrii Altukhov, David Meunier, Annalisa Pascarella, Mainak Jas, Golnoush Alamian, Etienne Combrisson, Jordan Alves, Vanessa Hadid, Arthur Dehgan, Anne-Lise Saive, Fanny Barlaam, Daphné Bertrand-Dubois, Karim Jerbi, Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Istituto per le Applicazioni del Calcolo 'Mauro Picone' (IAC), Consiglio Nazionale delle Ricerche [Roma] (CNR), Centre for Cognition and Decision Making [HSE, Moscow], Institut of Cognitive Neuroscience [HSE, Moscow] (ICN), Vysšaja škola èkonomiki = National Research University Higher School of Economics [Moscow] (HSE)-Vysšaja škola èkonomiki = National Research University Higher School of Economics [Moscow] (HSE), Signal, Statistique et Apprentissage (S2A), Laboratoire Traitement et Communication de l'Information (LTCI), Institut Mines-Télécom [Paris] (IMT)-Télécom Paris-Institut Mines-Télécom [Paris] (IMT)-Télécom Paris, Département Images, Données, Signal (IDS), Télécom ParisTech, Institut Polytechnique de Paris (IP Paris), Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Montréal (UdeM), Université du Québec à Montréal = University of Québec in Montréal (UQAM), University of Montreal, Aarhus University [Aarhus], Canada Research Chairs program and aDiscovery Grant (RGPIN-2015-04854) from the Natural Sciences andEngineering Research Council of Canada, a New Investigators Awardfrom the Fonds de Recherche du Quebec - Nature et Technologies (2018-NC-206005) and an IVADO-Apogee fundamental research project grant.This research is also supported in part by the FRQNT Strategic ClustersProgram (2020-RS4-265502 - Centre UNIQUE - Union Neurosciences&Artificial Intelligence - Quebec), Meunier, David, Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Centre de recherche en neurosciences de Lyon (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), National Research University Higher School of Economics [Moscow] (HSE)-National Research University Higher School of Economics [Moscow] (HSE), and National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR)

Subjects
Computer science, Source reconstruction, Functional connectivity, 0302 clinical medicine, Software, Magnetoencephalography (MEG), Multi-modality, MATLAB, computer.programming_language, 0303 health sciences, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 05 social sciences, Brain, Magnetoencephalography, Electroencephalography, Magnetic Resonance Imaging, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Toolbox, Electrophysiology, Neurology, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Algorithms, MNE, MRI, Brain networks, Cognitive Neuroscience, Neuroimaging, Brain imaging, 050105 experimental psychology, Nipype, lcsh:RC321-571, 03 medical and health sciences, Humans, 0501 psychology and cognitive sciences, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Electroencephalography (EEG), Implementation, MNE Source reconstruction, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, 030304 developmental biology, Pipelines, business.industry, Reproducibility of Results, Reproducible science, Modular design, Python (programming language), Graph theory, Computer architecture, Nerve Net, business, computer, 030217 neurology & neurosurgery, Electrophysiology MRI, Python
Abstract

Recent years have witnessed a massive push towards reproducible research in neuroscience. Unfortunately, this endeavor is often challenged by the large diversity of tools used, project-specific custom code and the difficulty to track all user-defined parameters. NeuroPycon is an open-source multi-modal brain data analysis toolkit which provides Python-based template pipelines for advanced multi-processing of MEG, EEG, functional and anatomical MRI data, with a focus on connectivity and graph theoretical analyses. Importantly, it provides shareable parameter files to facilitate replication of all analysis steps. NeuroPycon is based on the NiPype framework which facilitates data analyses by wrapping many commonly-used neuroimaging software tools into a common Python environment. In other words, rather than being a brain imaging software with is own implementation of standard algorithms for brain signal processing, NeuroPycon seamlessly integrates existing packages (coded in python, Matlab or other languages) into a unified python framework. Importantly, thanks to the multi-threaded processing and computational efficiency afforded by NiPype, NeuroPycon provides an easy option for fast parallel processing, which critical when handling large sets of multi-dimensional brain data. Moreover, its flexible design allows users to easily configure analysis pipelines by connecting distinct nodes to each other. Each node can be a Python-wrapped module, a user-defined function or a well-established tool (e.g. MNE-Python for MEG analysis, Radatools for graph theoretical metrics, etc.). Last but not least, the ability to use NeuroPycon parameter files to fully describe any pipeline is an important feature for reproducibility, as they can be shared and used for easy replication by others. The current implementation of NeuroPycon contains two complementary packages: The first, called ephypype, includes pipelines for electrophysiology analysis and a command-line interface for on the fly pipeline creation. Current implementations allow for MEG/EEG data import, pre-processing and cleaning by automatic removal of ocular and cardiac artefacts, in addition to sensor or source-level connectivity analyses. The second package, called graphpype, is designed to investigate functional connectivity via a wide range of graph-theoretical metrics, including modular partitions. The present article describes the philosophy, architecture, and functionalities of the toolkit and provides illustrative examples through interactive notebooks. NeuroPycon is available for download via github (https://github.com/neuropycon) and the two principal packages are documented online (https://neuropycon.github.io/ephypype/index.html. and https://neuropycon.github.io/graphpype/index.html). Future developments include fusion of multi-modal data (eg. MEG and fMRI or intracranial EEG and fMRI). We hope that the release of NeuroPycon will attract many users and new contributors, and facilitate the efforts of our community towards open source tool sharing and development, as well as scientific reproducibility.

Published
2020
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29. Sex differences in brain modular organization in chronic pain

Author

Camille, Fauchon, David, Meunier, Anton, Rogachov, Kasey S, Hemington, Joshua C, Cheng, Rachael L, Bosma, Natalie R, Osborne, Junseok A, Kim, Peter Shih-Ping, Hung, Robert D, Inman, and Karen D, Davis

Subjects
Male, Brain Mapping, Sex Characteristics, Neural Pathways, Brain, Humans, Female, Chronic Pain, Nerve Net, Magnetic Resonance Imaging
Abstract

Men and women can exhibit different pain sensitivities, and many chronic pain conditions are more prevalent in one sex. Although there is evidence of sex differences in the brain, it is not known whether there are sex differences in the organization of large-scale functional brain networks in chronic pain. Here, we used graph theory with modular analysis and machine-learning of resting-state-functional magnetic resonance imaging data from 220 participants: 155 healthy controls and 65 individuals with chronic low back pain due to ankylosing spondylitis, a form of arthritis. We found an extensive overlap in the graph partitions with the major brain intrinsic systems (ie, default mode, central, visual, and sensorimotor modules), but also sex-specific network topological characteristics in healthy people and those with chronic pain. People with chronic pain exhibited higher cross-network connectivity, and sex-specific nodal graph properties changes (ie, hub disruption), some of which were associated with the severity of the chronic pain condition. Females exhibited atypically higher functional segregation in the mid cingulate cortex and subgenual anterior cingulate cortex and lower connectivity in the network with the default mode and frontoparietal modules, whereas males exhibited stronger connectivity with the sensorimotor module. Classification models on nodal graph metrics could classify an individual's sex and whether they have chronic pain with high accuracies (77%-92%). These findings highlight the organizational abnormalities of resting-state-brain networks in people with chronic pain and provide a framework to consider sex-specific pain therapeutics.

Published
2020

30. Brainhack: Developing a culture of open, inclusive, community-driven neuroscience

Author

Selim Melvin Atay, Iska Moxon-Emre, Anders Eklund, Paula P. Brooks, Nandita Vijayakumar, Anibal Sólon Heinsfeld, Jean-Baptiste Poline, Yaroslav O. Halchenko, David Meunier, Daniela M. Hohmann, Martin Szinte, Arshitha Basavaraj, Andrija Štajduhar, Link Tejavibulya, Michael Dayan, Anisha Keshavan, Chao Jiang, Felix Hoffstaedter, Michael P. Milham, Davide Momi, Hua Xie, Ai Wern Chung, Georg Langs, Hao-Ting Wang, Xenia Kobeleva, Robert Oostenveld, Thomas G. Close, Lena Dorfschmidt, Jesse A. Brown, Serge Koudoro, J.P. Manzano-Patron, Isil P. Bilgin, Shreyas Fadnavis, Sylvain Takerkart, R. Cameron Craddock, Stephan Heunis, Scott Peltier, Kathryn Berluti, Hayli Spence, Pablo F. Damasceno, David H. O’Connor, Eleftherios Garyfallidis, Eugene P. Duff, Rudolph Pienaar, Nicolas Traut, AmanPreet Badhwar, Ali R. Khan, Marissa Laws, Abigail S. Greene, Richard A. I. Bethlehem, Angela R. Laird, Krista DeStasio, Ina Thome, Camille Maumet, Alexandru D. Iordan, P. Christiaan Klink, Damion V. Demeter, John A. Onofrey, Cassandra D. Gould van Praag, Jakub Vohryzek, Suzanne T. Witt, Aysha Motala, Valerie Hayot-Sasson, Geetika Gupta, Alexandre Rosa Franco, John W. VanMeter, Michel Thiebaut de Schotten, James M. Shine, Lucina Q. Uddin, Thomas S. Hartmann, Guillaume Flandin, Clara Moreau, Tomislav Lipic, Claire Bradley, Fernando A. Barrios, Daniel S. Margulies, R. Austin Benn, Sofie Van Den Bossche, Lydia Riedl, Xihe Xie, Christopher R. Madan, Roberto Toro, Viviana Siless, Fabrizio De Vico Fallani, Nikoloz Sirmpilatze, Emily Olafson, Anqi Qiu, Theresa W. Cheng, Valentina Borghesani, Sidhant Chopra, Claire Cury, Giorgio Marinato, Horea-Ioan Ioanas, Giorgia Cona, Michael Joseph, Angela Tam, Mathias Scharinger, Daniel A. Handwerker, Katherine L. Bottenhorn, Sina Mansour L, Kathryn L. Mills, Christopher J. Markiewicz, Elizabeth Levitis, Cyril Pernet, Stephanie J. Forkel, Agah Karakuzu, Edwina R Orchard, Sarah L. Dziura, Saige Rutherford, Kamalaker Dadi, Enrico Glerean, Desiree Lussier, Davide Poggiali, Molly Simmonite, Jason Kai, Jessica Flannery, Ting Xu, Jon Haitz Legarreta, Nasim Anousheh, Marco Bedini, Tristan Glatard, Thomas E. Nichols, Joscelin Rocha-Hidalgo, Erin W. Dickie, Dipankar Bachar, Malin Sandström, Xi-Nian Zuo, Pedro Pinheiro-Chagas, Laura C. Rice, Jakša Vukojević, Javier Gonzalez-Castillo, José C. García Alanis, Lorenzo Pasquini, Yu-Fang Yang, Matteo Mancini, Deena Shariq, Chao-Gan Yan, Laura Tomaz da Silva, César Caballero-Gaudes, Yasmine Bassil, Aurina Arnatkeviciute, Dustin Scheinost, Satrajit S. Ghosh, Gaël Varoquaux, Etienne Combrisson, Bramsh Qamar Chandio, Kelly Garner, Tiago Quendera, Patrick Friedrich, Shawn A. Rhoads, Roxane Licandro, Elizabeth DuPre, Aki Nikolaidis, Simon Schwab, Stephanie Noble, Guillaume Auzias, Daniel J. Lurie, Mahboobeh Parsapoor, Eneko Uruñuela, Andrew Doyle, Peer Herholz, Saampras Ganesan, Vincent Koppelmans, Corey Horien, Samir Das, Junaid S. Merchant, Siyuan Gao, Matheus Marcon, Nathalia Bianchini Esper, B.T. Thomas Yeo, Katja Heuer, Caroline O’Brien, Micaela Y. Chan, Sook-Lei Liew, Lindsay D. Oliver, Kirstie Whitaker, Christoph Vogelbacher, Dylan M. Nielson, Krisanne Litinas, Dorien C. Huijser, Pierre Bellec, R. Todd Constable, David N. Kennedy, Julia Sprenger, Lea-Theresa Mais, Oscar Esteban, Patrick J. Park, Patrick Callahan, Christopher R. Nolan, Johanna Bayer, Guillaume Dumas, Elise Bannier, Elizabeth A. McDevitt, Ariel Rokem, Samuel A. Nastase, Olivia W. Stanley, Ruggero Basanisi, Daniele Marinazzo, Gregory Kiar, Lisa Novello, Samuel Guay, John C. Flournoy, Stefano Moia, Kendra Oudyk, Fang-Cheng Yeh, Gustav Nilsonne, Thomas B. Shaw, Steve Wideman, Saskia Bollmann, Steffen Bollmann, Julia M. Huntenburg, Augusto Buchweitz, Matteo Visconti di Oleggio Castello, Dimitra Maoutsa, Lucy B. Whitmore, Catherine Alice Hahn, Antonino Vallesi, Remi Gau, Felipe Meneguzzi, Université Catholique de Louvain = Catholic University of Louvain (UCL), Yale University [New Haven], Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Max-Planck-Gesellschaft, Florida International University [Miami] (FIU), University of Reading (UOR), University of Würzburg, Champalimaud Centre for the Unknown [Lisbon], University of Melbourne, University of Cambridge [UK] (CAM), Georgetown University [Washington] (GU), Philipps Universität Marburg = Philipps University of Marburg, Université de Montréal (UdeM), University College of London [London] (UCL), University of Sussex, Universiteit Gent = Ghent University (UGENT), German Research Center for Neurodegenerative Diseases - Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Université de Sherbrooke (UdeS), Middle East Technical University [Ankara] (METU), McGill University = Université McGill [Montréal, Canada], Modelling brain structure, function and variability based on high-field MRI data (PARIETAL), Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Universiteit Leiden, Karolinska Institutet [Stockholm], Princeton University, Universität Zürich [Zürich] = University of Zurich (UZH), University of the Basque Country/Euskal Herriko Unibertsitatea (UPV/EHU), University medical center and campus biotech Geneva, Emory University [Atlanta, GA], Cardiff University's Brain Research Imaging Centre [Cardiff] (CUBRIC), School of Psychology [Cardiff University], Cardiff University-Cardiff University, The University of Sydney, Weill Cornell Medicine [Cornell University], Cornell University [New York], Università degli Studi di Padova = University of Padua (Unipd), Jülich Research Centre, University of Texas at Austin [Austin], Institut Pasteur [Paris] (IP), Centre de Recherche Interdisciplinaire / Center for Research and Interdisciplinarity [Paris, France] (CRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Basque Center on Cognition Brain and Language [Gipuzkoa, Espagne] (BCBL), Linköping University (LIU), University of Queensland [Brisbane], University of New South Wales [Sydney] (UNSW), Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), University of Maryland [College Park], University of Maryland System, University of Washington [Seattle], Harvard Medical School [Boston] (HMS), Child Mind Institute, University of Western Ontario (UWO), Indiana University [Bloomington], Indiana University System, Monash university, Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Neuroimagerie: méthodes et applications (Empenn), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), National Institute of Mental Health (NIMH), Università degli Studi di Trento (UNITN), Centro Nacional de Investigaciones Cardiovasculares Carlos III [Madrid, Spain] (CNIC), Instituto de Salud Carlos III [Madrid] (ISC), Queensland University of Technology [Brisbane] (QUT), University of California [San Francisco] (UC San Francisco), University of California (UC), Universidade Federal do Rio Grande do Sul [Porto Alegre] (UFRGS), University of Texas at Dallas [Richardson] (UT Dallas), University of Oregon [Eugene], Monash University [Melbourne], Boston Children's Hospital, Algorithms, models and methods for images and signals of the human brain (ARAMIS), Sorbonne Université (SU)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Neuroimagerie: méthodes et applications (EMPENN), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Chinese Academy of Sciences [Beijing] (CAS), Beijing Normal University (BNU), This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 867458 awarded to Julia M. Huntenburg, from ANR-19-DATA-0025 NeuroWebLab for Katja Heuer, Roberto Toro, and Nicholas Traut, and from NIH K00MH122372 for Stephanie Noble., Brainhack Community: Nasim Anousheh, Aurina Arnatkeviciute, Guillaume Auzias, Dipankar Bachar, Elise Bannier, Ruggero Basanisi, Arshitha Basavaraj, Marco Bedini, Pierre Bellec, R Austin Benn, Kathryn Berluti, Steffen Bollmann, Saskia Bollmann, Claire Bradley, Jesse Brown, Augusto Buchweitz, Patrick Callahan, Micaela Y Chan, Bramsh Q Chandio, Theresa Cheng, Sidhant Chopra, Ai Wern Chung, Thomas G Close, Etienne Combrisson, Giorgia Cona, R Todd Constable, Claire Cury, Kamalaker Dadi, Pablo F Damasceno, Samir Das, Fabrizio De Vico Fallani, Krista DeStasio, Erin W Dickie, Lena Dorfschmidt, Eugene P Duff, Elizabeth DuPre, Sarah Dziura, Nathalia B Esper, Oscar Esteban, Shreyas Fadnavis, Guillaume Flandin, Jessica E Flannery, John Flournoy, Stephanie J Forkel, Alexandre R Franco, Saampras Ganesan, Siyuan Gao, José C García Alanis, Eleftherios Garyfallidis, Tristan Glatard, Enrico Glerean, Javier Gonzalez-Castillo, Cassandra D Gould van Praag, Abigail S Greene, Geetika Gupta, Catherine Alice Hahn, Yaroslav O Halchenko, Daniel Handwerker, Thomas S Hartmann, Valérie Hayot-Sasson, Stephan Heunis, Felix Hoffstaedter, Daniela M Hohmann, Corey Horien, Horea-Ioan Ioanas, Alexandru Iordan, Chao Jiang, Michael Joseph, Jason Kai, Agah Karakuzu, David N Kennedy, Anisha Keshavan, Ali R Khan, Gregory Kiar, P Christiaan Klink, Vincent Koppelmans, Serge Koudoro, Angela R Laird, Georg Langs, Marissa Laws, Roxane Licandro, Sook-Lei Liew, Tomislav Lipic, Krisanne Litinas, Daniel J Lurie, Désirée Lussier, Christopher R Madan, Lea-Theresa Mais, Sina Mansour L, J P Manzano-Patron, Dimitra Maoutsa, Matheus Marcon, Daniel S Margulies, Giorgio Marinato, Daniele Marinazzo, Christopher J Markiewicz, Camille Maumet, Felipe Meneguzzi, David Meunier, Michael P Milham, Kathryn L Mills, Davide Momi, Clara A Moreau, Aysha Motala, Iska Moxon-Emre, Thomas E Nichols, Dylan M Nielson, Gustav Nilsonne, Lisa Novello, Caroline O'Brien, Emily Olafson, Lindsay D Oliver, John A Onofrey, Edwina R Orchard, Kendra Oudyk, Patrick J Park, Mahboobeh Parsapoor, Lorenzo Pasquini, Scott Peltier, Cyril R Pernet, Rudolph Pienaar, Pedro Pinheiro-Chagas, Jean-Baptiste Poline, Anqi Qiu, Tiago Quendera, Laura C Rice, Joscelin Rocha-Hidalgo, Saige Rutherford, Mathias Scharinger, Dustin Scheinost, Deena Shariq, Thomas B Shaw, Viviana Siless, Molly Simmonite, Nikoloz Sirmpilatze, Hayli Spence, Julia Sprenger, Andrija Stajduhar, Martin Szinte, Sylvain Takerkart, Angela Tam, Link Tejavibulya, Michel Thiebaut de Schotten, Ina Thome, Laura Tomaz da Silva, Nicolas Traut, Lucina Q Uddin, Antonino Vallesi, John W VanMeter, Nandita Vijayakumar, Matteo Visconti di Oleggio Castello, Jakub Vohryzek, Jakša Vukojević, Kirstie Jane Whitaker, Lucy Whitmore, Steve Wideman, Suzanne T Witt, Hua Xie, Ting Xu, Chao-Gan Yan, Fang-Cheng Yeh, B T Thomas Yeo, Xi-Nian Zuo, ANR-19-DATA-0025,NeuroWebLab,Un laboratoire de neuroscience collectif: Au delà de FAIR(2019), European Project: 867458,LC-FMR, Maumet, Camille, Un laboratoire de neuroscience collectif: Au delà de FAIR - - NeuroWebLab2019 - ANR-19-DATA-0025 - DONNEES - VALID, Brainhack: Developing a culture of open, inclusive, community-driven neuroscience - LC-FMR - 867458 - INCOMING, Leiden University, Weill Cornell Medicine [New York], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC), Universiteit Gent = Ghent University [Belgium] (UGENT), University Hospital Bonn, Sherbrooke Connectivity Imaging Lab [Sherbrooke] (SCIL), Département d'informatique [Sherbrooke] (UdeS), Faculté des sciences [Sherbrooke] (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS)-Faculté des sciences [Sherbrooke] (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS), Videos and Images Theory and Analytics Laboratory (VITAL), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Service NEUROSPIN (NEUROSPIN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Erasmus University Rotterdam, Origami (Origami), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Princeton Neuroscience Institute [Princeton], Human Neuroscience Platform, Brighton and Sussex Medical School (BSMS), Azienda Ospedale Università di Padova = Hospital-University of Padua (AOUP), Institute of Neuroscience and Medicine [Jülich] (INM-1), Département de Neuroscience - Department of Neuroscience, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPC), Queensland Brain Institute, Universidad Nacional Autónoma de México (UNAM), Radboud university [Nijmegen], McGovern Institute for Brain Research [Cambridge], Massachusetts Institute of Technology (MIT), The Brainhack Community - https://pubmed.ncbi.nlm.nih.gov/33932337, Philipps University of Marburg, University of the Basque Country [Bizkaia] (UPV/EHU), Universita degli Studi di Padova, Philipps Universität Marburg, Institut Pasteur [Paris], Empenn, Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), University of California [San Francisco] (UCSF), University of California, Geochemistry, and University of Padova [Padova, Italy]

Subjects
0301 basic medicine, Open science, Community building, Best practice, Neuroscience(all), Brainhack, Article, neuroscience, 03 medical and health sciences, 0302 clinical medicine, best practices, collaboration, community building, hackathon, inclusivity, open science, reproducibility, training, Congresses as Topic, Neurosciences, Practice Guidelines as Topic, Communication, Internet, Research community, Medical Bioscience, Psychology, ddc:610, Sociology, Brainhack Community, Training, Neurology & Neurosurgery, Scientific progress, organization & administration [Neurosciences], General Neuroscience, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, Medicinsk biovetenskap, 030104 developmental biology, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Cognitive Sciences, Engineering ethics, 030217 neurology & neurosurgery
Abstract

Available online 30 April 2021. Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress. The present manuscript is part of a growing community effort to collate Brainhack-related insights and expertise into a Jupyter Book (http://brainhack.org/brainhack_jupyter_book/) that will serve as a centralized set of resources for the community; we acknowledge all the individuals who contributed and will make ongoing contributions to these resources. A pre-print version of the present manuscript is available as part of the Jupyter Book. Moreover, we would like to acknowledge all Brainhack organizers, supporters, presenters, and participants for their contribution to growing and maintaining this community. The benefits described in this manuscript would not be possible without them. We also thank all institutions, labs, and organizations who have helped this community grow, meet in stimulating environments, and add an excellent educational resource pool and agenda. With an expanding community, Brainhack’s support network keeps growing, and we thank all labs and individual researchers for their dedication and expertise offered to this community (see http://brainhack.org/brainhack_jupyter_book/acknowledgments.html for a full list of individual acknowledgments; an updated list will be maintained in the Jupyter Book). Grants and funding bodies: This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 867458 awarded to Julia M. Huntenburg; from ANR-19-DATA-0025 NeuroWebLab for Katja Heuer, Roberto Toro, and Nicholas Traut; and from NIH K00MH122372 for Stephanie Noble. The Brainhack Community member list and contributions of the different authors are detailed at http://brainhack.org/brainhack_jupyter_book/contributors.html. Our crediting system is described here: http://brainhack.org/brainhack_jupyter_book/neuroview_authorship-agreement.html.

Published
2021
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31. Mobility Practices, Value of Time and Transport Appraisal

Author

David Meunier

Subjects
Travel time, Cost–benefit analysis, media_common.quotation_subject, Economics, Quality (business), Kosten nutzen analyse, Environmental economics, Affect (psychology), Value (mathematics), Value of time, media_common
Abstract

This paper discusses whether changes in mobility practices affect value of travel time savings. It considers the relationship between the theory of the value of time and its practical application in traffic models and cost-benefit analysis. The discussion covers the need to distinguish variations in utility due to changes in the quantity and quality of time spent in travelling, the relationships between changes in value of time and mobility practices and between collective and individual values of time.

Published
2020
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32. The Modular Organization of Pain Brain Networks: An fMRI Graph Analysis Informed by Intracranial EEG

Author

Camille Fauchon, David Meunier, Roland Peyron, I. Faillenot, Hélène Bastuji, Luis Garcia-Larrea, and Florence B. Pomares

Subjects
0301 basic medicine, Power graph analysis, Anterior insula, business.industry, Conscious perception, graph theory, functional connectivity, acute pain, Modular design, Intracranial eeg, intracranial EEG, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, network hubs, Connectome, General Earth and Planetary Sciences, Original Article, Functional organization, Psychology, business, Neuroscience, 030217 neurology & neurosurgery, General Environmental Science, Information integration
Abstract

Intracranial EEG (iEEG) studies have suggested that the conscious perception of pain builds up from successive contributions of brain networks in less than 1 s. However, the functional organization of cortico-subcortical connections at the multisecond time scale, and its accordance with iEEG models, remains unknown. Here, we used graph theory with modular analysis of fMRI data from 60 healthy participants experiencing noxious heat stimuli, of whom 36 also received audio stimulation. Brain connectivity during pain was organized in four modules matching those identified through iEEG, namely: 1) sensorimotor (SM), 2) medial fronto-cingulo-parietal (default mode-like), 3) posterior parietal-latero-frontal (central executive-like), and 4) amygdalo-hippocampal (limbic). Intrinsic overlaps existed between the pain and audio conditions in high-order areas, but also pain-specific higher small-worldness and connectivity within the sensorimotor module. Neocortical modules were interrelated via “connector hubs” in dorsolateral frontal, posterior parietal, and anterior insular cortices, the antero-insular connector being most predominant during pain. These findings provide a mechanistic picture of the brain networks architecture and support fractal-like similarities between the micro-and macrotemporal dynamics associated with pain. The anterior insula appears to play an essential role in information integration, possibly by determining priorities for the processing of information and subsequent entrance into other points of the brain connectome.

Published
2020
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33. Brain activity sustaining the modulation of pain by empathetic comments

Author

Luis Garcia-Larrea, David Meunier, Roland Peyron, Florian Chouchou, Charles Quesada, Camille Fauchon, I. Faillenot, Ingénierie, Recherche et Intervention, Sport Santé et Environnement (IRISSE), and Université de La Réunion (UR)

Subjects
Adult, Male, 0301 basic medicine, medicine.medical_specialty, Brain activity and meditation, media_common.quotation_subject, Precuneus, lcsh:Medicine, Pain, Empathy, Audiology, Insular cortex, behavioral disciplines and activities, Brain mapping, Article, Feedback, 03 medical and health sciences, 0302 clinical medicine, Cortex (anatomy), medicine, Humans, [PHYS.MECA.BIOM]Physics [physics]/Mechanics [physics]/Biomechanics [physics.med-ph], lcsh:Science, ComputingMilieux_MISCELLANEOUS, media_common, Brain Mapping, Multidisciplinary, Autobiographical memory, lcsh:R, Brain, Pain Perception, 030104 developmental biology, medicine.anatomical_structure, Posterior cingulate, lcsh:Q, Female, Sensory processing, Nerve Net, Psychology, psychological phenomena and processes, 030217 neurology & neurosurgery
Abstract

Empathetic verbal feedback from others has been shown to alleviate the intensity of experimental pain. To investigate the brain changes associated with this effect, we conducted 3T-fMRI measurements in 30 healthy subjects who received painful thermal stimuli on their left hand while overhearing empathetic, neutral or unempathetic comments, supposedly made by experimenters, via headsets. Only the empathetic comments significantly reduced pain intensity ratings. A whole-brain BOLD analysis revealed that both Empathetic and Unempathetic conditions significantly increased the activation of the right anterior insular and posterior parietal cortices to pain stimuli, while activations in the posterior cingulate cortex and precuneus (PCC/Prec) were significantly stronger during Empathetic compared to Unempathetic condition. BOLD activity increased in the DLPFC in the Empathetic condition and decreased in the PCC/Prec and vmPFC in the Unempathetic condition. In the Empathetic condition only, functional connectivity increased significantly between the vmPFC and the insular cortex. These results suggest that modulation of pain perception by empathetic feedback involves a set of high-order brain regions associated with autobiographical memories and self-awareness, and relies on interactions between such supra-modal structures and key nodes of the pain system.

Published
2019
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34. Ex-post evaluations in Norway and France

Author

Morten Welde and David Meunier

Subjects
050210 logistics & transportation, Engineering, Ex-ante, Cost–benefit analysis, business.industry, media_common.quotation_subject, 05 social sciences, Environmental resource management, 0211 other engineering and technologies, 021107 urban & regional planning, 02 engineering and technology, Norwegian, language.human_language, 0502 economics and business, language, Quality (business), business, Environmental planning, media_common
Abstract

The paper presents the French and Norwegian ex-post evaluation frameworks and outlines questions that ex-post analysis should address. French and Norwegian results are compared, providing indications on ex-post evaluation frameworks’ tailoring and feedback on the quality of ex ante assessments.

Published
2017
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35. Post-learning paradoxical sleep deprivation impairs reorganization of limbic and cortical networks associated with consolidation of remote contextual fear memory in mice

Author

Gaël Malleret, Marius Rosier, David Meunier, Léa Le Barillier, Malika El Yacoubi, Paul-Antoine Salin, Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Ville, Mobilité, Transport (LVMT ), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC), Centre de recherche en neurosciences de Lyon (CRNL), and École des Ponts ParisTech (ENPC)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Marne-la-Vallée (UPEM)

Subjects
Male, 0301 basic medicine, Brain activity and meditation, Emotions, Prefrontal Cortex, Sleep, REM, Hippocampus, Gyrus Cinguli, Mice, 03 medical and health sciences, [SCCO]Cognitive science, 0302 clinical medicine, Physiology (medical), Limbic System, medicine, Animals, Learning, Anterior cingulate cortex, ComputingMilieux_MISCELLANEOUS, Early Growth Response Protein 1, Memory Consolidation, Recall, Basolateral Nuclear Complex, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, Fear, Mice, Inbred C57BL, Sleep deprivation, Memory, Short-Term, 030104 developmental biology, medicine.anatomical_structure, Mental Recall, Sleep Deprivation, Orbitofrontal cortex, Neurology (clinical), medicine.symptom, business, Immediate early gene, Neuroscience, 030217 neurology & neurosurgery, Basolateral amygdala
Abstract

Study Objectives Paradoxical sleep (PS) has been shown to play an important role in memory, in particular in emotional memory processes. However, the involvement of this particular sleep stage in the systemic consolidation of remote (30 days old) memory has never been tested. We examined whether post-learning PS could play a role in the consolidation of remote fearful memory and in the brain network reorganization that depends on it. Methods Mice were PS-deprived during 6 hours after contextual fear conditioning using an automated method, and their memory was tested either 1 day or 30 days after learning. Brain activity during retrieval was assessed using the immediate early gene Egr1 (Zif 268) as a neuronal marker of activity. Results We found that PS deprivation impaired the recall of remote (30 days)-but not recent (1 day)-memory. We also showed that the superficial layers of the anterior cingulate cortex were significantly less activated during the retrieval of remote memory after PS deprivation. In contrast, after such deprivation, retrieval of remote memory significantly activated several areas involved in emotional processing such as the CA1 area of the ventral hippocampus, the basolateral amygdala and the superficial layers of the ventral orbitofrontal cortex. By performing graph-theoretical analyses, our result also suggests that post-learning PS deprivation could impact the reorganization of the functional connections between limbic areas in order to reduce the level of global activity in this network. Conclusions These findings suggest an important role for PS in the systemic consolidation of remote memory.

Published
2018
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36. Evolutions of the Reference Values Used in Transport CBA National Guidelines of 3 Countries and What they Reveal

Author

Hélène Le Maître, David Meunier, Tom Worsley, Christoph Walther, and Alexander Dahl

Subjects
Cost–benefit analysis, business.industry, cost-benefit analysis, 050204 development studies, 05 social sciences, Environmental resource management, reference values, Environmental economics, Reference values, 0502 economics and business, guidelines, Business, 050207 economics, transport projects, Transport infrastructure
Abstract

The paper presents, analyses and compares the evolution of reference values used in national guidelines issued for cost-benefit analysis of transport infrastructure projects, over the last fifty years, in France, UK and Germany.

Published
2016
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37. NeuroPycon: A python package for efficient multi-modal brain network analysis

Author

David Meunier, Annalisa Pascarella, Daphné Bertrand-Dubois, Jordan Alves, Fanny Barlaam, Arthur Dehgan, Tarek Lajnef, Etienne Combrisson, Dmitrii Altukhov, and Karim Jerbi

Subjects
python, open source, meg, fmri, connectivity, data analysis, eeg
Abstract

Background. With the exponential increase in data dimension and methodological complexities, brain networks analysis with MEG and EEG has become an increasingly challenging and time-consuming endeavor. To date, performing all the data processing steps that are required for a complete MEG/EEG analysis pipeline often require the use of a multitude of software packages and in-house or custom tools (e.g. MRI segmentation, pre-processing, source reconstruction, graph theoretical analysis, statistics). This is not only cumbersome, but may also increase sources of errors and hinders replication of results. Here we describe NeuroPycon, an open-source, multi-modal brain data analysis kit which provides Python-based pipelines for advanced multi-thread processing of fMRI, MEG, and EEG data, with a focus on connectivity and graph analyses [1]. Methods. NeuroPycon is based on the NiPype framework [2] which facilitates data analyses by wrapping numerous commonly-used neuroimaging software solutions into a common python framework. NeuroPycon allows accessing and interfacing with the existing open-science neuroimaging software and signal processing toolboxes, within a unified framework relying on several freely available Python packages which are developed for efficient and fast parallel processing. The current implementation of NeuroPycon comprises three different packages: 2 of 3 - ephypype is mainly based on MNE-Python package [3] and includes pipelines for electrophysiology analyses. Current implementation features MEG/EEG data import, data pre-processing and cleaning via an automatic removal of eyes and heart-related artefacts, and sensor or source-level connectivity analyses - graphpype is based on radatools [4], a set of freely distributed applications aimed at analyses of Complex Networks. It comprises pipelines for functional connectivity studies which heavily exploit graph-theoretical metrics including among other things modular partitions - neuropycon_cli is a command line interface for the ephypype package. Notably, NeuroPycon pipelines can be used in a stand-alone mode but they can also be combined within building blocks to form a larger workflow, in which case the input of one pipeline comes from the outputs of the others. Each pipeline, based upon the nipype engine, is defined by connecting different nodes, with each node being either a user-defined function or a python-wrapped external routine (as MNE-python modules or radatools functions). Results and Discussion. NeuroPycon provides a common and fast framework to develop workflows for advanced neuroimaging data analyses. Several workflows have already been developed to analyze different datasets coming from MEG and EEG studies, such as EEG sleep data and MEG resting state measurements. Furthermore, pipelines defined in graphpype have already been used to perform graph theoretical analysis on a different fMRI datasets. Results visualisation for NeuroPycon is provided through the visbrain (http://visbrain.org/), an open-source multi-purpose python software devoted to graphical representation of neuroscientific data and built on top of VisPy [5], a high-performance visualization library leveraging GPU acceleration. NeuroPycon will shortly be available for download via github (installation via Docker) and is currently being documented (https://neuropycon.github.io/neuropycon_doc/). Future developments will include fusion of multi-modal data (ex. MEG and fMRI or iEEG and fMRI) and feature an increased compatibility with the existing Python packages of interest such as machine learning tools. References: 1. Bullmore E, Sporns O (2009), Nat Rev Neuroscience 2. Gorgolewski et al. (2011) Front. Neuroinformatics 3. Gramfort et al. (2013), Front. Neuroscience 4. http://deim.urv.cat/~sergio.gomez/radatools.php 5. Campagnola et al. (2015), Proceedings of the 14th Python in Science Conference

Published
2018

38. CHANGES OF RESTING-STATE OSCILLATORY NETWORK DYNAMICS AFTER MOTOR LEARNING: A M.E.G. DEVELOPMENTAL STUDY

Author

Jordan ALVES, Fanny Barlaam, Claude-Bernard, David Meunier, Annalisa Pascarella, Sébastien Daligault, Claude Delpuech, Karim Jerbi, and Christina Schmitz

Subjects
MEG, neuroimaging, connectivity
Abstract

Introduction : Neuroimaging studies have shown that in adults, the motor learning induced alterations of the functional connectivity assessed during Resting State Networks (RSN) is age-dependent (Mary et al., 2017). Motor learning relies on the build-up of new sensori-motor representations, which has been studied using the bar-man task in adults (Barlaam, Vaugoyeau, Fortin, Assaiante, & Schmitz, 2016; Paulignan, Dufossé, Hugon, & Massion, 1989) and in children (Schmitz et al, 2002).. The aim of this study was to investigate the modulations of functional connectivity after a motor learning task in the childs resting state network. Method : 20 children aged 7 to 12 (12 boys; age 9y 9m ; age 1y et 8m) took part in the study. The resting state tasks consisted of a 3 session closed-eyes recording of 45 seconds. The first one was used as a baseline and the next two have been set around the motor learning task to evaluate the effect of motor learning on the connectivity in the RSN. The motor learning task was a load-lifting task where the participant was asked to lift a weight using its right hand which triggered the fall of a weight attached to the supporting left arm (Paulignan et al, 1989). We continuously recorded the neuromagnetic signals using a 275 channels CTFMEG system. To quantify the functional connectivity between brain regions, coherency analyses have been conducted, using the imaginary part of the coherency, corresponding to the correlation coefficient between two signals in the alpha and beta frequency bands. Moreover, graph theory analysis has provided an overview of the network organisation after the motor task. All resultshave been analysed using data-related permutation statistic with a 0.005 significance threshold (calculated as a relation between the number of conditions (n=2) and the number of subjects (N=20); = 1/, therefore < 0.005). 2 of 3 Results : The motor learning behavioural performances were assessed using a learning curve model throughout the trials which revealed a significant global learning effect (F(7 ;19) = 50,62 ; p

Published
2018

39. Project Appraisal and Long Term Strategic Vision

Author

Alain Quinet, Emile Quinet, David Meunier, Laboratoire Ville, Mobilité, Transport (LVMT ), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC), Sciences Po (Sciences Po), Paris-Jourdan Sciences Economiques (PSE), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Recherche Agronomique (INRA)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS), Paris School of Economics (PSE), École des Ponts ParisTech (ENPC)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ce travail a bénéficié d'une aide de l'Etat gérée par l'Agence Nationale de la Recherche au titre du programme « Investissements d'avenir » portant la référence ANR-10-LABX-93-01. This work was supported by the French National Research Agency, through the program Investissements d'Avenir, ANR-10-LABX-93-01., École des Ponts ParisTech (ENPC)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Marne-la-Vallée (UPEM), École normale supérieure - Paris (ENS Paris), École des Ponts ParisTech (ENPC)-École normale supérieure - Paris (ENS Paris), Université Paris-Est Marne-la-Vallée (UPEM)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École des Ponts ParisTech (ENPC), and École normale supérieure - Paris (ENS Paris)-Institut National de la Recherche Agronomique (INRA)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Strategic planning, carbon price, Actuarial science, Public economics, Cost–benefit analysis, cost-benefit analysis, long term scenarios, Commission, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Term (time), climate change, Project appraisal, Risk analysis (business), Carbon price, Economics, uncertainty, Set (psychology), risk
Abstract

International audience; France is reviewing its long-lived socio-economic appraisal of infrastructure projects, and recently a Commission has issued a report on this subject. After a rapid view of its conclusions we focus on some specific points more closely related to the present situation, marked by risk and possible changes in the rate and structure of economic growth, mainly due to environmental and energy constraints. The use of low discount rates together with growing uncertainties on future economic growth and climate change outcomes and counter-measures eagerly calls for research on long term issues. It becomes necessary to define a consistent, long term, strategic vision as an appropriate input for correct project appraisal, based on a set of scenarios. We discuss and illustrate concretely the changes that would be induced in investment choice procedures and CBA practice.

Published
2014
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40. The Backbone N-(4-Azidobutyl) Linker for the Preparation of Peptide Chimera

Author

Jaume Adan, Ana I. Fernández-Llamazares, Francesc Mitjans, Jesús García, David Meunier, Fernando Albericio, and Jan Spengler

Subjects
chemistry.chemical_classification, Azides, Molecular Structure, Acylation, Organic Chemistry, Cilengitide, Peptide, Alkylation, Peptides, Cyclic, Biochemistry, Combinatorial chemistry, chemistry.chemical_compound, chemistry, Click chemistry, Animals, Molecule, Click Chemistry, Azide, Physical and Theoretical Chemistry, Linker, Snake Venoms
Abstract

A robust synthetic strategy for the introduction of the N-(4-azidobutyl) linker into peptides using standard SPPS techniques is described. Based on the example of Cilengitide it is shown that the N-(4-azidobutyl) group exerts similar conformational restraints as a backbone N-Me group and allows conjugation of a desired molecule either via click chemistry or-after azide reduction-via acylation or reductive alkylation.

Published
2013
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41. Large-scale brain integration patterns differ in focused-attention and open-monitoring meditation

Author

Daphné Bertrand-Dubois, David Meunier, Annalisa Pascarella, Vittorio Pizzella, Laura Marzetti, and Karim Jerbi

Subjects
MEG, meditation, connecitivity
Abstract

An important process underlying meditation and its benefits involves the regulation of attention. Although the two main meditation categories - open-monitoring meditation (OMM) and focused-attention meditation (FAM) - are associated with different benefits and attentional processes, direct comparisons between the attentional neural mechanism of FAM and OMM are rare. This study uses magnetoencephalography (MEG) recordings in 12 expert meditators to compare FAM and OMM by assessing (i) source spectral power, (ii) seed-based functional connectivity of key regions in attention, (including anterior cingulate cortex, dorsolateral prefrontal cortex and the thalamus) and (iii) graph theory metrics that describe brain-wide efficiency of information processing. We reconstructed the source space using minimum norm estimate and computed spectral power and functional connectivity in multiple frequency bands (delta, theta, alpha, beta, gamma) using a custom-designed python-based MEG analysis pipeline (NeuroPycon). The results reveal unique patterns of neural processes specific to FAM or OMM. Among other things, compared to FAM, OMM appears to be characterized by enhanced small-world network properties. By contrast, FAM exhibits greater functional connectivity between the anterior cingulate cortex and frontal regions. These findings shed light onto the mechanisms that potentially mediate the different behavioral and attentional capacities associated with each of the two meditation techniques. Our results are discussed in the context of previous behavioral and fMRI studies on meditation and attention.

Published
2017

42. NeuroPycon: A Python-based package for advanced MEG, EEG and fMRI connectivity analyses

Author

David Meunier, Annalisa Pascarella, Daphné Bertrand-Dubois, Jordan Alves, Fanny Barlaam, Arthur Dehgan, Tarek Lajnef, Etienne Combrisson, Dmitrii Altukhov, and Karim Jerbi

Subjects
python, MEG, data analysis, Neuroimaging
Abstract

NeuroPycon is an open-source multi-modal brain data analysis kit which provides Python-based pipelines for advanced multi-thread processing of fMRI, MEG and EEG data, with a focus on connectivity and graph analyses [1]. NeuroPycon is based on NiPype framework [2] which facilitates data analyses by wrapping many commonly-used neuroimaging software into a common python framework. Therefore, a major strength of NeuroPycon is that it relies on (and interfaces with) several freely available Python packages developed for efficient and fast parallel processing and that it seamlessly connects with existing open-science neuroimaging and signal processing toolboxes. The flexible design allows users to configure analysis pipelines defined by connecting different nodes, where each node may be a user-defined function or a well-established tool or python-wrapped module (e.g. MNE-python for MEG analysis [3], etc.). The current implementation of NeuroPycon contains three different packages: - ephypype includes pipelines for electrophysiology analysis; current implementations allow for MEG/EEG data import, data pre-processing and cleaning by an automatic removal of eyes and heart related artefacts, sensor or source-level connectivity analyses - graphpype allows to study functional connectivity exploiting graph-theoretical metrics including also modular partitions - clipype is a command line interface for ephypype package. NeuroPycon will shortly be available for download via github (installation via Docker) and is currently being documented. Future developments include fusion of multi-modal data (ex. MEG and fMRI or iEEG and fMRI). References 1. Bullmore, Sporns (2009), Nat Rev Neurosci 2. Gorgolewski et al. (2011) Front. Neuroinform 3. Gramfort et al. (2013), Front. Neurosci

Published
2017

43. The neural bases of disgust for cheese: an fMRI study

Author

Nicolas Torquet, Jean-Pierre Royet, Tao Jiang, Anne-Marie Mouly, David Meunier, Centre de recherche en neurosciences de Lyon (CRNL), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut des Sciences Cognitives (ISC), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Neuroscience Paris Seine (NPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Centre National de la Recherche Scientifique (CNRS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Biologie Paris Seine (IBPS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), HAL UPMC, Gestionnaire, Neurosciences Paris Seine (NPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Biologie Paris Seine (IBPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), and Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, liking, motivational salience, reward circuit, media_common.quotation_subject, disliking, [SDV]Life Sciences [q-bio], disgust, Substantia nigra, wanting, Basal Ganglia, Developmental psychology, lcsh:RC321-571, Ventral pallidum, 03 medical and health sciences, Behavioral Neuroscience, 0302 clinical medicine, Food Aversion, Perception, Basal ganglia, medicine, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], External globus pallidus, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Biological Psychiatry, Original Research, media_common, medicine.diagnostic_test, fMRI, Disgust, humanities, Psychiatry and Mental health, 030104 developmental biology, Neuropsychology and Physiological Psychology, Neurology, Taste aversion, diswanting, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Functional magnetic resonance imaging, Psychology, 030217 neurology & neurosurgery, Neuroscience
Abstract

International audience; The study of food aversion in humans by the induction of illness is ethically unthinkable, and it is difficult to propose a type of food that is disgusting for everybody. However, although cheese is considered edible by most people, it can also be perceived as particularly disgusting to some individuals. As such, the perception of cheese constitutes a good model to study the cerebral processes of food disgust and aversion. In this study, we show that a higher percentage of people are disgusted by cheese than by other types of food. Functional magnetic resonance imaging then reveals that the internal and external globus pallidus and the substantia nigra belonging to the basal ganglia are more activated in participants who dislike or diswant to eat cheese (Anti) than in other participants who like to eat cheese, as revealed following stimulation with cheese odors and pictures. We suggest that the aforementioned basal ganglia structures commonly involved in reward are also involved in the aversive motivated behaviors. Our results further show that the ventral pallidum, a core structure of the reward circuit, is deactivated in Anti subjects stimulated by cheese in the wanting task, highlighting the suppression of motivation-related activation in subjects disgusted by cheese.

Published
2016
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45. CBA § Darwin: The Case of Transport Infrastructure in France

Author

David Meunier, Emile Quinet, Paris-Jourdan Sciences Economiques (PSE), École normale supérieure - Paris (ENS Paris)-Institut National de la Recherche Agronomique (INRA)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS), Paris School of Economics (PSE), Laboratoire Ville, Mobilité, Transport (LVMT ), Université Paris-Est Marne-la-Vallée (UPEM)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École des Ponts ParisTech (ENPC), Ce travail a bénéficié d'une aide de l'Etat gérée par l'Agence Nationale de la Recherche au titre du programme ' Investissements d'avenir ' portant la référence ANR-10-LABX-93-01. This work was supported by the French National Research Agency, through the program Investissements d'Avenir, ANR-10--LABX-93-01., Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Recherche Agronomique (INRA)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS), École des Ponts ParisTech (ENPC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), École des Ponts ParisTech (ENPC)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Marne-la-Vallée (UPEM), École normale supérieure - Paris (ENS-PSL), Université Paris 1 Panthéon-Sorbonne (UP1)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
Economic growth, Evolution, Context (language use), Sustainable development, 11. Sustainability, 0502 economics and business, Economics, General Materials Science, 050207 economics, Adaptation (computer science), ComputingMilieux_MISCELLANEOUS, 050210 logistics & transportation, [SHS.ARCHI]Humanities and Social Sciences/Architecture, space management, Transport infrastructure, Cost–benefit analysis, Corporate governance, 05 social sciences, Cost-benefit analysis, Land-use planning, Competitor analysis, Environmental economics, Private sector, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Project assessment, Darwin
Abstract

International audience; CBA has a long history in the field of transport projects. Still, its methodologies have been developed in a rather simple context which is now much more complex: is CBA still adapted to this context? CBA is now asked by decision makers not only to represent monetary flows and time savings, but also economic effects, social and distributive concerns, land use, climate change, and wider effects. It has to be implemented in a framework where private sector is involved and numerous entities are involved in project financing. Another strong evolution is that CBA has to interact more with public communication processes, and to take into account new types of governance. Adopting a Darwinian point of view, we consider the evolutions of CBA's environment, its resources and past adaptations. Then we pay attention to the potential competitors of CBA in this new environment. This analytical part is illustrated using several recent examples of new assessment questions and answers considered in France, at different scales: a great transport infrastructure scheme for the Parisian region, and the French national transportation infrastructure plan. They present more concretely how the new evaluative questions take form, and the kind of answers that have been found (or still have to be found). Building partly on the on-going evolution of the evaluation system in France, some ideas on the axes of adaptation of CBA will be presented in the last part of the paper, covering not only CBA's technical performance but also CBA's governance and integration in a more comprehensive assessment system.

Published
2012
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46. Genetic Influences on Cost-Efficient Organization of Human Cortical Functional Networks

Author

Edward T. Bullmore, Danielle S. Bassett, Andrew Zalesky, Stephen J. Wood, Jennifer A O'Connor, Alex Fornito, Karen L Shaw, Deborah A. Nertney, David Meunier, Ian Ellison-Wright, Murat Yücel, Bryan J. Mowry, and Christos Pantelis

Subjects
Adult, Male, Brain mapping, Young Adult, Cortex (anatomy), Twins, Dizygotic, medicine, Humans, Default mode network, Cerebral Cortex, Brain Mapping, medicine.diagnostic_test, General Neuroscience, Articles, Twins, Monozygotic, Human brain, Middle Aged, Complex network, Magnetic Resonance Imaging, medicine.anatomical_structure, Cerebral cortex, Posterior cingulate, Female, Nerve Net, Functional magnetic resonance imaging, Psychology, Neuroscience
Abstract

The human cerebral cortex is a complex network of functionally specialized regions interconnected by axonal fibers, but the organizational principles underlying cortical connectivity remain unknown. Here, we report evidence that one such principle for functional cortical networks involves finding a balance between maximizing communication efficiency and minimizing connection cost, referred to as optimization of network cost-efficiency. We measured spontaneous fluctuations of the blood oxygenation level-dependent signal using functional magnetic resonance imaging in healthy monozygotic (16 pairs) and dizygotic (13 pairs) twins and characterized cost-efficient properties of brain network functional connectivity between 1041 distinct cortical regions. At the global network level, 60% of the interindividual variance in cost-efficiency of cortical functional networks was attributable to additive genetic effects. Regionally, significant genetic effects were observed throughout the cortex in a largely bilateral pattern, including bilateral posterior cingulate and medial prefrontal cortices, dorsolateral prefrontal and superior parietal cortices, and lateral temporal and inferomedial occipital regions. Genetic effects were stronger for cost-efficiency than for other metrics considered, and were more clearly significant in functional networks operating in the 0.09–0.18 Hz frequency interval than at higher or lower frequencies. These findings are consistent with the hypothesis that brain networks evolved to satisfy competitive selection criteria of maximizing efficiency and minimizing cost, and that optimization of network cost-efficiency represents an important principle for the brain's functional organization.

Published
2011
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47. Motorway Provision and Management in France: Analyses and Policy Issues

Author

Emile Quinet, David Meunier, Alain Fayard, General Directorate for Roads, Laboratoire Ville, Mobilité, Transport (LVMT ), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC), Paris-Jourdan Sciences Economiques (PSE), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Recherche Agronomique (INRA)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS), Paris School of Economics (PSE), Université Paris 1 Panthéon-Sorbonne (UP1)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ce travail a bénéficié d'une aide de l'Etat gérée par l'Agence Nationale de la Recherche au titre du programme ' Investissements d'avenir ' portant la référence ANR-10-LABX-93-01. This work was supported by the French National Research Agency, through the program Investissements d'Avenir, ANR-10-LABX-93-01., Université Paris-Est Marne-la-Vallée (UPEM)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École des Ponts ParisTech (ENPC), École normale supérieure - Paris (ENS Paris)-Institut National de la Recherche Agronomique (INRA)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS), Ce travail a bénéficié d'une aide de l'Etat gérée par l'Agence Nationale de la Recherche au titre du programme ' Investissements d'avenir ' portant la référence ANR-10-LABX-93-01. This work was supported by the French National Research Agency, through the program Investissements d'Avenir, ANR-10--LABX-93-01., École des Ponts ParisTech (ENPC)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Université Paris-Est Marne-la-Vallée (UPEM), École normale supérieure - Paris (ENS Paris), École des Ponts ParisTech (ENPC)-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
Computer Networks and Communications, Process (engineering), Infrastructure charges, Politics, Quality of service, Artificial Intelligence, 0502 economics and business, Economics, 050207 economics, Architecture, Infrastructure, 050210 logistics & transportation, Public economics, Scope (project management), biology, 05 social sciences, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Public private financing, Incentive, Capital (economics), Toll, Motorways, biology.protein, Software, Externality, Regulation
Abstract

accès PDF payant http://www.springerlink.com/content/hx059484327r8461/; International audience; Motorways are one of the largest capital stocks of transportation infrastructure. It is therefore important to try to optimize their provision and management. This paper contributes to this goal by analysing France's historical long term experience through the prism of economic theory, and by offering suggestions and perspectives for the future. The first section presents a short history of motorway provision in France. It shows how the general framework evolved from isolated links to an integrated network. It discusses how concerns have changed with the growing importance of external factors; these changes are analysed in terms of economic characteristics, namely the relative importance of uncertainty, externalities and network effects. Finally, it assesses how the political decisions have had a major influence, mainly through the privatisation process and through changes in regulations. The second section uses these characteristics to make suggestions and recommendations on how to provide motorways. The main issues considered are the scope of a concession, and the architecture of the contract regarding toll regulation and incentives. Hints about possible future evolutions are presented too, concerning the choice between concession and public provision of motorways, and concerning the separation between infrastructure provision and management. The third section concludes by suggesting some research tracks that may help improving international knowledge through comparison between countries.

Published
2009
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48. An MEG investigation of the brain dynamics mediating Focused-Attention andOpen-Monitoring Meditation

Author

Daphné Bertrand-Dubois 1, David Meunier 2, Annalisa Pascarella 3, Tarek Lajnef 1, Vittorio Pizzella 4, Laura Marzetti 4, and and Karim Jerbi 5

Subjects
meg, meditation, data analysis
Abstract

The phenomenologyand reported effects of meditation vary according to the technique practiced.While numerous studies have explored the cerebral mechanisms involved inmeditation, little research provides direct comparisons between the neuronalnetwork dynamics involved in different meditation techniques. Here, we exploreand compare brain signals recorded with magnetoencephalography (MEG) during (a)resting state, (b) focused-attention meditation (FAM) and (c) open-monitoringmeditation (OMM) in a group of expert meditators (12 monks).To this end, weestimated MEG source time courses using a minimum-norm solution and computed (1)spectral power in multiple frequency bands (delta, theta, alpha, beta andgamma), (2) graph theoretical measures, (3) long-range coupling using imaginarycoherence and weighed phase-lag index and (4) multifractal scaling parameters using Wavelet Leader-based Multifractal formalism. We compared all the measures in the three conditions(OMM, FAM and resting state) and tested for statistical significance using permutationtest (paired t-test) corrected by maximum statistics. We also used a machinelearning framework in order to see which features provide the highestclassification across conditions. Our findings reveal several differencesbetween FAM, OMM and the resting-state condition. Compared to OMM, FAM isassociated with an increase in power in regions involved in attention andperformance monitoring. In OMM, increases in activity were observed in regionsinvolved in memory and emotion processing. Moreover, OMM seems to have strongestand more connections, while resting state have connections that are weaker andfewer in number compared to OMM and FAM. We discuss these results in thecontext of previous cognitive neuroimaging studies of meditation and paths forfuture research are proposed.

Published
2016

49. COMPARING THE NEURAL CORRELATES OF FOCUSED-ATTENTION AND OPEN-MONITORING MEDITATION: A MEG STUDY

Author

Daphné Bertrand-Dubois (1), David Meunier (2), Tarek Lajnef (1), Annalisa Pascarella (3), Vittorio Pizzella (4), Laura Marzetti (4), and Karim Jerbi (1)

Subjects
meg, meditation, data analysis
Abstract

The phenomenology and reported effects of meditation vary according to the technique practiced. While numerous studies have explored the cerebral mechanisms involved in meditation, little research provides direct comparisons between the neuronal network dynamics involved in different meditation techniques. Here, we explore and compare brain signals recorded with magnetoencephalography (MEG) during (a) focused-attention meditation (FAM), and (b) open-monitoring meditation (OMM) in a group of expert meditators (12 monks). To this end, we estimated MEG source time courses using minimum-norm and computed spectral power in multiple frequency bands (delta, theta, alpha, beta and gamma), graph theoretical measures and multifractal scaling parameters in both conditions. Preliminary findings reveal several differences between FAM and OMM. Interestingly, OMM was associated with higher theta power in the right temporal pole. We discuss these results in the context of previous cognitive neuroimaging studies of meditation and paths for future research are proposed.

Published
2016

50. Welcome to NeuroPype: A Python-based pipeline for advanced MEG and EEG connectivity analyses

Author

David Meunier 1, Annalisa Pascarella 2, Daphne Bertrand-Dubois 3, Lajnef Tarek 3, Etienne Combrisson 1, 3, 4, Dmitrii Altukhov 5, and Karim Jerbi 3

Subjects
python, software package, meg, data analysis
Abstract

With the exponential increase in data dimension and methodological complexities, conducting brain network analyses using MEG and EEG is becoming an increasingly challenging and time-consuming endeavor. To date, most of the MEG/EEG processing is done by combining software packages and custom tools which often hinders reproducibility of the experimental findings. Here we describe NeuroPype, which is a free open-source Python package we developed for efficient multi-thread processing of MEG and EEG studies. The proposed package is largely based on the NiPype framework and the MNE-Python software and benefits from standard Python packages such as NumPy and SciPy. It also incorporates several existing wrappers, such as a Freesurfer Python-wrapper for multi-subject MRI segmentation. The NeuroPype project includes three different packages: I Neuropype-ephy includes pipelines for electrophysiology analysis; current implementations allow for MEG/EEG data import, data pre-processing and cleaning by an automatic removal of eyes and heart related artefacts, sensor or source-level connectivity analyses II Neuropype-graph: functional connectivity exploiting graph-theoretical metrics including modular partitions III Neuropype-gui: a graphical interface wrapping the definition of parameters. NeuroPype provides a common and fast framework to develop workflows for advanced MEG/EEG analyses (but also fMRI and iEEG). Several pipelines have already been developed with NeuroPype to analyze different MEG and EEG datasets: e.g. EEG sleep data, MEG resting state measurements and MEG recordings in Autism. NeuroPype will be be made available via Github. Current developments will increase its compatibility with existing Python packages of interest such as machine learning tools.

Published
2016

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