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1. Bases de données virtuelles pour l'étude de la Maladie d'Alzheimer et du vieillissement en utilisant de la modélisation des réseaux cérébraux dynamiques

Author: Viktor K. Jirsa, Petra Ritter, Kelly Shen, Martin Hofmann-Apitius, Zheng Wang, Demian Battaglia, Lucas Arbabyazd, Anthony R. McIntosh, Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Rotman Research Institute at the Baycrest Centre (RRI), Fraunhofer Institute for Algorithms and Scientific Computing (Fraunhofer SCAI), Fraunhofer (Fraunhofer-Gesellschaft), Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], and Publica
Subjects: Computer science, whole-brain modelling, Neuroimaging, 02 engineering and technology, Novel Tools and Methods, Machine learning, computer.software_genre, 03 medical and health sciences, 0302 clinical medicine, Alzheimer’s diseases, Alzheimer's diseases, Alzheimer Disease, 0202 electrical engineering, electronic engineering, information engineering, medicine, Humans, [PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn], Healthy aging, 030304 developmental biology, Network model, Brain network, 0303 health sciences, Resting state fMRI, medicine.diagnostic_test, business.industry, General Neuroscience, aging, connectome, fMRI, Brain, 020207 software engineering, General Medicine, Research Article: Methods/New Tools, Magnetic Resonance Imaging, Statistical classification, Dynamics (music), Connectome, 020201 artificial intelligence & image processing, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Artificial intelligence, dataset completion, business, Functional magnetic resonance imaging, computer, 030217 neurology & neurosurgery
Abstract: Visual Abstract, Large neuroimaging datasets, including information about structural connectivity (SC) and functional connectivity (FC), play an increasingly important role in clinical research, where they guide the design of algorithms for automated stratification, diagnosis or prediction. A major obstacle is, however, the problem of missing features [e.g., lack of concurrent DTI SC and resting-state functional magnetic resonance imaging (rsfMRI) FC measurements for many of the subjects]. We propose here to address the missing connectivity features problem by introducing strategies based on computational whole-brain network modeling. Using two datasets, the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset and a healthy aging dataset, for proof-of-concept, we demonstrate the feasibility of virtual data completion (i.e., inferring “virtual FC” from empirical SC or “virtual SC” from empirical FC), by using self-consistent simulations of linear and nonlinear brain network models. Furthermore, by performing machine learning classification (to separate age classes or control from patient subjects), we show that algorithms trained on virtual connectomes achieve discrimination performance comparable to when trained on actual empirical data; similarly, algorithms trained on virtual connectomes can be used to successfully classify novel empirical connectomes. Completion algorithms can be combined and reiterated to generate realistic surrogate connectivity matrices in arbitrarily large number, opening the way to the generation of virtual connectomic datasets with network connectivity information comparable to the one of the original data.
Published: 2021
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2. Virtual Connectomic Datasets in Alzheimer’s Disease and Aging Using Whole-Brain Network Dynamics Modelling

Author: Arbabyazd, Lucas, Shen, Kelly, Wang, Zheng, Hofmann-Apitius, Martin, Ritter, Petra, Mcintosh, Anthony, Battaglia, Demian, Jirsa, Viktor, Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Rotman Research Institute at the Baycrest Centre (RRI), Fraunhofer Institute for Algorithms and Scientific Computing (Fraunhofer SCAI), Fraunhofer (Fraunhofer-Gesellschaft), Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], and Battaglia, Demian
Subjects: Alzheimer's diseases, aging, connectome, fMRI, whole-brain modelling, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], [PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn], [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], dataset completion, [PHYS.COND.CM-DS-NN] Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn]
Abstract: International audience; Large neuroimaging datasets, including information about structural (SC) and functional connectivity (FC), play an increasingly important role in clinical research, where they guide the design of algorithms for automated stratification, diagnosis or prediction. A major obstacle is, however, the problem of missing features (e.g., lack of concurrent DTI SC and resting-state fMRI FC measurements for many of the subjects).We propose here to address the missing connectivity features problem by introducing strategies based on computational whole-brain network modeling. Using two datasets, the ADNI dataset and a healthy aging dataset, for proof-of-concept, we demonstrate the feasibility of virtual data completion (i.e., inferring "virtual FC" from empirical SC or "virtual SC" from empirical FC), by using self-consistent simulations of linear and nonlinear brain network models. Furthermore, by performing machine learning classification (to separate age classes or control from patient subjects) we show that algorithms trained on virtual connectomes achieve discrimination performance comparable to when trained on actual empirical data; similarly, algorithms trained on virtual connectomes can be used to successfully classify novel empirical connectomes. Completion algorithms can be combined and reiterated to generate realistic surrogate connectivity matrices in arbitrarily large number, opening the way to the generation of virtual connectomic datasets with network connectivity information comparable to the one of the original data.Significance statementPersonalized information on anatomical connectivity ("structural connectivity", SC) or coordinated resting state activation patterns ("functional connectivity', FC) is a source of powerful neuromarkers to detect and track the development of neurodegenerative diseases. However, there are often "gaps" in the available information, with only SC (or FC) being known but not FC (or SC). Exploiting whole-brain modelling, we show that gap in databases can be filled by inferring the other connectome through computational simulations. The generated virtual connectomic data carry information analogous to the one of empirical connectomes, so that machine learning algorithms can be trained on them. This opens the way to the release in the future of cohorts of "virtual patients", complementing traditional datasets in data-driven predictive medicine.
Published: 2021
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3. What Affects the Magnitude of Age-Related Dual-Task Costs in Working Memory? The Role of Stimulus Domain and Access to Semantic Representations

Author: Clément Belletier, Pierre Barrouillet, Stephen Rhodes, Moshe Neveh-Benjamin, Jason M Doherty, Nelson Cowan, Agnieszka Jaroslawska, Robert H. Logie, Valérie Camos, Queen's University [Belfast] (QUB), University of Edinburgh, Rotman Research Institute at the Baycrest Centre (RRI), University of Missouri [Columbia] (Mizzou), University of Missouri System, Laboratoire de Psychologie Sociale et Cognitive (LAPSCO), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), University of Geneva [Switzerland], University of Fribourg, Université de Genève = University of Geneva (UNIGE), and Université de Fribourg = University of Fribourg (UNIFR)
Subjects: Aging, Physiology, Storage, Experimental and Cognitive Psychology, Stimulus (physiology), Processing, behavioral disciplines and activities, 050105 experimental psychology, 03 medical and health sciences, 0302 clinical medicine, Physiology (medical), Age related, Humans, 0501 psychology and cognitive sciences, Working Memory, General Psychology, Aged, Working memory, 05 social sciences, General Medicine, Original Articles, 16. Peace & justice, Semantics, Ageing, Neuropsychology and Physiological Psychology, Memory, Short-Term, Younger adults, Mental Recall, [SCCO.PSYC]Cognitive science/Psychology, Dual-Task, Psychology, 030217 neurology & neurosurgery, Cognitive psychology
Abstract: Although there is evidence that the effect of including a concurrent processing demand on the storage of information in working memory is disproportionately larger for older than younger adults, not all studies show this age-related impairment, and the critical factors responsible for any such impairment remain elusive. Here we assess whether domain overlap between storage and processing activities, and access to semantic representations, are important determinants of performance in a sample of younger and older adults ( N = 119). We developed four versions of a processing task by manipulating the type of stimuli involved (either verbal or non-verbal) and the decision that participants had to make about the stimuli presented on the screen. Participants either had to perform a spatial judgement, in deciding whether the verbal or non-verbal item was presented above or below the centre of the screen, or a semantic judgement, in deciding whether the stimulus refers to something living or not living. The memory task was serial-ordered recall of visually presented letters. The study revealed a large increase in age-related memory differences when concurrent processing was required. These differences were smaller when storage and processing activities both used verbal materials. Dual-task effects on processing were also disproportionate for older adults. Age differences in processing performance appeared larger for tasks requiring spatial decisions rather than semantic decisions. We discuss these findings in relation to three competing frameworks of working memory and the extant literature on cognitive ageing.
Published: 2021
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4. Exploring the influence of temporal factors on age differences in working memory dual task costs

Author: Jason M Doherty, Clément Belletier, Moshe Naveh-Benjamin, Valérie Camos, Robert H. Logie, Agnieszka Jaroslawska, Pierre Barrouillet, Stephen Rhodes, Nelson Cowan, Alicia Forsberg, Rotman Research Institute at the Baycrest Centre (RRI), University of Edinburgh, Queen's University [Belfast] (QUB), University of Missouri [Columbia] (Mizzou), University of Missouri System, Laboratoire de Psychologie Sociale et Cognitive (LAPSCO), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Université de Genève = University of Geneva (UNIGE), Université de Fribourg = University of Fribourg (UNIFR), Université de Genève (UNIGE), and University of Fribourg
Subjects: Adult, Male, Task switching, Aging, Time Factors, Social Psychology, Adolescent, Experimental psychology, Short-term memory, 050105 experimental psychology, working memory, Task (project management), Young Adult, [SCCO]Cognitive science, Encoding (memory), Task Performance and Analysis, Reaction Time, Humans, 0501 psychology and cognitive sciences, dual task, Aged, Aged, 80 and over, inference, Working memory, cognitive aging, switching, 05 social sciences, Information processing, PsyArXiv|Social and Behavioral Sciences|Cognitive Psychology|Memory, DUAL (cognitive architecture), Middle Aged, bepress|Social and Behavioral Sciences|Psychology|Cognitive Psychology, PsyArXiv|Social and Behavioral Sciences, Memory, Short-Term, Mental Recall, [SCCO.PSYC]Cognitive science/Psychology, bepress|Social and Behavioral Sciences, PsyArXiv|Social and Behavioral Sciences|Cognitive Psychology, Female, Geriatrics and Gerontology, Psychology, Interference, Cognitive psychology
Abstract: Working memory is defined by many as the system that allows us to simultaneously store information over brief time periods while engaging in other information processing activities. In a previous study (Rhodes, Jaroslawska et al. (2019) Journal of Experimental Psychology: General, 148, 1204-1227.) we found that retention of serially presented letters was disrupted by the introduction of an arithmetic processing task during a 10 second delay period. Importantly, the magnitude of this dual task disruption increased with age from 18 to 81. The demands of each task were adjusted prior to dual task so that age differences did not reflect baseline differences in single task performance. Motivated by these findings, theories of working memory, and additional analyses of processing reaction times from this previous experiment, we report two experiments, using the same tasks and adjustment procedure, attempting to modulate the magnitude of age differences in dual task effects via manipulations focused on time for encoding to-be-remembered material. Providing a delay prior to processing activities, to facilitate switching between the two tasks, did not modulate age differences. Neither did separating the to-be-remembered material temporally, to allow for the creation of more distinct representations. These findings provide two replications of our initial finding and suggest that age differences in working memory dual tasking are not due to limitations in the speed of encoding. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Published: 2021
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5. Bridging Scales in Alzheimer's Disease: Biological Framework for Brain Simulation With The Virtual Brain

Author: Stefanovski, Leon, Meier, Jil Mona, Pai, Roopa Kalsank, Triebkorn, Paul, Lett, Tristram, Martin, Leon, Bülau, Konstantin, Hofmann-Apitius, Martin, Solodkin, Ana, McIntosh, Anthony Randal, Ritter, Petra, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Fraunhofer Institute for Algorithms and Scientific Computing (Fraunhofer SCAI), Fraunhofer (Fraunhofer-Gesellschaft), University of Texas at Dallas [Richardson] (UT Dallas), Rotman Research Institute at the Baycrest Centre (RRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Aix Marseille Université (AMU), and Otten, Lisa
Subjects: multi-scale brain modeling, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, Review, Alzheimer's disease, brain simulation, connectomics, The Virtual Brain, 600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::610 Medizin und Gesundheit, Neuroscience
Abstract: International audience; Despite the acceleration of knowledge and data accumulation in neuroscience over the last years, the highly prevalent neurodegenerative disease of AD remains a growing problem. Alzheimer's Disease (AD) is the most common cause of dementia and represents the most prevalent neurodegenerative disease. For AD, disease-modifying treatments are presently lacking, and the understanding of disease mechanisms continues to be incomplete. In the present review, we discuss candidate contributing factors leading to AD, and evaluate novel computational brain simulation methods to further disentangle their potential roles. We first present an overview of existing computational models for AD that aim to provide a mechanistic understanding of the disease. Next, we outline the potential to link molecular aspects of neurodegeneration in AD with large-scale brain network modeling using The Virtual Brain ( www.thevirtualbrain.org ), an open-source, multiscale, whole-brain simulation neuroinformatics platform. Finally, we discuss how this methodological approach may contribute to the understanding, improved diagnostics, and treatment optimization of AD.
Published: 2021
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6. Dynamic Functional Connectivity between order and randomness and its evolution across the human adult lifespan

Author: Petra Ritter, Andreas Daffertshofer, Viktor K. Jirsa, Anthony R. McIntosh, Sabrina Chettouf, Diego Lombardo, Joelle Zimmermann, Demian Battaglia, Thomas Boudou, Enrique C. A. Hansen, Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de biologie de l'ENS Paris (IBENS), Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-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), Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Vrije Universiteit Amsterdam [Amsterdam] (VU), Rotman Research Institute at the Baycrest Centre (RRI), European Project: 9250595(1992), Battaglia, Demian, Integrating Experimentation with Theoretical and Simulation-Based Analysis in Electrical and Computer Engineering Laboratories - 1992-06-15 - 1994-11-30 - 9250595 - VALID, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Département de Biologie - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de biologie de l'ENS Paris (UMR 8197/1024) (IBENS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Département de Biologie - ENS Paris, IBBA, Coordination Dynamics, and AMS - Ageing & Vitality
Subjects: Adult, Male, Aging, Adolescent, Computer science, Cognitive Neuroscience, Human Development, Topology, 050105 experimental psychology, lcsh:RC321-571, Resting-state, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Connectome, Humans, 0501 psychology and cognitive sciences, Statistical physics, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Randomness, Dynamic functional connectivity, Aged, Aging| anomalous diffusion, Aged, 80 and over, Resting state fMRI, Functional connectivity, [SCCO.NEUR]Cognitive science/Neuroscience, 05 social sciences, [SCCO.NEUR] Cognitive science/Neuroscience, fMRI, Age Factors, Brain, Cognition, Middle Aged, Random walk, Magnetic Resonance Imaging, Neurology, Female, Nerve Net, 030217 neurology & neurosurgery, Psychomotor Performance
Abstract: Functional Connectivity (FC) during resting-state or task conditions is not fixed but inherently dynamic. Yet, there is no consensus on whether fluctuations in FC may resemble isolated transitions between discrete FC states rather than continuous changes. This quarrel hampers advancing the study of dynamic FC. This is unfortunate as the structure of fluctuations in FC can certainly provide more information about developmental changes, aging, and progression of pathologies. We merge the two perspectives and consider dynamic FC as an ongoing network reconfiguration, including a stochastic exploration of the space of possible steady FC states. The statistical properties of this random walk deviate both from a purely “order-driven” dynamics, in which the mean FC is preserved, and from a purely “randomness-driven” scenario, in which fluctuations of FC remain uncorrelated over time. Instead, dynamic FC has a complex structure endowed with long-range sequential correlations that give rise to transient slowing and acceleration epochs in the continuous flow of reconfiguration. Our analysis for fMRI data in healthy elderly revealed that dynamic FC tends to slow down and becomes less complex as well as more random with increasing age. These effects appear to be strongly associated with age-related changes in behavioural and cognitive performance.HighlightsDynamic Functional Connectivity (dFC) at rest and during cognitive task performs a “complex” (anomalous) random walk.Speed of dFC slows down with aging.Resting dFC replaces complexity by randomness with aging.Task performance correlates with the speed and complexity of dFC.
Published: 2020
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7. How Do Scientific Views Change? Notes From an Extended Adversarial Collaboration

Author: Jason M Doherty, Clément Belletier, Pierre Barrouillet, Stephen Rhodes, Valérie Camos, Nelson Cowan, Robert H. Logie, Moshe Naveh-Benjamin, Agnieszka Jaroslawska, Alicia Forsberg, Department of Psychological Sciences, University of Missouri, Laboratoire de Psychologie Sociale et Cognitive (LAPSCO), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Department of Psychology [Edinburgh], Heriot-Watt University [Edinburgh] (HWU), Department of Psychology, Queen's University, Rotman Research Institute at the Baycrest Centre (RRI), Faculté de Psychologie et des Sciences de l'Education (FPSE), Université de Genève (UNIGE), Département de Psychologie, Université de Fribourg, University of Fribourg, Université de Genève = University of Geneva (UNIGE), and Université de Fribourg = University of Fribourg (UNIFR)
Subjects: Aging, Competitive Behavior, Biomedical Research, adversarial collaboration, Computer science, Interprofessional Relations, Science, [SHS.PSY]Humanities and Social Sciences/Psychology, 050109 social psychology, Scientific views, 050105 experimental psychology, Article, working memory, Scientific method, Humans, Multicenter Studies as Topic, 0501 psychology and cognitive sciences, Attention, Cooperative Behavior, Changing views, General Psychology, 05 social sciences, Working memory, Retention, Psychology, scientific views, Mathematical Concepts, Adversarial collaboration, Data science, Test (assessment), Memory, Short-Term, changing views, scientific method, Psychological Theory
Abstract: International audience; There are few examples of an extended adversarial collaboration, in which investigators committed to different theoretical views collaborate to test opposing predictions. Whereas previous adversarial collaborations have produced single research articles, here, we share our experience in programmatic, extended adversarial collaboration involving three laboratories in different countries with different theoretical views regarding working memory, the limited information retained in mind, serving ongoing thought and action. We have focused on short-term memory retention of items (letters) during a distracting task (arithmetic), and effects of aging on these tasks. Over several years, we have conducted and published joint research with preregistered predictions, methods, and analysis plans, with replication of each study across two laboratories concurrently. We argue that, although an adversarial collaboration will not usually induce senior researchers to abandon favored theoretical views and adopt opposing views, it will necessitate varieties of their views that are more similar to one another, in that they must account for a growing, common corpus of evidence. This approach promotes understanding of others’ views and presents to the field research findings accepted as valid by researchers with opposing interpretations. We illustrate this process with our own research experiences and make recommendations applicable to diverse scientific areas.
Published: 2020
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8. Sparse Multiple Correspondence Analysis

Author: Guillemot, Vincent, Le Borgne, Julie, Gloaguen, Arnaud, Tenenhaus, Arthur, Saporta, Gilbert, Chollet, Sylvie, Beaton, Derek, Abdi, Hervé, Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Laboratoire des signaux et systèmes (L2S), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Unité Baobab (BAOBAB), Service NEUROSPIN (NEUROSPIN), 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)-Université Paris-Saclay, CEDRIC. Méthodes statistiques de data-mining et apprentissage (CEDRIC - MSDMA), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Institut Supérieur d'Agriculture de Lille (ISA), Rotman Research Institute at the Baycrest Centre (RRI), and University of Texas at Dallas [Richardson] (UT Dallas)
Subjects: [STAT]Statistics [stat], Multivariate Analysis, Parcimonie, Multiple Correspondence Analysis, Analyse Multivariée, Sparsity, Analyse des Correspondances Multiples
Abstract: International audience; Multiple Correspondence Analysis (MCA) is the method of choicefor themultivariate analysis of categorical data. In MCA each qualitative variable is representedby a group of binary variables (with a coding scheme called “complete disjunctive coding”)and each binary variable has a weight inversely proportional to its frequency. The datamatrix concatenates all these binary variables, and once normalized and centered thisdata matrix is analyzed with a generalized singular value decomposition (GSVD) thatincorporates the variable weights as constraints (or “metric”). The GSVD is, of course,based on the plain SVD and so MCA can be sparsified by extending algorithms designedto sparsify the SVD. To do so requires two additional features: to include weights andto be able to sparsify entire groups of variables at once. Another important feature ofsuch a sparsification should be to preserve the orthogonality of the components, Here, weintegrate all these constraints by using an exact projection scheme onto the intersectionof subspaces (i.e., balls) where each ball represents a specific type of constraints. Weillustrate our procedure with the data from a questionnaire survey on the perception ofcheese in two French cities.
Published: 2020

9. Sparse Multiple Correspondence Analysis

Author: Guillemot, Vincent, Le Borgne, Julie, Gloaguen, Arnaud, Tenenhaus, Arthur, Saporta, Gilbert, Chollet, Sylvie, Beaton, Derek, Abdi, Hervé, Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des signaux et systèmes (L2S), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Building large instruments for neuroimaging: from population imaging to ultra-high magnetic fields (BAOBAB), 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)-Centre National de la Recherche Scientifique (CNRS), CEDRIC. Méthodes statistiques de data-mining et apprentissage (CEDRIC - MSDMA), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Institut Supérieur d'Agriculture de Lille (ISA), Université catholique de Lille (UCL), Rotman Research Institute at the Baycrest Centre (RRI), University of Texas at Dallas [Richardson] (UT Dallas), Société Française de Statistique (SFdS), and Gloaguen, Arnaud
Subjects: [STAT]Statistics [stat], Multivariate Analysis, Parcimonie, Multiple Correspondence Analysis, Analyse Multivariée, Sparsity, Analyse des Correspondances Multiples, [STAT] Statistics [stat]
Abstract: International audience; Multiple Correspondence Analysis (MCA) is the method of choicefor themultivariate analysis of categorical data. In MCA each qualitative variable is representedby a group of binary variables (with a coding scheme called “complete disjunctive coding”)and each binary variable has a weight inversely proportional to its frequency. The datamatrix concatenates all these binary variables, and once normalized and centered thisdata matrix is analyzed with a generalized singular value decomposition (GSVD) thatincorporates the variable weights as constraints (or “metric”). The GSVD is, of course,based on the plain SVD and so MCA can be sparsified by extending algorithms designedto sparsify the SVD. To do so requires two additional features: to include weights andto be able to sparsify entire groups of variables at once. Another important feature ofsuch a sparsification should be to preserve the orthogonality of the components, Here, weintegrate all these constraints by using an exact projection scheme onto the intersectionof subspaces (i.e., balls) where each ball represents a specific type of constraints. Weillustrate our procedure with the data from a questionnaire survey on the perception ofcheese in two French cities.
Published: 2020

10. Analyse des Correspondances Multiples Parcimonieuse

Author: Vincent Guillemot, Julie Le Borgne, Arnaud Gloaguen, Arthur Tenenhaus, Gilbert Saporta, Sylvie Chollet, Derek Beaton, Hervé Abdi, Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Laboratoire des signaux et systèmes (L2S), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Unité Baobab (BAOBAB), Service NEUROSPIN (NEUROSPIN), 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)-Université Paris-Saclay, CEDRIC. Méthodes statistiques de data-mining et apprentissage (CEDRIC - MSDMA), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Institut Supérieur d'Agriculture de Lille (ISA), Rotman Research Institute at the Baycrest Centre (RRI), University of Texas at Dallas [Richardson] (UT Dallas), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Building large instruments for neuroimaging: from population imaging to ultra-high magnetic fields (BAOBAB), 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)-Centre National de la Recherche Scientifique (CNRS), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Université catholique de Lille (UCL), and Société Française de Statistique (SFdS)
Subjects: [STAT]Statistics [stat], Multivariate Analysis, Parcimonie, Multiple Correspondence Analysis, Analyse Multivariée, Sparsity, Analyse des Correspondances Multiples
Abstract: International audience; Multiple Correspondence Analysis (MCA) is the method of choicefor themultivariate analysis of categorical data. In MCA each qualitative variable is representedby a group of binary variables (with a coding scheme called “complete disjunctive coding”)and each binary variable has a weight inversely proportional to its frequency. The datamatrix concatenates all these binary variables, and once normalized and centered thisdata matrix is analyzed with a generalized singular value decomposition (GSVD) thatincorporates the variable weights as constraints (or “metric”). The GSVD is, of course,based on the plain SVD and so MCA can be sparsified by extending algorithms designedto sparsify the SVD. To do so requires two additional features: to include weights andto be able to sparsify entire groups of variables at once. Another important feature ofsuch a sparsification should be to preserve the orthogonality of the components, Here, weintegrate all these constraints by using an exact projection scheme onto the intersectionof subspaces (i.e., balls) where each ball represents a specific type of constraints. Weillustrate our procedure with the data from a questionnaire survey on the perception ofcheese in two French cities.
Published: 2020

11. Variability in the analysis of a single neuroimaging dataset by many teams

Author: Richard C. Reynolds, Jeremy Hogeveen, Joseph T. McGuire, Vittorio Iacovella, Gregory R. Samanez-Larkin, Cemal Koba, Paolo Avesani, Mikella A. Green, Margaret L. Schlichting, Claudio Toro-Serey, Tristan Glatard, Phui Cheng Lim, Emily A. Yearling, Simon B. Eickhoff, Katherine L. Bottenhorn, Susanne Weis, Andrew Erhart, Doris Pischedda, Mauricio R. Delgado, William A. Cunningham, Robert Langner, Matthew B. Wall, Amr Eed, Jorge Moll, Jeffrey B. Dennison, Wouter D. Weeda, Annabel B. Losecaat Vermeer, Anthony C. Juliano, Felix Hoffstaedter, Julia A. Camilleri, Nadège Bault, Cristian Buc Calderon, Xu Zhang, Gustav Tinghög, Vuong Truong, Leah Bakst, Stephan Heunis, Bertrand Thirion, Colin F. Camerer, Bradley C. Love, Tom Verguts, Luca Cecchetti, Patricia A. Reuter-Lorenz, Camille Maumet, Gabrielle Herman, Giacomo Handjaras, Michalis Kassinopoulos, Anthony Romyn, Xiangzhen Kong, Michael Notter, Nina Lauharatanahirun, Claire Donnat, Norberto Malpica, Jelle J. Goeman, Kamalaker Dadi, Michael Mack, Joke Durnez, Alberto De Luca, Margaret A. Sheridan, Shruti Ray, Colin Hawco, Enrico Glerean, J. Paul Hamilton, Qiang Shen, Sebastian Bobadilla-Suarez, Andrea Leo, David Wisniewski, Ayse Ilkay Isik, Lei Zhang, Bharat B. Biswal, Rotem Botvinik-Nezer, Flora Li, Bronson Harry, Andrew Jahn, Elise Lesage, Jean M. Vettel, Marco Barilari, Adrian I. Onicas, Susan Holmes, Khoi Vo, Aahana Bajracharya, Matthew Hughes, Rui Yuan, Nuri Erkut Kucukboyaci, Remi Gau, Sangsuk Yoon, Hongmi Lee, Alexandru D. Iordan, John Thorp, Russell A. Poldrack, Anna Dreber, Joshua E. Zosky, Dylan M. Nielson, Adriana S. Méndez Leal, Erin W. Dickie, Roeland Hancock, Tiago Bortolini, Kaustubh R. Patil, Monica Y.C. Li, Kristin N. Meyer, Fu Shiguang, Kenny Skagerlund, Juan Carlos de la Torre, Jennifer A. Silvers, R. Alison Adcock, Gustav Nilsonne, Zachary J. Cole, Emilio Sanz-Morales, Charles P. Davis, Michael Joseph, Sangil Lee, Tom Johnstone, Peder M. Isager, Jonathan E. Peelle, Emiliano Ricciardi, Scott A. Huettel, G. Matthew Fricke, Leonardo Tozzi, Brice A. Kuhl, Sagana Vijayarajah, Alexander Bowring, Jeanette A. Mumford, Blazej M. Baczkowski, Shabnam Hakimi, Sebastian Kupek, Michael Kirchler, Yanina Prystauka, Niall W. Duncan, Anna van 't Veer, Emily G. Brudner, Jamil P. Bhanji, Sarah M. Tashjian, Senne Braem, Paolo Papale, Simon R. Steinkamp, Georgios D. Mitsis, Kenneth S. L. Yuen, Magnus Johannesson, David J. White, Alec Smith, Krzysztof J. Gorgolewski, Alexander Leemans, Robert W. Cox, Emanuele Olivetti, Luca Turella, Juergen Huber, Tom Schonberg, David V. Smith, Lysia Demetriou, Peter Sokol-Hessner, Juergen Dukart, Glad Mihai, Taylor Salo, Jean-Baptiste Poline, Angela R. Laird, Sergej A.E. Golowin, Sarah Genon, Adriana Galván, Claus Lamm, Joseph W. Kable, Roni Iwanir, Theo Marins, Matthew R. Johnson, Anais Rodriguez-Thompson, Benjamin Meyer, Stefan Czoschke, Loreen Tisdall, Douglas H. Schultz, Evan N. Lintz, Derek Beaton, Peer Herholz, Olivia Guest, Jenny R. Rieck, Laura Fontanesi, Ekaterina Dobryakova, Alexandre Pérez, Olivier Collignon, Xin Di, Ruud Berkers, Sheryl B. Ball, Carlos González-García, Schuyler W. Liphardt, Edna C. Cieslik, Roland G. Benoit, João F. Guassi Moreira, Helena Melero, Jaime J. Castrellon, Hayley R. Brooks, Chuan-Peng Hu, Felix Holzmeister, Cheryl L. Grady, Thomas E. Nichols, Alba Xifra-Porxas, Steven H. Tompson, Kelsey McDonald, Julia Beitner, Timothy R. Koscik, Tel Aviv University (TAU), Dartmouth College [Hanover], Leopold Franzens Universität Innsbruck - University of Innsbruck, California Institute of Technology (CALTECH), Stockholm School of Economics (SSE), University of Wisconsin-Madison, Duke University [Durham], Fondazione Bruno Kessler [Trento, Italy] (FBK), University of Trento [Trento], Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Max-Planck-Gesellschaft, Washington University in Saint Louis (WUSTL), Boston University [Boston] (BU), Virginia Tech [Blacksburg], Université Catholique de Louvain = Catholic University of Louvain (UCL), Plymouth University, Rotman Research Institute at the Baycrest Centre (RRI), University of Amsterdam [Amsterdam] (UvA), Goethe-University Frankfurt am Main, Rutgers University [Newark], Rutgers University System (Rutgers), New Jersey Institute of Technology [Newark] (NJIT), University of Electronic Science and Technology of China [Chengdu] (UESTC), University College of London [London] (UCL), D'Or Institute for Research and Education [Rio de Janeiro], Florida International University [Miami] (FIU), University of Oxford, Vrije Universiteit Brussel (VUB), Universiteit Gent = Ghent University (UGENT), University of Denver, Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf], Jülich Research Centre, School for Advanced Studies Lucca (IMT), University of Nebraska–Lincoln, University of Nebraska System, National Institutes of Health [Bethesda] (NIH), University of Toronto, 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), Lancashire Teaching Hospital, University of Connecticut (UCONN), University Medical Center [Utrecht], Imperial College London, Temple University [Philadelphia], Pennsylvania Commonwealth System of Higher Education (PCSHE), Kessler Foundation [East Hanover], Stanford University, Taipei Medical University, TMU-ShuangHo Hospital [New Taipei City], Instituto de Neurociencias de Alicante, University of Basel (Unibas), The University of New Mexico [Albuquerque], Zhejiang University of Technology, University of California [Los Angeles] (UCLA), University of California (UC), Université catholique de Lille (UCL), Concordia University [Montreal], Aalto University, Leiden University Medical Center (LUMC), Universiteit Leiden, Linköping University (LIU), Western Sydney University, Centre for Addiction and Mental Health [Toronto] (CAMH), McGill University = Université McGill [Montréal, Canada], Eindhoven University of Technology [Eindhoven] (TU/e), Epilepsy Centre Kempenhaeghe [Heeze], Leibniz-Institut für Resilienzforschung [Mainz] (LIR), Swinburne University of Technology (Hawthorn campus), University of Michigan [Ann Arbor], University of Michigan System, Max Planck Institute for Empirical Aesthetics [Frankfurt am Main], University of Pennsylvania, Max Planck Institute for Psycholinguistics, Carver College of Medicine, University of Iowa, Rutgers New Jersey Medical School (NJMS), University of Oregon [Eugene], University of Vienna [Vienna], Johns Hopkins University (JHU), Nanjing University (NJU), Haskins Laboratories, The Alan Turing Institute, Universidad Rey Juan Carlos [Madrid] (URJC), 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), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Technische Universität Dresden = Dresden University of Technology (TU Dresden), Karolinska Institutet [Stockholm], Stockholm University, Université de Lausanne = University of Lausanne (UNIL), Netherlands Institute for Neuroscience (NIN), Royal Netherlands Academy of Arts and Sciences (KNAW), Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Humboldt University Of Berlin, Technical University of Berlin / Technische Universität Berlin (TU), University of California [Berkeley] (UC Berkeley), Columbia University [New York], Human Research and Engineering Directorate [Aberdeen Proving Ground], Stanford School of Medicine [Stanford], Stanford Medicine, Stanford University-Stanford University, University of California [Santa Barbara] (UC Santa Barbara), University of Dayton, Maumet, Camille, Technische Universität Berlin (TU), Leiden University, European Commission, Fundación 'la Caixa', Tel Aviv University [Tel Aviv], University of Innsbruck, University of Electronic Science and Technology of China (UESTC), University of Oxford [Oxford], Universiteit Gent = Ghent University [Belgium] (UGENT), University of Nebraska [Lincoln], 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), 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, University of California, University of Pennsylvania [Philadelphia], 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), Université de Lausanne (UNIL), Humboldt-Universität zu Berlin, University of California [Berkeley], University of California [Santa Barbara] (UCSB), Signal Processing Systems, and Human Technology Interaction
Subjects: Data Analysis, Male, Scientific community, Computer science, Decision, Datasets as Topic, Variation (game tree), Field (computer science), 0302 clinical medicine, Multidisciplinary approach, Data Science/methods, Models, Meta-Analysis as Topic, 0303 health sciences, Multidisciplinary, medicine.diagnostic_test, Brain, Magnetic Resonance Imaging, Research Personnel, Datasets as Topic/statistics & numerical data, Neurological, Female, ddc:500, Research Personnel/organization & administration, Models, Neurological, BF, Article, 03 medical and health sciences, Neuroimaging, Functional neuroimaging, Human behaviour, medicine, Humans, 030304 developmental biology, Statistical hypothesis testing, Flexibility (engineering), [SCCO.NEUR]Cognitive science/Neuroscience, Functional Neuroimaging, [SCCO.NEUR] Cognitive science/Neuroscience, Data Science, Reproducibility of Results, Brain/diagnostic imaging, Pipeline (software), Data science, Workflow, Logistic Models, Functional magnetic resonance imaging, Decision making, 030217 neurology & neurosurgery, Software
Abstract: Botvinik-Nezer, Rotem et al., Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed., European Union’s Horizon 2020 research and innovation programme (https://ec.europa.eu/programmes/horizon2020/en) under the Marie Skłodowska-Curie grant agreement no. 665501. A. Eed was supported by a predoctoral fellowship La Caixa-Severo Ochoa from Obra Social La Caixa. S.B.E. was supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 785907 (HBP SGA2).
Published: 2020
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12. Corticosteroids and Regional Variations in Thickness of the Human Cerebral Cortex across the Lifespan

Author: Leon French, Nadine Parker, Bernard Mazoyer, Anders M. Fjell, Henry Völzke, Reinhold Schmidt, Ian J. Deary, Perminder S. Sachdev, Aniket Mishra, Jean Shin, Kristine B. Walhovd, Norbert Hosten, Katharina Wittfeld, Qiong Yang, Gunter Schumann, Stéphanie Debette, Sudha Seshadri, Tomáš Paus, Claudia L. Satizabal, Simon R. Cox, Maria J. Knol, Hans J. Grabe, Jiyang Jiang, Hieab H.H. Adams, Henry Brodaty, Helena Schmidt, Stefan Frenzel, Zdenka Pausova, Giovanni Abrahão Salum, Wei Wen, Didac Vidal-Piñeiro, Mohammad Arfan Ikram, Epidemiology, Radiology & Nuclear Medicine, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Rotman Research Institute at the Baycrest Centre (RRI), Centre for Healthy Brain Ageing, University of New South Wales [Sydney] (UNSW), Groupe d'imagerie neurofonctionnelle (GIN), Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Metacohorts Consortium, Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, Institute for Community Medicine, Universität Greifswald - University of Greifswald, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), and University of Washington [Seattle]
Subjects: Male, Aging, [SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Gene Expression, 0302 clinical medicine, Glucocorticoid receptor, metabolism [Receptors, Mineralocorticoid], Gene expression, Child, metabolism [Receptors, Glucocorticoid], Aged, 80 and over, Cerebral Cortex, 0303 health sciences, Microglia, Human brain, Middle Aged, physiology [Aging], medicine.anatomical_structure, VINTAGE, Cerebral cortex, Child, Preschool, anatomy & histology [Cerebral Cortex], Corticosteroid, Female, Original Article, Glucocorticoid, medicine.drug, Adult, medicine.medical_specialty, Adolescent, medicine.drug_class, Cognitive Neuroscience, Biology, 03 medical and health sciences, Cellular and Molecular Neuroscience, Young Adult, Receptors, Glucocorticoid, Internal medicine, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], medicine, Humans, ddc:610, Gene, 030304 developmental biology, Aged, metabolism [Cerebral Cortex], Endocrinology, Receptors, Mineralocorticoid, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, 030217 neurology & neurosurgery
Abstract: Exposures to life stressors accumulate across the lifespan, with possible impact on brain health. Little is known, however, about the mechanisms mediating age-related changes in brain structure. We use a lifespan sample of participants (n = 21 251; 4–97 years) to investigate the relationship between the thickness of cerebral cortex and the expression of the glucocorticoid- and the mineralocorticoid-receptor genes (NR3C1 and NR3C2, respectively), obtained from the Allen Human Brain Atlas. In all participants, cortical thickness correlated negatively with the expression of both NR3C1 and NR3C2 across 34 cortical regions. The magnitude of this correlation varied across the lifespan. From childhood through early adulthood, the profile similarity (between NR3C1/NR3C2 expression and thickness) increased with age. Conversely, both profile similarities decreased with age in late life. These variations do not reflect age-related changes in NR3C1 and NR3C2 expression, as observed in 5 databases of gene expression in the human cerebral cortex (502 donors). Based on the co-expression of NR3C1 (and NR3C2) with genes specific to neural cell types, we determine the potential involvement of microglia, astrocytes, and CA1 pyramidal cells in mediating the relationship between corticosteroid exposure and cortical thickness. Therefore, corticosteroids may influence brain structure to a variable degree throughout life.
Published: 2020
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13. Progress update from the hippocampal subfields group

Author: Trevor A. Steve, Katrin Amunts, Olga Kedo, Rosanna K. Olsen, Elliott G. Johnson, Joshua K. Lee, Martina Bocchetta, Ulman Lindenberger, Craig E.L. Stark, Ricardo Insausti, Daniela J. Palombo, Naftali Raz, Margaret L. Schlichting, Gaël Chételat, Valerie A. Carr, Markus Werkle-Bergner, Nanthia Suthana, Paul A. Yushkevich, Jordan DeKraker, Attila Keresztes, Andrew R. Bender, Noa Ofen, John Pluta, Arnold Bakker, David Berron, Karen M. Rodrigue, Kristen M. Kennedy, Robert S. C. Amaral, Prabesh Kanel, Renaud La Joie, Mirjam I. Geerlings, Susanne G. Mueller, Qijing Yu, Songlin Ding, Jean C. Augustinack, Laura E.M. Wisse, Marina Boccardi, Lei Wang, Lorenzo Pasquini, Yee Lee Shing, Ana M. Daugherty, Elizabeth M. Mulligan, Robin de Flores, Yushan Huang, M. Mallar Chakravarty, Alison C. Burggren, Rotman Research Institute at the Baycrest Centre (RRI), University of Toronto, San Jose State University [San José] (SJSU), Wayne State University [Detroit], Memory and Aging Center [San Francisco, CA, États-Unis], University of California [San Francisco] (UCSF), University of California-University of California, Douglas Mental Health University Institute [Montréal], McGill University = Université McGill [Montréal, Canada], Institute of Neuroscience and Medicine [Jülich] (INM-1), Massachusetts General Hospital [Boston], Johns Hopkins University School of Medicine [Baltimore], Lund University [Lund], German Research Center for Neurodegenerative Diseases - Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Neuroimaging and Telemedicine (LENITEM), IRCCS Fatebenefratelli - Brescia, Dementia Research Centre [London] (DRC), University College of London [London] (UCL), University of Oregon [Eugene], Physiopathologie et imagerie des troubles neurologiques (PhIND), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), GIP Cyceron (Cyceron), Normandie Université (NU)-Normandie Université (NU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Normandie Université (NU), University of Western Ontario (UWO), Allen Institute for Brain Science [Seattle, WA, USA], University Medical Center [Utrecht], University of Alberta, Human Neuroanatomy Laboratory [Albacete, Spain] (School of Medicine - CRIB), University of Castilla-La Mancha (UCLM)-Centro Regional de Investigaciones Biomédicas (CRIB), University of California, University of Michigan Medical School [Ann Arbor], University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf], University of Texas at Dallas [Richardson] (UT Dallas), Max Planck Institute for Human Development, Max-Planck-Gesellschaft, University of California [Davis] (UC Davis), Freie Universität Berlin, Florida State University [Tallahassee] (FSU), Weizmann Institutes of Science [Rehovot, Israel], University of British Columbia (UBC), University of Pennsylvania [Philadelphia], Goethe-University Frankfurt am Main, University of California [Irvine] (UCI), University of California [Los Angeles] (UCLA), Northwestern University Feinberg School of Medicine, Penn Image Computing & Science Lab [Philadelphia] (PICSL), The work on this article was also supported by NIH grant R01 AG-011230 to Naftali Raz, NIH grant R01 AG-055121 to Lei Wang, NIH grant R01 AG-056014 to Paul Yushkevich, and NIH grant R01 AG-034613 to Craig Stark. M.M.C. receives salary support from the Fonds du Recherches Santes Quebec and also acknowledges support from NSERC, Weston Brain Institute, and CIHR., Hippocampal Subfields Group, San Jose State University [San Jose] (SJSU), University of California [San Francisco] (UC San Francisco), University of California (UC)-University of California (UC), Universidad de Castilla-La Mancha = University of Castilla-La Mancha (UCLM)-Centro Regional de Investigaciones Biomédicas (CRIB), University of California (UC), University of Pennsylvania, University of California [Irvine] (UC Irvine), and CHETELAT, Gaëlle
Subjects: Histology, Standardization, Computer science, Clinical Neurology, Structural imaging, Neuroimaging, lcsh:Geriatrics, Hippocampal formation, Hippocampus, lcsh:RC346-429, Special Section: Working Group Summaries for the European Joint Programme for Neurodegenerative Disease Research (JPND). (Guest Editors: Jorge Jovicich & Giovanni B. Frisoni), Temporal lobe, ddc:616.89, 03 medical and health sciences, 0302 clinical medicine, Volumetry, Segmentation, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], ddc:610, lcsh:Neurology. Diseases of the nervous system, Reliability (statistics), 030304 developmental biology, Protocol (science), 0303 health sciences, ex vivo, International working group, Data science, Ex vivo, 3. Good health, lcsh:RC952-954.6, Psychiatry and Mental health, Neuroanatomy, Cytoarchitec- ture, Cytoarchitecture, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurology (clinical), 030217 neurology & neurosurgery, Human
Abstract: Introduction Heterogeneity of segmentation protocols for medial temporal lobe regions and hippocampal subfields on in vivo magnetic resonance imaging hinders the ability to integrate findings across studies. We aim to develop a harmonized protocol based on expert consensus and histological evidence. Methods Our international working group, funded by the EU Joint Programme–Neurodegenerative Disease Research (JPND), is working toward the production of a reliable, validated, harmonized protocol for segmentation of medial temporal lobe regions. The working group uses a novel postmortem data set and online consensus procedures to ensure validity and facilitate adoption. Results This progress report describes the initial results and milestones that we have achieved to date, including the development of a draft protocol and results from the initial reliability tests and consensus procedures. Discussion A harmonized protocol will enable the standardization of segmentation methods across laboratories interested in medial temporal lobe research worldwide., Highlights • Harmonization of MRI-based segmentation of medial temporal regions is needed. • The Hippocampal Subfield Group includes >200 imaging and anatomy experts worldwide. • Reliable and valid protocol based on specialized histology data set in development. • A modified Delphi procedure is used to determine consensus on protocol rules. • Final protocol will provide subfield delineation in hippocampal body, head, and tail.
Published: 2019
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14. Cancer-related cognitive impairment: an update on state of the art, detection, and management strategies in cancer survivors

Author: Martine Dubois, Florence Joly, Janette L. Vardy, M.B. de Ruiter, Gordon Winocur, Tim A. Ahles, Laure Tron, Marie Lange, Hélène Castel, CASTEL, Hélène, Centre de recherche clinique [CHU Caen] (CRC), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN)-Centre Régional de Lutte contre le Cancer François Baclesse [Caen] (UNICANCER/CRLC), Normandie Université (NU)-UNICANCER-Tumorothèque de Caen Basse-Normandie (TCBN)-UNICANCER, Unité de recherche interdisciplinaire pour la prévention et le traitement des cancers (ANTICIPE), Normandie Université (NU)-UNICANCER-Tumorothèque de Caen Basse-Normandie (TCBN)-UNICANCER-Institut National de la Santé et de la Recherche Médicale (INSERM), Plateforme Cancer et Cognition, CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Ligue Nationale Contre le Cancer (LNCC)-Cancéropole Nord-Ouest, Service d'Oncologie médicale [CHU Caen], Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), University of New South Wales [Sydney] (UNSW), Memorial Sloane Kettering Cancer Center [New York], Différenciation et communication neuronale et neuroendocrine (DC2N), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institute for Research and Innovation in Biomedicine (IRIB), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Rotman Research Institute at the Baycrest Centre (RRI), Netherlands Cancer Institute (NKI), Antoni van Leeuwenhoek Hospital, Normandie Université (NU)-Normandie Université (NU)-Centre Régional de Lutte contre le Cancer François Baclesse [Caen] (UNICANCER/CRLC), UNICANCER-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-UNICANCER-Tumorothèque de Caen Basse-Normandie (TCBN)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), UNICANCER-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-UNICANCER-Institut National de la Santé et de la Recherche Médicale (INSERM), and Normandie Université (NU)-Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: 0301 basic medicine, Oncology, medicine.medical_specialty, [SDV]Life Sciences [q-bio], Neurogenesis, Reviews, [SDV.CAN]Life Sciences [q-bio]/Cancer, Antineoplastic Agents, Disease, Catechol O-Methyltransferase, [SCCO]Cognitive science, 03 medical and health sciences, 0302 clinical medicine, Apolipoproteins E, Cognition, [SDV.CAN] Life Sciences [q-bio]/Cancer, Cancer Survivors, Internal medicine, Neoplasms, medicine, Humans, Cognitive Dysfunction, Cognitive rehabilitation therapy, Exercise, Polymorphism, Genetic, business.industry, Brain-Derived Neurotrophic Factor, Neuropsychology, Cancer, [SCCO] Cognitive science, Hematology, Executive functions, medicine.disease, Chemotherapy regimen, Cognitive training, 3. Good health, [SDV] Life Sciences [q-bio], 030104 developmental biology, 030220 oncology & carcinogenesis, Quality of Life, Cytokines, business
Abstract: Background Advances in diagnostic and therapeutic strategies in oncology have significantly increased the chance of survival of cancer patients, even those with metastatic disease. However, cancer-related cognitive impairment (CRCI) is frequently reported in patients treated for non-central nervous system cancers, particularly during and after chemotherapy. Design This review provides an update of the state of the art based on PubMed searches between 2012 and March 2019 on ‘cognition’, ‘cancer’, ‘antineoplastic agents’ or ‘chemotherapy’. It includes the most recent clinical, imaging and pre-clinical data and reports management strategies of CRCI. Results Evidence obtained primarily from studies on breast cancer patients highlight memory, processing speed, attention and executive functions as the most cognitive domains impaired post-chemotherapy. Recent investigations established that other cancer treatments, such as hormone therapies and targeted therapies, can also induce cognitive deficits. Knowledge regarding predisposing factors, biological markers or brain functions associated with CRCI has improved. Factors such as age and genetic polymorphisms of apolipoprotein E, catechol-O-methyltransferase and BDNF may predispose individuals to a higher risk of cognitive impairment. Poor performance on neuropsychological tests were associated with volume reduction in grey matter, less connectivity and activation after chemotherapy. In animals, hippocampus-based memory and executive functions, mediated by the frontal lobes, were shown to be particularly susceptible to the effects of chemotherapy. It involves altered neurogenesis, mitochondrial dysfunction or brain cytokine response. An important next step is to identify strategies for managing cognitive difficulties, with primary studies to assess cognitive training and physical exercise regimens. Conclusions CRCI is not limited to chemotherapy. A multidisciplinary approach has improved our knowledge of the complex mechanisms involved. Nowadays, studies evaluating cognitive rehabilitation programmes are encouraged to help patients cope with cognitive difficulties and improve quality of life during and after cancer.
Published: 2019
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15. Chemotherapy and cognition: International cognition and cancer task force recommendations for harmonising preclinical research

Author: Ian Johnston, Gordon Winocur, Hélène Castel, Rotman Research Institute at the Baycrest Centre (RRI), The University of Sydney, Différenciation et communication neuronale et neuroendocrine (DC2N), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), and CASTEL, Hélène
Subjects: International Cooperation, Advisory Committees, Antineoplastic Agents, Disease, Neuropsychological Tests, Affect (psychology), 03 medical and health sciences, [SCCO]Cognitive science, 0302 clinical medicine, Neurochemical, Quality of life (healthcare), Neoplasms, medicine, Animals, Humans, Chemotherapy, Radiology, Nuclear Medicine and imaging, Cancer, Task force, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, Cognition, General Medicine, [SCCO] Cognitive science, medicine.disease, 3. Good health, Cognitive test, Disease Models, Animal, Oncology, Preclinical research, 030220 oncology & carcinogenesis, Cognitive function, business, Cognition Disorders, 030217 neurology & neurosurgery, Clinical psychology
Abstract: International audience; Cancer survivors who undergo chemotherapy for non-CNS tumours often report substantial cognitive disturbances that adversely affect quality of life, during and after treatment. The neurotoxic effects of anti-cancer drugs have been confirmed in clinical and pre-clinical research. Work with animals has also identified a range of factors and underlying mechanisms that contribute to chemotherapy-induced cognitive impairment. However, there is a continuing need to develop standard cognitive testing procedures for validation and comparison purposes, broaden the search for biological and neurochemical mechanisms, and develop improved animal models for investigating the combined effects of treatment, the disease, and other potential factors (e.g., age, stress). In this paper, a working group, formed under the auspices of the International Cognition and Cancer Task Force, reviews the state of pre-clinical research, formulates strategic priorities, and provides recommendations to guide animal research that meaningfully informs clinical investigations.
Published: 2018
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16. International Cognition and Cancer Task Force Recommendations for Harmonising Preclinical Research : Progress and Future Directions

Author: Winocur, Gordon, Johnston, Ian, Castel, Hélène, Rotman Research Institute at the Baycrest Centre (RRI), The University of Sydney, Différenciation et communication neuronale et neuroendocrine (DC2N), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), and CASTEL, Hélène
Subjects: [SDV] Life Sciences [q-bio], [SDV.CAN] Life Sciences [q-bio]/Cancer, [SDV]Life Sciences [q-bio], [SDV.CAN]Life Sciences [q-bio]/Cancer, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), ComputingMilieux_MISCELLANEOUS
Abstract: Organisation of a workshop “Pre-clinical Workshop"; International audience
Published: 2018

17. MicroRNAs 146a/b-5 and 425-3p and 24-3p are markers of antidepressant response and regulate MAPK/Wnt-system genes

Author: Hannah M. Cates, Francesco Leri, Gustavo Turecki, Laura M. Fiori, Roumen Milev, Steven C. Strother, Rixing Lin, Juan Pablo Lopez, Glenda MacQueen, Naguib Mechawar, Cristiana Cruceanu, Benicio N. Frey, Stacy M. Ku, Katherine J. Aitchison, Elizabeth A. Heller, Sidney H. Kennedy, Kenneth R. Evans, Raymond W. Lam, Kathrin Tyryshkin, Peter Giacobbe, Vincent Vialou, Daniel J. Müller, Rudolf Uher, Sagar V. Parikh, Cathryn M. Lewis, Christophe Gerald, Claudio N. Soares, Faranak Farzan, Susan Rotzinger, Benoit Labonté, Ming-Hu Han, Pierre Blier, Jane A. Foster, Eric J. Nestler, Harriet Feilotter, Gayle M. Wittenberg, Douglas Mental Health University Institute [Montréal], McGill University = Université McGill [Montréal, Canada], Icahn School of Medicine at Mount Sinai [New York] (MSSM), McMaster University [Hamilton, Ontario], St. Michael's Hospital, Queen's University [Kingston, Canada], University of Toronto, Centre for Addiction and Mental Health [Toronto] (CAMH), British Columbia, University of Guelph, University of Calgary, University of Ottawa [Ottawa], University of British Columbia (UBC), Vancouver Coastal Health Research Institute (VCH), University of Michigan [Ann Arbor], University of Michigan System, Rotman Research Institute at the Baycrest Centre (RRI), Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, University of Alberta, Dalhousie University [Halifax], Janssen Research & Development, and vialou, vincent
Subjects: 0301 basic medicine, MAPK/ERK pathway, Male, General Physics and Astronomy, Bioinformatics, law.invention, chemistry.chemical_compound, Mice, 0302 clinical medicine, Randomized controlled trial, law, Wnt Signaling Pathway, Regulation of gene expression, Multidisciplinary, Wnt signaling pathway, Brain, Middle Aged, Antidepressive Agents, 3. Good health, Major depressive disorder, Antidepressant, Female, Adult, MAP Kinase Signaling System, Science, Duloxetine Hydrochloride, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Young Adult, microRNA, medicine, Journal Article, Duloxetine, Animals, Humans, Aged, Depressive Disorder, Major, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, Computational Biology, General Chemistry, medicine.disease, Mice, Inbred C57BL, MicroRNAs, 030104 developmental biology, HEK293 Cells, chemistry, Gene Expression Regulation, business, 030217 neurology & neurosurgery, Biomarkers
Abstract: Antidepressants (ADs) are the most common treatment for major depressive disorder (MDD). However, only ∼30% of patients experience adequate response after a single AD trial, and this variability remains poorly understood. Here, we investigated microRNAs (miRNAs) as biomarkers of AD response using small RNA-sequencing in paired samples from MDD patients enrolled in a large, randomized placebo-controlled trial of duloxetine collected before and 8 weeks after treatment. Our results revealed differential expression of miR-146a-5p, miR-146b-5p, miR-425-3p and miR-24-3p according to treatment response. These results were replicated in two independent clinical trials of MDD, a well-characterized animal model of depression, and post-mortem human brains. Furthermore, using a combination of bioinformatics, mRNA studies and functional in vitro experiments, we showed significant dysregulation of genes involved in MAPK/Wnt signalling pathways. Together, our results indicate that these miRNAs are consistent markers of treatment response and regulators of the MAPK/Wnt systems., Antidepressant drugs are the most common treatment for depressive episodes but only a fraction of patients experience adequate response. Here the authors find dysregulation of miRNAs in peripheral blood samples from depressed patients after antidepressant treatment, and show that the miRNAs are regulators of psychiatrically relevant signalling pathways.
Published: 2017
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18. Randomized parcellation based inference

Author: Vincent Frouin, Tomáš Paus, Jean-Luc Martinot, Gareth J. Barker, Marcella Rietschel, Gaël Varoquaux, Patricia J. Conrod, Jean-Baptiste Poline, Uli Bromberg, Arun L.W. Bokde, Frauke Nees, Jürgen Gallinat, Bertrand Thirion, Virgile Fritsch, Tobias Banaschewski, Andreas Ströhle, Michael N. Smolka, Zdenka Pausova, Hugh Garavan, Benoit Da Mota, 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), Laboratoire de Neuroimagerie Assistée par Ordinateur (LNAO), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Department of Child and Adolescent Psychiatry and Psychotherapy [Mannheim], Universität Heidelberg [Heidelberg] = Heidelberg University, Institute of Psychiatry, King‘s College London, Institute of Neuroscience, Trinity College Dublin-Trinity College Dublin-Discipline of Psychiatry [Dublin], School of Medicine [Dublin], Trinity College Dublin-Trinity College Dublin-School of Medicine [Dublin], Trinity College Dublin, Universitaetsklinikum Hamburg-Eppendorf = University Medical Center Hamburg-Eppendorf [Hamburg] (UKE), Institute of Psychiatry, Psychology & Neuroscience, King's College London, Department of Psychiatry and Psychotherapy, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], University of Vermont [Burlington], Neuroimagerie en psychiatrie (U1000), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Rotman Research Institute at the Baycrest Centre (RRI), McConnell Brain Imaging Centre (MNI), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], School of Psychology [Nottingham], University of Nottingham, UK (UON), SickKids - The Hospital for sick children, The Hospital for sick children [Toronto] (SickKids), Department of Genetic Epidemiology in Psychiatry [Mannhein], Universität Heidelberg [Heidelberg] = Heidelberg University-Central Institute of Mental Health Mannheim, Technische Universität Dresden = Dresden University of Technology (TU Dresden), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Digitéo (HiDiNim project and ICoGeN project), Imagen Consortium, European Project: 39513,IMAGEN, 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), Universität Heidelberg [Heidelberg], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Sud - Paris 11 (UP11), Universität Heidelberg [Heidelberg]-Central Institute of Mental Health Mannheim, Fritsch, Virgile, and Reinforcement-related behaviour in normal brain function and psychopathology - IMAGEN - 39513 - OLD
Subjects: [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, permutations, Cognitive Neuroscience, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Inference, Neuroimaging, Stop signal, Catechol O-Methyltransferase, computer.software_genre, Polymorphism, Single Nucleotide, [STAT.AP] Statistics [stat]/Applications [stat.AP], Voxel, Resampling, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, medicine, Cluster Analysis, Humans, Computer Simulation, reproducibility, Genetic Association Studies, multiple comparisons, [STAT.AP]Statistics [stat]/Applications [stat.AP], medicine.diagnostic_test, business.industry, Brain, Contrast (statistics), Pattern recognition, Magnetic Resonance Imaging, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, Neurology, group analysis, parcellation, Multiple comparisons problem, Data mining, Artificial intelligence, Functional magnetic resonance imaging, Psychology, business, computer
Abstract: International audience; Neuroimaging group analyses are used to relate inter-subject signal differences observed in brain imaging with behavioral or genetic variables and to assess risks factors of brain diseases. The lack of stability and of sensitivity of current voxel-based analysis schemes may however lead to non-reproducible results. We introduce a new approach to overcome the limitations of standard methods, in which active voxels are detected according to a consensus on several random parcellations of the brain images, while a permutation test controls the false positive risk. Both on synthetic and real data, this approach shows higher sensitivity, better accuracy and higher reproducibility than state-of-the-art methods. In a neuroimaging-genetic application, we find that it succeeds in detecting a significant association between a genetic variant next to the COMT gene and the BOLD signal in the left thalamus for a functional Magnetic Resonance Imaging contrast associated with incorrect responses of the subjects from a Stop Signal Task protocol.
Published: 2014
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19. Brainhack: A collaborative workshop for the open neuroscience community

Author: Caroline Froehlich, David H. O’Connor, Robert C. Welsh, Sook-Lei Liew, Katharine Dunlop, Angela R. Laird, Yonggang Shi, Satrajit S. Ghosh, John W. Van Meter, Pierre-Olivier Quirion, Lucina Q. Uddin, R. Matthew Hutchison, Pierre Bellec, Salma Mesmoudi, Christopher J. Cannistraci, Maarten Mennes, Jonathan Downar, Sebastien Dery, Donald G. McLaren, Ariel Rokem, Prantik Kundu, Daniel S. Margulies, Fernando A. Barrios, Alexandre Rosa Franco, Ramon Fraga Pereira, Andrew J. Gerber, B. Nolan Nichols, R. Cameron Craddock, Erick H. Pasaye, Ziad S. Saad, Felipe Meneguzzi, Benjamin De Leener, Thomas J. Grabowski, Sean Hill, Sarael Alcauter, Julien Cohen-Adad, Daniel J. Lurie, Gautam Prasad, Roberto Toro, Ting Xu, John D. Van Horn, Yves Burnod, Anibal Sólon Heinsfeld, Jean-Baptiste Poline, Scott Peltier, Stephen C. Strother, Nathan S. Kline Institute for Psychiatric Research (NKI), New York State Office of Mental Health, Child Mind Institute, The Neuro Bureau [Leipzig], Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Max-Planck-Gesellschaft, Université de Montréal (UdeM), Centre de recherche de l'Institut universitaire de gériatrie de Montreal (CRIUGM), Silsoe Research Institute (SRI), Biotechnology and Biological Sciences Research Council, Stanford University, Universidad Nacional Autónoma de México (UNAM), Laboratoire d'Imagerie Biomédicale (LIB), 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), Institut des Systèmes Complexes - Paris Ile-de-France (ISC-PIF), École normale supérieure - Cachan (ENS Cachan)-Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Sud - Paris 11 (UP11)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut Curie [Paris]-École polytechnique (X), Icahn School of Medicine at Mount Sinai [New York] (MSSM), École Polytechnique de Montréal (EPM), McGill University = Université McGill [Montréal, Canada], University Health Network, University of Toronto, Pontifícia Universidade Católica do Rio Grande do Sul [Porto Alegre] (PUCRS), New York State Psychiatric Institute, Columbia University [New York], McGovern Institute for Brain Research [Cambridge], Massachusetts Institute of Technology (MIT), Harvard Medical School [Boston] (HMS), University of Washington [Seattle], International Neuroinformatics Coordinating Facility, Karolinska Institutet [Stockholm], Harvard University [Cambridge], Florida International University [Miami] (FIU), University of Southern California (USC), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Biospective [Montréal], Massachusetts General Hospital [Boston], Donders Institute for Brain, Cognition and Behaviour, Radboud university [Nijmegen], MATRICE Project (ISC-PIF), Sorbonnes university Paris 1, University of Michigan [Ann Arbor], University of Michigan System, The Helen Wills Neuroscience Institute (HWNI), University of California [Berkeley], University of California-University of California, Keck School of Medicine [Los Angeles], eScience Institute Seattle, National Institute of mental health , Bethesda, Rotman Research Institute at the Baycrest Centre (RRI), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris]-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Miami University, Miami University [Ohio] (MU), University of Miami Leonard M. Miller School of Medicine (UMMSM), Georgetown University Medical Center, We would also like to thank our sponsors, whose funds have been used to enrich the educational experience at Brainhack and have provided travel support for attendees. These include (in alphabetical order): Allen Institute for Brain Science (OHBM 2013), Amazon Web Services (OHBM 2013, OHBM 2014, Boston 2014, Brainhack AMX 2015), Athinoula A. Martinos Center for Biomedical Imaging (Boston 2014), Child Mind Institute, Inc. (NYC 2014, NYC 2015, MX 2015), FIU Division of Research (Miami 2014), Frontiers (OHBM 2014), Frontiers in Neuroscience (OHBM 2013), International Neuroinformatics Coordinating Facility (OHBM 2013, OHBM 2014, OHBM 2015, MX 2015), MATRICE (Paris 2013), Max Planck Institute for Cognitive and Brain Sciences (Leipzig 2012), Microsoft Azure (OHBM 2015), NIH BD2K Center (1U54EB020406-01) Big Data for Discovery Science (USC, PI: Toga, LA 2015), NIH BD2K Center (1U54EB020403-01) Enigma Center for Worldwide Medicine, Imaging, and Genomics (USC, PI: Thompson, LA 2015), NIH BD2K Supplement for NCANDA (3U01AA021697-04S1) and NCANDA: Data Analysis Component (5U01AA021697-04) (SRI International, PI: Pohl, OHBM2015, MX 2015), Organization for Human Brain Mapping (OHBM 2013, OHBM 2014, OHBM 2015), Ontario Brain Institute (Toronto 2014), Quebec Bio-Imaging Network (MTL 2014, MTL 2015), Siemens (Paris 2013), and University of Miami Flipse Funds (Miami 2015).References, HAL UPMC, Gestionnaire, Biotechnology and Biological Sciences Research Council (BBSRC), Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), 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), École normale supérieure - Cachan (ENS Cachan)-Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Sud - Paris 11 (UP11)-Université Pierre et Marie Curie - Paris 6 (UPMC)-École polytechnique (X)-Institut Curie [Paris]-Centre National de la Recherche Scientifique (CNRS), Pontifical Catholic University of Rio Grande do Sul (PUC-RS), Radboud University [Nijmegen], Université Paris 1 Panthéon-Sorbonne (UP1), University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), McGovern Institute for Brain Research at MIT, Ghosh, Satrajit S., Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Harvard University, and ANR-16-EQPX-0003,Matrice - 13 novembre,Matrice - 13 novembre(2016)
Subjects: 0301 basic medicine, Open science, Biomedical Research, Computer science, International Cooperation, Health Informatics, Review, Education, 03 medical and health sciences, Networking, 0302 clinical medicine, Humans, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Cooperative Behavior, Hackathon, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Neurosciences, 220 Statistical Imaging Neuroscience, Brain, Computational Biology, Congresses as Topic, Unconference, Data science, Collaboration, Research Personnel, Computer Science Applications, Data sharing, 030104 developmental biology, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neuroscience, 030217 neurology & neurosurgery
Abstract: Contains fulltext : 167121.pdf (Publisher’s version ) (Open Access) Brainhack events offer a novel workshop format with participant-generated content that caters to the rapidly growing open neuroscience community. Including components from hackathons and unconferences, as well as parallel educational sessions, Brainhack fosters novel collaborations around the interests of its attendees. Here we provide an overview of its structure, past events, and example projects. Additionally, we outline current innovations such as regional events and post-conference publications. Through introducing Brainhack to the wider neuroscience community, we hope to provide a unique conference format that promotes the features of collaborative, open science.
Published: 2016
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20. Measuring and Estimating the Effect Sizes of Copy Number Variants on General Intelligence in Community-Based Samples

Author: Thomas Bourgeron, Sonia Nizard, Roberto Toro, Sébastien Jacquemont, Gunter Schumann, Zdenka Pausova, Alexandre Mathieu, Jean-Baptiste Poline, Aurélie Labbe, Celia M. T. Greenwood, Guillaume Huguet, Elise Douard, Tomáš Paus, Emmanuelle Lemyre, Catherine Schramm, Patricia J. Conrod, Eva Loth, Frédérique Tihy, Lai Jiang, Géraldine Mathonnet, Université de Montréal (UdeM), CHU Sainte Justine [Montréal], Lady Davis Institute for Medical Research [Montréal], McGill University = Université McGill [Montréal, Canada]-Jewish General Hospital, HEC Montréal (HEC Montréal), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris]-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Gènes, Synapses et Cognition (CNRS - UMR3571 ), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, University of Toronto, McGill University = Université McGill [Montréal, Canada], Rotman Research Institute at the Baycrest Centre (RRI), Child Mind Institute, This research was enabled by support provided by Calcul Quebec (http://www.calculquebec.ca) and Compute Canada (http://www.computecanada.ca). Dr Bourgeron is supported by the Institut Pasteur, the University Paris Diderot, Centre National de la Recherche Scientifique, and the Bettencourt-Schueller Foundation. Dr Jacquemont is a recipient of a Bursary Professor fellowship of the Swiss National Science Foundation, a Canada Research Chair in neurodevelopmental disorders, and a chair from the Jeanne et Jean Louis Levesque Foundation. Dr Huguet is supported by the Sainte-Justine Foundation, the Merit scholarship program for foreign students, and the Network of Applied Genetic Medicine fellowships. Dr Schramm is supported by the Institute for Data Valorization fellowship. Dr Loth is supported by European Autism Interventions, which receives support from the Innovative Medicines Initiative Joint Undertaking under grant agreement 115300, the resources of which are composed of financial contributions from grant FP7/2007-2013 from the European Union's Seventh Framework Programme, the European Federation of Pharmaceutical Industries and Associations companies’ in-kind contributions, and Autism Speaks. This work is supported by a grant from the Brain Canada Multi Investigator initiative (Dr Jacquemont). The Canadian Institutes of Health Research and the Heart and Stroke Foundation of Canada fund the Saguenay Youth Study. Funding for the project was provided by the Wellcome Trust., European Project: 115300,EC:FP7:SP1-JTI,IMI-JU-03-2010,EU-AIMS(2012), Université de Montréal [Montréal], McGill University-Jewish General Hospital, Gènes, Synapses et Cognition, McGill University, Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), and Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Male, 0301 basic medicine, Adolescent, DNA Copy Number Variations, Genotype, Intraclass correlation, [SDV]Life Sciences [q-bio], Concordance, Intelligence, Population, Haploinsufficiency, Biology, Sampling Studies, Cohort Studies, 03 medical and health sciences, Loss of Function Mutation, Humans, Copy-number variation, Child, education, Original Investigation, Genetic association, Chromosome Aberrations, Genetics, education.field_of_study, Models, Genetic, Intelligence quotient, Genetic Carrier Screening, Quebec, Exons, Odds ratio, Europe, Psychiatry and Mental health, 030104 developmental biology, Neurodevelopmental Disorders, Female, Gene Deletion
Abstract: Importance; Copy number variants (CNVs) classified as pathogenic are identified in 10% to 15% of patients referred for neurodevelopmental disorders. However, their effect sizes on cognitive traits measured as a continuum remain mostly unknown because most of them are too rare to be studied individually using association studies. Objective To measure and estimate the effect sizes of recurrent and nonrecurrent CNVs on IQ. Design, Setting, and Participants This study identified all CNVs that were 50 kilobases (kb) or larger in 2 general population cohorts (the IMAGEN project and the Saguenay Youth Study) with measures of IQ. Linear regressions, including functional annotations of genes included in CNVs, were used to identify features to explain their association with IQ. Validation was performed using intraclass correlation that compared IQ estimated by the model with empirical data. Main Outcomes and Measures Performance IQ (PIQ), verbal IQ (VIQ), and frequency of de novo CNV events. Results The study included 2090 European adolescents from the IMAGEN study and 1983 children and parents from the Saguenay Youth Study. Of these, genotyping was performed on 1804 individuals from IMAGEN and 977 adolescents, 445 mothers, and 448 fathers (484 families) from the Saguenay Youth Study. We observed 4928 autosomal CNVs larger than 50 kb across both cohorts. For rare deletions, size, number of genes, and exons affect IQ, and each deleted gene is associated with a mean (SE) decrease in PIQ of 0.67 (0.19) points ( P = 6 × 10 −4 ); this is not so for rare duplications and frequent CNVs. Among 10 functional annotations, haploinsufficiency scores best explain the association of any deletions with PIQ with a mean (SE) decrease of 2.74 (0.68) points per unit of the probability of being loss-of-function intolerant ( P = 8 × 10 −5 ). Results are consistent across cohorts and unaffected by sensitivity analyses removing pathogenic CNVs. There is a 0.75 concordance (95% CI, 0.39-0.91) between the effect size on IQ estimated by our model and IQ loss calculated in previous studies of 15 recurrent CNVs. There is a close association between effect size on IQ and the frequency at which deletions occur de novo (odds ratio, 0.86; 95% CI, 0.84-0.87; P = 2.7 × 10 −88 ). There is a 0.76 concordance (95% CI, 0.41-0.91) between de novo frequency estimated by the model and calculated using data from the DECIPHER database. Conclusions and Relevance Models trained on nonpathogenic deletions in the general population reliably estimate the effect size of pathogenic deletions and suggest omnigenic associations of haploinsufficiency with IQ. This represents a new framework to study variants too rare to perform individual association studies and can help estimate the cognitive effect of undocumented deletions in the neurodevelopmental clinic.
Published: 2018
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21. Assessing and tuning brain decoders: cross-validation, caveats, and guidelines

Author: Andrés Hoyos-Idrobo, Bertrand Thirion, Yannick Schwartz, Denis A. Engemann, Gaël Varoquaux, Pradeep Reddy Raamana, 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), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Rotman Research Institute at the Baycrest Centre (RRI), Université Pierre et Marie Curie - Paris 6 (UPMC), ANR-11-BINF-0004,NiConnect,Outils pour la Recherche Clinique par cartographie de la connectivité cérébrale fonctionnelle(2011), 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), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay
Subjects: FOS: Computer and information sciences, 0301 basic medicine, model selection, decoding, Computer science, Cognitive Neuroscience, sparse, Neuroimaging, Machine Learning (stat.ML), computer.software_genre, cross-validation, Cross-validation, 03 medical and health sciences, 0302 clinical medicine, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, MVPA, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.4: Applications, Brain Diseases, Model selection, [SCCO.NEUR]Cognitive science/Neuroscience, fMRI, [SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences, bagging, 030104 developmental biology, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology/I.5.2.0: Classifier design and evaluation, Neurology, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Data mining, computer, 030217 neurology & neurosurgery, Decoding methods
Abstract: Decoding, ie prediction from brain images or signals, calls for empirical evaluation of its predictive power. Such evaluation is achieved via cross-validation, a method also used to tune decoders' hyper-parameters. This paper is a review on cross-validation procedures for decoding in neuroimaging. It includes a didactic overview of the relevant theoretical considerations. Practical aspects are highlighted with an extensive empirical study of the common decoders in within-and across-subject predictions, on multiple datasets --anatomical and functional MRI and MEG-- and simulations. Theory and experiments outline that the popular " leave-one-out " strategy leads to unstable and biased estimates, and a repeated random splits method should be preferred. Experiments outline the large error bars of cross-validation in neuroimaging settings: typical confidence intervals of 10%. Nested cross-validation can tune decoders' parameters while avoiding circularity bias. However we find that it can be more favorable to use sane defaults, in particular for non-sparse decoders., Comment: NeuroImage, Elsevier, 2016
Published: 2016
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22. Genomic architecture of human neuroanatomical diversity

Author: Gunter Schumann, Thomas Bourgeron, Bernd Ittermann, Zdenka Pausova, Roberto Toro, Fabiana M. Carvalho, Marcella Rietschel, Patricia J. Conrod, Karl Mann, J-B Poline, Hugh Garavan, Penny A. Gowland, Eva Loth, Mira Fauth-Bühler, Tomáš Paus, Herta Flor, Andreas Ströhle, Arun L.W. Bokde, Trevor W. Robbins, Claire Lawrence, Christian Büchel, Andreas Heinz, Michael N. Smolka, Tobias Banaschewski, Gareth J. Barker, Guillaume Huguet, Vincent Frouin, Frauke Nees, Jürgen Gallinat, Herve Lemaitre, Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), 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), Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, University Hospital Mannheim | Universitätsmedizin Mannheim, Universität Heidelberg [Heidelberg] = Heidelberg University, Trinity College Dublin, Universitaetsklinikum Hamburg-Eppendorf = University Medical Center Hamburg-Eppendorf [Hamburg] (UKE), CHU Sainte Justine [Montréal], Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], University of Vermont [Burlington], Physikalisch-Technische Bundesanstalt [Berlin] (PTB), University of Nottingham, UK (UON), Neuroimagerie en psychiatrie (U1000), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Maison de Solenn [CHU Cochin], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Cochin [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Rotman Research Institute at the Baycrest Centre (RRI), University of Toronto, University of Cambridge [UK] (CAM), Technische Universität Dresden = Dresden University of Technology (TU Dresden), Fondation FondaMental [Créteil], This work was supported by the European Union-funded FP6 Integrated Project IMAGEN (Reinforcement-related behaviour in normal brain function and psychopathology, LSHM-CT-2007-037286), the FP7 projects ADAMS (Genomic variations underlying common neuropsychiatric diseases and diseases related to cognitive traits in different human populations, 242257), the Innovative Medicine Initiative Project EU-AIMS (115300-2), the Medical Research Council Programme Grant ‘Developmental pathways into adolescent substance abuse’ (93558), the Swedish Funding Agency FORMAS, the German Bundesministerium und Forschung (FKZ: 01EV0711), Institut Pasteur, CNRS, Université Paris Diderot, the Bettencourt-Schueller Foundation, the Conny-Maeva Foundation, the Orange Foundation, the FondaMental Foundation and the Cognacq-Jay Foundation., European Project: 39513,IMAGEN, European Project: 242257,EC:FP7:HEALTH,FP7-HEALTH-2009-single-stage,ADAMS(2009), European Project: 115300,EC:FP7:SP1-JTI,IMI-JU-03-2010,EU-AIMS(2012), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Institut Pasteur [Paris], 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, Medical Faculty [Mannheim], Universität Heidelberg [Heidelberg], Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Cochin [AP-HP], Technische Universität Dresden (TUD), Université de Montréal. Faculté de médecine. Département de psychiatrie et d'addictologie, Institut Pasteur [Paris]-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Sud - Paris 11 (UP11)
Subjects: Male, Adolescent, Genotyping Techniques, media_common.quotation_subject, [SDV]Life Sciences [q-bio], Genome-wide association study, Single-nucleotide polymorphism, Neuroimaging, Biology, Genome, Polymorphism, Single Nucleotide, Cohort Studies, Heritability, Cellular and Molecular Neuroscience, 03 medical and health sciences, 0302 clinical medicine, medicine, Genetics, Humans, Computer Simulation, Molecular Biology, Gene, Genotyping, 030304 developmental biology, media_common, 0303 health sciences, Models, Genetic, Brain, Human brain, Organ Size, Magnetic Resonance Imaging, Psychiatry and Mental health, Neuroanatomy, medicine.anatomical_structure, Phenotype, Evolutionary biology, Female, 030217 neurology & neurosurgery, Diversity (politics), Genome-Wide Association Study
Abstract: International audience; Human brain anatomy is strikingly diverse and highly inheritable: genetic factors may explain up to 80% of its variability. Prior studies have tried to detect genetic variants with a large effect on neuroanatomical diversity, but those currently identified account for
Published: 2015
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23. Global Genetic Variations Predict Brain Response to Faces

Author: Erin W Dickie, Amir Tahmasebi, Leon French, Natasa Kovacevic, Tobias Banaschewski, Gareth J Barker, Arun Bokde, Christian Büchel, Patricia Conrod, Herta Flor, Hugh Garavan, Juergen Gallinat, Penny Gowland, Andreas Heinz, Bernd Ittermann, Claire Lawrence, Karl Mann, Jean-Luc Martinot, Frauke Nees, Thomas Nichols, Mark Lathrop, Eva Loth, Zdenka Pausova, Marcela Rietschel, Michal N Smolka, Andreas Ströhle, Roberto Toro, Gunter Schumann, Tomáš Paus, IMAGEN consortium, University of Toronto, Rotman Research Institute at the Baycrest Centre (RRI), University of Heidelberg, Medical Faculty, Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, Trinity College Dublin, Universitaetsklinikum Hamburg-Eppendorf = University Medical Center Hamburg-Eppendorf [Hamburg] (UKE), Université de Montréal (UdeM), Universität Mannheim, University of Vermont [Burlington], Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Sir Peter Mansfield Magnetic Resonance Centre [Nottingham], University of Nottingham, UK (UON), Physikalisch-Technische Bundesanstalt [Berlin] (PTB), Neuroimagerie en psychiatrie (U1000), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Warwick [Coventry], Centre National de Génotypage (CNG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Technische Universität Dresden = Dresden University of Technology (TU Dresden), Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), IMAGEN receives research funding from the European Community's Sixth Framework Programme (LSHM-CT-2007-037286). Further support was provided by the UK Department of Health NIHR-Biomedical Research Centre 'Mental Health' and the MRC programme grant 'Developmental pathways into adolescent substance abuse' (93558). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., Universität Mannheim [Mannheim], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Sud - Paris 11 (UP11), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Université de Montréal [Montréal], Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5), and Technische Universität Dresden (TUD)
Subjects: Male, Cancer Research, lcsh:QH426-470, Adolescent, Restricted maximum likelihood, [SDV]Life Sciences [q-bio], BF, Single-nucleotide polymorphism, Biology, Facial recognition system, Brain mapping, Polymorphism, Single Nucleotide, 500 Naturwissenschaften und Mathematik::570 Biowissenschaften, Biologie::576 Genetik und Evolution, 03 medical and health sciences, 0302 clinical medicine, Genetic variation, Statistics, Genetic model, medicine, Genetics, Humans, Molecular Biology, Genetics (clinical), Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, 0303 health sciences, Facial expression, Brain Mapping, medicine.diagnostic_test, Brain, Genetic Variation, Biology and Life Sciences, Genomics, QP, Magnetic Resonance Imaging, Facial Expression, lcsh:Genetics, Female, Functional magnetic resonance imaging, 030217 neurology & neurosurgery, Research Article, Neuroscience
Abstract: Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40–50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R2 = 0.38, p, Author Summary We measured brain response to facial expressions in a large sample of typically developing adolescents (n = 1,620) and assessed “heritability” of the response using common genetic variations across the genome. In a subset of brain regions, we explained 40–50% of phenotypic variance by genetic variance. These brain regions appear to differ from the rest of the face network in the degree of inter-individual variations in their functional connectivity. We propose that these regions, including the prefrontal and premotor cortex, represent “Optional” part of the network co-opted by its “Obligatory” members, including the posterior part of the superior temporal sulcus, fusiform face area and the lateral occipital cortex, concerned with processing complex visual stimuli.
Published: 2014
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24. Integrating neuroinformatics tools in TheVirtualBrain

Author: Woodman, M. Marmaduke, Pezard, Laurent, Domide, Lia, Knock, Stuart A., Sanz-Leon, Paula, Mersmann, Jochen, McIntosh, Anthony R., Jirsa, Viktor, Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Codemart, Codebox Gmbh, Rotman Research Institute at the Baycrest Centre (RRI), and European Project: 269921,EC:FP7:ICT,FP7-ICT-2009-6,BRAINSCALES(2011)
Subjects: magnetoencephalography, neural mass, time delays, connectivity, [SCCO.NEUR]Cognitive science/Neuroscience, Methods Article, functional MRI, brain networks, electroencephalography, Neuroscience, Python
Abstract: International audience; TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.
Published: 2014
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25. Breastfeeding and brain structure in adolescence

Author: Suzanne Veillette, Roberto Toro, Zdenka Pausova, Salomi Kafouri, Tomáš Paus, Bruce Pike, Louis Richer, Gabriel Leonard, Michael S. Kramer, Michel Perron, Rotman Research Institute at the Baycrest Centre (RRI), University of Toronto, McGill University = Université McGill [Montréal, Canada], Montreal Neurological Institute and Hospital, Université du Québec à Chicoutimi (UQAC), Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), CEGEP Jonquiere, This work was supported by the Canadian Institutes of Health Research (T.P., Z.P.), Heart and Stroke Foundation of Quebec (Z.P.) and the Canadian Foundation for Innovation (Z.P.)., and Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Male, Pediatrics, medicine.medical_specialty, Canada, Time Factors, Adolescent, Epidemiology, [SDV]Life Sciences [q-bio], Breastfeeding, Posterior parietal cortex, Neuropsychological Tests, 03 medical and health sciences, 0302 clinical medicine, Child Development, Cognition, Functional neuroimaging, Pregnancy, 030225 pediatrics, Surveys and Questionnaires, medicine, Humans, Child, development, Retrospective Studies, business.industry, Human milk, Brain, Inferior parietal lobule, General Medicine, cortical thickness, intelligence, medicine.disease, Child development, Magnetic Resonance Imaging, Breast Feeding, Socioeconomic Factors, Female, adolescence, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], business, Factor Analysis, Statistical, Breast feeding, 030217 neurology & neurosurgery, Clinical psychology
Abstract: International audience; BACKGROUND:The purpose of this investigation was to evaluate an association between duration of exclusive breastfeeding and structure of cortical regions implicated in general intelligence.METHODS:We studied adolescents (n = 571; aged 12-18 years) participating in the Saguenay Youth Study; half of the participants were exposed to maternal cigarette smoking during pregnancy. Hierarchical linear modelling was used to assess whether breastfeeding is an important predictor of cortical thickness when other predictors, such as age, sex, parental education and exposure to maternal smoking during pregnancy, are also considered. Target cortical regions were identified using a meta-analysis of functional neuroimaging studies of cognitive abilities relevant for general intelligence.RESULTS:We found that duration of exclusive breastfeeding was associated with cortical thickness in the superior and inferior parietal lobules (t = 2.31, P = 0.02). We also replicated the association between breastfeeding and general intelligence (t = 2.69, P = 0.008).CONCLUSION:In this study, we showed that breastfeeding is associated with variations in the thickness of the parietal cortex in a community-based sample of adolescents. We also found association of breastfeeding duration with full scale and performance IQ, as observed previously.
Published: 2013
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26. Multiple factor analysis: principal component analysis for multitable and multiblock data sets

Author: Abdi , Hervé, Williams , Lynne J., Valentin , Dominique, School of Behavioral and Brain Sciences, University of Texas at Dallas [Richardson] (UT Dallas), Rotman Research Institute at the Baycrest Centre (RRI), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), 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), AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, ProdInra, Archive Ouverte, University of Texas at Dallas [Richardson] ( UT Dallas ), Rotman research institute, University of Toronto, Centre des Sciences du Goût et de l'Alimentation [Dijon] ( CSGA ), 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: multiple factor analysis barycentric discriminant analysis (mufabada), statis, [STAT.TH] Statistics [stat]/Statistics Theory [stat.TH], principal component analysis, multiblock correspondence analysis, barycentric discriminant analysis (bada), generalized procrustes analysis (gpa), [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], [ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH], consensus pca, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], multiblock pca, multiple factor analysis (mfa), multiple factorial analysis, [ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST], multitable pca, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], indscal, multiblock barycentric discriminant analysis (mudica), generalized singular value decomposition
Abstract: absent
Published: 2013

27. KCTD8 Gene and Brain Growth in Adverse Intrauterine Environment: A Genome-wide Association Study

Author: Zdenka Pausova, Manon Bernard, Nicholas J. Timpson, Melkaye G Melka, Michel Perron, Tomáš Paus, Suzanne Veillette, M. Mallar Chakravarty, Anbarasu Lourdusamy, Gunter Schumann, George Davey Smith, G. Bruce Pike, Paul Pavlidis, Louis Richer, Gabriel Leonard, Roberto Toro, Jesse Gillis, Rotman Research Institute at the Baycrest Centre (RRI), University of Toronto, Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada], University of Bristol [Bristol], University of British Columbia (UBC), Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, Université du Québec à Chicoutimi (UQAC), Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), CEGEP Jonquiere, The Saguenay Youth Study project is funded by the Canadian Institutes of Health Research (T.P. [NET 54015, MOP 86678], Z.P. [MOP-74623, MOP-79571]) and the Canadian Foundation for Innovation (Z.P., Project CFI# 6862). UK Medical Research Council (grant ref: 74882), Wellcome Trust (grant ref: 076467), and University of Bristol provide core support for ALSPAC., and Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Parents, [SDV]Life Sciences [q-bio], Mice, 0302 clinical medicine, Image Processing, Computer-Assisted, Birth Weight, GWAS, Longitudinal Studies, Child, Cerebral Cortex, 0303 health sciences, Fetal Growth Retardation, Smoking, Articles, Human brain, Magnetic Resonance Imaging, Potassium channel, medicine.anatomical_structure, Cerebral cortex, In utero, Prenatal Exposure Delayed Effects, Brain size, Female, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], pregnancy, Algorithms, Intracellular, Adult, Canada, medicine.medical_specialty, Adolescent, Cognitive Neuroscience, brain, Gestational Age, Locus (genetics), Biology, White People, 03 medical and health sciences, Cellular and Molecular Neuroscience, Internal medicine, medicine, Animals, Humans, Progenitor cell, 030304 developmental biology, Body Height, Pregnancy Complications, Endocrinology, adolescence, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: International audience; The most dramatic growth of the human brain occurs in utero and during the first 2 years of postnatal life. Genesis of the cerebral cortex involves cell proliferation, migration, and apoptosis, all of which may be influenced by prenatal environment. Here, we show that variation in KCTD8 (potassium channel tetramerization domain 8) is associated with brain size in female adolescents (rs716890, P 5 5.40 3 10 209). Furthermore, we found that the KCTD8 locus interacts with prenatal exposure to maternal cigarette smoking visa `-vis cortical area and cortical folding: In exposed girls only, the KCTD8 locus explains up to 21% of variance. Using head circumference as a proxy of brain size at 7 years of age, we have replicated this gene-environment interaction in an independent sample. We speculate that KCTD8 might modulate adverse effects of smoking during pregnancy on brain development via apoptosis triggered by low intracellular levels of potassium, possibly reducing the number of progenitor cells.
Published: 2012
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28. STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling

Author: Domininique Valentin, Hervé Abdi, Mohammed Bennani-Dosse, Lynne J. Williams, School of Behavioral and Brain Sciences, University of Texas at Dallas [Richardson] (UT Dallas), Rotman Research Institute at the Baycrest Centre (RRI), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche Mathématique de Rennes (IRMAR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-INSTITUT AGRO Agrocampus Ouest, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), 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), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST-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)-École normale supérieure - Rennes (ENS Rennes)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), 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), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-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), University of Texas at Dallas [Richardson] ( UT Dallas ), Rotman research institute, University of Toronto, Centre des Sciences du Goût et de l'Alimentation [Dijon] ( CSGA ), 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 ), Institut de Recherche Mathématique de Rennes ( IRMAR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -AGROCAMPUS OUEST-École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National des Sciences Appliquées ( INSA ) -Université de Rennes 2 ( UR2 ), and Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS )
Subjects: Statistics and Probability, Mathematical optimization, Similarity (geometry), [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH], Linear discriminant analysis, computer.software_genre, 01 natural sciences, [ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH], Correspondence analysis, Set (abstract data type), 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Multiple factor analysis, Principal component analysis, Metric (mathematics), Data mining, Multidimensional scaling, [ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST], 0101 mathematics, computer, 030217 neurology & neurosurgery, ComputingMilieux_MISCELLANEOUS, Mathematics
Abstract: STATIS is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables collected on the same observations, or, alternatively, as in a variant called dual-STATIS, multiple data tables where the same variables are measured on different sets of observations. STATIS proceeds in two steps: First it analyzes the between data table similarity structure and derives from this analysis an optimal set of weights that are used to compute a linear combination of the data tables called the compromise that best represents the information common to the different data tables; Second, the PCA of this compromise gives an optimal map of the observations. Each of the data tables also provides a map of the observations that is in the same space as the optimum compromise map. In this article, we present STATIS, explain the criteria that it optimizes, review the recent inferential extensions to STATIS and illustrate it with a detailed example.
Published: 2012
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29. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

Author: Pm, Thompson, Jl, Stein, Se, Medland, Dp, Hibar, Aa, Vasquez, Me, Renteria, Toro R, Jahanshad N, Schumann G, Franke B, Mj, Wright, Ng, Martin, Agartz I, Alda M, Alhusaini S, Almasy L, Almeida J, Alpert K, Nc, Andreasen, Oa, Andreassen, Lg, Apostolova, Appel K, Nj, Armstrong, Aribisala B, Me, Bastin, Bauer M, Ce, Bearden, Bergmann O, Eb, Binder, Blangero J, Hj, Bockholt, Bøen E, Bois C, Di, Boomsma, Booth T, Ij, Bowman, Bralten J, Rm, Brouwer, Hg, Brunner, Dg, Brohawn, Rl, Buckner, Buitelaar J, Bulayeva K, Jr, Bustillo, Vd, Calhoun, Dm, Cannon, Rm, Cantor, Ma, Carless, Caseras X, Gl, Cavalleri, Mm, Chakravarty, Kd, Chang, Cr, Ching, Christoforou A, Cichon S, Vp, Clark, Conrod P, Coppola G, Crespo-Facorro B, Je, Curran, Czisch M, Ij, Deary, Ej, Geus, den Braber A, Delvecchio G, Depondt C, de Haan L, Gi, Zubicaray, Dima D, Dimitrova R, Djurovic S, Dong H, Donohoe G, Duggirala R, Td, Dyer, Ehrlich S, Cj, Ekman, Elvsåshagen T, Emsell L, Erk S, Espeseth T, Fagerness J, Fears S, Fedko I, Fernández G, Se, Fisher, Foroud T, Pt, Fox, Francks C, Frangou S, Em, Frey, Frodl T, Frouin V, Garavan H, Giddaluru S, Dc, Glahn, Godlewska B, Rz, Goldstein, Rl, Gollub, Hj, Grabe, Grimm O, Gruber O, Guadalupe T, Re, Gur, Rc, Gur, Hh, Göring, Hagenaars S, Hajek T, Gb, Hall, Hall J, Hardy J, Ca, Hartman, Hass J, Sn, Hatton, Uk, Haukvik, Hegenscheid K, Heinz A, Ib, Hickie, Bc, Ho, Hoehn D, Pj, Hoekstra, Hollinshead M, Aj, Holmes, Homuth G, Martine Hoogman, Le, Hong, Hosten N, Jj, Hottenga, He, Hulshoff Pol, Ks, Hwang, Cr, Jack Jr, Jenkinson M, Johnston C, Eg, Jönsson, Rs, Kahn, Kasperaviciute D, Kelly S, Kim S, Kochunov P, Koenders L, Krämer B, Jb, Kwok, Lagopoulos J, Laje G, Landen M, Ba, Landman, Lauriello J, Sm, Lawrie, Ph, Lee, Le Hellard S, Lemaître H, Cd, Leonardo, Cs, Li, Liberg B, Dc, Liewald, Liu X, Lm, Lopez, Loth E, Lourdusamy A, Luciano M, Macciardi F, Mw, Machielsen, Gm, Macqueen, Uf, Malt, Mandl R, Ds, Manoach, Jl, Martinot, Matarin M, Ka, Mather, Mattheisen M, Mattingsdal M, Meyer-Lindenberg A, McDonald C, Am, Mcintosh, Fj, Mcmahon, Kl, Mcmahon, Meisenzahl E, Melle I, Milaneschi Y, Mohnke S, Gw, Montgomery, Dw, Morris, Ek, Moses, Ba, Mueller, Muñoz Maniega S, Tw, Mühleisen, Müller-Myhsok B, Mwangi B, Nauck M, Nho K, Te, Nichols, Lg, Nilsson, Ac, Nugent, Nyberg L, Rl, Olvera, Oosterlaan J, Ra, Ophoff, Pandolfo M, Papalampropoulou-Tsiridou M, Papmeyer M, Paus T, Pausova Z, Gd, Pearlson, Bw, Penninx, Cp, Peterson, Pfennig A, Phillips M, Gb, Pike, Jb, Poline, Sg, Potkin, Pütz B, Ramasamy A, Rasmussen J, Rietschel M, Rijpkema M, Sl, Risacher, Jl, Roffman, Roiz-Santiañez R, Romanczuk-Seiferth N, Ej, Rose, Na, Royle, Rujescu D, Ryten M, Ps, Sachdev, Salami A, Td, Satterthwaite, Savitz J, Aj, Saykin, Scanlon C, Schmaal L, Hg, Schnack, Aj, Schork, Sc, Schulz, Schür R, Seidman L, Shen L, Jm, Shoemaker, Simmons A, Sm, Sisodiya, Smith C, Jw, Smoller, Jc, Soares, Sr, Sponheim, Sprooten E, Jm, Starr, Vm, Steen, Strakowski S, Strike L, Sussmann J, Pg, Sämann, Teumer A, Aw, Toga, Tordesillas-Gutierrez D, Trabzuni D, Trost S, Turner J, Van den Heuvel M, Nj, Wee, van Eijk K, Tg, Erp, Ne, Haren, van 't Ent D, Mj, Tol, Mc, Valdés Hernández, Dj, Veltman, Versace A, Völzke H, Walker R, Walter H, Wang L, Jm, Wardlaw, Me, Weale, Mw, Weiner, Wen W, Lt, Westlye, Hc, Whalley, Cd, Whelan, White T, Am, Winkler, Wittfeld K, Woldehawariat G, Wolf C, Zilles D, Mp, Zwiers, Thalamuthu A, Pr, Schofield, Nb, Freimer, Ns, Lawrence, Drevets W, The Alzheimer’s Disease Neuroimaging Initiative, Epigen Consortium, Laboratory of Neuro Imaging [Los Angeles] (LONI), University of California [Los Angeles] (UCLA), University of California-University of California, David Geffen School of Medicine [Los Angeles], Medstar Research Institute, Keck School of Medicine [Los Angeles], University of Southern California (USC), Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, Department of Psychiatry, Donders Centre for Neuroscience, Radboud university [Nijmegen]-Radboud University Medical Center [Nijmegen]-Radboud university [Nijmegen]-Radboud University Medical Center [Nijmegen], Genetic Epidemiology Lab [Brisbane], Queensland Institute of Medical Research, Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), KG Jebsen Centre for Psychosis Research, University of Oslo (UiO)-Institute of Clinical Medicine-Oslo University Hospital [Oslo], Dalhousie University [Halifax], Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland (RCSI), Department of Genetics, Southwest Foundation for Biomedical Research, Departamento de Matemática Pura, Faculdade de Ciências (UNIVERSIDADE DO PORTO), Universidade do Porto = University of Porto, Department of Psychiatry and Psychotherapy, University of Edinburgh, Center for Sepsis Control & Care, Jena University Hospital, Division Genetic Epidemiology in Psychiatry, Central Institute of Mental Health [Mannheim], Medical Faculty [Mannheim]-Medical Faculty [Mannheim], Texas Biomedical Research Institute [San Antonio, TX], Donders Institute for Brain, Cognition and Behaviour, Radboud university [Nijmegen], Brain Center Rudolf Magnus, Department of Psychiatry, UMC Utrecht, Utrecht 3584 CX, The Netherlands, Radboud University Medical Center [Nijmegen], Department of Psychiatry [Boston], Massachusetts General Hospital [Boston], Karakter Child and Adolescent Psychiatry University Centre [Nijmegen], N.I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Human Genetics Branch, National Institutes of Health [Bethesda] (NIH)-National Institute of Mental Health (NIMH), Department of Genomics, Douglas Mental Health University Institute, McGill University = Université McGill [Montréal, Canada], sans affiliation, Università degli Studi di Salermo, Università degli Studi di Salerno (UNISA), Centro de Investigación Biomédica en Red Salud Mental [Madrid] (CIBER-SAM), Bijvoet Center of Biomolecular Research [Utrecht], Utrecht University [Utrecht], Biological Psychology, Neuroscience Campus Amsterdam & EMGO Institute for Health and Care Research, VU University & VU Medical Center, Amsterdam 1081 BT, The Netherlands, Department of Neurology, Hôpital Erasme [Bruxelles] (ULB), Faculté de Médecine [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB)-Faculté de Médecine [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB), Department of Psychiatry [Pittsburgh], University of Pittsburgh School of Medicine, Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), School of Psychology, University of Queensland, University of Queensland [Brisbane], Department of Hematology, 'Ion Chiricuta' Cancer Institute, University of Oslo (UiO), The University of Texas Health Science Center at Houston (UTHealth), MetaGenoPolis, Institut National de la Recherche Agronomique (INRA), Department of Psychiatry, Division of Medical Psychology, Champalimaud Neuroscience Programme, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indiana University System-Indiana University System, Language and Genetics Department [Nijmegen], Max Planck Institute for Psycholinguistics, Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Icahn School of Medicine at Mount Sinai [New York] (MSSM), Division of Hemato-Oncology, Saint Anna Children's Hospital [Vienne] = St Anna Kinderspital (St. Anna Children's Hospital), Psychiatry and Psychotherapy, 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), University of Vermont [Burlington], Haukeland University Hospital, University of Bergen (UiB), Dpt of Psychiatry [New Haven], Yale School of Medicine [New Haven, Connecticut] (YSM), Laboratory of Molecular Neuropsychiatry, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], HELIOS Klinikum Stralsund Hanseatic-Greifswald University Hospital, Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Universität Heidelberg [Heidelberg], International Max Planck Research School for Language Sciences (IMPRS ), Lancaster University, Georgia Institute of Technology [Atlanta], Greifswald University Hospital, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Clinical Research Unit, Brain & Mind Research Institute-The University of Sydney, Department of Psychiatry, University of Iowa, University of Iowa [Iowa City], Max Planck Institute of Psychiatry, Max-Planck-Gesellschaft, University Medical Center Groningen [Groningen] (UMCG), Interfaculty Institute for Genetics and Functional Genomics, Universität Greifswald - University of Greifswald, Mental Health Sciences Unit, University College of London [London] (UCL), University Medical Center [Utrecht], Department of Radiology [Rochester], Mayo Clinic [Rochester], Department of Clinical Neurology [Oxford], University of Oxford [Oxford]-FMRIB Centre- John Radcliffe Hospital [Oxford University Hospital], Centre for the Cellular Basis of Behavior, Bureau d'Économie Théorique et Appliquée (BETA), Institut National de la Recherche Agronomique (INRA)-Université de Strasbourg (UNISTRA)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Department of Medicine, Imperial College London, MetaCase [Jyväskylä], Structure et Réactivité des Systèmes Moléculaires Complexes (SRSMC), Institut de Chimie du CNRS (INC)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), University of Maryland [Baltimore County] (UMBC), University of Maryland System-University of Maryland System-University of Maryland School of Medicine, University of Maryland System, Sahlgrenska Academy at University of Gothenburg [Göteborg], Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Université de Cergy Pontoise (UCP), Université Paris-Seine, National Institutes of Health [Bethesda] (NIH), Department of Forensic and Neurodevelopmental Sciences, University of California [Irvine] (UCI), University of California, Neuroimagerie en psychiatrie (U1000), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Clinical And Experimental Epilepsy, Centre for Healthy Brain Ageing, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia, Department of Life Sciences, Mathematical Sciences Institute (MSI), Australian National University (ANU), Centre for Advanced Imaging, Division of Mental Health and Addiction, Oslo University Hospital [Oslo], VU University Medical Center [Amsterdam], Metacohorts Consortium, Translational Centre for Regenerative Medicine (TRM), Department of Cell Therapy, Universität Leipzig [Leipzig]-Universität Leipzig [Leipzig], Institute of Clinical Chemistry and Laboratory Medicine, Indiana Alzheimer Disease Center, Department of Statistics [Warwick], University of Warwick [Coventry], Department of Health Science, Division of Health and Rehabilitation, Luleå University of Technology (LUT), University Medical Center [Utrecht]-Brain Center Rudolf Magnus, McConnell Brain Imaging Centre (MNI), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Canada, Technische Universität Dresden = Dresden University of Technology (TU Dresden), Modelling brain structure, function and variability based on high-field MRI data (PARIETAL), 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), Statistical Genetics Group, Respiratory Epidemiology and Public Health, Imperial College London-School of public health, The University of Hong Kong (HKU)-The University of Hong Kong (HKU)-MRC-HPA Centre for Environment and Health, Donders Center for Cognitive Neuroimaging, Donders Centre for Cognitive Neuroimaging, Radboud university [Nijmegen]-Radboud university [Nijmegen], Institut Parisien de Chimie Moléculaire (IPCM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Centre for Healthy Brain Ageing, University of New South Wales [Sydney] (UNSW), Umeå Centre for Functional Brain Imaging (UFBI), Umeå University, Umeå 901 87, Sweden, University of Pennsylvania [Philadelphia], Department of Cognitive Sciences [San Diego], University of California [San Diego] (UC San Diego), Indiana University System, Natbrainlab, Department of Forensic and Neurodevelopmental Sciences, Institute of psychiatry-King‘s College London, Institute of Neurology [London], Laboratoire des symbioses tropicales et méditerranéennes (UMR LSTM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université Montpellier 1 (UM1)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Stanley Center for Psychiatric Research, Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], King Faisal Specialist Hospital and Research Centre, Georgia State University, University System of Georgia (USG), Department of Psychiatry and Human Behavior [Irvine], Leiden University Medical Center (LUMC), Institute for Community Medicine, School of Music and Music Education (UNSW), Science & Technology Information Institute, Shandong Academy of Agricultural Science, University of California [San Francisco] (UCSF), Department of Physics [Hong Kong University of Science and Technology], Hong Kong University of Science and Technology (HKUST), Department of Psychology [Oslo], Faculty of Social Sciences [Oslo], University of Oslo (UiO)-University of Oslo (UiO), Research Laboratory for Archaeology & the History of Art, German Research Center for Neurodegenerative Diseases - Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Dundee Technopole, CXR Biosciences Ltd, Georg-August-University [Göttingen], Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney 2052, Australia, Prince of Wales Medical Research Institute, Center for Neurobehavioral Genetics, Wales Institute of Cognitive Neuroscience, Cardiff University, Complutense University of Madrid (UCM), Universidade do Porto [Porto], Texas Biomedical Research Institute [San Antonio, Texas], Karakter Child and Adolescent Psychiatry University Centre, McGill University, Bijvoet Center of Biomolecular Research, Université Libre de Bruxelles [Bruxelles] (ULB)-Hôpital Erasme (Bruxelles), St. Anna Children's Hospital, 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, University of Bergen (UIB), Yale University School of Medicine, Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS), Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Sud - Paris 11 (UP11), McGill University-McGill University, Technische Universität Dresden (TUD), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Inria Saclay - Ile de France, Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Department of Physics [Kowloon], University of California (UC)-University of California (UC), QIMR Berghofer Medical Research Institute, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Department of Clinical Neurosciences, Neurology Division, Karolinska Institutet, Karolinska University Hospital [Stockholm], Pennsylvania Commonwealth System of Higher Education (PCSHE), Northwestern University [Chicago, Ill. USA], Norwegian Centre for Mental Disorders Research [Oslo] (NORMENT), University of Oslo (UiO)-Haukeland University Hospital, University of Bergen (UiB)-University of Bergen (UiB)-Oslo University Hospital [Oslo], Ernst-Moritz-Arndt-Universität Greifswald, School of Mathematics and Statistics, Brain Research Imaging Centre, Imaging Sciences, University Hospital Carl Gustav Carus [Dresden, Germany], Semel Institute for Neuroscience and Human Behavior [Los Angeles, Ca], Institute of Clinical Medicine [Oslo], Faculty of Medicine [Oslo], Royal Hospital for Sick Children [Edinburgh], Department of General Practice/EMGO Institute, Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE), University of Edinburgh-Medical Research Council (MRC), Radboud University [Nijmegen], Brain Centre Rudolf Magnus [Utrecht], Department of Human Genetics [Nijmegen], Psychiatric and Neurodevelopmental Genetics Unit, Harvard University, Russian Academy of Sciences [Moscow] (RAS), The University of New Mexico [Albuquerque], The Mind Research Network, Department of Electrical and Computer Engineering [Albuquerque] (ECE Department), National University of Ireland [Galway] (NUI Galway), University of California (UC), Institute of Psychological Medicine and Clinical Neurosciences, Centre for Addiction and Mental Health [Toronto] (CAMH), Institute of Biomaterials and Biomedical Engineering [Toronto, ON, Canada] (IBBME), University of Toronto, Stanford School of Medicine [Stanford], Stanford Medicine, Stanford University-Stanford University, Universität Bonn = University of Bonn, Jülich Research Centre, University of Basel (Unibas), Centre de recherche du CHU Sainte-Justine / Research Center of the Sainte-Justine University Hospital [Montreal, Canada], Université de Montréal (UdeM)-CHU Sainte Justine [Montréal], Fundación Marqués de Valdecilla-Instituto de Formación e Investigación Marqués de Valdecilla (IFIMAV), Centre for Cognitive Ageing and Cognitive Epidemiology, Trinity College Dublin, Department of Psychiatry Massachusetts General Hospital (MGH), South Texas Veterans Health Care System, San Antonio, Texas 78229, USA, University Hospital Regensburg, Hartford Hospital, University of Oxford, HELIOS Klinikum Stralsund Hanseatic, University of Heidelberg, Medical Faculty, Georg-August-University = Georg-August-Universität Göttingen, University of Pennsylvania, McMaster University [Hamilton, Ontario], UCL, Institute of Neurology [London], Brain and Mind Research Institute, University of Technology Sydney (UTS), Diakonhjemmet Hospital, University of Maryland School of Medicine, Oakland University, University of Rochester School of Medicine, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), South London and Maudsley NHS Foundation Trust, Institute for Molecular Medicine Finland [Helsinki] (FIMM), Helsinki Institute of Life Science (HiLIFE), Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, University of Maryland [Baltimore], Neuroscience Research Australia (NeuRA), University of Gothenburg (GU), Karolinska Institutet [Stockholm], Vanderbilt University [Nashville], University of Missouri [Columbia] (Mizzou), University of Missouri System, Service Hospitalier Frédéric Joliot (SHFJ), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Clinatec - Centre de recherche biomédicale Edmond J.Safra (SCLIN), Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Neuroscience, Yale University School of Medicine, Columbia University Medical Center (CUMC), Columbia University [New York], University of Nottingham, UK (UON), University of California [Irvine] (UC Irvine), Università degli Studi di Milano = University of Milan (UNIMI), Hotchkiss Brain Institute, University of Calgary, Oslo and Akershus University College of Applied Sciences [Oslo] (HiOA), Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, UNSW Medicine, University of New South Wales, Sydney, Aarhus University [Aarhus], Sorlandet Hospital HF, University Hospital Mannheim | Universitätsmedizin Mannheim, Centre for Advanced Imaging [Brisbane] (CAI), Ludwig Maximilian University [Munich] (LMU), Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, The University of Western Australia (UWA), University of Minnesota [Morris], University of Minnesota System, Munich Cluster for systems neurology [Munich] (SyNergy), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM)-Ludwig-Maximilians-Universität München (LMU), The University of Texas Medical School at Houston, Indiana State University, Stockholm Brain Institute [Stockholm, Sweden], Stockholm University, Umeå University, University of Texas Health Science Center, Department of Clinical Neuropsychology, University of Amsterdam [Amsterdam] (UvA), Rotman Research Institute at the Baycrest Centre (RRI), The Hospital for sick children [Toronto] (SickKids), University of Pittsburgh (PITT), University of California [Berkeley] (UC Berkeley), King's College, Reta Lila Weston Institute, UCL Institute of Neurology, Department of Molecular Neuroscience, University College of London [London] (UCL)-Institute of Neurology, University of Cantabria, Santander, Research Triangle Institute International (RTI International), Martin-Luther-Universität Halle Wittenberg (MLU), Prince of Wales Hospital, Karolinska Institute, Laureate institute for brain research, Tulsa, University of Tulsa, Department of Cognitive Sciences [Univ California San Diego] (CogSci - UC San Diego), University of Minnesota Medical School, Beth Israel Deaconess Medical Center [Boston] (BIDMC), Harvard Medical School [Boston] (HMS), Maudsley NHS Foundation Trust and Institute of Psychiatry, NIHR Biomedical Research Centre [London], Guy's and St Thomas' NHS Foundation Trust-King‘s College London, Edinburgh Dementia Prevention & Centre for Clinical Brain Sciences, Center for Human Genetic Research, VA NY Harbor Health Care System, Alzheimer Scotland Dementia Research Centre, Department of Psychiatry and Behavioral Neuroscience [UC, Cincinnati], University of Cincinnati (UC), University of Cincinnati College of Medicine, Marqués de Valdecilla University Hospital [Santander], King Faisal Specialist Hospital and Resarch Centre [Riyadh, Saudi Arabia] (KFSHRC), Psychiatry and Leiden Institute for Brain and Cognition, Universiteit Leiden-Universiteit Leiden, Universiteit Leiden, Department of Biological Psychology [Amsterdam], Vrije Universiteit Amsterdam [Amsterdam] (VU), The Centre for Regenerative Medicine, Berlin School of Mind and Brain [Berlin], Humboldt University Of Berlin, University of California [San Francisco] (UC San Francisco), School of Chemistry, University of Edinburgh, Department of Public Health, Erasmus University Medical Centre, Rotterdam, Erasmus University Medical Centre, Rotterdam, Department of Psychiatry and Biobehavioral Sciences, University of Exeter, Janssen Research & Development, A complete listing of ADNI investigators is available at http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf The work reviewed here was funded by a large number of federal and private agencies worldwide, listed in Stein et al. (2012), the funding for listed consortia is also itemized in Stein et al. (2012)., Medical Oncology, Epidemiology, Clinical Chemistry, Cardiology, Neurosciences, Child and Adolescent Psychiatry / Psychology, Radboud University Medical Center [Nijmegen]-Radboud university [Nijmegen]-Radboud University Medical Center [Nijmegen]-Radboud university [Nijmegen], Universidade do Porto, FMRIB Centre- John Radcliffe Hospital [Oxford University Hospital]-University of Oxford [Oxford], Université de Lorraine (UL)-Université de Strasbourg (UNISTRA)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Sud - Paris 11 (UP11), 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), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences, Smoller, Jordan, Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), ANS - Amsterdam Neuroscience, Adult Psychiatry, Other departments, University of Oxford [Oxford]- John Radcliffe Hospital [Oxford University Hospital]-FMRIB Centre, and Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)
Subjects: endocrine system, Multi-site, Cognitive Neuroscience, [SDV]Life Sciences [q-bio], body-mass index, Clinical Neurology, multivariate parallel ica, Neuroimaging, methods [Genome-Wide Association Study], human brain structure, methods [Brain Mapping], Behavioral Neuroscience, Cellular and Molecular Neuroscience, ddc:150, Meta-Analysis as Topic, cortical surface-area, Genetics, voxel-based morphometry, GWAS, Humans, Cooperative Behavior, disease risk variant, Brain Mapping, MRI, Consortium, Meta-analysis, white-matter microstructure, SI: Genetic Neuroimaging in Aging and Age-Related Diseases, Psychiatry and Mental health, Neurology, Radiology Nuclear Medicine and imaging, quantitative trait loci, RC0321, genome-wide association, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], tensor-based morphometry, methods [Neuroimaging], Genome-Wide Association Study
Abstract: The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA’s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
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29 results on '"Rotman Research Institute at the Baycrest Centre (RRI)"'

1. Bases de données virtuelles pour l'étude de la Maladie d'Alzheimer et du vieillissement en utilisant de la modélisation des réseaux cérébraux dynamiques

2. Virtual Connectomic Datasets in Alzheimer’s Disease and Aging Using Whole-Brain Network Dynamics Modelling

3. What Affects the Magnitude of Age-Related Dual-Task Costs in Working Memory? The Role of Stimulus Domain and Access to Semantic Representations

4. Exploring the influence of temporal factors on age differences in working memory dual task costs

5. Bridging Scales in Alzheimer's Disease: Biological Framework for Brain Simulation With The Virtual Brain

6. Dynamic Functional Connectivity between order and randomness and its evolution across the human adult lifespan

7. How Do Scientific Views Change? Notes From an Extended Adversarial Collaboration

8. Sparse Multiple Correspondence Analysis

9. Sparse Multiple Correspondence Analysis

10. Analyse des Correspondances Multiples Parcimonieuse

11. Variability in the analysis of a single neuroimaging dataset by many teams

12. Corticosteroids and Regional Variations in Thickness of the Human Cerebral Cortex across the Lifespan

13. Progress update from the hippocampal subfields group

14. Cancer-related cognitive impairment: an update on state of the art, detection, and management strategies in cancer survivors

15. Chemotherapy and cognition: International cognition and cancer task force recommendations for harmonising preclinical research

16. International Cognition and Cancer Task Force Recommendations for Harmonising Preclinical Research : Progress and Future Directions

17. MicroRNAs 146a/b-5 and 425-3p and 24-3p are markers of antidepressant response and regulate MAPK/Wnt-system genes

18. Randomized parcellation based inference

19. Brainhack: A collaborative workshop for the open neuroscience community

20. Measuring and Estimating the Effect Sizes of Copy Number Variants on General Intelligence in Community-Based Samples

21. Assessing and tuning brain decoders: cross-validation, caveats, and guidelines

22. Genomic architecture of human neuroanatomical diversity

23. Global Genetic Variations Predict Brain Response to Faces

24. Integrating neuroinformatics tools in TheVirtualBrain

25. Breastfeeding and brain structure in adolescence

26. Multiple factor analysis: principal component analysis for multitable and multiblock data sets

27. KCTD8 Gene and Brain Growth in Adverse Intrauterine Environment: A Genome-wide Association Study

28. STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling

29. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

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29 results on '"Rotman Research Institute at the Baycrest Centre (RRI)"'

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