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4 results on '"The Computational, Cognitive and Clinical Neuroimaging Lab"'

1. Accelerating the Evolution of Nonhuman Primate Neuroimaging

Author

Olivier Coulon, Michael P. Milham, Patrik Lindenfors, Karl-Heinz Nenning, Xiaojin Liu, Ravi S. Menon, Stephanie J. Forkel, Adam Messinger, Zheng Wang, Alexander Thiele, Luciano Simone, Benjamin Jung, Chika Sato, Jamie Nagy, Sean Froudist-Walsh, Kelvin Mok, Renée Hartig, Julien Sein, Alessandro Gozzi, Julien Vezoli, Tomoko Sakai, Lynn Uhrig, Martine Meunier, Christienne G. Damatac, Bonhwang Koo, Roberto Toro, Rogier B. Mars, Henrietta Howells, Lea Roumazeilles, Ming Zhan, Ann-Marie Mallon, Román Rossi-Pool, Elinor L. Sullivan, Yannick Becker, Doris Y. Tsao, Antoine Grigis, Lei Ai, Céline Amiez, Sara Wells, Reza Rajimehr, Aki Nikolaidis, Anna S. Mitchell, Simon M. Reader, Michele A. Basso, Béchir Jarraya, Amir Raz, Wim Vanduffel, Charles R.E. Wilson, Brian E. Russ, Christopher R. Madan, Orlin S. Todorov, Wasana Madushanka, Carole Guedj, Mark A. Pinsk, Clémentine Bodin, Hugo Merchant, Jennifer Nacef, Damien A. Fair, Anna W. Roe, Sze Chai Kwok, Stephen J. Sawiak, Essa Yacoub, Bastien Cagna, Kevin N. Laland, Wilbert Zarco, Charles E. Schroeder, Ting Xu, P. Christiaan Klink, Stanislas Dehaene, Takuya Hayashi, Matthew F. S. Rushworth, Amir Shmuel, Fadila Hadj-Bouziane, Katja Heuer, Ioana-Sabina Rautu, Andrew S. Fox, Austin Benn, Sabine Kastner, Thomas Brochier, Emmanuel Procyk, Marco Pagani, David C. Van Essen, Frank Q. Ye, Dirk Jan Ardesch, Régis Trapeau, Jakob Seidlitz, Marike Schiffer, Bassem Hiba, John H. Morrison, David A. Rudko, Paula L. Croxson, Patrick Friedrich, Augix Guohua Xu, Lazar Fleysher, Piotr Majka, Jonathan Smallwood, Aihua Chen, Timothy D. Griffiths, Fabien Balezeau, Stefan Everling, Michael C. Schmid, Robert Leech, Leslie G. Ungerleider, Mark G. Baxter, Afonso C. Silva, Clare Kelly, Zhi-ming Shen, Daniel S. Margulies, Mark J. Prescott, Pascal Belin, Erwin L. A. Blezer, Igor Kagan, Suliann Ben Hamed, David A. Leopold, Adrien Meguerditchian, Wendy Jarrett, Michel Thiebaut de Schotten, Nikoloz Sirmpilatze, Julia Sliwa, Henry Kennedy, Vikas Pareek, Yong-di Zhou, Michael Ortiz-Rios, Sherif Hamdy El-Gohary, Susann Boretius, Christopher I. Petkov, Pamela Garcia-Saldivar, Bella Williams, Jordy Tasserie, Hank P. Jedema, Jerome Sallet, Pieter R. Roelfsema, Winrich A. Freiwald, Eduardo A. Garza-Villarreal, Noam Harel, Caspar M. Schwiedrzik, Kevin Marche, Colline Poirier, Yang Gao, Henry C. Evrard, Ashkan Alvand, ANS - Cellular & Molecular Mechanisms, Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS), Institut cellule souche et cerveau (SBRI), Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM), Collège de France - Chaire Psychologie cognitive expérimentale, Collège de France (CdF (institution)), Institut des sciences cognitives Marc Jeannerod - Centre de neuroscience cognitive - UMR5229 (ISC-MJ), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Consortium, PRIMatE Data Exchange Global Collaboration Workshop and, Nathan S. Kline Institute for Psychiatric Research (NKI), New York State Office of Mental Health, Newcastle University [Newcastle], Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Max-Planck-Gesellschaft, Medical Oncology, Department of Internal Medicine, Università Cattolica del Sacro Cuore [Roma] (Unicatt), Voice Neurocognition Laboratory, University of Glasgow, Oregon Health and Science University [Portland] (OHSU), Manchester Royal Infirmary, University of Manchester [Manchester], Princeton Neuroscience Institute [Princeton], University of Pennsylvania [Philadelphia], National Institute of Mental Health (NIMH), Harvard Medical School [Boston] (HMS), Washington University in St Louis, Laboratoire de psychologie cognitive (LPC), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Institut des sciences cognitives Marc Jeannerod - Centre de neuroscience cognitive - UMR5229 (CNC), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, New York University [New York] (NYU), NYU System (NYU), State Key Laboratory of Novel Software Technology, University of Nanjing, Center for Nanotechnology Innovation, @NEST (CNI), National Enterprise for nanoScience and nanoTechnology (NEST), Scuola Normale Superiore di Pisa (SNS)-Scuola Universitaria Superiore Sant'Anna [Pisa] (SSSUP)-Istituto Italiano di Tecnologia (IIT)-Consiglio Nazionale delle Ricerche [Pisa] (CNR PISA)-Scuola Normale Superiore di Pisa (SNS)-Scuola Universitaria Superiore Sant'Anna [Pisa] (SSSUP)-Istituto Italiano di Tecnologia (IIT)-Consiglio Nazionale delle Ricerche [Pisa] (CNR PISA), Unité Analyse et Traitement de l'Information (UNATI), 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, Neuroimagerie cognitive - Psychologie cognitive expérimentale (UNICOG-U992), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Saclay (COmUE), Institut cellule souche et cerveau (U846 Inserm - UCBL1), Royal Netherlands Academy of Arts and Sciences (KNAW), East China Normal University [Shangaï] (ECNU), The Computational, Cognitive and Clinical Neuroimaging Lab, Imperial College London, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Medical Research Counc, Station de primatologie (SP), Centre National de la Recherche Scientifique (CNRS), Institute of Language, Communication and the Brain (ILCB), The University of Western Ontario, Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM), Institute of integrative biology (Liverpool), University of Liverpool, McGovern Institute for Brain Research [Cambridge], Massachusetts Institute of Technology (MIT), University of Cambridge [UK] (CAM), Rockefeller University [New York], McConnell Brain Imaging Centre (MNI), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Laboratory for Neuro- and Psychofysiology, katho, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of York [York, UK], Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (CRICM), 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), Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Tianjin University of Science and Technology (TUST), Child Mind Institute, Center for Magnetic Resonance Research [Minneapolis] (CMRR), University of Minnesota Medical School, University of Minnesota System-University of Minnesota System, Institut cellule souche et cerveau / Stem Cell and Brain Research Institute (U1208 Inserm - UCBL1 / SBRI), Icahn School of Medicine at Mount Sinai [New York] (MSSM), University Medical Center [Utrecht], Radboud university [Nijmegen], Chaire Psychologie cognitive expérimentale, Centre de recherche en neurosciences de Lyon (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), University of St Andrews [Scotland], Stockholm University, Hôpital du Bocage, Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Princeton University, Utrecht University [Utrecht], Netherlands Institute for Neuroscience, Wellcome Trust Centre for Integrative Neuroimaging (WIN - FMRIB), University of Oxford [Oxford], National Institute of Environmental Health Sciences [Durham] (NIEHS-NIH), National Institutes of Health [Bethesda] (NIH), Oregon National Primate Research Center (ONPRC), California Institute of Technology (CALTECH), Johns Hopkins University (JHU), The PRIMatE Data Exchange (PRIME-DE) Global Collaboration Workshop and Consortium, ANR-16-CONV-0002,ILCB,ILCB: Institute of Language Communication and the Brain(2016), Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Complex Trait Genetics, Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Recherche Agronomique (INRA), and Vanduffel, Wim

Subjects
Primates, 0301 basic medicine, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, education, Neuroimaging, Article, [SPI]Engineering Sciences [physics], 03 medical and health sciences, 0302 clinical medicine, London, Psychology, Animals, Humans, Sociology, ComputingMilieux_MISCELLANEOUS, Cognitive science, Science & Technology, Human Connectome Project, [SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior, Action, intention, and motor control, Information Dissemination, General Neuroscience, Neurosciences, Brain, [SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences, Congresses as Topic, Nonhuman primate, 030104 developmental biology, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurosciences & Neurology, Life Sciences & Biomedicine, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 030217 neurology & neurosurgery
Abstract

Contains fulltext : 217200.pdf (Publisher’s version ) (Closed access) Nonhuman primate neuroimaging is on the cusp of a transformation, much in the same way its human counterpart was in 2010, when the Human Connectome Project was launched to accelerate progress. Inspired by an open data-sharing initiative, the global community recently met and, in this article, breaks through obstacles to define its ambitions. 4 p.

Published
2020
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2. A framework for inter-subject prediction of functional connectivity from structural networks

Author

Daniel Rueckert, Robert Leech, Fani Deligianni, Gaël Varoquaux, Bertrand Thirion, Christian Ledig, David J. Sharp, Department of Computing [London], Biomedical Image Analysis Group [London] (BioMedIA), Imperial College London-Imperial College London, Imaging and Biophysics Unit, University College of London [London] (UCL), Modelling brain structure, function and variability based on high-field MRI data (PARIETAL), 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-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, Service NEUROSPIN (NEUROSPIN), Computational, Cognitive and Clinical Neuroimaging Laboratory (C3NL), Imperial College London, The Computational, Cognitive and Clinical Neuroimaging Lab, 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), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)

Subjects
Computer science, structural brain connectivity, ACM: J.: Computer Applications/J.3: LIFE AND MEDICAL SCIENCES, Machine learning, computer.software_genre, functional brain connectivity, statistical associations, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, symbols.namesake, 0302 clinical medicine, Salience (neuroscience), medicine, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Graphical model, Electrical and Electronic Engineering, Gaussian process, Default mode network, Radiological and Ultrasound Technology, medicine.diagnostic_test, Artificial neural network, business.industry, Functional connectivity, [SCCO.NEUR]Cognitive science/Neuroscience, Computer Science Applications, symbols, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artificial intelligence, business, Functional magnetic resonance imaging, computer, predictive modeling, 030217 neurology & neurosurgery, Software
Abstract

Functional connections between brain regions are supported by structural connectivity. Both functional and structural connectivity are estimated from in vivo magnetic resonance imaging and offer complementary information on brain organization and function. However, imaging only provides noisy measures, and we lack a good neuroscientific understanding of the links between structure and function. Therefore, inter-subject joint modeling of structural and functional connectivity, the key to multimodal biomarkers, is an open challenge. We present a probabilistic framework to learn across subjects a mapping from structural to functional brain connectivity. Expanding on our previous work [1], our approach is based on a predictive framework with multiple sparse linear regression. We rely on the randomized LASSO to identify relevant anatomo-functional links with some confidence interval. In addition, we describe resting-state functional magnetic resonance imaging in the setting of Gaussian graphical models, on the one hand imposing conditional independences from structural connectivity and on the other hand parameterizing the problem in terms of multivariate autoregressive models. We introduce an intrinsic measure of prediction error for functional connectivity that is independent of the parameterization chosen and provides the means for robust model selection. We demonstrate our methodology with regions within the default mode and the salience network as well as, atlas-based cortical parcellation.

Published
2013
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3. A probabilistic framework to infer brain functional connectivity from anatomical connections

Author

Bertrand Thirion, Daniel Rueckert, Emma C. Robinson, Gaël Varoquaux, David J. Sharp, Fani Deligianni, A. David Edwards, Department of Computing [London], Biomedical Image Analysis Group [London] (BioMedIA), Imperial College London-Imperial College London, Laboratoire de Neuroimagerie Assistée par Ordinateur (LNAO), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Modelling brain structure, function and variability based on high-field MRI data (PARIETAL), 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-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, Neuroimagerie cognitive - Psychologie cognitive expérimentale (UNICOG-U992), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Saclay (COmUE)-Institut National de la Santé et de la Recherche Médicale (INSERM), The Computational, Cognitive and Clinical Neuroimaging Lab, Imperial College London, Institute of Clinical Sciences, Gábor Székely, Horst Hahn, 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)-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)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, and Varoquaux, Gaël

Subjects
Computer science, Brain activity and meditation, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, brain, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.5: Multivariate statistics, ACM: J.: Computer Applications/J.3: LIFE AND MEDICAL SCIENCES, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Linear prediction, Machine learning, computer.software_genre, Brain mapping, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, learning, Basis (linear algebra), business.industry, Model selection, functional connectivity, Function (mathematics), Covariance, anatomical connectivity, Conditional independence, Artificial intelligence, business, computer, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 030217 neurology & neurosurgery, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning
Abstract

International audience; We present a novel probabilistic framework to learn across several subjects a mapping from brain anatomical connectivity to functional connectivity, i.e. the covariance structure of brain activity. This prediction problem must be formulated as a structured-output learning task, as the predicted parameters are strongly correlated. We introduce a model selection framework based on cross-validation with a parametrization-independent loss function suitable to the manifold of covariance matrices. Our model is based on constraining the conditional independence structure of functional activity by the anatomical connectivity. Subsequently, we learn a linear predictor of a stationary multivariate autoregressive model. This natural parameterization of functional connectivity also enforces the positive-definiteness of the predicted covariance and thus matches the structure of the output space. Our results show that functional connectivity can be explained by anatomical connectivity on a rigorous statistical basis, and that a proper model of functional connectivity is essential to assess this link.

Published
2011
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4. Abnormal brain activation in excoriation (skin-picking) disorder: evidence from an executive planning fMRI study.

Author

Odlaug BL, Hampshire A, Chamberlain SR, and Grant JE

Subjects
Adolescent, Adult, Case-Control Studies, Disruptive, Impulse Control, and Conduct Disorders physiopathology, Executive Function, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Obsessive-Compulsive Disorder physiopathology, Self-Injurious Behavior psychology, Skin injuries, Young Adult, Corpus Striatum physiopathology, Frontal Lobe physiopathology, Gyrus Cinguli physiopathology, Neural Pathways physiopathology, Self-Injurious Behavior physiopathology
Abstract

Background: Excoriation (skin-picking) disorder (SPD) is a relatively common psychiatric condition whose neurobiological basis is unknown., Aims: To probe the function of fronto-striatal circuitry in SPD., Method: Eighteen participants with SPD and 15 matched healthy controls undertook an executive planning task (Tower of London) during functional magnetic resonance imaging (fMRI). Activation during planning was compared between groups using region of interest and whole-brain permutation cluster approaches., Results: The SPD group exhibited significant functional underactivation in a cluster encompassing bilateral dorsal striatum (maximal in right caudate), bilateral anterior cingulate and right medial frontal regions. These abnormalities were, for the most part, outside the dorsal planning network typically activated by executive planning tasks., Conclusions: Abnormalities of neural regions involved in habit formation, action monitoring and inhibition appear involved in the pathophysiology of SPD. Implications exist for understanding the basis of excessive grooming and the relationship of SPD with putative obsessive-compulsive spectrum disorders., (© The Royal College of Psychiatrists 2016.)

Published
2016
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