Journal Article

FZJ-2020-04130

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Individual Brain Charting dataset extension, second release of high-resolution fMRI data for cognitive mapping

Pinho, A. L. (Corresponding author) ; Amadon, A. ; Gauthier, B. ; Clairis, N. ; Knops, A. ; Genon, S.FZJ* ; Dohmatob, E. ; Torre, J. J. ; Ginisty, C. ; Becuwe-Desmidt, S. ; Roger, S. ; Lecomte, Y. ; Berland, V. ; Laurier, L. ; Joly-Testault, V. ; Médiouni-Cloarec, G. ; Doublé, C. ; Martins, B. ; Salmon, E. ; Piazza, M. ; Melcher, D. ; Pessiglione, M. ; van Wassenhove, V. ; Eger, E. ; Varoquaux, G. ; Dehaene, S. ; Hertz-Pannier, L. ; Thirion, B.

2020
figshare London

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Please use a persistent id in citations: http://hdl.handle.net/2128/25973  doi:10.1038/s41597-020-00670-4  doi:10.6084/M9.FIGSHARE.12958181

Abstract: <div>This dataset contains key characteristics about the data described in the Data Descriptor Individual Brain Charting dataset extension, second release of high-resolution fMRI data for cognitive mapping.</div> <br> <div>Contents: </div> <br> <div> 1. human readable metadata summary table in CSV format </div> <div> 2. machine readable metadata file in JSON format </div> <br> <br> <div><br></div>We present an extension of the Individual Brain Charting dataset –a high spatial-resolution, multitask,functional Magnetic Resonance Imaging dataset, intended to support the investigation on thefunctional principles governing cognition in the human brain. The concomitant data acquisition fromthe same 12 participants, in the same environment, allows to obtain in the long run finer cognitivetopographies, free from inter-subject and inter-site variability. This second release provides more datafrom psychological domains present in the first release, and also yields data featuring new ones. Itincludes tasks on e.g. mental time travel, reward, theory-of-mind, pain, numerosity, self-referenceeffect and speech recognition. In total, 13 tasks with 86 contrasts were added to the dataset and 63new components were included in the cognitive description of the ensuing contrasts. As the datasetbecomes larger, the collection of the corresponding topographies becomes more comprehensive,leading to better brain-atlasing frameworks. This dataset is an open-access facility; raw data andderivatives are publicly available in neuroimaging repositories.Background & SummaryUnderstanding the fundamental principles that govern human cognition requires mapping the brain in terms offunctional segregation of specialized regions. This is achieved by measuring local differences of brain activationrelated to behavior. Functional Magnetic Resonance Imaging (fMRI) has been used for this purpose as an attemptto better understand the neural correlates underlying cognition. However, while there is a rich literature concerningperformance of isolated tasks, little is still known about the overall functional organization of the brain.Meta- and mega-analyses constitute active efforts at providing accumulated knowledge on brain systems,wherein data from different studies are pooled to map regions consistently linked to mental functions1–9 Because1Université Paris-Saclay, Inria, CEA, Palaiseau, 91120, France. 2Université Paris-Saclay, CEA, CNRS, BAOBAB,NeuroSpin, 91191, Gif-sur-Yvette, France. 3Cognitive Neuroimaging Unit, INSERM, CEA, Université Paris-Saclay,NeuroSpin center, 91191, Gif/Yvette, France. 4Laboratory of Cognitive Neuroscience, Brain Mind Institute, School ofLife Sciences and Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Campus Biotech, Geneva,Switzerland. 5Motivation, Brain and Behavior (MBB) team, Institut du Cerveau (ICM), Inserm UMRS 1127, CNS UMR7225, Sorbonne Université, Paris, France. 6Center for Mind/Brain Sciences, University of Trento, I-38068, Rovereto,Italy. 7LaPsyDÉ, UMR CNRS 8240, Université de Paris, Paris, France. 8GIGA-CRC In vivo Imaging, University of Liège,Liège, Belgium. 9Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7) Research Centre Jülich, Jülich,Germany. 10Criteo AI Lab, Paris, France. 11Université Paris-Saclay, CEA, UNIACT, NeuroSpin, 91191 Gif-sur-Yvette,France. 12Collège de France, Université Paris-Sciences-Lettres, Paris, France. 13UMR 1141, NeuroDiderot, Universitéde Paris, Paris, France. ✉e-mail: ana.pinho@inria.frData Descrip torOPENScientific Data | (2020) 7:353 | https://doi.org/10.1038/s41597-020-00670-4 2www.nature.com/scientificdata/ www.nature.com/scientificdatadata are impacted by both intra- and inter-subject plus inter-site variability, these approaches still limit the exactdemarcation of functional territories and, consequently, formal generalizations about brain mechanisms. Severallarge-scale brain-imaging datasets are suitable for atlasing, wherein differences can be mitigated across subjectsand protocols together with standardized data-processing routines. Yet, as they have different scopes, notall requirements are met for cognitive mapping. For instance, the Human Connectome Project (HCP)10,11 andCONNECT/Archi12,13 datasets provide large subject samples as they are focused in population analysis across differentmodalities; task-fMRI data combine here 24 and 28 conditions, respectively, which is scarce for functionalatlasing. Another example is the studyforrest dataset14–17, that includes a variety of task data on complex auditoryand visual information, but restricted to naturalistic stimuli. Additionally, one shall note that within-subject variabilityreduces task-fMRI replicability; thus, more data per subject can in fact facilitate reliability of group-levelresults18.To obtain as many cognitive signatures as possible and simultaneously achieve a wide brain coverage at a finescale, extensive functional mapping of individual brains over different psychological domains is necessary. Withinthis context, the Individual Brain Charting (IBC) project pertains to the development of a 1.5mm-resolution,task-fMRI dataset acquired in a fixed environment, on a permanent cohort of 12 participants. Data collectionfrom a broad range of tasks, at high spatial resolution, yields a sharp characterization of the neurocognitive componentscommon to the different tasks. This extension corresponds to the second release of the IBC dataset,meant to increase the number of psychological domains of the first one19. It both aims at a consistent mapping ofelementary spatial components, extracted from all tasks, and a fine characterization of the individual architectureunderlying this topographic information.The first release encompassed a sample of modules ranging from perception to higher-level cognition, e.g.retinotopy, calculation, language and social reasoning10,12,20. The second release refers to tasks predominantlyfocused on higher-level functions, like mental time travel, reward, theory-of-mind, self-reference effect andspeech recognition. Nonetheless, a subset dedicated to lower-level processes is also included, covering pain,action perception and numerosity. These tasks are intended to complement those from the first release, such thata considerable cognitive overlap is attained, while new components are introduced. For instance, componentsconcerning social cognition, already found in ARCHI Standard, ARCHI Social and HCP Social tasks from theprevious release, are now present in tasks about theory-of-mind and self-reference effect. Likewise, componentson incentive salience, already tackled in the HCP Gambling task, are now included in a task battery addressingpositive-incentive value. Yet also, a battery on mental time travel brings in new modules pertaining to timeorientation and cardinal-direction judgment. Data from both releases are organized in 25 tasks –most of themreproduced from other studies– and they amount for 205 contrasts described on the basis of 110 cognitive atoms,extracted from the Cognitive Atlas21.Here, we give an account –focused on the second release– of the experimental procedures and the datasetorganization and show that raw task-fMRI data and their derivatives represent functional activity in directresponse to behavior. Data collection is ongoing and more releases are planned for the next years. Despite beinga long-term project, IBC is not dedicated to longitudinal surveys; acquisitions of the same tasks will not be conductedsystematically.The IBC dataset is an open-access facility devoted to providing high-resolution, functional maps of individualbrains as basis to support investigations in human cognition.MethodsTo avoid ambiguity with MRI-related terms used throughout this manuscript, definitions of such terms follow theBrain-Imaging-Data-Structure (BIDS) Specification version 1.2.122.Complementary information about dataset organization and MRI-acquisition protocols can be found in theIBC documentation available online: https://project.inria.fr/IBC/data/

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Contributing Institute(s):

1. Gehirn & Verhalten (INM-7)

Research Program(s):

1. 571 - Connectivity and Activity (POF3-571) (POF3-571)

Appears in the scientific report 2020

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