1
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Individual Brain Charting dataset extension, third release for movie watching and retinotopy data

      data-paper

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The Individual Brain Charting (IBC) is a multi-task functional Magnetic Resonance Imaging dataset acquired at high spatial-resolution and dedicated to the cognitive mapping of the human brain. It consists in the deep phenotyping of twelve individuals, covering a broad range of psychological domains suitable for functional-atlasing applications. Here, we present the inclusion of task data from both naturalistic stimuli and trial-based designs, to uncover structures of brain activation. We rely on the Fast Shared Response Model (FastSRM) to provide a data-driven solution for modelling naturalistic stimuli, typically containing many features. We show that data from left-out runs can be reconstructed using FastSRM, enabling the extraction of networks from the visual, auditory and language systems. We also present the topographic organization of the visual system through retinotopy. In total, six new tasks were added to IBC, wherein four trial-based retinotopic tasks contributed with a mapping of the visual field to the cortex. IBC is open access: source plus derivatives imaging data and meta-data are available in public repositories.

          Related collections

          Most cited references52

          • Record: found
          • Abstract: not found
          • Article: not found

          The assessment and analysis of handedness: The Edinburgh inventory

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Advances in functional and structural MR image analysis and implementation as FSL.

            The techniques available for the interrogation and analysis of neuroimaging data have a large influence in determining the flexibility, sensitivity, and scope of neuroimaging experiments. The development of such methodologies has allowed investigators to address scientific questions that could not previously be answered and, as such, has become an important research area in its own right. In this paper, we present a review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB). This research has focussed on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data. The majority of the research laid out in this paper has been implemented as freely available software tools within FMRIB's Software Library (FSL).
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.

              Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements. Copyright © 2011 Elsevier Inc. All rights reserved.
                Bookmark

                Author and article information

                Contributors
                agrilopi@uwo.ca , anagpinho@gmail.com
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                5 June 2024
                5 June 2024
                2024
                : 11
                : 590
                Affiliations
                [1 ]Université Paris-Saclay, Inria, CEA, ( https://ror.org/03xjwb503) Palaiseau, 91120 France
                [2 ]Department of Computer Science, Western University, ( https://ror.org/02grkyz14) London, Ontario Canada
                [3 ]Western Centre for Brain and Mind, Western University, ( https://ror.org/02grkyz14) London, Ontario Canada
                [4 ]Criteo AI Labs, Paris, France
                [5 ]FAIRPLAY - IA coopérative: équité, vie privée, incitations, Paris, France
                [6 ]Flatiron Institute, ( https://ror.org/00sekdz59) New York, USA
                [7 ]Université Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, ( https://ror.org/03xjwb503) 91191 Gif-sur-Yvette, France
                [8 ]Meta FAIR, Paris, France
                [9 ]GRID grid.460789.4, ISNI 0000 0004 4910 6535, Cognitive Neuroimaging Unit, INSERM, CEA, , Université Paris-Saclay, NeuroSpin center, ; 91191 Gif-sur-Yvette, France
                [10 ]Collège de France, ( https://ror.org/04ex24z53) Paris, France
                [11 ]GRID grid.5583.b, ISNI 0000 0001 2299 8025, CEA Saclay/DRF/IFJ/NeuroSpin/UNIACT, ; Paris, France
                [12 ]GRID grid.508487.6, ISNI 0000 0004 7885 7602, UMR 1141, NeuroDiderot, , Université de Paris, ; Paris, France
                Author information
                http://orcid.org/0000-0001-8718-0902
                http://orcid.org/0000-0002-2667-9387
                http://orcid.org/0000-0001-5018-7895
                Article
                3390
                10.1038/s41597-024-03390-1
                11153490
                38839770
                666f19f4-cf43-4ee3-9df3-f894530a2304
                © Crown 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 November 2023
                : 20 May 2024
                Funding
                Funded by: Human Brain Project SGA1: no. 720270 Human Brain Project SGA2: no. 785907 Human Brain Project SGA3: no. 945539
                Categories
                Data Descriptor
                Custom metadata
                © Springer Nature Limited 2024

                cognitive neuroscience,databases
                cognitive neuroscience, databases

                Comments

                Comment on this article