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      The organizational principles of de-differentiated topographic maps in somatosensory cortex

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          Abstract

          Topographic maps are a fundamental feature of cortex architecture in the mammalian brain. One common theory is that the de-differentiation of topographic maps links to impairments in everyday behavior due to less precise functional map readouts. Here, we tested this theory by characterizing de-differentiated topographic maps in primary somatosensory cortex (SI) of younger and older adults by means of ultra-high resolution functional magnetic resonance imaging together with perceptual finger individuation and hand motor performance. Older adults’ SI maps showed similar amplitude and size to younger adults’ maps, but presented with less representational similarity between distant fingers. Larger population receptive field sizes in older adults’ maps did not correlate with behavior, whereas reduced cortical distances between D2 and D3 related to worse finger individuation but better motor performance. Our data uncover the drawbacks of a simple de-differentiation model of topographic map function, and motivate the introduction of feature-based models of cortical reorganization.

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          The assessment and analysis of handedness: The Edinburgh inventory

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            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).
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              Cortical surface-based analysis. I. Segmentation and surface reconstruction.

              Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging. Copyright 1999 Academic Press.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                18 May 2021
                2021
                : 10
                : e60090
                Affiliations
                [1 ]Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg MagdeburgGermany
                [2 ]German Center for Neurodegenerative Diseases (DZNE) MagdeburgGermany
                [3 ]Vision and Computational Cognition Group, Max Planck Institute for Human Cognitive and Brain Sciences LeipzigGermany
                [4 ]Center for Behavioral Brain Sciences (CBBS) Magdeburg MagdeburgGermany
                University College London United Kingdom
                Radboud University Netherlands
                University College London United Kingdom
                CHUV Switzerland
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0001-7257-428X
                https://orcid.org/0000-0003-3169-1951
                Article
                60090
                10.7554/eLife.60090
                8186903
                34003108
                54ea966d-94c6-469c-b5be-52f16c1335de
                © 2021, Liu et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 16 June 2020
                : 17 May 2021
                Funding
                Funded by: Center for Behavioral Brain Sciences;
                Award ID: ESIF/EFRE 2014-2020 FKZ: ZS/2016/04/78113
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, German Research Foundation;
                Award ID: KU 3711/2-1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, German Research Foundation;
                Award ID: project number: 423633679
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003042, Else Kröner-Fresenius-Stiftung;
                Award ID: 2019-A03
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Neuroscience
                Custom metadata
                SI topographic finger maps of older adults show signs of cortical aging but do not show classical hallmarks of cortical de-differentiation.

                Life sciences
                aging,prf mapping,7 tesla mri,somatosensation,somatotopy,touch,human
                Life sciences
                aging, prf mapping, 7 tesla mri, somatosensation, somatotopy, touch, human

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