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      Decoding brain states on the intrinsic manifold of human brain dynamics across wakefulness and sleep

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          Abstract

          Current state-of-the-art functional magnetic resonance imaging (fMRI) offers remarkable imaging quality and resolution, yet, the intrinsic dimensionality of brain dynamics in different states (wakefulness, light and deep sleep) remains unknown. Here we present a method to reveal the low dimensional intrinsic manifold underlying human brain dynamics, which is invariant of the high dimensional spatio-temporal representation of the neuroimaging technology. By applying this intrinsic manifold framework to fMRI data acquired in wakefulness and sleep, we reveal the nonlinear differences between wakefulness and three different sleep stages, and successfully decode these different brain states with a mean accuracy across participants of 96%. Remarkably, a further group analysis shows that the intrinsic manifolds of all participants share a common topology. Overall, our results reveal the intrinsic manifold underlying the spatiotemporal dynamics of brain activity and demonstrate how this manifold enables the decoding of different brain states such as wakefulness and various sleep stages.

          Abstract

          Rué-Queralt et al. present a method for calculating low dimensional manifolds in functional magnetic resonance imaging data and use it across human sleep-wake cycles. Their results indicate that non-REM sleep states occupy distinct areas of this intrinsic manifold and can be used to differentiate stages of sleep and waking.

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          Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.

          An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute (MNI) (D. L. Collins et al., 1998, Trans. Med. Imag. 17, 463-468) was performed. The MNI single-subject main sulci were first delineated and further used as landmarks for the 3D definition of 45 anatomical volumes of interest (AVOI) in each hemisphere. This procedure was performed using a dedicated software which allowed a 3D following of the sulci course on the edited brain. Regions of interest were then drawn manually with the same software every 2 mm on the axial slices of the high-resolution MNI single subject. The 90 AVOI were reconstructed and assigned a label. Using this parcellation method, three procedures to perform the automated anatomical labeling of functional studies are proposed: (1) labeling of an extremum defined by a set of coordinates, (2) percentage of voxels belonging to each of the AVOI intersected by a sphere centered by a set of coordinates, and (3) percentage of voxels belonging to each of the AVOI intersected by an activated cluster. An interface with the Statistical Parametric Mapping package (SPM, J. Ashburner and K. J. Friston, 1999, Hum. Brain Mapp. 7, 254-266) is provided as a freeware to researchers of the neuroimaging community. We believe that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain in which deformations are well known. However, this tool does not alleviate the need for more sophisticated labeling strategies based on anatomical or cytoarchitectonic probabilistic maps.
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            Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

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              Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.

              The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. In this Article we review recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity. Although several challenges remain, these studies have provided insight into the intrinsic functional architecture of the brain, variability in behaviour and potential physiological correlates of neurological and psychiatric disease.
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                Author and article information

                Contributors
                joan.rue.q@gmail.com
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                9 July 2021
                9 July 2021
                2021
                : 4
                : 854
                Affiliations
                [1 ]GRID grid.5612.0, ISNI 0000 0001 2172 2676, Center of Brain and Cognition, , Universitat Pompeu Fabra, ; Barcelona, Spain
                [2 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Centre for Eudaimonia and Human Flourishing, , University of Oxford, ; Oxford, UK
                [3 ]GRID grid.7048.b, ISNI 0000 0001 1956 2722, Center for Music in the Brain, , Aarhus University, ; Aarhus, Denmark
                [4 ]GRID grid.7345.5, ISNI 0000 0001 0056 1981, Instituto de Física de Buenos Aires and Physics Deparment (University of Buenos Aires), ; Buenos Aires, Argentina
                [5 ]GRID grid.7839.5, ISNI 0000 0004 1936 9721, Department of Neurology and Brain Imaging Center, , Goethe University, ; Frankfurt am Main, Germany
                [6 ]GRID grid.9764.c, ISNI 0000 0001 2153 9986, Department of Neurology, University Hospital Schleswig-Holstein, , Christian-Albrechts-University, ; Kiel, Germany
                [7 ]GRID grid.425902.8, ISNI 0000 0000 9601 989X, Institució Catalana de Recerca i Estudis Avancats (ICREA), ; Barcelona, Spain
                [8 ]GRID grid.419524.f, ISNI 0000 0001 0041 5028, Department of Neuropsychology, , Max Planck Institute for Human Cognitive and Brain Sciences, ; Leipzig, Germany
                [9 ]GRID grid.1002.3, ISNI 0000 0004 1936 7857, School of Psychological Sciences, , Monash University, ; Melbourne, Australia
                Author information
                http://orcid.org/0000-0002-9595-4557
                http://orcid.org/0000-0002-3908-6898
                http://orcid.org/0000-0002-8995-7583
                Article
                2369
                10.1038/s42003-021-02369-7
                8270946
                34244598
                b695b710-8f9a-45c0-bad1-a1dc28e6c079
                © The Author(s) 2021

                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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 26 June 2020
                : 18 June 2021
                Funding
                Funded by: Fundació Catalunya La Pedrera - Masters of excellence Fellowship
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                network models,consciousness,dynamical systems
                network models, consciousness, dynamical systems

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