The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core.
Identifieur interne : 000B14 ( PubMed/Corpus ); précédent : 000B13; suivant : 000B15The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core.
Auteurs : Gustavo Deco ; Morten L. Kringelbach ; Viktor K. Jirsa ; Petra RitterSource :
- Scientific reports [ 2045-2322 ] ; 2017.
Abstract
In the human brain, spontaneous activity during resting state consists of rapid transitions between functional network states over time but the underlying mechanisms are not understood. We use connectome based computational brain network modeling to reveal fundamental principles of how the human brain generates large-scale activity observable by noninvasive neuroimaging. We used structural and functional neuroimaging data to construct whole- brain models. With this novel approach, we reveal that the human brain during resting state operates at maximum metastability, i.e. in a state of maximum network switching. In addition, we investigate cortical heterogeneity across areas. Optimization of the spectral characteristics of each local brain region revealed the dynamical cortical core of the human brain, which is driving the activity of the rest of the whole brain. Brain network modelling goes beyond correlational neuroimaging analysis and reveals non-trivial network mechanisms underlying non-invasive observations. Our novel findings significantly pertain to the important role of computational connectomics in understanding principles of brain function.
DOI: 10.1038/s41598-017-03073-5
PubMed: 28596608
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pubmed:28596608Le document en format XML
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<author><name sortKey="Kringelbach, Morten L" sort="Kringelbach, Morten L" uniqKey="Kringelbach M" first="Morten L" last="Kringelbach">Morten L. Kringelbach</name>
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<front><div type="abstract" xml:lang="en">In the human brain, spontaneous activity during resting state consists of rapid transitions between functional network states over time but the underlying mechanisms are not understood. We use connectome based computational brain network modeling to reveal fundamental principles of how the human brain generates large-scale activity observable by noninvasive neuroimaging. We used structural and functional neuroimaging data to construct whole- brain models. With this novel approach, we reveal that the human brain during resting state operates at maximum metastability, i.e. in a state of maximum network switching. In addition, we investigate cortical heterogeneity across areas. Optimization of the spectral characteristics of each local brain region revealed the dynamical cortical core of the human brain, which is driving the activity of the rest of the whole brain. Brain network modelling goes beyond correlational neuroimaging analysis and reveals non-trivial network mechanisms underlying non-invasive observations. Our novel findings significantly pertain to the important role of computational connectomics in understanding principles of brain function.</div>
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<Abstract><AbstractText>In the human brain, spontaneous activity during resting state consists of rapid transitions between functional network states over time but the underlying mechanisms are not understood. We use connectome based computational brain network modeling to reveal fundamental principles of how the human brain generates large-scale activity observable by noninvasive neuroimaging. We used structural and functional neuroimaging data to construct whole- brain models. With this novel approach, we reveal that the human brain during resting state operates at maximum metastability, i.e. in a state of maximum network switching. In addition, we investigate cortical heterogeneity across areas. Optimization of the spectral characteristics of each local brain region revealed the dynamical cortical core of the human brain, which is driving the activity of the rest of the whole brain. Brain network modelling goes beyond correlational neuroimaging analysis and reveals non-trivial network mechanisms underlying non-invasive observations. Our novel findings significantly pertain to the important role of computational connectomics in understanding principles of brain function.</AbstractText>
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<AffiliationInfo><Affiliation>Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, 08010, Spain.</Affiliation>
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<AffiliationInfo><Affiliation>Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany.</Affiliation>
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<AffiliationInfo><Affiliation>School of Psychological Sciences, Monash University, Melbourne, Clayton VIC 3800, Australia.</Affiliation>
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<AffiliationInfo><Affiliation>Department of Psychiatry, University of Oxford, Oxford, UK. morten.kringelbach@psych.ox.ac.uk.</Affiliation>
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<AffiliationInfo><Affiliation>Center of Music in the Brain (MIB), Clinical Medicine, Aarhus University, Aarhus C, DK, Denmark. morten.kringelbach@psych.ox.ac.uk.</Affiliation>
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<CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Neuroimage. 2015 Jan 15;105:525-35</RefSource>
<PMID Version="1">25462790</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neurosci Biobehav Rev. 2006;30(6):823-38</RefSource>
<PMID Version="1">16911826</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Nat Rev Neurosci. 2001 Apr;2(4):229-39</RefSource>
<PMID Version="1">11283746</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuropsychologia. 2007 Apr 8;45(7):1363-77</RefSource>
<PMID Version="1">17126370</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Chaos. 2012 Dec;22(4):043131</RefSource>
<PMID Version="1">23278066</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Science. 1988 Dec 23;242(4886):1654-64</RefSource>
<PMID Version="1">3059497</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>PLoS Comput Biol. 2015 Feb 18;11(2):e1004100</RefSource>
<PMID Version="1">25692996</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Trends Cogn Sci. 2015 Oct;19(10):616-28</RefSource>
<PMID Version="1">26412099</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Nat Commun. 2016 Jul 18;7:12141</RefSource>
<PMID Version="1">27424918</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Trends Neurosci. 2013 May;36(5):268-74</RefSource>
<PMID Version="1">23561718</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuron. 2013 Feb 6;77(3):586-95</RefSource>
<PMID Version="1">23395382</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Prog Neurobiol. 2014 Mar;114:102-31</RefSource>
<PMID Version="1">24389385</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Philos Trans R Soc Lond B Biol Sci. 2000 Feb 29;355(1394):215-36</RefSource>
<PMID Version="1">10724457</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>JAMA Psychiatry. 2015 Apr;72(4):305-15</RefSource>
<PMID Version="1">25651064</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuroimage. 2004 Nov;23(3):1176-85</RefSource>
<PMID Version="1">15528117</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Cogn Neurodyn. 2008 Jun;2(2):115-20</RefSource>
<PMID Version="1">19003478</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 2006 Sep 12;103(37):13848-53</RefSource>
<PMID Version="1">16945915</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuron. 2014 Dec 3;84(5):892-905</RefSource>
<PMID Version="1">25475184</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Brain Connect. 2013;3(2):121-45</RefSource>
<PMID Version="1">23442172</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuroimage. 2011 Jul 1;57(1):130-9</RefSource>
<PMID Version="1">21511044</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Brain Connect. 2012;2(2):91-101</RefSource>
<PMID Version="1">22559794</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Neurosci. 2006 Jan 4;26(1):63-72</RefSource>
<PMID Version="1">16399673</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuroimage. 2006 Jul 1;31(3):968-80</RefSource>
<PMID Version="1">16530430</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Neurosci. 2012 Mar 7;32(10):3366-75</RefSource>
<PMID Version="1">22399758</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Front Neuroinform. 2013 Jun 11;7:10</RefSource>
<PMID Version="1">23781198</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Science. 1974 Sep 27;185(4157):1124-31</RefSource>
<PMID Version="1">17835457</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuroimage. 2015 Aug 15;117:343-57</RefSource>
<PMID Version="1">25837600</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Nat Rev Neurosci. 2015 Jul;16(7):430-9</RefSource>
<PMID Version="1">26081790</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuroimage. 2014 Apr 15;90:423-35</RefSource>
<PMID Version="1">24321555</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>PLoS Comput Biol. 2011 Sep;7(9):e1002198</RefSource>
<PMID Version="1">21980278</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuron. 2015 May 6;86(3):646-64</RefSource>
<PMID Version="1">25950633</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Elife. 2014 Mar 25;3:e01867</RefSource>
<PMID Version="1">24668169</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuron. 2014 Jan 8;81(1):35-48</RefSource>
<PMID Version="1">24411730</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Behav Brain Sci. 2000 Oct;23(5):645-65; discussion 665-726</RefSource>
<PMID Version="1">11301544</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Nat Rev Neurosci. 2001 Oct;2(10 ):685-94</RefSource>
<PMID Version="1">11584306</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>PLoS Comput Biol. 2012;8(8):e1002634</RefSource>
<PMID Version="1">22912567</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Neurosci. 2013 Jul 3;33(27):11239-52</RefSource>
<PMID Version="1">23825427</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Psychol Rev. 2014 Jul;121(3):302-36</RefSource>
<PMID Version="1">25090422</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Neurosci. 2011 Apr 27;31(17 ):6353-61</RefSource>
<PMID Version="1">21525275</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Phys Rev Lett. 1990 Oct 1;65(14):1701-1704</RefSource>
<PMID Version="1">10042341</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Science. 2008 Jul 4;321(5885):48-50</RefSource>
<PMID Version="1">18599763</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 2003 Jan 7;100(1):253-8</RefSource>
<PMID Version="1">12506194</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Proc Natl Acad Sci U S A. 2009 Jun 23;106(25):10302-7</RefSource>
<PMID Version="1">19497858</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Nat Neurosci. 2017 Feb 23;20(3):340-352</RefSource>
<PMID Version="1">28230845</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Nature. 1999 Nov 11;402(6758):179-81</RefSource>
<PMID Version="1">10647008</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>PLoS Comput Biol. 2008 May 02;4(5):e1000072</RefSource>
<PMID Version="1">18452000</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Neuron. 2015 Oct 21;88(2):419-31</RefSource>
<PMID Version="1">26439530</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>PLoS Comput Biol. 2008 Oct;4(10):e1000196</RefSource>
<PMID Version="1">18846206</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Philos Trans R Soc Lond B Biol Sci. 2009 May 12;364(1521):1211-21</RefSource>
<PMID Version="1">19528002</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>J Neurosci. 2009 Feb 11;29(6):1860-73</RefSource>
<PMID Version="1">19211893</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Philos Trans R Soc Lond B Biol Sci. 2005 May 29;360(1457):1001-13</RefSource>
<PMID Version="1">16087444</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Nat Rev Neurosci. 2011 Jan;12(1):43-56</RefSource>
<PMID Version="1">21170073</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Cereb Cortex. 2014 Mar;24(3):663-76</RefSource>
<PMID Version="1">23146964</PMID>
</CommentsCorrections>
<CommentsCorrections RefType="Cites"><RefSource>Magn Reson Med. 1995 Oct;34(4):537-41</RefSource>
<PMID Version="1">8524021</PMID>
</CommentsCorrections>
</CommentsCorrectionsList>
</MedlineCitation>
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