Dynamics analysis of neural univariate time series by recurrence plots
Identifieur interne : 000030 ( Pmc/Corpus ); précédent : 000029; suivant : 000031Dynamics analysis of neural univariate time series by recurrence plots
Auteurs : Tamara Toši ; Peter Beim Graben ; Kristin K. Sellers ; Flavio Fröhlich ; Axel HuttSource :
- BMC Neuroscience [ 1471-2202 ] ; 2015.
Url:
DOI: 10.1186/1471-2202-16-S1-P105
PubMed: NONE
PubMed Central: 4697542
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Dynamics analysis of neural univariate time series by recurrence plots</title><author><name sortKey="Tosi, Tamara" sort="Tosi, Tamara" uniqKey="Tosi T" first="Tamara" last="Toši">Tamara Toši</name><affiliation><nlm:aff id="I1">Inria, CNRS, Loria, UMR nº 7503, Vandœuvre-lès-Nancy, F-54500, France</nlm:aff></affiliation></author><author><name sortKey="Graben, Peter Beim" sort="Graben, Peter Beim" uniqKey="Graben P" first="Peter Beim" last="Graben">Peter Beim Graben</name><affiliation><nlm:aff id="I2">Institute of German Studies and Linguistics, Humboldt-University, 10178, Berlin, Germany</nlm:aff></affiliation><affiliation><nlm:aff id="I3">Bernstein Center for Computational Neuroscience, 10178, Berlin, Germany</nlm:aff></affiliation></author><author><name sortKey="Sellers, Kristin K" sort="Sellers, Kristin K" uniqKey="Sellers K" first="Kristin K" last="Sellers">Kristin K. Sellers</name><affiliation><nlm:aff id="I4">University of North Carolina at Chapel Hill, Chapel Hill, 27599, NC, USA</nlm:aff></affiliation></author><author><name sortKey="Frohlich, Flavio" sort="Frohlich, Flavio" uniqKey="Frohlich F" first="Flavio" last="Fröhlich">Flavio Fröhlich</name><affiliation><nlm:aff id="I4">University of North Carolina at Chapel Hill, Chapel Hill, 27599, NC, USA</nlm:aff></affiliation></author><author><name sortKey="Hutt, Axel" sort="Hutt, Axel" uniqKey="Hutt A" first="Axel" last="Hutt">Axel Hutt</name><affiliation><nlm:aff id="I1">Inria, CNRS, Loria, UMR nº 7503, Vandœuvre-lès-Nancy, F-54500, France</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmc">4697542</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4697542</idno><idno type="RBID">PMC:4697542</idno><idno type="doi">10.1186/1471-2202-16-S1-P105</idno><idno type="pmid">NONE</idno><date when="2015">2015</date><idno type="wicri:Area/Pmc/Corpus">000030</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000030</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Dynamics analysis of neural univariate time series by recurrence plots</title><author><name sortKey="Tosi, Tamara" sort="Tosi, Tamara" uniqKey="Tosi T" first="Tamara" last="Toši">Tamara Toši</name><affiliation><nlm:aff id="I1">Inria, CNRS, Loria, UMR nº 7503, Vandœuvre-lès-Nancy, F-54500, France</nlm:aff></affiliation></author><author><name sortKey="Graben, Peter Beim" sort="Graben, Peter Beim" uniqKey="Graben P" first="Peter Beim" last="Graben">Peter Beim Graben</name><affiliation><nlm:aff id="I2">Institute of German Studies and Linguistics, Humboldt-University, 10178, Berlin, Germany</nlm:aff></affiliation><affiliation><nlm:aff id="I3">Bernstein Center for Computational Neuroscience, 10178, Berlin, Germany</nlm:aff></affiliation></author><author><name sortKey="Sellers, Kristin K" sort="Sellers, Kristin K" uniqKey="Sellers K" first="Kristin K" last="Sellers">Kristin K. Sellers</name><affiliation><nlm:aff id="I4">University of North Carolina at Chapel Hill, Chapel Hill, 27599, NC, USA</nlm:aff></affiliation></author><author><name sortKey="Frohlich, Flavio" sort="Frohlich, Flavio" uniqKey="Frohlich F" first="Flavio" last="Fröhlich">Flavio Fröhlich</name><affiliation><nlm:aff id="I4">University of North Carolina at Chapel Hill, Chapel Hill, 27599, NC, USA</nlm:aff></affiliation></author><author><name sortKey="Hutt, Axel" sort="Hutt, Axel" uniqKey="Hutt A" first="Axel" last="Hutt">Axel Hutt</name><affiliation><nlm:aff id="I1">Inria, CNRS, Loria, UMR nº 7503, Vandœuvre-lès-Nancy, F-54500, France</nlm:aff></affiliation></author></analytic><series><title level="j">BMC Neuroscience</title><idno type="eISSN">1471-2202</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Beim Graben, P" uniqKey="Beim Graben P">P beim Graben</name></author><author><name sortKey="Hutt, A" uniqKey="Hutt A">A Hutt</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Marvan, N" uniqKey="Marvan N">N Marvan</name></author><author><name sortKey="Romano, Mc" uniqKey="Romano M">MC Romano</name></author><author><name sortKey="Thiel, M" uniqKey="Thiel M">M Thiel</name></author><author><name sortKey="Kurths, J" uniqKey="Kurths J">J Kurths</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sellers, Kk" uniqKey="Sellers K">KK Sellers</name></author><author><name sortKey="Bennett, Dv" uniqKey="Bennett D">DV Bennett</name></author><author><name sortKey="Frohlich, F" uniqKey="Frohlich F">F Frohlich</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="abstract" xml:lang="en"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Neurosci</journal-id><journal-id journal-id-type="iso-abbrev">BMC Neurosci</journal-id><journal-title-group><journal-title>BMC Neuroscience</journal-title></journal-title-group><issn pub-type="epub">1471-2202</issn><publisher><publisher-name>BioMed Central</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmc">4697542</article-id><article-id pub-id-type="publisher-id">1471-2202-16-S1-P105</article-id><article-id pub-id-type="doi">10.1186/1471-2202-16-S1-P105</article-id><article-categories><subj-group subj-group-type="heading"><subject>Poster Presentation</subject></subj-group></article-categories><title-group><article-title>Dynamics analysis of neural univariate time series by recurrence plots</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="A1"><name><surname>Tošić</surname><given-names>Tamara</given-names></name><xref ref-type="aff" rid="I1">1</xref><email>tamara.tosic@inria.fr</email></contrib><contrib contrib-type="author" id="A2"><name><surname>Graben</surname><given-names>Peter beim</given-names></name><xref ref-type="aff" rid="I2">2</xref><xref ref-type="aff" rid="I3">3</xref></contrib><contrib contrib-type="author" id="A3"><name><surname>Sellers</surname><given-names>Kristin K</given-names></name><xref ref-type="aff" rid="I4">4</xref></contrib><contrib contrib-type="author" id="A4"><name><surname>Fröhlich</surname><given-names>Flavio</given-names></name><xref ref-type="aff" rid="I4">4</xref></contrib><contrib contrib-type="author" id="A5"><name><surname>Hutt</surname><given-names>Axel</given-names></name><xref ref-type="aff" rid="I1">1</xref></contrib></contrib-group><aff id="I1"><label>1</label>Inria, CNRS, Loria, UMR nº 7503, Vandœuvre-lès-Nancy, F-54500, France</aff><aff id="I2"><label>2</label>Institute of German Studies and Linguistics, Humboldt-University, 10178, Berlin, Germany</aff><aff id="I3"><label>3</label>Bernstein Center for Computational Neuroscience, 10178, Berlin, Germany</aff><aff id="I4"><label>4</label>University of North Carolina at Chapel Hill, Chapel Hill, 27599, NC, USA</aff><pub-date pub-type="collection"><year>2015</year></pub-date><pub-date pub-type="epub"><day>18</day><month>12</month><year>2015</year></pub-date><volume>16</volume><issue>Suppl 1</issue><supplement><named-content content-type="supplement-title">24th Annual Computational Neuroscience Meeting: CNS*2015</named-content><named-content content-type="supplement-editor">Gennady Cymbalyuk and Anthony Burkitt</named-content><named-content content-type="supplement-sponsor">The publication charges for this supplement were funded by the Organization for Computational Neurosciences. The Supplement Editors declare that they have no competing interests.</named-content></supplement><fpage>P105</fpage><lpage>P105</lpage><permissions><copyright-statement>Copyright © 2015 Tošić et al.</copyright-statement><copyright-year>2015</copyright-year><copyright-holder>Tošić et al.</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0">http://creativecommons.org/licenses/by/4.0</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><self-uri xlink:href="http://www.biomedcentral.com/1471-2202/16/S1/P105"></self-uri><conference><conf-date>18-23 July 2015</conf-date><conf-name>24th Annual Computational Neuroscience Meeting: CNS*2015</conf-name><conf-loc>Prague, Czech Republic</conf-loc></conference></article-meta></front><body><sec><title></title><p>Transients in non-linear biological signals (e.g., population dynamics or physiological signals) encode an intrinsic behaviour of system dynamics. We study the problem of detecting dynamical transients given a set of signal trials. In general case, different biological signals emerge from different origins and hence exhibit distinct properties that are hard to grasp. For example, to analyze sleep recordings, one considers rhythms of the brain, the cardio-vascular and the respiratory systems. The synchronous analysis of the corresponding time series is an unsolved problem and extracting information from such signals and their trial statistics is challenging. In addition, measurement noise and time jitters between trials may corrupt signals. To attack this demanding problem, we start by a preliminary study of extracting features in multiple trials from univariate time series of the same origin, but without taking into account the common origin. The new method jointly analyzes neural signals by extracting statistical properties, obtained by exploiting the fundamental feature of dynamical systems, the recurrence structure.</p><p>Recurrences represent instances in time when the system's trajectory returns to a phase space neighborhood of a location it has visited previously, cf. [<xref ref-type="bibr" rid="B1">1</xref>]. Classical recurrence plots (RP) [<xref ref-type="bibr" rid="B2">2</xref>] represent symmetric binary valued matrices and characterise the system's phase space. Since neural recurrence patterns occur in particular frequency bands, we propose to build novel, frequency-selective recurrence plots from their time-frequency signal representations. To evaluate the recurrence results, we compute surrogate RPs by time randomisation of the original time-frequency representations. To obtain statistically significant recurrence information, statistics of the original RPs is pixel-wise compared with the surrogate dataset statistics. This novel inference test provides statistically significant pixel values and the corresponding recurrence structure. Results in Figure <xref ref-type="fig" rid="F1">1</xref> show an artificial and neural time series and corresponding statistically significant recurrence plots. One observes that the method extracts well several transient oscillations of different frequencies. The analysis of the ferrets data reveals that the first stimulation response at t = 0ms is recurrent to the second response one stimulation period later, while the third response at t = 3s is different from the first two. This result indicates temporal neural adaptation during the stimulation.</p><fig id="F1" position="float"><label>Figure 1</label><caption><p><bold>Detection of dynamical transients</bold>. (A) Superposition of several transient oscillations of different frequencies. (B) experimental Local Field Potentials measured in ferret visual cortex in the presence of a periodic 1Hz visual stimulus [<xref ref-type="bibr" rid="B3">3</xref>] starting at sample 0 with a period of 100 samples. Time series are given in left column. Statistically significant data (white values) of recurrence points are illustrated in right column figures (Chi-square test, p = 0.1).</p></caption><graphic xlink:href="1471-2202-16-S1-P105-1"></graphic></fig></sec></body><back><sec><title>Acknowledgements</title><p>Research reported in this publication was supported by (1) the LIRA, a research initiative of Fraunhofer Society, Philips and Inria (2) the National Institute Of Mental Health of the National Institutes of Health under Award Number R01MH101547. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.</p></sec><ref-list><ref id="B1"><mixed-citation publication-type="journal"><name><surname>beim Graben</surname><given-names>P</given-names></name><name><surname>Hutt</surname><given-names>A</given-names></name><article-title>Detecting recurrence domains of dynamical systems by symbolic dynamics</article-title><source>Physical Review Letters</source><year>2013</year><volume>110</volume><issue>15</issue><fpage>154101</fpage><pub-id pub-id-type="pmid">25167271</pub-id></mixed-citation></ref><ref id="B2"><mixed-citation publication-type="journal"><name><surname>Marvan</surname><given-names>N</given-names></name><name><surname>Romano</surname><given-names>MC</given-names></name><name><surname>Thiel</surname><given-names>M</given-names></name><name><surname>Kurths</surname><given-names>J</given-names></name><article-title>Recurrence plots for analysis of complex systems</article-title><source>Physiscs reports</source><year>2007</year><volume>438</volume><fpage>237</fpage><lpage>329</lpage></mixed-citation></ref><ref id="B3"><mixed-citation publication-type="journal"><name><surname>Sellers</surname><given-names>KK</given-names></name><name><surname>Bennett</surname><given-names>DV</given-names></name><name><surname>Frohlich</surname><given-names>F</given-names></name><article-title>Frequency-Band Signatures of Visual Responses to Naturalistic Input in Ferret Primary Visual Cortex during Free Viewing</article-title><source>Brain Research</source><year>2015</year><volume>1598</volume><fpage>31</fpage><lpage>45</lpage><pub-id pub-id-type="pmid">25498982</pub-id></mixed-citation></ref></ref-list></back></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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