Differentiating resting brain states using ordinal symbolic analysis

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  • dc.contributor.author Quintero-Quiroz, Carlos
  • dc.contributor.author Montesano, Luis
  • dc.contributor.author Pons, Antonio J.
  • dc.contributor.author Torrent, Maria Carme
  • dc.contributor.author García Ojalvo, Jordi
  • dc.contributor.author Masoller, Cristina
  • dc.date.accessioned 2019-05-15T07:54:23Z
  • dc.date.available 2019-05-15T07:54:23Z
  • dc.date.issued 2018
  • dc.description.abstract Symbolic methods of analysis are valuable tools for investigating complex time-dependent signals. In particular, the ordinal method defines sequences of symbols according to the ordering in which values appear in a time series. This method has been shown to yield useful information, even when applied to signals with large noise contamination. Here, we use ordinal analysis to investigate the transition between eyes closed (EC) and eyes open (EO) resting states. We analyze two electroencephalography datasets (with 71 and 109 healthy subjects) with different recording conditions (sampling rates and the number of electrodes in the scalp). Using as diagnostic tools the permutation entropy, the entropy computed from symbolic transition probabilities, and an asymmetry coefficient (that measures the asymmetry of the likelihood of the transitions between symbols), we show that the ordinal analysis applied to the raw data distinguishes the two brain states. In both datasets, we find that, during the EC-EO transition, the EO state is characterized by higher entropies and lower asymmetry coefficient, as compared to the EC state. Our results thus show that these diagnostic tools have the potential for detecting and characterizing changes in time-evolving brain states.
  • dc.description.sponsorship This work was supported in part by ITN NETT (FP7 289146), the Spanish MINECO (FIS2015-66503 and FIS2015-66503-C3-2-P), and the program ICREA ACADEMIA of Generalitat de Catalunya.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Quintero-Quiroz C, Montesano L, Pons AJ, Torrent MC, García-Ojalvo J, Masoller C. Differentiating resting brain states using ordinal symbolic analysis. Chaos. 2018;28(10):106307. DOI: 10.1063/1.5036959
  • dc.identifier.doi http://dx.doi.org/10.1063/1.5036959
  • dc.identifier.issn 1054-1500
  • dc.identifier.uri http://hdl.handle.net/10230/37230
  • dc.language.iso eng
  • dc.publisher American Institute of Physics (AIP)
  • dc.relation.ispartof Chaos. 2018;28(10):106307
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/289146
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/FIS2015-66503
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/FIS2015-66503-C3-2-P
  • dc.rights © American Institute of Physics. The following article appeared in Quintero-Quiroz C, Montesano L, Pons AJ, Torrent MC, García-Ojalvo J, Masoller C. Chaos. 28(10), 2018 and may be found at https://aip.scitation.org/doi/10.1063/1.5036959
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.title Differentiating resting brain states using ordinal symbolic analysis
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/acceptedVersion

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