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DC Field | Value | Language |
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dc.contributor | Sistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP | - |
dc.contributor.author | TAKAHASHI, Daniel Y. | - |
dc.contributor.author | BACCALA, Luiz A. | - |
dc.contributor.author | SAMESHIMA, Koichi | - |
dc.date.accessioned | 2015-07-01T20:19:25Z | - |
dc.date.available | 2015-07-01T20:19:25Z | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | FRONTIERS IN NEUROINFORMATICS, v.8, article ID 49, 11p, 2014 | - |
dc.identifier.issn | 1662-5196 | - |
dc.identifier.uri | https://observatorio.fm.usp.br/handle/OPI/9327 | - |
dc.description.abstract | Partial directed coherence (PDC) and directed coherence (DC) which describe complementary aspects of the directed information flow between pairs of univariate components that belong to a vector of simultaneously observed time series have recently been generalized as bPDC/bDC, respectively, to portray the relationship between subsets of component vectors (Takahashi, 2009; Fees and Nollo, 2013). This generalization is specially important for neuroscience applications as one often wishes to address the link between the set of time series from an observed ROI (region of interest) with respect to series from some other physiologically relevant ROI. bPDC/bDC are limited, however, in that several time series within a given subset may be irrelevant or may even interact opposingly with respect to one another leading to interpretation difficulties. To address this, we propose an alternative measure, termed cPDC/cDC, employing canonical decomposition to reveal the main frequency domain modes of interaction between the vector subsets. We also show bPDC/bDC and cPDC/cDC are related and possess mutual information rate interpretations. Numerical examples and a real data set illustrate the concepts. The present contribution provides what is seemingly the first canonical decomposition of information flow in the frequency domain. | - |
dc.description.sponsorship | CNPq [307163/2013-0, 309381/2012-6] | - |
dc.description.sponsorship | FAPESP [2005/56464- 9] | - |
dc.description.sponsorship | Pew Latin American Fellowship | - |
dc.description.sponsorship | Ciencia sem Fronteiras Fellowship-CNPq grant [246778/2012-1] | - |
dc.language.iso | eng | - |
dc.publisher | FRONTIERS RESEARCH FOUNDATION | - |
dc.relation.ispartof | Frontiers in Neuroinformatics | - |
dc.rights | openAccess | - |
dc.subject | directed connectivity measures | - |
dc.subject | canonical decomposition | - |
dc.subject | frequency domain | - |
dc.subject | information flow | - |
dc.subject | generalized coherence | - |
dc.subject.other | granger causality | - |
dc.subject.other | connectivity | - |
dc.subject.other | regions | - |
dc.title | Canonical information flow decomposition among neural structure subsets | - |
dc.type | article | - |
dc.rights.holder | Copyright FRONTIERS RESEARCH FOUNDATION | - |
dc.identifier.doi | 10.3389/fninf.2014.00049 | - |
dc.identifier.pmid | 24910609 | - |
dc.subject.wos | Mathematical & Computational Biology | - |
dc.subject.wos | Neurosciences | - |
dc.type.category | original article | - |
dc.type.version | publishedVersion | - |
hcfmusp.author.external | TAKAHASHI, Daniel Y.:Princeton Univ, Inst Neurosci, Dept Psychol, Princeton, NJ 08544 USA | - |
hcfmusp.author.external | BACCALA, Luiz A.:Univ Sao Paulo, Escola Politecn, Telecommun & Control Dept, BR-05508900 Sao Paulo, Brazil | - |
hcfmusp.description.articlenumber | 49 | - |
hcfmusp.description.volume | 8 | - |
hcfmusp.origem | WOS | - |
hcfmusp.origem.id | 2-s2.0-84901823188 | - |
hcfmusp.origem.id | WOS:000348112200001 | - |
hcfmusp.publisher.city | LAUSANNE | - |
hcfmusp.publisher.country | SWITZERLAND | - |
hcfmusp.relation.reference | Ashrafulla S, 2013, NEUROIMAGE, V83, P189, DOI 10.1016/j.neuroimage.2013.06.056 | - |
hcfmusp.relation.reference | Baccala L. A., 2014, METHODS BRAIN CONNEC, P245, DOI [10.1201/b16550-18, DOI 10.1201/B16550-18] | - |
hcfmusp.relation.reference | Baccala LA, 2001, BIOL CYBERN, V84, P463, DOI 10.1007/PL00007990 | - |
hcfmusp.relation.reference | Brillinger D. R., 1981, TIME SERIES DATA ANA, V36 | - |
hcfmusp.relation.reference | Faes L, 2013, BIOL CYBERN, V107, P217, DOI 10.1007/s00422-013-0547-5 | - |
hcfmusp.relation.reference | Gelfand I. M., 1959, AM MATH SOC TRANSL S, V2, P3 | - |
hcfmusp.relation.reference | Hannan E. J., 1970, MULTIPLE TIME SERIES, DOI [10.1002/9780470316429, DOI 10.1002/9780470316429] | - |
hcfmusp.relation.reference | Hotelling H, 1936, BIOMETRIKA, V28, P321, DOI 10.2307/2333955 | - |
hcfmusp.relation.reference | KAMINSKI MJ, 1991, BIOL CYBERN, V65, P203, DOI 10.1007/BF00198091 | - |
hcfmusp.relation.reference | Lutkepohl H., 1996, HDB MATRICES | - |
hcfmusp.relation.reference | Nedungadi AG, 2011, BIOL CYBERN, V104, P197, DOI 10.1007/s00422-011-0429-7 | - |
hcfmusp.relation.reference | Pinsker M. S., 1964, INFORM INFORM STABIL | - |
hcfmusp.relation.reference | Sameshima K., 2014, METHODS BRAIN CONNEC, P113, DOI [10.1201/bl6550-9, DOI 10.1201/B16550-9] | - |
hcfmusp.relation.reference | Sato JR, 2010, NEUROIMAGE, V52, P1444, DOI 10.1016/j.neuroimage.2010.05.022 | - |
hcfmusp.relation.reference | Takahashi D. Y., 2009, THESIS U SAO PAULO | - |
hcfmusp.relation.reference | Takahashi DY, 2010, BIOL CYBERN, V103, P463, DOI 10.1007/s00422-010-0410-x | - |
hcfmusp.relation.reference | Wu GR, 2011, IEEE T BIO-MED ENG, V58, P3088, DOI 10.1109/TBME.2011.2162669 | - |
dc.description.index | PubMed | - |
hcfmusp.citation.scopus | 6 | - |
hcfmusp.scopus.lastupdate | 2024-03-28 | - |
Appears in Collections: | Artigos e Materiais de Revistas Científicas - FM/MDR Artigos e Materiais de Revistas Científicas - LIM/43 |
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art_TAKAHASHI_Canonical_information_flow_decomposition_among_neural_structure_subsets_2014.PDF | publishedVersion (English) | 1.1 MB | Adobe PDF | View/Open |
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