Linear and Nonlinear Measures and Seizure Anticipation in Temporal Lobe Epilepsy
dc.contributor.author | Li, Dingzhou | en_US |
dc.contributor.author | Zhou, Weiping | en_US |
dc.contributor.author | Drury, Ivo | en_US |
dc.contributor.author | Savit, Robert S. | en_US |
dc.date.accessioned | 2006-09-11T17:37:28Z | |
dc.date.available | 2006-09-11T17:37:28Z | |
dc.date.issued | 2003-11 | en_US |
dc.identifier.citation | Li, Dingzhou; Zhou, Weiping; Drury, Ivo; Savit, Robert; (2003). "Linear and Nonlinear Measures and Seizure Anticipation in Temporal Lobe Epilepsy." Journal of Computational Neuroscience 15(3): 335-345. <http://hdl.handle.net/2027.42/46310> | en_US |
dc.identifier.issn | 0929-5313 | en_US |
dc.identifier.issn | 1573-6873 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/46310 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=14618068&dopt=citation | en_US |
dc.description.abstract | In a recent paper, we showed that the value of a nonlinear quantity computed from scalp electrode data was correlated with the time to a seizure in patients with temporal lobe epilepsy. In this paper we study the relationship between the linear and nonlinear content and analyses of the scalp data. We do this in two ways. First, using surrogate data methods, we show that there is important nonlinear structure in the scalp electrode data to which our methods are sensitive. Second, we study the behavior of some simple linear metrics on the same set of scalp data to see whether the nonlinear metrics contain additional information not carried by the linear measures. We find that, while the nonlinear measures are correlated with time to seizure, the linear measures are not, over the time scales we have defined. The linear and nonlinear measures are themselves apparently linearly correlated, but that correlation can be ascribed to the influence of a small set of outliers, associated with muscle artifact. A remaining, more subtle relation between the variance of the values of a nonlinear measure and the expectation value of a linear measure persists. Implications of our observations are discussed. | en_US |
dc.format.extent | 89817 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Biomedicine | en_US |
dc.subject.other | Human Genetics | en_US |
dc.subject.other | Neurosciences | en_US |
dc.subject.other | Neurology | en_US |
dc.subject.other | Theory of Computation | en_US |
dc.subject.other | Seizure Anticipation | en_US |
dc.subject.other | Temporal Lobe Epilepsy | en_US |
dc.title | Linear and Nonlinear Measures and Seizure Anticipation in Temporal Lobe Epilepsy | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Neurosciences | en_US |
dc.subject.hlbsecondlevel | Internal Medicine and Specialties | en_US |
dc.subject.hlbsecondlevel | Psychology | en_US |
dc.subject.hlbsecondlevel | Biological Chemistry | en_US |
dc.subject.hlbsecondlevel | Molecular, Cellular and Developmental Biology | en_US |
dc.subject.hlbsecondlevel | Public Health | en_US |
dc.subject.hlbtoplevel | Social Sciences | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Physics Department, University of Michigan, Ann Arbor, MI, USA | en_US |
dc.contributor.affiliationum | Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA | en_US |
dc.contributor.affiliationum | Michigan Center for Theoretical Physics, University of Michigan, Ann Arbor, MI, USA; Physics Department, University of Michigan, Ann Arbor, MI, USA; Center for the Study of Complex Systems and Biophysics Research Division, University of Michigan, Ann Arbor, MI, USA | en_US |
dc.contributor.affiliationother | Department of Neurology, Henry Ford Health System, Detroit, MI, USA | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.identifier.pmid | 14618068 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/46310/1/10827_2004_Article_5252207.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/A:1027415927155 | en_US |
dc.identifier.source | Journal of Computational Neuroscience | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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