@article{RN194,
   author = {Gupta, L. and Jansen, J. F. A. and Hofman, P. A. M. and Besseling, R. M. H. and de Louw, A. J. A. and Aldenkamp, A. P. and Backes, W. H.},
   title = {Wavelet entropy of BOLD time series: An application to Rolandic epilepsy},
   journal = {J Magn Reson Imaging},
   volume = {46},
   number = {6},
   pages = {1728-1737},
   note = {Gupta, Lalit
Jansen, Jacobus F A
Hofman, Paul A M
Besseling, Rene M H
de Louw, Anton J A
Aldenkamp, Albert P
Backes, Walter H
eng
2017/03/16 06:00
J Magn Reson Imaging. 2017 Dec;46(6):1728-1737. doi: 10.1002/jmri.25700. Epub 2017 Mar 11.},
   abstract = {PURPOSE: To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. MATERIALS AND METHODS: The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated. Using a model time series consisting of multiple harmonics and nonstationary components, the wavelet entropy was compared with Shannon and spectral (Fourier-based) entropy. As an application, the wavelet entropy in 22 children with Rolandic epilepsy was compared to 22 age-matched healthy controls. The images were obtained by performing resting-state functional magnetic resonance imaging (fMRI) using a 3T system, an 8-element receive-only head coil, and an echo planar imaging pulse sequence ( T2*-weighted). The wavelet entropy was also compared to spectral entropy, regional homogeneity, and Shannon entropy. RESULTS: Wavelet entropy was found to identify the nonstationary components of the model time series. In Rolandic epilepsy patients, a significantly elevated wavelet entropy was observed relative to controls for the whole cerebrum (P = 0.03). Spectral entropy (P = 0.41), regional homogeneity (P = 0.52), and Shannon entropy (P = 0.32) did not reveal significant differences. CONCLUSION: The wavelet entropy measure appeared more sensitive to detect abnormalities in cerebral fluctuations represented by nonstationary effects in the BOLD time series than more conventional measures. This effect was observed in the model time series as well as in Rolandic epilepsy. These observations suggest that the brains of children with Rolandic epilepsy exhibit stronger nonstationary temporal signal fluctuations than controls. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1728-1737.},
   keywords = {Brain/*diagnostic imaging/*physiopathology
Brain Mapping/*methods
Child
Entropy
Epilepsy, Rolandic/*diagnostic imaging/*physiopathology
Female
Humans
Magnetic Resonance Imaging/*methods
*BOLD time series
*Rolandic epilepsy
*discrete wavelet transform
*frequency structure
*wavelet entropy},
   ISSN = {1522-2586 (Electronic)
1053-1807 (Linking)},
   DOI = {10.1002/jmri.25700},
   url = {http://www.ncbi.nlm.nih.gov/pubmed/28295824
https://onlinelibrary.wiley.com/doi/abs/10.1002/jmri.25700},
   year = {2017},
   type = {Journal Article}
}

{"_id":"qQgKYriniXkegs5JT","bibbaseid":"gupta-jansen-hofman-besseling-delouw-aldenkamp-backes-waveletentropyofboldtimeseriesanapplicationtorolandicepilepsy-2017","downloads":0,"creationDate":"2017-09-02T16:45:18.629Z","title":"Wavelet entropy of BOLD time series: An application to Rolandic epilepsy","author_short":["Gupta, L.","Jansen, J. F. A.","Hofman, P. A. M.","Besseling, R. M. H.","de Louw, A. J. A.","Aldenkamp, A. P.","Backes, W. H."],"year":2017,"bibtype":"article","biburl":"https://raw.githubusercontent.com/jansenjfa1/bibbase.github.io/master/jansenjfa.bib","bibdata":{"bibtype":"article","type":"Journal Article","author":[{"propositions":[],"lastnames":["Gupta"],"firstnames":["L."],"suffixes":[]},{"propositions":[],"lastnames":["Jansen"],"firstnames":["J.","F.","A."],"suffixes":[]},{"propositions":[],"lastnames":["Hofman"],"firstnames":["P.","A.","M."],"suffixes":[]},{"propositions":[],"lastnames":["Besseling"],"firstnames":["R.","M.","H."],"suffixes":[]},{"propositions":["de"],"lastnames":["Louw"],"firstnames":["A.","J.","A."],"suffixes":[]},{"propositions":[],"lastnames":["Aldenkamp"],"firstnames":["A.","P."],"suffixes":[]},{"propositions":[],"lastnames":["Backes"],"firstnames":["W.","H."],"suffixes":[]}],"title":"Wavelet entropy of BOLD time series: An application to Rolandic epilepsy","journal":"J Magn Reson Imaging","volume":"46","number":"6","pages":"1728-1737","note":"Gupta, Lalit Jansen, Jacobus F A Hofman, Paul A M Besseling, Rene M H de Louw, Anton J A Aldenkamp, Albert P Backes, Walter H eng 2017/03/16 06:00 J Magn Reson Imaging. 2017 Dec;46(6):1728-1737. doi: 10.1002/jmri.25700. Epub 2017 Mar 11.","abstract":"PURPOSE: To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. MATERIALS AND METHODS: The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated. Using a model time series consisting of multiple harmonics and nonstationary components, the wavelet entropy was compared with Shannon and spectral (Fourier-based) entropy. As an application, the wavelet entropy in 22 children with Rolandic epilepsy was compared to 22 age-matched healthy controls. The images were obtained by performing resting-state functional magnetic resonance imaging (fMRI) using a 3T system, an 8-element receive-only head coil, and an echo planar imaging pulse sequence ( T2*-weighted). The wavelet entropy was also compared to spectral entropy, regional homogeneity, and Shannon entropy. RESULTS: Wavelet entropy was found to identify the nonstationary components of the model time series. In Rolandic epilepsy patients, a significantly elevated wavelet entropy was observed relative to controls for the whole cerebrum (P = 0.03). Spectral entropy (P = 0.41), regional homogeneity (P = 0.52), and Shannon entropy (P = 0.32) did not reveal significant differences. CONCLUSION: The wavelet entropy measure appeared more sensitive to detect abnormalities in cerebral fluctuations represented by nonstationary effects in the BOLD time series than more conventional measures. This effect was observed in the model time series as well as in Rolandic epilepsy. These observations suggest that the brains of children with Rolandic epilepsy exhibit stronger nonstationary temporal signal fluctuations than controls. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1728-1737.","keywords":"Brain/*diagnostic imaging/*physiopathology Brain Mapping/*methods Child Entropy Epilepsy, Rolandic/*diagnostic imaging/*physiopathology Female Humans Magnetic Resonance Imaging/*methods *BOLD time series *Rolandic epilepsy *discrete wavelet transform *frequency structure *wavelet entropy","issn":"1522-2586 (Electronic) 1053-1807 (Linking)","doi":"10.1002/jmri.25700","url":"http://www.ncbi.nlm.nih.gov/pubmed/28295824 https://onlinelibrary.wiley.com/doi/abs/10.1002/jmri.25700","year":"2017","bibtex":"@article{RN194,\n author = {Gupta, L. and Jansen, J. F. A. and Hofman, P. A. M. and Besseling, R. M. H. and de Louw, A. J. A. and Aldenkamp, A. P. and Backes, W. H.},\n title = {Wavelet entropy of BOLD time series: An application to Rolandic epilepsy},\n journal = {J Magn Reson Imaging},\n volume = {46},\n number = {6},\n pages = {1728-1737},\n note = {Gupta, Lalit\nJansen, Jacobus F A\nHofman, Paul A M\nBesseling, Rene M H\nde Louw, Anton J A\nAldenkamp, Albert P\nBackes, Walter H\neng\n2017/03/16 06:00\nJ Magn Reson Imaging. 2017 Dec;46(6):1728-1737. doi: 10.1002/jmri.25700. Epub 2017 Mar 11.},\n abstract = {PURPOSE: To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. MATERIALS AND METHODS: The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated. Using a model time series consisting of multiple harmonics and nonstationary components, the wavelet entropy was compared with Shannon and spectral (Fourier-based) entropy. As an application, the wavelet entropy in 22 children with Rolandic epilepsy was compared to 22 age-matched healthy controls. The images were obtained by performing resting-state functional magnetic resonance imaging (fMRI) using a 3T system, an 8-element receive-only head coil, and an echo planar imaging pulse sequence ( T2*-weighted). The wavelet entropy was also compared to spectral entropy, regional homogeneity, and Shannon entropy. RESULTS: Wavelet entropy was found to identify the nonstationary components of the model time series. In Rolandic epilepsy patients, a significantly elevated wavelet entropy was observed relative to controls for the whole cerebrum (P = 0.03). Spectral entropy (P = 0.41), regional homogeneity (P = 0.52), and Shannon entropy (P = 0.32) did not reveal significant differences. CONCLUSION: The wavelet entropy measure appeared more sensitive to detect abnormalities in cerebral fluctuations represented by nonstationary effects in the BOLD time series than more conventional measures. This effect was observed in the model time series as well as in Rolandic epilepsy. These observations suggest that the brains of children with Rolandic epilepsy exhibit stronger nonstationary temporal signal fluctuations than controls. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. 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