메뉴 건너뛰기




Volumn 245, Issue , 2015, Pages 73-90

Causal inference in neuronal time-series using adaptive decomposition

Author keywords

Directed functional connectivity; Empirical mode decomposition; Granger causality; Time series analysis; Time frequency analysis

Indexed keywords

ADAPTIVE DECOMPOSITION; ALGORITHM; ARTICLE; CAUSAL ANALYSIS; CAUSAL MODELING; DATA ANALYSIS; EMPIRICAL MODE DECOMPOSITION; GRANGER CAUSALITY; NEUROSCIENCE; NOISE; NONHUMAN; PRIORITY JOURNAL; RAT; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; SIMULATION; TIME SERIES ANALYSIS; ANIMAL; ARTIFICIAL NEURAL NETWORK; BRAIN; COMPUTER SIMULATION; ELECTROENCEPHALOGRAM; ELECTROENCEPHALOGRAPHY; FOURIER ANALYSIS; HUMAN; MULTIVARIATE ANALYSIS; PHYSIOLOGY; TIME;

EID: 84924972117     PISSN: 01650270     EISSN: 1872678X     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2015.02.013     Document Type: Article
Times cited : (2)

References (80)
  • 1
    • 84908691492 scopus 로고    scopus 로고
    • Synchrosqueezing-based time-frequency analysis of multivariate data
    • Ahrabian A., Looney D., Stanković L., Mandic D.P. Synchrosqueezing-based time-frequency analysis of multivariate data. Signal Process 2015, 106:331-341. 10.1016/j.sigpro.2014.08.010.
    • (2015) Signal Process , vol.106 , pp. 331-341
    • Ahrabian, A.1    Looney, D.2    Stanković, L.3    Mandic, D.P.4
  • 2
    • 84873458594 scopus 로고    scopus 로고
    • Bivariate empirical mode decomposition for unbalanced real-world signals
    • Ahrabian A., Rehman N.U., Mandic D. Bivariate empirical mode decomposition for unbalanced real-world signals. IEEE Signal Process Lett 2013, 20:245-248.
    • (2013) IEEE Signal Process Lett , vol.20 , pp. 245-248
    • Ahrabian, A.1    Rehman, N.U.2    Mandic, D.3
  • 3
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • Akaike H. A new look at the statistical model identification. IEEE Trans Autom Control 1974, 19:716-723. 10.1109/TAC.1974.1100705.
    • (1974) IEEE Trans Autom Control , vol.19 , pp. 716-723
    • Akaike, H.1
  • 5
    • 39749120932 scopus 로고    scopus 로고
    • Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators
    • Astolfi L., Cincotti F., Mattia D., De Vico Fallani F., Tocci A., Colosimo A., et al. Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators. IEEE Trans Biomed Eng 2008, 55:902-913. 10.1109/TBME.2007.905419.
    • (2008) IEEE Trans Biomed Eng , vol.55 , pp. 902-913
    • Astolfi, L.1    Cincotti, F.2    Mattia, D.3    De Vico Fallani, F.4    Tocci, A.5    Colosimo, A.6
  • 6
    • 0035377249 scopus 로고    scopus 로고
    • Partial directed coherence: a new concept in neural structure determination
    • Baccalá L.a, Sameshima K. Partial directed coherence: a new concept in neural structure determination. Biol Cybern 2001, 84:463-474.
    • (2001) Biol Cybern , vol.84 , pp. 463-474
    • Baccalá, L.1    Sameshima, K.2
  • 8
    • 84889444756 scopus 로고    scopus 로고
    • Computer intensive testing for the influence between time series
    • Wiley-VCH Verlag GmbH & Co. KGaA
    • Baccalá L., Takahashi D., Sameshima K. Computer intensive testing for the influence between time series. Handbook of time series analysis 2006, 411-436. Wiley-VCH Verlag GmbH & Co. KGaA.
    • (2006) Handbook of time series analysis , pp. 411-436
    • Baccalá, L.1    Takahashi, D.2    Sameshima, K.3
  • 9
    • 71549116419 scopus 로고    scopus 로고
    • Granger causality and transfer entropy are equivalent for Gaussian variables
    • Barnett L. Granger causality and transfer entropy are equivalent for Gaussian variables. Phys Rev Lett 2009, 103:238701. 10.1103/PhysRevLett.103.238701.
    • (2009) Phys Rev Lett , vol.103 , pp. 238701
    • Barnett, L.1
  • 10
    • 80053212789 scopus 로고    scopus 로고
    • Behaviour of Granger causality under filtering: theoretical invariance and practical application
    • Barnett L., Seth A.K. Behaviour of Granger causality under filtering: theoretical invariance and practical application. J Neurosci Methods 2011, 201:404-419. 10.1016/j.jneumeth.2011.08.010.
    • (2011) J Neurosci Methods , vol.201 , pp. 404-419
    • Barnett, L.1    Seth, A.K.2
  • 11
    • 84890962645 scopus 로고    scopus 로고
    • The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference
    • Barnett L., Seth A.K. The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference. J Neurosci Methods 2014, 223:50-68. 10.1016/j.jneumeth.2013.10.018.
    • (2014) J Neurosci Methods , vol.223 , pp. 50-68
    • Barnett, L.1    Seth, A.K.2
  • 12
    • 84938451367 scopus 로고
    • A product theorem for Hilbert transforms
    • Bedrosian E. A product theorem for Hilbert transforms. Proc IEEE 1963, 51:868-869.
    • (1963) Proc IEEE , vol.51 , pp. 868-869
    • Bedrosian, E.1
  • 13
    • 79956204167 scopus 로고    scopus 로고
    • Role of local network oscillations in resting-state functional connectivity
    • Cabral J., Hugues E., Sporns O., Deco G. Role of local network oscillations in resting-state functional connectivity. Neuroimage 2011, 57:130-139. 10.1016/j.neuroimage.2011.04.010.
    • (2011) Neuroimage , vol.57 , pp. 130-139
    • Cabral, J.1    Hugues, E.2    Sporns, O.3    Deco, G.4
  • 14
    • 31344435870 scopus 로고    scopus 로고
    • Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data
    • Chen Y., Bressler S.L., Ding M. Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data. J Neurosci Methods 2006, 150:228-237. 10.1016/j.jneumeth.2005.06.011.
    • (2006) J Neurosci Methods , vol.150 , pp. 228-237
    • Chen, Y.1    Bressler, S.L.2    Ding, M.3
  • 15
    • 78751584911 scopus 로고    scopus 로고
    • Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool
    • Daubechies I., Lu J., Wu H.-T. Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool. Appl Comput Harmon Anal 2011, 30:243-261. 10.1016/j.acha.2010.08.002.
    • (2011) Appl Comput Harmon Anal , vol.30 , pp. 243-261
    • Daubechies, I.1    Lu, J.2    Wu, H.-T.3
  • 16
    • 85130292704 scopus 로고    scopus 로고
    • A nonlinear squeezing of the continuous wavelet transform based on auditory nerve models
    • CRC Press, M.U. Aldroubi (Ed.)
    • Daubechies I., Maes S. A nonlinear squeezing of the continuous wavelet transform based on auditory nerve models. Wavelets in medicine and biology 1996, 527-546. CRC Press. M.U. Aldroubi (Ed.).
    • (1996) Wavelets in medicine and biology , pp. 527-546
    • Daubechies, I.1    Maes, S.2
  • 17
    • 44149095492 scopus 로고    scopus 로고
    • Analyzing information flow in brain networks with nonparametric Granger causality
    • Dhamala M., Rangarajan G., Ding M. Analyzing information flow in brain networks with nonparametric Granger causality. Neuroimage 2008, 41:354-362. 10.1016/j.neuroimage.2008.02.020.
    • (2008) Neuroimage , vol.41 , pp. 354-362
    • Dhamala, M.1    Rangarajan, G.2    Ding, M.3
  • 18
    • 0034220863 scopus 로고    scopus 로고
    • Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment
    • Ding M., Bressler S.L., Yang W., Liang H. Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment. Biol Cybern 2000, 83:35-45.
    • (2000) Biol Cybern , vol.83 , pp. 35-45
    • Ding, M.1    Bressler, S.L.2    Yang, W.3    Liang, H.4
  • 19
    • 1842761446 scopus 로고    scopus 로고
    • Rain gauge derived precipitation variability over Virginia and its relation with the El Nino southern oscillation
    • EL-Askary H., Sarkar S., Chiu L., Kafatos M., El-Ghazawi T. Rain gauge derived precipitation variability over Virginia and its relation with the El Nino southern oscillation. Adv Space Res 2004, 33:338-342. 10.1016/S0273-1177(03)00478-2.
    • (2004) Adv Space Res , vol.33 , pp. 338-342
    • El-Askary, H.1    Sarkar, S.2    Chiu, L.3    Kafatos, M.4    El-Ghazawi, T.5
  • 20
    • 0442326792 scopus 로고    scopus 로고
    • Empirical mode decomposition as a filter bank
    • Flandrin P. Empirical mode decomposition as a filter bank. IEEE Signal Process Lett 2004, 11:112-114.
    • (2004) IEEE Signal Process Lett , vol.11 , pp. 112-114
    • Flandrin, P.1
  • 21
    • 77952297676 scopus 로고    scopus 로고
    • The effect of filtering on Granger causality based multivariate causality measures
    • Florin E., Gross J., Pfeifer J., Fink G.R., Timmermann L. The effect of filtering on Granger causality based multivariate causality measures. Neuroimage 2010, 50:577-588. 10.1016/j.neuroimage.2009.12.050.
    • (2010) Neuroimage , vol.50 , pp. 577-588
    • Florin, E.1    Gross, J.2    Pfeifer, J.3    Fink, G.R.4    Timmermann, L.5
  • 22
    • 84894912254 scopus 로고
    • Measurement of linear dependence and feedback between multiple time series
    • Geweke J. Measurement of linear dependence and feedback between multiple time series. J Am Stat Assoc 1982, 77:304-313.
    • (1982) J Am Stat Assoc , vol.77 , pp. 304-313
    • Geweke, J.1
  • 23
    • 84950949120 scopus 로고
    • Measures of conditional linear dependence and feedback between time series
    • Geweke J.F. Measures of conditional linear dependence and feedback between time series. J Am Stat Assoc 1984, 79:907-915. 10.2307/2288723.
    • (1984) J Am Stat Assoc , vol.79 , pp. 907-915
    • Geweke, J.F.1
  • 25
    • 0000351727 scopus 로고
    • Investigating causal relations by econometric models and cross-spectral methods
    • Granger C.W.J. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 1969, 37:424-438. 10.2307/1912791.
    • (1969) Econometrica , vol.37 , pp. 424-438
    • Granger, C.W.J.1
  • 26
    • 77955306267 scopus 로고    scopus 로고
    • Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data
    • Havlicek M., Jan J., Brazdil M., Calhoun V.D. Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data. Neuroimage 2010, 53:65-77. 10.1016/j.neuroimage.2010.05.063.
    • (2010) Neuroimage , vol.53 , pp. 65-77
    • Havlicek, M.1    Jan, J.2    Brazdil, M.3    Calhoun, V.D.4
  • 27
    • 81355149839 scopus 로고    scopus 로고
    • Intrinsic mode entropy based on multivariate empirical mode decomposition and its application to neural data analysis
    • Hu M., Liang H. Intrinsic mode entropy based on multivariate empirical mode decomposition and its application to neural data analysis. Cogn Neurodyn 2011, 5:277-284. 10.1007/s11571-011-9159-8.
    • (2011) Cogn Neurodyn , vol.5 , pp. 277-284
    • Hu, M.1    Liang, H.2
  • 28
    • 84555197047 scopus 로고    scopus 로고
    • Adaptive multiscale entropy analysis of multivariate neural data
    • Hu M., Liang H. Adaptive multiscale entropy analysis of multivariate neural data. IEEE Trans Biomed Eng 2012, 59:12-15. 10.1109/TBME.2011.2162511.
    • (2012) IEEE Trans Biomed Eng , vol.59 , pp. 12-15
    • Hu, M.1    Liang, H.2
  • 29
    • 84903289020 scopus 로고    scopus 로고
    • Search for information-bearing components in neural data
    • Hu M., Liang H. Search for information-bearing components in neural data. PLOS ONE 2014, 9:e99793. 10.1371/journal.pone.0099793.
    • (2014) PLOS ONE , vol.9 , pp. e99793
    • Hu, M.1    Liang, H.2
  • 30
    • 84868201484 scopus 로고    scopus 로고
    • An optimization based empirical mode decomposition scheme
    • Huang B., Kunoth A. An optimization based empirical mode decomposition scheme. J Comput Appl Math 2013, 240:174-183. 10.1016/j.cam.2012.07.012.
    • (2013) J Comput Appl Math , vol.240 , pp. 174-183
    • Huang, B.1    Kunoth, A.2
  • 31
    • 5444236478 scopus 로고    scopus 로고
    • The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
    • Huang N.E., Shen Z., Long S.R., Wu M.C., Shih H.H., Zheng Q., et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc A Math Phys Eng Sci 1998, 454:903-995. 10.1098/rspa.1998.0193.
    • (1998) Proc R Soc A Math Phys Eng Sci , vol.454 , pp. 903-995
    • Huang, N.E.1    Shen, Z.2    Long, S.R.3    Wu, M.C.4    Shih, H.H.5    Zheng, Q.6
  • 32
    • 0142227017 scopus 로고    scopus 로고
    • Applications of Hilbert-Huang transform to non-stationary financial time series analysis
    • Huang N.E., Wu M.-L., Qu W., Long S.R., Shen S.S.P. Applications of Hilbert-Huang transform to non-stationary financial time series analysis. Appl Stoch Model Bus Ind 2003, 19:245-268. 10.1002/asmb.501.
    • (2003) Appl Stoch Model Bus Ind , vol.19 , pp. 245-268
    • Huang, N.E.1    Wu, M.-L.2    Qu, W.3    Long, S.R.4    Shen, S.S.P.5
  • 34
    • 54949146599 scopus 로고    scopus 로고
    • A review on Hilbert-Huang transform: method and its applications to geophysical studies
    • Huang N.E., Wu Z. A review on Hilbert-Huang transform: method and its applications to geophysical studies. Rev Geophys 2008, 46:1-23. 10.1029/2007RG000228.
    • (2008) Rev Geophys , vol.46 , pp. 1-23
    • Huang, N.E.1    Wu, Z.2
  • 36
    • 0035433274 scopus 로고    scopus 로고
    • Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance
    • Kamiński M., Ding M., Truccolo W.a., Bressler S.L. Evaluating causal relations in neural systems: Granger causality, directed transfer function and statistical assessment of significance. Biol Cybern 2001, 85:145-157. 10.1007/s004220000235.
    • (2001) Biol Cybern , vol.85 , pp. 145-157
    • Kamiński, M.1    Ding, M.2    Truccolo, W.3    Bressler, S.L.4
  • 38
    • 20644453750 scopus 로고    scopus 로고
    • Empirical mode decomposition of field potentials from macaque V4 in visual spatial attention
    • Liang H., Bressler S.L., Buffalo E.a, Desimone R., Fries P. Empirical mode decomposition of field potentials from macaque V4 in visual spatial attention. Biol Cybern 2005, 92:380-392. 10.1007/s00422-005-0566-y.
    • (2005) Biol Cybern , vol.92 , pp. 380-392
    • Liang, H.1    Bressler, S.L.2    Buffalo, E.3    Desimone, R.4    Fries, P.5
  • 39
    • 81255172245 scopus 로고    scopus 로고
    • TRENTOOL: a Matlab open source toolbox to analyse information flow in time series data with transfer entropy
    • Lindner M., Vicente R., Priesemann V., Wibral M. TRENTOOL: a Matlab open source toolbox to analyse information flow in time series data with transfer entropy. BMC Neurosci 2011, 12:119. 10.1186/1471-2202-12-119.
    • (2011) BMC Neurosci , vol.12 , pp. 119
    • Lindner, M.1    Vicente, R.2    Priesemann, V.3    Wibral, M.4
  • 40
    • 79952283352 scopus 로고    scopus 로고
    • Multivariate information-theoretic measures reveal directed information structure and task relevant changes in fMRI connectivity
    • Lizier J.T., Heinzle J., Horstmann A., Haynes J.-D., Prokopenko M. Multivariate information-theoretic measures reveal directed information structure and task relevant changes in fMRI connectivity. J Comput Neurosci 2011, 30:85-107. 10.1007/s10827-010-0271-2.
    • (2011) J Comput Neurosci , vol.30 , pp. 85-107
    • Lizier, J.T.1    Heinzle, J.2    Horstmann, A.3    Haynes, J.-D.4    Prokopenko, M.5
  • 41
    • 84878214752 scopus 로고    scopus 로고
    • Spatio-temporal Granger causality: a new framework
    • Luo Q., Lu W., Cheng W., Valdes-Sosa P.a, Wen X., Ding M., et al. Spatio-temporal Granger causality: a new framework. Neuroimage 2013, 79:241-263. 10.1016/j.neuroimage.2013.04.091.
    • (2013) Neuroimage , vol.79 , pp. 241-263
    • Luo, Q.1    Lu, W.2    Cheng, W.3    Valdes-Sosa, P.4    Wen, X.5    Ding, M.6
  • 42
    • 85032750818 scopus 로고    scopus 로고
    • Empirical mode decomposition-based time-frequency analysis of multivariate signals: the power of adaptive data analysis
    • Mandic D.P., Wu Z., Huang N.E. Empirical mode decomposition-based time-frequency analysis of multivariate signals: the power of adaptive data analysis. IEEE Signal Process Mag 2013, 30:74-86.
    • (2013) IEEE Signal Process Mag , vol.30 , pp. 74-86
    • Mandic, D.P.1    Wu, Z.2    Huang, N.E.3
  • 43
    • 84862276538 scopus 로고    scopus 로고
    • Causal information approach to partial conditioning in multivariate data sets
    • Marinazzo D., Pellicoro M., Stramaglia S. Causal information approach to partial conditioning in multivariate data sets. Comput Math Methods Med 2012, 2012:303601. 10.1155/2012/303601.
    • (2012) Comput Math Methods Med , vol.2012 , pp. 303601
    • Marinazzo, D.1    Pellicoro, M.2    Stramaglia, S.3
  • 44
    • 36749090569 scopus 로고    scopus 로고
    • A new formulation for empirical mode decomposition based on constrained optimization
    • Meignen S., Perrier V. A new formulation for empirical mode decomposition based on constrained optimization. IEEE Signal Process Lett 2007, 14:932-935. 10.1109/LSP.2007.904706.
    • (2007) IEEE Signal Process Lett , vol.14 , pp. 932-935
    • Meignen, S.1    Perrier, V.2
  • 45
    • 79952163572 scopus 로고    scopus 로고
    • Multivariate empirical mode decomposition for quantifying multivariate phase synchronization
    • Mutlu A.Y., Aviyente S. Multivariate empirical mode decomposition for quantifying multivariate phase synchronization. EURASIP J Adv Signal Process 2011, 2011:1-13. 10.1155/2011/615717.
    • (2011) EURASIP J Adv Signal Process , vol.2011 , pp. 1-13
    • Mutlu, A.Y.1    Aviyente, S.2
  • 47
    • 80053562750 scopus 로고    scopus 로고
    • Ictal high-frequency oscillations at 80-200Hz coupled with delta phase in epileptic spasms
    • Nariai H., Matsuzaki N., Juhász C. Ictal high-frequency oscillations at 80-200Hz coupled with delta phase in epileptic spasms. Epilepsia 2011, 52:1-7. 10.1111/j.1528-1167.2011.03263.x.Ictal.
    • (2011) Epilepsia , vol.52 , pp. 1-7
    • Nariai, H.1    Matsuzaki, N.2    Juhász, C.3
  • 48
    • 45249091476 scopus 로고    scopus 로고
    • Robustly estimating the flow direction of information in complex physical systems
    • Nolte G., Ziehe A., Nikulin V., Schlögl A., Krämer N., Brismar T., et al. Robustly estimating the flow direction of information in complex physical systems. Phys Rev Lett 2008, 100:1-4. 10.1103/PhysRevLett.100.234101.
    • (2008) Phys Rev Lett , vol.100 , pp. 1-4
    • Nolte, G.1    Ziehe, A.2    Nikulin, V.3    Schlögl, A.4    Krämer, N.5    Brismar, T.6
  • 49
    • 84938437548 scopus 로고
    • On the quadrature approximation to the Hilbert transform of modulated signals
    • Nuttall A.H., Bedrosian E. On the quadrature approximation to the Hilbert transform of modulated signals. Proc IEEE 1966, 54:1458-1459.
    • (1966) Proc IEEE , vol.54 , pp. 1458-1459
    • Nuttall, A.H.1    Bedrosian, E.2
  • 50
    • 67650139090 scopus 로고    scopus 로고
    • On the circularity of a complex random variable
    • Ollila E. On the circularity of a complex random variable. IEEE Signal Process Lett 2008, 15:841-844.
    • (2008) IEEE Signal Process Lett , vol.15 , pp. 841-844
    • Ollila, E.1
  • 52
    • 84875184099 scopus 로고    scopus 로고
    • A time-frequency based approach for generalized phase synchrony assessment in nonstationary multivariate signals
    • Omidvarnia A., Azemi G., Colditz P.B., Boashash B. A time-frequency based approach for generalized phase synchrony assessment in nonstationary multivariate signals. Digit Signal Process 2013, 23:780-790. 10.1016/j.dsp.2013.01.002.
    • (2013) Digit Signal Process , vol.23 , pp. 780-790
    • Omidvarnia, A.1    Azemi, G.2    Colditz, P.B.3    Boashash, B.4
  • 53
    • 84901346892 scopus 로고    scopus 로고
    • The physiological plausibility of time-varying Granger-causal modeling: normalization and weighting by spectral power
    • Plomp G., Quairiaux C., Michel C.M., Astolfi L. The physiological plausibility of time-varying Granger-causal modeling: normalization and weighting by spectral power. Neuroimage 2014, 97:206-216. 10.1016/j.neuroimage.2014.04.016.
    • (2014) Neuroimage , vol.97 , pp. 206-216
    • Plomp, G.1    Quairiaux, C.2    Michel, C.M.3    Astolfi, L.4
  • 54
    • 79959925486 scopus 로고    scopus 로고
    • Functional development of large-scale sensorimotor cortical networks in the brain
    • Quairiaux C., Mégevand P., Kiss J.Z., Michel C.M. Functional development of large-scale sensorimotor cortical networks in the brain. J Neurosci 2011, 31:9574-9584. 10.1523/JNEUROSCI.5995-10.2011.
    • (2011) J Neurosci , vol.31 , pp. 9574-9584
    • Quairiaux, C.1    Mégevand, P.2    Kiss, J.Z.3    Michel, C.M.4
  • 55
    • 41349108278 scopus 로고    scopus 로고
    • Markov models from data by simple nonlinear time series predictors in delay embedding spaces
    • Ragwitz M., Kantz H. Markov models from data by simple nonlinear time series predictors in delay embedding spaces. Phys Rev E 2002, 65:1-12. 10.1103/PhysRevE.65.056201.
    • (2002) Phys Rev E , vol.65 , pp. 1-12
    • Ragwitz, M.1    Kantz, H.2
  • 56
    • 77952080754 scopus 로고    scopus 로고
    • Multivariate empirical mode decomposition
    • Rehman N., Mandic D.P. Multivariate empirical mode decomposition. Proc R Soc A Math Phys Eng Sci 2010, 466:1291-1302. 10.1098/rspa.2009.0502.
    • (2010) Proc R Soc A Math Phys Eng Sci , vol.466 , pp. 1291-1302
    • Rehman, N.1    Mandic, D.P.2
  • 59
    • 41349109501 scopus 로고    scopus 로고
    • Identification of coupling direction: application to cardiorespiratory interaction
    • Rosenblum M., Cimponeriu L., Bezerianos A., Patzak A., Mrowka R. Identification of coupling direction: application to cardiorespiratory interaction. Phys Rev E 2002, 65:041909. 10.1103/PhysRevE.65.041909.
    • (2002) Phys Rev E , vol.65 , pp. 041909
    • Rosenblum, M.1    Cimponeriu, L.2    Bezerianos, A.3    Patzak, A.4    Mrowka, R.5
  • 60
    • 33745741282 scopus 로고    scopus 로고
    • A comparison of multivariate autoregressive estimators
    • Schlögl A. A comparison of multivariate autoregressive estimators. Signal Process 2006, 86:2426-2429. 10.1016/j.sigpro.2005.11.007.
    • (2006) Signal Process , vol.86 , pp. 2426-2429
    • Schlögl, A.1
  • 61
    • 12944275674 scopus 로고    scopus 로고
    • Measuring information transfer
    • Schreiber T. Measuring information transfer. Phys Rev Lett 2000, 85:461-464.
    • (2000) Phys Rev Lett , vol.85 , pp. 461-464
    • Schreiber, T.1
  • 62
    • 84893945219 scopus 로고    scopus 로고
    • Improved surrogate data for nonlinearity tests
    • Schreiber T., Schmitz A. Improved surrogate data for nonlinearity tests. Phys Rev Lett 1996, 635:1-4.
    • (1996) Phys Rev Lett , vol.635 , pp. 1-4
    • Schreiber, T.1    Schmitz, A.2
  • 63
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwarz G. Estimating the dimension of a model. Ann Stat 1978, 6:461-464.
    • (1978) Ann Stat , vol.6 , pp. 461-464
    • Schwarz, G.1
  • 64
    • 74149089224 scopus 로고    scopus 로고
    • A MATLAB toolbox for Granger causal connectivity analysis
    • Seth A.K. A MATLAB toolbox for Granger causal connectivity analysis. J Neurosci Methods 2010, 186:262-273. 10.1016/j.jneumeth.2009.11.020.
    • (2010) J Neurosci Methods , vol.186 , pp. 262-273
    • Seth, A.K.1
  • 65
    • 81555204352 scopus 로고    scopus 로고
    • Inference of Granger causal time-dependent influences in noisy multivariate time series
    • Sommerlade L., Thiel M., Platt B., Plano A., Riedel G., Grebogi C., et al. Inference of Granger causal time-dependent influences in noisy multivariate time series. J Neurosci Methods 2012, 203:173-185. 10.1016/j.jneumeth.2011.08.042.
    • (2012) J Neurosci Methods , vol.203 , pp. 173-185
    • Sommerlade, L.1    Thiel, M.2    Platt, B.3    Plano, A.4    Riedel, G.5    Grebogi, C.6
  • 66
    • 84908068841 scopus 로고    scopus 로고
    • Synergy and redundancy in the Granger causal analysis of dynamical networks
    • Stramaglia S., M Cortes J., Marinazzo D. Synergy and redundancy in the Granger causal analysis of dynamical networks. New J Phys 2014, 16:105003. 10.1088/1367-2630/16/10/105003.
    • (2014) New J Phys , vol.16 , pp. 105003
    • Stramaglia, S.1    Cortes, M.J.2    Marinazzo, D.3
  • 67
    • 34548797247 scopus 로고    scopus 로고
    • A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition
    • Sweeney-Reed C.M., Nasuto S.J. A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition. J Comput Neurosci 2007, 23:79-111. 10.1007/s10827-007-0020-3.
    • (2007) J Comput Neurosci , vol.23 , pp. 79-111
    • Sweeney-Reed, C.M.1    Nasuto, S.J.2
  • 68
    • 0000779360 scopus 로고
    • Detecting strange attractors in turbulence
    • Springer-Verlag, D.A. Rand, L.-S. Young (Eds.)
    • Takens F. Detecting strange attractors in turbulence. Dynamical systems and turbulence, lecture notes in mathematics 1981, 366-381. Springer-Verlag. D.A. Rand, L.-S. Young (Eds.).
    • (1981) Dynamical systems and turbulence, lecture notes in mathematics , pp. 366-381
    • Takens, F.1
  • 69
    • 33847675789 scopus 로고    scopus 로고
    • Complex empirical mode decomposition
    • Tanaka T., Mandic D.P. Complex empirical mode decomposition. IEEE Signal Process Lett 2007, 14:101-104. 10.1109/LSP.2006.882107.
    • (2007) IEEE Signal Process Lett , vol.14 , pp. 101-104
    • Tanaka, T.1    Mandic, D.P.2
  • 70
    • 44049111332 scopus 로고
    • Testing for nonlinearity in time series: the method of surrogate data
    • Theiler J., Eubank S., Longtin A. Testing for nonlinearity in time series: the method of surrogate data. Phys D 1992, 58:77-94.
    • (1992) Phys D , vol.58 , pp. 77-94
    • Theiler, J.1    Eubank, S.2    Longtin, A.3
  • 71
    • 78449288116 scopus 로고    scopus 로고
    • Empirical mode decomposition for trivariate signals
    • Rehman N., Mandic D.P. Empirical mode decomposition for trivariate signals. IEEE Trans Signal Process 2010, 58:1059-1068. 10.1109/TSP.2009.2033730.
    • (2010) IEEE Trans Signal Process , vol.58 , pp. 1059-1068
    • Rehman, N.1    Mandic, D.P.2
  • 72
    • 79954532442 scopus 로고    scopus 로고
    • Filter bank property of multivariate empirical mode decomposition
    • Ur Rehman N., Mandic D.P. Filter bank property of multivariate empirical mode decomposition. IEEE Trans Signal Process 2011, 59:2421-2426.
    • (2011) IEEE Trans Signal Process , vol.59 , pp. 2421-2426
    • Ur Rehman, N.1    Mandic, D.P.2
  • 73
    • 84899502032 scopus 로고    scopus 로고
    • EMD Via MEMD: multivariate noise-aided computation of standard emd
    • Ur Rehman N., Park C., Huang N.E., Mandic D.P. EMD Via MEMD: multivariate noise-aided computation of standard emd. Adv Adapt Data Anal 2013, 05:1350007. 10.1142/S1793536913500076.
    • (2013) Adv Adapt Data Anal , vol.5 , pp. 1350007
    • Ur Rehman, N.1    Park, C.2    Huang, N.E.3    Mandic, D.P.4
  • 74
    • 70349233762 scopus 로고    scopus 로고
    • Confounding effects of indirect connections on causality estimation
    • Vakorin V.a, Krakovska O.a, McIntosh A.R. Confounding effects of indirect connections on causality estimation. J Neurosci Methods 2009, 184:152-160.
    • (2009) J Neurosci Methods , vol.184 , pp. 152-160
    • Vakorin, V.1    Krakovska, O.2    McIntosh, A.R.3
  • 76
    • 79955041195 scopus 로고    scopus 로고
    • BioSig: the free and open source software library for biomedical signal processing
    • Vidaurre C., Sander T.H., Schlögl A. BioSig: the free and open source software library for biomedical signal processing. Comput Intell Neurosci 2011, 2011:935364. 10.1155/2011/935364.
    • (2011) Comput Intell Neurosci , vol.2011 , pp. 935364
    • Vidaurre, C.1    Sander, T.H.2    Schlögl, A.3
  • 77
    • 0015489975 scopus 로고
    • The factorization of matricial spectral densities
    • Wilson G.T. The factorization of matricial spectral densities. SIAM J Appl Math 1972, 23:420-426.
    • (1972) SIAM J Appl Math , vol.23 , pp. 420-426
    • Wilson, G.T.1
  • 78
    • 2542525254 scopus 로고    scopus 로고
    • A study of the characteristics of white noise using the empirical mode decomposition method
    • Wu Z., Huang N.E. A study of the characteristics of white noise using the empirical mode decomposition method. Proc R Soc A Math Phys Eng Sci 2004, 460:1597-1611. 10.1098/rspa.2003.1221.
    • (2004) Proc R Soc A Math Phys Eng Sci , vol.460 , pp. 1597-1611
    • Wu, Z.1    Huang, N.E.2
  • 79
    • 80052078099 scopus 로고    scopus 로고
    • Ensemble empirical mode decomposition: a noise-assisted data analysis method
    • Wu Z., Huang N.E. Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv Adapt Data Anal 2009, 01:1-41. 10.1142/S1793536909000047.
    • (2009) Adv Adapt Data Anal , vol.1 , pp. 1-41
    • Wu, Z.1    Huang, N.E.2
  • 80
    • 35448971374 scopus 로고    scopus 로고
    • Analysis of earthquake ground motions using an improved Hilbert-Huang transform
    • Yinfeng D., Yingmin L., Mingkui X., Ming L. Analysis of earthquake ground motions using an improved Hilbert-Huang transform. Soil Dyn Earthq Eng 2008, 28:7-19. 10.1016/j.soildyn.2007.05.002.
    • (2008) Soil Dyn Earthq Eng , vol.28 , pp. 7-19
    • Yinfeng, D.1    Yingmin, L.2    Mingkui, X.3    Ming, L.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.