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Volumn 23, Issue 3, 2013, Pages

Adaptive filtering and random variables coefficient for analyzing functional magnetic resonance imaging data

Author keywords

Adaptive filtering; fMRI; functional connectivity; nonstationarity test; physiological noise; principal component analysis; resting state; RV coefficient

Indexed keywords

FMRI; FUNCTIONAL CONNECTIVITY; NON-STATIONARITIES; PHYSIOLOGICAL NOISE; RESTING STATE; RV COEFFICIENT;

EID: 84877263279     PISSN: 01290657     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0129065713500111     Document Type: Article
Times cited : (5)

References (47)
  • 1
    • 84859354964 scopus 로고    scopus 로고
    • A new parametric feature descriptor for the classification of epileptic and control eeg records in pediatric population
    • M. Cabrerizo, M. Ayala, M. Goryawala, P. Jayakar and M. Adjouadi, A new parametric feature descriptor for the classification of epileptic and control EEG records in pediatric population, Int. J. Neural Syst. 22(02) (2012) 1250001.
    • (2012) Int. J. Neural Syst. , vol.22 , Issue.2 , pp. 1250001
    • Cabrerizo, M.1    Ayala, M.2    Goryawala, M.3    Jayakar, P.4    Adjouadi, M.5
  • 2
    • 78649560818 scopus 로고    scopus 로고
    • Analysis and automatic identification of sleep stages using higher order spectra
    • U. Acharya, E. C. P. Chua, K. C. Chua, L. C. Min and T. Tamura, Analysis and automatic identification of sleep stages using higher order spectra, Int. J. Neural Syst. 20(6) (2010) 509-521.
    • (2010) Int. J. Neural Syst. , vol.20 , Issue.6 , pp. 509-521
    • Acharya, U.1    Chua, E.C.P.2    Chua, K.C.3    Min, L.C.4    Tamura, T.5
  • 3
    • 78751551710 scopus 로고    scopus 로고
    • Semi-supervised analysis of human brain tumours from partially labeled mrs information, using manifold learning models, int
    • R. Cruz-Barbosa and A. Vellido, Semi-supervised analysis of human brain tumours from partially labeled MRS information, using manifold learning models, Int. J. Neural Syst. 21(1) (2011) 17.
    • (2011) J. Neural Syst. , vol.21 , Issue.1 , pp. 17
    • Cruz-Barbosa, R.1    Vellido, A.2
  • 4
    • 78751550144 scopus 로고    scopus 로고
    • Recurrence-based estimation of time-distortion functions for erp waveform reconstruction
    • M. Ihrke, H. Schrobsdorff and J. M. Herrmann, Recurrence-based estimation of time-distortion functions for Erp waveform reconstruction, Int. J. Neural Syst. 21(1) (2011) 65.
    • (2011) Int. J. Neural Syst. , vol.21 , Issue.1 , pp. 65
    • Ihrke, M.1    Schrobsdorff, H.2    Herrmann, J.M.3
  • 5
    • 82655173325 scopus 로고    scopus 로고
    • Rankingbased kernels in applied biomedical diagnostics using a support vector machine
    • V. Jumutc, P. Zayakin and A. Borisov, Rankingbased kernels in applied biomedical diagnostics using a support vector machine, Int. J. Neural Syst. 21(6) (2011) 459.
    • (2011) Int. J. Neural Syst. , vol.21 , Issue.6 , pp. 459
    • Jumutc, V.1    Zayakin, P.2    Borisov, A.3
  • 6
    • 82655181688 scopus 로고    scopus 로고
    • Blood glucose level neural model for type 1 diabetes mellitus patients
    • A. Y. Alanis, B. S. Leon, E. N. Sanchez and E. Ruiz-Velazquez, Blood glucose level neural model for type 1 diabetes mellitus patients, Int. J. Neural Syst. 21(6) (2011) 491.
    • (2011) Int. J. Neural Syst. , vol.21 , Issue.6 , pp. 491
    • Alanis, A.Y.1    Leon, B.S.2    Sanchez, E.N.3    Ruiz-Velazquez, E.4
  • 7
    • 84862065733 scopus 로고    scopus 로고
    • Artificial neural network based approach to eeg signal simulation
    • N.M. Tomasevic, A.M. Neskovic and N. J. Neskovic, Artificial neural network based approach to EEG signal simulation, Int. J. Neural Syst. 22(03) (2012) 1250008.
    • (2012) Int. J. Neural Syst. , vol.22 , Issue.3 , pp. 1250008
    • Tomasevic, N.M.1    Neskovic, A.M.2    Neskovic, N.J.3
  • 8
    • 79953329176 scopus 로고    scopus 로고
    • Spatio-temporal resolution enhancement of vocal tract mri sequences based on image registration
    • A. L. D. Martins, N. D. A. Mascarenhas and C. A. T. Suazo, Spatio-temporal resolution enhancement of vocal tract MRI sequences based on image registration, Integr. Comput.-Aided Eng. 18(2) (2011) 143-155.
    • (2011) Integr. Comput.-Aided Eng. , vol.18 , Issue.2 , pp. 143-155
    • Martins, A.L.D.1    Mascarenhas, N.D.A.2    Suazo, C.A.T.3
  • 11
    • 77951560201 scopus 로고    scopus 로고
    • Protein subcellular multilocalization prediction using a min-max modular support vector machine, int
    • Y. Yang and B. L. Lu, Protein subcellular multilocalization prediction using a min-max modular support vector machine, Int. J. Neural Syst. 20(1) (2010) 13.
    • (2010) J. Neural Syst. , vol.20 , Issue.1 , pp. 13
    • Yang, Y.1    Lu, B.L.2
  • 12
    • 33846338227 scopus 로고    scopus 로고
    • Recurrence plots for the analysis of complex systems
    • N. Marwan, M. Carmen Romano, M. Thiel and J. Kurths, Recurrence plots for the analysis of complex systems, Phys. Rep. 438(5) (2007) 237-329.
    • (2007) Phys. Rep. , vol.438 , Issue.5 , pp. 237-329
    • Marwan, N.1    Carmen Romano, M.2    Thiel, M.3    Kurths, J.4
  • 13
    • 0000688735 scopus 로고
    • Embeddings and delays as derived from quantification of recurrence plots
    • J. P. Zbilut and C. L. Webber Jr., Embeddings and delays as derived from quantification of recurrence plots, Phys. Lett. A 171(3-4) (1992) 199-203.
    • (1992) Phys. Lett. , vol.A 171 , Issue.3-4 , pp. 199-203
    • Zbilut, J.P.1    Webber Jr., C.L.2
  • 14
    • 79960037752 scopus 로고    scopus 로고
    • Application of recurrence quantification analysis for the automated identification of epileptic eeg signals
    • U. R. Acharrya, S. V. Sree, S. Chattopadhyay, W. Yu and P. C. A. Ang, Application of recurrence quantification analysis for the automated identification of epileptic EEG signals, Int. J. Neural Syst. 21(3) (2011) 199.
    • (2011) Int. J. Neural Syst. , vol.21 , Issue.3 , pp. 199
    • Acharrya, U.R.1    Sree, S.V.2    Chattopadhyay, S.3    Yu, W.4    Ang, P.C.A.5
  • 16
    • 84859351360 scopus 로고    scopus 로고
    • Application of non-linear and wavelet based features for the automated identification of epileptic eeg signals
    • U. R. Acharya, S. V. Sree, P. C. A. Ang, R. Yanti and J. S. Suri, Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals, Int. J. Neural Syst. 22(02) (2012) 1250002.
    • (2012) Int. J. Neural Syst. , vol.22 , Issue.2 , pp. 1250002
    • Acharya, U.R.1    Sree, S.V.2    Ang, P.C.A.3    Yanti, R.4    Suri, J.S.5
  • 17
    • 77951577412 scopus 로고    scopus 로고
    • Automatic identification of epileptic and background eeg signals using frequency domain parameters
    • O. Faust, U. R. Acharya, L. Min and B. H. C. Sputh, Automatic identification of epileptic and background EEG signals using frequency domain parameters, Int. J. Neural Syst. 20(2) (2010) 159-176.
    • (2010) Int. J. Neural Syst. , vol.20 , Issue.2 , pp. 159-176
    • Faust, O.1    Acharya, U.R.2    Min, L.3    Sputh, B.H.C.4
  • 18
    • 79953191488 scopus 로고    scopus 로고
    • Detection of nonlinear interactions of eeg alpha waves in the brain by a new coherence measure and its application to epilepsy and anti-epileptic drug therapy
    • D. Sherman, N. Zhang, S. Garg, N. V. Thakor, M. A. Mirski, M. A. White and M. J. Hinich, Detection of nonlinear interactions of EEG alpha waves in the brain by a new coherence measure and its application to epilepsy and anti-epileptic drug therapy, Int. J. Neural. Syst. 21 (2) (2011) 115-126.
    • (2011) Int. J. Neural. Syst. , vol.21 , Issue.2 , pp. 115-126
    • Sherman, D.1    Zhang, N.2    Garg, S.3    Thakor, N.V.4    Mirski, M.A.5    White, M.A.6    Hinich, M.J.7
  • 19
    • 80053348045 scopus 로고    scopus 로고
    • Automatic detection of epileptic eeg signals using higher order cumulant features
    • U. R. Acharya, S. V. Sree and J. S. Suri, Automatic detection of epileptic EEG signals using higher order cumulant features, Int. J. Neural Syst. 21(05) (2011) 403-414.
    • (2011) Int. J. Neural Syst. , vol.21 , Issue.5 , pp. 403-414
    • Acharya, U.R.1    Sree, S.V.2    Suri, J.S.3
  • 20
    • 0028190347 scopus 로고
    • Functional and effective connectivity in neuroimaging: A synthesis
    • K. J. Friston, Functional and effective connectivity in neuroimaging: A synthesis, Hum. Brain Mapp. 2(1-2) (1994) 56-78. (Pubitemid 124000442)
    • (1994) Human Brain Mapping , vol.2 , Issue.1-2 , pp. 56-78
    • Friston, K.J.1
  • 21
    • 0029166541 scopus 로고
    • Functional connectivity in the motor cortex of resting human brain using echo-planar mri
    • B. Biswal, F. Z. Yetkin, V. M. Haughton and J. S. Hyde, Functional connectivity in the motor cortex of resting human brain using echo-planar MRI, Magn. Reson. Med. 34(4) (1995) 537-541.
    • (1995) Magn. Reson. Med. , vol.34 , Issue.4 , pp. 537-541
    • Biswal, B.1    Yetkin, F.Z.2    Haughton, V.M.3    Hyde, J.S.4
  • 22
    • 0036483610 scopus 로고    scopus 로고
    • What does fMRI tell us about neuronal activity?
    • DOI 10.1038/nrn730
    • D. J. Heeger and D. Ress, What does fMRI tell us about neuronal activity?, Nat. Rev. Neurosci. 3(2) (2002) 142-151. (Pubitemid 135706583)
    • (2002) Nature Reviews Neuroscience , vol.3 , Issue.2 , pp. 142-151
    • Heeger, D.J.1    Ress, D.2
  • 23
    • 57649221314 scopus 로고    scopus 로고
    • Influence of heart rate on the bold signal: The cardiac response function
    • C. Chang, J. P. Cunningham and G. H. Glover, Influence of heart rate on the BOLD signal: The cardiac response function, Neuroimage 44(3) (2009) 857-869.
    • (2009) Neuroimage , vol.44 , Issue.3 , pp. 857-869
    • Chang, C.1    Cunningham, J.P.2    Glover, G.H.3
  • 24
    • 35148820975 scopus 로고    scopus 로고
    • Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal
    • DOI 10.1016/j.neuroimage.2007.07.037, PII S1053811907006702
    • K. Shmueli, P. van Gelderen, J. A. de Zwart, S. G. Horovitz, M. Fukunaga, J. M. Jansma and J. H. Duyn, Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal, Neuroimage 38(2) (2007) 306-320. (Pubitemid 47534282)
    • (2007) NeuroImage , vol.38 , Issue.2 , pp. 306-320
    • Shmueli, K.1    Van Gelderen, P.2    De Zwart, J.A.3    Horovitz, S.G.4    Fukunaga, M.5    Jansma, J.M.6    Duyn, J.H.7
  • 25
    • 33746852686 scopus 로고    scopus 로고
    • Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI
    • DOI 10.1016/j.neuroimage.2006.02.048, PII S1053811906001248
    • R. M. Birn, J. B. Diamond, M. A. Smith and P. A. Bandettini, Separating respiratory-variation-related fluctuations from neuronal-Activity-related fluctuations in fMRI, Neuroimage 31(4) (2006) 1536-1548. (Pubitemid 44192499)
    • (2006) NeuroImage , vol.31 , Issue.4 , pp. 1536-1548
    • Birn, R.M.1    Diamond, J.B.2    Smith, M.A.3    Bandettini, P.A.4
  • 26
    • 1842609636 scopus 로고    scopus 로고
    • Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal
    • DOI 10.1016/j.neuroimage.2003.11.025, PII S1053811903007663
    • R. G.Wise, K. Ide, M. J. Poulin and I. Tracey, Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal, Neuroimage 21(4) (2004) 1652-1664. (Pubitemid 38446588)
    • (2004) NeuroImage , vol.21 , Issue.4 , pp. 1652-1664
    • Wise, R.G.1    Ide, K.2    Poulin, M.J.3    Tracey, I.4
  • 27
    • 29244477177 scopus 로고    scopus 로고
    • Non-white noise in fMRI: Does modelling have an impact?
    • DOI 10.1016/j.neuroimage.2005.07.005, PII S105381190500501X
    • T. E. Lund, K. H. Madsen, K. Sidaros, W. L. Luo and T. E. Nichols, Non-white noise in fMRI: Does modeling have an impact?, Neuroimage 29(1) (2006) 54-66. (Pubitemid 41828030)
    • (2006) NeuroImage , vol.29 , Issue.1 , pp. 54-66
    • Lund, T.E.1    Madsen, K.H.2    Sidaros, K.3    Luo, W.-L.4    Nichols, T.E.5
  • 33
    • 0032777187 scopus 로고    scopus 로고
    • Localization of cardiac-induced signal change in fMRI
    • DOI 10.1006/nimg.1998.0424
    • M. S. Dagli, J. E. Ingeholm and J. V. Haxby, Localization of cardiac-induced signal change in fMRI, Neuroimage 9(4) (1999) 407-415. (Pubitemid 29369860)
    • (1999) NeuroImage , vol.9 , Issue.4 , pp. 407-415
    • Dagli, M.S.1    Ingeholm, J.E.2    Haxby, J.V.3
  • 34
    • 0001400228 scopus 로고
    • A unifying tool for linear multivariate statistical methods: The rv-coefficient
    • P. Robert and Y. Escoufier, A unifying tool for linear multivariate statistical methods: The RV-coefficient, J. R. Stat. Soc. Ser. C Appl. Stat. 25(3) (1976) 257-265.
    • (1976) J. R. Stat. Soc. Ser. C Appl. Stat. , vol.25 , Issue.3 , pp. 257-265
    • Robert, P.1    Escoufier, Y.2
  • 35
    • 0000899112 scopus 로고
    • Refined approximations to permutation tests for multivariate inference
    • F. Kazi-Aoual, S. Hitier, R. Sabatier and J. D. Lebreton, Refined approximations to permutation tests for multivariate inference, Comput. Stat. Data Anal. 20(6) (1995) 643-656.
    • (1995) Comput. Stat. Data Anal. , vol.20 , Issue.6 , pp. 643-656
    • Kazi-Aoual, F.1    Hitier, S.2    Sabatier, R.3    Lebreton, J.D.4
  • 36
    • 51749086345 scopus 로고    scopus 로고
    • Testing the significance of the rv coefficient
    • J. Josse, J. Paǵes and F. Husson, Testing the significance of the RV coefficient, Comput. Stat. Data Anal. 53(1) (2008) 82-91.
    • (2008) Comput. Stat. Data Anal. , vol.53 , Issue.1 , pp. 82-91
    • Josse, J.1    Paǵes, J.2    Husson, F.3
  • 37
    • 0034846506 scopus 로고    scopus 로고
    • FcMRI - Mapping functional connectivity or correlating cardiac-induced noise? (multiple letters)
    • DOI 10.1002/mrm.1238
    • T. E. Lund, fcMRI-mapping functional connectivity or correlating cardiac-induced noise?, Magn. Reson. Med. 46(3) (2001) 628-629. (Pubitemid 32831342)
    • (2001) Magnetic Resonance in Medicine , vol.46 , Issue.3 , pp. 628-629
    • Lund, T.E.1
  • 38
    • 34548014282 scopus 로고    scopus 로고
    • Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
    • DOI 10.1038/nrn2201, PII NRN2201
    • M. D. Fox and M. E. Raichle, Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging, Nat. Rev. Neurosci. 8(9) (2007) 700-711. (Pubitemid 47283145)
    • (2007) Nature Reviews Neuroscience , vol.8 , Issue.9 , pp. 700-711
    • Fox, M.D.1    Raichle, M.E.2
  • 39
    • 0030175198 scopus 로고    scopus 로고
    • AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages
    • DOI 10.1006/cbmr.1996.0014
    • R. W. Cox, AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages, Comput. Biomed. Res. 29(3) (1996) 162-173. (Pubitemid 26266657)
    • (1996) Computers and Biomedical Research , vol.29 , Issue.3 , pp. 162-173
    • Cox, R.W.1
  • 42
    • 84937549955 scopus 로고
    • The scree test for the number of factors
    • R. Catell, The scree test for the number of factors, Multivar. Behav. Res. 1(2) (1966) 245-276.
    • (1966) Multivar. Behav. Res. , vol.1 , Issue.2 , pp. 245-276
    • Catell, R.1
  • 47
    • 0029773391 scopus 로고    scopus 로고
    • Scaling behaviour of heartbeat intervals obtained by wavelet-based time- series analysis
    • DOI 10.1038/383323a0
    • P. C. Ivanov, M. G. Rosenblum, C. Peng, J. Mietus, S. Havlin, H. E. Stanley and A. L. Goldberger, Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis, Nature 383(6598) (1996) 323-327. (Pubitemid 26321758)
    • (1996) Nature , vol.383 , Issue.6598 , pp. 323-327
    • Ivanov, P.C.1    Rosenblum, M.G.2    Peng, C.-K.3    Mietus, J.4    Havlin, S.5    Stanley, H.E.6    Goldberger, A.L.7


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