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378 related items for PubMed ID: 20153834

  • 1. A group model for stable multi-subject ICA on fMRI datasets.
    Varoquaux G, Sadaghiani S, Pinel P, Kleinschmidt A, Poline JB, Thirion B.
    Neuroimage; 2010 May 15; 51(1):288-99. PubMed ID: 20153834
    [Abstract] [Full Text] [Related]

  • 2. Modeling state-related fMRI activity using change-point theory.
    Lindquist MA, Waugh C, Wager TD.
    Neuroimage; 2007 Apr 15; 35(3):1125-41. PubMed ID: 17360198
    [Abstract] [Full Text] [Related]

  • 3. Independent component model of the default-mode brain function: combining individual-level and population-level analyses in resting-state fMRI.
    Esposito F, Aragri A, Pesaresi I, Cirillo S, Tedeschi G, Marciano E, Goebel R, Di Salle F.
    Magn Reson Imaging; 2008 Sep 15; 26(7):905-13. PubMed ID: 18486388
    [Abstract] [Full Text] [Related]

  • 4. Multi-level bootstrap analysis of stable clusters in resting-state fMRI.
    Bellec P, Rosa-Neto P, Lyttelton OC, Benali H, Evans AC.
    Neuroimage; 2010 Jul 01; 51(3):1126-39. PubMed ID: 20226257
    [Abstract] [Full Text] [Related]

  • 5. Semi-blind ICA of fMRI: A method for utilizing hypothesis-derived time courses in a spatial ICA analysis.
    Calhoun VD, Adali T, Stevens MC, Kiehl KA, Pekar JJ.
    Neuroimage; 2005 Apr 01; 25(2):527-38. PubMed ID: 15784432
    [Abstract] [Full Text] [Related]

  • 6. Independent vector analysis (IVA): multivariate approach for fMRI group study.
    Lee JH, Lee TW, Jolesz FA, Yoo SS.
    Neuroimage; 2008 Mar 01; 40(1):86-109. PubMed ID: 18165105
    [Abstract] [Full Text] [Related]

  • 7. Effects of aging on default mode network activity in resting state fMRI: does the method of analysis matter?
    Koch W, Teipel S, Mueller S, Buerger K, Bokde AL, Hampel H, Coates U, Reiser M, Meindl T.
    Neuroimage; 2010 May 15; 51(1):280-7. PubMed ID: 20004726
    [Abstract] [Full Text] [Related]

  • 8. Correction of low-frequency physiological noise from the resting state BOLD fMRI--Effect on ICA default mode analysis at 1.5 T.
    Starck T, Remes J, Nikkinen J, Tervonen O, Kiviniemi V.
    J Neurosci Methods; 2010 Feb 15; 186(2):179-85. PubMed ID: 19941896
    [Abstract] [Full Text] [Related]

  • 9. Model-free fMRI group analysis using FENICA.
    Schöpf V, Windischberger C, Robinson S, Kasess CH, Fischmeister FP, Lanzenberger R, Albrecht J, Kleemann AM, Kopietz R, Wiesmann M, Moser E.
    Neuroimage; 2011 Mar 01; 55(1):185-93. PubMed ID: 21078400
    [Abstract] [Full Text] [Related]

  • 10. Subject order-independent group ICA (SOI-GICA) for functional MRI data analysis.
    Zhang H, Zuo XN, Ma SY, Zang YF, Milham MP, Zhu CZ.
    Neuroimage; 2010 Jul 15; 51(4):1414-24. PubMed ID: 20338245
    [Abstract] [Full Text] [Related]

  • 11. Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA.
    Zhang J, Anderson JR, Liang L, Pulapura SK, Gatewood L, Rottenberg DA, Strother SC.
    Magn Reson Imaging; 2009 Feb 15; 27(2):264-78. PubMed ID: 18849131
    [Abstract] [Full Text] [Related]

  • 12. The non-separability of physiologic noise in functional connectivity MRI with spatial ICA at 3T.
    Beall EB, Lowe MJ.
    J Neurosci Methods; 2010 Aug 30; 191(2):263-76. PubMed ID: 20600313
    [Abstract] [Full Text] [Related]

  • 13. Cortex-based independent component analysis of fMRI time series.
    Formisano E, Esposito F, Di Salle F, Goebel R.
    Magn Reson Imaging; 2004 Dec 30; 22(10):1493-504. PubMed ID: 15707799
    [Abstract] [Full Text] [Related]

  • 14. Dissecting cognitive stages with time-resolved fMRI data: a comparison of fuzzy clustering and independent component analysis.
    Smolders A, De Martino F, Staeren N, Scheunders P, Sijbers J, Goebel R, Formisano E.
    Magn Reson Imaging; 2007 Jul 30; 25(6):860-8. PubMed ID: 17482412
    [Abstract] [Full Text] [Related]

  • 15. Spatial registration of multichannel multi-subject fNIRS data to MNI space without MRI.
    Singh AK, Okamoto M, Dan H, Jurcak V, Dan I.
    Neuroimage; 2005 Oct 01; 27(4):842-51. PubMed ID: 15979346
    [Abstract] [Full Text] [Related]

  • 16. Segregation of frontoparietal and cerebellar components within saccade and vergence networks using hierarchical independent component analysis of fMRI.
    Alkan Y, Biswal BB, Taylor PA, Alvarez TL.
    Vis Neurosci; 2011 May 01; 28(3):247-61. PubMed ID: 21554775
    [Abstract] [Full Text] [Related]

  • 17. Discriminative analysis of resting-state functional connectivity patterns of schizophrenia using low dimensional embedding of fMRI.
    Shen H, Wang L, Liu Y, Hu D.
    Neuroimage; 2010 Feb 15; 49(4):3110-21. PubMed ID: 19931396
    [Abstract] [Full Text] [Related]

  • 18. A connectivity-based method for defining regions-of-interest in fMRI data.
    Deleus F, Van Hulle MM.
    IEEE Trans Image Process; 2009 Aug 15; 18(8):1760-71. PubMed ID: 19414287
    [Abstract] [Full Text] [Related]

  • 19. Analyzing consistency of independent components: an fMRI illustration.
    Ylipaavalniemi J, Vigário R.
    Neuroimage; 2008 Jan 01; 39(1):169-80. PubMed ID: 17931888
    [Abstract] [Full Text] [Related]

  • 20. Independent component analysis of fMRI group studies by self-organizing clustering.
    Esposito F, Scarabino T, Hyvarinen A, Himberg J, Formisano E, Comani S, Tedeschi G, Goebel R, Seifritz E, Di Salle F.
    Neuroimage; 2005 Mar 01; 25(1):193-205. PubMed ID: 15734355
    [Abstract] [Full Text] [Related]

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