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Items: 1 to 20 of 148

1.

Validating the independent components of neuroimaging time series via clustering and visualization.

Himberg J, Hyvärinen A, Esposito F.

Neuroimage. 2004 Jul;22(3):1214-22.

PMID:
15219593
2.

Analyzing consistency of independent components: an fMRI illustration.

Ylipaavalniemi J, Vigário R.

Neuroimage. 2008 Jan 1;39(1):169-80. Epub 2007 Aug 28.

PMID:
17931888
3.

Multivariate analysis of neuronal interactions in the generalized partial least squares framework: simulations and empirical studies.

Lin FH, McIntosh AR, Agnew JA, Eden GF, Zeffiro TA, Belliveau JW.

Neuroimage. 2003 Oct;20(2):625-42.

PMID:
14568440
4.

Spatial independent component analysis of functional MRI time-series: to what extent do results depend on the algorithm used?

Esposito F, Formisano E, Seifritz E, Goebel R, Morrone R, Tedeschi G, Di Salle F.

Hum Brain Mapp. 2002 Jul;16(3):146-57.

PMID:
12112768
5.

An independent component analysis-based approach on ballistocardiogram artifact removing.

Briselli E, Garreffa G, Bianchi L, Bianciardi M, Macaluso E, Abbafati M, Grazia Marciani M, Maraviglia B.

Magn Reson Imaging. 2006 May;24(4):393-400. Epub 2006 Mar 20.

PMID:
16677945
6.

A K-means multivariate approach for clustering independent components from magnetoencephalographic data.

Spadone S, de Pasquale F, Mantini D, Della Penna S.

Neuroimage. 2012 Sep;62(3):1912-23. doi: 10.1016/j.neuroimage.2012.05.051. Epub 2012 May 24.

PMID:
22634861
7.

Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms.

Calhoun VD, Adali T, Pearlson GD, Pekar JJ.

Hum Brain Mapp. 2001 May;13(1):43-53.

PMID:
11284046
8.

Comparison of two exploratory data analysis methods for fMRI: unsupervised clustering versus independent component analysis.

Meyer-Baese A, Wismueller A, Lange O.

IEEE Trans Inf Technol Biomed. 2004 Sep;8(3):387-98.

PMID:
15484444
9.

Estimating the number of independent components for functional magnetic resonance imaging data.

Li YO, Adali T, Calhoun VD.

Hum Brain Mapp. 2007 Nov;28(11):1251-66.

PMID:
17274023
10.

Unified SPM-ICA for fMRI analysis.

Hu D, Yan L, Liu Y, Zhou Z, Friston KJ, Tan C, Wu D.

Neuroimage. 2005 Apr 15;25(3):746-55.

PMID:
15808976
11.
12.

Real-time independent component analysis of fMRI time-series.

Esposito F, Seifritz E, Formisano E, Morrone R, Scarabino T, Tedeschi G, Cirillo S, Goebel R, Di Salle F.

Neuroimage. 2003 Dec;20(4):2209-24.

PMID:
14683723
13.

Testing the ICA mixing matrix based on inter-subject or inter-session consistency.

Hyvärinen A.

Neuroimage. 2011 Sep 1;58(1):122-36. doi: 10.1016/j.neuroimage.2011.05.086. Epub 2011 Jun 17.

PMID:
21704714
14.

Latency (in)sensitive ICA. Group independent component analysis of fMRI data in the temporal frequency domain.

Calhoun VD, Adali T, Pekar JJ, Pearlson GD.

Neuroimage. 2003 Nov;20(3):1661-9.

PMID:
14642476
15.

Cortex-based independent component analysis of fMRI time series.

Formisano E, Esposito F, Di Salle F, Goebel R.

Magn Reson Imaging. 2004 Dec;22(10):1493-504.

PMID:
15707799
16.
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18.

Source density-driven independent component analysis approach for fMRI data.

Hong B, Pearlson GD, Calhoun VD.

Hum Brain Mapp. 2005 Jul;25(3):297-307.

PMID:
15832316
19.

[Blind source separation for fMRI signals using a new independent component analysis algorithm and principal component analysis].

Zhang W, Shi Z, Tang H, Tang Y.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2007 Apr;24(2):430-3. Chinese.

PMID:
17591275
20.

Independent vector analysis (IVA): multivariate approach for fMRI group study.

Lee JH, Lee TW, Jolesz FA, Yoo SS.

Neuroimage. 2008 Mar 1;40(1):86-109. doi: 10.1016/j.neuroimage.2007.11.019. Epub 2007 Nov 28.

PMID:
18165105
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