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Literature DB >> 16202626

Estimation of the intrinsic dimensionality of fMRI data.

Abstract

A new method based on an autoregressive noise model of order 1 is introduced to the problem of detecting the number of components in fMRI data. Unlike current information-theoretic criteria like AIC, MDL, and related PPCA, which do not incorporate autocorrelations in the noise, the new method leads to more consistent estimates of the model order, as illustrated in simulated and real fMRI resting-state data.

Entities: Gene

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Year: 2005 PMID： 16202626 DOI： 10.1016/j.neuroimage.2005.07.054

Source DB: PubMed Journal: Neuroimage ISSN： 1053-8119 Impact factor: 6.556

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Cited

22 in total

1. A new approach to estimating the signal dimension of concatenated resting-state functional MRI data sets.

Authors: Sharon Chen; Thomas J Ross; Keh-Shih Chuang; Elliot A Stein; Yihong Yang; Wang Zhan
Journal: Magn Reson Imaging Date: 2010-07-22 Impact factor: 2.546

2. Methods to detect, characterize, and remove motion artifact in resting state fMRI.

Authors: Jonathan D Power; Anish Mitra; Timothy O Laumann; Abraham Z Snyder; Bradley L Schlaggar; Steven E Petersen
Journal: Neuroimage Date: 2013-08-29 Impact factor: 6.556

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

Authors: Yi-Ou Li; Tülay Adali; Vince D Calhoun
Journal: Hum Brain Mapp Date: 2007-11 Impact factor: 5.038

4. Partner-matching for the automated identification of reproducible ICA components from fMRI datasets: algorithm and validation.

Authors: Zhishun Wang; Bradley S Peterson
Journal: Hum Brain Mapp Date: 2008-08 Impact factor: 5.038

5. Higher-order contrast functions improve performance of independent component analysis of fMRI data.

Authors: Vincent J Schmithorst
Journal: J Magn Reson Imaging Date: 2009-01 Impact factor: 4.813

6. Independent component analysis as a model-free approach for the detection of BOLD changes related to epileptic spikes: a simulation study.

Authors: Pierre LeVan; Jean Gotman
Journal: Hum Brain Mapp Date: 2009-07 Impact factor: 5.038

Estimation of the intrinsic dimensionality of fMRI data.

1. A new approach to estimating the signal dimension of concatenated resting-state functional MRI data sets.

2. Methods to detect, characterize, and remove motion artifact in resting state fMRI.

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

4. Partner-matching for the automated identification of reproducible ICA components from fMRI datasets: algorithm and validation.

5. Higher-order contrast functions improve performance of independent component analysis of fMRI data.

6. Independent component analysis as a model-free approach for the detection of BOLD changes related to epileptic spikes: a simulation study.

7. Dimensionality reduction of fMRI time series data using locally linear embedding.

8. Aberrant default mode network in subjects with amnestic mild cognitive impairment using resting-state functional MRI.

9. The Lag Structure of Intrinsic Activity is Focally Altered in High Functioning Adults with Autism.

10. Group independent component analysis reveals consistent resting-state networks across multiple sessions.