The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Estimating the number of independent components for functional magnetic resonance imaging data
Open accessAbstract
Multivariate analysis methods such as independent component analysis (ICA) have been applied to the analysis of functional magnetic resonance imaging (fMRI) data to study brain function. Because of the high dimensionality and high noise level of the fMRI data, order selection, i.e., estimation of the number of informative components, is critical to reduce over/underfitting in such methods. Dependence among fMRI data samples in the spatial and temporal domain limits the usefulness of the practical formulations of information‐theoretic criteria (ITC) for order selection, since they are based on likelihood of independent and identically distributed (i.i.d.) data samples. To address this issue, we propose a subsampling scheme to obtain a set of effectively i.i.d. samples from the dependent data samples and apply the ITC formulas to the effectively i.i.d. sample set for order selection. We apply the proposed method on the simulated data and show that it significantly improves the accuracy of order selection from dependent data. We also perform order selection on fMRI data from a visuomotor task and show that the proposed method alleviates the over‐estimation on the number of brain sources due to the intrinsic smoothness and the smooth preprocessing of fMRI data. We use the software package ICASSO (Himberg et al. [ 2004]: Neuroimage 22:1214–1222) to analyze the independent component (IC) estimates at different orders and show that, when ICA is performed at overestimated orders, the stability of the IC estimates decreases and the estimation of task related brain activations show degradation. Hum Brain Mapp, 2007. © 2007 Wiley‐Liss, Inc.
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Cited by
Aberrant “Default Mode” Functional Connectivity in Schizophrenia
Garrity, A. G., Pearlson, G. D., McKiernan, K., Lloyd, D., Kiehl, K. A., & Calhoun, V. D. (2007) · American Journal of Psychiatry · doi:10.1176/ajp.2007.164.3.450 · Cited by 1,114
Self-citationSelective changes of resting-state networks in individuals at risk for Alzheimer’s disease
Sorg, C., Riedl, V., Mühlau, M., Calhoun, V. D., Eichele, T., Läer, L., Drzezga, A., Förstl, H., Kurz, A., Zimmer, C., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0708803104 · Cited by 1,036
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Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients
Assaf, M., Jagannathan, K., Calhoun, V. D., Miller, L., Stevens, M. C., Sahl, R., O'Boyle, J. G., Schultz, R. T., & Pearlson, G. D. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.067 · Cited by 680
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Metadata
- Authors
- Li, Y., Adalı, T., & Calhoun, V. D.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2007-02
- Volume
- 28
- Issue
- 11
- Pages
- 1251-1266
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2082207932
- Cited by
- 912
- References
- 39
- FWCI
- 49.18
- Type
- journal article
- Language
- en
- Open access
- green
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