CORSICA: correction of structured noise in fMRI by automatic identification of ICA components - PubMed (original) (raw)
CORSICA: correction of structured noise in fMRI by automatic identification of ICA components
Vincent Perlbarg et al. Magn Reson Imaging. 2007 Jan.
Abstract
When applied to functional magnetic resonance imaging (fMRI) data, spatial independent component analysis (sICA), a data-driven technique that addresses the blind source separation problem, seems able to extract components specifically related to physiological noise and brain movements. These components should be removed from the data to achieve structured noise reduction and improve any subsequent detection and analysis of signal fluctuations related to neural activity. We propose a new automatic method called CORSICA (CORrection of Structured noise using spatial Independent Component Analysis) to identify the components related to physiological noise, using prior information on the spatial localization of the main physiological fluctuations in fMRI data. As opposed to existing spectral priors, which may be subject to aliasing effects for long-TR data sets (typically acquired with TR >1 s), such spatial priors can be applied to fMRI data, regardless of the TR of the acquisitions. By comparing the proposed automatic selection to a manual selection performed visually by a human operator, we first show that CORSICA is able to identify the noise-related components for long-TR data with a high sensitivity and a specificity of 1. On short-TR data sets, we validate that the proposed method of noise reduction allows a substantial improvement of the signal-to-noise ratio evaluated at the cardiac and respiratory frequencies, even in the gray matter, while preserving the main fluctuations related to neural activity.
Similar articles
- Characterization of cardiac-related noise in fMRI of the cervical spinal cord.
Piché M, Cohen-Adad J, Nejad MK, Perlbarg V, Xie G, Beaudoin G, Benali H, Rainville P. Piché M, et al. Magn Reson Imaging. 2009 Apr;27(3):300-10. doi: 10.1016/j.mri.2008.07.019. Epub 2008 Sep 17. Magn Reson Imaging. 2009. PMID: 18801632 - Reduction of physiological noise with independent component analysis improves the detection of nociceptive responses with fMRI of the human spinal cord.
Xie G, Piché M, Khoshnejad M, Perlbarg V, Chen JI, Hoge RD, Benali H, Rossignol S, Rainville P, Cohen-Adad J. Xie G, et al. Neuroimage. 2012 Oct 15;63(1):245-52. doi: 10.1016/j.neuroimage.2012.06.057. Epub 2012 Jul 6. Neuroimage. 2012. PMID: 22776463 - 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. Calhoun VD, et al. Neuroimage. 2005 Apr 1;25(2):527-38. doi: 10.1016/j.neuroimage.2004.12.012. Neuroimage. 2005. PMID: 15784432 - The effect of physiological noise in phase functional magnetic resonance imaging: from blood oxygen level-dependent effects to direct detection of neuronal currents.
Hagberg GE, Bianciardi M, Brainovich V, Cassarà AM, Maraviglia B. Hagberg GE, et al. Magn Reson Imaging. 2008 Sep;26(7):1026-40. doi: 10.1016/j.mri.2008.01.010. Epub 2008 May 13. Magn Reson Imaging. 2008. PMID: 18479875 Review. - Real-time functional magnetic resonance imaging: methods and applications.
Weiskopf N, Sitaram R, Josephs O, Veit R, Scharnowski F, Goebel R, Birbaumer N, Deichmann R, Mathiak K. Weiskopf N, et al. Magn Reson Imaging. 2007 Jul;25(6):989-1003. doi: 10.1016/j.mri.2007.02.007. Epub 2007 Apr 23. Magn Reson Imaging. 2007. PMID: 17451904 Review.
Cited by
- Chronic brain functional ultrasound imaging in freely moving rodents performing cognitive tasks.
El Hady A, Takahashi D, Sun R, Akinwale O, Boyd-Meredith T, Zhang Y, Charles AS, Brody CD. El Hady A, et al. J Neurosci Methods. 2024 Mar;403:110033. doi: 10.1016/j.jneumeth.2023.110033. Epub 2023 Dec 4. J Neurosci Methods. 2024. PMID: 38056633 Free PMC article. - Unsupervised physiological noise correction of functional magnetic resonance imaging data using phase and magnitude information (PREPAIR).
Bancelin D, Bachrata B, Bollmann S, de Lima Cardoso P, Szomolanyi P, Trattnig S, Robinson SD. Bancelin D, et al. Hum Brain Mapp. 2023 Feb 15;44(3):1209-1226. doi: 10.1002/hbm.26152. Epub 2022 Nov 19. Hum Brain Mapp. 2023. PMID: 36401844 Free PMC article. - WHOCARES: WHOle-brain CArdiac signal REgression from highly accelerated simultaneous multi-Slice fMRI acquisitions.
Colenbier N, Marino M, Arcara G, Frederick B, Pellegrino G, Marinazzo D, Ferrazzi G. Colenbier N, et al. J Neural Eng. 2022 Sep 6;19(5):10.1088/1741-2552/ac8bff. doi: 10.1088/1741-2552/ac8bff. J Neural Eng. 2022. PMID: 35998568 Free PMC article. - NRM 2021 Abstract Booklet.
[No authors listed] [No authors listed] J Cereb Blood Flow Metab. 2021 Dec;41(1_suppl):11-309. doi: 10.1177/0271678X211061050. J Cereb Blood Flow Metab. 2021. PMID: 34905986 Free PMC article. No abstract available. - Intrinsic network activity reflects the ongoing experience of chronic pain.
Jahn P, Deak B, Mayr A, Stankewitz A, Keeser D, Griffanti L, Witkovsky V, Irving S, Schulz E. Jahn P, et al. Sci Rep. 2021 Nov 8;11(1):21870. doi: 10.1038/s41598-021-01340-0. Sci Rep. 2021. PMID: 34750460 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Research Materials
Miscellaneous