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Principal component analysis (PCA)-based techniques, which derive regressors from a noise region of interest (ROI), have been used in both brain (e.g., CompCor) and spinal cord fMRI. However, spinal cord fMRI denoising methods have yet to be systematically evaluated. Here, we formalize and evaluate a PCA-based technique for deriving nuisance regressors for spinal cord fMRI analysis (SpinalCompCor). In this method, regressors are derived with PCA from a noise ROI, an area defined outside of the spinal cord and cerebrospinal fluid. A parallel analysis is used to systematically determine how many components to retain as regressors for modeling; this designated a median of 9 regressors across four fMRI datasets: motor task (n = 26), breathing task (n = 27), and resting state (n = 15 and n = 10). First-level fMRI modeling demonstrated that principal component regressors did fit noise (e.g., physiological noise from blood vessels), though the effectiveness may be dependent upon the acquisition parameters. However, group-level activation maps did not show a clear benefit from including SpinalCompCor regressors. The potential for collinearity of principal component regressors with the task may be a concern, and this should be considered in future implementations for which task-correlated noise is anticipated. In general, denoising with SpinalCompCor regressors in place of physiological recording-derived regressors is only recommended when the latter are unavailable, as SpinalCompCor may not consistently reproduce recording-based denoising across datasets or acquisitions.<\/jats:p>","DOI":"10.1162\/imag.a.1143","type":"journal-article","created":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T20:01:31Z","timestamp":1770062491000},"update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":0,"title":["Data-driven denoising in spinal cord fMRI with principal component analysis"],"prefix":"10.1162","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9913-492X","authenticated-orcid":false,"given":"Kimberly J.","family":"Hemmerling","sequence":"first","affiliation":[{"name":"Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States"},{"name":"Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3166-0688","authenticated-orcid":false,"given":"Andrew D.","family":"Vigotsky","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States"},{"name":"Department of Statistics & Data Science, Weinberg College of Arts and Sciences, Northwestern University, Evanston, IL, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charlotte","family":"Glanville","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert L.","family":"Barry","sequence":"additional","affiliation":[{"name":"Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States"},{"name":"Harvard Medical School, Boston, MA, United States"},{"name":"Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7257-9646","authenticated-orcid":false,"given":"Molly G.","family":"Bright","sequence":"additional","affiliation":[{"name":"Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States"},{"name":"Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","published-online":{"date-parts":[[2026,2,20]]},"reference":[{"key":"2026022014553664900_IMAG.a.1143-b1","doi-asserted-by":"crossref","DOI":"10.1162\/IMAG.a.98","article-title":"EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data","volume":"3","author":"Banerjee","year":"2025","journal-title":"Imaging Neuroscience"},{"issue":"1","key":"2026022014553664900_IMAG.a.1143-b2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-34841-6","article-title":"A practical protocol for measurements of spinal cord functional connectivity","volume":"8","author":"Barry","year":"2018","journal-title":"Scientific Reports"},{"key":"2026022014553664900_IMAG.a.1143-b3","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.neuroimage.2016.02.058","article-title":"Reproducibility of resting state spinal cord networks in healthy volunteers at 7 Tesla","volume":"133","author":"Barry","year":"2016","journal-title":"NeuroImage"},{"key":"2026022014553664900_IMAG.a.1143-b4","doi-asserted-by":"crossref","first-page":"e02812","DOI":"10.7554\/eLife.02812","article-title":"Resting state functional connectivity in the human spinal cord","volume":"3","author":"Barry","year":"2014","journal-title":"ELife"},{"issue":"1","key":"2026022014553664900_IMAG.a.1143-b5","first-page":"90","article-title":"A component based noise correction method (CompCor) for BOLD and perfusion based fMRI","volume":"37","author":"Behzadi","year":"2007","journal-title":"Human Brain Mapping Journal"},{"issue":"18","key":"2026022014553664900_IMAG.a.1143-b6","doi-asserted-by":"crossref","first-page":"6471","DOI":"10.1002\/hbm.26523","article-title":"Association between activity in the ventral premotor cortex and spinal cord activation during force generation\u2014A combined cortico-spinal fMRI study","volume":"44","author":"Braa\u00df","year":"2023","journal-title":"Human Brain Mapping"},{"issue":"2","key":"2026022014553664900_IMAG.a.1143-b7","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1016\/j.neuroimage.2007.09.018","article-title":"Physiological noise modelling for spinal functional magnetic resonance imaging studies","volume":"39","author":"Brooks","year":"2008","journal-title":"NeuroImage"},{"key":"2026022014553664900_IMAG.a.1143-b8","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.neuroimage.2016.12.018","article-title":"Methods for cleaning the BOLD fMRI signal","volume":"154","author":"Caballero-Gaudes","year":"2017","journal-title":"NeuroImage"},{"issue":"1","key":"2026022014553664900_IMAG.a.1143-b9","doi-asserted-by":"crossref","first-page":"18189","DOI":"10.1038\/s41598-023-45302-0","article-title":"Detection of resting-state functional connectivity in the lumbar spinal cord with 3T MRI","volume":"13","author":"Combes","year":"2023","journal-title":"Scientific Reports"},{"key":"2026022014553664900_IMAG.a.1143-b10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1162\/imag_a_00273","article-title":"Reliability of task-based fMRI in the dorsal horn of the human spinal cord","volume":"2","author":"Dabbagh","year":"2024","journal-title":"Imaging Neuroscience"},{"key":"2026022014553664900_IMAG.a.1143-b11","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.neuroimage.2017.10.041","article-title":"PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space","volume":"165","author":"De Leener","year":"2018","journal-title":"NeuroImage"},{"key":"2026022014553664900_IMAG.a.1143-b12","doi-asserted-by":"crossref","unstructured":"Deshpande, R., & Barry, R. 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