{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T14:21:34Z","timestamp":1762957294698,"version":"3.41.2"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T00:00:00Z","timestamp":1695772800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neuroinform."],"abstract":"<jats:p>Neuroimaging research requires sophisticated tools for analyzing complex data, but efficiently leveraging these tools can be a major challenge, especially on large datasets. CBRAIN is a web-based platform designed to simplify the use and accessibility of neuroimaging research tools for large-scale, collaborative studies. In this paper, we describe how CBRAIN\u2019s unique features and infrastructure were leveraged to integrate TAPAS PhysIO, an open-source MATLAB toolbox for physiological noise modeling in fMRI data. This case study highlights three key elements of CBRAIN\u2019s infrastructure that enable streamlined, multimodal tool integration: a user-friendly GUI, a Brain Imaging Data Structure (BIDS) data-entry schema, and convenient in-browser visualization of results. By incorporating PhysIO into CBRAIN, we achieved significant improvements in the speed, ease of use, and scalability of physiological preprocessing. Researchers now have access to a uniform and intuitive interface for analyzing data, which facilitates remote and collaborative evaluation of results. With these improvements, CBRAIN aims to become an essential open-science tool for integrative neuroimaging research, supporting FAIR principles and enabling efficient workflows for complex analysis pipelines.<\/jats:p>","DOI":"10.3389\/fninf.2023.1251023","type":"journal-article","created":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T09:31:52Z","timestamp":1695893512000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN"],"prefix":"10.3389","volume":"17","author":[{"given":"Darius","family":"Valevicius","sequence":"first","affiliation":[]},{"given":"Natacha","family":"Beck","sequence":"additional","affiliation":[]},{"given":"Lars","family":"Kasper","sequence":"additional","affiliation":[]},{"given":"Sergiy","family":"Boroday","sequence":"additional","affiliation":[]},{"given":"Johanna","family":"Bayer","sequence":"additional","affiliation":[]},{"given":"Pierre","family":"Rioux","sequence":"additional","affiliation":[]},{"given":"Bryan","family":"Caron","sequence":"additional","affiliation":[]},{"given":"Reza","family":"Adalat","sequence":"additional","affiliation":[]},{"given":"Alan C.","family":"Evans","sequence":"additional","affiliation":[]},{"given":"Najmeh","family":"Khalili-Mahani","sequence":"additional","affiliation":[]}],"member":"1965","published-online":{"date-parts":[[2023,9,27]]},"reference":[{"volume-title":"SPM12 Manual","year":"2021","author":"Ashburner","key":"ref1"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"864","DOI":"10.1016\/j.neuroimage.2012.01.016","article-title":"The role of physiological noise in resting-state functional connectivity","volume":"62","author":"Birn","year":"2012","journal-title":"NeuroImage"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"1536","DOI":"10.1016\/j.neuroimage.2006.02.048","article-title":"Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI","volume":"31","author":"Birn","year":"2006","journal-title":"NeuroImage"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1016\/j.neuroimage.2007.11.059","article-title":"The respiration response function: the temporal dynamics of fMRI signal fluctuations related to changes in respiration","volume":"40","author":"Birn","year":"2008","journal-title":"NeuroImage"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1016\/j.neuroimage.2016.12.027","article-title":"Potential pitfalls when denoising resting state fMRI data using nuisance regression","volume":"154","author":"Bright","year":"2017","journal-title":"NeuroImage"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.dcn.2018.03.001","article-title":"The adolescent brain cognitive development (ABCD) study: imaging acquisition across 21 sites","volume":"32","author":"Casey","year":"2018","journal-title":"Dev. 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