{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["12(3)"],"submitter":["Dipasquale O"],"pubmed_abstract":["Artifact removal in resting state fMRI (rfMRI) data remains a serious challenge, with even subtle head motion undermining reliability and reproducibility. Here we compared some of the most popular single-echo de-noising methods-regression of Motion parameters, White matter and Cerebrospinal fluid signals (MWC method), FMRIB's ICA-based X-noiseifier (FIX) and ICA-based Automatic Removal Of Motion Artifacts (ICA-AROMA)-with a multi-echo approach (ME-ICA) that exploits the linear dependency of BOLD on the echo time. Data were acquired using a clinical scanner and included 30 young, healthy participants (minimal head motion) and 30 Attention Deficit Hyperactivity Disorder patients (greater head motion). De-noising effectiveness was assessed in terms of data quality after each cleanup procedure"],"journal":["PloS one"],"pagination":["e0173289"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC5360253"],"repository":["biostudies-literature"],"pubmed_title":["Comparing resting state fMRI de-noising approaches using multi- and single-echo acquisitions."],"pmcid":["PMC5360253"],"pubmed_authors":["Baglio F","Kundu P","Sethi A","Lagana MM","Dipasquale O","Cercignani M","Baselli G","Harrison NA"],"additional_accession":[]},"is_claimable":false,"name":"Comparing resting state fMRI de-noising approaches using multi- and single-echo acquisitions.","description":"Artifact removal in resting state fMRI (rfMRI) data remains a serious challenge, with even subtle head motion undermining reliability and reproducibility. Here we compared some of the most popular single-echo de-noising methods-regression of Motion parameters, White matter and Cerebrospinal fluid signals (MWC method), FMRIB's ICA-based X-noiseifier (FIX) and ICA-based Automatic Removal Of Motion Artifacts (ICA-AROMA)-with a multi-echo approach (ME-ICA) that exploits the linear dependency of BOLD on the echo time. Data were acquired using a clinical scanner and included 30 young, healthy participants (minimal head motion) and 30 Attention Deficit Hyperactivity Disorder patients (greater head motion). De-noising effectiveness was assessed in terms of data quality after each cleanup procedure","dates":{"release":"2017-01-01T00:00:00Z","publication":"2017","modification":"2025-04-04T12:40:09.586Z","creation":"2019-03-26T22:49:45Z"},"accession":"S-EPMC5360253","cross_references":{"pubmed":["28323821"],"doi":["10.1371/journal.pone.0173289"]}}