{ "BIDSVersion": "1.5.0", "DatasetType": "derivative", "GeneratedBy": [ { "CodeURL": "https://github.com/ME-ICA/tedana", "Command": "tedana_workflow(data=['/nox1/data/WELL22/ImagingData/BIDS/UCLABMC/ImagingData/SubjectsRESTSBREF_tedana_derivatives/reduced_files/sub-OPT0047_ses-01_task-REST_dir-AP_echo-1_desc-preproc_bold.nii.gz', '/nox1/data/WELL22/ImagingData/BIDS/UCLABMC/ImagingData/SubjectsRESTSBREF_tedana_derivatives/reduced_files/sub-OPT0047_ses-01_task-REST_dir-AP_echo-2_desc-preproc_bold.nii.gz', '/nox1/data/WELL22/ImagingData/BIDS/UCLABMC/ImagingData/SubjectsRESTSBREF_tedana_derivatives/reduced_files/sub-OPT0047_ses-01_task-REST_dir-AP_echo-3_desc-preproc_bold.nii.gz', '/nox1/data/WELL22/ImagingData/BIDS/UCLABMC/ImagingData/SubjectsRESTSBREF_tedana_derivatives/reduced_files/sub-OPT0047_ses-01_task-REST_dir-AP_echo-4_desc-preproc_bold.nii.gz'], tes=[15.6, 38.2, 60.8, 83.4], out_dir=/nox1/data/WELL22/ImagingData/BIDS/UCLABMC/ImagingData/SubjectsRESTSBREF_tedana_derivatives/sub-OPT0047/ses-01/func/sub-OPT0047_ses-01_task-REST_dir-AP, mask=/nox1/data/WELL22/ImagingData/BIDS/UCLABMC/ImagingData/SubjectsRESTSBREF_23.2.3_derivatives/sub-OPT0047/ses-01/func/sub-OPT0047_ses-01_task-REST_dir-AP_desc-brain_mask.nii.gz, convention=bids, prefix=sub-OPT0047_ses-01_task-REST_dir-AP_, masktype=['dropout'], fittype=curvefit, combmode=t2s, tree=tedana_orig, tedpca=75, fixed_seed=42, maxit=500, maxrestart=10, tedort=True, gscontrol=None, no_reports=False, png_cmap=coolwarm, verbose=False, low_mem=False, debug=False, quiet=False, overwrite=False, t2smap=None, mixm=None)", "Description": "A denoising pipeline for the identification and removal of non-BOLD noise from multi-echo fMRI data.", "Name": "tedana", "Node": { "Machine": "x86_64", "Name": "nox", "Processor": "x86_64", "Release": "5.15.0-101-generic", "System": "Linux", "Version": "#111-Ubuntu SMP Tue Mar 5 20:16:58 UTC 2024" }, "Python": "3.11.9 | packaged by conda-forge | (main, Apr 19 2024, 18:36:13) [GCC 12.3.0]", "Python_Libraries": { "bokeh": "3.4.1", "mapca": "0.0.5", "matplotlib": "3.9.1", "nibabel": "5.2.1", "nilearn": "0.10.4", "numpy": "1.26.4", "pandas": "2.2.2", "scikit-learn": "1.4.2", "scipy": "1.13.0", "threadpoolctl": "3.5.0" }, "Version": "24.0.1" } ], "Name": "tedana Outputs" }