cmp.pipelines.functional.fMRI module
Functional pipeline Class definition.
- class cmp.pipelines.functional.fMRI.GlobalConfig[source]
Bases:
traits.has_traits.HasTraitsGlobal pipeline configurations.
- process_type
Processing pipeline type
- Type
‘fMRI’
- imaging_model
Imaging model used by
RegistrationStage- Type
‘fMRI’
- class cmp.pipelines.functional.fMRI.fMRIPipeline(project_info)[source]
Bases:
cmp.pipelines.common.PipelineClass that extends a
Pipelineand represents the processing pipeline for structural MRI.- It is composed of:
the preprocessing stage that can perform slice timing correction, deskiping and motion correction
the registration stage that co-registered the anatomical T1w scan to the mean BOLD image and projects the parcellations to the native fMRI space
the extra-preprocessing stage (FunctionalMRIStage) that can perform nuisance regression and bandpass filtering
the connectome stage that extracts the time-series of each parcellation ROI and computes the Pearson’s correlation coefficient between ROI time-series to create the functional connectome.
See also
cmp.stages.preprocessing.fmri_preprocessing.PreprocessingStage,cmp.stages.registration.registration.RegistrationStage,cmp.stages.functional.functionalMRI.FunctionalMRIStage,cmp.stages.connectome.fmri_connectome.ConnectomeStage- check_config()[source]
Check if the fMRI pipeline parameters is properly configured.
- Returns
message – String that is empty if success, otherwise it contains the error message
- Return type
string
- check_input(layout, gui=True)[source]
Check if input of the diffusion pipeline are available.
- Parameters
layout (bids.BIDSLayout) – Instance of BIDSLayout
gui (traits.Bool) – Boolean used to display different messages but not really meaningful anymore since the GUI components have been migrated to
cmp.bidsappmanager
- Returns
valid_inputs – True if inputs are available
- Return type
traits.Bool
- create_datagrabber_node(base_directory, bids_atlas_label)[source]
Create the appropriate Nipype DataGrabber node depending on the
parcellation_scheme- Parameters
base_directory (Directory) – Main CMP output directory of a subject e.g.
/output_dir/cmp/sub-XX/(ses-YY)bids_atlas_label (string) – Parcellation atlas label
- Returns
datasource – Output Nipype Node with
DataGrabberinterface- Return type
Output Nipype DataGrabber Node
- create_datasinker_node(base_directory, bids_atlas_label)[source]
Create the appropriate Nipype DataSink node depending on the
parcellation_scheme- Parameters
base_directory (Directory) – Main CMP output directory of a subject e.g.
/output_dir/cmp/sub-XX/(ses-YY)bids_atlas_label (string) – Parcellation atlas label
- Returns
sinker – Output Nipype Node with
DataSinkinterface- Return type
Output Nipype DataSink Node
- create_pipeline_flow(cmp_deriv_subject_directory, nipype_deriv_subject_directory)[source]
Create the pipeline workflow.
- Parameters
cmp_deriv_subject_directory (Directory) – Main CMP output directory of a subject e.g.
/output_dir/cmp/sub-XX/(ses-YY)nipype_deriv_subject_directory (Directory) – Intermediate Nipype output directory of a subject e.g.
/output_dir/nipype/sub-XX/(ses-YY)
- Returns
fMRI_flow – An instance of
nipype.pipeline.engine.Workflow- Return type
nipype.pipeline.engine.Workflow
- define_custom_mapping(custom_last_stage)[source]
Define the pipeline to be executed until a specific stages.
Not used yet by CMP3.
- Parameters
custom_last_stage (string) – Last stage to execute. Valid values are: “Preprocessing”, “Registration”, “FunctionalMRI” and “Connectome”.
- global_conf = <cmp.pipelines.functional.fMRI.GlobalConfig object>
- init_subject_derivatives_dirs()[source]
Return the paths to Nipype and CMP derivatives folders of a given subject / session.
Notes
self.subjectis updated to “sub-<participant_label>_ses-<session_label>” when subject has multiple sessions.
- input_folders = ['anat', 'func']
- now = '20221025_1359'
- ordered_stage_list = ['Preprocessing', 'Registration', 'FunctionalMRI', 'Connectome']