workflows.rsfmri.fsl.resting

create_realign_flow()

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Realign a time series to the middle volume using spline interpolation

Uses MCFLIRT to realign the time series and ApplyWarp to apply the rigid body transformations using spline interpolation (unknown order).

Example

>>> wf = create_realign_flow()
>>> wf.inputs.inputspec.func = 'f3.nii'
>>> wf.run()

Graph

digraph realign{ label="realign"; realign_inputspec[label="inputspec (utility)"]; realign_realigner[label="realigner (fsl)"]; realign_splitter[label="splitter (fsl)"]; realign_warper[label="warper (fsl)"]; realign_joiner[label="joiner (fsl)"]; realign_outputspec[label="outputspec (utility)"]; realign_inputspec -> realign_realigner; realign_inputspec -> realign_realigner; realign_realigner -> realign_splitter; realign_realigner -> realign_warper; realign_realigner -> realign_warper; realign_splitter -> realign_warper; realign_warper -> realign_joiner; realign_joiner -> realign_outputspec; }

create_resting_preproc()

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Create a “resting” time series preprocessing workflow

The noise removal is based on Behzadi et al. (2007)

Parameters

name : name of workflow (default: restpreproc)

Inputs:

inputspec.func : functional run (filename or list of filenames)

Outputs:

outputspec.noise_mask_file : voxels used for PCA to derive noise components
outputspec.filtered_file : bandpass filtered and noise-reduced time series

Example

>>> TR = 3.0
>>> wf = create_resting_preproc()
>>> wf.inputs.inputspec.func = 'f3.nii'
>>> wf.inputs.inputspec.num_noise_components = 6
>>> wf.inputs.inputspec.highpass_sigma = 100/(2*TR)
>>> wf.inputs.inputspec.lowpass_sigma = 12.5/(2*TR)
>>> wf.run()

Graph

digraph restpreproc{ label="restpreproc"; restpreproc_inputspec[label="inputspec (utility)"]; restpreproc_slicetimer[label="slicetimer (fsl)"]; restpreproc_tsnr[label="tsnr (misc)"]; restpreproc_getthreshold[label="getthreshold (fsl)"]; restpreproc_threshold[label="threshold (fsl)"]; restpreproc_compcorr[label="compcorr (utility)"]; restpreproc_remove_noise[label="remove_noise (fsl)"]; restpreproc_bandpass_filter[label="bandpass_filter (fsl)"]; restpreproc_outputspec[label="outputspec (utility)"]; restpreproc_inputspec -> restpreproc_bandpass_filter; restpreproc_inputspec -> restpreproc_bandpass_filter; restpreproc_inputspec -> restpreproc_slicetimer; restpreproc_inputspec -> restpreproc_compcorr; subgraph cluster_restpreproc_realign { label="realign"; restpreproc_realign_inputspec[label="inputspec (utility)"]; restpreproc_realign_realigner[label="realigner (fsl)"]; restpreproc_realign_splitter[label="splitter (fsl)"]; restpreproc_realign_warper[label="warper (fsl)"]; restpreproc_realign_joiner[label="joiner (fsl)"]; restpreproc_realign_outputspec[label="outputspec (utility)"]; restpreproc_realign_inputspec -> restpreproc_realign_realigner; restpreproc_realign_inputspec -> restpreproc_realign_realigner; restpreproc_realign_realigner -> restpreproc_realign_warper; restpreproc_realign_realigner -> restpreproc_realign_warper; restpreproc_realign_realigner -> restpreproc_realign_splitter; restpreproc_realign_splitter -> restpreproc_realign_warper; restpreproc_realign_warper -> restpreproc_realign_joiner; restpreproc_realign_joiner -> restpreproc_realign_outputspec; } restpreproc_tsnr -> restpreproc_getthreshold; restpreproc_tsnr -> restpreproc_threshold; restpreproc_tsnr -> restpreproc_remove_noise; restpreproc_getthreshold -> restpreproc_threshold; restpreproc_threshold -> restpreproc_outputspec; restpreproc_threshold -> restpreproc_compcorr; restpreproc_compcorr -> restpreproc_remove_noise; restpreproc_remove_noise -> restpreproc_bandpass_filter; restpreproc_bandpass_filter -> restpreproc_outputspec; restpreproc_slicetimer -> restpreproc_realign_inputspec; restpreproc_realign_outputspec -> restpreproc_tsnr; restpreproc_realign_outputspec -> restpreproc_compcorr; }

extract_noise_components()

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Derive components most reflective of physiological noise

select_volume()

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Return the middle index of a file