Home · Quickstart · Documentation · Citation · NiPy

# workflows.rsfmri.fsl.resting

## `create_realign_flow()`

Link to code

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

## `create_resting_preproc()`

Link to code

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

## `extract_noise_components()`

Link to code

Derive components most reflective of physiological noise

## `select_volume()`

Link to code

Return the middle index of a file