xcp_d.utils.boilerplate module

Functions for generating boilerplate code.

xcp_d.utils.boilerplate.describe_atlases(atlases)

Build a text description of the atlases that will be used.

xcp_d.utils.boilerplate.describe_censoring(motion_filter_type, fd_thresh, exact_scans)

Build a text description of the FD censoring process.

Parameters:

• motion_filter_type ({None, “lp”, “notch”}) – Type of filter to use for removing respiratory artifact from motion regressors.

  If None, no filter will be applied.

  If the filter type is set to “notch”, frequencies between band_stop_min and band_stop_max will be removed with a notch filter. In this case, both band_stop_min and band_stop_max must be defined.

  If “lp”, frequencies above band_stop_min will be removed with a Butterworth filter. In this case, only band_stop_min must be defined.

• fd_thresh (float) – Framewise displacement threshold for censoring, in millimeters. Any framewise displacement values higher than the threshold are flagged as “high motion”. If set to <=0, no censoring will be performed. Default is 0.2 mm.

• exact_scans (list of int, optional) – If used, this parameter will produce correlation matrices limited to each requested amount of time. If there is more than the required amount of low-motion data, then volumes will be randomly selected to produce denoised outputs with the exact amounts of time requested. If there is less than the required amount of ‘good’ data, then the run will not be post-processed.

Returns:

desc – A text description of the censoring procedure.

Return type:

str

xcp_d.utils.boilerplate.describe_motion_parameters(*, motion_filter_type, motion_filter_order, band_stop_min, band_stop_max, head_radius, TR)

Build a text description of the motion parameter filtering and FD calculation process.

Parameters:

• motion_filter_type ({None, “lp”, “notch”}) – Type of filter to use for removing respiratory artifact from motion regressors.

  If None, no filter will be applied.

  If the filter type is set to “notch”, frequencies between band_stop_min and band_stop_max will be removed with a notch filter. In this case, both band_stop_min and band_stop_max must be defined.

  If “lp”, frequencies above band_stop_min will be removed with a Butterworth filter. In this case, only band_stop_min must be defined.

• motion_filter_order (int) – Number of filter coefficients for the motion parameter filter. Motion filtering is only performed if motion_filter_type is not None. This parameter is used in conjunction with band_stop_max and band_stop_min.

• band_stop_min (float or None) – Lower frequency for the motion parameter filter, in breaths-per-minute (bpm). Motion filtering is only performed if motion_filter_type is not None. If used with the “lp” motion_filter_type, this parameter essentially corresponds to a low-pass filter (the maximum allowed frequency in the filtered data). This parameter is used in conjunction with motion_filter_order and band_stop_max.

  Here is a list of recommended values, based on participant age:

  Age Range (years)	Recommended Value
  < 1	30
  1 - 2	25
  2 - 6	20
  6 - 12	15
  12 - 18	12
  19 - 65	12
  65 - 80	12
  > 80	10

  When motion_filter_type is set to “lp” (low-pass filter), another commonly-used value for this parameter is 6 BPM (equivalent to 0.1 Hertz), based on Gratton et al.[1].

• band_stop_max (float or None) – Upper frequency for the motion parameter filter, in breaths-per-minute (bpm). Motion filtering is only performed if motion_filter_type is not None. This parameter is only used if motion-filter-type is set to “notch”. This parameter is used in conjunction with motion_filter_order and band_stop_min.

  Here is a list of recommended values, based on participant age:

  Age Range (years)	Recommended Value
  < 1	60
  1 - 2	50
  2 - 6	35
  6 - 12	25
  12 - 18	20
  19 - 65	18
  65 - 80	28
  > 80	30

• head_radius (float or “auto”) – Radius of the head, in millimeters, for framewise displacement calculation.

  xcp_d’s default head radius is 50. The recommended value for infants is 35. A value of ‘auto’ is also supported, in which case the brain radius is estimated from the preprocessed brain mask.

• TR (float) – Repetition time of the BOLD run, in seconds.

Returns:

desc – A text description of the motion parameters.

Return type:

str

xcp_d.utils.boilerplate.describe_regression(params, custom_confounds_file, motion_filter_type)

Build a text description of the regression that will be performed.

Parameters:

• params ({“36P”, “24P”, “27P”, “acompcor”, “acompcor_gsr”, “aroma”, “aroma_gsr”, “custom”}, optional) – Shorthand for the parameter set to extract from the confounds TSV. Default is “36P”, most expansive option.

• custom_confounds_file (str or None) – Path to custom nuisance regressors.

• motion_filter_type ({None, “lp”, “notch”}) – Type of filter to use for removing respiratory artifact from motion regressors.

  If None, no filter will be applied.

  If the filter type is set to “notch”, frequencies between band_stop_min and band_stop_max will be removed with a notch filter. In this case, both band_stop_min and band_stop_max must be defined.

  If “lp”, frequencies above band_stop_min will be removed with a Butterworth filter. In this case, only band_stop_min must be defined.

Returns:

desc – A text description of the regression.

Return type:

str