LNCD

Table of Contents

  • LNCD Home
  • Administration
  • Notebooks
  • Journal Club Presentations
  • Publications
  • Current Projects
  • Completed Projects
  • Current Grants
  • Datasets by Project
  • Brain ROIs and Measures
  • ️Tools And Methods
  • Big Data
  • RA Homepage
  • Recent Changes
  • Maintenance
  • Site Map
  • Random Page
LNCD
Docs » Preprocess Functional (Hallquist pipeline)

Preprocess Functional (Hallquist pipeline)

  • https://github.com/LabNeuroCogDevel/fmri_processing_scripts
  • https://zenodo.org/badge/latestdoi/5274327

Developed by Michael Hallquist

Output 4D nifti prefix

As the pipeline progresses it outputs files with distinct prefixes that describe each step in reverse order. e.g. final output might be brnwsdktm_func_4.nii.gz where motion correction was the first preproc step preformed and bandpassing the last.

br bandpass and nuisance regresssion (simultaneous to not re-intro noise from one to the other) – used in resting state
f high pass filter. used for task (cf. b full bandpass)
n voxel normliazation (prob to 1000*x/median)
s smoothing. also prepends the FWHM size to the end (_4)
w warp (“spatial normalization”). likely to MNI 2009c Asym template
d despike (with wavelets)
k skull strip
t slice time correct. usually done at the same time as motion below (via 4dslicealign.py)
m motion: realign (6dof affine – trans and rot) every timepoint to the mean so a voxel is in the same spot over time
Previous Next