Skip to content

dowdlelt/meica_tool

Folders and files

NameName
Last commit message
Last commit date

Latest commit

4e1d532 · Apr 5, 2021

History

43 Commits
Mar 10, 2017
Mar 10, 2017
Sep 22, 2017
Sep 22, 2017
Apr 5, 2021
Mar 10, 2017
Mar 10, 2017
Feb 5, 2019
Feb 5, 2019
Mar 17, 2017
Mar 17, 2017

Repository files navigation

These images are now produced in tedana, which can be found here: https://github.com/ME-ICA/tedana

This "toolbox" is no longer maintained, updated and may not even work anymore. The figures are produced by default in the much improved multi-echo denoising package tedana.

meica_tool

I've created a handy matlab script that works with meica.py (https://bitbucket.org/prantikk/me-ica) v3 - from the experimental branch.

It creates a series of figures that are useful for visualizing the output in a quick manner, including component timeseries from meica.py, color coded on whether they were:

  • BOLD-like - green
  • Non-BOLD - red
  • r2 weighted - pink
  • Ignored - black.

2017/09/22 update - now more 4ier - enjoy a fft plot.

Each plot includes brain slices of the component beta values (from TED/betas_OC.nii)

  • motion parameters and framewise displacement
  • kappa vs rho scatter plot, where size is proportaional to variance, colors as above
  • kappa vs rho line plot
  • Bar plot of variance explained
  • tSNR figures, with histograms

It then creates a bar plot showing the relative variance of each of those categories.

Its (still) ugly code, but effective...for now.

Current dependencies include:

But these few functions will eventually be packaged together and included.

Usage

  • Add to matlab path
  • run meica_component_displayer(tr), where tr is the repitition of your EPI timeseries in seconds.
  • select the meica.py output folder, ex. meica_nback_e1.label
  • wait a bit

Example Figures Kappa vs Rho plot Kappa vs Rho Scatter Timeseries and brains Noise even!

Thanks to bramila framewise displacement and detrend code (from https://git.becs.aalto.fi/bml/bramila/tree/master) for dvars calculation