• ICA_PNM

Overview

ICA-PNM de-noising pipeline combines noise regressors identified by tools such as PNM and ICA (and FIX) and effectively prepares them for entry into a single FEAT model, thus allowing the user to clean their data in a single step. Note that it is essential to combine PNM and ICA into a single regression step, rather than performing them separately. The reason for this is that variance can be reintroduced into the “cleaned” data if regressions are performed separately.

Pre-processing

• Before combining your sources of noise you should follow the relevant pipelines for PNM and MELODIC, including pre-processing steps such as motion correction, registration and smoothing, and have ready their respective output files along with any other noise time series information you may wish to include

Stripping noise from ICA time series

• The final line of your ICA-labels file contains the numbers of all noise components. This file is obtained either via manual classification using FSLeyes, or from automated classification using ICA-FIX or ICA-AROMA.

• These numbers can be used to index the file containing the time-series information for each component – ordinarily named melodic_Tmodes, located within the filtered_func_data.ica folder of your MELODIC directory. To run ICA-PNM clean up, we need to generate a file that contains only the noise component timecourses from melodic_Tmodes. This new noise time series text file (named for example: ICA_noise.txt) should be space separated. In addition to ICA identified noise components, signal associated with white matter, CSF or motion outliers can also be appended to this text file. You can use the fsl_ENTS functionality to achieve this should you wish to.

Inputting the noise text files into your model

• If you have carried out both PNM and ICA you should now have 2 text files – one for your PNM noise output, which should be input into the Voxel Confound List in FEAT.

And one containing the time series information of ICA noise components along with any other sources of noise that you wish to model. This file should be space delimited and should be input into the Add additional confound EVs box. The input within the data tab should be your raw data and FEAT can be run from scratch, including all pre-processing steps.

The model

• The PNM noise text tile and FIX noise text file have been combined by FEAT and input into your model as one long series of regressors of no interest. Many of these components are likely to not be independent and therefore we do not expect the degrees of freedom to be overly reduced.

• If resting state data are entered into the ICA-PNM pipeline, there will be no task EVs in the model. In this case, res4d.nii.gz file obtained from running Feat as described above is the ‘cleaned’ data, which can be used for subsequent resting state analysis

Referencing

If you use fsl_ENTS in your research, please make sure that you reference at least the first of the articles listed below, and ideally the complete list. .