Neuroscan 32-channel files error upload in Brainstorm

Hello. uploading 3 files from Neuroscan recording.

https://neuroimage.usc.edu/forums/t/problem-importiAcquisition 01.dap (3.8 KB)
Acquisition 01.rs3 (4.6 KB)
ng-eeglab-pre-processed-epochs/8316/2

There are only two files linked in your message.
What would you like me to do with these files?

Francois,

Got it working buy using Curry (*.dat, .cdt) instead of using Neuroscan (.dat). However, I can't seem to work on averaging 2-minute recordings as I can't see the average feature in the pipeline editor.

You need to epoch these files before averaging them (import segments of them in your database).
I recommend you start by following the introduction tutorials (section “Get started” until #19) and the tutorial "EEG and Epilepsy), using the example datasets provided, before you try processing your own recordings. You will save a lot of time by getting a proper training instead of losing time trying things by yourself.
https://neuroimage.usc.edu/brainstorm/Tutorials

Francois,

In our experiment, we asked our participants to breath normally or undergo paced breathing and took 2-minute recording. Thus, I think it’s not possible for us to establish epochs (not sure on this). Is it possible to get 200 ms data after each spike in ECG (evoked related potential)? Thank you very much for your assistance.

Cheers

Yes, you could, if you are interested in the signal components (artifacts and brain activity) related with the heartbeats.

Note that if you do not epoch your recordings based on a precise time reference, it does not make sense to average multiple recording blocks. If you various recording sessions are already synchronized, you can simply import the entire recordings to the database (menu Import MEG/EEG, disable the option “Use events”), and then average them.

Thank you very much for this. We’re interested in determining 180-240 ms block after each R-peak from a 10-minute recording. We are comparing normal breathing with paced breathing. How do you do this?

Managed to average multiple recordings and will soon compare EEG from different frequencies (e.g. alpha, theta). Thanks again.

Cheers

I think all you want to do is part of the introduction tutorials:
https://neuroimage.usc.edu/brainstorm/Tutorials/ArtifactsDetect#Detection:_Heartbeats

Thank you very much for this. Appreciate your help!

Francois,

How are you doing? In our experiment, we only used one channel for VEOG and one channel for ECG. When we applied SSP, there’s a warning that SSP may not be accurate using few sensors. Is there an alternative for this? Thanks.

Cheers

I don’t recommend using SSP cleaning on such a low number of EEG signals (and I don’t recommend it for EEG in general). Prefer an ICA decomposition:
https://neuroimage.usc.edu/brainstorm/Tutorials/Epilepsy#Artifact_cleaning_with_ICA

Thank you again. Here are my steps:

  1. upload raw file
  2. perform ICA (34 EEG channels not 32 as said before)
  3. band filter (0.5 to 35 Hz)
  4. Detect event: Heartbeat
  5. Perform event related potential (Heart evoked potential)

Cheers

If you are interested by heart evoked potentials, you are probably averaging a lot of data (several hundreds of trials). In this context, all the noise is probably going away without any pre-processing (except maybe for the high-pass filter).
You could try for one subject to reproduce the same analysis without ICA and without low-pass filter, and see if you get similar results. A general recommendation is to limit the number of pre-processing steps strictly to the minimum required for the analysis you want to perform.

Thank you for this. I’ve tried the following:
ICA, low-pass filter, high-pass filter
No ICA, low-pass filter, high-pass filter
No ICA, NO low-pass filter, high-pass filter

Values from the first and second were somehow similar. Maybe I’ll use the second option. Really grateful for your inputs.

All Best