[Eeglablist] Preprocessing suggestions

[ivano triggiani]

Ciao Chiara,

In my opinion you should have a pipeline like:

1. Downsampling (EEGlab has the anti-aliasing filter), maybe to 250.
2. Filter
3. Check the channels, remove the bad ones
4. Epoching
5. Remove the bad epochs
6. Remove the baseline
7. ICA
8. Interpolate the bad channels

Ivano



----
Antonio Ivano Triggiani, Ph.D.
Research Physiologist [C]
Human Motor Control Section, Medical Neurology Branch
National Institute of Neurological Disorders and Stroke
National Institutes of Health
10 Center Drive, Building 10, Room 7D42
Bethesda, MD 20892-1428
Phone: (301) 402-2983
MSC 1428
________________________________________________



On Tue, May 18, 2021 at 11:50 AM Chiara Gattoni via eeglablist <
eeglablist at sccn.ucsd.edu> wrote:

> Hi all,
>
> I am in the process of starting the preprocessing of my EEG data which
> have been collected during a cycling task of 40 minutes duration under
> different conditions. Participants were cycling at a constant intensity
> (moderate intensity domain).
>
> This is my first time analysing EEG during physical activity and one of the
> first times analysing EEG data in general (I come from sport and exercise
> sciences).
>
> I would like to do frequency and time-frequency analyses and focus on
> alpha, beta and theta bands. No events have been measured and I was
> thinking of dividing the 40-min EEG data collected into 5-minute time
> intervals.
> Have you got any suggestions to give me regarding the preprocessing part?
> Data collected are going to be more noisy than resting EEG for sure, so if
> you have any specific tips it would be helpful.
>
> These are the steps I was thinking to follow:
>
> 1) Baseline removal;
> 2) Bandpass filter (0.5 - 30 Hz);
> 3) Downsampling (128 Hz; sampling rate was 500 Hz);
> 4) Removing artifacts manually;
> 5) ICA;
> 6) Using SASICA for removing bad components (2 maximum);
> 7) Epoching (4 seconds overlap).
>
> Would you please let me know if I am going in the right direction?
>
> Many thanks in advance,
>
> Chiara
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