[Eeglablist] Flexible preprocessing (ICA then epoching and vice versa)

[Zaeem Hadi]

Dear Velu,
Many thanks for your suggestion. 
By high threshold, I meant the "max acceptable 0.5 sec window SD" option in EEGLAB. By default, it is set to 20. I have tried much higher values for it (ranging from 20-50) however it doesn't do well in many of the high amplitude or high-frequency noise periods in my data but keeps clipping the eye-blinks. I also have task related data and I am interested in time-frequency measures with a 4 second epoch (-1 to 3s), which is why I avoided ASR rejection as it can result in too much rejection within the trials. I was concerned that it might impact the time-frequency dynamics.
I have resorted to manually interpolating the noisy time periods and then ICA as I wanted more control of the artifact removal process.
Anyways, my main question was still about ICA then epoching or epoching then ICA, are there any expected differences due to the choice of either? (apart from the reordering of components due to variance differences, which is expected as epoch data is lesser than continuous data) 
I know both are possible choices of a pipeline, but could this be flexible within the same dataset? Can I do ICA-->epoching in some participants and epoching-->ICA in other participants within the same dataset,

Best wishes,Zaeem   On Tuesday, May 7, 2024 at 09:51:06 AM GMT+1, Velu Prabhakar Kumaravel <velu.kumaravel at unitn.it> wrote:  
 
 Hi Zaeem,
1) When you say high threshold, do you mean a higher value for the ASR parameter? In ASR, the strict cleaning occurs at a lower ASR cut-off parameter (e.g., 3). But, from our experience on newborn EEG data (characteristic of high noise levels with non-stereotypical artifacts), a strict threshold of 3 removes an excessive amount of neural information. Moreover, we have repeatedly observed (both in adults and newborns) that ASR Rejection is better than ASR Correction. (see figure 7 in this manuscript: https://urldefense.com/v3/__https://www.sciencedirect.com/science/article/pii/S1878929322000123?via*3Dihub*sec0190__;JSM!!Mih3wA!GdxOq_kFP5WazJaxA_Jg655ZzjFnuk9RxuNskUzgJA_J-z8ehjf52KezVMGD5kdyZ16cQHUaiYAunlSq4m7l0CQ$ )
2) It was not clear from your email whether or not you considered integrating ASR and ICA for your pipeline. In this case, you could use a relaxed ASR threshold (e.g., 20) and the residual eye-related artifacts can be removed by ICA + ICLabel.
Hope this helps.
Best,
Velu Prabhakar Kumaravel, PhD
On Mon, 6 May 2024 at 19:02, Zaeem Hadi via eeglablist <eeglablist at sccn.ucsd.edu> wrote:

Hi,
I was wondering if it would be reasonable to keep the preprocessing pipeline a bit flexible as below in different participants of the same dataset. Particularly the order of ICA and epoching.

In some subjects, continuous data is much cleaner and could be used for ICA with minimal rejection/interpolation. Whereas in some subjects the continuous data is very noisy and I was considering epoching first (which takes away most of the noise) and then doing ICA on epoched data in those subjects. I tried ASR but it keeps picking up eye-related data (blinks, eye movements) even with a very high threshold which I would like to keep for ICA and for later removal from data, so I would prefer to avoid it.
In each case, I am doing re-referencing and epoch baseline correction after ICA as recommended.
Is there an appropriate reference for justification for using this approach? 
Kind Regards,
Zaeem
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