[Eeglablist] Baseline correction with resting state data

[Arnaud Delorme]

Hi Michelle,

Yes, Cedric is right. If you have large offsets in your channels (also called DC offsets), you may also remove the mean of each channel (using menu item Tools > Remove baseline). This would help with filters’ artifacts at the beginning and the end of the data.

Arno

> On May 1, 2023, at 6:15 AM, Cedric Cannard via eeglablist <eeglablist at sccn.ucsd.edu> wrote:
> 
> Hi Michelle,
> 
> No, for continuous data, simply apply a highpass filter to remove the very low-frequency DC drifts, ~1 hz is ideal for ICA if you're going to use ICA. And by the way, baseline removal is no longer recommended for ERP: https://urldefense.com/v3/__https://www.nature.com/articles/s41598-023-27528-0__;!!Mih3wA!HSTLmdoouQshT5RAGhVlYjkmxeviKB-yzgKfg99dUmCnRDFPE96s7EEwaH0b0zuBPCoOGs3Yw33XyujTityNy-HFBQ$ 
> 
> 
> Cedric
> 
> 
> 
> ------- Original Message -------
> On Monday, May 1st, 2023 at 6:15 AM, Michelle Lobermeier via eeglablist <eeglablist at sccn.ucsd.edu> wrote:
> 
> 
>> Hello everyone,
>> 
>> I am currently working on completing my dissertation, and we are gathering
>> resting state EEG data from 4- and 5-year-old children (2 minutes eyes
>> open, 2 minutes eyes closed). When working with resting state data like
>> this in MatLab/EEGLab, is baseline correction and removal recommended? I
>> know this is an important part of pre-processing with ERP data, but I am
>> having trouble finding information about whether this should be done with
>> continuous resting state data.
>> 
>> Thank you in advance for any insight you can provide. I appreciate it!
>> 
>> Best,
>> Michelle Lobermeier
>> 
>> 
>> 
>> --
>> Michelle Lobermeier, M.S., TLLP
>> Pronouns: she/her/hers
>> Doctoral Fellow, Clinical Psychology
>> Eastern Michigan University
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