[Eeglablist] 回复： Makoto's preprocessing pipeline: ICA matrices transfer

[Ya Zheng]

Thanks, Scott.
I agree with that the upper limit is best left open. My furhter question is whether IClabel should be applied to the 1-Hz high-pass data or the 0.1-Hz high-pass data after the ICA matrices transfer? I found that the confidence of classification by IClabel is lower for the 0.1-Hz high-pass data than for the 1-Hz high-pass data.
Ya




------------------ 原始邮件 ------------------
发件人:                                                                                                                        "smakeig"                                                                                    <smakeig at gmail.com>;
发送时间: 2021年10月8日(星期五) 凌晨1:09
收件人: "Ya Zheng"<123975520 at qq.com>;
抄送: "eeglablist"<eeglablist at sccn.ucsd.edu>;
主题: Re: [Eeglablist] Makoto's preprocessing pipeline: ICA matrices transfer



Ya - 

Why do you bandlimit 1-35 Hz before applying ICA decomposition? The upper limit is best left open, as ICA decomposition can use spatially differentiating information contained in higher frequency portions of the source signals. The (~1 Hz) lower limit is justified by the understanding that very-low-frequency contributions may be dominated by non-brain artifact processes that would compete with brain sources for places/separate dimensions in the decomposition. If the same were to occur at high frequencies (e.g., hypothetically, say, spatially complex and varying broadband 100-150 Hz noise), then using a high-pass cutoff (e.g., < 100 Hz) would be justified by the same reasoning.


Likely your finding that ICLabel returns more EMG sources when applied to the 0.1-Hz high-passed data (without low pass filtering) arises because ICLabel looks for the spectral signature of EMG (conceptually, a noise plateau from 20 Hz  to max Hz) as well as for scalp map characteristics, and doesn't see the spectral signature it is looking for in the 35-Hz low-passed data...


Scott


On Thu, Oct 7, 2021 at 12:21 PM Ya Zheng via eeglablist <eeglablist at sccn.ucsd.edu> wrote:

Hi Makoto,
 I calculated ICA weight matrix and sphereing matrix with 1-35 Hz band-passed data, then appled it to 0.1-Hz high-passed data. Then, I applied the ICLabel to identify the artifact-related ICs. My question is which dataset should be applied to? The 1-35 band-passed data or the 0.1-Hz high-passed data? I found that the ICLabel resulted in some different results, e.g, more muscle ICs found for the 0.1-Hz high-pass data. Thanks!
 Best,
 Ya
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-- 
Scott Makeig, Research Scientist and Director, Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott