[Eeglablist] Fw: Re: ECG Channel Inclusion in ICA and ICLabel Steps

Mon Aug 5 15:48:34 PDT 2024

Hi Cedric and Makoto,

My thoughts re the heartbeat source--I believe the heartbeat itself is mainly dipolar viewed from the "far field" of the scalp electrodes, which is why it shows up as a rainbow looking map. The actual dynamics of the EM field are more complex, but we mainly see only one component if any for the heartbeat.

If there is a heartbeat related brain signal, I think it would likely be blood flow related, but we don't really see such components. I don't think such a component would be part of the heart located component since the blood flow would not be instantaneously synched to the heartbeat. All standard ICA components are only supposed to be instantaneously independent.

Best,
Jason

-----Original Message-----
From: eeglablist <eeglablist-bounces at sccn.ucsd.edu> On Behalf Of Cedric Cannard via eeglablist
Sent: Monday, August 5, 2024 4:47 PM
To: EEGLAB List <eeglablist at sccn.ucsd.edu>
Subject: [Eeglablist] Fw: Re: ECG Channel Inclusion in ICA and ICLabel Steps

Hi Makoto,

Sorry for the typo. As you can guess, I meant "I do not believe including auxiliary channels violates ICA assumptions."

> Tony Bell is a legend

haha :)

> For example, concatenating millivolt-range signals with microvolt-range signals for decomposition may cause unexpected trouble.

Yes, I generally rescale the ECG signal to the EEG range if the ECG scale is vastly different, so ICA does not prioritize the larger ECG signals over the smaller EEG ones, which gives better results.

> Then ICA would not identify non-brain artifacts, right?

Why? Non-brain artifacts have independent sources. My point was that, as you summarized, ICA assumes sources to be independent, mixed, and non-gaussian, not that the sources of all signals are EPSP/IPSPs from pyramidal neurons.

> I'm rather curious to know if heartbeat-evoked potential is a real thing. For example, if I decompose a heartbeat IC which typically has a broad and dipolar projection from the depth. Is there any neuronal contribution there? If yes, then the heartbeat IC is contributed by both the heart and the brain. If no, it is generated only by the heart. Which is the case?

I agree and am wondering the same thing. And I don't think there is an answer to this yet. removing heart ICs may remove both the CFAs and the relevant neuronal-related HEP. Ideally, heart ICs would capture the cardiac field artifacts (CFA) which travel by volume conduction (e.g., skin) and are picked up by scalp EEG electrodes. The broad and dipolar spatial properties of the heart ICs reflect these CFAs (i.e., the source is non-neuronal). And HEPs (after removing these CFAs) would only reflect neuronal processing of heart activity.
I think one potential way of answering this would be to have intracranial electrodes time-locked to scalp electrodes, mark the R-peaks in both, and compare. But even then, heart activity can travel to the brain via various direct and indirect pathways: directly via the vagus nerve, indirectly via volume conduction through the spinal cord (surrounded by conductive CSF) and conductive arteries, or via blood pressure-related activity detected by baroreceptors/chemoreceptors.

I am currently developing a multivariate method that would provide more information on the synchronization (coherence & partial coherence), system response (transfer function matrix, spectral matrix, inverse spectral matrix), and causal interactions (directed coherence, directed transfer function, partial directed coherence) between heart and EEG signals. hopefully, that can provide some insights (direct, indirect interactions and direction of the interaction).

I think what provides some answer is the growing body of literature showing meaningful associations between HEP and interoception and integration of internal bodily states, highlighting brain areas known to be involved in these processes from the neuroimaging literature, e.g. insula, ACC, somatosensory cortex.

Some good references for HEP:
https://urldefense.com/v3/__https://pubmed.ncbi.nlm.nih.gov/31051293/__;!!Mih3wA!A7XPAnqNlQiz9pvotlbJTJbG2_n0TrNLB20H1cJLZDjdmMz8JsfHFIdXHQufx-wO2xcvGmCGkuOn8VQfYj8XKL4HCQ$ 

https://urldefense.com/v3/__https://pubmed.ncbi.nlm.nih.gov/22541740/__;!!Mih3wA!A7XPAnqNlQiz9pvotlbJTJbG2_n0TrNLB20H1cJLZDjdmMz8JsfHFIdXHQufx-wO2xcvGmCGkuOn8VQfYj8D2qUf-A$ 

https://urldefense.com/v3/__https://pubmed.ncbi.nlm.nih.gov/28651745/__;!!Mih3wA!A7XPAnqNlQiz9pvotlbJTJbG2_n0TrNLB20H1cJLZDjdmMz8JsfHFIdXHQufx-wO2xcvGmCGkuOn8VQfYj9BgOZjfw$ 

Cedric

------- Forwarded Message -------
From: Makoto Miyakoshi via eeglablist <eeglablist at sccn.ucsd.edu>
Date: On Monday, August 5th, 2024 at 7:59 AM
Subject: Re: [Eeglablist] ECG Channel Inclusion in ICA and ICLabel Steps
To: EEGLAB List <eeglablist at sccn.ucsd.edu>

> Hello John and
> 
> Cedric
> 
> 
> ,
> 
> This double negative makes it difficult to understand what you are 
> trying to say, Cedric.
> 
> > I do not believe including auxiliary channels does not violate ICA
> 
> assumptions.
> 
> You are saying that including ECG violates ICA's assumption, but your 
> claim seems opposite.
> 
> ICA's assumptions are, off the top of the head,
> 
> - The sources are non-Gaussian
> - The sources are linearly independent
> - The sources are linearly and instantly mixed
> - Tony Bell is a legend
> 
> So ECG channels may be included in ICA with no problem in theory. 
> However, if empirical observations recommend otherwise, there may be 
> some reason that is specific to each application which is worth 
> investigating. For example, concatenating millivolt-range signals with 
> microvolt-range signals for decomposition may cause unexpected trouble.
> 
> > It does not inherently assume that all sources must be of the same 
> > nature
> 
> or originate from EPSP/IPSPs from pyramidal neurons in cortical gyri, 
> does it?
> 
> Then ICA would not identify non-brain artifacts, right?
> 
> I'm rather curious to know if heartbeat-evoked potential is a real thing.
> For example, if I decompose a heartbeat IC which typically has a broad 
> and dipolar projection from the depth. Is there any neuronal 
> contribution there? If yes, then the heartbeat IC is contributed by 
> both the heart and the brain. If no, it is generated only by the heart. Which is the case?
> 
> Makoto
> 
> 
> 
> On Mon, Aug 5, 2024 at 12:58 AM Cedric Cannard via eeglablist < 
> eeglablist at sccn.ucsd.edu> wrote:
> 
> > Dear John,
> > 
> > This is the same debate as including EOG for separating and 
> > extracting ocular components (isn't that common practice?). The only 
> > reason why you can get away without EOG channels is that ocular 
> > activity is so large compared to EEG, so easy to identify as an 
> > independent source. However, cardiac artifacts are difficult to 
> > identify without an explicit reference signal (except occasionally 
> > in some individuals where you can see them visually in the raw time series).
> > 
> > Someone will correct me if I'm wrong, but I do not believe including 
> > auxiliary channels does not violate ICA assumptions. ICA is an 
> > algorithm designed to separate a mixture of signals into 
> > statistically independent components. It does not inherently assume 
> > that all sources must be of the same nature or originate from 
> > EPSP/IPSPs from pyramidal neurons in cortical gyri, does it?
> > 
> > By providing a clear reference for ECG artifacts, ECG channels can 
> > enhance the accuracy of this separation in my experience, in line 
> > with Sofia's observation. In fact, this is a method supported by my 
> > new BrainBeats plugin (along with HEP/HEO and HRV analysis which 
> > implements validated algorithms and guidelines via command line or 
> > GUI). See here for a step-by-step tutorial:
> > https://urldefense.com/v3/__https://www.jove.com/t/65829/author-spot
> > light-advancing-study-brain-heart-interplay-with__;!!Mih3wA!CWCJFZKu
> > 2zYD1n7sKo1ur_bO9g_iWhAy9vSTS18Bf-jfmH6errEXOVCDaXANh_5ukcj1Wajfh_MI
> > n3CPFGGRV09qjA$
> > And Github repo:
> > https://urldefense.com/v3/__https://github.com/amisepa/BrainBeats__;
> > !!Mih3wA!CWCJFZKu2zYD1n7sKo1ur_bO9g_iWhAy9vSTS18Bf-jfmH6errEXOVCDaXA
> > Nh_5ukcj1Wajfh_MIn3CPFGGKS9yf5A$
> > 
> > Sofia, my question is: Why are you using ICA in the context of HEP? 
> > You generally want to keep ECG-related activity for HEP. Do you 
> > suspect the HEP is a CFA? I have wondered about that but haven't found a work-around.
> > 
> > Curious to hear more on this!
> > 
> > Cedric Cannard
> > 
> > On Thursday, August 1st, 2024 at 7:08 AM, Richards, John via 
> > eeglablist < eeglablist at sccn.ucsd.edu> wrote:
> > 
> > > Don't include ECG in the EEG signal for ICA. For various technical 
> > > reasons (amplitude, frequency, signal spikes, location) and 
> > > theoretical ones (its NOT a brain signal; you want to correlate ECG and EEG).
> > > 
> > > See poster by Wanze Xie at ICIS, or contact him. He has 
> > > synchronized cardiac cycles and ERPs. His techniques might be 
> > > useful and he has some very interesting VEP/cardiac cycle data.
> > > 
> > > John
> > > 
> > > ***********************************************
> > > John E. Richards
> > > Carolina Distinguished Professor
> > > Department of Psychology
> > > University of South Carolina
> > > Columbia, SC 29208
> > > Dept Phone: 803 777 2079
> > > Fax: 803 777 9558
> > > Email: richards-john at sc.edu
> > 
> > https://urldefense.com/v3/__https://jerlab.sc.edu/__;!!Mih3wA!B4rXaM
> > GVhHYr_2oHmmQc94PJcfhiYYPWsZNqJtpm0CRKhOTeHaXWrkUCGI-mcxaW1b2qR1YWJv
> > 1lJrPrNV29FIao1z4gCQ$
> > 
> > > ***********************************************
> > > 
> > > -----Original Message-----
> > > From: eeglablist eeglablist-bounces at sccn.ucsd.edu On Behalf Of 
> > > Sofia Amaoui via eeglablist
> > > 
> > > Sent: Thursday, August 1, 2024 8:54 AM
> > > To: eeglablist at sccn.ucsd.edu
> > > Subject: [Eeglablist] ECG Channel Inclusion in ICA and ICLabel 
> > > Steps
> > > 
> > > Dear all,
> > > 
> > > We are conducting a Heart-Evoked Potential (HEP) study using EEG 
> > > signals that are time-locked to R-peak via ECG. Our preprocessing 
> > > pipeline is being implemented with EEGLAB, including the ERPLAB 
> > > and HEPLAB plugins. As part of this process, we employ Independent 
> > > Component Analysis (ICA) and ICLabel to identify ocular and cardiac field artefacts (CFA).
> > > 
> > > A key question has arisen regarding including the ECG channel in 
> > > the ICA and ICLabel steps. Our preliminary findings show that when 
> > > we include it, CFA classification is much higher.
> > > 
> > > We are seeking your insights on whether the inclusion of the ECG 
> > > channel is aiding in the identification of CFA components or if it 
> > > might be compromising EEG information of interest by focusing on 
> > > identifying and removing CFA.
> > > 
> > > Thank you for your time and assistance.
> > > 
> > > Best regards,
> > > 
> > > Sofia Amaoui,
> > > _______________________________________________
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