[Eeglablist] Source analysis trade-offs: ICA + ECD versus distributed methods

Makoto Miyakoshi mmiyakoshi at ucsd.edu
Mon Jan 11 11:00:38 PST 2021


Dear Justin,

> why would someone prefer finding a priori known sources in EEG with a
given source methods?

It is because the inverse problem of the head volume conductor does not
have a unique solution. Because of this fundamental limitation, there can
be multiple reasonable assumptions about the spatial distribution of
'source of EEG' to reach the unique solution (to a reasonable degree, given
the assumption).

In the 'Electric Field of the Brain' (2006) by Nunez and Srinivasan, they
advocate an alternative approach in which you do get a unique solution in
estimating EEG source distribution at the cost of resolution in sulci. In
other words, you accept the limitation that you will only analyze
continuous gyri with no sulci and you get an unique solution. The
justification for this trade-off is that apparently potentials cancel each
between the two cortices facing to each other at a sulcus. You can find
quantitative evaluation on this in their book.

In sum, what you can give up determines what you can say for sure. But the
critical difference concerns the qualitative differences, such as whether
the solution is unique or non-unique. For non-unique solutions, you may be
able to take advantage of electrophysiological facts by incorporating
sparticy and/or smoothness of the 'EEG sources' (such as
sparse-compact-smooth constraint by Chen used in Zeynep's SCALE, not SCORE)
as well as dynamics (such as Stefan Haufe's method that can be used for
SIFT which Tim Mullen always talk highly of) to 'improve' the result, or
better to say, 'inform' the result. Hence the goodness of the result
depends on the goodness of the assumptions.

I'm not super knowledgeable in this topic but do have a strong interest to
learn. I'd be happy to discuss this topic with you.

Makoto



On Sat, Jan 9, 2021 at 9:46 AM Fine, Justin Michael <justfine at iu.edu> wrote:

> Dear list:
>
> I have a question that the literature does not really seem to answer
> regarding source analysis: why would someone prefer findings a priori known
> sources in EEG with a given source methods? Specifically, I am asking about
> the benefits and obvious trade-offs if (1) ICA + ECD ,(2) distributed (and
> sparse or group hierarchical methods) source methods (e.g., MSP in SPM) or
> (3) a Bayesian ECD approach which does not rely on fitting separate IC
> components but relies on specifying a prior source locations?
>
> Quick background, I have T1s and recorded electrode positions (64 channel
> acticap) for all participants.  The main goal here is extracting
> time-frequency and evoked (ERP) from an rIFG, pre-SMA/ACC/MCC, and left M1
> source.The study was a standard stop signal task, of which the literature
> tends to prefer the method (1) of ICA + ECD. But I gather that might have
> something to do with researchers typically (1) not having electrode
> locations and (2) T1s?
>
> Any thoughts and feedback would be greatly appreciated.
>
> Thanks!
> Justin Fine
> Post-doctoral researcher
> Indiana University
> -----Original Message-----
> From: eeglablist <eeglablist-bounces at sccn.ucsd.edu> On Behalf Of Scott
> Makeig
> Sent: Friday, January 8, 2021 2:32 PM
> To: JULIANA CORLIER <corlier at g.ucla.edu>; Johanna Wagner <
> joa.wagn at gmail.com>
> Cc: eeglablist at sccn.ucsd.edu
> Subject: [External] Re: [Eeglablist] Analysis of TMS-induced harmonics in
> the EEG
>
> This message was sent from a non-IU address. Please exercise caution when
> clicking links or opening attachments from external sources.
> -------
>
> Juliana -
>
> These will also soon be a new toolbox, the 'Independent Modulator Analysis
> Toolbox' (IMAT), that can separate harmonic from non-harmonic activity. If
> you might like to test its use, write Johanna Wagner <joa.wagn at gmail.com>.
>
> Scott Makeig
>
> On Thu, Jan 7, 2021 at 3:20 PM JULIANA CORLIER <corlier at g.ucla.edu> wrote:
>
> > Dear list,
> >
> > I would like to get some expert advice on how to assess/quantify the
> > presence of harmonics in the EEG.
> > Notably, our lab is using EEG recordings during repetitive
> > transcranial magnetic stimulation (TMS) and we would like to assess
> > whether the stimulation at a certain frequency elicits an entrainment
> > at the stimulation frequency but also at other frequencies.
> >
> > My first approach was to check for ‘ratios of frequencies’ that show
> > activation in the time-frequecy domain post stimulation, but that
> > turned out to be a more tricky than I have aniticipated.
> > I was wondering if there is a proper approach to harmonics analysis?
> > One would think that engineers and signal processing experts outside
> > of neurosciences deal all the time with that.
> >
> > Any advice is much appreciated!
> >
> > Thank you!
> >
> > Juliana Corlier
> >
> >
> >
> > _______________________________________________
> > Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
> > To unsubscribe, send an empty email to
> > eeglablist-unsubscribe at sccn.ucsd.edu
> > For digest mode, send an email with the subject "set digest mime" to
> > eeglablist-request at sccn.ucsd.edu
>
>
>
> --
> 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
> _______________________________________________
> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
> To unsubscribe, send an empty email to
> eeglablist-unsubscribe at sccn.ucsd.edu
> For digest mode, send an email with the subject "set digest mime" to
> eeglablist-request at sccn.ucsd.edu
> _______________________________________________
> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
> To unsubscribe, send an empty email to
> eeglablist-unsubscribe at sccn.ucsd.edu
> For digest mode, send an email with the subject "set digest mime" to
> eeglablist-request at sccn.ucsd.edu


More information about the eeglablist mailing list