[Eeglablist] ICA decomposition with 128 versus 64 channels?

Mon Jan 23 14:24:08 PST 2006

Yes!

On 23 Jan 2006 at 16:59, philip grieve wrote:

> Would this same problem effect fMRI group studies as well??
> 
> -----Original Message-----
> From: eeglablist-bounces at sccn.ucsd.edu
> [mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Jürgen Kayser
> Sent: Monday, January 23, 2006 1:09 PM
> To: ramesh; Dien, Joseph
> Cc: eeglablist at sccn.ucsd.edu; Craig Tenke; Matthew Belmonte
> Subject: Re: [Eeglablist] ICA decomposition with 128 versus 64 channels?
> 
> Ramesh and Joe:
> 
> Your comments, while informative, fail to address the point of our paper, 
> which is the loss of individual topographic specificity in group (!) data.
> The 
> implications affect any analysis concerned with sources of brain activity.  
> 
> Jürgen and Craig
> 
> Dept of Biopsychology, New York State Psychiatric Institute
> New York, NY 10032
> kayserj at pi.cpmc.columbia.edu
> tenkecr at pi.cpmc.columbia.edu
> 
> 
> 
> On 22 Jan 2006 at 22:39, ramesh wrote:
> 
> > CSD -current source density - is an overarching term   for a number of  
> > techniques with different physical (and hence physiological meaning).   
> > For instance, current source density methods in animal studies are  
> > often estimates of current flowing vertically across layers.
> > 
> > Surface Laplacians used in EEG also give you information of current  
> > density (rather than potential).   The current density estimated is the  
> > current flowing radially through the skull into the scalp.  We have  
> > shown that this is a pretty good estimates of localized (sources  
> > smaller than about 3 cm in surface tangential directions) sources in  
> > superficial cortex (within 3 cm of the electrodes).  However, if your  
> > sources are deeper or are actually over a larger area - say  extending  
> > 10 cm in tangential directions, the surface Laplacian will  
> > underestimate these sources.
> > 
> > In any case, surface Laplacians are a way to estimate skull current  
> > density and is hence a "CSD" method.  I think CSD is bad terminology in  
> > the case of EEG, since the current density is not actually brain  
> > "source" current density.
> > 
> > ramesh
> > On Jan 22, 2006, at 9:25 PM, Dien, Joseph wrote:
> > 
> > > Hey Ramesh!
> > >
> > > Oops, just so.  :)
> > >
> > > I'm not very familiar with CSD and Laplacian techniques.  What is the  
> > > difference between CSD and surface Laplacians?  Quick version?
> > >
> > > Joe
> > >
> > >
> > > -----Original Message-----
> > > From: ramesh [mailto:srinivar at uci.edu]
> > > Sent: Sun 1/22/2006 3:52 PM
> > > To: Dien, Joseph
> > > Cc: eeglablist at sccn.ucsd.edu; Jürgen Kayser; Matthew Belmonte
> > > Subject: Re: [Eeglablist] ICA decomposition with 128 versus 64  
> > > channels?
> > >
> > > Joe - I think you meant high-pass spatial filter and if you look at my
> > > new book - http://www.electricfieldsofthebrain Chapter 8, or 1995 paper
> > > in Brain Topography, it is only for surface Laplacians (or I suppose
> > > source localization) that the higher channel count is helpful.   Indeed
> > > if you want to do surface Laplacians there is potentially more
> > > information upto an interelectrode spacing of 2 cm, which would require
> > > more than 180 electrodes.
> > >
> > > I suspect for PCA, ICA algorithms the same is true, as outlined by
> > > Delome in previous emails to this group.
> > >
> > > If your just going to look at the EP waveforms or spectra at each
> > > channel the move from 64 to 128 is only marginally beneficial.  Again
> > > see my book, Chapter 7.
> > >
> > > ramesj
> > > On Jan 21, 2006, at 7:05 PM, Joseph Dien wrote:
> > >
> > >> I dare say it depends on the intended analysis approach.  CSD is, by
> > >> its nature, a low-pass filter.  It therefore makes sense to me that
> > >> such an approach might not take advantage of a higher channel count.
> > >> Given the Srinivasan et al (1996) and the Fletcher et al (1996)
> > >> simulation studies, I'm a little surprised by the findings of this new
> > >> study and look forward to reading it.  However, in my experience as
> > >> well, for dipole localization procedures more electrodes are better.
> > >>
> > >> Cheers!
> > >>
> > >> Joe
> > >>
> > >>
> > >>
> > >> On Jan 20, 2006, at 10:56 AM, Jürgen Kayser wrote:
> > >>
> > >>> Matthew:
> > >>>
> > >>> You might be interested in looking at the following article, which
> > >>> will be
> > >>> published in the February 2006 issue of Clinical Neurophysiology
> > >>> (currently
> > >>> available via the DOI pointer at Elsevier's web site).
> > >>>
> > >>> Kayser, J., Tenke, C.E. (2006). Principal components analysis of
> > >>> Laplacian
> > >>> waveforms as a generic method for identifying ERP generator patterns:
> > >>> II.
> > >>> Adequacy of low-density estimates. Clinical Neurophysiology, 117(2),
> > >>> in
> > >>> press.
> > >>>
> > >>> http://dx.doi.org/10.1016/j.clinph.2005.08.033
> > >>>
> > >>> Our report investigates the benefits of using high- vs. low-density
> > >>> EEG
> > >>> montages (129 vs. 31 channels) for typical ERP group data, which is
> > >>> likely to
> > >>> be relevant to your question. Individual topographic specificity of
> > >>> ERP
> > >>> components derived from high-resolution ERP/CSD data is largely lost
> > >>> in
> > >>> ERP group data, because averaging across subjects results in a
> > >>> spatial low-
> > >>> pass filter. If the focus is on brain processes that can be
> > >>> generalized to the
> > >>> population under study, there seems to be no immediate gain of
> > >>> high-density
> > >>> recordings. These findings may come as a surprise as they seem to
> > >>> contradict common ERP knowledge based on previous recommendations
> > >>> using simulated and individual ERP data. Consequently, a (clinical)
> > >>> ERP
> > >>> researcher would be well-advised to consider the costs and benefits  
> > >>> of
> > >>> engaging in high-density EEG recordings.
> > >>>
> > >>> Best, Jürgen and Craig
> > >>>
> > >>>
> > >>>
> > >>> On 18 Jan 2006 at 23:41, Matthew Belmonte wrote:
> > >>>
> > >>>> I'm in the process of putting together a proposal for an EEG
> > >>>> facility, and
> > >>>> would like to select hardware with EEGLAB processing in mind.  I'm
> > >>>> approaching
> > >>>> this from perhaps a bit of a dated perspective: in 1996 I was using
> > >>>> only 16
> > >>>> channels and homebrewed software for time-frequency analysis, and
> > >>>> I've spent
> > >>>> the intervening decade working exclusively with fMRI.
> > >>>>
> > >>>> I've heard from one EEGLAB user that 128 channels don't confer much
> > >>>> advantage
> > >>>> over 64, since inputs must be spatially downsampled in order to be
> > >>>> processed
> > >>>> practically on typical computing hardware, and since the independent
> > >>>> components
> > >>>> of interest (those from neural sources) don't become much cleaner
> > >>>> with 128
> > >>>> inputs as compared to 64.  (The tradeoff of spatial resolution and
> > >>>> SNR to
> > >>>> electrode application time also is a consideration; we'd be
> > >>>> recording from
> > >>>> autistic children and couldn't afford any great deal of time spent
> > >>>> fiddling.)
> > >>>>
> > >>>> I'd like to hear from EEGLAB users (and developers!) with experience
> > >>>> at 128
> > >>>> and/or 64 channels:  Do you find a 64-channel system adequate?  What
> > >>>> improvement in data quality has moving to 128 channels given you?
> > >>>> If I loaded
> > >>>> up a GNU/Linux system with the most RAM that I could get (16GB on an
> > >>>> IBM
> > >>>> IntelliStation), would it be able to handle an ICA decomposition of
> > >>>> 128-channel
> > >>>> data without thrashing, or would I be doubling my investment in
> > >>>> amplifiers only
> > >>>> to have to mix down 128 signals to 64 before ICA?  And, even if it
> > >>>> would be
> > >>>> computationally practical, would it be scientifically useful enough
> > >>>> to justify
> > >>>> the extra preparation time?
> > >>>>
> > >>>> Many thanks
> > >>>>
> > >>>> Matthew Belmonte <mkb30 at cam.ac.uk>
> > >>>> _______________________________________________
> > >>>> eeglablist mailing list eeglablist at sccn.ucsd.edu
> > >>>> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
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> > >>>
> > >>>
> > >>>
> > >>> _______________________________________________
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> > >>
> > >> ---------------------------------------------------------------------- 
> > >> -
> > >> ---------
> > >>
> > >> Joseph Dien
> > >> Assistant Professor of Psychology
> > >> Department of Psychology
> > >> 419 Fraser Hall
> > >> 1415 Jayhawk Blvd
> > >> University of Kansas
> > >> Lawrence, KS 66045-7556
> > >> E-mail: jdien at ku.edu
> > >> Office: 785-864-9822 (note: no voicemail)
> > >> Fax: 785-864-5696
> > >> http://people.ku.edu/~jdien/Dien.html
> > >>
> > >>
> > >> _______________________________________________
> > >> eeglablist mailing list eeglablist at sccn.ucsd.edu
> > >> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
> > >> To unsubscribe, send an empty email to
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> > >>
> > > Ramesh Srinivasan
> > > Assistant Professor
> > > Department of Cognitive Sciences
> > > University of California, Irvine
> > > Irvine, CA 92697-5100
> > >
> > >
> > >
> > Ramesh Srinivasan
> > Assistant Professor
> > Department of Cognitive Sciences
> > University of California, Irvine
> > Irvine, CA 92697-5100
> > 
> 
> 
> 
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