[Eeglablist] Rereference

Iman M.Rezazadeh irezazadeh at ucdavis.edu
Tue Oct 7 11:58:25 PDT 2014


Hi, 

Re-referencing does not change CSD maps.

Suppose, the following numbers are the voltage values from 6 electrodes/LFP at time point t=T1 with an unknown voltage reference: 

 5, 7, 6,9,3, 2  

Since Current source density (CSD) is the second spatial derivative of the local field potential/EEG, the first derivative and the second derivative for the data are [ -2,1,-3,6,1] and [-3,4, -9,5], respectively.

 

Now , if we would like to change reference values (re-reference) consider for example 3 volte as the new reference value then the new voltage values would be :

2,4,3,6,0,-1

First derivative : -2,1,-3,6,1 

Second derivative : :-3,4, -9,5

 

So the CSD maps are invariant the re-referencing !

 

============================================

Iman M.Rezazadeh, Ph.D. , M.Sc., B.Sc.

Research Associate II

UCLA David Geffen School of Medicine

Semel Institute for Neuroscience and Human Behavior

760 Westwood Plaza, Ste 47-448

Los Angeles, CA  90095

 <http://www.linkedin.com/pub/iman-m-rezazadeh/10/859/840/> http://www.linkedin.com/pub/iman-m-rezazadeh/10/859/840/

 

 

 

 

 

From: Pål Gunnar Larsson [mailto:pall at ous-hf.no] 
Sent: Monday, October 6, 2014 10:42 PM
To: 'Iman M.Rezazadeh'
Subject: SV: [Eeglablist] Rereference

 

In this context, what is the status of CSD (nearest neighbour and spherical spline approximation) and other reference free montages?

 

Best 

 

Pål

 

Pål G. Larsson M.D., PhD.

Head of Clinical Neurophysiology

Department of Neurosurgery

Division of Surgery and Clinical Neuroscience

 

Oslo University Hospital

Po.box 4950 Nydalen

0424 Oslo

Norway

Tel:  (+47) 23074407

Mobile: (+47) 93429791

E-mail: pall at ous-hf.no <mailto:pall at ous-hf.no> 

not sensitive

 

Fra: eeglablist-bounces at sccn.ucsd.edu <mailto:eeglablist-bounces at sccn.ucsd.edu>  [mailto:eeglablist-bounces at sccn.ucsd.edu] På vegne av Iman M.Rezazadeh
Sendt: 6. oktober 2014 06:37
Til: japalmer at ucsd.edu <mailto:japalmer at ucsd.edu> ; 'Simon Finnigan'; mmiyakoshi at ucsd.edu <mailto:mmiyakoshi at ucsd.edu> 
Kopi: 'eeglablist'; 'Eric HG'
Emne: Re: [Eeglablist] Rereference

 

I would like to suggest you read also the following archive :

http://sccn.ucsd.edu/pipermail/eeglablist/2014/007810.html

 

 

From: eeglablist-bounces at sccn.ucsd.edu <mailto:eeglablist-bounces at sccn.ucsd.edu>  [mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Jason Palmer
Sent: Sunday, October 5, 2014 5:33 PM
To: 'Simon Finnigan'; mmiyakoshi at ucsd.edu <mailto:mmiyakoshi at ucsd.edu> 
Cc: 'eeglablist'; 'Eric HG'
Subject: Re: [Eeglablist] Rereference

 

Dear Eric, Simon, et al.,

 

This issue has been discussed several times before and you can check the archives for more discussion. I have argued before, mainly from a linear algebra point of view, that any referencing using a linear combination some of the other channels is essentially projecting the data onto an space of dimension (nchan-1), where sources along a particular direction become invisible. In the case of average reference, this direction is the source that equally increases or decreases all the channel potentials by the same amount, i.e. [1 1 1 1 …. 1], and in consequence, all the learned ICA maps are orthogonal to this direction, and any sources along that direction are lost. But if there is any part of the source map that is not constant, this part will be retained and can be extracted by ICA.

 

Using average reference makes all ICA sources have zero total potential. I have argued before that zero total potential makes sense for brain sources assuming approximately complete surrounding of head by electrode array, by a charge conservation argument. This will of course not hold exactly in practice, and there will be some shunting, so the learned ICA maps must be assumed to have an unknown constant potential added to each electrode for localization purposes.

 

What I said to Makoto was that the reference didn’t really matter ultimately as long as you choose a combination of channels that cannot likely represent a real source. I suggest average reference because this makes all the maps sum to zero, clearly indicating dipolarity/directionality by having negative (blue) and positive (red) values in each map, rather than having maps that have dark blue background and light blue source “blob” (or dark red and light red). As I said, there must be assumed to be an unknown constant added to each map. My natural default for display purposes would be the total potential, and using average reference does this for you “automatically” with little risk of losing any sources of interest.

 

People often worry that including a bad channel in the average reference will contaminate everything by adding noise to every channel. However the change is just a linear addition of one noise direction along the channel, which can be easily undone by ICA, at the cost of using one of the ICA sources to contain this noise channel. I would still of course suggest removing bad channels first for practical reasons.

 

Best,

Jason

 

 

From: eeglablist-bounces at sccn.ucsd.edu <mailto:eeglablist-bounces at sccn.ucsd.edu>  [mailto:eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Simon Finnigan
Sent: Saturday, October 04, 2014 2:51 AM
To: mmiyakoshi at ucsd.edu <mailto:mmiyakoshi at ucsd.edu> 
Cc: eeglablist; Eric HG
Subject: Re: [Eeglablist] Rereference

 

Hi All

 

Firstly I must say that as a scientist, I find the rationale from Jason via Makoto to be un-scientific and unsatisfactory.

 

Second - This will only partly answer your question I think, but here goes: it all depends on how you're analysing your data [what you're looking  at/for] and particularly, whether or not scalp topographies are of interest to you - but in general and in brief, the consensus seems to be that common-average referencing is preferable over mastoid referencing, at least - and probably other references sites too [e.g. vertex; nasion]. [Also are your data referenced to one or both mastoids? and if both - were they linked, or averaged together after recording?]

 

My 2002 paper in 'Neuropsychologia' addressed this issue scientifically, at least in part - e.g. see final figure [albeit we weren't doing ICA back then either!].

 

Regards, Simon

 


On 04/10/2014, at 8:21, Makoto Miyakoshi <mmiyakoshi at ucsd.edu <mailto:mmiyakoshi at ucsd.edu> > wrote:

Here is update.

I asked the question to Jason. He told me that the main reason avg reference is useful is that it returns brain maps that look like nice localized sources inside the head with red blob and slight negative (aqua/green) background. This makes sense.

 

Makoto

 

On Thu, Oct 2, 2014 at 10:00 AM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu <mailto:mmiyakoshi at ucsd.edu> > wrote:

Dear Eric,

 

I have the same question for long time. In my case, because I run ICA and remain in IC analysis and almost never come back to channels, I really wonder if I need re-referencing at all.

 

I've heard Jason Palmer, who wrote AMICA for EEGLAB, say average reference before ICA is necessary, but he did not give me a clear explanation for that. Scott wanted to know it too, but we were interrupted at that time. Next time I'll ask it to him (when I ever see him in the lab...)

 

Makoto 

 

On Tue, Sep 30, 2014 at 2:44 PM, Eric HG <erichg2013 at gmail.com <mailto:erichg2013 at gmail.com> > wrote:

Dear list,

 

I have read the tutorial on the site and it says: "Converting data, before analysis, from fixed or common reference (for example, from a common earlobe or other channel reference) to 'average reference' is advocated by some researchers, particularly when the electrode montage covers nearly the whole head (as for some high-density recording systems)." 

 

I have data collected with a mastoid reference and I was wondering in which cases it would be considered best to rereference to the average? Are there any specific papers about rereferencing that anyone would recommend?

 

Regards,

 

Eric 

 

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-- 

Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego





 

-- 

Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego

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