[Eeglablist] sLORETA question

Delorme, Arnaud adelorme at ucsd.edu
Sun Nov 21 00:43:56 PST 2021


Thanks Ernesto,

You are right, I confused sLoreta and swLorera (weighted version of sLoreta https://urldefense.proofpoint.com/v2/url?u=https-3A__www.ncbi.nlm.nih.gov_pubmed_17374911&d=DwIGaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=HZ3WlEyR6cRM2QAwZE8mvMIGyyqbnlfESjj_XZeiP6-Yn-1q9Q6cPUFdthDf7BDR&s=qrrZyGp84G6flU2oQ8rbEdPsOiQpWwv38_rtgvev9J8&e= ) which is the rarely used version I was thinking about (and the one in NeuroGuide). 

Cheers,

Arno

> On Nov 20, 2021, at 10:02 PM, Ernesto Palmero Soler <e.palmero at icloud.com> wrote:
> 
> Dear Arno:
> 
> With all my respect I think you statement in this email is wrong. First sLORETA and LORETA are not related at all except the name. This is clear from the original Pascual Marqui original paper where we clear mention that. Second sLORETA has being use in many per review papers and it has been tested but in simulation and in real data (myself has done my thesis on the topic). Third it is not true that sLORETA is only present in the NeuroGuide software, just to mention a few CURRY, ASA software package has both implemented the method.
> 
> Finally the reason why the sLORETA method is interesting is due to his zero location error in ideal conditions, which of course is not true for real data but it give you a better start than the LORETA one which does not have this properties. Just to finish although I can see the advantage of using beamformer type of method in some cases, it is important to notice to problems with this type of methods:
> 
> 1. They are not really an inverse solution method but a way to separate independent sources.
> 2, Due to 1 in cases where cases where the sources are highly correlated the beamformer method miss them because it is not done for this. This is particularly important if you want to study connectivity on the sources.
> 
> Have a great day 
> Ernesto Palmero Soler 
> 
>> On 19 Nov 2021, at 05:18, Neri Baker via eeglablist <eeglablist at sccn.ucsd.edu> wrote:
>> 
>> Hi Arno,
>> 
>> Thanks for this info. I have been using eLORETA, but I was interested in whether similar functionality was available in EEGLAB (partly to reduce data transfer back and forth between packages, and partly to see the source code to understand exactly what the various parameters do).
>> 
>> Thank you for the suggestion of LCMV beamforming - it looks very interesting. 
>> 
>> Many thanks,
>> Neri
>> 
>> -----Original Message-----
>> From: eeglablist <eeglablist-bounces at sccn.ucsd.edu> On Behalf Of Delorme, Arnaud via eeglablist
>> Sent: Friday, 19 November 2021 12:19 PM
>> Cc: eeglablist at sccn.ucsd.edu
>> Subject: Re: [Eeglablist] sLORETA question
>> 
>> sLoreta is an obscure Loreta decomposition, which nobody uses except the NeuroGuide Neurofeedback software. As far as I know, the only way to use sLoreta is to use the NeuroGuide software. It has not been demonstrated to be superior (or inferior) to eLoreta (see the seminal article https://urldefense.proofpoint.com/v2/url?u=https-3A__www.frontiersin.org_articles_10.3389_fnbeh.2014.00066_full&d=DwIFAg&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=Zxef-biWZfrFE9qFTeNsdtYkrHGyh-ZQ8zYm6OxqK8wZhat8hxJJrtPPTFIbHWD1&s=aB-mQ2PLolwFcEqW8bssg_UhLPlQLXH6xXjEJNMt8Do&e= ). It seems relatively equivalent in numerical tests. If someone can enlighten us as to the difference between sLoreta and other Loreta source reconstruction methods, please do so.
>> 
>> Because sLoreta is a rare and not widely accepted form of Loreta, I would recommend instead Pascual Marqui's original eLoreta implementation. 
>> 
>> Also try LCMV beam forming (also available in DIPFIT) which provides less smooth solutions, and is recommended for region of interest connectivity analysis by brain connectivity analysis researchers such as Stefan Haufe.
>> 
>> Arno
>> 
>>> On Nov 17, 2021, at 11:15 AM, Neri Baker via eeglablist <eeglablist at sccn.ucsd.edu> wrote:
>>> 
>>> Hi Makoto
>>> 
>>> This sounds really useful. I am also interested in trying it out.
>>> 
>>> Kind regards,
>>> Neri
>>> ________________________________
>>> From: eeglablist <eeglablist-bounces at sccn.ucsd.edu> on behalf of ivano 
>>> triggiani via eeglablist <eeglablist at sccn.ucsd.edu>
>>> Sent: Thursday, November 18, 2021 7:43:30 AM
>>> To: Makoto Miyakoshi <mmiyakoshi at ucsd.edu>; eeglablist at sccn.ucsd.edu 
>>> <eeglablist at sccn.ucsd.edu>
>>> Subject: Re: [Eeglablist] sLORETA question
>>> 
>>> Dear Makoto,
>>> 
>>> I would be interested as well.
>>> 
>>> Thank you,
>>> 
>>> Ivano
>>> 
>>>> On Wed, Nov 17, 2021, 3:23 PM Makoto Miyakoshi via eeglablist < 
>>>> eeglablist at sccn.ucsd.edu> wrote:
>>>> 
>>>> Dear Matthew,
>>>> 
>>>> Dipfit supports eLORETA but it is more like a proof of concept. I 
>>>> recommend you check it out first.
>>>> I have stripped the function and wrote my own wrapper. If you are 
>>>> interested, I can upload it online so that you can try it out. It is 
>>>> not an EEGLAB plugin so does not come with a nice GUI. My code also 
>>>> allows voxel-level subtraction to show current density differences 
>>>> between two conditions. Let me know if you want to try it out.
>>>> 
>>>> Makoto
>>>> 
>>>> On Tue, Nov 16, 2021 at 12:28 PM Gunn, Matthew P via eeglablist < 
>>>> eeglablist at sccn.ucsd.edu> wrote:
>>>> 
>>>>> Hello,
>>>>> 
>>>>> Does anyone know if there are any programs like sLORETA in EEGLAB or 
>>>>> an APP that MATlab has that could do this process. I know of 
>>>>> erpsource; but, didn't know if this tool existed or if a team is 
>>>>> currently working on
>>>> one.
>>>>> 
>>>>> Thank you for your time,
>>>>> 
>>>>> Matt G.
>>>>> _______________________________________________
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