[Eeglablist] sLORETA question

Fri Dec 17 17:59:58 PST 2021

Dear eLORETA explorers,

Sorry for the slow progress.
I uploaded the sample output from the wrapped-up eLORETA plugin to this
page.
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.youtube.com_watch-3Fv-3DTL77GbC2wE8&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=JPMLUdaFccPYzcUbq68auJkGHzq4G3uzL0wsJWR_pZsmcSXDpEaTGJ3JE2k9UW4g&s=vuPGRPEJ5SwZVXzFrneIvb3BYfjC1RM43vOMPoGHXlE&e= 
Basically, I am thinking about making a toolbox that can create something
like this as a default output--but I want to know if that is something you
want to see/show.
Please let me know what you think.

If I were to make a GUI for this function, what are the parameters you want
to specify?
Do you always want to make it into a movie, or is a 2-D image with a
selected time slice sufficient?
I stored all the voxel (?) values for every time frame but it was only a
few MB. I can probably store all the output so that next time you can skip
calculation. It makes easier to cut and try to optimize color scale limit
and brain angle etc.
Do any of you know a convenient way to find anatomical label/info from
128x128x128 (mm) voxels? (I am not even sure what atlas it uses now--is it
MNI? I'm using the Fieldtrip function to generate this eLORETA image.)

Please help me develop it by posting your opinions. Is the brain image too
small? Is the ERP plot helpful? etc etc.

Makoto

On Sat, Nov 20, 2021 at 8:27 AM Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
wrote:

> Dear Matthew, Michael, Ivano, Neri, Vahid, and others,
>
> Thank you for your responses.
> As Michael wrote, the eLORETA implementation is taken from Fieldtrip. Arno
> developed the first EEGLAB wrapper to use eLORETA function a couple of
> years ago, which I stripped and modified several times.
> And Arno is right, it is eLORETA (published in 2005) and not sLORETA
> (published in 2002). For detail, see this official website
>
> https://urldefense.proofpoint.com/v2/url?u=http-3A__www.uzh.ch_keyinst_eLORETA_index.html&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=JPMLUdaFccPYzcUbq68auJkGHzq4G3uzL0wsJWR_pZsmcSXDpEaTGJ3JE2k9UW4g&s=Y2V1aeM0JW7pIRegwSemPXr3yvUi9mbcyI7QMmnF9mY&e= 
>
> Let me quote the author's description about the difference between eLORETA
> and sLORETA.
>
>
> *...One particular member of this family is sLORETA (standardized low
> resolution brain electromagnetic tomography; Pascual-Marqui, Methods Find.
> Exp. Clin. Pharmacol. 2002,
> 24D:5-12;http://www.unizh.ch/keyinst/NewLORETA/sLORETA/sLORETA-Math01.pdf
> <https://urldefense.proofpoint.com/v2/url?u=http-3A__www.unizh.ch_keyinst_NewLORETA_sLORETA_sLORETA-2DMath01.pdf&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=JPMLUdaFccPYzcUbq68auJkGHzq4G3uzL0wsJWR_pZsmcSXDpEaTGJ3JE2k9UW4g&s=lFvDKbDjfY0s2DgGVeI6FruykA8m8NBDddZZGYfTcuQ&e= >). It is
> shown here that sLORETA has no localization bias in the presence of
> measurement and biological noise. Another member of this family, denoted as
> eLORETA (exact low resolution brain electromagnetic
> tomography; Pascual-Marqui 2005:
> https://urldefense.proofpoint.com/v2/url?u=http-3A__www.research-2Dprojects.unizh.ch_p6990.htm&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=JPMLUdaFccPYzcUbq68auJkGHzq4G3uzL0wsJWR_pZsmcSXDpEaTGJ3JE2k9UW4g&s=NbDBlXRgOSRPRdYHRWWY_vHGg_FLngc5i9uYKL13YJw&e= 
> <https://urldefense.proofpoint.com/v2/url?u=http-3A__www.research-2Dprojects.unizh.ch_p6990.htm&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=JPMLUdaFccPYzcUbq68auJkGHzq4G3uzL0wsJWR_pZsmcSXDpEaTGJ3JE2k9UW4g&s=NbDBlXRgOSRPRdYHRWWY_vHGg_FLngc5i9uYKL13YJw&e= >), is a genuine inverse
> solution (not merely a linear imaging method) with exact, zero error
> localization in the presence of measurement and structured biological
> noise.*
>
> I don't know what he means by 'a genuine inverse solution (not merely a
> linear imaging method)' and I can't explain the difference between sLORETA
> and eLORETA. If you can explain it in a plain language, please help me
> understand it.
>
> I want to know what level of solution you need. Please answer the
> following questions.
>
>    1. Do you use continuous data (resting etc) or event-related epoched
>    data (any ERP paradigm)?
>    2. How comfortable it is for you to use these functions in Matlab
>    command line? In other words, do you need GUI?
>    3. I ask the users to input parameters for (1) latency to plot and (2)
>    color scale limit (optionally, color scheme itself?). What else do you want
>    to specify when generating the LORETA image?
>    4. It comes with a subtraction function i.e. eLORETA result 1 -
>    eLORETA result 2. This works, but the result is without stats. I know how
>    to run a stats on this result using permutation test, but it is horribly
>    inefficient. It's much easier if you determine statistically significant
>    differences on the scalp topos, and generate a corresponding eLORETA
>    difference image (a LORETA version of kernel trick) Does it make sense? Do
>    you think LORETA stats on current density is still necessary?
>    5. Any other general request before I start the finalization?
>
> Please let me know what you want to see. I'd like to wrap it up into a
> convenient tool for you.
>
> Makoto
>
> On Thu, Nov 18, 2021 at 8:18 PM 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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>