[Eeglablist] Choosing right head model in Dipfit with BrainProducts Cap

[Makoto Miyakoshi]

Dear Maya,

Between you and me I have been also using 2013a for code development.

Makoto

On Wed, Aug 17, 2016 at 1:01 PM, Maya Pinacle <mayapinacle at gmail.com> wrote:

> Dear Tarik and Makoto,
>
>
> thank you very much for your very valuable comments. They have been very
> helpful. After a long investigation that I have done I found out that the
> Matlab version that I am using 2014a is causing a lot of trouble to use
> many EEGLAB features even though I use latest version of the toolbox and
> plugins of it. So I managed to locate dipoles using Matlab 2013a with the
> latest version of the EEGLAB. I also use both (Matlab 2013a and latest
> EEGLAB) for pop_clustedit() function because many features doesn't work
> with Matlab 2014a as well.
>
>
> Thank you very much for the help again.
>
> Maya
>
> 2016-08-05 17:53 GMT+01:00 Makoto Miyakoshi <mmiyakoshi at ucsd.edu>:
>
>> Dear Maya,
>>
>> It seems the dipoles were fitted only by 'coarse fit' and not with 'fine
>> fit'. That's why you see the apparent grid structure there. Make sure you
>> performed 'autofit' because it does both coarse and fine fit. If you are
>> sure you did 'autofit', then it failed for some reason. If that's the case,
>> check the error/warning message and tell me what it says.
>>
>> Makoto
>>
>> On Wed, Jul 27, 2016 at 3:50 PM, Maya Pinacle <mayapinacle at gmail.com>
>> wrote:
>>
>>> Hi all,
>>>
>>> I collected my data with 32 channel BrainProducts cap, and would like to
>>> locate dipoles via Dipfit. I tried to use manual Co-registration option
>>> choosing BEM MNI as head model however unfortunately it is not working well
>>> and it is very difficult to align the electrode template with my own
>>> electrode locations.
>>>
>>> However tutorial says that if the electrode locations within the
>>> Internaitional 10-20 system best way is to use standard channel coordinates
>>> associated with the head model. So as I know BrainProducts caps are in
>>> 10-20 systems so I used this option with recomended settings, choosing
>>> Boundary Element Mode (MNI) as Head model with No Coregistration to be
>>> chosen.
>>>
>>>
>>>  The tutorial also says to go to channel locations from edit option of
>>> EEGLAB and look up for the channel locations. In which case I choose ''use
>>> MNI coordinate file for BEM dipfit model'' option. In each condition
>>> (Coarse  fine or auto fit ) the coordinates of the dipoles seems sort of
>>> overlapping rather than spreaded all over the brain. And when I create
>>> STUDY from different subjects file and cluster the component dipoles they
>>> lined up in a very straight coordinates (I have added 4 pictures.)
>>>
>>> When I compare visually a component and a dipole that represents it, it
>>> seems that estimation of the dipole location is pretty good with those
>>> selection of options as it was described in the tutorial. However, this
>>> very well organised appearance of the dipoles in a cluster made me think
>>> that whether something wrong with it. Because it seems like rather than
>>> finding actual source, the dipoles try to locate around the channels and I
>>> wonder whether the result is kind of misleading. So I wonder is there
>>> anyone would like to comment on that? I can also share the data in the case
>>> you would like to see.
>>>
>>> So from one data the clusters and dipole locations can be found here.
>>>
>>> Cluster 1 - 33 dipoles - Sagital
>>> https://www.dropbox.com/s/rf77qcznrk7bvia/cluster1_sagital.png?dl=0
>>>
>>> Cluster 1 - 33 dipole - Top
>>>
>>> https://www.dropbox.com/s/9l2p7l7kmlsz7r0/cluster1_top.png?dl=0
>>>
>>> Cluster 2 - 62 dipole Sagital
>>>
>>> https://www.dropbox.com/s/cphtiemq05xeacu/cluster2_sagital.png?dl=0
>>>
>>>
>>> Thank you
>>>
>>> Maya
>>>
>>> Cluser 2 - 62 dipole Top
>>> https://www.dropbox.com/s/64ofdpixqo6bw4k/cluster2_top.png?dl=0
>>>
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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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