[Mne_analysis] visualizing "activation" regions with MNE

[Martin Luessi]

Martin Luessi wrote:
> Mingbo Cai wrote:
>> Thanks Dan!
>> I tried tksurfer but it is less intuitive for me to draw ROI there by hand. Does anyone know if there is information of neighborhood between vertices so that we can include neighbor vertices of each activated vertices in order to obtain a continuous "activation" patch?
>>
>> Mingbo
> 
> For visualization purposes, you could try to use PySurfer 
> (http://pysurfer.github.com). In the latest version on github, there is 
> an example "plot_meg_inverse_solution.py", which shows how to show MEG 
> activations on the surface. Internally, the function 
> utils/smoothing_matrix is used to create a matrix which interpolates the 
> data from a down sampled mesh to the high resolution freesurfer mesh.
> 
> For your application, you could create an all-zero array with the same 
> number of elements as your low-res mesh. Set the elements corresponding 
> to the label to some non-zero value and then use the interpolation 
> matrix to create a high resolution version of your label. The obtained 
> array can then be visualized using the add_data function of the Brain 
> object.

Actually, it is even simpler than that. You can use Brain.add_data() 
directly with data defined on the low-resolution mesh and PySurfer will 
create the interpolation matrix automatically (you will need to specify 
the vertices on which your data is defined).

> I hope this helps,
> 
> Martin
> 
>> -----Original Message-----
>> From: Dan Wakeman [mailto:dgwakeman at gmail.com] 
>> Sent: Monday, January 30, 2012 3:59 PM
>> To: Mingbo Cai
>> Cc: mne_analysis at nmr.mgh.harvard.edu
>> Subject: Re: [Mne_analysis] visualizing "activation" regions with MNE
>>
>> Hi Mingbo,
>>
>> This will depend on how the ROIs look from the criteria. You could try
>> to go through and generate a label using the vertex numbers you have
>> produced and tksurfer. i.e. select each of the vertices one by one and
>> use the draw line features to generate a closed ROI. This will likely
>> end up including more vertices than the ones, which have "passed the
>> criteria". It may also be influenced by the size of the source space
>> you use.
>>
>> D
>>
>> On Mon, Jan 30, 2012 at 4:52 PM, Mingbo Cai <mcai at cpu.bcm.edu> wrote:
>>> Dear colleagues,
>>> I have a question of visualizing interesting regions. I identified a group
>>> of vertices of which the time course of mne pass certain criterion, saved
>>> these vertices to a label file, and viewed them with mne_analyze. But
>>> probably because the vertices that have mne estimation are only a subset of
>>> all the vertices on the cortex, they appear as isolated dots within a
>>> constrained area. So my question is: is there any way that I can find all
>>> the vertices that are within the region this group of “activated” vertices
>>> span? In this way, instead of showing many isolated dots, I can show a small
>>> region on the inflated brain just as what we usually see when we load a
>>> label file from freesurfer parcellation.
>>>
>>>
>>>
>>> Mingbo Cai
>>>
>>> Department of Neuroscience
>>>
>>> Baylor College of Medicine
>>>
>>>
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> 
>