[FieldTrip] Interpolation for power values in surface source space.

[Schoffelen, J.M. (Jan Mathijs)]

Hi Jinhan,

I assume that you have first tried a 3D visualization (i.e. cfg.method = ‘ortho’ in ft_sourceplot) and ensured that everything looks OK with respect to coregistration with the anatomical image that you use for plotting, and also with respect to the metric units? Note that everything needs to be consistent, for the source reconstruction, and the visualization, to make sense.


Best wishes,

Jan-Mathijs

On 17 Jan 2024, at 16:15, Park, Jinhan via fieldtrip <fieldtrip at science.ru.nl<mailto:fieldtrip at science.ru.nl>> wrote:

Hello,

I am Jinhan Park, a third-year Ph.D. Candidate at the University of Florida. I am currently working on the analysis of resting-state EEG data with eyes closed in the source space. For the data analysis, I employed EEGLAB for preprocessing, ICA, and dipole fitting with independent components. The processed datasets were then transformed into the FieldTrip format for source localization (eLORETA).

I created a source model using 'ft_prepare_leadfield' and obtained distributed dipoles' power values using 'ft_sourceanalysis'. With this data, I attempted to visualize a 3D brain figure using 'ft_sourceplot' with the surface method. However, I noticed that certain areas of the brain appeared empty, and despite their size being relatively small, it's causing some inconvenience. I've heard that this issue can potentially be addressed by interpolating the distributed values, but I'm uncertain about how to proceed.

Could you please let me know how to fix this problem?

By the way, I wrote down some codes I did.
% Source model
vol = load('-mat', EEG.dipfit.hdmfile);% Load headfile from EEGLAB data processed by DIFIT
cfg            = [];
cfg.elec       = dataPre.elec;% Channels' information
cfg.headmodel  = vol.vol;% Headmodel
cfg.resolution = 10;   % use a 3-D grid with a 1 cm resolution
cfg.unit       = 'mm';% Unit of voxels
cfg.channel    = { 'all' };% Channels of interest
cfg.normalize  ='yes';
sourcemodel = ft_prepare_leadfield(cfg);% Create a source model (leadfield)
%% Inverse solution
% eLORETA
cfg             = [];
cfg.method      = 'eloreta';% Method for source localization
cfg.sourcemodel = sourcemodel;% Put the leadfield
cfg.headmodel   = vol.vol;% Headmodel
source          = ft_sourceanalysis(cfg, freq_pow);% Conduct the inverse solution. freq_pow is the power values in the frequency domain.
source_paf = source;
source_paf.avg.pow = dominant_f;% Change original PSD values (1 to 40 Hz) to peak frequencies
cfg = [];
cfg.method         = 'surface';% 3D brain image
cfg.funparameter   = 'pow';% Represent "sourceoi.avg.pow"
cfg.maskparameter  = cfg.funparameter;
cfg.funcolormap    = 'jet';% Types of the colorbar
cfg.projmethod     = 'nearest';
cfg.surffile       = 'surface_white_both.mat';% Brain tamplate
cfg.surfdownsample = 10;% Downsample the voxels
ft_sourceplot(cfg, source_paf);% Plot the eLORETA figure
I would sincerely appreciate it if you could answer my question.

Best regards,
Jinhan




Jinhan Park (Hans) | Ph.D. candidate
Department of Applied Physiology and Kinesiology
University of Florida
Laboratory of Rehabilitation Neuroscience | lrnlab.org<https://eur01.safelinks.protection.outlook.com/?url=http%3A%2F%2Flrnlab.org%2F&data=05%7C02%7Cfieldtrip%40science.ru.nl%7C6db815f76c1444606bde08dc18446aad%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638411929313261006%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=EIDAhCVlnQK9OZ9DiyxKeT%2Fatu1eYlTbQ4XPCS49HvI%3D&reserved=0>
Phone: +1 (352) 328-6605
Email: jinhan.park at ufl.edu<mailto:jinhan.park at ufl.edu>



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