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Hi Sina,
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<div>There are 2 well-known issues related to beamforming EEG data that you need to look into, and tackle:</div>
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<div>- depending on the type of volume conductor used, there might be numerical instabilities close to the edges/boundaries of the said volume conductor.</div>
<div>- beamformers have an inherent depth bias, which needs to be addressed in some kind of contrast/NAI etc. before any visualized result kan be interpreted in a meaningful way.</div>
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<div>Please consult the literature (e.g. Britta’s paper: <a href="https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS1053811921010612&data=05%7C02%7Cfieldtrip%40science.ru.nl%7C6537ec6e7e5a49d13e2108dcfca359b3%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638663025711972955%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=nax3Rq7y0m8nKS3a5k8jSePtkIktT8bDnj8KZwkxYH8%3D&reserved=0" originalsrc="https://www.sciencedirect.com/science/article/pii/S1053811921010612" shash="LvFd8+cUZcSlhwdq438ZjklTZP3FcUya4ykbeMt1twHvAcdRi9NHT5KPn6C0HL3kIKuKL5w94hHsoSYJvvhV3f0SHtlpiqBFn6dLGD8AF8/HLtU07p5vWF3MTtuAPuFmmhpK/e/DpMxn9c23tBLSKPGFNl5Fo4xqz+FVvg22l+Q=">https://www.sciencedirect.com/science/article/pii/S1053811921010612</a>)
and online resources to get on track.</div>
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<div>Best wishes,</div>
<div>Jan-Mathijs</div>
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<div>On 3 Nov 2024, at 21:35, Sina Makhdoomi Kaviri via fieldtrip <fieldtrip@science.ru.nl> wrote:</div>
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<div>To whom it may concern,<br>
I am working with a dataset related to reach and grasp tasks involving<br>
six distinct motor tasks. I have divided the data based on event<br>
markers and am using DICS Beamforming for source localization. Here is<br>
an overview of the analysis steps I am following:<br>
<br>
I am using a multitaper method for frequency analysis (mtmfft with<br>
DPSS tapers) to compute the power and cross-spectral density (CSD) for<br>
frequencies ranging from 0 to 100 Hz. Subsequently, I perform DICS<br>
beamforming on the frequency-domain data to localize the sources in<br>
the brain.<br>
<br>
After obtaining the source estimates, I visualize the results using<br>
orthogonal views. The problem I'm encountering is that, instead of<br>
locating the main sources in the motor cortex as expected for the<br>
reach and grasp tasks, the beamforming results show activation in the<br>
parietal and occipital lobes. This is inconsistent with the expected<br>
motor activity. Could you please help me identify any issues with my<br>
approach or the code that might be causing this discrepancy?<br>
<br>
cfg = [];<br>
cfg.method = 'mtmfft';<br>
cfg.taper = 'dpss';<br>
cfg.output = 'powandcsd';<br>
cfg.foi = 0:5:100; % or when I use 18<br>
cfg.tapsmofrq = 2;<br>
powcsd_all = ft_freqanalysis(cfg, EEG_avg);<br>
cfg = [];<br>
cfg.method = 'dics';<br>
cfg.frequency = 18;<br>
cfg.grid = leadfield;<br>
cfg.headmodel = headmodel_eeg;<br>
cfg.channel = matching_channels;<br>
cfg.senstype = 'EEG';<br>
cfg.dics.keepfilter = 'yes';<br>
cfg.dics.lambda = '15%';<br>
source = ft_sourceanalysis(cfg, powcsd_all);<br>
%% Plot DICS Beamforming Results<br>
cfg = [];<br>
cfg.parameter = 'avg.pow';<br>
sourceint = ft_sourceinterpolate(cfg, source, mri_resliced);<br>
cfg = [];<br>
cfg.method = 'ortho';<br>
cfg.funparameter = 'pow';<br>
cfg.funcolorlim = 'zeromax';<br>
ft_sourceplot(cfg, sourceint);<br>
<br>
<br>
Best regards,<br>
Sina Makhdoomi Kaviri<br>
PhD Candidate & Graduate Research Assistant<br>
Sensorimotor Control Lab/Vinjamuri Lab<br>
Department of Computer Science and Electrical Engineering<br>
University of Maryland, Baltimore County<br>
<span id="cid:f_m321md080"><task4_trial1_subjectG01_BF.png></span>_______________________________________________<br>
fieldtrip mailing list<br>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip<br>
https://doi.org/10.1371/journal.pcbi.1002202<br>
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