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Dear Christodoulos,
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<div class="">The ‘pow’ field is obtained by sandwiching the sensor level covariance between the spatial filter, i.e. w’ * C * w. </div>
<div class="">The ‘mom’ field is obtained by left multiplication of the spatial filter with the sensor level average, w’ * avg. </div>
<div class="">Computing the variance from the w’*avg will indeed yield something that is different from the ‘pow’.</div>
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<div class="">This is because the sensor-level covariance is typically the average of the single trial covariances, and not the covariance of the trial average.</div>
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<div class="">Best wishes,</div>
<div class="">Jan-Mathijs</div>
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<div class="">PS: the ’noise’ is typically obtained by sandwiching a scaled identity matrix between the spatial filters, i.e. w’ * Identitymatrix * w * <a number>, where the <a number> is usually the smallest singular value of the matrix. I would take this
with a grain of salt, since the noise is rarely diagonal, nor does the smallest singular value accurately reflect the noise level.</div>
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<div class="">On 26 Nov 2020, at 16:15, Christodoylos Karittevlis <<a href="mailto:christodoylos_k@hotmail.com" class="">christodoylos_k@hotmail.com</a>> wrote:</div>
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Dear Fieldtrip community,</div>
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I have one question. I am using the beamformer LCMV method for source localization of simulated data (1 dipole in a sphere).</div>
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I am trying to figure out how the source.avg.power is estimated from the function ft_sourceanalysis. Can anyone give me some explanation on that or maybe some directions where I can find more details on the estimation of power/noise using the function ft_sourceanalysis.</div>
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I tried to estimate it from the source.avg.mom but I could not really produce the power.</div>
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Thank you in advance.</div>
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Kind regards,</div>
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Christodoulos Karittevlis</div>
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PhD Candidate, ESR11- iCONN network</div>
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