[FieldTrip] REPOST: Beamforming, "Inf" during source estimation by subject

[Tate, Lindsey R.]

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Hello Fieldtrip Community,


On Tuesday 6/28, I sent out the original message forwarded below. I received some response but have been unable to resolve my problem. [Attempted to allow lambda to be estimated/not specified, but this didn't eliminate the "Inf" in the pow matrices.]


I've been working on beamforming the MEG data collected from 16 subjects during a saccade task. There are 4 conditions, with a maximum of 30 trials each per subject (some trials eliminated due to loss of focus). This is my first time beamforming so I've been heavily relying on the tutorial.


I'm having what appears to be two issues:


1) Number of trials per subject may be too low. When I collapse across all subjects or even collapse across two random subjects so as to artificially increase the number of trials per "artificial subject," real numbers are produced by ft_sourceinterpolate in the pow matrix. When I run each subject individually, the pow matrix from ft_sourceinterpolate "Inf" where numbers were for the other runs. Is there a way to resolve this issue, such as a default setting to override? Or do I have too few trials per condition?


2) The pow matrix from ft_sourceinterpolate produces primarily "NaN," with about 90% of the rows being "NaN." This seems problematic. Also, it seems like it may be causing problems with ft_sourcestatistics as the stat.prob and stat.mask matrices always come back empty, even when ft_sourceinterpolate produces pow matrices with real numbers divided by "artificial subjects." Could this prevalence of "NaN" be an indication that the beamforming isn't happening correctly? Could the prevalence be causing the ft_sourcestatistics to produce blank stat.prob and stat.mask matrices?


Code and raw dataset attached.

Thank you for any assistance or guidance you may offer!

Lindsey
University of Oklahoma



________________________________
From: Tate, Lindsey R.
Sent: Tuesday, June 28, 2016 3:05 AM
To: fieldtrip at science.ru.nl
Subject: Beamforming, "Inf" during source estimation by subject


Hello Fieldtrip Community,


I've been working on beamforming the MEG data collected from 16 subjects during a saccade task. This is my first time beamforming so I've been heavily relying on the tutorial.


When I collapse trials across subjects and do beamforming, I can get the ft_sourceplot commands to produce something that makes some sense. However, I need to be able to have the data separated by subject for ft_sourcestatistics. I've created structures that should work for this purpose and that look correct. However, the ".pow" from the Neural Activity Index calculation step ends up mostly "NaN" and partly "Inf" when I run the beamforming divided by subject.


Is this related to the number of trials per subject somehow (e.g., do I have too few? is there some kind of setting I need to change?)? Why is the ".pow" coming back "Inf" instead of a real number? Does anyone have suggestions for fixing this problem so that I don't get "Inf" anymore?


My code and raw data structure are attached.


Thank you,


Lindsey Tate

University of Oklahoma
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