[FieldTrip] interpolate missing grad positions

[go puluto]

Hi All,

Thanks for the reply. The reason I wanted to interpolate the missing grad
is that I thought more sensors would give a better forward solution. For
the forward modelling, we calculate how the unit activation in the
souces transformed to the sensors. Is it correct that If there are missing
channels, after the forward calculation, the gap between sensors need to be
interpolated in the sensor space? I thought this is the reason for a better
forward solution using a higher number of sensors.
I am sorry that I don't get the point of rank deficiency, first of all,
after interpolation, could we solve the dependent (rank deficient) problem
by filtering? Secondly, how the rank deficiency affects the
activity transformation from a higher-dimension (source) to a lower
dimension (sensors), we could transform dependent 2d vectors to a 3d space,
right?
The interpolation function, ft_chanrepair, solves the interpolation when
the grad position is given, i.e., we can interpolate the missing channels
using the ctf275 template. However, for the source reconstruction, we need
the online recorded grad positions, in which some sensors were initially
missed at the data collection stage. So, I was wondering could I
reconstruct the missing grad positions.
Thanks for all the answers, I am very happy to learn in the community.

best,
Fan
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