Help with dipole fitting
Ludwing Torres
lumatobu2 at HOTMAIL.COM
Fri Jul 23 02:56:34 CEST 2010
Hi, I'm very sorry for using capital letters, please excuse me.
I'm new at fieldtrip, I don't know much about this and I'm searching for help desperately.
Well, I am trying to compute a fordward model by now, like this:
V=A*J
where:
V= a matrix of potentials measured in the scalp surface by each electrode, for example 32 electrodes or channels and 5 seconds at 256 samples per second, (which is equal to 5*256=1280, which comes to a 32x1280 matrix, one epoch I guess, and one trial, just measure, no events, please correct me if i'm wrong)
J= a matrix of the sources in the brain that produce the potentials above, with its time course, which are more than the electrodes placed there.
Let me understand this: ¿these sources and its time course, are the same dipole moments?
If so, ¿The sources (dipoles) have a time component in the three dimensions in the dipoles?
Thus, if we consider 128 sources, ¿ are we considering 128 dipoles, and J matrix would be 128x1280 with the time course?
or ¿Are we considering 128 sources of 3 dimensions and J matrix would be of 128x(1280x3)?
A= the lead field matrix. I've seen the function compute_leadfield of FieldTrip, This uses the electrodes positions, the dipoles (or sources) positions, and the standard volume of sphere and conductivities to perform the computing of a leadfield matrix that has dimensions numch x (3xnums) where numch=nuber of channels or electrodes (32 in this case) and nums=number of sources (in this case 128) ¿why is the number of sources multiplied by 3? ¿ it is because they compute the leadfield matrix to each of the cartesian coordinates? and if so, ¿How should I take the J matrix to compute the fordward model? ¿ should I take this each row having the time course of the sources, in the order: row 1:3 dipole n1 (x;y;z) , row 4:6 dipole n2 (x;y;z) , row 7:9 dipole n3 (x;y;z) , row 10:12 dipole n4 (x;y;z) and so on? ¿ so, I'd have a (128x3)x1280 matrix, (128x3) rows and 1280 columns, and not like above 128x(1280x3)?
And, once I have performed the forward model and I compute the V matrix, ¿Which function could I use to perform the inverse problem, i.e. , could I use a function that allows me recovering or regain the J matrix from the A and V matrices, and compare the new J with the old J to see if the inverse problem could be performed well?
Please, If you could suggest me some article or book or paragraph that I can read to clear these doubts, or if you could clear these to me yourselves, I would be very much thankful to you, please I'm begging you help please. Sorry for all the possible fouls and lacks of politeness, sincerely.Thanks for your attention.
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