The purpose of this page is just to serve as todo or scratch pad for the development project and to list and share some ideas.
After making changes to the code and/or documentation, this page should remain on the wiki as a reminder of what was done and how it was done. However, there is no guarantee that this page is updated in the end to reflect the final state of the project
So chances are that this page is considerably outdated and irrelevant. The notes here might not reflect the current state of the code, and you should not use this as serious documentation.
The rat beamformer
Introduction
The project deals with the source reconstruction of brain activity recorded by a polyimide grid placed in direct contact with the dura, and thus very close to the gray matter. The step to generate a correct inverse solution are listed belo
Creating a model for the rat inner skull
This is done already (George’s work, here a part of his email…)
“The volume conductor is an STL file that represents a closed surface of the inside of the skull. The front area (front of the olfactory bulb) and the back area (where the spine comes out) are not closed in reality so I had to close them manually. They are not too large holes and they are far from where we collect data so I hope this won’t interfere with the model. The 0,0,0 is the bregma point. I did my best to keep the triangles as isoskeles as possible. (…) So I have to take the original extruded object and put it through a smoothing process that I do by eye. The resulting surface is much closer to the real bone structure but the splines are not any more fully coincident with this surface. (…) I would use the stl file which is a very good overall fit to reality and forget about the splines. (…) I wanted in the area of functional interest my Loni atlas pictures to be as close to the existing Paxinos atlas slices and Paxinos didn’t do every half a millimetre slices.”
Refine the model for the rat inner skull
This involves checking for uniqueness of the vertices and interpolation of the triangles in the area covered by the grid’s leads. These functions are partly implemented in the ‘surface’ branch of FieldTri http://code.google.com/p/fieldtrip/source/browse/#svn%2Fbranches%2Fsurface
Has to be completed and consists o

retriangulation of the mesh
addpath ~/fieldtripdev/surface cfg=[]; cfg.checkdoublevertices = ‘yes’; cfg.convert = ‘yes’; newshape = ft_surfacecheck(cfg,shape);

interpolation of the triangles

elastic repositioning (to create a regular grid triangles spacing)
Look at the Gram matrix of the leadfields to check for regularity, by looking at the sorted eigenvalues.
Use the geometrical model to create a ‘vol’ structure
FieldTrip typically generated a volume conductor structure when dealing with Electrostatics/Magnetostatics forward solutions. Here is the logi
shape = ft_read_headshape('rat_dura','format','STL');
cfg=[];
cfg.method = 'dipoli';
vol=ft_prepare_headmodel(cfg,shape);
where ‘shape’ is a structure defining the boundary for the Boundary Element model to be used in the next step. (shape.tri is the vertex connectivity for each triangle element, shape.pnt are all the vertices, a M points X 3 matrix).
Use the ‘vol’ structure to create the leadfields
The electrodes are also given as a matrix of NX3 elements. They have to be put in a FieldTrip ‘sensor’ structure (see ). Given the electrodes and the volume conductor we are already able to generate the forward solution by means of the general purpose function ‘ft_prepare_leadfield’.
% check for uniqueness of triangles and remove the nearest ones...
%initialize the elec structure
elec = [];
elec.chanpos = elecmat;
elec.elecpos = elecmat;
for i=1:size(elecmat,1)
elec.label{i} = num2str(i);
end
The real labels are then assigned using the routine ft_apply_montage (a manual operations to be done by the experimenter). The next step is the calculation of the lead field
% Option 1. Calculate the lead fields (example with only one point)
cfg = [];
cfg.elec = elec;
cfg.vol = vol;
cfg.grid.pos = point; % this can be done manually by clicking
lf = ft_prepare_leadfield(cfg);
% Option 2. Alternatively use a grid of equally spaced points
res = 1; % 1 mm spacing
xlim = [8 8];
ylim = [15 15];
zlim = [0 12];
cfg = [];
cfg.grid.xgrid = xlim(1):res:xlim(2);
cfg.grid.ygrid = ylim(1):res:ylim(2);
cfg.grid.zgrid = zlim(2):res:zlim(1);
gridd = ft_prepare_sourcemodel(cfg, vol, elec);
cfg = [];
cfg.elec = elec;
cfg.vol = vol;
cfg.grid = gridd;
lf = ft_prepare_leadfield(cfg);
Visualize the leadfields
Uses the function ft_plot_topo3d.m
Solve the inverse problem, finally …
See /tutorial/beamformer, look for ‘Scanning the brain volume’