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main.m
Implements the comparison between 4 different methods to compute the mean ROI activation.
First, turn on the TBV 3.2 with the network plugin 1.7.
run main.m.
The first part, will establish a connection with the network plugin (please define configs.TBV_IP and configs.TBV_PORT according to the properties of the TBV network plugin). If the connection is successful a message will appear in the MATLAB command prompt: "connection open: 1"
Then, the number of ROIs is retrieved (tbvNetInt.tGetNrOfROIs();) as well as the coordinates for each ROI. Please notice that TBV indexes variables using 0-index, and MATLAB 1-index (to retrieve coordinates for the ROI #1, please use tGetAllCoordsOfVoxelsOfROI(0) )!
coordsOfVoxelsOfROI = cell([1 n_rois]);
for i=1:n_rois
coordsOfVoxelsOfROI{i} = tbvNetInt.tGetAllCoordsOfVoxelsOfROI(i - 1);
end
The function tGetDimsOfFunctionalData returns the dimensions of the functional dataset (64x64x30 for the default dataset); and tGetExpectedNrOfTimePoints returns the number of points expected in the dataset.
Then we can iterate over time t (Please notice that TBV indexes variables using 0-index, and MATLAB 1-index):
while time <= currentTime
if time == currentTime && currentTime ~= expectedTime
disp('Waiting...')
pause(5)
counter = counter + 1;
if counter == 5
break;
end
else
%---Method 1 --> Get Mean ROI
[ROImeansM1(time,:),timeM1(time)] = method1(n_rois,tbvNetInt,time-1);
%---Method 2 --> All Voxels
[ROImeansM2(time,:),timeM2(time)] = method2(n_rois,tbvNetInt,coordsOfVoxelsOfROI,xDim,yDim,time-1);
%---Method 3 --> All Voxels Raw
[ROImeansM3(time,:),timeM3(time)] = method3(n_rois,tbvNetInt,coordsOfVoxelsOfROI,xDim,yDim,time-1);
%---Method 4 --> Voxels 1by1
[ROImeansM4(time,:),timeM4(time)] = method4(n_rois,tbvNetInt,coordsOfVoxelsOfROI,time-1);
fprintf('Time %d \n',time);
time = time + 1;
counter = 0;
end
currentTime = tbvNetInt.tGetCurrentTimePoint;
end