I have a small footprint EEG measurement device with 8 measurement electrodes and 1 reference electrode - the reference electrode is in the center of the sensor array, 4 measurement electrodes on the corners of the 2cm x 2cm sensor array and 4 measurement electrodes in the center of the faces of the square making a pattern as given below,
X X X
X X X
X X X
Now, if I take a single or 10 contiguous and concurrent set of time samples of voltage levels from each of these 8 spatial channels, how do I create a MATLAB plot or scatter plot of Interpolated distribution of electric potentials with "hot" and "cold" regions as shown in the attached figure ?
.
Source: http://www.sciencedirect.com/science/article/pii/S1053811913012615
Any suggestion on achieving the above would be of great help.
M=-1+2*rand(3) %// sample data
[x,y]=meshgrid(0:0.5:1); %// grid for sample data
[X,Y]=meshgrid(0:0.005:1); %// grid to interpolate onto
IN=interp2(x,y,M,X,Y); %// interpolate data onto finer grid
Now the plotting (note I defined a new colormap that roughly matches with your example, it's at the bottom of the answer, just define it before doing colormap(MAP)
if you want to use it).
colormap(MAP)
surf(X,Y,IN,'EdgeColor','none') %// create the surface plot
caxis([-1 1]) %// set color axxis range
colorbar
shading interp
view([0 90]) %// put view right on top of plot, looking straight down
MAP = [...
0 1.000000000000000 1.000000000000000
0 0.952380955219269 1.000000000000000
0 0.904761910438538 1.000000000000000
0 0.857142865657806 1.000000000000000
0 0.809523820877075 1.000000000000000
0 0.761904776096344 1.000000000000000
0 0.714285731315613 1.000000000000000
0 0.666666686534882 1.000000000000000
0 0.619047641754150 1.000000000000000
0 0.571428596973419 1.000000000000000
0 0.523809552192688 1.000000000000000
0 0.476190477609634 1.000000000000000
0 0.428571432828903 1.000000000000000
0 0.380952388048172 1.000000000000000
0 0.333333343267441 1.000000000000000
0 0.285714298486710 1.000000000000000
0 0.238095238804817 1.000000000000000
0 0.190476194024086 1.000000000000000
0 0.142857149243355 1.000000000000000
0 0.095238097012043 1.000000000000000
0 0.047619048506021 1.000000000000000
0 0 1.000000000000000
0.047619048506021 0 0.952380955219269
0.095238097012043 0 0.904761910438538
0.142857149243355 0 0.857142865657806
0.190476194024086 0 0.809523820877075
0.238095238804817 0 0.761904776096344
0.285714298486710 0 0.714285731315613
0.333333343267441 0 0.666666686534882
0.380952388048172 0 0.619047641754150
0.428571432828903 0 0.571428596973419
0.476190477609634 0 0.523809552192688
0.523809552192688 0 0.476190477609634
0.571428596973419 0 0.428571432828903
0.619047641754150 0 0.380952388048172
0.666666686534882 0 0.333333343267441
0.714285731315613 0 0.285714298486710
0.761904776096344 0 0.238095238804817
0.809523820877075 0 0.190476194024086
0.857142865657806 0 0.142857149243355
0.904761910438538 0 0.095238097012043
0.952380955219269 0 0.047619048506021
1.000000000000000 0 0
1.000000000000000 0.047619048506021 0
1.000000000000000 0.095238097012043 0
1.000000000000000 0.142857149243355 0
1.000000000000000 0.190476194024086 0
1.000000000000000 0.238095238804817 0
1.000000000000000 0.285714298486710 0
1.000000000000000 0.333333343267441 0
1.000000000000000 0.380952388048172 0
1.000000000000000 0.428571432828903 0
1.000000000000000 0.476190477609634 0
1.000000000000000 0.523809552192688 0
1.000000000000000 0.571428596973419 0
1.000000000000000 0.619047641754150 0
1.000000000000000 0.666666686534882 0
1.000000000000000 0.714285731315613 0
1.000000000000000 0.761904776096344 0
1.000000000000000 0.809523820877075 0
1.000000000000000 0.857142865657806 0
1.000000000000000 0.904761910438538 0
1.000000000000000 0.952380955219269 0
1.000000000000000 1.000000000000000 0];