You can definitely create a custom color map in MATLAB. One way to do this is by defining the RGB values for your maximum, minimum, and indexed value (your value of "1" is what I am calling the indexed value). You can then create a vector representing RGB values ranging from the minimum to the indexed colors and from the indexed to the maximum colors.
Because the index value may not be the median value of the dataset, the vectors' sizes will need to be adjusted proportionally to where the index falls between the minimum and maximum values.
I have written a script that illustrates this workaround. See if you can apply it to your situation.
L = 10; %number of datapoints
data = 3.6*rand(L); % create example data set with values ranging from 0 to 3.6
indexValue = 1; % value for which to set a particular color
topColor = [1 0 0]; % color for maximum data value (red = [1 0 0])
indexColor = [1 1 1]; % color for indexed data value (white = [1 1 1])
bottomcolor = [0 0 1]; % color for minimum data value (blue = [0 0 1])
% Calculate where proportionally indexValue lies between minimum and
% maximum values
largest = max(max(data));
smallest = min(min(data));
index = L*abs(indexValue-smallest)/(largest-smallest);
% Create color map ranging from bottom color to index color
% Multipling number of points by 100 adds more resolution
customCMap1 = [linspace(bottomcolor(1),indexColor(1),100*index)',...
linspace(bottomcolor(2),indexColor(2),100*index)',...
linspace(bottomcolor(3),indexColor(3),100*index)'];
% Create color map ranging from index color to top color
% Multipling number of points by 100 adds more resolution
customCMap2 = [linspace(indexColor(1),topColor(1),100*(L-index))',...
linspace(indexColor(2),topColor(2),100*(L-index))',...
linspace(indexColor(3),topColor(3),100*(L-index))'];
customCMap = [customCMap1;customCMap2]; % Combine colormaps
colormap(customCMap)
psudo = pcolor(data);
colorbar
