How to calculate T test for my data matrix

Question

I have a fMRI data matrix, the size of which is 9*10 (I randomly put the value in it). The first two rows are under class 1 stimulus;the next two rows are under class 2 stimulus, the next next two rows are under class 3 stimulus, the last three rows are under no stimulus(rest condition). I want to test difference in signal between two conditions(class 1 stimulus vs rest condition), (class 2 stimulus vs rest condition) and (class 3 stimulus vs rest condition). My question is how to do T-test for the fMRI data?

H1: Condition1 ≠ Condition2
H0: Condition1 = Condition2

And should I compute based on these:1.Difference between the mean intensities of each condition
2. Degree of overlap in intensities
-7  0   -1  -5  -1  -2  -3  0   1   -8
2   -1  3   -1  -1  -1  -2  1   2   -3  ----> under class 1 stimulus

-4  -1  1   -1  8   1   0   -8  -2  -1
-2  -2  -5  -3  -1  -1  -15 0   -1  2   ----> under class 2 stimulus

3   0   5   8   -5  2   -2  8   10  -8
5   0   2   -4  8   2   6   0   -11 2   ----> under class 3 stimulus

-6  4   1   -2  6   -6  -5  0   11  -6
6   8   3   -4  -1  -5  5   -4  2   0
3   2   1   -6  -8  -4  2   0   5   3   -----> under rest (no stimulus) condition 

Answer 1

It looks like you want to perform 2 sample (paired) t-test, in which case you want to use the ttest2 function. It's quite easy to compute: Without much information about your data I re-arranged them into single row vectors for comparisons.

The code I use is straightforward:

clear
clc    

% Define experimental data.
Cond1 =  [-8 2   -1  3   -1  -1  -1  -2  1   2   -3];

Cond2 = [-4  -1  1   -1  8   1   0   -8  -2  -1 -2  -2  -5  -3  -1  -1  -15 0   -1  2];

Cond3 = [3   0   5   8   -5  2   -2  8   10  -8 5   0   2   -4  8   2   6   0   -11 2];

Rest = [ -6  4   1   -2  6   -6  -5  0   11  -6 6   8   3   -4  -1  -5  5   -4  2   0 3   2   1   -6  -8  -4  2   0   5   3] ;

% Group data for easy referencing in plots
AllData = {Cond1;Cond2;Cond3;Rest}; 

% Perform the t tests. The p-value is given together with h, which tells you whether the null hypothesis is rejected (value of 0) or not (value of 1).

[h1,p1]=ttest2(Rest,Cond1)

[h2,p2]=ttest2(Rest,Cond2)

[h3,p3]=ttest2(Rest,Cond3)

PValues = [p1;p2;p3];

Plot the results

figure

for k = 1:4

    if k < 4
        subplot(1,4,k)
        boxplot(AllData{k})
        set(gca,'YLim',[-10 10])

        TitleString = sprintf('Condition %i\n p-value of %0.2f',k,PValues(k));
        title(TitleString,'FontSize',14)

    else
        subplot(1,4,k)
        boxplot(AllData{4})
        set(gca,'YLim',[-10 10])
        title('Rest','FontSize',14)

    end
end

Giving the following:

Is that what you meant? If not please provide more details about your data.