I am running a binary classification over 100 subjects' EEG data, and I want to test the average (over subjects) performance's significance using permutation test. I need to generate a null distribution. Could anyone help me how to produce null distribution?
I have presented two types of sounds to the subjects for 1000ms (1000 time points). So there are two condition in the experiment. For each subject and condition, there are 200 repetitions. So the dimension of data for each subject is: 400 (trials) * 32 (channels) * 1000 (time points). For each subject and at each time point, I have performed a binary classification to discriminate between the two conditions. This gives a classification performance for each time point and each subject. I have averaged this signal over subjects to get the mean classification performance (the dimension is: 1*1000). Now I want to test the significance of the results (decoding between two conditions) at each time point using permutation test.