Does xcp-d complete a Fisher's z transformation?


I completed my post-processing fMRI analysis with xcp-d. I am now wanting to go on to perform a z-test and t-test on my data. I am wondering if xcp-d applies a Fisher’s z transformation to the Pearson correlation coefficients for the functional connectivity matrices?

I am new to fMRI analysis and also am wondering if you have suggestions for software to use for the z-test and t-test?

Thanks for your help!


XCP-D doesn’t do the transform itself, but you can apply the transform pretty easily if you want. Something like the following should work:

import pandas as pd
import numpy as np

df = pd.read_table("/path/to/corrmat.tsv", index_col="Node")
# set diagonal to 0
np.fill_diagonal(df.values, 0)
df_z = df.apply(np.arctanh)
df_z.to_csv("output.tsv", index_label="Node", sep="\t")

You can use most statistical software to do a t-test across these converted correlation matrix files. scipy.stats.ttest_ind would probably work, depending on the specific test you want to do.

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