Hi Zhou,

Once your data is preprocessed and you have transformations mapping your data to the reference space, you can use legacy BIS to estimate connectivity. The legacy manual will get you much of the way there—see "Chapter 13: The Single Subject fMRI Tool":
https://medicine.yale.edu/bioimaging/sui... Please note that this will require legacy BIS—it is not yet possible to estimate matrices or GLM-based activation in BISWeb.

Essentially this will guide you in the process of creating a "setupfile" to estimate parameters for a GLM, but you can instead change some parameters in this file to estimate functional connectivity*. You can then run the setupfile to estimate FC like this:
bis_fmrisetup.tcl my_setupfile.xmlg matrix

Feel free to reach out if you encounter any issues going through these steps.

Best,
Stephanie

* Functional connectivity-specific parameters in the setupfile + example arguments:
#-----------------------------------------------------
#Resting State Connectivity Extra Inputs
#-----------------------------------------------------
#VOI Definition
/my_dir/shen_1mm_368_parcellation.nii.gz
#VOI Definition Space (Reference,Anatomical,Conventional,Functional)
Reference
#Inverse Reference Transformation
/my_dir/i.matr
#-----------------------------------------------------
#Connectivity Parameters
#-----------------------------------------------------
#Mask Level (% of max intensity)
masklevel : 0.05
#Polynomial Drift
driftpol : 3
# Slice Mean Removal
slicemeanremoval : 0
# Volume Mean Removal
volumemeanremoval : 1
#Raw Correlation
rawcorrelation : 0
#Z Transform
ztransform : 0
#Process Runs Individually
individualruns : 0
#Temporal Smoothing Sigma (Frames)
temporalsigma : 1
#Intrinsic Connectivity Threshold
threshold : 0.25
#Intrinsic Connectivity Range
range : Positive
#Intrinsic Connectivity Mode
mode : Sqr
#Use VOI Image as mask For Intrinsic Connectivity
usermask : 1
#Preprocess (Eliminate Motion Parameters)
usemotionparams : 1
#Preprocess (Eliminate CSF/White Matter Mean)
usecsfmean : 1