Dear CONN Team,

We are using the CONN toolbox to perform seed-based functional connectivity analyses from the subgenual ACC (sgACC) in native anatomical space, using externally preprocessed 7T fMRI data aligned to each subject’s FreeSurfer conformed space (verified in Freeview). Our goal is to export Fisher Z-transformed connectivity maps in native space for use in TMS neuronavigation.

We initially ran the analysis in MNI space, which produced good whole-brain connectivity maps.

However, for individualized targeting, we now need all processing and outputs to remain in native anatomical space.

Settings We Tried for Native-Space Output:

• 
  

  Disabled normalization to MNI in the preprocessing pipeline

  
  


• 
  

  Set bounding box to: [-180 -180 -180 ; 180 180 180] to avoid template constraints

  
  


• 
  

  Changed registration type from 'MNI' to 'rigid'

  
  

Despite these steps, the output maps still show misalignment between functional and anatomical images, suggesting internal transformations may still be applied.

We would greatly appreciate your help with:

1. 
   

   Which preprocessing steps must be modified or disabled to ensure full processing and outputs remain in native anatomical space?

   
   
   
2. 
   

   How to correctly configure CONN for use with externally preprocessed data, already aligned in native space?

   
   
   
3. 
   

   How can we visualize the raw (unthresholded) functional connectivity map from sgACC, overlaid on the subject’s anatomical image (e.g., FreeSurfer conformed T1)?

   
   
   
4. 
   

   Is there a way to view the full Fisher Z map without thresholding or restricting to predefined ROIs (e.g., to inspect whole-brain patterns)?

   
   
   

Thank you very much for your support—native-space processing is essential for our individualized TMS targeting workflow.

Best regards,
Farzan