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The longitudinal stream extracts reliable volume and thickness estimations across individuals across multiple time points. This workflow generates an unbiased within-subject template space and image to create a new data set in a longitudinal series, improving robustness and sensitivity of the overall longitudinal analysis.

Further information on the importance of the longitudinal pre-processing stream, and steps on how to run it are listed here and here.

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There are 3 main steps for longitudinal pre-processing:

1. Recon-all

Cross sectionally process all time points with the default recon-all pipeline (manually or automatically)

Code Block
recon-all -i FTD####.nii -subjid subject1_tp1 -all

2. Base

Create an unbiased template from all time points for each subject.

Code Block
recon-all -base subject1_template -tp subject1_tp1 -tp subject1_tp2 -tp subject1_tp3 ... -all

3. Long

Longitudinally process all time points

Code Block
recon-all -long subject1_tp1 subject1_template -all
recon-all -long subject1_tp2 subject1_template -all
recon-all -long subject1_tp3 subject1_template -all