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Following an email exchange with Bob Cox, I wanted to record that the the default drift model in AFNI is as follows:
It is a Legendre polynomial, the order automatically set by the duration of the imaging run to N = 1+int(D/150) where D is in seconds.
(Where I assume int() to be the usual truncation, i.e. floor() for positive values).
For short runs (less than 150 s) this will be linear, but for longer runs it will be some higher order polynomial. This is the behaviour obtained by the (recommended) "afni_proc.py" or "uber_proc.py" tools.
The text was updated successfully, but these errors were encountered:
@cmaumet etc,
Following an email exchange with Bob Cox, I wanted to record that the the default drift model in AFNI is as follows:
(Where I assume int() to be the usual truncation, i.e. floor() for positive values).
For short runs (less than 150 s) this will be linear, but for longer runs it will be some higher order polynomial. This is the behaviour obtained by the (recommended) "afni_proc.py" or "uber_proc.py" tools.
The text was updated successfully, but these errors were encountered: