Thanks Paul!

I'm using 3TProject to regress out fixed components from resting state data and I use a bandpass filter 0.01 0.1 (TR=2):
I get this output:

++ setting up stopband frequency mask
+ Block #0: 250 time points -- 147 stopband regressors
++ 1 Blocks * 3 polynomials -- 3 polort regressors
+ -- 65 other fixed ort regressors
++ 250 retained time points MINUS 215 regressors ==> 35 D.O.F. left
++ no -mask option ==> processing all 123410 voxels in dataset
++ Compute pseudo-inverse of fixed orts

I have two questions:

1. What are the minimum D.O.F. acceptable for resting state data?
2. reading the afni_proc.py documentation was very helpful but I'm confused with the recommendation given in Resting state note ~2~.
"Resting state data should be processed with physio recordings (for typical single-echo EPI data). Without such recordings, bandpassing is currently considered as the default."
but then below that it seems that the recommendation is not to bandpass, because we end up loosing 60% of D.O.F (with TR of 2). I have no physio recordings, so do you still recommend bandpass filtering the resting state data?
Best regards,
Sam