Hey AFNI gurus,
I have recently encountered the 3dLocalACF function, and been interested in its various outputs. This interest has led to a few questions (predictably). The help notes state that this program is experimental - should I expect any dramatic changes in the near future?
A second, perhaps more interesting question, is how time is used in 3dLocalACF. I’ve found that the program requires 39 timepoints - is there a particular reason for the 39 TR boundary - something like the stability of the a,b,c estimates?
Thanks folks - it’s still fun to find a new AFNI tool that does exactly what you want that you never knew existed.
“Experimental” in AFNI-help-speak means that the program has not be used in a lot of cases. Which describes 3dLocalACF - as far as I know, I am the only person who has ever run this program. Any changes will only come when the program gets used again (by myself or by YOU), and issues arise.
The lower limit of at least 39 time points is from the fact that the first thing computed by the program (in each neighborhood) is the correlation of the central time series with every other voxel’s time series in the neighborhood. For stability, I set the lower limit on the number of time points to 39, so that the correlations would have some meaning (e.g., with only 9 time points, what does correlation even mean?). Where did I get “39”? I just made it up.
Thanks for the explanation - its a fun program, and despite all the warnings, isn’t even as slow as I expected it to be. So far no issues with this, and it seems to be behaving as I expect it to.
Am I correct in understanding that this time series correlation approach is fundamentally different from the approach used by 3dLocalStat -stat fwhm -nbhd XX? I’m clear enough on the reason for the ACF and its corresponding long tail - but it seems that 3dLocalStat FWHM doesn’t care so much about time.