AFNI Message Board

Dear AFNI users-

We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:

https://discuss.afni.nimh.nih.gov

Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.

The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.

Sincerely, AFNI HQ

History of AFNI updates  

Previous Message Next Message
Message List New Topic Print View
|
tamtam
June 06, 2018 04:09PM
Hello,

I am working through the AFNI tutorials for pre-processing and I have a question regarding the "auto block: outcount" procedure. It indicates that "at each voxel, the data is detrended using the default polynominal degree based on the duration of the first run. For that voxel time series, any value that is too far from the trend is considered an outlier."

Does this mean that (1) the data takes into account scanner drift by using the default polynominal degree and then (2) outliers are removed based on whether they are too far from the trend? If so, what does "trend" refer to? Does it refer to the mean raw signal or the trend that was computed to de-trend the data?

Thank you for your help.

Best,
Tamara
Reply Quote
RSS
Subject Author Posted

Outliers too far from the "trend"

tamtam June 06, 2018 04:09PM

Re: Outliers too far from the "trend"

rick reynolds June 07, 2018 02:08PM

Re: Outliers too far from the "trend"

tamtam June 07, 2018 02:15PM

Re: Outliers too far from the "trend"

rick reynolds June 07, 2018 02:33PM

Re: Outliers too far from the "trend"

tamtam June 07, 2018 02:56PM