AFNI HISTORY
level 4 and higher
The levels of importance go from 1 to 5, with meanings:
1 - users would not care
2 - of little importance, though some users might care
3 - fairly important
4 - a big change or new program
5 - IMPORTANT: we expect users to know
generated via the command : afni_history -html -reverse -min_level 4 -past_years 2
---- log of AFNI updates (most recent first) ----
21 Aug 2008, RW Cox, 3dREMLfit, level 4 (SUPER), type 1 (NEW_PROG)
Program to mimic 3dDeconvolve, but with serial correlations
Uses ARMA(1,1) model of noise, separately for each voxel.
07 Apr 2008, DR Glen, align_epi_anat.py, level 4 (SUPER), type 1 (NEW_PROG)
Alignment of EPI and Anatomical datasets
Aligns anat and EPI data. Alignment is in either direction of anat to
epi or epi to anat. Transformations are combined where possible as
from time series registration and talairach transformations. Multiple
child epi datasets may be aligned at the same time.
29 Feb 2008, G Chen, 3dICA.R, level 4 (SUPER), type 1 (NEW_PROG)
An R program that runs independent component analysis in AFNI.
This testing program for ICA only takes one dataset that presumably has
already been properly pre-processed. See more details on:
http://afni.nimh.nih.gov/sscc/gangc/ica.html
27 Feb 2008, RC Reynolds, afni_history, level 4 (SUPER), type 1 (NEW_PROG)
program to display the history of AFNI updates
This will be used to create a web page of AFNI updates.
Please see 'afni_history -help' for more details.
21 Feb 2008, RC Reynolds, GIFTI, level 4 (SUPER), type 0 (GENERAL)
AFNI programs can now read and write GIFTI datasets
GIFTI datasets are for data in the surface domain, with file suffix .gii.
Support must be requested at compile time, and it requires libexpat.
Please see http://www.nitrc.org/projects/gifti for many details.
16 Feb 2008, RW Cox, 3dTfitter, level 4 (SUPER), type 1 (NEW_PROG)
new program = linear fits to voxel time series
Uses L1 or L2 regression, with optional constraints to fit each voxel
time series as a sum of basis time series, which can be 1D files or
3D+time datasets. Basis time series that are 1D time series are
the same for all input voxels. Basis time series that are 3D+time
datasets are different for each voxel.
Differences from 3dDeconvolve:
* Basis time series can vary across voxels.
* Fit coefficients can be found with L1 or L2 error functions, and
can be constrained to be positive or negative.
* 3dTfitter does not compute goodness-of-fit statistics.
26 Sep 2007, ZS Saad, SurfFWHM, level 4 (SUPER), type 1 (NEW_PROG)
Program to estimate FWHM of data on surface
20 Sep 2007, G Chen, 3dLME.R, level 4 (SUPER), type 1 (NEW_PROG)
An R program that runs linear mixed-effects analysis at group level in AFNI.
See more details on: http://afni.nimh.nih.gov/sscc/gangc/lme.html
17 Jan 2007, G Chen, 1dSEM, level 4 (SUPER), type 1 (NEW_PROG)
An AFNI program that runs path analysis (or structural equation modeling) at
group level.
See more details on: http://afni.nimh.nih.gov/sscc/gangc/PathAna.html
20 Dec 2006, RC Reynolds, afni_proc.py, level 4 (SUPER), type 1 (NEW_PROG)
program to write complete single subject FMRI processing script
auto-generated by afni_history on Oct 3 2008