AFNI program: whereami_afni
Output of -help
++ ----- Atlas list: -------
++ Name Space Dataset Description
++ __________________________________________________________
++ MNI_Glasser_HCP_v1.0 MNI_2009c_asym /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//MNI_Glasser_HCP_v1.0.nii.gz Glasser HCP 2016 surface-based parcellation
++ Brainnetome_1.0 MNI /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//BN_Atlas_246_1mm.nii.gz Brainnetome MPM
++ CA_MPM_22_MNI MNI_N27 /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//MNI_caez_mpm_22+tlrc Eickhoff-Zilles MPM atlas
++ CA_MPM_22_TT TT_N27 /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//TT_caez_mpm_22+tlrc Eickhoff-Zilles MPM atlas 2.2 - Talairach space
++ CA_N27_ML TT_N27 /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//TT_caez_ml_18+tlrc Macro Labels (N27)
++ CA_N27_GW TT_N27 /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//TT_caez_gw_18+tlrc Cytoarch. Prob. Maps for gray/white matter 1.8
++ CA_ML_18_MNI MNI_N27 /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//MNI_caez_ml_18+tlrc Macro Labels (N27-MNI)
++ CA_LR_18_MNI MNI_N27 /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//MNI_caez_lr_18+tlrc Left/Right (N27-MNI)
++ Haskins_Pediatric_Nonline HaskinsPeds /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//HaskinsPeds_NL_atlas1.01+tlrc.HEAD Version 1.01
++ FS.afni.MNI2009c_asym MNI_2009c_asym /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//FS.afni.MNI2009c_asym.nii.gz Freesurfer MNI2009c DK parcellation
++ FS.afni.TTN27 TT_N27 /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//FS.afni.TTN27.nii.gz Freesurfer TT_N27 DK parcellation
++ Brodmann_Pijn MNI_N27 /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//Brodmann.nii.gz Brodmann atlas MNI N27 - Pijnenburg
++ Brodmann_Pijn_AFNI MNI_2009c_asym /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//Brodmann_pijn_afni.nii.gz Brodmann atlas for MNI 2009c - Pijnenburg AFNI version
++ Julich_MNI2009c MNI_2009c_asym /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//Julich_MNI2009c.nii.gz JulichBrain 3.0 for MNI 2009c asymmetric space
++ Julich_MNI_N27 MNI_N27 /home/afniHQ/afni.build/pub.dist/bin/linux_ubuntu_24_64//Julich_MNI_N27.nii.gz JulichBrain 3.0 for MNI N27 space
++
++ MNI_Glasser_HCP_v1.0: Glasser, et al,A multi-modal parcellation of human cerebral cortex,
Nature,2016.
Atlas was constructed from surface analysis in Contee grayordinates.
Use with caution on volumetric analysis. Transformed to MNI space
via FreeSurfer and then to a standard mesh in AFNI.
More details on this implementation in Atlas_notes.txt and here:
https://openwetware.org/wiki/Beauchamp:CorticalSurfaceHCP
++ Brainnetome_1.0: Please cite Fan, L. et al., The Human Brainnetome Atlas:
A New Brain Atlas Based on Connectional Architecture.
Cerebral Cortex, 26 (8): 3508-3526,(2016).
In HCP-40 space, a space similar to MNI_2009c
++ CA_MPM_22_MNI: Eickhoff-Zilles maximum probability map from cytoarchitectonic probabilistic atlas
SPM ANATOMY TOOLBOX v2.2
For full list of references,
http://www.fz-juelich.de/inm/inm-1/EN/Forschung/_docs/SPMAnatomyToolbox/SPMAnatomyToolbox_node.html
Primary references:
Contact: Simon Eickhoff (s.eickhoff@fz-juelich.de)
Eickhoff SB et al.: A new SPM toolbox... (2005) NeuroImage 25(4): 1325-1335
Eickhoff SB et al.: Testing anatomically specified hypotheses... (2006) NeuroImage 32(2): 570-82
Eickhoff SB et al.: Assignment of functional activations... (2007) NeuroImage 36(3): 511-521
Publications describing included probabilistic maps:
TE 1.0, TE 1.1, TE 1.2------------------------------------------ Morosan et al., NeuroImage 2001
BA 44, BA 45---------------------------------------------------- Amunts et al., J Comp Neurol 1999
BA 4a, BA 4p BA 6----------------------------------------------- Geyer et al., Nature 1996 S. Geyer,
Springer press 2003
BA 3a, BA 3b, BA 1 BA 2----------------------------------------- Geyer et al., NeuroImage, 1999, 2000
Grefkes et al., NeuroImage 2001
OP 1, OP 2, OP 3, OP 4------------------------------------------ Eickhoff et al., Cerebral Cortex 2006a,b
PFt, PF, PFm, PFcm, PFop, PGa, PGp 5Ci, 5L, 5M, 7A, 7M, 7P, 7PC- Caspers et al., Neuroimage 2007, BSF 2008
Scheperjans et al., Cerebral Cortex 2008a,b
hIP1, hIP2 hIP3------------------------------------------------- Choi et al., J Comp Neurol 2006
Scheperjans et al., Cerebral Cortex 2008a,b
Ig1, Ig2, Id1--------------------------------------------------- Kurth et al., Cerebral Cortex 2010
CM/LB/SF FD/CA/SUB/EC/HATA-------------------------------------- Amunts et al., Anat Embryol 2005
Amunts et al., Anat Embryol 2005
BA 17, BA 18 hOC5 hOC3v / hOC4v--------------------------------- Amunts et al., NeuroImage 2000
Malikovic et al., Cerebral Cortex 2006
Rottschy et al., Hum Brain Mapp 2007
13 structures--------------------------------------------------- Burgel et al., NeuroImage 1999, 2006
18 structures--------------------------------------------------- Diedrichsen et al., NeuroImage 2009
Dorsal extrastriate cortex (hOC3d / hOC4d)---------------------- Kujovic et al., Brain Struct Funct 2012
Gyrus fusiformis (FG1, FG2)------------------------------------- Caspers et al., Brain Struct Funct 2012
Frontal pole (Fp1, Fp2)----------------------------------------- Bludau et al., Neuroimage, 2014
Other areas may only be used with authors' permission !
AFNI adaptation by
Ziad S. Saad and Daniel Glen (SSCC/NIMH/NIH)
++ CA_MPM_22_TT: Eickhoff-Zilles maximum probability map- 2.2 version on TT_N27
from post-mortem analysis
++ CA_N27_ML: Eickhoff-Zilles macro labels from N27 in Talairach TT_N27 space
SPM ANATOMY TOOLBOX v1.8
Primary references:
Contact: Simon Eickhoff (s.eickhoff@fz-juelich.de)
Eickhoff SB et al.: A new SPM toolbox... (2005) NeuroImage 25(4): 1325-1335
Eickhoff SB et al.: Testing anatomically specified hypotheses... (2006) NeuroImage 32(2): 570-82
Eickhoff SB et al.: Assignment of functional activations... (2007) NeuroImage 36(3): 511-521
Publications describing included probabilistic maps:
TE 1.0, TE 1.1, TE 1.2------------------------------------------ Morosan et al., NeuroImage 2001
BA 44, BA 45---------------------------------------------------- Amunts et al., J Comp Neurol 1999
BA 4a, BA 4p BA 6----------------------------------------------- Geyer et al., Nature 1996 S. Geyer,
Springer press 2003
BA 3a, BA 3b, BA 1 BA 2----------------------------------------- Geyer et al., NeuroImage, 1999, 2000
Grefkes et al., NeuroImage 2001
OP 1, OP 2, OP 3, OP 4------------------------------------------ Eickhoff et al., Cerebral Cortex 2006a,b
PFt, PF, PFm, PFcm, PFop, PGa, PGp 5Ci, 5L, 5M, 7A, 7M, 7P, 7PC- Caspers et al., Neuroimage 2007, BSF 2008
Scheperjans et al., Cerebral Cortex 2008a,b
hIP1, hIP2 hIP3------------------------------------------------- Choi et al., J Comp Neurol 2006
Scheperjans et al., Cerebral Cortex 2008a,b
Ig1, Ig2, Id1--------------------------------------------------- Kurth et al., Cerebral Cortex 2010
CM/LB/SF FD/CA/SUB/EC/HATA-------------------------------------- Amunts et al., Anat Embryol 2005
Amunts et al., Anat Embryol 2005
BA 17, BA 18 hOC5 hOC3v / hOC4v--------------------------------- Amunts et al., NeuroImage 2000
Malikovic et al., Cerebral Cortex 2006
Rottschy et al., Hum Brain Mapp 2007
13 structures--------------------------------------------------- Burgel et al., NeuroImage 1999, 2006
18 structures--------------------------------------------------- Diedrichsen et al., NeuroImage 2009
Other areas may only be used with authors' permission !
AFNI adaptation by
Ziad S. Saad and Daniel Glen (SSCC/NIMH/NIH)
++ CA_N27_GW: Eickhoff-Zilles probability maps on MNI-152 1.8 version
from post-mortem analysis
++ CA_ML_18_MNI: Eickhoff-Zilles macro labels from N27 (MNI space)
++ CA_LR_18_MNI: Simple left, right hemisphere segmentation (MNI space)
++ Haskins_Pediatric_Nonlinear_1.01: Haskins Pediatric Atlas 1.01 Nonlinearly aligned group template.
Please cite:
Molfese PJ, et al, The Haskins pediatric atlas:
a magnetic-resonance-imaging-based pediatric template and atlas.
Pediatr Radiol. 2021 Apr;51(4):628-639. doi: 10.1007/s00247-020-04875-y
++ FS.afni.MNI2009c_asym: Freesurfer recon-all freesurfer-linux-centos7_x86_64-7.3.2-20220804-6354275
++ FS.afni.TTN27: Freesurfer recon-all freesurfer-linux-centos7_x86_64-7.3.2-20220804-6354275
++ Brodmann_Pijn: Pijnenburg, R., et al (2021). Myelo- and cytoarchitectonic microstructural and functional human cortical atlases reconstructed in common MRI space. NeuroImage, 239, 118274.
++ Brodmann_Pijn_AFNI: Pijnenburg, R., et al (2021). Myelo- and cytoarchitectonic microstructural
and functional human cortical atlases reconstructed in common MRI space.
NeuroImage, 239, 118274.
This AFNI version has been reprojected into the MNI 2009c template space
via a standard mesh surface and then modally smoothed and renumbered.
++ Julich_MNI2009c: From EBRAINS3.0 website, v3.0.3 available here:
https://search.kg.ebrains.eu/instances/d69b70e2-3002-4eaf-9c61-9c56f019bbc8
Please cite this dataset version and the original research publication:
Amunts, K, Mohlberg, H, Bludau, S, Caspers, S, Lewis, LB, Eickhoff, SB,
Pieperhoff, P (2023).
Julich-Brain Atlas, cytoarchitectonic maps (v3.0.3) [Data set].
DOI: 10.25493/56EM-75H
Evans, AC, Janke, AL, Collins, DL, Baillet, S (2012).
Brain templates and atlases. NeuroImage, 62(2), 911–922.
DOI: 10.1016/j.neuroimage.2012.01.024
Eickhoff, SB, Stephan, KE, Mohlberg, H, Grefkes, C, Fink, GR, Amunts, K,
Zilles, K. (2005).
A new SPM toolbox for combining probabilistic cytoarchitectonic maps and
functional imaging data. NeuroImage, 25(4), 1325–1335.
DOI: 10.1016/j.neuroimage.2004.12.034
For the overall scientific concept and methodology of the Julich-Brain, please cite:
Amunts, K, Mohlberg, H, Bludau, S, & Zilles, K (2020).
Julich-Brain: A 3D probabilistic atlas of the human brain’s cytoarchitecture.
Science, 369(6506), 988–992.
DOI: 10.1126/science.abb4588
++ Julich_MNI_N27: From EBRAINS3.0 website, v3.0.3 available here:
https://search.kg.ebrains.eu/instances/d69b70e2-3002-4eaf-9c61-9c56f019bbc8
Please cite this dataset version and the original research publication:
Amunts, K, Mohlberg, H, Bludau, S, Caspers, S, Lewis, LB, Eickhoff, SB,
Pieperhoff, P (2023).
Julich-Brain Atlas, cytoarchitectonic maps (v3.0.3) [Data set].
DOI: 10.25493/56EM-75H
Evans, AC, Janke, AL, Collins, DL, Baillet, S (2012).
Brain templates and atlases. NeuroImage, 62(2), 911–922.
DOI: 10.1016/j.neuroimage.2012.01.024
Eickhoff, SB, Stephan, KE, Mohlberg, H, Grefkes, C, Fink, GR, Amunts, K,
Zilles, K. (2005).
A new SPM toolbox for combining probabilistic cytoarchitectonic maps and
functional imaging data. NeuroImage, 25(4), 1325–1335.
DOI: 10.1016/j.neuroimage.2004.12.034
For the overall scientific concept and methodology of the Julich-Brain, please cite:
Amunts, K, Mohlberg, H, Bludau, S, & Zilles, K (2020).
Julich-Brain: A 3D probabilistic atlas of the human brain’s cytoarchitecture.
Science, 369(6506), 988–992.
DOI: 10.1126/science.abb4588
>
++ --------------------------
Usage: whereami_afni [x y z [output_format]] [-lpi/-spm] [-atlas ATLAS]
++ Reports brain areas located at x y z mm in some template space
++ according to atlases present with your AFNI installation.
++ Show the contents of available atlases
++ Extract ROIs for certain atlas regions using symbolic notation
++ Report on the overlap of ROIs with Atlas-defined regions.
Options (all options are optional):
-----------------------------------
x y z [output_format] : Specifies the x y z coordinates of the
location probed. Coordinate are in mm and
assumed to be in RAI or DICOM format, unless
otherwise specified (see -lpi/-spm below)
In the AFNI viewer, coordinate format is
specified above the coordinates in the top-left
of the AFNI controller. Right click in that spot
to change between RAI/DICOM and LPI/SPM.
NOTE I:In the output, the coordinates are reported
in LPI, in keeping with the convention used
in most publications.
NOTE II:To go between LPI and RAI, simply flip the
sign of the X and Y coordinates.
Output_format is an optional flag where:
0 is for standard AFNI 'Where am I?' format.
1 is for Tab separated list, meant to be
friendly for use in spreadsheets.
The default output flag is 0. You can use
options -tab/-classic instead of the 0/1 flag.
-coord_file XYZ.1D: Input coordinates are stored in file XYZ.1D
Use the '[ ]' column selectors to specify the
X,Y, and Z columns in XYZ.1D.
Say you ran the following 3dclust command:
3dclust -1Dformat -1clip 0.3 5 3000 func+orig'[1]' > out.1D
You can run whereami_afni on each cluster's center
of mass with:
whereami_afni -coord_file out.1D'[1,2,3]' -tab
NOTE: You cannot use -coord_file AND specify x,y,z on
command line.
-linkrbrain: get report from linkRbrain from list of coordinates
only with -coord_file and -space or -dset_space
-linkr_type tasks/genes: report for correlation with tasks or genes
Default is tasks
-lpi/-spm: Input coordinates' orientation is in LPI or SPM format.
-rai/-dicom: Input coordinates' orientation is in RAI or DICOM format.
NOTE: The default format for input coordinates' orientation is set by
AFNI_ORIENT environment variable. If it is not set, then the default
is RAI/DICOM
-space SPC: Space of input coordinates.
SPC can be any template space name. Without a NIML table definition,
the space name is limited to MNI, MNI_ANAT or TLRC (the default).
-classic: Classic output format (output_format = 0).
-tab: Tab delimited output (output_format = 1).
Useful for spreadsheeting.
-atlas ATLAS: Use atlas ATLAS for the query.
You can use this option repeatedly to specify
more than one atlas. Default is all available atlases.
ATLAS is one of:
-dset: Determine the template space to use from this reference dataset
Space for human data is usually TLRC, MNI, MNI_ANAT.
If the space is known and a reference atlas can be found, the
regions will be based on the coordinates from this template space.
-atlas_sort: Sort results by atlas (default)
-zone_sort | -radius_sort: Sort by radius of search
-old : Run whereami_afni in the olde (Pre Feb. 06) way.
-show_atlas_code: Shows integer code to area label map of the atlases
in use. The output is not too pretty because
the option is for debugging use.
-show_atlas_region REGION_CODE: You can now use symbolic notation to
select atlas regions. REGION_CODE has
three colon-separated elements forming it:
Atlas_Name:Side:Area.
Atlas_Name: one of the atlas names listed above.
If you do not have a particular atlas in your AFNI
installation, you'll need to download it (see below).
Side : Either left, right or nothing(::) for bilateral.
Area : A string identifying an area. The string cannot contain
blanks. Replace blanks by '_' for example Cerebellar Vermis
is Cerebellar_Vermis. You can also use the abbreviated
version cereb_ver and the program will try to guess at
what you want and offer suggestions if it can't find the
area or if there is ambiguity. Abbreviations are formed
by truncating the components (chunks) of an area's name
(label). For example:
1- TT_Daemon::ant_cing specifies the bilateral
anterior cingulate in the TT_Daemon atlas.
2- CA_N27_ML:left:hippo specifies the left
hippocampus in the CA_N27_ML atlas.
3- CA_N27_MPM:right:124 specifies the right
ROI with integer code 124 in the CA_N27_MPM atlas
4- CA_N27_ML::cereb_ver seeks the Cerebellar
Vermis in the CA_N27_ML atlas. However there
many distinct areas with this name so the program
will return with 'potential matches' or suggestions.
Use the suggestions to refine your query. For example:
CA_N27_ML::cereb_vermis_8
-mask_atlas_region REGION_CODE: Same as -show_atlas_region, plus
write out a mask dataset of the region.
-index_to_label index: Reports the label associated with index using the
label table of dset, if provided, or using the atlas_points_list
of a specified atlas. After printing, the program exits.
-prefix PREFIX: Prefix for the output mask dataset
-max_areas MAX_N: Set a limit on the number of distinct areas to report.
This option will override the value set by the environment
variable AFNI_WHEREAMI_MAX_FIND, which is now set to 9
The variable AFNI_WHEREAMI_MAX_FIND should be set in your
.afnirc file.
-max_search_radius MAX_RAD: Set a limit on the maximum searching radius when
reporting results. This option will override the
value set by the environment variable
AFNI_WHEREAMI_MAX_SEARCH_RAD,
which is now set to 7.500000 .
-min_prob MIN_PROB: set minimum probability to consider in probabilistic
atlas output. This option will overrid the value set by the
environment variable AFNI_WHEREAMI_PROB_MIN (default is 1E-10)
NOTE: You can turn off some of the whining by setting the environment
variable AFNI_WHEREAMI_NO_WARN
-debug DEBUG: Debug flag
-verb VERB: Same as -debug DEBUG
Options for determining the percent overlap of ROIs with Atlas-defined areas:
---------------------------------------------------------------------------
-bmask MASK: Report on the overlap of all non-zero voxels in MASK dataset
with various atlas regions. NOTE: The mask itself is not binary,
the masking operation results in a binary mask.
-omask ORDERED_MASK:Report on the overlap of each ROI formed by an integral
value in ORDERED_MASK. For example, if ORDERED_MASK has
ROIs with values 1, 2, and 3, then you'll get three
reports, one for each ROI value. Note that -omask and
-bmask are mutually exclusive.
-cmask MASK_COMMAND: command for masking values in BINARY_MASK,
or ORDERED_MASK on the fly.
e.g. whereami_afni -bmask JoeROIs+tlrc \
-cmask '-a JoeROIs+tlrc -expr equals(a,2)'
Would set to 0, all voxels in JoeROIs that are not
equal to 2.
Note that this mask should form a single sub-brick,
and must be at the same resolution as the bmask (binary mask) or
the omask (the ordered mask) datasets.
This option follows the style of 3dmaskdump (since the
code for it was, uh, borrowed from there (thanks Bob!, thanks Rick!)).
See '3dmaskdump -help' for more information.
Note on the reported coordinates of the Focus Point:
----------------------------------------------------
Coordinates of the Focus Point are reported in available template spaces in
LPI coordinate order. The three principal spaces reported are Talairach
(TLRC), MNI, MNI Anatomical (MNI_ANAT).
The TLRC coordinates follow the convention specified by the Talairach and
Tournoux Atlas.
The MNI coordinates are derived from the TLRC ones using an approximation
equation.
The MNI Anat. coordinates are a shifted version of the MNI coordinates
(see Eickhoff et al. 05).
For users who do not use the NIML table method of specifying template
and transformations, the MNI coordinates reported here are derived from TLRC
by an approximate function (the Brett transform). For transformations
between MNI_ANAT and TLRC coordinates, the 12 piece-wise linear transformation
that was used to transform the MNI_ANAT N27 brain to TLRC space is also
used to compute the coordinates in either direction.
For users who do use the NIML table method, the transformations among
the various Talairach, MNI and MNI_ANAT spaces may be performed a variety
of ways. The default method uses the Brett transform for TLRC to MNI, and
a simple shift for MNI to MNI_ANAT.
How To See Atlas Data In AFNI as datasets:
------------------------------------------
If you want to view the atlases in the same session
that you are working with, choose one of options below.
For the sake of illustrations, I will assume that atlases
reside in directory: /user/abin/
1-Load the session where atlases reside on afni's command
line: afni ./ /user/abin
2-Set AFNI's environment variable AFNI_GLOBAL_SESSION
to the directory where the atlases reside.
You can add the following to you .afnirc file:
AFNI_GLOBAL_SESSION = /user/abin
Or, for a less permanent solution, you can set this environment
variable in the shell you are working in with (for csh and tcsh):
setenv AFNI_GLOBAL_SESSION /user/abin
***********
BE CAREFUL: Do not use the AFNI_GLOBAL_SESSION approach
*********** if the data in your session is not already
written in +tlrc space. To be safe, you must have
both +tlrc.HEAD and +tlrc.BRIK for all datasets
in that session (directory). Otherwise, if the anat parents are
not properly set, you can end up applying the +tlrc transform
from one of the atlases instead of the proper anatomical
parent for that session.
Note: You can safely ignore the:
** Can't find anat parent ....
messages for the Atlas datasets.
Convenient Color maps For Atlas Datasets:
----------------------------------------
Color maps (color scales) for atlas dataset should automatically be used
when these datasets are viewed in the overlay. To manually select a
a specific color scale in the AFNI GUI's overlay panel:
o set the color map number chooser to '**'
o right-click on the color map's color bar and select
'Choose Colorscale'
o pick one of: CytoArch_ROI_256, CytoArch_ROI_256_gap, ROI_32. etc.
o set autorange off and set the range to the number of colors
in the chosen map (256, 32, etc.).
Color map CytoArch_ROI_256_gap was created for the proper viewing
of the Maximum Probability Maps of the Anatomy Toolbox.
How To See Atlas regions overlaid in the AFNI GUI:
--------------------------------------------------
To see specific atlas regions overlaid on underlay and other overlay data,
1. In Overlay control panel, check "See Atlas Regions"
2. Switch view to Talairach in View Panel
3. Right-click on image and select "-Atlas colors". In the Atlas colors
menu, select the colors you would like and then choose Done.
The images need to be redrawn to see the atlas regions, for instance,
by changing slices. Additional help is available in the Atlas colors
menu.
For the renderer plug-in, the underlay and overlay datasets should both
have Talairach view datasets actually written out to disk
The whereami_afni and "Talairach to" functions are also available by
right-clicking in an image window.
Example 1:
----------
To find a cluster center close to the top of the brain at -12,-26, 76 (LPI),
whereami_afni, assuming the coordinates are in Talairach space,
would report:
whereami_afni -12 -26 76 -lpi
++ Input coordinates orientation set by user to LPI
+++++++ nearby Atlas structures +++++++
Original input data coordinates in TLRC space
Focus point (LPI)=
-12 mm [L], -26 mm [P], 76 mm [S] {TLRC}
-12 mm [L], -31 mm [P], 81 mm [S] {MNI}
-13 mm [L], -26 mm [P], 89 mm [S] {MNI_ANAT}
Atlas CA_N27_MPM: Cytoarch. Max. Prob. Maps (N27)
Within 4 mm: Area 6
Within 7 mm: Area 4a
Atlas CA_N27_ML: Macro Labels (N27)
Within 1 mm: Left Paracentral Lobule
Within 6 mm: Left Precentral Gyrus
-AND- Left Postcentral Gyrus
Example 2:
----------
To create a mask dataset of both left and right amygdala, you can do:
whereami_afni -prefix amymask -mask_atlas_region 'TT_Daemon::amygdala'
Note masks based on atlas regions can be specified "on the fly" in
the same way with other afni commands as a dataset name (like 3dcalc,
for instance), so a mask, very often, is not needed as a separate,
explicit dataset on the disk.
Example 3:
----------
To create a mask from a FreeSurfer 'aparc' volume parcellation:
(This assumes you have already run @SUMA_Make_Spec_FS, and your
afni distribution is recent. Otherwise update afni then run:
@MakeLabelTable -atlasize_labeled_dset aparc.a2009s+aseg_rank.nii
from the SUMA/ directory for that subject.)
To find the region's name, try something like:
whereami_afni -atlas aparc.a2009s+aseg_rank -show_atlas_code | \
grep -i insula
Or you can try this search, assuming you screwed up the spelling:
whereami_afni -atlas aparc+aseg_rank -show_atlas_code | \
apsearch -word insola -stdin
If you really screw up the spelling try:
whereami_afni -atlas aparc+aseg_rank -show_atlas_code | \
sed 's/[-_]/ /g' | \
apsearch -word insolent -stdin
Pick one area then run:
whereami_afni -atlas aparc.a2009s+aseg_rank \
-mask_atlas_region \
aparc.a2009s+aseg_rank::ctx_rh_S_circular_insula_sup
---------------
Atlas NIML tables:
Atlas, templates, template spaces and transforms may all now be specified
in a text file that follows an XML-like format, NIML. The specifications
for the NIML table files will be described more fully elsewhere, but an
overview is presented here. By default, and soon to be included with the
AFNI distributions, the file AFNI_atlas_spaces.niml contains entries for
each of the available atlases, template spaces, templates and
transformations. Two other additional files may be specified and changed
using the environment variables, AFNI_SUPP_ATLAS and AFNI_LOCAL_ATLAS.
It is best to examine the provided NIML table as an example for extending
and modifying the various atlas definitions.
Show atlas NIML table options:
-show_atlases : show all available atlases
-show_templates : show all available templates
-show_spaces : show all available template spaces
-show_xforms : show all available xforms
-show_atlas_all : show all the above
-show_atlas_dset : print dataset associated with each atlas
can be used with -atlas option above
-show_available_spaces srcspace : show spaces that are available from
the source space
-show_chain srcspace destspace : show the chain of transformations
needed to go from one space to another
-calc_chain srcspace destspace : compute the chain of transformations
combining and inverting transformations where possible
examples: convert coordinates from TT_N27 to MNI or MNI anat space
whereami_afni -calc_chain TT_N27 MNI -xform_xyz_quiet 10 20 30
whereami_afni -calc_chain TT_N27 MNI -xform_xyz_quiet 0 0 0
whereami_afni -calc_chain TT_N27 MNIA -xform_xyz_quiet 0 0 0
-xform_xyz : used with calc_chain, takes the x,y,z coordinates and
applies the combined chain of transformations to compute
a new x,y,z coordinate
-xform_xyz_quiet : Same as -xform_xyz but only outputs the final result
-coord_out outfile : with -xform_xyz, -coord_file and -calc_chain,
specifies an output file for transformed coordinates
If not specified, coord_files will be transformed and printed
to stdout
Note setting the environment variable AFNI_WAMI_DEBUG will show detailed
progress throughout the various functions called within whereami_afni.
For spaces defined using a NIML table, a Dijkstra search is used to find
the shortest path between spaces. Each transformation carries with it a
distance attribute that is used for this computation. By modifying this
field, the user can control which transformations are preferred.
-web_atlas_type XML/browser/struct : report results from web-based atlases
using XML output to screen, open a browser for output or just
return the name of the structure at the coordinate
-html : put whereami_afni output in html format for display in a browser
---------------
More information about Atlases in AFNI can be found here:
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/template_atlas/framework.html
Class document illustrating whereami_afni usage:
https://afni.nimh.nih.gov/pub/dist/edu/latest/afni11_roi/afni11_roi.pdf
---------------
Global Options (available to all AFNI/SUMA programs)
-h: Mini help, at time, same as -help in many cases.
-help: The entire help output
-HELP: Extreme help, same as -help in majority of cases.
-h_view: Open help in text editor. AFNI will try to find a GUI editor
-hview : on your machine. You can control which it should use by
setting environment variable AFNI_GUI_EDITOR.
-h_web: Open help in web browser. AFNI will try to find a browser.
-hweb : on your machine. You can control which it should use by
setting environment variable AFNI_GUI_EDITOR.
-h_find WORD: Look for lines in this programs's -help output that match
(approximately) WORD.
-h_raw: Help string unedited
-h_spx: Help string in sphinx loveliness, but do not try to autoformat
-h_aspx: Help string in sphinx with autoformatting of options, etc.
-all_opts: Try to identify all options for the program from the
output of its -help option. Some options might be missed
and others misidentified. Use this output for hints only.
-overwrite: Overwrite existing output dataset.
Equivalent to setting env. AFNI_DECONFLICT=OVERWRITE
-ok_1D_text: Zero out uncommented text in 1D file.
Equivalent to setting env. AFNI_1D_ZERO_TEXT=YES
-Dname=val: Set environment variable 'name' to value 'val'
For example: -DAFNI_1D_ZERO_TEXT=YES
-Vname=: Print value of environment variable 'name' to stdout and quit.
This is more reliable that the shell's env query because it would
include envs set in .afnirc files and .sumarc files for SUMA
programs.
For example: -VAFNI_1D_ZERO_TEXT=
-skip_afnirc: Do not read the afni resource (like ~/.afnirc) file.
-pad_to_node NODE: Output a full dset from node 0 to MAX_NODE-1
** Instead of directly setting NODE to an integer you
can set NODE to something like:
ld120 (or rd17) which sets NODE to be the maximum
node index on an Icosahedron with -ld 120. See
CreateIcosahedron for details.
d:DSET.niml.dset which sets NODE to the maximum node found
in dataset DSET.niml.dset.
** This option is for surface-based datasets only.
Some programs may not heed it, so check the output if
you are not sure.
-pif SOMETHING: Does absolutely nothing but provide for a convenient
way to tag a process and find it in the output of ps -a
-echo_edu: Echos the entire command line to stdout (without -echo_edu)
for edification purposes
SPECIAL PURPOSE ARGUMENTS TO ADD *MORE* ARGUMENTS TO THE COMMAND LINE
------------------------------------------------------------------------
Arguments of the following form can be used to create MORE command
line arguments -- the principal reason for using these type of arguments
is to create program command lines that are beyond the limit of
practicable scripting. (For one thing, Unix command lines have an
upper limit on their length.) This type of expanding argument makes
it possible to input thousands of files into an AFNI program command line.
The generic form of these arguments is (quotes, 'single' or "double",
are required for this type of argument):
'<<XY list'
where X = I for Include (include strings from file)
or X = G for Glob (wildcard expansion)
where Y = M for Multi-string (create multiple arguments from multiple strings)
or Y = 1 for One-string (all strings created are put into one argument)
Following the XY modifiers, a list of strings is given, separated by spaces.
* For X=I, each string in the list is a filename to be read in and
included on the command line.
* For X=G, each string in the list is a Unix style filename wildcard
expression to be expanded and the resulting filenames included
on the command line.
In each case, the '<<XY list' command line argument will be removed and
replaced by the results of the expansion.
* '<<GM wildcards'
Each wildcard string will be 'globbed' -- expanded from the names of
files -- and the list of files found this way will be stored in a
sequence of new arguments that replace this argument:
'<<GM ~/Alice/*.nii ~/Bob/*.nii'
might expand into a list of hundreds of separate datasets.
* Why use this instead of just putting the wildcards on the command
line? Mostly to get around limits on the length of Unix command lines.
* '<<G1 wildcards'
The difference from the above case is that after the wildcard expansion
strings are found, they are catenated with separating spaces into one
big string. The only use for this in AFNI is for auto-catenation of
multiple datasets into one big dataset.
* '<<IM filenames'
Each filename string will result in the contents of that text file being
read in, broken at whitespace into separate strings, and the resulting
collection of strings will be stored in a sequence of new arguments
that replace this argument. This type of argument can be used to input
large numbers of files which are listed in an external file:
'<<IM Bob.list.txt'
which could in principle result in reading in thousands of datasets
(if you've got the RAM).
* This type of argument is in essence an internal form of doing something
like `cat filename` using the back-quote shell operator on the command
line. The only reason this argument (or the others) was implemented is
to get around the length limits on the Unix command line.
* '<<I1 filenames'
The difference from the above case is that after the files are read
and their strings are found, they are catenated with separating spaces
into one big string. The only use for this in AFNI is for auto-catenation
of multiple datasets into one big dataset.
* 'G', 'M', and 'I' can be lower case, as in '<<gm'.
* 'glob' is Unix jargon for wildcard expansion:
https://en.wikipedia.org/wiki/Glob_(programming)
* If you set environment variable AFNI_GLOB_SELECTORS to YES,
then the wildcard expansion with '<<g' will not use the '[...]'
construction as a Unix wildcard. Instead, it will expand the rest
of the wildcard and then append the '[...]' to the results:
'<<gm fred/*.nii[1..100]'
would expand to something like
fred/A.nii[1..100] fred/B.nii[1..100] fred/C.nii[1..100]
This technique is a way to preserve AFNI-style sub-brick selectors
and have them apply to a lot of files at once.
Another example:
3dttest++ -DAFNI_GLOB_SELECTORS=YES -brickwise -prefix Junk.nii \
-setA '<<gm sub-*/func/*rest_bold.nii.gz[0..100]'
* However, if you want to put sub-brick selectors on the '<<im' type
of input, you will have to do that in the input text file itself
(for each input filename in that file).
* BE CAREFUL OUT THERE!
------------------------------------------------------------------------
Thanks to Kristina Simonyan for feedback and testing.
++ Compile date = Oct 31 2024 {AFNI_24.3.06:linux_ubuntu_24_64}
This page auto-generated on
Thu Oct 31 09:45:50 PM EDT 2024