7.1.509. whereami

Link to classic view

++ —– Atlas list: ——- ++ Name Space Dataset Description ++ __________________________________________________________ ++ TT_Daemon TLRC TTatlas+tlrc Talairach-Tournoux Atlas ++ CA_N27_ML TT_N27 TT_caez_ml_18+tlrc Macro Labels (N27) ++ CA_N27_MPM TT_N27 TT_caez_mpm_18+tlrc Cytoarch. Max. Prob. Maps ++ CA_N27_PM TT_N27 TT_caez_pmaps_18+tlr Cytoarch. Probabilistic Maps ++ CA_N27_GW TT_N27 TT_caez_gw_18+tlrc Cytoarch. Prob. Maps for gray/white matter ++ CA_N27_LR TT_N27 TT_caez_lr_18+tlrc Left/Right (N27) ++ CA_ML_18_MNIA MNI_ANAT MNIa_caez_ml_18+tlrc Macro Labels (N27) ++ CA_MPM_18_MNIA MNI_ANAT MNIa_caez_mpm_18+tlr Cytoarch. Max. Prob. Maps ++ CA_PM_18_MNIA MNI_ANAT MNIa_caez_pmaps_18+t Cytoarch. Probabilistic Maps ++ CA_GW_18_MNIA MNI_ANAT MNIa_caez_gw_18+tlrc Cytoarch. Prob. Maps for gray/white matter ++ CA_LR_18_MNIA MNI_ANAT MNIa_caez_lr_18+tlrc Left/Right (N27) ++ DKD_Desai_PM TT_N27 TT_desai_dkpmaps+tlr Probability maps of 35 cortical areas (gyri) ++ DD_Desai_PM TT_N27 TT_desai_ddpmaps+tlr Probability maps of 75 cortical areas ++ FS_Desai_PM TT_N27 TT_desai_fspmaps+tlr Contains 40 subcortical areas ++ DD_Desai_MPM TT_N27 TT_desai_dd_mpm+tlrc Contains the maximum probability maps of Desai DD and FS maps ++ DKD_Desai_MPM TT_N27 TT_desai_dk_mpm+tlrc Contains the maximum probability maps of Desai DKD and FS maps ++ MNI_VmPFC MNI MNI_VmPFC+tlrc Ventromedial Prefrontal Cortex ++ Haskins_Pediatri HaskinsP HaskinsPeds_aff_atla Version 1.0 ++ Haskins_Pediatri HaskinsP HaskinsPeds_NL_atlas Version 1.0 ++ ++ TT_Daemon: The standard talaraich atlas ++ 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_MPM: Eickhoff-Zilles maximum probability map on TT_N27 from post-mortem analysis ++ CA_N27_PM: Eickhoff-Zilles probablity maps on TT_N27 from post-mortem analysis ++ CA_N27_GW: Eickhoff-Zilles probablity maps on MNI-152 from post-mortem analysis ++ CA_N27_LR: Simple left, right hemisphere segmentation ++ CA_ML_18_MNIA: Eickhoff-Zilles macro labels from N27 ++ CA_MPM_18_MNIA: Eickhoff-Zilles maximum probability map on MNI-152 from post-mortem analysis ++ CA_PM_18_MNIA: Eickhoff-Zilles probablity maps on MNI-152 from post-mortem analysis ++ CA_GW_18_MNIA: Eickhoff-Zilles probablity maps on MNI-152 from post-mortem analysis ++ CA_LR_18_MNIA: Simple left, right hemisphere segmentation ++ DKD_Desai_PM:

Please cite: Desikan et al., Neuroimage 2006 (31) pp. 968-980.
++ DD_Desai_PM:

For each hemisphere,including both gyri and sulci. Please cite:

Destrieux et al., Neuroimage 2010 (53) pp. 1-15.

++ FS_Desai_PM: 15 in left & right hemispheres,10 midline structures parcellated by freesurfer ++ DD_Desai_MPM: Smoothed maximum maps masked by unsmoothed maximum map ++ DKD_Desai_MPM: Smoothed maximum maps masked by unsmoothed maximum map ++ MNI_VmPFC: Mackey, S. and Petrides, M. (2014), Architecture and morphology

of the human ventromedial prefrontal cortex. European Journal of Neuroscience, 40: 2777-796. doi: 10.1111/ejn.12654

++ Haskins_Pediatric_Affine_1.0: Haskins Atlas 1.0. REF: Molfese, Glen, Mesite, Pugh... (In Prep.) ++ Haskins_Pediatric_Nonlinear_1.0: Haskins Atlas 1.0. REF: Molfese, Glen, Mesite, Pugh... (In Prep.) ++ ————————– Usage: whereami [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 on each cluster’s center of mass with:
whereami -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 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.
-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 5 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 -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 TT 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 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, assuming the coordinates are in Talairach space, would report:
whereami -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 -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 -atlas aparc.a2009s+aseg_rank -show_atlas_code | grep -i insula

Or you can try this search, assuming you screwed up the spelling: whereami -atlas aparc+aseg_rank -show_atlas_code |

apsearch -word insola -stdin

If you really screw up the spelling try: whereami -atlas aparc+aseg_rank -show_atlas_code |

sed ‘s/[-_]/ /g’ | apsearch -word insolent -stdin
Pick one area then run:
whereami -atlas aparc.a2009s+aseg_rank
-mask_atlas_region
 aparc.a2009s+aseg_rank::ctx_rh_S_circular_insula_sup

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_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
-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 ouputs 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. 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 output in html format for display in a browser
-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

Thanks to Kristina Simonyan for feedback and testing.

++ Compile date = Dec 16 2015

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