function atlas = ft_read_atlas(filename, varargin)

% FT_READ_ATLAS reads an template/individual segmentation or parcellation from disk.

% The volumetric segmentation or the surface-based parcellation can either represent

% a template atlas (e.g. AAL or the Talairach Daemon), it can represent an

% individualized atlas (e.g. obtained from FreeSurfer) or it can represent an

% unlabeled parcellation/segmentation obtained from an individual's DTi, anatomical,

% or resting state fMRI scan.

%

% Use as

% atlas = ft_read_atlas(filename, ...)

% or

% atlas = ft_read_atlas({filenamelabels, filenamemesh}, ...)

%

% Additional options should be specified in key-value pairs and can include

% 'format' = string, see below

% 'unit' = string, e.g. 'mm' (default is to keep it in the native units of the file)

% 'map' = string, 'maxprob' (default), or 'prob', for FSL-based atlases, providing

% either a probabilistic segmentation or a maximum a posterior probability map

% 'labelfile' = string, point to a (generic) text or xml file for interpretation of the values in the atlas

%

% For individual surface-based atlases from FreeSurfer you should specify two

% filenames as a cell-array: the first points to the file that contains information

% with respect to the parcels' labels, the second points to the file that defines the

% mesh on which the parcellation is defined.

%

% The 'format' variable, if not specified, will be determined automatically. In general

% it will not be needed to specify it. The following formats are supported:

%

% Volumetric atlases based on a (gzipped) nifti-file with an companion txt-file for interpretation

% 'aal' assumes filename starting with 'ROI_MNI'

% 'brainnetome' assumes companion lookuptable txt-file starting with 'Brainnetome Atlas'

% 'simnibs_v4' assumes filename starting with 'final_tissues', with companion freesurfer-style lookuptable txt-file

% 'wfu' assumes specific formatting of companion lookuptable txt-file

%

% Volumetric atlases based on a (gzipped) nifti-file with hard coded assumption on the labels

% 'yeo7'

% 'yeo17'

%

% Volumetric atlases based on a folder with (gzipped) nifti-files with a companion xml-file for interpretation

% 'fsl' assumes path to folder with data mentioned in the xml-file. Use xml-file as filename

%

% Volumetric atlases based on the freesurfer mgz format with standard lookuptable txt-file for interpretation

% 'freesurfer_volume' assumes the freesurfer LUT file for interpretation, and assumes aparc or aseg in the

% filename, used for subject-specific parcellations

%

% Volumetric atlases based on the afni software

% 'afni' assumes filename containing BRIK or HEAD, assumes generic interpretation of the labels

% for the TTatlas+tlrc, or otherwise the interpretation should be in the file

%

% Volumetric atlas based on the spm_anatomy toolbox

% 'spm_anatomy' pair of .hdr/.img files, and an associated mat-file for the interpretation

% Specify the associated mat-file with MPM in filename

%

% Surface based atlases, requiring a pair of files, containing the labels, and the associated geometry

% 'caret_label' hcp-workbench/caret style .gii, with .label. in filename, requires additional file describing the geometry

% 'freesurfer_surface' freesurfer style annotation file, requires additional file describing the geometry

%

% Miscellaneous formats

% 'mat' mat-file, with FieldTrip style struct, other matlab data that FieldTrip knows to handle, can also be

% Brainstorm derived surfaces

% 'vtpm'

%

% For volume data for whicth the format cannot be automatically detected, or if the volume data does not have a companion file

% for the interpretation of the labels, a list of 'fake' labels will be generated.

%

% The output atlas will be represented as structure according to FT_DATATYPE_SEGMENTATION or

% FT_DATATYPE_PARCELLATION.

%

% The 'lines' and the 'colorcube' colormaps may be useful for plotting the different

% patches, for example using FT_PLOT_MESH, or FT_SOURCEPLOT.

%

% See also FT_READ_MRI, FT_READ_HEADSHAPE, FT_PREPARE_SOURCEMODEL, FT_SOURCEPARCELLATE, FT_PLOT_MESH

% Copyright (C) 2005-2019, Robert Oostenveld, Ingrid Nieuwenhuis, Jan-Mathijs Schoffelen, Arjen Stolk

% Copyright (C) 2023, Jan-Mathijs Schoffelen

%

% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org

% for the documentation and details.

%

% FieldTrip is free software: you can redistribute it and/or modify

% it under the terms of the GNU General Public License as published by

% the Free Software Foundation, either version 3 of the License, or

% (at your option) any later version.

%

% FieldTrip is distributed in the hope that it will be useful,

% but WITHOUT ANY WARRANTY; without even the implied warranty of

% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the

% GNU General Public License for more details.

%

% You should have received a copy of the GNU General Public License

% along with FieldTrip. If not, see <http://www.gnu.org/licenses/>.

%

% $Id$

% deal with multiple filenames, if the geometry and labels are stored

% in different files, as with freesurfer/caret

if isa(filename, 'cell')

if numel(filename)==2

filenamemesh = filename{2};

filename = filename{1};

else

ft_error('with multiple filenames, only 2 files are allowed');

end % if precisely two input files

end % iscell

% optionally get the data from an URL and make a temporary local copy

filename = fetch_url(filename);

[p, f, x] = fileparts(filename);

labelfile = ft_getopt(varargin, 'labelfile', []);

ftype = ft_filetype(filename);

% if the original file was a .gz

if isequal(x,'.gz')

[p, f, x] = fileparts(filename(1:end-3));

end

% do an educated guess of the format based on the input, ensure that the

% required additional functions are available, and specify the companion labelfile

if contains(filename, 'BRIK') || contains(filename, 'HEAD')

% the above is needed to correctly detect zipped files

ft_hastoolbox('afni', 1);

% this is robust for both compressed or uncompressed afni atlases.

format = 'afni';

elseif startsWith(ftype, 'nifti')

% first handle the ones for which the labels are implicit in the filename

if contains(f, 'Yeo2011_7Networks')

% assume to be conform the shared atlas, with hardcoded index-to-label mapping

format = 'yeo7';

elseif contains(f, 'Yeo2011_17Networks')

% assume to be conform the shared atlas, with hardcoded index-to-label mapping

format = 'yeo17';

end

% try for different conventions of the naming of a potential companion labelfile

if isempty(labelfile)

labelfile = fullfile(p, sprintf('%s.txt', f));

if ~exist(labelfile, 'file')

% in case the volume was zipped, and the txt only replaced the gz

labelfile = fullfile(p, sprintf('%s.nii.txt', f));

end

if ~exist(labelfile, 'file')

labelfile = ''; % revert back to empty

end

end

if ~isempty(labelfile)

% do a quick check on the companion labelfile to specify the format

fid = fopen_or_error(labelfile, 'rt');

l1 = fgetl(fid);

if strcmp(l1(1),'[') && strcmp(l1(end),']')

% specific to this one is that some of the wakeforest atlases contain non-human data, so no fixed coordsys can be assumed

format = 'wfu';

coordsys = 'unknown';

elseif strcmp(l1,'Brainnetome Atlas')

% specific to this one is the coordinate system it seems

format = 'brainnetome';

coordsys = 'mni'; % apparently the image is in radiological convention,

% so the voxel-axes are left-handed. The even valued parcels should end

% up in the right hemisphere

elseif contains(filename, 'ROI_MNI') || contains(filename, 'AAL')

% newer versions of AAL also exist with a companion .xml file, this is not yet supported

format = 'aal';

coordsys = 'mni';

end

fclose(fid);

end

if contains(filename, 'final_tissues')

ft_hastoolbox('freesurfer', 1); % required to read lookuptable

% assume to be from SimNIBS version 4

format = 'simnibs_v4';

labelfile = fullfile(p, sprintf('%s_LUT.txt', f));

end

if isempty(labelfile)

% just a nifti file without interpretation of labels

format = 'nifti_no_label';

end

elseif isequal(ftype, 'freesurfer_mgz') && contains(f, 'aparc') || contains(f, 'aseg')

ft_hastoolbox('freesurfer', 1);

% individual volume based segmentation from freesurfer

format = 'freesurfer_volume';

if isempty(labelfile)

% use the version for freesurfer that is in fieldtrip/external/freesurfer

[ftver, ftpath] = ft_version;

labelfile = fullfile(ftpath, 'external/freesurfer', 'FreeSurferColorLUT.txt');

end

elseif isequal(ftype, 'freesurfer_annot')

ft_hastoolbox('freesurfer', 1);

% individual volume based segmentation from freesurfer

format = 'freesurfer_surface';

elseif isequal(ftype, 'caret_label')

ft_hastoolbox('gifti', 1);

% this is a gifti file that contains both the values for a set of vertices as well as the labels.

format = 'caret_label';

elseif contains(filename, 'MPM.mat')

ft_hastoolbox('spm8up', 1);

% assume to be from the spm_anatomy toolbox

format = 'spm_anatomy';

elseif exist(fullfile(p, [f '_MPM.mat']), 'file')

ft_warning('please specify the corresponding MPM.mat file as the filename');

filename = fullfile(p, [f '_MPM.mat']); % update the filename

[p, f, x] = fileparts(filename);

ft_hastoolbox('spm8up', 1);

% assume to be from the spm_anatomy toolbox

format = 'spm_anatomy';

elseif strcmp(x, '.xml')

ft_hastoolbox('gifti', 1); % required to read the xml

% fsl-style atlas, this is assumed to consist of an .xml file that specifies the labels, as well as a pointer

% to the file/folder with the volume data.

format = 'fsl';

labelfile = fullfile(p, sprintf('%s.xml',f));

elseif strcmp(x, '.mat')

% mat-file to contain a well-defined structure

format = 'mat';

else

format = 'unknown';

end

% get the optional input arguments

fileformat = ft_getopt(varargin, 'format', format);

unit = ft_getopt(varargin, 'unit');

switch fileformat

case {'aal' 'brainnetome' 'freesurfer_volume' 'nifti_no_label' 'simnibs_v4' 'wfu'}

atlas = ft_read_mri(filename, 'outputfield', 'tissue');

% interpret the format specific labelfile

if isequal(fileformat, 'aal')

% The labelfile is a combination of nii+txt file, where the txt file may contain three columns like this

% FAG Precentral_L 2001

% FAD Precentral_R 2002

% ...

fid = fopen_or_error(labelfile, 'rt');

C = textscan(fid, '%s%s%d');

lab = C{2};

idx = C{3};

fclose(fid);

elseif isequal(fileformat, 'wfu')

% the download from http://fmri.wfubmc.edu comes with pairs of nii and txt files

% the text file looks like this, with tabs between the colums

% the section at the end with three times 191 does not always exist

%

% [ TD Labels]

% 53 Angular Gyrus 191 191 191

% 39 Anterior Cingulate 191 191 191

% ...

fid = fopen_or_error(labelfile, 'rt');

C = textscan(fid, '%d%s%*[^\n]', 'HeaderLines', 1, 'Delimiter', '\t');

lab = C{2};

idx = C{1};

fclose(fid);

elseif any(strcmp(fileformat, {'simnibs_v4' 'freesurfer_volume'}))

[idx, lab, rgba] = read_fscolorlut(labelfile);

lab = cellstr(lab);

elseif isequal(fileformat, 'brainnetome')

% Brainnetome Atlas: L. Fan, et al.The Human Brainnetome Atlas: A New Brain Atlas Based on

% Connectional Architecture. Cereb Cortex 2016; 26 (8): 3508-3526. doi: 10.1093/cercor/bhw157

fid = fopen_or_error(labelfile, 'rt');

fgetl(fid); % this reads: 'Brainnetome Atlas'

lab = cell(246,1);

for i=1:246

lab{i,1}=fgetl(fid);

end

idx = (1:246)';

fclose(fid);

elseif isequal(fileformat, 'nifti_no_label')

% the file does not exist

ft_warning('cannot locate a labelfile, making default tissue labels');

idx = (1:max(atlas.tissue(:)))';

lab = cell(size(idx));

for i = 1:numel(lab)

% this is consistent with FIXSEGMENTATION

lab{i} = sprintf('tissue %d', i);

end

end

if ~isfield(atlas, 'coordsys') && exist('coordsys', 'var')

atlas.coordsys = coordsys;

end

uval = unique(atlas.tissue(:));

sel = find(ismember(idx, uval));

fprintf('subselecting %d labels from the total list of %d\n', numel(sel), numel(lab));

idx = idx(sel);

lab = lab(sel);

if exist('rgba', 'var')

tmprgba = rgba(sel,:);

rgba = zeros(0,4);

end

% remap the values in the data, if needed

if ~isequal(idx(:)', 1:numel(idx))

dat = zeros(atlas.dim);

cnt = 0;

for k = 1:numel(idx)

sel = atlas.tissue==idx(k);

if sum(sel(:))

cnt = cnt+1;

fprintf('re-indexing label %s to a value of %d (was %d)\n', lab{k}, cnt, idx(k));

dat(sel) = cnt;

tissuelabel{cnt,1} = lab{k};

if exist('rgba', 'var')

rgba(cnt,:) = tmprgba(k,:);

end

end

end

atlas.tissue = dat;

else

tissuelabel = lab;

end

atlas.tissuelabel = tissuelabel;

if exist('rgba', 'var'), atlas.rgba = rgba; end

% reduce memory footprint

if numel(tissuelabel)<=intmax('uint8')

atlas.tissue = uint8(atlas.tissue);

elseif numel(tissuelabel)<=intmax('uint16')

atlas.tissue = uint16(atlas.tissue);

elseif numel(tissuelabel)<=intmax('uint32')

atlas.tissue = uint32(atlas.tissue);

end

case 'afni'

tmp = ft_read_mri(filename);

if isfield(tmp, 'coordsys') && ~strcmp(tmp.coordsys, 'unknown')

coordsys = tmp.coordsys;

elseif isfield(tmp.hdr, 'TEMPLATE_SPACE') && ~isempty(tmp.hdr.TEMPLATE_SPACE)

coordsys = lower(tmp.hdr.TEMPLATE_SPACE); % FIXME this is based on AFNI conventions, not easily decodable by FT

else

coordsys = 'tal'; % FIXME could be different in other atlases

end

if isfield(tmp.hdr, 'ATLAS_LABEL_TABLE') && ~isempty(tmp.hdr.ATLAS_LABEL_TABLE)

if isfield(tmp.hdr.ATLAS_LABEL_TABLE(1), 'sb_label') && ~all(tmp.anatomy(:)==round(tmp.anatomy(:)))

% probabilistic atlas

isprobabilistic = true;

else

% indexed atlas

isprobabilistic = false;

end

labels = {tmp.hdr.ATLAS_LABEL_TABLE.struct}';

values = [tmp.hdr.ATLAS_LABEL_TABLE.val]';

elseif contains(filename, 'TTatlas+tlrc')

isprobabilistic = false;

[labels, values] = TTatlas_labels;

else

ft_error('no information about the atlas labels is available');

end

atlas = [];

atlas.dim = tmp.dim(1:3);

atlas.transform = tmp.transform;

atlas.hdr = tmp.hdr;

atlas.coordsys = coordsys;

nbrick = size(tmp.anatomy,4);

for k = 1:nbrick

if ~isprobabilistic

brickname = sprintf('brick%d',k-1);

brick = tmp.anatomy(:,:,:,k);

ulabel = setdiff(unique(brick(:)), 0);

label = cell(size(ulabel));

nlabel = numel(label);

% renumber the brick from 1:N and keep track of the label

newbrick = zeros(size(brick));

for i = 1:nlabel

sel = find(values==ulabel(i));

if ~isempty(sel)

label(i) = labels(sel);

newbrick(brick==ulabel(i)) = i;

else

ft_warning('the value %d does not have a label according to the ATLAS_LABEL_TABLE and will be discarded', ulabel(i));

end

end

atlas.(brickname) = newbrick;

atlas.([brickname 'label']) = label;

else

atlas.(labels{k}) = tmp.anatomy(:,:,:,values(k)+1); % indexing is 0-based in this case

end

end

case {'freesurfer_surface'}

if contains(filename, 'a2009s')

parcelfield = 'a2009s';

elseif contains(filename, 'aparc')

parcelfield = 'aparc';

elseif contains(filename, 'ba')

parcelfield = 'BA';

else

ft_error('unknown freesurfer parcellation type requested');

end

% read the labels

[v, p, c] = read_annotation(filename);

label = c.struct_names;

rgba = c.table(:,1:4);

rgb = c.table(:,5); % compound value that is used for the indexing in vector p

index = ((1:c.numEntries)-1)';

switch ft_filetype(filenamemesh)

case 'freesurfer_triangle_binary'

[pos, tri] = read_surf(filenamemesh);

% ensure the triangles to be 1-indexed

if min(tri(:))==0 && max(tri(:))==size(pos,1)-1

tri = tri+1;

end

bnd.pos = pos;

bnd.tri = tri;

reindex = true;

otherwise

ft_error('unsupported fileformat for surface mesh');

end

% check the number of vertices

if size(bnd.pos,1) ~= numel(p)

ft_error('the number of vertices in the mesh does not match the number of elements in the parcellation');

end

% reindex the parcels, if needed: I am not fully sure about this, but the caret

% label files seem to have the stuff numbered with normal numbers, with unknown

% being -1. assuming them to be in order;

if reindex

% this is then freesurfer convention, coding in rgb

newp = zeros(size(p));

for k = 1:numel(label)

newp(p==rgb(k)) = index(k)+1;

end

else

uniquep = unique(p);

if uniquep(1)<0

p(p<0) = 0;

end

newp = p;

end

atlas = [];

atlas.pos = bnd.pos;

atlas.tri = bnd.tri;

atlas.(parcelfield) = newp;

atlas.([parcelfield, 'label']) = label;

atlas.rgba = rgba;

atlas = ft_determine_units(atlas);

case 'caret_label'

g = gifti(filename);

rgba = [];

if isfield(g, 'labels')

label = g.labels.name(:);

key = g.labels.key(:);

if isfield(g.labels, 'rgba')

rgba = g.labels.rgba; % I'm not sure whether this always exists

end

else

label = g.private.label.name(:);

key = g.private.label.key(:);

if isfield(g.private.label, 'rgba')

rgba = g.private.label.rgba; % I'm not sure whether this always exists

end

end

%label = g.private.label.name; % provides the name of the parcel

%key = g.private.label.key; % maps value to name

% Store each column in cdata as an independent parcellation, because

% each vertex can have multiple values in principle

atlas = [];

for k = 1:size(g.cdata,2)

tmporig = g.cdata(:,k);

tmpnew = nan(size(tmporig));

tmplabel = cell(0,1);

tmprgba = zeros(0,4);

cnt = 0;

for m = 1:numel(label)

sel = find(tmporig==key(m));

if ~isempty(sel)

cnt = cnt+1;

if any(strcmp(tmplabel,deblank(label{m})))

% one feature of a gifti can be that the same labels can exist (and

% are treated as a different parcel) while they should be the same

% parcel, i.e. when there's an empty space at the end of the label

val = find(strcmp(tmplabel, deblank(label{m})));

else

% add as a new label

tmplabel{end+1,1} = label{m};

if ~isempty(rgba), tmprgba(end+1,:) = rgba(m,:); end

val = cnt;

end

tmpnew(tmporig==key(m)) = val;

end

end

% there is some additional meta data that may be useful, but for now

% stick to the rather uninformative parcellation1/2/3 etc.

%

% if strcmp(g.private.data{k}.metadata(1).name, 'Name')

% parcelfield = fixname(g.private.data{k}.metadata(1).value);

% else

% ft_error('could not determine parcellation name');

% end

if size(g.cdata,2)>1

parcelfield = ['parcellation' num2str(k)];

else

parcelfield = 'parcellation';

end

atlas.(parcelfield) = tmpnew;

atlas.([parcelfield 'label']) = tmplabel;

if ~isempty(tmprgba), atlas.rgba = tmprgba; end

end

if exist('filenamemesh', 'var')

tmp = ft_read_headshape(filenamemesh);

atlas.pos = tmp.pos;

atlas.tri = tmp.tri;

atlas = ft_determine_units(atlas);

elseif ~isfield(atlas, 'coordsys')

atlas.coordsys = 'unknown';

end

case 'spm_anatomy'

% load the map, this is assumed to be the struct-array MAP

load(filename);

[p,f,e] = fileparts(filename);

mrifilename = fullfile(p,[strrep(f, '_MPM',''),'.img']);

atlas = ft_read_mri(mrifilename, 'dataformat', 'analyze_img', 'outputfield', 'tissue');

tissue = round(atlas.tissue); % I don't know why the values are non-integer

label = {MAP.name}';

idx = [MAP.GV]';

% check whether all labels are present

if numel(intersect(idx,unique(tissue(:))))<numel(idx)

fprintf('there are fewer labels in the volume than in the list\n');

end

% remap the values of the labels to run from 1-numel(idx)

newtissue = zeros(size(tissue));

for k = 1:numel(idx)

newtissue(tissue==idx(k)) = k;

end

atlas.tissue = newtissue;

atlas.tissuelabel = label;

atlas.coordsys = 'spm'; % I think this is safe to assume

clear tissue newtissue;

case 'fsl'

map = ft_getopt(varargin, 'map', 'maxprob');

switch map

case 'prob'

imagefile = 'imagefile';

case 'maxprob'

imagefile = 'summaryimagefile';

otherwise

error('unknown map requested');

end

ft_hastoolbox('gifti', 1);

hdr = xmltree(filename);

hdr = convert(hdr);

% get the full path

[p, f , x] = fileparts(filename);

mrifilename = sprintf('%s.nii.gz', hdr.header.images{1}.(imagefile));

if isequal(mrifilename(1), '/')

mrifilename = mrifilename(2:end); % remove first backslash to avoid error if no full path was given

end

% this uses the thresholded image

switch map

case 'maxprob'

atlas = ft_read_mri(fullfile(p, mrifilename), 'outputfield', 'tissue');

atlas.tissuelabel = hdr.data.label(:);

atlas.coordsys = 'mni';

case 'prob'

tmp = ft_read_mri(fullfile(p, mrifilename));

atlas = removefields(tmp, 'anatomy');

for m = 1:numel(hdr.data.label)

fn = strrep(hdr.data.label{m}, ' ' , '_');

fn = strrep(fn, '-', '_');

fn = strrep(fn, '(', '');

fn = strrep(fn, ')', '');

atlas.(fn) = tmp.anatomy(:,:,:,m);

if ~isa(atlas.(fn), 'double') && ~isa(atlas.(fn), 'single')

% ensure that the probabilistic values are either double or

% single precision, do single precision to save memory

atlas.(fn) = single(atlas.(fn));

end

if any(atlas.(fn)(:)>1) && all(atlas.(fn)(:)<=100)

% convert to probability values, assuming 100 to be max

atlas.(fn) = atlas.(fn)./100;

end

end

atlas.coordsys = 'mni';

atlas.dim = atlas.dim(1:3);

end

case 'mat'

tmp = load(filename);

if isfield(tmp, 'Vertices') && isfield(tmp, 'Atlas')

% this applies to BrainStorm *.mat files containing cortical meshes

atlas.pos = tmp.Vertices;

% copy some optional fields over with a new name

atlas = copyfields(tmp, atlas, {'Faces', 'Curvature', 'SulciMap'});

atlas = renamefields(atlas, {'Faces', 'Curvature', 'SulciMap'}, {'tri', 'curv', 'sulc'});

for i=1:numel(tmp.Atlas)

name = fixname(tmp.Atlas(i).Name);

nlabel = numel(tmp.Atlas(i).Scouts);

label = cell(1, nlabel);

index = zeros(size(atlas.pos,1), 1);

for j=1:nlabel

index(tmp.Atlas(i).Scouts(j).Vertices) = j;

label{j} = tmp.Atlas(i).Scouts(j).Label;

end

atlas.( name ) = index;

atlas.([name 'label']) = label;

end

elseif isfield(tmp, 'atlas')

% this applies to most FieldTrip *.mat files

atlas = tmp.atlas;

elseif numel(fieldnames(tmp))==1

% just take whatever variable is contained in the file

fn = fieldnames(tmp);

atlas = tmp.(fn{1});

if isstruct(atlas)

ft_warning('assuming that the variable "%s" in "%s" represents the atlas', fn{1}, filename);

else

ft_error('cannot read atlas structure from "%s"', filename);

end

else

ft_error('the mat-file %s does not contain a variable called ''atlas''',filename);

end

case 'yeo7'

% this uses Yeo2011_7Networks_MNI152_FreeSurferConformed1mm_LiberalMask_colin27.nii, which is

% the 7 network parcellation from https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation_Yeo2011

% aligned to the colin27 template (skull-stripped version of single_subj_T1_1mm.nii)

% using AFNI's 3dQwarp and 3dNwarpApply

atlas = ft_read_mri(filename, 'outputfield', 'tissue');

atlas.coordsys = 'mni';

atlas.tissuelabel = {

'7Networks_1'

'7Networks_2'

'7Networks_3'

'7Networks_4'

'7Networks_5'

'7Networks_6'

'7Networks_7'

};

colors = [

120 18 134;

70 130 180;

0 118 14;

196 58 250;

220 248 164;

230 148 34;

205 62 78

]; % not used

case 'yeo17'

% this uses Yeo2011_17Networks_MNI152_FreeSurferConformed1mm_LiberalMask_colin27.nii, which is

% the 17 network parcellation from https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation_Yeo2011

% aligned to the colin27 template (skull-stripped version of single_subj_T1_1mm.nii) using AFNI's 3dQwarp and 3dNwarpApply

atlas = ft_read_mri(filename, 'outputfield', 'tissue');

atlas.coordsys = 'mni';

atlas.tissuelabel = {

'17Networks_1'

'17Networks_2'

'17Networks_3'

'17Networks_4'

'17Networks_5'

'17Networks_6'

'17Networks_7'

'17Networks_8'

'17Networks_9'

'17Networks_10'

'17Networks_11'

'17Networks_12'

'17Networks_13'

'17Networks_14'

'17Networks_15'

'17Networks_16'

'17Networks_17'

};

colors = [

120 18 134;

255 0 0;

70 130 180;

42 204 164;

74 155 60;

0 118 14;

196 58 250;

255 152 213;

220 248 164;

122 135 50;

119 140 176;

230 148 34;

135 50 74;

12 48 255;

0 0 130;

255 255 0;

205 62 78

]; % not used

otherwise

ft_error('unsupported format "%s"', fileformat);

end % switch fileformat

if ~isempty(unit)

% ensure the atlas is in the desired units

atlas = ft_convert_units(atlas, unit);

else

% ensure the units of the atlas are specified

try

atlas = ft_determine_units(atlas);

catch

% ft_determine_units will fail for triangle-only gifties.

end

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% TTatlas labels moved to a subfunction for readability of the above code

function [labels, values] = TTatlas_labels

% the following information is from https://sscc.nimh.nih.gov/afni/doc/misc/afni_ttatlas/index_html

values = [

68

71

20

21

22

24

25

26

27

28

29

30

31

32

33

34

35

36

37

39

40

41

42

43

44

45

46

47

48

49

50

51

52

70

72

73

74

75

76

77

124

125

126

128

129

130

131

132

133

134

135

136

137

138

144

145

151

146

147

148

149

81

82

83

84

85

86

87

88

89

90

91

93

94

95

96

97

98

99

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

53

54

55

56

57

58

59

60

61

62

63

66

65

127

64

67

];

labels = {

'Hippocampus'

'Amygdala'

'Posterior Cingulate'

'Anterior Cingulate'

'Subcallosal Gyrus'

'Transverse Temporal Gyrus'

'Uncus'

'Rectal Gyrus'

'Fusiform Gyrus'

'Inferior Occipital Gyrus'

'Inferior Temporal Gyrus'

'Insula'

'Parahippocampal Gyrus'

'Lingual Gyrus'

'Middle Occipital Gyrus'

'Orbital Gyrus'

'Middle Temporal Gyrus'

'Superior Temporal Gyrus'

'Superior Occipital Gyrus'

'Inferior Frontal Gyrus'

'Cuneus'

'Angular Gyrus'

'Supramarginal Gyrus'

'Cingulate Gyrus'

'Inferior Parietal Lobule'

'Precuneus'

'Superior Parietal Lobule'

'Middle Frontal Gyrus'

'Paracentral Lobule'

'Postcentral Gyrus'

'Precentral Gyrus'

'Superior Frontal Gyrus'

'Medial Frontal Gyrus'

'Lentiform Nucleus'

'Hypothalamus'

'Red Nucleus'

'Substantia Nigra'

'Claustrum'

'Thalamus'

'Caudate'

'Caudate Tail'

'Caudate Body'

'Caudate Head'

'Ventral Anterior Nucleus'

'Ventral Posterior Medial Nucleus'

'Ventral Posterior Lateral Nucleus'

'Medial Dorsal Nucleus'

'Lateral Dorsal Nucleus'

'Pulvinar'

'Lateral Posterior Nucleus'

'Ventral Lateral Nucleus'

'Midline Nucleus'

'Anterior Nucleus'

'Mammillary Body'

'Medial Globus Pallidus'

'Lateral Globus Pallidus'

'Putamen'

'Nucleus Accumbens'

'Medial Geniculum Body'

'Lateral Geniculum Body'

'Subthalamic Nucleus'

'Brodmann area 1'

'Brodmann area 2'

'Brodmann area 3'

'Brodmann area 4'

'Brodmann area 5'

'Brodmann area 6'

'Brodmann area 7'

'Brodmann area 8'

'Brodmann area 9'

'Brodmann area 10'

'Brodmann area 11'

'Brodmann area 13'

'Brodmann area 17'

'Brodmann area 18'

'Brodmann area 19'

'Brodmann area 20'

'Brodmann area 21'

'Brodmann area 22'

'Brodmann area 23'

'Brodmann area 24'

'Brodmann area 25'

'Brodmann area 27'

'Brodmann area 28'

'Brodmann area 29'

'Brodmann area 30'

'Brodmann area 31'

'Brodmann area 32'

'Brodmann area 33'

'Brodmann area 34'

'Brodmann area 35'

'Brodmann area 36'

'Brodmann area 37'

'Brodmann area 38'

'Brodmann area 39'

'Brodmann area 40'

'Brodmann area 41'

'Brodmann area 42'

'Brodmann area 43'

'Brodmann area 44'

'Brodmann area 45'

'Brodmann area 46'