FieldTrip supports the use of an anatomical atlas to look up the anatomical label of a source that you have localized. Vice versa you can also first look up the location of an anatomical region and subsequently use that in source analysis, e.g. as region of interest for beamforming or as starting point for dipole fitting.

脑部区域被分类成很多区域,这里主要讲的是如何利用分区模板进行 单独调用


%% ROI descritive for source data
aal = ft_read_atlas(‘ROI_MNI_V4.nii’); % the template segement of brain  这个是mni的模板 分成117个区域
front_idx = strmatch(‘Front’, aal.tissuelabel); % just for example the area of interest, 将含有Front的区域调取出来
%Occipital_idx = strmatch(‘Occipital’, aal.tissuelabel);

cfg = [];
cfg.inputcoord = ‘mni';
cfg.atlas = aal;
cfg.roi = aal.tissuelabel(front_idx);
mask = ft_volumelookup(cfg, sourceNAIIntfu); 通过roi labels来获取对应的mask

cfg = [];
cfg.inputcoord = ‘mni';
cfg.atlas = aal;
cfg.maskparameter = ‘mask';
labels= ft_volumelookup(cfg, sourceNAIIntfu); % 通过mask来获取对应的labels

cfg = [];
cfg.atlas =aal;
cfg.roi =aal.tissuelabel(ccipital_idx);
cfg.atlascoordinates =’mni';
cfg.method = ‘surface'; % only ortho supported  注意这种区域图只支持ortho方式
cfg.funparameter = ‘avg.pow';
cfg.maskparameter = cfg.funparameter;
cfg.funcolorlim = [2.2 4.2];
cfg.opacitylim = [2.2 4.2];
cfg.opacitymap = ‘rampup';
ft_sourceplot(cfg, sourceNAIIntfu); 如下图所示,可以拖动蓝线进行查看  这里使用的 3D gird model 的 5mm分辨率, 你也可以生成1mm的分辨率,时间嘛  我花了一晚上没跑完。

% end of the source subselecting plot method .




关于Colin27 多说两句 这个是有蒙特利尔神经研究所无聊的人 将多次扫描结果进行平均得来的脑部解剖mri