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ajay:neuroelf_usage_notes [2013/10/21 12:50] – [Visualization Help] ajayajay:neuroelf_usage_notes [2025/01/21 02:00] (current) – [Exporting files to SPM, FSL, etc.] asatpute
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   - Then...<code matlab ajay_get_betas_in_glm_from_voi.m>   - Then...<code matlab ajay_get_betas_in_glm_from_voi.m>
-voi_betas = glm.VOIBetas(voi);</code>  +voi_betas = glm.VOIBetas(voi); 
- +%or to get all the beta maps not limited to a voi 
 +betas = glm.GLMData.Subject(S).BetaMaps(:,:,:,:);  
 +</code> 
 ==== Using command lines to extract design information from glm NeuroElf ==== ==== Using command lines to extract design information from glm NeuroElf ====
   - glm.SubjectPredictors provides names of predictors   - glm.SubjectPredictors provides names of predictors
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   - to restrict stats to voxels with brain data, keep the multiplication box checked; potentially alter the minimum anatomical value to increase/decrease visibility of stats around the border of the data   - to restrict stats to voxels with brain data, keep the multiplication box checked; potentially alter the minimum anatomical value to increase/decrease visibility of stats around the border of the data
   - higher interpolation (cubic/sinc) takes longer but gives also better quality output (mostly useful for higher resolution renderings); only set to sinc for final shot!   - higher interpolation (cubic/sinc) takes longer but gives also better quality output (mostly useful for higher resolution renderings); only set to sinc for final shot!
 +
 +===== Using the new 3D rendering tool with skull =====
 +Jochen Email
 +  - download and install the latest snapshot: http://neuroelf.net/NE_14032023.zip
 +  - then use "neuroelf_setup" and "neuroelf_makefiles all" (without quotes)
 +  - when you next open the NeuroElf GUI, load the following VMR/anatomical from the File -> Colin menu: colin_brain_rendskull_ICBMnorm.vmr and colin_hires_ICBMnorm.vmr
 +  - in the main UI, ensure that the colin_hires_ICBMnorm.vmr is selected
 +  - use the render button (below the surface view button) on the right side to switch to render view
 +  - in the newly open render UI, select the colin_brain_rendskull_ICBMnorm.vmr dataset as the "Alpha volume" (transparency information; dropdown close to the top)
 +  - once the rendering is complete, you can use the same controls as for the surface view (mouse; with shift to translate and alt to zoom; and also cursor keys)
 +
 +When you want to add a stats map (or several maps), please know that each map will be resampled into the resolution of the anatomical prior to rendering, so to display 3 stats maps (at the same time) on top of the high-res colin brain, you probably need between 2 and 3 GB free memory! Also, for stats maps, I suggest changing them to "stats-dependent transparency" (pressing the "n" key while in the slice-view, THEN selecting the map/s you want to show, and then switching to render view)
  
 ===== Drawing/creating a mask ===== ===== Drawing/creating a mask =====
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-==== Scripting and Batching: Dangers  ==== +==== Scripting and Batching: Tips and Pitfalls ====
-Sometimes we may want to run multiple glms changing one or another option.+
  
-If this is what you want to do, BE SURE TO DO THESE TWO THINGS+Verify the parameters for you GLM. In the command line, once you load the glm (E.g. by using >>glm = xff('*.glm')), you can ensure the parameters (e.g. motion correction as covariates, percent signal change transform, filter type and implementation, etc.) using the following two locations in the glm object. 
 +  - glm.Study(1).RunTimeVars.Predictors'  
 +  - glm.RunTimeVars 
 + 
 +Sometimes we may want to run multiple glms changing one or another option. If so, BE SURE TO DO THESE TWO THINGS:
   - clear the object between analyses. glm.ClearObject; mdm.ClearObject;   - clear the object between analyses. glm.ClearObject; mdm.ClearObject;
   - 'bless' the command where you run the mdm: glm = bless(mdm.ComputeGLM(opts));   - 'bless' the command where you run the mdm: glm = bless(mdm.ComputeGLM(opts));
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   - INCORRECT: struct('tfilter',200,'tfilttype','dct','motpars',rps)   - INCORRECT: struct('tfilter',200,'tfilttype','dct','motpars',rps)
   - where rps is a cell array pointing to files name for realignment parameters   - where rps is a cell array pointing to files name for realignment parameters
 +  - VERIFY YOUR GLM using the methods indicated above.
 +
 +If your scripting is running inordinately slow, it may be because NeuroElf is loading, closing, and re-loading relevant data for a given step in your code. For example, when obtaining the betas from a glm for a set of vois, if you iterate across the vois to load the GLM, then it may reload all the GLM data each time. This is because NeuroElf runs efficiently by not loading up all the data unless it really needs to, but if you're coding, then you need to specify that. Use the following:
 +   >>glm.LoadTransIOData
  
  
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   - where the second argument, true, makes the output be written in TAL order, such that it complies with FSL's internal preference.   - where the second argument, true, makes the output be written in TAL order, such that it complies with FSL's internal preference.
   - also works with vtc, glm, etc.   - also works with vtc, glm, etc.
 +
 +==== Installing Neuroelf on Apple Silicon  ====
 +
 +1. Update MAC OS
 +2. Update Matlab 
 +3. Download neuroelf
 +4. You may run into issues with mexmaca64 files. You either have to tell OS that those files are allowed to be opened by trying to open them. Or you can delete all of them, install XCode, and then recompile the mexmaca64 files from scratch (see below).
 +5. in matlab, add path to the parent neuroelf directory (not with subdirectories)
 +7. then, save path
 +8. >>n = neuroelf
 +9. >>n.neuroelf_makelibs %this is to make the mexmaca64 files
 +10. >>neuroelf_setup
 +
  
  
ajay/neuroelf_usage_notes.1382359839.txt.gz · Last modified: 2013/10/21 12:50 by ajay