fMRI数据处理的几个matlab小程序

fMRI数据处理的几个matlab小程序

（内容转载自网络，网址：http://www.dartmouth.edu/~raj/fmri-matlab.html）

Here are some tutorial files that show how to use Matlab for fMRI. Please feel more than free to use the code for teaching, and if you do, please mail me with comments and feedback.

The code has lots of comments in it, which attempt to explain the concepts as explicitly as possible. No prior knowledge of Matlab or linear algebra is assumed.

• hrf_tutorial.m - This program is a good place to start. It shows the basic shape of a Haemodynamic Response Function (HRF), how to convolve an HRF with a time-series of stimulus onsets in order to produce a predicted fMRI signal, and how to plot the results in Matlab. The program also shows what happens when closely-spaced stimuli produce HRFs which overlap in time and linearly sum.
  
  
• math_of_convolution.m - This program shows how convolution works, going through all the steps of exactly what gets added up and multiplied with what. It also explains from the ground-up how to do for-loops in Matlab. (By the way, if you want to see an example of how to "vectorise" code to avoid for-loops altogether, look at the bkprop.m program in my Matlab for neural-nets page).
  
  
• design_matrix_tutorial.m - This program shows what the rows and columns of a design matrix mean, how each column represents the predicted response to a given stimulus condition, and how the design matrix gets used to estimate the sensitivity of a voxel to various stimulus conditions. The program walks step-by-step through the process of estimating the model parameters for a voxel's noisy fMRI-signal, making plots of the results along the way.

The following programs show how to use Matlab to view brain slices and to overlay statistical maps on top of anatomical scans. In order to run them, you need the companion .mat file that contains the brain images: speech_brain_images.mat (Choose "Download link to disk" with right-click, or Control-mouseclick).

• showing_brain_images_tutorial.m - Start with this program. It doesn't assume any prior knowledge of Matlab. It shows how to extract slices (axial, sagittal etc.) from a 3D volume and how to plot them with the appropriate axes, colormaps, and color-scaling.
  
  
• overlaying_Tmaps_tutorial.m - This program shows how to overlay a statistical map on top of an anatomical map. It assumes that you've already worked through showing_brain_images_tutorial.m You can see some more examples of showing brain images, this time using the transparency properties of Matlab 6, in the program put_into_same_voxel_space.m below.
  

The programs below are slightly more complicated, and use functions from SPM99. The code gives commented examples of how to do things like reading SPM images into Matlab, finding their origins, displaying overlays, and extracting parts of SPM plots.

• put_into_same_voxel_space.m - This program lets you put one image into the same voxel space as another image. E.g. you might want to extract a Brodmann area from the brodmann.img file that comes with MRIcro, and then put that set of 1x1x1mm voxels into the same voxel space as your functional data, which probably covers a smaller volume and has larger voxels. Then you can use the Brodmann area as an ROI to explore your functional results.
• grab_mip.m - This program grabs the "glass brain" Maximum Intensity Projection (MIP) from an SPM99 results plot, makes the voxels orange-ish instead of gray, and offers the option of saving the separate brain images into EPS files, which are good for distilling into PDFs or for loading directly into Adobe Illustrator. By the way, the EPS files are large (around 192K), but they shrink into nice compact 8K PDF files.