1.The Brainvisa Hierarchy for fmri databases

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1 fmri Pipeline.The Brainvisa Hierarchy for fmri databases The Brainvisa software defines a directory structure in order to help the selection of various files for the available treatments. Usually, a treatment has one or more entry files and one or two output files. In the functional pipeline, the input files are fmri datasets stored in a directory (the Session* directory as showed in fig. ) as well as all the preprocessed datasets (slice timed, smoothed,...). The results of the GLM are saved in a directory named according to data after the data directory in glm and the results of the contrast computation are stored in the Contrast directory. The Minf directory contains the data used for all the sessions such as a mask image, the contrast definitions or the experimental paradigm. Protocol Subject fmri Subject fmri Acquisition Acquisition Minf glm Session Session mask.img contrast.con paradigm.csv Session vba.hdf vba_config.con Residual_Variance.nii design_mat.csv Contrast con_id.nii TestT_id.nii TestF_id.nii ResMS_id.nii z_map_id.nii Session.nii asession.nii rasession.nii swrasession.nii... Fig. : The Brainvisa hierarchy (only the functionnal part). All images (D volumes and D fmri datasets) are stored in the nifti file format (in a unique file with a.nii extension).

2 .Preprocessing The preprocessings implemented in Brainvisa are calls to the SPM preprocessings. The user must have : A Matlab license available SPM Linux..Slice Timing The Slice Timing process corrects differences in image acquisition time between slices. Slice time corrected files are prefixed with an a The original fmri datasets. The Matlab file containing the SPM job that will be launched (for user control). The time between two image acquisition (reception time, in seconds, default :.). The duration of an image acquisition (acquisition time, in second, default :.). The number of slices in a volume of the fmri serie 6. The slice order in the volume 7. The first slice 8. The resulting images..realignment The Realignment process do a within subject registration of fmri series (estimation of realigment and reslicing of images).

3 . The fmri dataset to realign (with or without Slice timing). The Matlab file containing the SPM job that will be launched. Select wich images will be resliced : All images ([ 0]) All images (exluding the first one) ([ 0]) All images and the mean image ([ ] or [ ]) (Default) The mean image only ([0 ]). The resulting realigned images. The resulting mean images..coregistration. The fmri series to coregister on the anatomical image. The reference anatomical images (one for each fmri serie). The mean images of the fmri series (one for each fmri serie). The Matlab file containing the SPM job that will be launched. The written coregistered images

4 ..Normalization. Anatomical normalization 7 6. The anatomical data to normalize. (optional) The anatomical template. If not present the T MNI template is found in the matlab hierarchy.. The Matlab file containing the SPM job that will be launched. The size of each voxel of the volume. The type of transformation (Inf = rigid transformation, Default : ) 6. The number of iterations for the normalization (Default : 6) 7. The resulting transformation matrices. Functional normalization. The fmri series that will be normalized with the results of the anatomical normalization. The transformation matrix computed by th anatomical normalization. The Matlab file containing the SPM job that will be launched. The size of each voxel of each volume of the fmri datasets. The normalized images written by SPM

5 ..Smoothing. The fmri series to smooth. The Matlab file containing the SPM job that will be launched. The smoothing kernel size.. The smoothed images written by SPM For more details on the preprocessings, see the SPM documentation..subject analysis Mask Computation This process computes a mask image for one or more fmri dataset. It is important for the contrast computation to have only one mask for each subject (for multisession contrasts).. The fmri datasets for which we need a mask image. The brain mask (either placed in the Minf directory of the hierarchy or in the protocol directory). A threshold used to determine the minimum value of the brain (0 < infthreshold < ). A threshold used to determine the minimum value of the brain (0 < supthreshold < ) Importing paradigm from Eprime The importation of the experimental paradigm is the first step in the contrast computation pipeline.

6 It will be needed to compute the design matrix for each session of a subject. This process uses an excel like file to extract the experimental paradigm. An exportation of Eprime format files to Excel files then to Comma Separated Values (CSV) files is necessary. The user has to specify the presence of headers (column names), the paradigm type (event or bloc) and which columns contains the onset time of each task, the id of the task done and the corresponding session id. If a user wants to define his paradigm without this process, he has to : put the paradigm in the file : protocol/subject/fmri/acquisition/minf/paradigm.csv the paradigm file must have four columns in the following order : task, onset time, task duration and session The protocol/subject/fmri/acquisition/minf/misc_info.con file has to be created and must contain: [sessions] sessname = task, task, task... All the sessions of the acquisition must be described (with numbers if not with names)

7 The Comma Separated Values file containing Eprime extracted informations. The paradigm file containing four columns : task, onset time, task duration, session. A file that will contain some informations used for later processes. The presence of the columns names. The type of paradigm : event or bloc 6. The name of the tasks onsets column 7. The name of the tasks numbers column 8. The name of the session number column 9. The different sessions names to fill the information file (format as follows : sess sess...) 0. Optional : The names of the tasks (will be set to the numbers of the tasks if nothing is defined).

8 Format as follows : task task task... Design Matrix Creation The creation of the design matrix is the next step in the computation of the contrasts. The user can specify the type of hemodynamic response function (HRF) and the drift. A design matrix must be created for each session for a given subject. The names of the conditions are stored in the information file, there is a correspondance between the order of those names and the columns of the design matrix file The functional serie will be used to define the frame sequence and its corresponding times. The paradigm file created at the previous step. The information file created by the previous process. The time between two acquisitions. The type of HRF : Glover, Glover with derivative or FIR Model 6. The type of drift : Blank (column of identical values), cosine or polynomial 7. Optional : If a drift matrix is given, the drift parameter is ignored and the drift matrix is appended to the design matrix. 8. Optional : The frequency cut for a cosine drift. 9. Optional : The polynomial order for a polynomial drift. 0. Optional : The order of the FIR Model. It is the number of column that will be created for each condition in the design matrix.. Optional : The lenght of the FIR Model. It is the length of the hemodynamic response. Each column that will be created will have FIR_length / FIR_order non zeros values.. The design matrix file

9 Contrast Definition There are two methods to define the different contrasts, either you use the Brainvisa process or you write it yourself. A contrast definition file is as follow : contrast = Contrast, Contrast, Contrast... [Contrast] Type = t Dimension = sess_row0 = 0, 0, 0,, 0, 0... sess_row0 = 0, 0, 0, 0, 0, 0... [Contrast] Type = F Dimension = sess_row0 = 0, 0, 0,, 0... sess_row = 0, 0, 0, 0,... sess_row0 = 0, 0, 0, 0, 0... sess_row = 0,, 0, 0, The first line must be present and contain the contrasts names (in the order of computation willed be the user). Each contrast is defined by its name in braces and followed by the Type definition, and the dimension definition. Each sess*_row* defines a vector of integer as long as the regressor list defined in the information file.

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12 7 6. The file that already contains or will contains the contrasts definitions. The information file that is used to fill the contrast definition lines with the appropriate number of zeros. Choose the action to be done : Add a contrast, Edit an existing contrast, Remove a contrast or print a contrast. The list of contrasts already defined (empty at first, and filled as new contrasts are added). The type of contrast : Student t test or F test 6. The contrast dimension (for now it cannot be changed) 7. The contrast name (it will be filled with the selected contrast name if on is chosen from the contrast list) 8. The contrast definition for the first session/first dimension

13 GLM Computation 6 7. The fmri serie of images to fit with the GLM. The previously computed design matrix file. The mask image that will be applied on the volumes of the fmri serie. The algorithm used to fit the data : Kalman AR, Ordinary Least Square or Kalman. The hdf output file. It will be a dump of the glm object that will be loaded by the next process to compute the contrasts 6. The configuration file used to reload the hdf file 7. The residual variance image (mainly used to control results)

14 Contrast Computation. The contrast definition file (hand made or made with the appropriate process). The information file that will be used to load the GLM dumps. The save mode : Named contrasts or Numbered contrasts.group analysis Group Definition To do a group analysis you have to define a group of subjects concerned by the analysis. Be careful, there are two directories defined with the Session tag. For each subject, don t forget to choose only one of them (their paths are different).

15 . The list of subject selected (select only one session for each subject). The file containing the group definition. Be careful to select the sessions with the same path for each subject

16 Group analysis. Non parametric analysis 6 7. The name (or the number) of the contrast used for the group analysis. All the subjects of the group must have the contrast in their analysis. The group definition created with the previous process. The number of permutation that will be done. The use of random effect (only if the variance files can be found). The decision statistic : Empirical Likelihood ratio, Mean or Wilcoxon signed rank 6. The RFX analysis result (be sure you have the cond attribute set to contrast_name in the File Exploration dialog box) 7. The RFX image. Parametric analysis. The name (or the number) of the contrast used for the group analysis. All the subjects of the group must have the contrast in their analysis. The group definition created with the previous process. The fit algorithm of the GLM : Ordinary Least Square or Kalman. The resulting image