conn
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1. control these effects by weighting down the initial scans within a block hrf weights or both the beginning and end scans within a block hanning weights Click on Connectivity Measures to change the method of analysis correlation or regression semipartial for multiple sources The right panel Preview results displays the connectivity measures for each subject condition source Analyses here are performed in real time any changes in the Define sources definitions affect directly the results displayed in the Preview window The measures displayed in the Preview results brain image correspond to the connectivity measure selected r if correlation is selected beta if regression is selected The threshold value is also defined in the same units in the figure above voxels with correlation coefficients above 0 3 are shown colored When finished defining exploring the connectivity analyses press Done This will perform the defined analyses for all subjects and allow the user to explore second level between subject results in the next step First level results r maps or beta maps are also exported as nii volumes one per Subject Condition Source combination in the resu ts firstlevel folder 6 Functional connectivity toolbox manual v1 0 Step four Results Define and explore contrasts of interest and second level results SETUP PREPROCESSING ANALYSES RESULTS FUNCTIONAL CONNECTIMITY RESULTS Subjects2. the right panel shows the total variance explained 1 square by each of the possible confounding sources for the selected subject session data The dimensions of each confound can be changed up to the values entered in the Setup stage to explore its effect on the total variance explained Enter the band pass filter information in the bottom left box two numbers in Hz defining the band pass frequency window of interest When finished press the Done button This will filter the functional data and remove the effect of the defined confounds on all brain voxels and regions of interest 5 Functional connectivity toolbox manual v1 0 Step three Analyze Define and initially view the functional connectivity of different sources in single subject level SETUP PREPROCESSING ANALYSES RESULTS GLM CONNECTIVITY DEFINE SOURCES PREVIEW RESULTS Sources derivatives order dimensions Connectivity measure Within condition weights Click on the ANALYSES tab to define source of interest seed ROIs Use the With in condition weights for the following When estimating connectivity from rest blocks in a more complex design with other task blocks between condition differences in activation can affect the activation at the beginning or end of the rest block These effects are partially controlled by entering the condition regressors as possible confounds Hrf and hanning within condition weights attempt to further
3. Conditions Sources 5 correlation bivariate Between subjects contrast Between sources contrast 1 1 At this point second level analysis can be defined in the RESULTS window note that alternatively second level analyses can also be performed outside the toolbox by loading the nii images from the first level analysis into a random effects analysis program such as SPM A second level model is defined by selecting one or multiple elements in the Subjects list and specifying the desired between subjects contrast For example if we have two groups defined in the covariates second level setup step patients and controls simply select both of them in the Subjects list and enter 1 1 in the Between subject Contrast window This will compare the connectivity between the two groups Multiple ROIs sources can be selected simultaneously in order to analyze connectivity results across several ROIs by specifying the contrast in Between source contrast e g select both LLP and RLP sources and enter a 5 5 contrast to estimate the average connectivity with both sources The brain display at the right allows you to explore the results of the second level analyses estimated in real time These results can be thresholded using a voxel level uncorrected p value threshold p lt 001 uncorrected in the figure above When finished defining exploring the contrasts press Done This will 1 Export th
4. d extent cluster level thresholds Clusters are listed below together with their peak voxel location in mm number of voxels k uncorrected FWE corrected and FDR corrected cluster level p values and uncorrected and FDR corrected voxel level p values of the peak voxel Statistics are one sided select negative contrast in the dropdown menu at the top right to view the results for the reverse directionality of the contrast You can also export the results as a text file containing the significant clusters and their statistics export stats or as a nii mask file defining voxels that pass the significance threshold chosen export mask
5. e defined second level model to SPM second level SPM mat beta and contrast volumes are saved in a folder selected by the user 2 Produce whole brain maximum intensity projection MIP results that can be interactively thresholded using a combination of height thresholds based on uncorrected or FDR corrected voxel level p values and extent thresholds based on uncorrected FWE corrected or FDR corrected cluster level p values 7 Functional connectivity toolbox manual v1 0 positive contrast w height threshold voxel p 0 05 FDR corrected w extent threshold cluster p 0 05 PAE corrected w export mask export stats n n E Clusters x 2Z k cluster p unc cluster p FWE cluster p FDR voxel p unc voxel p FDR 00 44 20 6154 0 000000 0 000000 0 000000 0 000000 0 000073 a 06 58 20 4286 0 000000 0 000000 0 000000 0 000000 0 000073 30 22 18 550 0 000000 0 000000 0 000000 0 000002 0 000402 54 6 amp 4 26 429 0 000000 0 000005 0 000001 0 000004 0 000552 60 04 24 381 0 000000 0 000017 0 000002 0 000000 0 000207 20 30 48 327 0 000001 0 000076 0 000007 0 000000 0 000201 30 30 22 319 0 000001 0 000096 0 000008 0 000010 0 000958 422 30 44 306 0 000001 0 000140 0 000010 0 000026 0 001766 60 04 28 143 0 000309 0 028783 0 001821 0 000024 0 001663 This MIP display shows the results of the second level analyses thresholded by a combination of height voxel level an
6. elect the functional images img or nii or 4d nii This will take a second to load check the middle panel Functional data setup to make sure the correct volumes are loaded The brain display in the Functional data setup window shows the first left and last right scan for the selected subject session as in the figure above The current version of the toolbox assumes analyses are performed in normalized space GUI tip 1 The Find in the Select functional data files window can be used to search for all files within the target folder recursively Change the Filter window to narrow the search GUI tip 2 If multiple subjects are selected in the Subjects list and the number of files selected in the Select functional data files window matches the number of subjects each subject is assigned one single file from the list this is useful when one has 4 dimensional nii files one file per session in order to enter all of the functional files for each session simultaneously o Click on the Structural button on the left side to load the structural images Option 1 load raw anatomical image the toolbox will perform normalization and segmentation on it Option 2 If the normalized segmented images are available load the normalized anatomical image and load the white matter and CSF masks in the next step see below o Click on the ROIs button on the left side to load ROI mask files 1mg or nii vo
7. iates from these SPM mat files 4 Functional connectivity toolbox manual v1 0 Step two Preprocess Define explore and remove possible confounds SETUP B REPROCESSING T ANALYSES RESULTS GLM DEFINE POSSIBLE CONFOUNDS PREVIEW RESULTS Confounds derivatives order dimensions band pass filter Hz 0 003 0 09 Click on the PREPROCESSING tab By default the system will start with three different sources of possible confounders 1 BOLD signal from the white matter and CSF masks 5 dimensions each 2 any previously defined within subject covariate realignment parameters together with their first order derivatives and 3 the main condition effects blocks convolved with hrf For each of the selected possible confounds you can change the number of dimensions specifying how many temporal components are being used and the derivatives order specifying how many successive orders of temporal derivatives are included in the model For example the realignment confound derived from the estimated subject motion parameters is defined by default by 6 dimensions and 1 derivative order indicating that the six motion parameters are being used in addition to their first order temporal derivative terms Similarly the White Matter confound is defined by default by 5 dimensions and O derivative order indicating that 5 PCA temporal components are being used with not additional temporal derivative terms The Preview results window in
8. l Functional connectivity toolbox manual v1 0 Overview The toolbox performs seeded voxel correlations by estimating maps showing temporal correlations between the BOLD signal from given seed and that at every brain voxel The toolbox implements aCompCor strategy for physiological and other noise source reduction first level General Linear Model for correlation and regression connectivity estimation and second level random effect analyses The toolbox is designed to work with both resting state scans and block designs Installing the toolbox 1 download conn zip unzip the file 2 add conn directory to matlab path To start the toolbox On the matlab prompt type conn make sure your matlab path include the path to the connectivity toolbox Usage Functional connectivity toolbox manual v1 0 Step one Setup Defines experiment information file sources for functional data structural data regions of interest and other covariates SETUP Load Save Save as Import Basic Structural ROIs Conditions Covariates PREPROCESSING ANALYSES RESULTS Done Select functional data files Folder d zdrive mit susan connectivity data dost FUNCTIONAL DATA SETUP Subjects Sessions Click on the SETUP tab o Click on the Basic button on the left side enter experiment information Number of subjects TR and number of sessions per subject o Click on Functional button on the left side from the right side panel s
9. lumes or Talairach coordinate files tal text files 3 Functional connectivity toolbox manual v1 0 By default all files in the rois toolbox folder conn rois will be imported as initial regions of interest To import new ROIs click below the last ROI listed and enter the appropriate information Load the grey matter white matter and CSF mask for each subject if they already exist Option 2 in structural step above Mask files should be coregistered to the normalized structural of this subject they could be defined in normalized space or they could be defined in subject space and then transformed to normalized space in SPM The default dimensions number of PCA components to be extracted for each ROI can be changed here In the following steps preprocessing analyses you can later select the number of components among the extracted ones you wish to use in the connectivity analyses o Click on the Conditions button on the left side to enter onsets and durations in seconds of each experimental condition o Click on the Covariates First level button to define first level covariates such as realignment parameters to be used in the model o Click on the Covariates Second level button to define groups and subject level regressors e g behavioral measures Use 1 0 to define subject groups or continuous values to perform between subject regression models Click on the empty space below All to add a variable e g patie
10. nts 11110000 controls 00001111 performance 12323456 Note Second level covariates can be defined at any time in the analyses changes to any of other Setup options requires rerunning all the analyses steps while changes to the second level covariates do not as they only affect the second level analyses in the Results window When finished defining the experiment data press Done This will import the functional data It will also perform normalization amp segmentation of the structural data in order to define gray matter white matter CSF regions of interest option 1 in structural step above Last it will extract the ROIs time series performing PCA on the within ROI activations when appropriate After this process is finished come back to Setup to inspect the resulting ROIs for possible inconsistencies A mat file and a folder of the same name will be created for the project Save Save as button will save the setup configurations in a mat file which can be loaded later Load button The mat file will be updated each time the Done button is pressed Note If the data has initially been defined in SPM you can click the Import button right after entering the number of subjects in the Basic setup and specify one SPM mat file for each subject The program will extract the location of the functional data the number of conditions per subject the onset length of the conditions of interest and any specified first level covar
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