AFNI. h'p://afni.nimh.nih.gov/afni

Transcription

1 AFNI h'p://afni.nimh.nih.gov/afni

2 AFNI Fundamentals Basic unit of data in AFNI is the dataset A collection of 1 or more 3D arrays of numbers o Each entry in the array is in a particular spatial location in a 3D grid (a voxel = 3D pixel) o Image datasets: each array holds a collection of slices from the scanner Each number is the signal intensity for that particular voxel o Derived datasets: each number is computed from other dataset(s) e.g., each voxel value is a t-statistic reporting activation significance from an FMRI time series dataset, for that voxel Each 3D array in a dataset is called a sub-brick o There is one number in each voxel in each sub-brick 3x3x3 Dataset With 4 Sub-bricks

3 AFNI Dataset Files AFNI forma'ed datasets are stored in 2 file types.head holds auxiliary informabon.brik hold all the numbers in the sub- briks 3 coordinate systems Original (+orig) AC- PC aligned (+acpc) Talairach (+tlrc) AFNI can read many kinds of datasets: analyze (.hdr/.img),.mnc,.mri,.1d.nii is the new standard (when giving a prefix, must end in.nii to be saved in that format)

4 AFNI controller window at startup Titlebar shows current datasets: first one is [A], etc Coordinates of current focus point Switch to different coordinate system for viewing images Control crosshairs appearance Time index Open images and graphs of datasets Open new AFNI controller Help Button Markers control transformation to +acpc and +tlrc coordinates Controls color functional overlay Miscellaneous menus Switch between directories, underlay (anatomical) datasets, and overlay (functional) datasets Close this controller Place to show amusing logos Controls display of overlaid surfaces

5 AFNI Image Viewer Disp and Mont control panels

6 AFNI Time Series Graph Viewer Data (black) and Reference waveforms (red) Menus for controlling graph displays

7 Define Overlay: Colorizing Panel (etc) Threshold slider: voxels with Thr subbrick above this get colorized from Olay sub-brick p-value of current threshold value Color map for overlay Hidden popup menus here Choose which dataset makes the underlay image Cluster above-threshold voxels into contiguous blobs bigger than some given size Choose which sub-brick from Underlay dataset to display (usually an anatomical dataset) Choose which sub-brick of functional dataset is colorized (after threshold) Choose which sub-brick of functional dataset is the Threshold Shows ranges of data in Underlay and Overlay dataset Choose range of threshold slider, in powers of 10 Shows automatic range for color scaling Rotates color map Positive-only or both signs of function? Number of panes in color map (2-20 or **) Shows voxel values at focus Lets you choose range for color scaling (instead of autorange)

8 Volume Rendering: an AFNI plugin Pick new underlay dataset Name of underlay dataset Sub-brick to display Open color overlay controls Range of values in underlay Change mapping from values in dataset to brightness in image Range of values to render Histogram of values in underlay dataset Mapping from values to opacity Maximum voxel opacity Cutout parts of 3D volume Compute many images in a row Show 2D crosshairs Menu to control scripting (control rendering from a file) Render new image immediately when a control is changed Control viewing angles Accumulate a history of rendered images (can later save to an animation) Detailed instructions Force a new image to be rendered Reload values from the dataset Close all rendering windows

9 Command Line Programs Most parts of AFNI are only available through the command line 3dDeconvolve mulbple linear regression on 3D+Bme datasets, to fit each voxel s Bme series to an acbvabon model and test these fits for significance 3dNLfim for nonlinear fizng 3dANOVA 1, 2, 3, and 4- way ANOVA layouts for combining and contrasbng datasets in standard space 3dcalc general purpose voxel- wise calculator 3dclust find clusters of acbvated voxels 3dresample re- orient and/or resize dataset voxel grid

10 Single Subject Data Processing Assemble images into AFNI-formatted datasets Check images for quality (visual & automatic) Register (realign) images Smooth images spatially Mask out non-brain parts of images Normalize time series baseline to 100 (for %-izing) Fit stimulus timing + hemodynamic model to time series catenates imaging runs, removes residual movement effects, computes response sizes & inter-stim contrasts Segregate into differentially activated blobs Look at results, and ponder to group analysis (next page) 3dvolreg OR 3dWarpDrive 3dmerge OR (optional) 3dBlurToFWHM afni AND your personal brain to3d OR can do at NIH scanners afni + 3dToutcount 3dAutomask + 3dcalc (optional) 3dTstat + 3dcalc (optional: could be done post-fit) Alphasim + 3dmerge OR Extraction from ROIs 3dDeconvolve

11 Single Subject Get the data from dicom into a format readable by AFNI to3d Structural scan to3d prefix anat *.dcm Can also use d2afni FuncBonal scan to3d Bme:zt alt+z prefix EPI1 *.dcm - Bme:zt slices presented in the order of space then Bme 34 number of slices 67 number of volumes 2.5 TR Alt+z slices gathered in alternabng order in the z direcbon - prefix name the output dataset; if you want a niei file format, use EPI1.nii

12 Single Subject Get the data from dicom into a format readable by AFNI to3d *.dcm

13 Single Subject Time shie to 0 3dTshie tzero 0 prefix Ts_Run1 EPI1.nii Register to one volume 3dvolreg base Ts_Run1+orig [173] prefix VrTs_Run1 Ts_Run1+orig Smoothing 3dmerge - 1blur_fwhm 4 doall prefix BlVeTs_Run1 VrTs_Run1 Remove highpass and lowpass 3dFourier prefix FrBlVrTs_Run1 lowpass.1 highpass.01 ignore 5 retrend BlVrTs_Run1+orig

14 Create brain- only mask Single Subject 3dAutomask dilate 1 prefix mask_run1 FrBlVrTs_Run1+orig Combine masks from mulbple runs 3dcalc a mask_run1+orig b mask_run2+orig c mask_run3+orig expr or(a+b+c) prefix fullmask Scale each run s mean to 100 (% signal change) 3dTstat prefix mean_run1 FrBlVrTs_Run1+orig 3dcalc a FrBlVrTs_Run1+orig b mean_run1+orig c fullmask+orig expr (a/b * 100)*c prefix ScFrBlVrTs_Run1

15 MoBon CorrecBon Single Subject movecensor.pl creates one file for each run with six values of mobon for each Bme point Concatenate mobon files cat mobon_1 mobon_2 mobon_3 > AllRuns_moBon

16 Single Subject Signal DeconvoluBon 3dDeconvolve \ - input ScBlVrTs_EPI1+orig ScBlVrTs_EPI2+orig ScBlVrTs_EPI3+orig \ - polort 3 \ - num_sbmts 12 \ - sbm_bmes 1 EPI_Studied_R.1D 'TENT(0,15,7)' \ - sbm_label 1 Studied_R \ - sbm_bmes 2 EPI_Studied_K.1D 'TENT(0,15,7)' \ - sbm_label 2 Studied_K \ - sbm_bmes 3 EPI_Studied_N.1D 'TENT(0,15,7)' \ - sbm_label 3 Studied_N \ - sbm_bmes 4 EPI_Novel_R.1D 'TENT(0,15,7)' \ - sbm_label 4 Novel_R \ - sbm_bmes 5 EPI_Novel_K.1D 'TENT(0,15,7)' \ - sbm_label 5 Novel_K \ - sbm_bmes 6 EPI_Novel_N.1D 'TENT(0,15,7)' \ - sbm_label 6 Novel_N \ - sbm_file 7 AllRuns_moBon_EPI'[0]' - sbm_base 7 \ - sbm_file 8 AllRuns_moBon_EPI'[1]' - sbm_base 8 \ - sbm_file 9 AllRuns_moBon_EPI'[2]' - sbm_base 9 \ - sbm_file 10 AllRuns_moBon_EPI'[3]' - sbm_base 10 \ - sbm_file 11 AllRuns_moBon_EPI'[4]' - sbm_base 11 \ - sbm_file 12 AllRuns_moBon_EPI'[5]' - sbm_base 12 \ - iresp 1 iresp_epi_studied_r \ - iresp 2 iresp_epi_studied_k \ - iresp 3 iresp_epi_studied_n \ - iresp 4 iresp_epi_novel_r \ - iresp 5 iresp_epi_novel_k \ - iresp 6 iresp_epi_novel_n \ - fout - tout - nobout - xjpeg Xmat \ - bucket bucket_epi_se1 \ - xsave \ - allzero_ok \ - num_glt 10 \ - gltsym 'SYM: +Studied_R' - glt_label 1 Studied- R \ - gltsym 'SYM: +Studied_K' - glt_label 2 Studied- K \ - gltsym 'SYM: +Studied_N' - glt_label 3 Studied- N \ - gltsym 'SYM: +Novel_R' - glt_label 4 Novel- R \ - gltsym 'SYM: +Novel_K' - glt_label 5 Novel- K \ - gltsym 'SYM: +Novel_N' - glt_label 6 Novel- N \ - gltsym 'SYM: +Novel_R +Novel_K' - glt_label 7 Novel- Inc \ - gltsym 'SYM: +Studied_R - Studied_K' - glt_label 8 Studied_R- K \ - gltsym 'SYM: +Studied_R - Studied_N' - glt_label 9 Studied_R- N \ - gltsym 'SYM: +Studied_K - Studied_N' - glt_label 10 Studied_K- N \ - censor censor_mobon_epi.txt

17 Single Subject ConverBng to Standard Space Manual or automabc ac- pc and talairaching Adwarp coverts funcbonals adwarp - apar ANAT+tlrc - dpar bucket_rt+orig \ - prefix bucket_rt \ - dxyz thr NN - func Bk

18 Group Analysis 3d'est \ - session../analysis_roi_hc+dn \ - prefix 'est_dn_12subj \ - base1 0.0 \ - set2 \ am041609_bucket_dn_ms_postdemons+tlrc'[3]' \ aw043009_bucket_dn_ms_postdemons+tlrc'[3]' \ ec041709_bucket_dn_ms_postdemons+tlrc'[3]' \ es041509_bucket_dn_ms_postdemons+tlrc'[3]' \ gg043009_bucket_dn_ms_postdemons+tlrc'[3]' \ jf042809_bucket_dn_ms_postdemons+tlrc'[3]' \ lk041509_bucket_dn_ms_postdemons+tlrc'[3]' \ mj043009_bucket_dn_ms_postdemons+tlrc'[3]' \ ng041609_bucket_dn_ms_postdemons+tlrc'[3]' \ rb041409_bucket_dn_ms_postdemons+tlrc'[3]' \ sk041709_bucket_dn_ms_postdemons+tlrc'[3]' \ sm042709_bucket_dn_ms_postdemons+tlrc'[3]' \

19 Group Analysis Clustering 3dmerge \ - 1thresh \ - 1clust \ - 1dindex 0 \ - 1Bndex 1 \ - prefix Clust_'est.05_DN_12subj \ 'est_dn_12subj

20 Group Analysis ExtracBng impulse response curves or beta values 3dROIstats - mask Clustorder_'est.05_DN_12subj+tlrc - nzmean \ Brewer_${subject}_bucket+tlrc'[3]' >>Analysis_HC/3dROIstats_HC_12subj.txt