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AFNI. Robert W Cox, PhD Biophysics Research Institute M edical C ollege of W isconsin Milwaukee WI. AFNI A nalysis of F unctional N euro I mages. Genesis (mid-1994): “Need” for MCW neuroscientists to transform FMRI activation maps to Talairach-Tournoux coordinates Initial goals:
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AFNI Robert W Cox, PhD Biophysics Research Institute Medical College of Wisconsin Milwaukee WI
AFNIAnalysis of Functional NeuroImages • Genesis (mid-1994): “Need” for MCW neuroscientists to transform FMRI activation maps to Talairach-Tournoux coordinates • Initial goals: • T-T transformation via manual AC-PC marking • Interactive browsing of image data in 5 “dimensions”: 3 spatial + imaging run + subject • Basic unit of data: 3D AFNIdataset • Big array of numbers plus geometrical information • Developed for Unix+X11+Motif (including Linux)
An FMRI Analysis Environment • Philosophy: • Encompass all needed classes of data and computations • Extensibility + Openness + Scalability: Anticipating what will be needed to solve problems that have not yet been posed • Interactive vs. Batch operations: Stay close to data or view from a distance • Components: • Data Objects: Arrays of 3D arrays + auxiliary data • Data Viewers: Numbers, Graphs, Slices, Volumes • Data Processors: Plugins, Plugouts, Batch Programs
Steps in Processing with AFNI • Image assembly into datasets [to3d] • Can be done at the scanner with the realtime plugin • Image registration [3dvolreg] • Functional activation calculations [AFNI, 3dfim] • Linear and nonlinear time series regression [3dDeconvolve, 3dNLfim] • Transformation to Talairach coordinates [AFNI] • Alternative: selection of anatomical ROIs [AFNI] • Integration of results from multiple subjects [many] • Visualization of & thinking about results [AFNI & you]
Interactive Analysis with AFNI Control Panel Displaying EP images from time series Graphing voxel time series data
Looking at the Results Multislice layouts FIM overlaid on SPGR, in Talairach coords
Sample Rendering: Coronal slice viewed from side; function not cut out < 1 CPU s per frame (Pentium II 400 MHz)
Integration of Results • Done with batch programs (usually in scripts) • 3dmerge: edit and combine 3D datasets • 3dttest: voxel-by-voxel: 1- and 2-sample t-tests • 3dANOVA: • Voxel-by-voxel: 1-, 2-, and 3-way layouts • Fixed and random effects • Other voxel-by-voxel statistics are available • 3dpc: principal components (space time) • ROI analyses are a labor-intensive alternative
Extending AFNI Package • Batch programs • Output new 3D datasets for viewing with AFNI • Plugins — searched for and loaded at startup • Add interactive capabilities to AFNI program • “Fill in the blanks” menu for input from users • 40 page manual and some samples included • Plugouts — attach themselves in middle of run • External programs that communicate with AFNIwith shared memory or TCP/IP sockets
Whole Brain Realtime FMRI • Assembly of images into AFNI datasets during acquisition • Can use AFNI tools to visualize during scanning • Realtime 3D registration • Graph of estimated motion parameters • Recursive signal processing to update activation map with each new data volume • Color overlay changes with each TR
The Goal: Interactive Functional Brain Mapping • See functional map as scanning proceeds 1 minute 2 minutes 3 minutes