Slicer fMRI introduction

Goal… augment slicer to be a platform for fMRI analysis

strong coupling to anatomical analysis situate fMRI results in anatomy of individual make ROIs for use in fMRI analysis

workflow / human factors easy to use Wendy Plesniak

open source Matlab $$$ buy in from research community distributed development

Functional Magnetic Resonance Imaging & fMRI data Slicer workshop: prototype tools for fMRI and multi-volume applications Functional Magnetic Resonance Imaging & fMRI data Protocols and modeling Analysis and inference Visualization Tools: Ibrowser, fMRIEngine (hands-on demos) Wendy Plesniak, Haiying Liu

Slicer workshop: prototype tools for fMRI and multi-volume applications What is BOLD-fMRI? BOLD-fMRI is a technique for determining which parts of the brain are activated by different types of sensation (sight, sound), activity (tapping a finger), or by performing cognitive tasks. This functional "brain mapping" is achieved by detecting the increased blood flow to the activated areas of the brain during a sequence of MRI scans.

Slicer workshop: prototype tools for fMRI and multi-volume applications How is it being used? Mapping of the brain Informing neurosurgery Understanding of disease/disease processes … Neuromarketing...

Functional Magnetic Resonance Imaging Slicer workshop: prototype tools for fMRI and multi-volume applications Functional Magnetic Resonance Imaging fMRI: volumetric time-series, e.g. acquire one volume every 2 sec for 5 min, to study brain function over time. MRI: single volumetric dataset to study brain structure (One slice in a single volume.) High res: 1mm3 voxels (Same slices from three volumes.) Low res: ~3mm3 voxels

fMRI Setup

 neural activity   blood oxygen   fMRI signal Slicer workshop: prototype tools for fMRI and multi-volume applications fMRI: data Takes temporal volumetric sampling of blood oxygen level in blood flow (BOLD signal) in brain of subject performing a motor or cognitive task, or attending to a sensory stimulus. Experimental protocol: blocked or event-related design Data collected: a time-series of brain volumes (e.g. 150 x 64 x 64 x 32 voxels) Blood Oxygenation Level Dependent (BOLD) signal indirect measure of neural activity  neural activity   blood oxygen   fMRI signal

voxel or ROI time course Slicer workshop: prototype tools for fMRI and multi-volume applications fMRI: simple signal detection overview extract voxel or ROI timecourse… … and compare to protocol Rest (c1) fMRI Signal (% change) voxel or ROI time course t … protocol … c2 Auditory (c2) c1 t time … … ... ~ 11+ min

Slicer workshop: prototype tools for fMRI and multi-volume applications Form statistical inferences: test hypothesis that protocol-related signal is present in the data e.g. using t-test Convert into a p-value Threshold to form a parametric map of activation

fMRI: what to visualize? Slicer workshop: prototype tools for fMRI and multi-volume applications fMRI: what to visualize? Statistical parametric map of activation (superimposed on high resolution anatomical MRI image) 2. Interactive plot of voxel time-course, compared to protocol (visual check)

Other new techniques (future work fMRIEngine): Slicer workshop: prototype tools for fMRI and multi-volume applications Other new techniques (future work fMRIEngine): Techniques based on the mutual information between the protocol and the voxel timecourse: Junmo Kim, John W. Fisher III, Andy Tsai, Cindy Wible, Alan S. Willsky, William M. Wells III. “Incorporating Spatial Priors into an Information Theoretic Approach for fMRI Data Analysis.” MICCAI 2000: 62-71. Andy Tsai, John W. Fisher III, Cindy Wible, William M. Wells III, Junmo Kim, Alan S. Willsky. “Analysis of Functional MRI Data Using Mutual Information.” MICCAI 1999; 473-480. Techniques that incorporate spatial priors: Eric Cosman, John Fisher, Wanmei Ou, and William Wells“Exact MAP Activity Detection in fMRI Using A GLM with an Ising Spatial Prior”. MICCAI 2004. Wanmei Ou : MS thesis