1. Slicer fMRI introduction

2. Goal…
augment slicer to be a platform for fMRI analysis

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

4. workflow / human factors
easy to use
Wendy Plesniak

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

6. 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

7. 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.

8. 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...

9. 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

10. fMRI Setup

11.  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

12. 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

13. 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

14. 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)

15. 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:
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;
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