1. fMRI Activation in a Visual- Perception Task: Network of Areas Detected Using the General Linear Model and Independent Components Analysis Calhoun, Adali, McGinty, Pekar, Watson, & Pearlson (2001). Geneviève Desmarais - November 5, 2002

2. MVPT-R Motor-free Visual Perception Task (Revised) Probes: –spatial relationships –visual discrimination –figure-ground perception –visual closure –etc...

3. Basic Paradigm

4. Participants 2 females, 8 males mean age 27 screened with physical and neurological exam no Axis 1 disorders (clinical) good visual acuity without correction

5. Imaging Parameters Anatomic Scan T-1 weighted –TR = 500 msec –TE = 30 msec –slice thickness = 5 mm –gap = 0.5 mm 18 slices through entire brain Functional Scan single-shot echo-planar TR = 1 s TE = 39 msec 5 min = 300 scans –10 dummy scans at beginning

6. Data Analysis - Preprocessing (fudging?) Corrected for timing differences Motion corrected Spatially smoothed Normalized to Talairach space

7. Data Analysis General Linear Model 1. Fixed-effect group analysis stimulus function –times when figures were presented to the participants Filters: –High-pass –Low pass trends verified in each individual data set 2. Random effect analysis on individual data

8. Data Analysis Independent Component Analysis Decomposes data into signals that are maximally independent –individual preprocessed data arranged into 2D matrix of space and time 20 components estimated, grouped into: –motor, visual, cerebellar, frontoparietal, orbitofrontal, and basal ganglia

9. Data Analysis Independent Component Analysis Components normalized Components within each area averaged across participants Each group image converted to Z scores –threshold = 2.5

10. Results 85% average correct response –range 67 - 100 (…) Incorrect and correct responses grouped together

11. Activation GLM analysis * visual areas * visual association * frontal eye fields * dorsolateral prefrontal * supplemental motor * no positive parietal * extensive cerebellar

12. Activation ICA analysis * colours = diff component * mostly same regions * superior parietal and prefrontal in same as FEF

13. Discussion Expected activation in: –large network of areas involved in visual and spatial perception –all primary visual areas and many visual association areas

14. Event-averaged time courses

15. Parietal regions Decreasing signal following figural presentation attributed to –eye movement –working memory –both eye movement and attention

16. No Primary Motor Region? ICA finds it… Why not GLM? Because participants were responding with both hands… –GLM = averaged over trials for each subject, and is only active some of the times –ICA = looks for independent activation, and only one hand will be active at a time

17. Cerebellum Surprised at the extensive involvement of the cerebellum maybe because button box was vertically configured

18. Conclusions MVPT-R battery activates a large network of areas… Both methods selected similar but not identical regions GLM: more selective and sensitive –especially primary visual and cerebellar ICA: detected motor components not detected via SPM