1. Retinotopic mapping workshop COSMO 2012

2. Starting materials In the folder ‘COSMO’ you will find raw data and toolboxes – as if you had just finished an fMRI retino mapping scan Your mission is to process these data to the stage where you can see phase-encoded retinotopy on the cortical surface. How many visual areas can you delineate?

3. Stages I Examine raw (aligned) data Average time series Compute coherence / phase maps Visualize data in the ‘Inplane’ view Plot (and understand) time series from different parts of the brain

4. Stages II Compute alignment between ‘Inplanes’ and a high resolution reference anatomy Project data into this ‘Gray’ view Find the calcarine sulcus. Plot times series along this anatomical feature Render the surface of the brain as a 3D mesh Project retinotopy data to this surface. Inflate the surface

5. Stages III Create flattened representations of the left and right occipital cortex Project data to ‘Flat maps’ Identify the borders of visual areas. Create and label ROIs around these areas Project these ROIs back to th Gray view Render them.

6. Help! http://white.stanford.edu/Wiki.php http://white.stanford.edu/newlm/index.php/Mr Vista

7. Step 1 – The inplane view Anatomical view

8. Step 1 – The inplane view Mean fMRI BOLD amplitude map

9. Step 1 – The inplane view Computing the correlation analysis

10. Step 1 – The inplane view First view of phase-encoded data

11. Step 1 – The inplane view Multiple slices through the same dataset

12. Step 1 – The inplane view Defining an ROI – use CTRL-R or the ‘ROI’ menu

13. Step 1 – The inplane view Accessing the plotting tools

14. Step 1 – The inplane view A sample fMRI time course

15. Step 1 – The inplane view Average of a single cycle

16. Step 1 – The inplane view FFT of a mean time series

17. Step 1 – The inplane view FFT of a mean time series after data averaging

18. Step 1 – The inplane view Plot single cycle time courses in a set of ROIs down the calcarine sulcus

19. Step 1 – The inplane view Averaging time series data across scans

20. Alignment Purpose: Compute an affine transformation between the ‘Inplane’ anatomical data and a high-resolution anatomical dataset. Segmentation, mesh generation has been performed on the highres anatomy already If all functional datasets are transformed into this space then data from different expt on the same subject can be compared

21. Alignment http://white.stanford.edu/newlm/index.php/RxAlign

22. Alignment http://white.stanford.edu/newlm/index.php/RxAlign

23. Alignment http://white.stanford.edu/newlm/index.php/RxAlign

24. Alignment http://white.stanford.edu/newlm/index.php/RxAlign

25. Alignment http://white.stanford.edu/newlm/index.php/RxAlign

26. Alignment http://white.stanford.edu/newlm/index.php/RxAlign

27. Alignment http://white.stanford.edu/newlm/index.php/RxAlign

28. Alignment http://white.stanford.edu/newlm/index.php/RxAlign

29. Install segmentation

33. View data in high-resolution anatomy

34. Rendering on flat map

35. Flattening…

39. This is the end… Or in fact the beginning How many visual areas can you find? Define ROIs around some of them (use the polygon ROI tool) Plot some statistics (co vs phase?)

40. More Transform ROIs back into the Gray view. Build and render a 3D mesh in this view (you will have to find and run mrmMeshSrv.exe first) Look at data on the inflated mesh Extract voxel-level data from an ROI