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Retinotopic Mapping Workshop: COSMO 2012 Data Processing Techniques

In this hands-on workshop, participants will work with raw data and toolboxes provided in the 'COSMO' folder, simulating a completed fMRI retinotopy scan. The objective is to process the data to visualize phase-encoded retinotopy on the cortical surface, delineating visual areas via three stages. These stages include examining raw data, computing time series and coherence maps, aligning anatomical references, and creating flattened maps of the occipital cortex. Participants will gain practical skills in data visualization and ROI definition within the context of retinotopic mapping.

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Retinotopic Mapping Workshop: COSMO 2012 Data Processing Techniques

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  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/MrVista

  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

  30. Install segmentation

  31. Install segmentation

  32. Install segmentation

  33. View data in high-resolution anatomy

  34. Rendering on flat map

  35. Flattening…

  36. Flattening…

  37. Flattening…

  38. 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

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