Connectivity between MS lesion density and cortical thickness Keith Worsley Arnaud Charil Jason Lerch Department of Mathematics and Statistics, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University

Connectivity Measured by the correlation between data at pairs of voxels: Voxel 2 Voxel Activation only Voxel 2 Voxel Correlation only

Method 1: ‘Seed’ Friston et al. (19??): Pick one voxel, then find all others that are correlated with it: Problem: how to pick the ‘seed’ voxel?

Method 2: Iterated ‘seed’ Problem: how to find the rest of the connectivity network? Hampson et al., (2002): Find significant correlations, use them as new seeds, iterate.

Method 3: All correlations Problem: how to find isolated parts of the connectivity network? Cao & Worsley (1998): find all correlations (!)

Practical details Find threshold first, using random field theory Keep only correlations > threshold Then keep only local maxima i.e. cor(voxel 1, voxel 2 ) > cor(voxel 1, neighbours of voxel 2 ), > cor(neighbours of voxel 1, voxel 2 ),

MS lesions and cortical thickness (Arnaud et al., 2004) N = 425 mild MS patients Lesion density, smoothed 10mm Cortical thickness, smoothed 20mm Hypothesis: increased lesion density in white matter -> thinner cortex in connected grey matter Find connectivity i.e. find voxels in 3D, nodes in 2D with high cor(lesion density, cortical thickness)

Average lesion volume Average cortical thickness n=425 subjects, correlation =

threshold

What would be really nice: Use DTI fibre tracking data to get a measure of probability of connection between each point in WM and each point on the cortical surface Huge fibre tracking problem: –Seeds at every voxel! –Repeat over subjects? –How to combine subjects? Plot correlation vs. probability of connection - should be a positive relationship …

Dinner: meet in Hilton Coffee Shop, 6 p.m.