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NODDI and Tensor-Based Microstructural Indices as Predictors of Functional Connectivity

Fig 3

Probability maps for NODDI-based microstructural indices, respectively.

These probability maps are represented as 68 × 68 square arrays with a value in each cell that represents the probability of each structural connection to be selected during randomised Lasso bootstrap iterations. WICVF, WODI, WISO and Wkappa reflect that the underlying structural connectivity matrices are derived as a weighted average of the intra-cellular volume fraction (ICVF), the orientation distribution index (ODI), the isotropic compartment (ISO) and the kappa parameter, respectively, along the streamlines. On the other hand, δ, θ, α, β and γ represent that the underlying EEG functional connectivity matrices have been derived based on bandpass filtering in five frequency bands 1–4Hz, 4–8Hz, 8–13Hz, 13–30Hz and 30–70Hz, respectively.

Fig 3