This page contains descriptions and examples to build hub susceptibility models. For additional details on hub susceptibility models, please see our manuscript entitled Network-based atrophy modeling in the common epilepsies: a worldwide ENIGMA study.
Normative structural and functional connectomes hold valuable information for relating macroscopic brain network organization to patterns of disease-related atrophy. Using the HCP connectivity data, we can first compute weighted (optimal for unthresholded connectivity matrices) degree centrality to identify structural and functional hub regions (i.e., brain regions with many connections). This is done by simply computing the sum of all weighted cortico-cortical connections for every region. Higher degree centrality denotes increased hubness.
Prerequisites ↪ Load cortico-cortical connectivity matrices
The HCP connectivity data can also be used to identify structural and functional subcortico-cortical hub regions. As above, we simply compute the sum of all weighted subcortico-cortical connections for every subcortical area. Once again, higher degree centrality denotes increased hubness.
No ventricles, no problem 👌🏼
Because we do not have connectivity values for the ventricles, do make sure to set
the “ventricles” flag to
False when displaying the findings on the subcortical surfaces.
Prerequisites ↪ Load subcortico-cortical connectivity matrices
Now that we have established the spatial distribution of hubs in the brain, we can then assess whether these hub regions are selectively vulnerable to syndrome-specific atrophy patterns. For simplicity, in the following example, we will spatially correlate degree centrality measures to measures of cortical and subcortical atrophy (where lower values indicate greater atrophy relative to controls).
Prerequisites ↪ Load summary statistics or example data ↪ Re-order subcortical data (mega only) ↪ Z-score data (mega only) ↪ Load cortico-cortical and subcortico-cortical connectivity matrices ↪ Compute cortical-cortical and subcortico-cortical degree centrality
Plot hub-atrophy correlations¶
Now that we have done all the necessary analyses, we can finally display our correlations. Here, a negative correlation indicates that greater atrophy correlates with the spatial distribution of hub regions (greater degree centrality).
Prerequisites The script below can be used to show relationships between any two variables, as for example: degree centrality vs. atrophy ↪ Load summary statistics or example data ↪ Re-order subcortical data (mega only) ↪ Z-score data (mega only) ↪ Load cortico-cortical and subcortico-cortical connectivity matrices ↪ Compute cortical-cortical and subcortico-cortical degree centrality ↪ Assess statistical significance via spin permutation tests