Global excitability and network structure in the human brain

We utilize a model of Wilson-Cowan oscillators to investigate structure-function relationships in the human brain by means of simulations of the spontaneous dynamics of brain networks generated through human connectome data. This allows us to establish relationships between the global excitability of such networks and global structural network quantities for connectomes of two different sizes for a number of individual subjects. We compare the qualitative behavior of such correlations between biological networks and shuffled networks, the latter generated by shuffling the pairwise connectivities of the former while preserving their distribution. Our results point towards a remarkable propensity of the brain to achieve a trade-off between low network wiring cost and strong functionality, and highlight the unique capacity of brain network topologies to exhibit a strong transition from an inactive state to a globally excited one.

Automated summary

We use a model of Wilson-Cowan oscillators to investigate the relationship between brain structure and function in the human brain. Through simulations of brain networks generated from connectome data, we establish connections between the global excitability of these networks and global structural network quantities. Comparisons between biological networks and shuffled networks reveal the brain's ability to achieve a balance between low wiring cost and strong functionality, and its capacity for a strong transition from an inactive state to a globally excited one.