Global and local nature of cortical slow waves.

Explaining the macroscopic activity of a neuronal population from its microscopic properties poses a great challenge, not just because of the many local agents that play a role, but due to the impact of long-range connections from other brain regions. We used a computational model to explore how local and global components of a network shape the slow wave activity (SWA). A sensitivity analysis allowed us to explore how local properties and long-range connections shaped the SWA of a population and its neighbors. We show that while manipulations in the synaptic excitatory/inhibitory balance can create local changes, cellular components that modulate the excitability or adaptation led to changes in neighboring populations too. We also show in silico and in vivo how heterogeneities in excitability can determine the directionality of traveling Up states. We expect these results to motivate research exploring and comparing cortical circuits through the analysis of their SWA.