Emergence of Metastable State Dynamics in Interconnected Cortical Networks with Propagation Delays

Abstract

The importance of the large number of thin-diameter and unmyelinated axons that connect different cortical areas is unknown. The pronounced propagation delays in these axons may prevent synchronization of cortical networks and therefore hinder efficient information integration and processing. Yet, such global information integration across cortical areas is vital for higher cognitive function. We hypothesized that delays in communication between cortical areas can disrupt synchronization and therefore enhance the set of activity trajectories and computations interconnected networks can perform. To evaluate this hypothesis, we studied the effect of long-range cortical projections with propagation delays in interconnected large-scale cortical networks that exhibited spontaneous rhythmic activity. Long-range connections with delays caused the emergence of metastable, spatio-temporally distinct activity states between which the networks spontaneously transitioned. Interestingly, the observed activity patterns correspond to macroscopic network dynamics such as globally synchronized activity, propagating wave fronts, and spiral waves that have been previously observed in neurophysiological recordings from humans and animal models. Transient perturbations with simulated transcranial alternating current stimulation (tACS) confirmed the multistability of the interconnected networks by switching the networks between these metastable states. Our model thus proposes that slower long-range connections enrich the landscape of activity states and represent a parsimonious mechanism for the emergence of multistability in cortical networks. These results further provide a mechanistic link between the known deficits in connectivity and cortical state dynamics in neuropsychiatric illnesses such as schizophrenia and autism, as well as suggest non-invasive brain stimulation as an effective treatment for these illnesses. The brain mediates behavior by orchestrating the activity of billions of neurons that communicate with each other through electric impulses. The transmission of these action potentials is surprisingly slow for a large fraction of these connections. Given the importance of precise timing of neuronal activity, the function of these slow connections has remained a puzzle. We here used computer simulations to investigate how slow connection speeds alter the overall activity patterns of two brain networks. We found that these connections enable the interconnected networks to generate distinct activity patterns such as different types of waves of electric activity. Our results therefore suggest that the slow transmission of electric impulses in the brain is not a “design flaw” but rather plays an important role in enabling the brain to generate a richer set of activity patterns. The ability of the brain to switch between different activity states is crucial to normal cognition, and abnormalities in switching behavior are associated with cognitive symptoms in psychiatric disorders such as schizophrenia and autism. It is therefore promising that we were able to control transitions between different activity states with non-invasive brain stimulation in our simulations, suggesting a novel approach to the treatment of these illnesses.