Abstract
Communication and dynamic routing play important roles in the human brain to facilitate flexibility in task solving and thought processes. Here, we present a new network perturbation methodology and a corresponding analysis method to investigate and demonstrate the dynamic switching between different excitable pathways in the network. The methodology probes for dynamic changes in network communication pathways based on the relative phase offsets between two weak external oscillatory drivers. To investigate the feasibility and the properties of this method we use a computational modeling approach with delay-coupled neural mass models. In a model of the human connectome we show that network pathways have characteristic timescales and thus specific preferences for the phase lag between the regions they connect. For the analysis of dynamic switches of communication pathways we define the pathway-synchronization-facilitation index (PSF), which measures for a given pair of network nodes how their interaction is modulated by specific phase offsets. Our simulation results indicate that the PSF decreases with increasing shortest path length between the node-pair and increases with the number of different pathways by which the two nodes are connected. To further analyze the contribution of different interaction pathways to the communication between two network nodes, we define the pathway-activation index (PA). Our results show that most pairs of nodes in the connectome have interaction pathways that can be dynamically activated and that 60.1% of node pairs can switch their communication from one pathway to another depending on the phase offsets between the two nodes.
Significance A big challenge in elucidating information processing in the brain is to understand the neural mechanisms that dynamically organize the communication between different brain regions in a flexible and task-dependent manner. In this theoretical study, we present an approach to investigate the routing and gating of information flow along different pathways from one region to another. We show that stimulation of the brain at two sites with different frequencies and oscillatory phases can reveal the underlying effective connectivity. This yields new insights into the underlying processes that govern dynamic switches in the communication pathways between remote sites of the brain.
Footnotes
↵2 holger.finger{at}uni-osnabrueck.de