Computational studies in network neuroscience build models of communication dynamics in the connectome that help us understand the structure-function relationships of the brain. In these models, the dynamics of cortical signal transmission in brain networks are approximated with simple propagation strategies such as random walks and shortest path routing. Furthermore, the signal transmission dynamics in brain networks can be associated with the switching architectures of engineered communication systems (e.g., message switching and packet switching). However, it has been unclear how propagation strategies and switching architectures are related in models of brain network communication. Here, we investigate the effects of the difference between packet switching and message switching (i.e., whether signals are packetized or not) on the transmission completion time of propagation strategies when simulating signal propagation in mammalian brain networks. The results show that packetization in the connectome with hubs increases the time of the random walk strategy and does not change that of the shortest path strategy, but decreases that of more plausible strategies for brain networks that balance between communication speed and information requirements. This finding suggests an advantage of packet-switched communication in the connectome and provides new insights into modeling the communication dynamics in brain networks.

Communication dynamics in brain networks have been modeled with various approximations to signaling in the connectome. These approximations differ in their assumptions about propagation strategies (random walks, shortest path routing) and switching architectures (message switching, packet switching); however, their relationships in brain network communication models have been unclear so far. Here, we link them by investigating how the difference between packet and message switching (whether signals are packetized or not) affects the transmission completion time of propagation strategies in communication simulations in the connectome. We find that packetization selectively reduces the time of physiologically plausible strategies for the connectome that balance communication speed and information requirements. This study sheds light on the utility of packet switching for modeling efficient communication in brain networks.

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Competing Interests: The authors declare no conflict of interests.

Handling Editor: Alex Fornito

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