  Modeling communication dynamics in the brain is a key challenge in network
neuroscience. We present here a framework that combines two measurements for
any system where different communication processes are taking place on top of a
fixed structural topology: Path Processing Score (PPS) estimates how much the
brain signal has changed or has been transformed between any two brain regions
(source and target); Path Broadcasting Strength (PBS) estimates the propagation
of the signal through edges adjacent to the path being assessed. We use PPS and
PBS to explore communication dynamics in large-scale brain networks. We show
that brain communication dynamics can be divided into three main 'communication
regimes' of information transfer: absent communication (no communication
happening); relay communication (information is being transferred almost
intact); transducted communication (the information is being transformed). We
use PBS to categorize brain regions based on the way they broadcast
information. Subcortical regions are mainly direct broadcasters to multiple
receivers; Temporal and frontal nodes mainly operate as broadcast relay brain
stations; Visual and somato-motor cortices act as multi-channel transducted
broadcasters. This work paves the way towards the field of brain network
information theory by providing a principled methodology to explore
communication dynamics in large-scale brain networks.
