Information and communication theoretical modeling and analysis of the gut-brain axis

The gut-brain axis (GBA) represents one of the most sophisticated and crucial communication networks in the human body. However, a quantitative understanding of its signaling mechanisms has remained elusive, as conventional approaches fail to capture the inherently stochastic, nonlinear, and multi-scale nature of intra-body communication. The most promising paradigm to address these challenges is Molecular Communication (MC). Understanding biological signaling from an information and communication theoretical perspective provides insight into the fundamental dynamics of these systems. Therefore, this thesis applies MC principles to the GBA to establish a comprehensive and quantitative communication framework. Building on this objective, the thesis constructs a multi-scale understanding of the GBA through a deliberate progression from a foundational single channel to a complete, bidirectional communication network. The research first develops a channel model for the propagation of a single microbial metabolite (p-cresol), deriving its impulse response and linking gut dysbiosis to a neurological outcome. It then advances the analysis to a complete end-to-end model of molecular-to-neural communication, modeling the short-chain fatty acid (SCFA)-driven vagal nerve pathway and quantifying its information-theoretic performance. Finally, the work culminates in a novel system-level model of the bidirectional communication within GBA that incorporates closed-loop feedback between the hypothalamic-pituitary-adrenal (HPA) axis, immune system, and gut barrier. This framework is used to analyze the system's transition into a pathological state and quantify its corresponding loss of channel capacity. Collectively, the developed communication framework provides the tools to unravel the fundamental signaling mechanisms within the GBA, allowing for a detailed analysis of how signaling disruptions contribute to disease progression. This in-depth, quantitative understanding creates a foundation for a new generation of medical technologies, providing a roadmap for ICT-inspired diagnostic tools and therapeutic strategies to detect and repair communication failures. Furthermore, it lays the essential theoretical groundwork for future Internet of Bio-Nano Things (IoBNT) applications to restore healthy information flow within the body.