Malin Ramne,

Phantom limb pain is a condition where pain is perceived as arising from a missing limb. Despite being one of the most prevalent and distressing consequences of limb amputation, theories regarding its underlying mechanisms remain disputed. Research on phantom limb pain faces several challenges: pain is a subjective experience that is difficult to measure and quantify, the array of available experimental methods is limited by ethical constraints, and the heterogeneity within the amputee population further complicates efforts to empirically disentangle the factors driving pain.

Mathematical modeling offers a way to shed light on complex topics such as phantom limb pain. This approach is particularly valuable when direct empirical observations are difficult to obtain, since mathematical models can provide insight to how systems behave, enable predictions of scenarios that have not yet occurred and forecast possible consequences of perturbations to a system. While mathematical models alone cannot definitively determine the mechanisms underlying phantom limb pain, they can reveal patterns in complex data, generate testable hypotheses, and guide future research directions.

This thesis aims to apply mathematical models to bridge gaps in the current understanding of phantom limb pain. The included models span neurophysiological mechanisms, cognitive processes, quantification of pain perception, and statistical modeling of neural activity. Together, these models offer insights that can support future research and inform the development and use of interventions aimed at relieving phantom limb pain.