Although death due to lethal cardiac arrhythmias is the leading cause of mortality in Western Society, many of the fundamental mechanisms underlying their onset, maintenance and termination, still remain poorly understood. In recent years, experimental techniques such as optical mapping have provided useful high-resolution recordings of cardiac electrical dynamics during complex arrhythmias and defibrillation episodes, which have been combined with detailed computer simulations to further our understanding of these phenomena. However, mechanistic enquiry is severely restricted as the optical mapping technique suffers from a number of distortion effects which compromise the fidelity of the experimental measurements, presenting difficulties in the comparison of experimental data with computational simulations. This Thesis presents a thorough investigation into the distortion effects encountered in optical mapping experiments, guided by the development of a coherent series of computational models. The models presented successfully characterise the specific mechanisms of fluorescent signal distortion due to photon scattering. Photon transport in cardiac tissue is modelled using both continuous (reaction-diffusion) and discrete stochastic (Monte Carlo) approaches to simulate the effects of photon scattering within the myocardium upon the recorded fluorescent signal, which include differing levels of detail and associated computational complexity. Specifically, these models are used to investigate the important role played by the complex ventricular structural anatomy, as well as the specifics of the experimental set-up itself. In addition, a tightly coupled electromechanical model of a contracting cardiac fibre is developed which provides an important first-step towards the development of a model to quantitatively assess the distortion observed when recording from a freely contracting cardiac preparation. Simulation of these distortion effects using the models allows discrimination to be made between those parts of the experimental signal which are due to underlying tissue electrophysiology and those due to artifact, facilitating a more accurate interpretation of experimentally-obtained data. The models presented succeed in two main respects. Firstly, they provide a ‘post-processing’ tool which can be added on to computational simulations of electrical activation, allowing for a more accurate and faithful comparison between simulations and experiments, helping to validate predictions made by electrical models. Secondly, they provide a higher degree of mechanistic insight into the fundemental ways in which optical signals are distorted, showing how this distortion can be maximised or controlled. The understanding and quantification of the fundemental mechanisms of optical mapping signal distortion, provided by this Thesis, therefore fulfils an important role in the study of arrhythmia mechanisms.