Dr. Al Benson and I run the Leeds Systems Physiology Lab, part of the Cardiovascular Sciences Research group in the Faculty of Biological Sciences, University of Leeds. Our research focuses on dissecting physiological mechanisms in both health and disease, primarily related to cardiac function and exercise physiology. These pages describe the basics of the underlying biomedical concepts to place the context for our research.

Cardiovascular disease is a leading cause of morbidity and mortality in the developed world, yet current treatment strategies are sub-optimal. Cardiac dysfunction can be electrical (arrhythmia – where the regular rhythm of the heart is interrupted) or mechanical (where the development of mechanical contractile force is inhibited); the two are also closely linked to each-other, as the electrical excitation is the local trigger for mechanical contraction. Due to the substantial socio-economic costs of cardiovascular disease, there is a pressing need to develop greater understanding of the mechanisms underlying abnormal rhythm and failed contraction in the heart in order to devise more effective diagnostic, prevention and treatment approaches.

The details of the mechanisms of the transition to- and perpetuation of- arrhythmia are complex and depend on function from the smallest (single proteins) right up to the largest (whole-heart) scales, making them challenging to understand and manage with pure experimental approaches. The mechanisms of the coupling between the electrical and mechanical function of the heart are also subject to similar multi-scale considerations, in particular depending on complex structures from the sub-cellular to the whole-tissue levels.

Computational modelling - simulation of the electrical and mechanical activity of the heart - has become an increasingly powerful tool in the wider effort to understand, diagnose and treat cardiac disorders. In particular, computational modelling allows true multi-scale investigation, linking behaviour at the sub-cellular scale to organ scale phenomena. My research interests lie at the interface of physics and biomedical science, in the application of mathematical and physics techniques currently used for theoretical investigation to develop advanced multi-scale computational frameworks for simulation of cardiac activity.

My research interests are in the development and application of novel multi-scale joint experimental-simulation frameworks to understand the mechanisms of cardiac electrophysiology, intracellular calcium handling, and excitation-contraction coupling. The aim is to improve understanding of cardiac dysfunction and ultimately lead to better diagnosis and treatment strategies. Primarily, my focus is on the multi-scale interactions of components from the sub-micron to the whole-heart scale, and the role of these interactions in the pathologies associated with heart failure, Atrial Fibrillation, and ageing, regarding arrhythmia and excitation-contraction coupling. Finally, in order to assist in the development of improved diagnostic strategies, I also have an interest in non-invasive cardiac mapping.

Current funded projects

A computational model of fibrosis and the cardiac conduction system: the next generation of virtual heart models for research and teaching

Source: NC3Rs PhD Studentship
Total value: £124,159
Tenure: 2024-2028

Description: In collaboration with the Universities of Manchester and Auckland, we will combine pre-clinical and clinical images of the human atria with our approach for modelling fibrosis and spontaneous calcium release. The resulting model, which will include realistic image-based structure of the cardiac conduction system, should provide a valuable platform for future exploratory and mechanistic studies to address the mechanisms of arrhyhmia in patients.

Remodelling of structure-function relationships underlying cardiac dysfunction in ageing

Source: MRC Career Development Award
Total value: £1,504,340
Tenure: October 2021 - October 2026

Description: This project brings together many of the different areas of research in our group. It will use a combination of simulations and experiments to characterise the nature of ageing-associated remodelling of the structures of cardiac cells and tissues, and mechanistically link these remodelled structures to emergent dysfunction.

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Research Areas

Understanding Atrial Fibrillation

Atrial fibrillation is the most common cardiac arrhythmia, leading to reduced cardiac output and increased incidence of stroke and sudden cardiac death. Working with collaborators from the University of Glasgow and King’s College London, computational models of atrial electrophysiology from cell-to-organ are developed and applied to understand how the condition occurs, the details of its behaviour, and provide insight into how it may be more effectively treated.
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Cardiac Excitation-contraction Coupling

The cycling of intracellular calcium ions is responsible for the coupling between the electrical and mechanical (contractile) function of cardiac cells. Detailed computational models of the structure-function relationships underlying this coupling at multiple scales are developed in order to isolate and dissect the roles and importance of different cellular components of this function.
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Arrhythmia Mechanisms and Calcium Dynamics

One consequence of the intracellular calcium handling system is the potential to exhibit complex, non-linear behaviour which can influence the electrical activity and lead to arrhythmia events. A major challenge is that these abnormal phenomena are inherently dependent on the structure-function relationships in single cells, whereas arrhythmia occurs only at the tissue scales. Novel approaches are developed to integrate models across these scales and study the role of calcium handling in whole-heart arrhythmia.
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Non-invasive Cardiac Mapping

The standard approach to measure the electrical activity of the heart non-invasively is the electro-cardiogram (ECG). The aim is provide as much information as possible on the electrical excitation patterns on the heart from measurements taken from contact or non-contact sensors on the skin. However, there are significant challenges in accurately mapping cardiac excitation from this limited information. Led by Erick Perez Alday, we combine simulation and experimental investigations in an attempt to improve the diagnostic ability of bedside tools.
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