Advancing the Understanding of Phantom Limb Pain through Mathematical Models
Doctoral thesis, 2026
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.
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.
electroencephalography
resting state EEG
neuropathic pain
computational neuroscience
chronic pain
Phantom limb pain
pain
Bayesian inference
pain maps
EEG
active inference
mathematical modeling
Lecture hall EC, Hörsalsvägen 11
Opponent: Professor Christian Büchel, University Medical Center, Hamburg-Eppendorf, Germany
Author
Malin Ramne
Chalmers, Electrical Engineering, Systems and control
A Computational Model of Dorsal Horn Circuits’ Contribution to Neuropathic Pain
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS,;(2025)
Paper in proceeding
A Computational Framework for Understanding the Impact of Prior Experiences on Pain Perception and Neuropathic Pain
PLoS Computational Biology,;Vol. 20(2024)
Journal article
Modeling the Action-Perception Loop and its role in Phantom Limb Pain using Active Inference
Preprint
Unified measures quantifying intensity and similarity of pain and somatosensory percepts
Journal of Neurophysiology,;Vol. 134(2025)p. 292-302
Journal article
Protection from harm is one of the most fundamental functions of the human body. Pain serves this purpose by acting as a warning signal of actual or potential tissue damage. Although pain has evolved as a protective mechanism essential for survival, it can sometimes become detached from this function and persist even after an injury has healed. One of the most striking examples of such dysfunctional pain is phantom limb pain, in which pain is felt in a limb that is no longer present.
Despite being one of the most common and distressing consequences of limb amputation, the mechanisms behind phantom limb pain are not entirely clear. There are many challenges in studying phantom limb pain, such as practical and ethical constraints of performing experiments and variability in clinical characteristics within the amputee population, which makes it difficult to disentangle the factors that may be driving the pain. As a result, it is often challenging to ensure that treatments target the relevant underlying mechanisms, which contributes to low effectiveness of treatments.
Mathematical modeling offers one way to shed light on complex phenomena, particularly in situations where it is difficult to directly study the phenomena of interest. Phantom limb pain ticks both of those boxes, motivating the central theme of this thesis: advancing the understanding of phantom limb pain through mathematical models. By combining different mathematical modeling approaches, the work presented here addresses neurophysiological mechanisms, cognitive processes, and methods for quantifying various aspects of phantom limb pain. Together, these models provide insights that may guide future research and help inform the development and clinical use of treatments aimed at relieving phantom limb pain.
Despite being one of the most common and distressing consequences of limb amputation, the mechanisms behind phantom limb pain are not entirely clear. There are many challenges in studying phantom limb pain, such as practical and ethical constraints of performing experiments and variability in clinical characteristics within the amputee population, which makes it difficult to disentangle the factors that may be driving the pain. As a result, it is often challenging to ensure that treatments target the relevant underlying mechanisms, which contributes to low effectiveness of treatments.
Mathematical modeling offers one way to shed light on complex phenomena, particularly in situations where it is difficult to directly study the phenomena of interest. Phantom limb pain ticks both of those boxes, motivating the central theme of this thesis: advancing the understanding of phantom limb pain through mathematical models. By combining different mathematical modeling approaches, the work presented here addresses neurophysiological mechanisms, cognitive processes, and methods for quantifying various aspects of phantom limb pain. Together, these models provide insights that may guide future research and help inform the development and clinical use of treatments aimed at relieving phantom limb pain.
Subject Categories (SSIF 2025)
Neurosciences
DOI
10.63959/chalmers.dt/5817
ISBN
978-91-8103-360-1
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5817
Publisher
Chalmers
Lecture hall EC, Hörsalsvägen 11
Opponent: Professor Christian Büchel, University Medical Center, Hamburg-Eppendorf, Germany