Improving TMS-EEG acquisition for clinical populations

Lead supervisor:  Prof. Charlotte Stagg 

Co-supervisor: Prof. Timothy Denison

Commercial partner: Welcony (Magstim Company Ltd and MagstimEGI)

Transcranial Magnetic Stimulation (TMS) has emerged as a promising non-invasive technology for stimulating brain circuits, with significant implications for both neuroscience research and clinical treatments. While TMS has shown efficacy in treating conditions such as major depressive disorder, OCD, and migraine, there remains substantial room for improvement. For instance, in depression treatment, only about one-third of patients achieve remission. This project aims to enhance TMS utility by exploring two complementary areas of technology, aligning closely with the MRC's remit of advancing medical research for improved human health.

First, expanding the stimulation parameter space is likely beneficial. Historically, TMS applications have used frequencies between 1-20Hz, either continuously or in simple repetitive bursts. However, recent innovations like Theta Burst Stimulation have demonstrated the potential for improved outcomes with shorter treatment intervals (Cole et al., Am J Psych, 2021). Furthermore, insights from alternative neuromodulation therapies, such as Deep Brain Stimulation, suggest that higher frequencies may yield additional therapeutic benefits. By developing and using a TMS system with expanded parameter capabilities, including higher rates, extended pattern options, and variations in pulse shaping, we aim to unlock novel therapeutic uses and improve treatment outcomes.

Secondly, to maximise the impact of these capabilities, we need to develop a systematic methodology for exploring this expanded parameter space. Despite the current range of options, only a limited set of parameters are utilised in practice, with their underlying mechanisms not fully understood (Klimjai et al., Annals Phys Rehab Med, 2015). This project will design and implement a reinforcement learning algorithm to efficiently search the stimulation parameter space. By integrating physiological sensors to estimate real-time brain states and applying perturbations in stimulation, we will develop both model-based and "black box" approaches to optimise TMS paradigms.

This project will utilise an enhanced TMS system (Ali et al., IEEE Appl Power Electron, 2023), to develop TMS-EEG capabilities. We will employ established methods for modulating motor brain regions as objective markers for method validation, while simultaneously recording EEG. This approach will ultimately allow us to extend our approach into frontal brain regions crucial for depression treatment.

The project will also include measurements of Long Term Potentiation and Inhibition of selected neuronal networks, using advanced analysis approaches of simultaneous EEG.

The final deliverable will be a proof-of-concept framework for advancing TMS clinical neuroscience research and applications, combined with EEG. This project has the potential to significantly enhance our understanding of TMS mechanisms and improve patient outcomes across a range of neurological and psychiatric disorders, aligning perfectly with the MRC's mission to improve human health through world-class medical research.

This project is the next step in a long-standing collaboration between the university and the commercial partner (Magstim Ltd), which offers multiple mutual benefits. For the academic team, it provides access to cutting-edge TMS technology and industry expertise, facilitating the development of novel stimulation paradigms and analysis techniques. For the commercial partner, this research opens avenues for product innovation and improvement, potentially leading to more effective and versatile TMS systems for both research and clinical applications.

Apply using course: DPhil in Clinical Neurosciences