| EPSRC Reference: |
EP/T027703/1 |
| Title: |
Seizures and the Brain: The Role of Perturbed Dynamic Networks |
| Principal Investigator: |
Terry, Professor JR |
| Other Investigators: |
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| Project Partners: |
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| Department: |
School of Mathematics |
| Organisation: |
University of Birmingham |
| Scheme: |
EPSRC Fellowship |
| Starts: |
01 February 2021 |
Ends: |
31 January 2026 |
Value (£): |
1,911,878
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| EPSRC Research Topic Classifications: |
| Non-linear Systems Mathematics |
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Summary on Grant Application Form |
Accurate diagnosis, prognosis and management of epilepsy is a significant unmet medical need. Epilepsy is a serious brain condition whereby susceptible individuals have recurrent seizures. It affects almost 1% of the UK population at some point in their lives. Every year 125,000 people attend first seizure clinics across the UK. Of these, 40,000 eventually receive a confirmed diagnosis of epilepsy, typically following an average delay of a year (Joint Epilepsy Council, September 2011). Whilst two-thirds of these confirmed cases can ultimately be controlled by anti-epilepsy drugs (AED), approximately 50% remain uncontrolled a year after commencing treatment, with no clear indicators of choice of AED or dose. Treatment response is currently a case of "watchful waiting" to see whether further seizures occur and adjusting choice of medication and dose accordingly. For those who do not respond they continue to have seizures, apparently at random, which leads to a significant reduction in quality and quantity of life. Every year over 1,000 people die in the UK as a direct consequence of epilepsy.
I propose an exciting programme of research in which mathematical models and computer algorithms will be developed to improve our understanding of how seizures occur. These models will describe how different regions of the brain interact with each other and how internal and external stimuli can influence these interactions. The interplay between neural activity within brain regions and the connections between regions critically determines whether seizures can occur and how frequently they are likely to happen. Having developed this fundamental understanding, computer algorithms can be developed to inform key parameters of these models directly from clinical recordings collected from people with epilepsy. This makes the models personalised and therefore suitable to address key questions for people with (suspected) epilepsy:
- is the diagnosis accurate?
- are the drugs being prescribed effective?
- will exposure to stress make seizures more likely?
- can I know when my seizures are most likely to happen?
- will surgery stop my seizures happening?
I will work with a software engineer and people with epilepsy to translate this understanding into a prototype tools to address these questions. For example, developing a tool that can aid a multi-disciplinary clinical team in determining where in the brain seizures originate from and using this information to better plan for surgery. Alternatively, a smart-phone based app that receives electrical brain recordings from a wireless headset to provide a forecast of seizure risk. Co-designing and developing these prototypes with people with lived experience and clinicians will maximise the likelihood of their leading to impact of the fundamental research.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.bham.ac.uk |