Seizures and the Brain: The Role of Perturbed Dynamic Networks

癫痫的准确诊断、预后和管理是一个重要的未满足的医疗需求。癫痫是一种严重的脑部疾病，易感个体会反复发作。它影响了近1%的英国人在他们生命中的某个阶段。在英国，每年有125000人到首次癫痫发作诊所就诊。其中4万人最终确诊为癫痫，通常平均延迟一年（联合癫痫理事会，2011年9月）。虽然这些确诊病例中有三分之二可以通过抗癫痫药物（AED）最终得到控制，但大约50%在开始治疗一年后仍然无法控制，没有明确的指标表明选择AED或剂量。治疗反应目前是一种“观察等待”的情况，看看是否会发生进一步的癫痫发作，并相应地调整药物和剂量的选择。对于那些没有反应的人，他们继续癫痫发作，显然是随机的，这导致生活质量和数量的显著下降。在英国，每年有超过1000人直接死于癫痫。我提出了一个令人兴奋的研究计划，其中将开发数学模型和计算机算法，以提高我们对癫痫发作的理解。这些模型将描述大脑的不同区域如何相互作用，以及内部和外部刺激如何影响这些相互作用。大脑区域内的神经活动和区域之间的联系之间的相互作用，关键地决定了癫痫发作是否会发生以及发作的频率。有了这一基本认识，计算机算法就可以开发出来，直接从癫痫患者的临床记录中获取这些模型的关键参数。这使得模型个性化，因此适合解决（疑似）癫痫患者的关键问题：诊断准确吗？-所开的药物是否有效？-压力会使癫痫发作的可能性增加吗？-我能知道什么时候癫痫最容易发作吗？手术能阻止癫痫发作吗？我将与一名软件工程师和癫痫患者合作，将这种理解转化为解决这些问题的原型工具。例如，开发一种工具，可以帮助多学科临床团队确定大脑癫痫发作的起源，并利用这些信息更好地计划手术。另外，一个基于智能手机的应用程序可以接收来自无线耳机的脑电记录，以提供癫痫发作风险的预测。与有生活经验的人和临床医生共同设计和开发这些原型，将最大限度地提高它们对基础研究产生影响的可能性。

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.