OPTIMISED CHARACTERISATION OF DEEP BRAIN OSCILLATORY DYNAMICS IN HEALTH & DISEASE, USING NOVEL ACQUISITION/ANALYSIS OF SIMULTANEOUS MEG AND EEG

健康中深部大脑振荡动力学的优化表征

• 批准号: 1799542
• 金额: --
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1799542
• 关键词: OPTIMISED; CHARACTERISATION; DEEP; BRAIN; OSCILLATORY

The aim of this project is to better localise sources of oscillatory activity within the brain by developing and applying novel methods to combine concurrent MEG and EEG (MEEG). In particular, the combination of EEG with MEG will allow more sensitive characterisation of deeper brain structures such as the amygdala and medial temporal lobe - structures that are difficult to measure from with MEG alone. In this project I first will develop methods based on work from my previous Masters course in Physics at Nottingham. I will then demonstrate the application of these optimised methods in cognitive paradigms such as MEEG localisation of emotional responses in the amygdala to, for example, face stimuli. The methods will also be used to better characterise deep activity, such as hippocampal theta oscillations in spatial memory paradigms, in mesial temporal lobe epilepsy patients.

该项目的目的是通过开发和应用新的方法将联合收割机同时结合MEG和EEG（MEEG）来更好地定位大脑内的振荡活动源。特别是，EEG与MEG的组合将允许更敏感地表征更深的大脑结构，例如杏仁核和内侧颞叶-难以单独使用MEG测量的结构。在这个项目中，我首先将发展的方法，从我以前的工作，在物理学硕士课程在诺丁汉。然后，我将展示这些优化的方法在认知范式中的应用，如MEEG本地化杏仁核的情绪反应，例如，面对刺激。该方法还将用于更好地研究内侧颞叶癫痫患者的深层活动，例如空间记忆范式中的海马theta振荡。