Investigating electrophysiological brain network dynamics and mechanisms underlying attentional processes during learning

研究学习过程中注意力过程的电生理脑网络动力学和机制

• 批准号: 2735194
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2735194
• 关键词: Investigating; electrophysiological; brain; network; dynamics

In both adults and children, the efficiency of learning is heavily dependent on cognitive control and executive function. In my project, I will aim to study the underlying brain networks and mechanisms involved in these processes. Using newly developed machine learning models of network dynamics, I will investigate network connectivity and coherence patterns and relate them to behavioural indices of adult learning using resting state and task electroencephalography (EEG) data. Later, I will collect further electrophysiological datasets, employing new behavioural paradigms and data collection methods (such as higher density EEG or OPM-MEG) and extend computational methods for modelling brain network dynamics. Additionally, I will use collected data to build on my previous work investigating relationships between memory replay and resting-state brain networks.- Understanding the rules of life- Transformative technologies- Bioscience for an integrated understanding of health"

在成人和儿童中，学习效率在很大程度上取决于认知控制和执行功能。在我的项目中，我将旨在研究这些过程中涉及的潜在大脑网络和机制。使用新开发的网络动态机器学习模型，我将研究网络连接性和相干模式，并将它们与使用静止状态和任务脑电图（EEG）数据的成人学习的行为指数相关联。稍后，我将采用新的电生理数据集，采用新的行为范式和数据收集方法（例如更高的密度EEG或OPM-MEG），并扩展用于建模大脑网络动态的计算方法。此外，我将使用收集的数据来建立我以前的工作调查记忆重播和静止状态大脑网络之间关系的工作。