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

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"