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5. Further methodological development of analysis of MEG/EEG data, particularly in relation to Bayesian methods for multimodal integration (Henson et al., 2011).

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Potential PhD topics

Note that the list below is not exhaustive; i.e, if you have a topic in mind that overlaps with my general interests, please do email to discuss!

1. Exploration of the effect of schema on new learning (Greve et al., 2018), and their neural correlates (van Kesteren et al., 2012).

2. Behavioural, fMRI and/or M/EEG and/or computational tests of our "Predictive Interactive Multiple Memory Systems" (PIMMS) framework (Henson & Gagnepain, 2010), particularly the role of prediction error in driving memory encoding (Greve et al., 2017).

3. Further development of neural models of simple repetition effects (e.g., priming) as measured with fMRI and MEG/EEG (Alink et al, 2018).

4. Behavioural, fMRI and/or M/EEG experiments on the effect of healthy ageing on priming, familiarity and recollection, as part of our large, collaborative Cambridge Centre for Ageing and Neuroscience (Cam-CAN), particularly multivariate methods for integration of behavioural and neuroimaging data (Henson et al., 2016).

5. Investigation of MEG and simple memory paradigms for early detection of dementia, particularly using machine learning classification methods (Hughes et al, 2018).

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