Extensive work on adults and non-human primates tells us that neuronal networks are highly flexible and dynamic. But in developmental cognitive neuroscience we typically use sluggish or static methods to study these networks, for example functional magnetic resonance imaging. These large-scale brain networks operate through the spontaneous synchronisation of neural oscillations across spatially distinct neuronal populations, and part of our work uses electro- (EEG) and magnetoencephalography (MEG) to study these network dynamics in childhood.

In doing so we developed and applied multiple different MEG analysis pipelines to: i) examine phase-phase coupling between fronto-parietal and visual cortex as participants orient spatial attention; ii) identify sub-second fluctuations in control networks and their impact on sensory processing and performance in childhood; iii) show that individual differences in the spatial distribution of these dynamic networks, even at rest, is a significant predictor of children’s working memory capacity, and iv) demonstrate that these networks can be significantly altered with training.

In some cases we have used these methods explore causal mechanisms in developmental disorders. For example, we have shown that large-scale network dynamics are altered in individuals with specific genetic mutations associated with cognitive difficulties.

If you would like to find out more then check out some of the papers appearing in the slider, or get in touch via the website.


Key collaborators:

Professor Usha Goswami (University of Cambridge)

Professor Kia Nobre (University of Oxford)

Dr Kate Baker (University of Cambridge)

Professor Mark Woolrich (University of Oxford)

Current Funders

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