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Andrew Quinn

BSc MSc PhD


Post-Doctoral Scientist

I am a postdoctoral fellow at the Oxford Centre for Human Brain Activity (OHBA) and the Brain and Cognition Lab supervised by Kia Nobre and Mark Woolrich, and I am funded by NIHR Oxford HealthBiomedical Research Centre

My research involves developing analysis approaches to characterise oscillatory patterns in electrophysiological data. Such oscillations have a rich and rapidly changing structure which is tightly linked to synchronisation and co-ordination in underlying neuronal populations. I am interested in exploring how features such as connectivity and waveform shape reflect behaviour and processing, whilst overcoming some limitations of our standard analysis approaches in this area. Towards this aim, I use the Empirical Mode Decomposition, Hidden Markov Models and Multivariate Autoregression to explore Magnetoencephalography data.

Currently I am working on a range of clinical projects that are looking to use these methods to explore neuronal change during neurodegeneration. Oscillatory signals are strongly coupled to neuronal activity and, as such, have the potential to provide a sensitive, non-invasive metric of neuronal dysfunction, both across individuals and in single individuals over time.

This work relates to questions from both basic neuroscience (How do brain regions communicate? What can we estimate about the brain from non-invasive elelctrophysiology?) and translational neuroscience (How can we non-invasively measure neurodegeneration? How can we track its progress over time?).

Prior to joining OHBA and the B&C lab, I was in the University of York Psychology Department and York NeuroImaging Centre. I studied for a BSc (Hons) in Psychology and an MSc in Cognitive Neuroscience and completed a PhD in with Professor Gary Green entitled "Neural Dynamics In Brain Networks During The Resting State And Visual Word Recognition".

I have a strong interest in developing robust methods in time-series analysis for Neuroscience and ensuring that the engineering and software underlying these analyses are of a high quality. I try to establish clear communication of analysis methods research, particularly by ensuring that more complicated methods are approachable to those looking to apply them for scientific or clinical applications.

Recent publications

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