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 Luke Tait

Luke Tait

Research Associate

School of Psychology

+44 (0)29 208 70365
Cardiff University Brain Research Imaging Centre, Maindy Road, Cardiff, CF24 4HQ


My research interests invole the use of computational techniques such as time series analysis, graph theory, and non-linear dynamical systems to understand brain dynamics during cognitive processes and in neurodegenerative disorders. I joined the Cardiff University Brain Research Imaging Centre in July 2019 as a Research Associate in Dr Jiaxiang Zhang's lab, integrating functional imaging (fMRI, MEG) and computational modelling to understand the neuronal mechanisms underpinning decision making. Prior to this, the focus on my PhD research was using similar techniques to understand alterations to brain dynamics in Alzheimer’s disease. 


  • July 2019 - Present: Research Associate, CUBRIC, Cardiff University
  • September 2015 - June 2019: PhD Student, Living Systems Institute, College of Engineering, Mathematics, and Physical Sciences, University of Exeter
  • 2011 - 2015: MMath Mathematical Physics, University of Liverpool

Honours and awards

  • Travel grant, Guarantors of Brain (2018)

Research Interests

  • Mathematical modelling of neuronal dynamics at a range of spatial scales
  • Dynamical systems and bifurcation theory
  • Neurodegenerative disorders
  • Decision making
  • Analysis of functional neuroimaging data (EEG/MEG/fMRI), including time series analysis and graph theory

Current research

Since July 2019, I have been working at CUBRIC in the Cognition and Computation Brain Lab. This project aims to integrate functional neuroimaging data such as MEG/fMRI with computational models of macro-scale brain dynamics to uncover the neuronal mechanisms underpinning decision making. My background involves using similar computational techniques to study how the electrophysiological dynamics of the brain were altered in people living with Alzheimer's disease and rodent models of dementia pathology.


Tait L, Tamagnini F, Stothart G, Barvas E, Monaldini C, Frusciante R, Volpini M, Guttmann S, Coulthard E, Brown JT, Kazanina N, Goodfellow M (2019). EEG microstate complexity for aiding early diagnosis of Alzheimer's disease. Scientific Reports 10:17627

Tait L, Ozkan A, Szul MJ, Zhang J (2020) Cortical source imaging of resting-state MEG with a high resolution atlas: An evaluation of methods. bioRxiv 2020.01.12.903302

Lopes M, Junges L, Tait L, Terry JR, Abela E, Richardson MP, Goodfellow M (2020). Computational modelling in source space from scalp EEG to inform presurgical evaluation of epilepsy surgery. Clinical Neurophysiology 131(1):225-234

Tait L (2019) Multi-Scale Mathematical Modelling of Brain Networks in Alzheimer's Disease. Doctoral Thesis, University of Exeter.

Tait L, Stothart G, Coulthard E, Brown JT, Kazanina N, Goodfellow M (2019). Network Substrates of Cognitive Impairment in Alzheimer's Disease. Clinical Neurophysiology 130(9):1581-1595

Tait L, Wedgwood K, Tsaneva-Atanasova K, Brown JT, Goodfellow M (2018). Control of clustered action potential firing in a mathematical model of entorhinal cortex stellate cells. Journal of Theoretical Biology 449:23-34

Stothart G, Petkov G, Kazanina N, Goodfellow M, Tait L, Brown JT (2016) Graph-theoretical measures provide translational markers of large-scale brain network disruption in human dementia patients and animal models of dementia. International Journal of Psychophysiology 108:71