Dr Luke Tait

Dr Luke Tait

Institute of Metabolism and Systems Research
Research Fellow

Contact details

Address
College of Medical and Dental Sciences
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Luke Tait is a Research Fellow at the Centre for Systems Modelling and Quantitative Biomedicine. His research involves using quantitative methods (dynamical systems, graph theory, time-series analysis, machine learning) and functional brain data (EEG, MEG) to study brain dynamics in neurological disorders such as epilepsy and Alzheimer’s disease. The aims of this research are to uncover neural mechanisms of brain disease and to develop methodologies to aid with diagnosis of disease.

Qualifications

  • PhD in Mathematics, 2019
  • MMath in Mathematical Physics, 2015

Biography

Dr Luke Tait graduated from the University of Liverpool with a Master of Mathematics in Mathematical Physics in 2015. He subsequently did his PhD in Mathematics based at the Living Systems Institute in the University of Exeter, where he focused on multi-scale mathematical modelling and analysis of brain networks in Alzheimer’s disease and other dementia. After finishing his PhD in 2019, Luke moved to the Cardiff University Brain Research Imaging Centre (CUBRIC) as a Research Associate in the Cognition and Computational Brain Lab, where he focused on computational methods to uncover dynamic brain states at the cortical level from MEG data.

Since February 2021, Luke has been working as a Research Fellow at the University of Birmingham Centre for Systems Modelling and Quantitative Biomedicine.

Research

  • Dynamical systems theory, including multi-scale modelling of brain electrophysiological dynamics
  • EEG/MEG
  • Machine learning for predicting risk scores for disease
  • Brain microstate analysis
  • Functional connectivity and graph theory

Publications

Tait L, Lopes MA, Stothart G, Baker J, Kazanina N, Zhang J, Goodfellow M (2021) A Large-Scale Brain Network Mechanism for Increased Seizure Propensity in Alzheimer’s Disease. [preprint] bioRxiv 2021.01.19.427236

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. [preprint] bioRxiv 2020.01.12.903302

Tait L, Tamagnini F, Stothart G, Barvas E, Monaldini C, Frusciante R, Volpini M, Guttmann S, Coulthard E, Brown JT, Kazanina N, Goodfellow M (2020) EEG microstate complexity for aiding early diagnosis of Alzheimer’s disease. Scientific Reports 10(1):17627

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, 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 J (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

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