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Dr Luke Tait
(he/him)
MMath (Liverpool), PhD (Exeter)
Post-Doctoral Research Associate
- Available for postgraduate supervision
Overview
My research aims to understand how the dynamics of the electrophysiological activity of the brain are association with cognitive health and disorders such as Alzheimer's disease, Epilepsy, and risk of psychosis/Schizophrenia. With a background in mathematical physics and computational neuroscience, I am particularly interested in developing new methods to interrogate and model the activity of the brain measured by MEG, EEG, and MRI.
I am currently a post-doctoral Research Associate on the CONVERGE project. This project aims to understand the association between brain connectivity/dynamics and genetic risks of Schizophrenia. I am responsible for collecting data such as brain imaging (MEG, MRI), and cognitive, motor, and psychiatric assessments from children with copy number variants associated with increased risk of Schizophrenia in adulthood. I am also involved in analysing this data, and integrating human/cell line/rodent data across multiple scales in dynamic causal models.
Publication
2024
- Tait, L. et al. 2024. Estimating the likelihood of epilepsy from clinically noncontributory electroencephalograms using computational analysis: A retrospective, multisite case–control study. Epilepsia 65(8), pp. 2459-2469. (10.1111/epi.18024)
- Maiarù, M. et al. 2024. Substance P-botulinum mediates long-term silencing of pain pathways that can be re-instated with a second injection of the construct in mice. The Journal of Pain 25(6), article number: 104466. (10.1016/j.jpain.2024.01.331)
- Kopcanová, M. et al. 2024. Resting-state EEG signatures of Alzheimer's disease are driven by periodic but not aperiodic changes. Neurobiology of Disease 190, article number: 106380. (10.1016/j.nbd.2023.106380)
2022
- Karahan, E. et al. 2022. The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure. Communications Biology 5, article number: 1007. (10.1038/s42003-022-03974-w)
- Tait, L. and Zhang, J. 2022. MEG cortical microstates: spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses. NeuroImage 251, article number: 119006. (10.1016/j.neuroimage.2022.119006)
2021
- Tait, L., Ozkan, A., Szul, M. J. and Zhang, J. 2021. A systematic evaluation of source reconstruction of resting MEG of the human brain with a new high-resolution atlas: performance, precision, and parcellation. Human Brain Mapping 42(14), pp. 4685-4707. (10.1002/hbm.25578)
- Tait, L., Lopes, M. A., Stothart, G., Baker, J., Kazanina, N., Zhang, J. and Goodfellow, M. 2021. A large-scale brain network mechanism for increased seizure propensity in Alzheimer's disease. PLoS Computational Biology 17(8), article number: e1009252. (10.1371/journal.pcbi.1009252)
2020
- Lopes, M. A., Junges, L., Tait, L., Terry, J. R., Abela, E., Richardson, M. P. and Goodfellow, M. 2020. Computational modelling in source space from scalp EEG to inform presurgical evaluation of epilepsy. Clinical Neurophysiology 131(1), pp. 225-234. (10.1016/j.clinph.2019.10.027)
- Tait, L. et al. 2020. EEG microstate complexity for aiding early diagnosis of Alzheimer’s disease. Scientific Reports 10, article number: 17627. (10.1038/s41598-020-74790-7)
2019
- Tait, L., Stothart, G., Coulthard, E., Brown, J. T., Kazanina, N. and Goodfellow, M. 2019. Network substrates of cognitive impairment in Alzheimer's Disease. Clinical Neurophysiology 130(9), pp. 1581-1595. (10.1016/j.clinph.2019.05.027)
2018
- Tait, L., Wedgwood, K., Tsaneva-Atanasova, K., Brown, J. T. and Goodfellow, M. 2018. Control of clustered action potential firing in a mathematical model of entorhinal cortex stellate cells. Journal of Theoretical Biology 449, pp. 23-34. (https://doi.org/10.1016/j.jtbi.2018.04.013)
2016
- Stothart, G., Petkov, G., Kazanina, N., Goodfellow, M., Tait, L. and 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, pp. 71-71. (10.1016/j.ijpsycho.2016.07.232)
Articles
- Tait, L. et al. 2024. Estimating the likelihood of epilepsy from clinically noncontributory electroencephalograms using computational analysis: A retrospective, multisite case–control study. Epilepsia 65(8), pp. 2459-2469. (10.1111/epi.18024)
- Maiarù, M. et al. 2024. Substance P-botulinum mediates long-term silencing of pain pathways that can be re-instated with a second injection of the construct in mice. The Journal of Pain 25(6), article number: 104466. (10.1016/j.jpain.2024.01.331)
- Kopcanová, M. et al. 2024. Resting-state EEG signatures of Alzheimer's disease are driven by periodic but not aperiodic changes. Neurobiology of Disease 190, article number: 106380. (10.1016/j.nbd.2023.106380)
- Karahan, E. et al. 2022. The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure. Communications Biology 5, article number: 1007. (10.1038/s42003-022-03974-w)
- Tait, L. and Zhang, J. 2022. MEG cortical microstates: spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses. NeuroImage 251, article number: 119006. (10.1016/j.neuroimage.2022.119006)
- Tait, L., Ozkan, A., Szul, M. J. and Zhang, J. 2021. A systematic evaluation of source reconstruction of resting MEG of the human brain with a new high-resolution atlas: performance, precision, and parcellation. Human Brain Mapping 42(14), pp. 4685-4707. (10.1002/hbm.25578)
- Tait, L., Lopes, M. A., Stothart, G., Baker, J., Kazanina, N., Zhang, J. and Goodfellow, M. 2021. A large-scale brain network mechanism for increased seizure propensity in Alzheimer's disease. PLoS Computational Biology 17(8), article number: e1009252. (10.1371/journal.pcbi.1009252)
- Lopes, M. A., Junges, L., Tait, L., Terry, J. R., Abela, E., Richardson, M. P. and Goodfellow, M. 2020. Computational modelling in source space from scalp EEG to inform presurgical evaluation of epilepsy. Clinical Neurophysiology 131(1), pp. 225-234. (10.1016/j.clinph.2019.10.027)
- Tait, L. et al. 2020. EEG microstate complexity for aiding early diagnosis of Alzheimer’s disease. Scientific Reports 10, article number: 17627. (10.1038/s41598-020-74790-7)
- Tait, L., Stothart, G., Coulthard, E., Brown, J. T., Kazanina, N. and Goodfellow, M. 2019. Network substrates of cognitive impairment in Alzheimer's Disease. Clinical Neurophysiology 130(9), pp. 1581-1595. (10.1016/j.clinph.2019.05.027)
- Tait, L., Wedgwood, K., Tsaneva-Atanasova, K., Brown, J. T. and Goodfellow, M. 2018. Control of clustered action potential firing in a mathematical model of entorhinal cortex stellate cells. Journal of Theoretical Biology 449, pp. 23-34. (https://doi.org/10.1016/j.jtbi.2018.04.013)
- Stothart, G., Petkov, G., Kazanina, N., Goodfellow, M., Tait, L. and 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, pp. 71-71. (10.1016/j.ijpsycho.2016.07.232)
Biography
Post-doctoral
2022-Present: Research Associate, CUBRIC, Cardiff University
CONVERGE: Understanding altered brain dynamics in children with genetic risk of schizophrenia
2021-2022: Research Fellow, Centre for Systems Modelling & Quantitative Biomedicine, University of Birmingham
Predictive modelling of epilepsy based on statistical features of resting EEG signals
2019-2021: Research Associate, CUBRIC, Cardiff University
Project working on dynamic networks/microstates in rest and cognitive task
Post-graduate
2015-2019: PhD Mathematics, Living Systems Institute, University of Exeter.
Thesis title: Multiscale Mathematical Modelling of Brain Networks in Alzheimer's Disease
Undergraduate
2011-2015: MMath (1st Class Hons) Mathematical Physics, University of Liverpool
Contact Details
+44 29206 88756
Cardiff University Brain Research Imaging Centre, Maindy Road, Cardiff, CF24 4HQ