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Dr Luke Tait
(he/him)
MMath (Liverpool), PhD (Exeter)
- Available for postgraduate supervision
Teams and roles for Luke Tait
Lecturer
Mathematics
Overview
My research aims to use techniques from Mathematics and Physics to understand how the activity of the brain is associated with cognitive health, genetics, and disorders such as Alzheimer's disease, epilepsy, and 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. This includes analysis techniques, clustering of data into dynamic microstates, optimising statistical pipelines for multidimensional neuroimaging data, and fitting parameters of neural mass models to such data to relate dynamics with mechanisms.
Publication
2026
- Námešná, A. et al. 2026. Synaptic and circuit mechanisms shaping neurodevelopmental and psychiatric outcomes associated with 16p11.2 copy number variation. Genes 17 (6) 716. (10.3390/genes17060716)
2025
- Walsh, C. et al., 2025. Transient cortical beta-frequency oscillations associated with contextual novelty in high density mouse EEG. Scientific Reports 15 (1) 2897. (10.1038/s41598-025-86008-9)
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) 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 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 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 119006. (10.1016/j.neuroimage.2022.119006)
2021
- Tait, L. et al. 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. et al. 2021. A large-scale brain network mechanism for increased seizure propensity in Alzheimer's disease. PLoS Computational Biology 17 (8) e1009252. (10.1371/journal.pcbi.1009252)
2020
- Lopes, M. A. et al., 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 17627. (10.1038/s41598-020-74790-7)
2019
- Tait, L. et al. 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. et al. 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. et al., 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
- Námešná, A. et al. 2026. Synaptic and circuit mechanisms shaping neurodevelopmental and psychiatric outcomes associated with 16p11.2 copy number variation. Genes 17 (6) 716. (10.3390/genes17060716)
- Walsh, C. et al., 2025. Transient cortical beta-frequency oscillations associated with contextual novelty in high density mouse EEG. Scientific Reports 15 (1) 2897. (10.1038/s41598-025-86008-9)
- 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) 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 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 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 119006. (10.1016/j.neuroimage.2022.119006)
- Tait, L. et al. 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. et al. 2021. A large-scale brain network mechanism for increased seizure propensity in Alzheimer's disease. PLoS Computational Biology 17 (8) e1009252. (10.1371/journal.pcbi.1009252)
- Lopes, M. A. et al., 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 17627. (10.1038/s41598-020-74790-7)
- Tait, L. et al. 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. et al. 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. et al., 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
Academic
2026-Present: Lecturer in Statistics, School of Mathematics, Cardiff University
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
[email protected]
+44 29206 88756
Abacws, Room 4.23, Senghennydd Road, Cathays, Cardiff, CF24 4AG
Cardiff University Brain Research Imaging Centre, Room 1.031, Maindy Road, Cardiff, CF24 4HQ
+44 29206 88756
Abacws, Room 4.23, Senghennydd Road, Cathays, Cardiff, CF24 4AG
Cardiff University Brain Research Imaging Centre, Room 1.031, Maindy Road, Cardiff, CF24 4HQ