1. Wang, Y., Schroeder, G.M., Sinha, N., Taylor, P.N., 2019, Personalised network modelling in epilepsy.
  2. Schroeder, G.M., Diehl, B., Chowdhury, F.A., Duncan, J.S., de Tisi, J., Trevelyan, A.J., Forsyth, R., Jackson, A. Taylor, P.N., Wang, Y., 2019, Slow changes in seizure pathways in individual patients with focal epilepsy.
  3. Sinha, N., Wang, Y., Silva, N., Miserocchi, A., McEvoy, A.W., de Tisi, J., Vos, S.B., Winston, G.P., Duncan, J.S., Taylor, P.N., 2019, Node abnormality predicts seizure outcome and relates to long-term relapse after epilepsy surgery.
  4. Ramaraju, S., Reichert, S., Wang, Y., Forsyth, R.†, Taylor, P.N.†, 2019, Carbogen inhalation during Non-Convulsive Status Epilepticus: A quantitative analysis of EEG recordings
  5. Wang, Y., Sinha, N., Schroeder, G.M., Ramaraju, S., McEvoy, A.W., Miserocchi, A., de Tisi, J., Chowdhury, F.A., Diehl, B., Duncan, J.S., Taylor P.N., 2019, Interictal intracranial EEG for predicting surgical success: the importance of space and time

Peer-reviewed journal publications

  1. Wang, Y., Necus, J., Peraza-Rodriguez, L., Taylor, P.N., Mota, B., 2019, Universality in human cortical folding across lobes of individual brains. Communications Biology, 2:191
  2. Necus, J., Sinha, N., Smith, F.E., Thelwall, P.E., Flowers, C.J., Taylor, P.N., Blamire, A.M., Cousins, D.A., Wang, Y., 2019, White matter microstructural properties in bipolar disorder and its relationship to the spatial distribution of lithium in the brain. Journal of Affective Disorders 253:224-231
  3. Sinha, N., Wang, Y., Dauwels, J., Kaiser, M., Thesen, T., Forsyth, R., Taylor, P.N., 2019, Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy. NeuroImage: Clinical 21:101655
  4. França, L.G.S., Miranda, J.G.V., Leite, M., Sharma, N.K., Walker, M.C., Lemieux, L. and Wang, Y., 2018. Fractal and Multifractal Properties of Electrographic Recordings of Human Brain Activity: Toward Its Use as a Signal Feature for Machine Learning in Clinical Applications. Frontiers in physiology, 9.
  5. Taylor, P.N., Sinha, N., Wang, Y., Vos, S.B., de Tisi, J., Miserocchi, A., McEvoy, A.W., Winston, G.P.†, Duncan, J.S.†, 2018, The impact of epilepsy surgery on the structural connectome and its relation to outcome, NeuroImage: Clinical 18:202-214
  6. Wang, Y., Trevelyan, A.T., Valentin, A., Alarcon, G., Taylor, P.N., Kaiser, M., 2017, Mechanisms underlying different onset patterns of focal seizures, PLoS Computational Biology e1005475
  7. Baier, G., Taylor, P.N., Wang, Y., 2017, Understanding epileptiform after-discharges as rhythmic oscillatory transients, Frontiers in Computational Neuroscience, 11:25
  8. Sinha, N., Dauwels, J., Kaiser, M., Cash, S.S., Westover, M.B., Wang, Y., Taylor, P.N., 2017, Predicting neurosurgical outcomes in focal epilepsy patients using computational modelling, Brain, 140 (2), 319-332.
  9. Taylor, P.N., Wang, Y., Kaiser, M., 2017, Within brain area tractography suggests local modularity using high resolution connectomics, Scientific Reports 39859
  10. Wang, Y., Necus, J., Kaiser, M. and Mota, B., 2016. Universality in human cortical folding in health and disease. Proceedings of the National Academy of Sciences, 113(45), pp.12820-12825.
  11. Taylor, P.N., Forsyth, R., 2016, Heterogeneity of trans-callosal structural connectivity and effects on resting state subnetwork integrity may underlie wanted and unwanted effects of therapeutic corpus callostomy, NeuroImage: Clinical 12:341-347
  12. Hutchings, F., Han, C.E., Keller, S.S., Weber, B., Taylor, P.N.†, Kaiser, M.†, 2015. Predicting surgery targets in temporal lobe epilepsy through structural connectome based simulations, PloS Computational Biology 11 (12), e1004642 Press coverage in New Scientist here
  13. Basu, A., Taylor, P.N., Lowther, E., Forsyth, E.O., Blamire, A., Forsyth, R., 2015. Structural connectivity in a paediatric case of anarchic hand syndrome, BMC Neurology 15:1:234
  14. Taylor, P.N., Thomas J., Sinha N., Dauwels J., Kaiser M., Thesen T., Ruths J., 2015, Optimal control based seizure abatement using patient derived connectivity. Frontiers in Neuroscience, 9:1-10
  15. Taylor, P.N.*, Han, C.E.*, Schoene-Bake, J.C., Weber, B., Kaiser, M., 2015, Structural connectivity changes in temporal lobe epilepsy: Spatial features contribute more than topological measures, NeuroImage: Clinical 8:322-328
  16. Papasavvas, C.A., Wang, Y., Trevelyan, A.J. and Kaiser, M., 2015. Gain control through divisive inhibition prevents abrupt transition to chaos in a neural mass model. Physical Review E, 92(3), p.032723.
  17. Taylor, P.N.*, Wang, Y*., Goodfellow, M., Dauwels, J., Moeller, F., Stephani, U., Baier, G., 2014, A computational study of stimulus driven epileptic seizure abatement, PloS One 9(12),e114316
  18. Taylor, P.N., Kaiser, M., Dauwels., 2014 Structural connectivity based whole brain modelling in epilepsy, Journal of Neuroscience Methods 236, 51-57
  19. Wang, Y., Goodfellow., Taylor, P.N., Baier, G., 2014 Dynamic mechanisms of neocortical focal seizure onset, PloS Computational Biology 10 (8), e1003787
  20. Taylor, P.N., Goodfellow, M., Wang, Y., Baier G., 2013, Towards a large scale model of epileptic spike-wave discharges, Biological Cybernetics 107 (1), 83-94
  21. Baier, G., Goodfellow, M., Taylor, P.N., Wang, Y., Garry, D.J., 2012, The importance of modelling epileptic seizure dynamics as spatio-temporal patterns, Frontiers in Physiology 3, 281
  22. Goodfellow, M., Taylor, P.N., Wang, Y., Garry, D.J., Baier, G., 2012. Modelling the role of tissue heterogeneity in epileptic rhythms, European Journal of Neuroscience 36(2), 2178-2187
  23. Wang, Y., Goodfellow, M., Taylor, P.N., Baier, G., 2012, Phase space approach for modelling of epileptic dynamics, Physical Review E 85(6), 061918
  24. Geenen, S., Taylor, P.N., Snoep J.L., Wilson, I.J. Kenna G., Westerhoff H.V., 2012. Systems biology tools for toxicology, Archives of Toxicology 86(8), 1251-1271
  25. Taylor, P.N., Baier, G., 2011. A spatially extended model for macroscopic spike-wave discharges, Journal of Computational Neuroscience 3(3), 679-6841

Full length peer reviewed conference proceedings

  1. Sinha, N., Dauwels, J., Wang, Y., Cash, S.S., Taylor, P.N., 2014, An in silico approach for pre-surgical evaluation of an epileptic cortex, Proceedings IEEE EMBC 4884-4887
  2. Sinha, N., Taylor, P.N., Dauwels, J., Ruths, J., 2014, Development of optimal stimuli in a heterogeneous model of epileptic spike-wave oscillations, Proceedings IEEE SMC 3160-3165
  3. Schwartz, J.M., Taylor, P.N., 2014 In silico prediction of elementary mode fluxes, 2014, Proceedings IWBBIO
  4. Ruths, J., Taylor, P. N., Dauwels, J. 2014. Optimal Control of an Epileptic Neural Population Model, Proceedings IFAC, 47(3) 3116-3121
  5. Taylor, P. N., Baier, G., Cash, S. S., Dauwels, J., Slotine J.J., Wang, Y., 2013, A model of stimulus induced epileptic spike-wave discharges, Proceedings IEEE SCCI 53-59

Book chapters

  1. Wang Y., Goodfellow M., Taylor P.N., Garry D.J., Baier G., 2014, Computational modelling of micro-seizures and focal seizure onset; Recent Advances in Predicting and Preventing Epileptic Seizures. World Scientific ISBN: 978-981-4525-34-3
  2. Wang Y., Hutchings F.E., Kaiser M., 2015, Computational Modelling of Stimulation in Brain Diseases. Progress In Brain Research.
  3. Baier G., Rosch R., Taylor P.N., Wang Y., 2018, Design Principle for a Population-Based Model of Epileptic Dynamics. In: Müller S., Plath P., Radons G., Fuchs A. (eds) Complexity and Synergetics. Springer, Cham, ISBN: 978-3-319-64334-2