• Haemodynamics
• Cerebral blood flow and metabolism
• Cerebral autoregulation 
• Computational biomechanics

I have published 3 books; over 100 journal papers in international peer-reviewed journals (with > 100 different co-authors); 1 book chapter; and >25 international peer-reviewed conference papers. A list of my published and accepted journal papers in the last ten years is given below. I have >2800 citations and an hindex of 30 (Google Scholar, 1.ix.21).

Books

Payne, S.J. Cerebral Blood Flow and Metabolism. World Scientific, 2017.

Payne, S.J. Cerebral Autoregulation. Springer, 2016. [Chinese edition to appear in 2022]

Chappell, M.A. and Payne, S.J. Physiology for Engineers. Springer, 2016 (1st edition), 2020 (2nd edition).

In press

[116] Miller, C., Padmos, R., van der Kolk, M., Jozsa, T.I., Samuels, N., Xue, Y., Payne, S.J. and Hoekstra, A.G. In Silico Trials for Treatment of Acute Ischemic Stroke: Design and Implementation. Computers in Biology and Medicine, in press.

[115] Xue, Y., El-Bouri, W.K., Jozsa, T.I. and Payne, S.J. Modelling the effects of cerebral microthrombi on tissue oxygenation and cell death. Journal of Biomechanics, in press.

[114] Tong, Z., Catherall, M.G.F. and Payne S.J. A multiscale model of cerebral autoregulation. Medical Engineering and Physics, in press.

[113] Graff, B.J., Payne, S.J. and El-Bouri, W.K. The ageing brain: Investigating the role of age in changes to the human cerebral microvasculature with an in-silico model. Frontiers in Aging Neuroscience, in press.

[112] Raghu, A. et al. Pallido-putaminal connectivity predicts outcomes of deep brain stimulation for cervical dystonia. Brain, in press.

[111] Jozsa, T.I., Padmos, R.M., El-Bouri, W.K., Hoekstra, A. and Payne, S.J. On the sensitivity analysis of porous finite element models for cerebral perfusion estimation. Annals of Biomedical Engineering, in press.

[110] Tran, M.C. et al. Simulation-based optimisation to quantify heterogeneity of specific ventilation and perfusion in the lung by the Inspired Sinewave Test. Scientific Reports, in press.

[109] Simpson, D.M., Payne S.J. , and Panerai, R.B. Methods for assessing cerebral autoregulation. Journal of Cerebral Blood Flow and Metabolism, in press.

2021

[108] Milanovic, S., Shaw, K., Hall, C. and Payne, S.J. Investigating the role of pericytes in cerebral autoregulation: a modelling study. Physiological Measurement, 42(5): 054003, 2021.

[107] Raghu, A., Parker, T., Divanbeighi Zand, A.P., Payne S.J. , Andersson, J., Stein, J.F., Aziz, T.Z. and Green, A.L. Tractography patterns of pedunculopontine nucleus deep brain stimulation. Journal of Neural Transmission, 128: 659–670, 2021.

[106] El-Bouri, W.K., MacGowan, A., Jozsa, T.I., Gounis, M. and Payne, S.J. Modelling the impact of clot fragmentation on the microcirculation after thrombectomy. PLOS Computational Biology, 17(3):e1008515, 2021.

[105] Padmos, R., Jozsa, T.I., El-Bouri, W.K., Konduri, P.R., Payne, S.J. and Hoekstra, A.G. Coupling 1-D arterial blood flow to 3-D tissue perfusion models for in silico trials of acute ischaemic stroke. Interface Focus, 11(1), 2021.

[104] Jozsa, T.I., Padmos, T.I., Samuels, N., El-Bouri, W.K., Hoekstra, A.G. and Payne, S.J. A porous circulation model of the human brain for in silico clinical trials in ischaemic stroke. Interface Focus, 11(1), 2021.

2020

[103] Tran, M., Crockett, D., Forment, F., Phan, P., Hedenstierna, G., Larsson, A., Payne, S.J. and Farmery, A. Lung heterogeneity and deadspace volume in Acute Respiratory Distress Syndrome animals using the Inspired Sinewave Test. Physiological Measurement, 41(11): 115009, 2020.

[102] van Oostenbrugge, T.J., Heidkamp, J., Voigt, P., Moche, M., Weir, P., Mariappan, P., Flanagan, R., Pollari, M., Payne S.J. , Ellerweg, R., Kolesnik, M., Jenniskens, S.F.M. and Futterer, J.J. Validation of a webbased and user friendly planning tool for percutaneous cryoablation of renal tumors. CardioVascular and Interventional Radiology, 43: 1661-1670, 2020.

[101] Lee, Y.-K., Rothwell, P., Payne, S.J. and Webb, A. Reliability, Reproducibility and Validity of Dynamic Cerebral Autoregulation in a Large Cohort with Transient Ischaemic Attack or Minor Stroke. Physiological Measurement, 41(9): 095002, 2020.

[100] Beishon, L., Minhas, J.S., Nogueira, R., Castro, P., Budgeon, C., Aries, M., Payne S.J. , Robinson, T.G. and Panerai, R.B. INFOMATAS multi-center systematic review and meta-analysis individual patient data of dynamic cerebral autoregulation in ischemic stroke. International Journal of Stroke, 15: 807-812, 2020.

[99] Elting, J.W., ... Payne S.J. , ... and Claassen J.A.H.R. Assessment of dynamic cerebral autoregulation in humans: is reproducibility dependent on blood pressure variability? PLOS One, 15: e0227651, 2020.

[98] Payne, S.J. Searching for the stimulus controlling brain oxygen supply. Journal of Physiology, 598: 617-218, 2020.

2019

[97] Murallidharan, J.S. and Payne, S.J. Thrombus growth modelling and stenosis prediction in the cerebral microvasculature. Journal of Theoretical Biology, 478: 1-13, 2019.

[96] Sanders, M., ... Payne S.J. , ... and Claassen, J.A.H.R. Dynamic cerebral autoregulation reproducibility is affected by physiological variability. Frontiers in Physiology, 10: 865, 2019.

[95] Gkontra, P., El-Bouri, W.K., Norton, K.-A., Santos, A., Popel, A., Payne, S.J. and Arroyo, A. Dynamic changes in microvascular flow conductivity and perfusion post myocardial infarction by image-based modelling. JAHA, 8(7): e011058, 2019.

2018

[94] Sanders, M., ... Payne S.J. , ... and Elting, J.W. Reproducibility of cerebral auto regulation parameters: a multi-centre, multi-method study. Physiological Measurement, 39(12): 125002, 2018.

[93] Payne, S.J. Identifying the myogenic and metabolic components of cerebral autoregulation. Medical Engineering and Physics, 58: 23-30, 2018.

[92] Payne, S.J. and El-Bouri, W.K. Modelling dynamic changes in blood flow and volume in the cerebral vasculature. NeuroImage, 176: 124-137, 2018.

[91] Payne, S.J. and Lucas, C. Oxygen delivery from the cerebral microvasculature to tissue is governed by a single time constant of approximately 6 seconds. Microcirculation, 25: e12428, 2018.

[90] El-Bouri, W.K. and Payne, S.J. Investigating the effects of a penetrating vessel occlusion with a multiscale microvasculature model of the human cerebral cortex. NeuroImage, 172: 94-106, 2018.

[89] Kennedy McConnell, F.A. and Payne, S.J. Autoregulating cerebral tissue selfishly exploits collateral flow routes through the circle of Willis. Acta Neurochirurgica: supplement, 126: 275-279, 2018.

[88] Park C.S., Hall, S.K., Liu, C. and Payne, S.J. A thermoelastic deformation model of tissue contraction during thermal ablation. International Journal of Hyperthermia, 34: 221-228, 2018.

[87] Jacob, P.E., Alavi, S.M.M., Mahdi, A., Payne, S.J. and Howey, D.A. Bayesian inference in non-Markovian state-space models with applications to battery fractional order systems. IEEE Transactions on Control Systems Technology, 26: 497-506, 2018.

2017

[86] Laranjeira, S., Regan-Komito, D., Iqbal, A.J., Greaves, D.R., Payne, S.J. and Orlowski, P. A model for the optimization of anti-inflammatory treatment with Chemerin. Interface Focus, 8(1): 20170007, 2017.

[85] Stroux, L., Redman, C.W.G., Georgieva, A., Payne, S.J. and Clifford, G.D. Doppler-based fetal heart rate analysis markers for the detection of early intrauterine growth restriction. Acta Obstetricia et Gynecologica Scandinavica, 96: 1322-1329, 2017.

[84] Laranjeira, S., Symmonds, M., Palace, J., Payne, S.J. and Orlowski, P. A mathematical model of cellular swelling in Neuromyelitis Optica. Journal of Theoretical Biology, 433: 39-48, 2017.

[83] Mahdi, A., Rutter, E. and Payne, S.J. Effects of non-physiological blood pressure artefacts on cerebral autoregulation. Medical Engineering and Physics, 47: 218-221, 2017.

[82] Mahdi, A., Nikolic, D., Birch, A.A., Olufsen, M.S., Panerai, R.B., Simpson, D.M. and Payne, S.J. Increased blood pressure variability upon standing up improves reproducibility of cerebral autoregulation indices. Medical Engineering and Physics, 47:151-158, 2017.

[81] Harrison, C.D., Phan, P.A., Zhang, C., Geer, D., Farmery, A.D. and Payne, S.J. Modelling mixing within the dead space of the lung improves predictions of functional residual capacity. Respiratory Physiology and Neurobiology, 242: 12-18, 2017.

[80] Alavi, S.M.M., Mahdi, A., Payne, S.J. and Howey, D.A. Identifiability of generalized Randles circuit models. IEEE Transactions on Control Systems Technology, 25: 2112-2120, 2017.

[79] Mahdi, A., Nikolic, D., Birch, A.A. and Payne, S.J. At what length do cerebral autoregulation indices stabilise? Physiological Measurement, 38: 1396-1404, 2017.

[78] Papoutsis, K., Near, J., Payne, S.J., Edwards, D.J., Li, L. and Jezzard, P. A purpose-built neck coil for black-blood DANTE-prepared carotid artery imaging at 7 Tesla. Magnetic Resonance Imaging, 40: 53-61, 2017.

[77] Kennedy-McConnell, F. and Payne, S.J. The dual role of cerebral autoregulation and collateral flow in the circle of Willis after major vessel occlusion. IEEE Transactions on Biomedical Engineering, 64: 1793-1802, 2017.

[76] Hoyer, D., ..., Payne, S.J., ... and Schneider, U. Monitoring fetal maturation - objectives, techniques and indices of autonomic function. Physiological Measurement, 38: R61-R88, 2017.

[75] Harston, G.W.J. et al. Optimizing image registration and infarct definition in stroke research. Annals of Clinical and Translational Neurology, 4: 166-174, 2017.

[74] Mahdi, A., Clifford, G.D. and Payne, S.J. A model for generating synthetic arterial blood pressure. Physiological Measurement, 38: 477-488, 2017.

[73] Mokhtarudin, M.J.M. and Payne, S.J. The study of the function of AQP4 in cerebral ischemiareperfusion injury using poroelastic theory. International Journal for Numerical Methods in Biomedical Engineering, 33: e02784, 2017.

2016

[72] Payne, S.J. Continuous positive airway pressure might not solve your cerebral autoregulation problem if you have obstructive sleep apnoea. Journal of Physiology, 594: 6803, 2016.

[71] El-Bouri, W.K. and Payne, S.J. A statistical model of the penetrating arterioles and venules in the human cerebral cortex. Microcirculation, 23: 580-590, 2016.

[70] Park, C.S., Hall, S.K. Liu, C. and Payne, S.J. A model of tissue contraction during thermal ablation. Physiological Measurement, 37: 1474-84, 2016.

[69] Liu, C., Park, C.S., Hall, S.K. and Payne, S.J. Mathematical model of the post-ablation enhancement zone as a tissue-level oedematic response. International Journal of Hyperthermia, 28: 1-11, 2016.

[68] Park, C.S. and Payne, S.J. Modelling the effects of cerebral microvasculature morphology on oxygen transport. Medical Engineering and Physics, 38: 41-47, 2016.

2015

[67] Hall, S.K., Ooi, E.H. and Payne, S.J. Cell death, perfusion and electrical parameters are critical in models of hepatic radio frequency ablation. International Journal of Hyperthermia, 31: 538-550, 2015.

[66] El-Bouri, W.K. and Payne, S.J. Multi-scale homogenization of blood flow in 3-dimensional human cerebral microvascular networks. Journal of Theoretical Biology, 380: 40-47, 2015.

[65] Mokhtarudin, M.J.M. and Payne, S.J. Mathematical model of the effect of ischemia-reperfusion on brain capillary collapse and tissue swelling. Mathematical Biosciences, 263: 111-120, 2015.

[64] Harston, G.W.J., Tee, Y.K., Blockley, N., Okell, T.W., Thandeswaran, S., Shaya, G., Sheerin, F., Cellerini, M., Payne, S.J., Jezzard, P., Chappell, M.A. and Kennedy, J. Identifying the ischaemic penumbra using pHweighted magnetic resonance imaging. Brain, 138: 36-42, 2015.

[63] Oster, J., Llinares, R., Payne, S.J., Tse, Z.T.H., Schmidt, E.J. and Clifford, G.D. Comparison of three artificial models of the magnetohydrodynamic effect on the electrocardiogram. Computer Methods in Biomechanics and Biomedical Engineering, 18:1400-1417, 2015.

2014

[62] Hall, S.K., Ooi, E.H. and Payne, S.J. A mathematical framework for minimally invasive cancer treatments. Critical Reviews in Biomedical Engineering, 42: 383-417, 2014.

[61] Mehndiratta, A., Calamante, F., MacIntosh, B.J., Crane, D.E., Payne, S.J. and Chappell, M.A. Modelling and correction of bolus dispersion effects in DSC-MRI. Magnetic Resonance in Medicine, 72: 1762-1774, 2014.

[60] Mehndiratta, A., Calamante, F., MacIntosh, B.J., Crane, D.E., Payne, S.J. and Chappell, M.A. Modelling the residue function in DSC-MRI simulations: analytical approximation to in vivo data. Magnetic Resonance in Medicine, 72: 1486-1491, 2014.

[59] Tee, Y.K., Donahue, M.J., Harston, G.W.J., Payne, S.J. and Chappell, M.A. Quantification of Amide Proton Transfer effect pre- and post-Gadolinium contrast agent administration. Journal of Magnetic Resonance Imaging, 40: 832-838, 2014.

[58] Tee, Y.K., Harston, G. W.J., Blockley, N., Okell, T.W., Levman, J., Sheerin, F., Cellerini, M., Jezzard, P., Kennedy, J., Payne, S. J. and Chappell, M. A. Comparing different analysis methods for quantifying the MRI Amide Proton Transfer (APT) effect in hyperacute stroke patients. NMR in Biomedicine, 27: 1019-1029, 2014.

[57] van den Abeelen, A.S.S., ... Payne, S.J., ... and Claassen, J.A.H.R. Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure-flow relation: The CARNet study. Medical Engineering and Physics, 36: 620-627, 2014.

[56] Georgieva, A., Papageorghiou, A., Payne, S.J., Moulden, M. and Redman, C.W.G. Phase rectified signal averaging for intrapartum electronic fetal heart rate monitoring predicts acidaemia at birth. British Journal of Obstetrics and Gynaecology, 121: 889-894, 2014.

[55] Xu, L., Redman, C.W.G., Payne, S.J. and Georgieva, A. Feature selection using genetic algorithms for fetal heart rate analysis. Physiological Measurement, 35: 1357-1371, 2014.

[54] Orlowski, P., Kennedy McConnell, F. and Payne, S.J. A mathematical model of cellular metabolism during ischemic stroke and hypothermia. IEEE Transactions on Biomedical Engineering, 61: 484-490, 2014.

2013

[53] Harston, G.W.J., Tee, Y.K., Jones, M., Payne, S.J., Pope, G., Sheerin, F. and Kennedy, J. Ventricular extension of intracerebral hemorrhage during intravenous thrombolysis. Cerebrovascular Diseases, 36: 324-325, 2013.

[52] Tee, Y.K., Khrapitchev, A.A., Sibson, N.R., Payne, S.J. and Chappell, M.A. Optimal Sampling Schedule for Chemical Exchange Saturation Transfer (CEST). Magnetic Resonance in Medicine, 70: 1251-1262, 2013.

[51] Chappell, M.A., Donahue, M.J., Tee, Y.K., Krapitchev, A.A., Sibson, N.R., Jezzard, P.J. and Payne, S.J. Quantitative Bayesian model-based analysis of Amide Proton Transfer MRI. Magnetic Resonance in Medicine, 70: 556-567, 2013.

[50] Orlowski, P., O'Neill, D.P., Grau, V., Ventikos, Y. and Payne, S.J. Modelling of the physiological response of the brain to ischaemic stroke. Interface Focus, 3 2 20120079, 2013.

[49] Park, C.S. and Payne, S.J. A generalised mathematical framework for estimating the residue function for arbitrary vascular networks. Interface Focus, 3 2 20120078, 2013.

[48] Peng, T., Niazy, R., Payne, S.J. and Wise, R.G. The effects of respiratory CO2 fluctuations in the restingstate BOLD signal differ between eyes open and eyes closed. Magnetic Resonance Imaging, 31: 336-345, 2013.

[47] Chappell, M.A., Woolrich, M.W., Petersen, E., Golay, X. and Payne, S.J. Comparing model-based and model-free analysis methods for QUASAR arterial spin labelling perfusion quantification. Magnetic Resonance in Medicine, 69: 1466-1475, 2013.

[46] Chappell, M.A., Woolrich, M.W., Kazan, S.M., Jezzard,P., Payne, S.J. and MacIntosh, B.J. Modeling dispersion in arterial spin labelling: Validation using dynamic angiographic measurements. Magnetic Resonance in Medicine, 69: 563-570, 2013.

[45] Georgieva, A., Payne, S.J., Moulden, M. and Redman, C.W.G. Artificial neural networks applied to fetal monitoring in labour. Neural Computing and Applications, 22: 85-93, 2013.

[44] Mehndiratta, A., MacIntosh, B.J., Crane, D.E., Payne, S.J. and Chappell, M.A. A control point interpolation method for the non-parametric quantification of cerebral haemodynamics from Dynamic Susceptibility Contrast MRI. NeuroImage, 64: 560-570, 2013.

2012

[43] Phillip, D., Schytz, H.W., Selb, J., Payne, S.J., Iversen, H.K., Skovgaard, L.T., Boas, D.A. and Ashina, M. Low frequency oscillations in cephalic vessels assessed by near infrared spectroscopy. European Journal of Clinical Investigation, 42: 1180-1188, 2012.

[42] Tee, Y.K., Khrapitchev, A.A., Sibson, N.R., Payne, S.J. and Chappell, M.A. Evaluating the use of a continuous approximation for model-based quantification of pulsed Chemical Exchange Saturation Transfer (CEST). Journal of Magnetic Resonance, 222: 88-95, 2012.

[41] Chappell, M.A., Okell, T., Payne, S.J., Jezzard, P. and Woolrich, M.W. A fast analysis method for noninvasive imaging of blood flow in individual cerebral arteries using vessel-encoded arterial spin labeling angiography. Medical Image Analysis, 16: 831-839, 2012.

[40] Georgieva, A., Payne, S.J., Moulden, M. and Redman, C.W.G. Relation of fetal heart rate signals with unassignable baseline to poor neonatal state at birth. Medical and Biological Engineering and Computing, 50: 717-725, 2012.

[39] Payne, S.J., Oakes, C.N. and Park, C.S. Vasomotion does inhibit mass exchange between axisymmetric blood vessels and tissue. Journal of Theoretical Biology, 302: 1-5, 2012.

[38] Su, S.W., Catherall, M.G.F. and Payne, S.J. The influence of network structure on the transport of blood in the human cerebral microvasculature. Microcirculation, 19: 175-187, 2012.

2011

[37] Webb, I.R., Payne, S.J. and Coussios, C.-C. Effect of temperature on rectified diffusion during ultrasound-induced heating. Journal of the Acoustical Society of America, 130: 3450-3457, 2011.

[36] Webb, I.R., Payne, S.J. and Coussios, C.-C. The effect of temperature and viscoelasticity on cavitation dynamics during ultrasonic ablation. Journal of the Acoustical Society of America, 130: 3458-3466, 2011.

[35] Payne, S.J., Flanagan, R., Pollari, M., Alhonnoro, T., O'Neill, D.P., Peng, T. and Steigler, P. Image-based multi-scale modelling and validation of radio frequency ablation in liver tumours. Philosophical Transactions of the Royal Society A, 369: 4233-4254, 2011.

[34] Georgieva, A., Moulden, M., Payne, S.J. and Redman, C.W.G. Computerized fetal heart rate analysis in labor: detection of intervals with un-assingable baseline, Physiological Measurement, 32: 1549-1560, 2011.

[33] Orlowski, P., Chappell, M.A., Park, C.S., Grau, V. and Payne, S.J. Modelling of pH dynamics in brain cells after stroke. Interface Focus (formerly Journal of the Royal Society Interface), 1: 408-416, 2011.

[32] Payne, S.J., Mohammad, J., Tisdall, M.M. and Tachtsidis, I. The effects of arterial blood gas levels on cerebral blood flow and oxygen transport. Biomedical Optics Express, 2: 966-979, 2011.

[31] Peng, T., O'Neill, D.P. and Payne, S.J. A two-equation coupled system for determination of liver tissue temperature during thermal ablation. International Journal of Heat and Mass Transfer, 54: 2100-2109, 2011.

[30] Park, C.S. and Payne, S.J. Nonlinear and viscous effects on wave propagation in an elastic axi-symmetric vessel. Journal of Fluids and Structures, 27: 134-144, 2011.

[29] O'Neill, D.P., Peng. T., Stiegler, P., Mayrhauser, U., Koestenbauer, S., Tscheliessnigg, K. and Payne, S.J. A three-state mathematical model of hyperthermic cell death. Annals of Biomedical Engineering, 39: 570-579, 2011.

My earlier journal papers [1-28], covering the period before 2011, can be found on my website.