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Mark Damian McDonnell

University of Adelaide, Adelaide, South Australia, Australia 
Computational neuroscience, stochastic neurodynamical models
"Mark McDonnell"
Mean distance: 20.7 (cluster 39)
Cross-listing: Computational Biology Tree

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Moezzi B, Schaworonkow N, Plogmacher L, et al. (2018) Simulation of electromyographic recordings following transcranial magnetic stimulation. Journal of Neurophysiology
Xu L, Duan F, Gao X, et al. (2017) Adaptive recursive algorithm for optimal weighted suprathreshold stochastic resonance. Royal Society Open Science. 4: 160889
Newton AJH, Seidenstein AH, McDougal RA, et al. (2017) 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Bmc Neuroscience. 18
Sharpee TO, Destexhe A, Kawato M, et al. (2016) 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54
Moezzi B, Iannella N, McDonnell MD. (2016) Ion channel noise can explain firing correlation in auditory nerves. Journal of Computational Neuroscience
McDonnell MD, Goldwyn JH, Lindner B. (2016) Editorial: Neuronal Stochastic Variability: Influences on Spiking Dynamics and Network Activity. Frontiers in Computational Neuroscience. 10: 38
Gunn LJ, Chapeau-Blondeau F, McDonnell MD, et al. (2016) Too good to be true: when overwhelming evidence fails to convince. Proceedings. Mathematical, Physical, and Engineering Sciences / the Royal Society. 472: 20150748
Xu L, Duan F, Abbott D, et al. (2016) Optimal weighted suprathreshold stochastic resonance with multigroup saturating sensors Physica a: Statistical Mechanics and Its Applications. 457: 348-355
McDonnell MD, Iannella N, To MS, et al. (2015) A review of methods for identifying stochastic resonance in simulations of single neuron models. Network (Bristol, England). 26: 35-71
Greenwood PE, McDonnell MD, Ward LM. (2015) Dynamics of gamma bursts in local field potentials. Neural Computation. 27: 74-103
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