Optimisation and computational methods to model the oculomotor system with focus on nystagmus

............................................................................................................. 2 Acknowledgements ............................................................................................ 4 List of Abbreviations ......................................................................................... 10 Nomenclature ................................................................................................... 13 List of Figures ................................................................................................... 15 List of Tables .................................................................................................... 26

[1]  Jonathan E. Fieldsend,et al.  Visualising High-Dimensional Pareto Relationships in Two-Dimensional Scatterplots , 2013, EMO.

[2]  R A Clement,et al.  Eye movement instabilities and nystagmus can be predicted by a nonlinear dynamics model of the saccadic system , 2005, Journal of mathematical biology.

[3]  R. J. van Beers,et al.  The role of execution noise in movement variability. , 2004, Journal of neurophysiology.

[4]  T. Back.  Selective pressure in evolutionary algorithms: a characterization of selection mechanisms , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[5]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[6]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[7]  I. Gottlob,et al.  Nystagmus in childhood. , 2014, Pediatrics and neonatology.

[8]  Qingfu Zhang,et al.  Multiobjective evolutionary algorithms: A survey of the state of the art , 2011, Swarm Evol. Comput..

[9]  P. Pospichal.  GPU-based Acceleration of the Genetic Algorithm , 2009 .

[10]  J. Thompson,et al.  The prevalence of nystagmus: the Leicestershire nystagmus survey. , 2009, Investigative ophthalmology & visual science.

[11]  Kalyanmoy Deb,et al.  A Computationally Efficient Evolutionary Algorithm for Real-Parameter Optimization , 2002, Evolutionary Computation.

[12]  Maria Romano,et al.  Characterisation of baseline oscillation in congenital nystagmus eye movement recordings , 2009, Biomed. Signal Process. Control..

[13]  Karl Rupp,et al.  Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries , 2012, SIAM J. Sci. Comput..

[14]  Fernando M. Ramos,et al.  Metaheuristics for the feedforward artificial neural network (ANN) architecture optimization problem , 2011, Neural Computing and Applications.

[15]  M. Caramia,et al.  Multi-objective Management in Freight Logistics: Increasing Capacity, Service Level and Safety with Optimization Algorithms , 2008 .

[16]  A. Faisal,et al.  Noise in the nervous system , 2008, Nature Reviews Neuroscience.

[17]  Joshua D. Knowles,et al.  On metrics for comparing nondominated sets , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[18]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[19]  P. W. Poon,et al.  Genetic algorithm crossover operators for ordering applications , 1995, Comput. Oper. Res..

[20]  Julio R. Banga,et al.  Optimization in computational systems biology , 2008, BMC Systems Biology.

[21]  R. A. Clement,et al.  Dynamical systems analysis: a new method of analysing congenital nystagmus waveforms , 1997, Experimental Brain Research.

[22]  Kalyanmoy Deb,et al.  Multi-objective Optimisation Using Evolutionary Algorithms: An Introduction , 2011, Multi-objective Evolutionary Optimisation for Product Design and Manufacturing.

[23]  Edward L Keller,et al.  Shared Brainstem Pathways for Saccades and Smooth‐Pursuit Eye Movements , 2003, Annals of the New York Academy of Sciences.

[24]  Enrique Alba,et al.  Parallel Genetic Algorithms , 2011, Studies in Computational Intelligence.

[25]  Dario Floreano,et al.  Selection methods regulate evolution of cooperation in digital evolution , 2014, Journal of The Royal Society Interface.

[26]  L. Osso.  CONGENITAL NYSTAGMUS WAVEFORMS AND FOVEATION STRATEGY , 1975 .

[27]  Kevin O’Regan,et al.  Saccade size control in reading: Evidence for the linguistic control hypothesis , 1979, Perception & psychophysics.

[28]  Mustafa Khammash,et al.  Parameter Estimation and Model Selection in Computational Biology , 2010, PLoS Comput. Biol..

[29]  Antonio Pescapè,et al.  Genetic Algorithm Modeling with GPU Parallel Computing Technology , 2012, WIRN.

[30]  Kalyanmoy Deb,et al.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.

[31]  Jonathan M. Garibaldi,et al.  Parameter Estimation Using Metaheuristics in Systems Biology: A Comprehensive Review , 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[32]  I. Gottlob,et al.  Living with nystagmus: a qualitative study , 2010, British Journal of Ophthalmology.

[33]  M. Brodsky,et al.  A unifying neurologic mechanism for infantile nystagmus. , 2014, JAMA ophthalmology.

[34]  Richard A. Clement,et al.  Fixed point analysis of nystagmus , 2007, Journal of Neuroscience Methods.

[35]  G. P. King,et al.  Extracting qualitative dynamics from experimental data , 1986 .

[36]  F. Takens.  Detecting strange attractors in turbulence , 1981 .

[37]  Jonathan E. Fieldsend,et al.  The Rolling Tide Evolutionary Algorithm: A Multiobjective Optimizer for Noisy Optimization Problems , 2015, IEEE Transactions on Evolutionary Computation.

[38]  R. Reynolds,et al.  Optimizing Stochastic and Multiple Fitness Functions , 1995 .

[39]  Riccardo Poli,et al.  Parallel genetic algorithm taxonomy , 1999, 1999 Third International Conference on Knowledge-Based Intelligent Information Engineering Systems. Proceedings (Cat. No.99TH8410).

[40]  S Forrest,et al.  Genetic algorithms , 1996, CSUR.

[41]  Mervyn G. Thomas,et al.  Abnormal retinal development associated with FRMD7 mutations , 2014, Human molecular genetics.

[42]  L. Optican,et al.  A hypothetical explanation of congenital nystagmus , 1984, Biological Cybernetics.

[43]  Maksat Ashyraliyev,et al.  Systems biology: parameter estimation for biochemical models , 2009, The FEBS journal.

[44]  Jonathan E. Fieldsend,et al.  Visualizing Mutually Nondominating Solution Sets in Many-Objective Optimization , 2013, IEEE Transactions on Evolutionary Computation.

[45]  Syed Murtuza Baker,et al.  Comparison of different algorithms for simultaneous estimation of multiple parameters in kinetic metabolic models , 2010, J. Integr. Bioinform..

[46]  A. J. Roberts,et al.  Modify the Improved Euler scheme to integrate stochastic differential equations , 2012, 1210.0933.

[47]  I. Gottlob,et al.  Social and visual function in nystagmus , 2005, British Journal of Ophthalmology.

[48]  C. Harris.  Oculomotor developmental pathology: an ‘evo-devo’ perspective , 2011 .

[49]  Sébastien Vérel,et al.  On the influence of selection operators on performances in cellular Genetic Algorithms , 2007, 2007 IEEE Congress on Evolutionary Computation.

[50]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[51]  Bruce Hendrickson,et al.  A Spectral Algorithm for Seriation and the Consecutive Ones Problem , 1999, SIAM J. Comput..

[52]  Susanne Mauthner,et al.  Step size control in the numerical solution of stochastic differential equations , 1998 .

[53]  Richard V Abadi,et al.  Retinal slip velocities in congenital nystagmus , 1989, Vision Research.

[54]  Irene Gottlob,et al.  Aetiology of infantile nystagmus. , 2014, Current opinion in neurology.

[55]  C. Bockisch,et al.  Positive or negative feedback of optokinetic signals: degree of the misrouted optic flow determines system dynamics of human ocular motor behavior. , 2014, Investigative ophthalmology & visual science.

[56]  Antonio J. Nebro,et al.  A survey of multi-objective metaheuristics applied to structural optimization , 2014 .

[57]  Olympia Roeva,et al.  Influence of the population size on the genetic algorithm performance in case of cultivation process modelling , 2013, 2013 Federated Conference on Computer Science and Information Systems.

[58]  Richard V Abadi,et al.  Waveform characteristics in congenital nystagmus , 1987, Documenta Ophthalmologica.