Relevant bibliographies by topics / Electrophysiology - Mathematical models

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Electrophysiology - Mathematical models'

Author: Grafiati
Published: 4 June 2021
Last updated: 28 January 2023

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Journal articles on the topic "Electrophysiology - Mathematical models"

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Amuzescu, Bogdan, Razvan Airini, Florin Bogdan Epureanu, Stefan A. Mann, Thomas Knott, and Beatrice Mihaela Radu. "Evolution of mathematical models of cardiomyocyte electrophysiology." Mathematical Biosciences 334 (April 2021): 108567. http://dx.doi.org/10.1016/j.mbs.2021.108567.

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Johnstone, Ross, Rémi Bardenet, Teun de Boer, et al. "Cell-specific mathematical models of cardiac electrophysiology." Journal of Pharmacological and Toxicological Methods 81 (September 2016): 343. http://dx.doi.org/10.1016/j.vascn.2016.02.029.

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Linge, S., J. Sundnes, M. Hanslien, G. T. Lines, and A. Tveito. "Numerical solution of the bidomain equations." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1895 (2009): 1931–50. http://dx.doi.org/10.1098/rsta.2008.0306.

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Knowledge of cardiac electrophysiology is efficiently formulated in terms of mathematical models. However, most of these models are very complex and thus defeat direct mathematical reasoning founded on classical and analytical considerations. This is particularly so for the celebrated bidomain model that was developed almost 40 years ago for the concurrent analysis of extra- and intracellular electrical activity. Numerical simulations based on this model represent an indispensable tool for studying electrophysiology. However, complex mathematical models, steep gradients in the solutions and co
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Lines, G. T., M. L. Buist, P. Grottum, A. J. Pullan, J. Sundnes, and A. Tveito. "Mathematical models and numerical methods for the forward problem in cardiac electrophysiology." Computing and Visualization in Science 5, no. 4 (2002): 215–39. http://dx.doi.org/10.1007/s00791-003-0101-4.

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Cherry, Elizabeth M., and Flavio H. Fenton. "A tale of two dogs: analyzing two models of canine ventricular electrophysiology." American Journal of Physiology-Heart and Circulatory Physiology 292, no. 1 (2007): H43—H55. http://dx.doi.org/10.1152/ajpheart.00955.2006.

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The extensive development of detailed mathematical models of cardiac myocyte electrophysiology in recent years has led to a proliferation of models, including many that model the same animal species and specific region of the heart and thus would be expected to have similar properties. In this paper we review and compare two recently developed mathematical models of the electrophysiology of canine ventricular myocytes. To clarify their similarities and differences, we also present studies using them in a range of preparations from single cells to two-dimensional tissue. The models are compared
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Jacquemet, Vincent. "Steady-state solutions in mathematical models of atrial cell electrophysiology and their stability." Mathematical Biosciences 208, no. 1 (2007): 241–69. http://dx.doi.org/10.1016/j.mbs.2006.10.007.

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Carlu, M., O. Chehab, L. Dalla Porta, et al. "A mean-field approach to the dynamics of networks of complex neurons, from nonlinear Integrate-and-Fire to Hodgkin–Huxley models." Journal of Neurophysiology 123, no. 3 (2020): 1042–51. http://dx.doi.org/10.1152/jn.00399.2019.

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Population models are a powerful mathematical tool to study the dynamics of neuronal networks and to simulate the brain at macroscopic scales. We present a mean-field model capable of quantitatively predicting the temporal dynamics of a network of complex spiking neuronal models, from Integrate-and-Fire to Hodgkin–Huxley, thus linking population models to neurons electrophysiology. This opens a perspective on generating biologically realistic mean-field models from electrophysiological recordings.
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Collin, Annabelle, and Sébastien Imperiale. "Mathematical analysis and 2-scale convergence of a heterogeneous microscopic bidomain model." Mathematical Models and Methods in Applied Sciences 28, no. 05 (2018): 979–1035. http://dx.doi.org/10.1142/s0218202518500264.

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The aim of this paper is to provide a complete mathematical analysis of the periodic homogenization procedure that leads to the macroscopic bidomain model in cardiac electrophysiology. We consider space-dependent and tensorial electric conductivities as well as space-dependent physiological and phenomenological nonlinear ionic models. We provide the nondimensionalization of the bidomain equations and derive uniform estimates of the solutions. The homogenization procedure is done using 2-scale convergence theory which enables us to study the behavior of the nonlinear ionic models in the homogen
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Corre, S., and A. Belmiloudi. "Coupled lattice Boltzmann simulation method for bidomain type models in cardiac electrophysiology with multiple time-delays." Mathematical Modelling of Natural Phenomena 14, no. 2 (2019): 207. http://dx.doi.org/10.1051/mmnp/2019045.

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In this work, we propose a mathematical model of the cardiac electrophysiology which take into account time delays in signal transmission, in order to capture the whole activities of macro- to micro-scale transport processes, and use this model to analyze the propagation of electrophysiological waves in the heart by using a developed coupling Lattice Boltzmann Method (LBM). The propagation of electrical activity in the heart is mathematically modeled by a modified bidomain system. As transmembrane potential evolves, the domain has anisotropical properties which are transposed into intracellula
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Lei, Chon Lok, Sanmitra Ghosh, Dominic G. Whittaker, et al. "Considering discrepancy when calibrating a mechanistic electrophysiology model." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2173 (2020): 20190349. http://dx.doi.org/10.1098/rsta.2019.0349.

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Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterize uncertainty in model inputs and how that propagates through to outputs or predictions; examples of this can be seen in the papers of this issue. In this review and perspective piece, we draw attention to an important and under-addressed source of uncertainty in our predictions—that of uncertainty in the model structure or the equations themselves. The difference between imperfect models and real
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Dissertations / Theses on the topic "Electrophysiology - Mathematical models"

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戚大衛 and Tai-wai David Chik. "A numerical study of Hodgkin-Huxley neurons." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31224210.

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Chavarette, Fabio Roberto. "Dinamica e controle não lineares de um sistema neuronal ideal e nã-ideal." [s.n.], 2005. http://repositorio.unicamp.br/jspui/handle/REPOSIP/263219.

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Orientadores: Jose Manoel Balthazar, Helder Anibal Hermini<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica<br>Made available in DSpace on 2018-08-06T09:09:07Z (GMT). No. of bitstreams: 1 Chavarette_FabioRoberto_D.pdf: 4150246 bytes, checksum: 9d985ec5ea9fe6e142b97323e3bcc2d9 (MD5) Previous issue date: 2005<br>Resumo: Nesta tese de doutorado, estuda-se o comportamento da membrana plasmática modelada através de um circuito elétrico. O modelo elétrico foi desenvolvido por Hodgkin e Huxley em 1952 e trata da variação do tempo em relação à condutância de
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Lin, Risa J. "Real-time methods in neural electrophysiology to improve efficacy of dynamic clamp." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/49016.

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In the central nervous system, most of the processes ranging from ion channels to neuronal networks occur in a closed loop, where the input to the system depends on its output. In contrast, most experimental preparations and protocols operate autonomously in an open loop and do not depend on the output of the system. Real-time software technology can be an essential tool for understanding the dynamics of many biological processes by providing the ability to precisely control the spatiotemporal aspects of a stimulus and to build activity-dependent stimulus-response closed loops. So far, applica
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鄭嘉亨 and Ka-hang Cheng. "Expert system in stochastic analysis of neuronal signals." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31233028.

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Britton, Oliver Jonathan. "Combined experimental and computational investigation into inter-subject variability in cardiac electrophysiology." Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:6299240d-0528-4662-8e1f-5025f39e730f.

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The underlying causes of variability in the electrical activity of hearts from individuals of the same species are not well understood. Understanding this variability is important to enable prediction of the response of individual hearts to diseases and therapies. Current experimental and computational methods for investigating the behaviour of the heart do not incorporate biological variation between individuals. In experimental studies, experimental results are averaged together to control errors and determine the average behaviour of the studied organism. In computational studies, averaged
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Oshiyama, Natália Ferreira 1985. "Modelo matemático de potencial de ação e transporte de Ca2+ em miócitos ventriculares de ratos neonatos." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260926.

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Orientadores: José Wilson Magalhães Bassani, Rosana Almada Bassani<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-24T11:00:56Z (GMT). No. of bitstreams: 1 Oshiyama_NataliaFerreira_D.pdf: 4721295 bytes, checksum: 5ed8a9a173462afb13315f133bf426f8 (MD5) Previous issue date: 2014<br>Resumo: O potencial de ação (PA), variação do potencial elétrico através da membrana (Em), é gerado por fluxos iônicos através de canais e transportadores, cuja função e expressão pode ser alterada por hormônios, neurotr
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Besse, Ian Matthew. "Modeling caveolar sodium current contributions to cardiac electrophysiology and arrhythmogenesis." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/463.

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Proper heart function results from the periodic execution of a series of coordinated interdependent mechanical, chemical, and electrical processes within the cardiac tissue. Central to these processes is the action potential - the electrochemical event that initiates contraction of the individual cardiac myocytes. Many models of the cardiac action potential exist with varying levels of complexity, but none account for the electrophysiological role played by caveolae - small invaginations of the cardiac cell plasma membrane. Recent electrophysiological studies regarding these microdomains revea
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Hurdal, Monica Kimberly. "Mathematical and computer modelling of the human brain with reference to cortical magnification and dipole source localisation in the visual cortx." Thesis, Queensland University of Technology, 1998.

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Skoczelas, Brenda M. "A mathematical model for calculating the effect of toroidal geometry on the measured magnetic field." Muncie, Ind. : Ball State University, 2009. http://cardinalscholar.bsu.edu/714.

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Campana, Chiara. "A 2-dimensional computational model to analyze the effects of cellular heterogeinity on cardiac pacemaking." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8596/.

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The mechanical action of the heart is made possible in response to electrical events that involve the cardiac cells, a property that classifies the heart tissue between the excitable tissues. At the cellular level, the electrical event is the signal that triggers the mechanical contraction, inducing a transient increase in intracellular calcium which, in turn, carries the message of contraction to the contractile proteins of the cell. The primary goal of my project was to implement in CUDA (Compute Unified Device Architecture, an hardware architecture for parallel processing created by NVIDIA) a
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Books on the topic "Electrophysiology - Mathematical models"

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José, Jalife, and New York Academy of Sciences., eds. Mathematical approaches to cardiac arrhythmias. New York Academy Sciences, 1990.

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Doi, S. Computational electrophysiology: Dynamical systems and bifurcations. Springer, 2010.

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Plonsey, Robert. Bioelectricity: A quantitative approach. Plenum Press, 1988.

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Plonsey, Robert. Bioelectricity: A quantitative approach. 2nd ed. Kluwer Academic/Plenum Publishers, 2000.

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Cronin, Jane. Mathematical aspects of Hodgkin-Huxley neural theory. Cambridge University Press, 1987.

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1943-, Othmer H. G., and National Science Foundation (U.S.), eds. Some mathematical questions in biology: The dynamics of excitable media. American Mathematical Society, 1989.

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K, Cheng Leo, and Buist Martin L, eds. Mathematical modelling the electrical activity of the heart: From cell to body surface and back again. World Scientific, 2005.

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Titomir, L. I. Bioelectric and biomagnetic fields: Theory and applications in electrocardiology. CRC Press, 1994.

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Plonsey, Robert. Bioelectricity: A Quantitative Approach. Springer US, 2000.

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Möller, Holger. Möglichkeiten und Grenzen Linearer Strukturmodelle zur Parametrisierung ereigniskorrelierter Potentiale: Eine Untersuchung am Beispiel von emotional bedeutsamem Reizmaterial. WVT, 1991.

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Book chapters on the topic "Electrophysiology - Mathematical models"

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Doi, Shinji, Junko Inoue, and Zhenxing Pan. "Computational and Mathematical Models of Neurons." In Computational Electrophysiology. Springer Japan, 2010. http://dx.doi.org/10.1007/978-4-431-53862-2_3.

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Ince, Can. "Application of Mathematical Models in the Membrane Electrophysiology of Macrophages." In Lecture Notes in Biomathematics. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-51691-7_15.

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Corre, S., and A. Belmiloudi. "Coupled Lattice Boltzmann Modeling of Bidomain Type Models in Cardiac Electrophysiology." In Mathematical and Computational Approaches in Advancing Modern Science and Engineering. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30379-6_20.

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Dawson, John, Anna Gams, Ivan Rajen, Andrew M. Soltisz, and Andrew G. Edwards. "Computational Prediction of Cardiac Electropharmacology - How Much Does the Model Matter?" In Computational Physiology. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05164-7_5.

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AbstractAnimal data describing drug interactions in cardiac tissue are abundant, however, nuanced inter-species differences hamper the use of these data to predict drug responses in humans. There are many computational models of cardiomyocyte electrophysiology that facilitate this translation, yet it is unclear whether fundamental differences in their mathematical formalisms significantly impact their predictive power. A common solution to this problem is to perform inter-species translations within a collection of models with internally consistent formalisms, termed a “lineage”, but there has been little effort to translate outputs across lineages. Here, we translate model outputs between lineages from Simula and Washington University for models of ventricular cardiomyocyte electrophysiology of humans, canines, and guinea pigs. For each lineage-species combination, we generated a population of 1000 models by varying common parameters, namely ion conductances, according to a Guassian log-normal distribution with a mean at the parameter’s species-specific default value and standard deviation of 30%.We used partial least squares regression to translate the influences of one model to another using perturbations to calculated descriptors of resulting electrophysiological behavior derived from these parameter variations. Finally, we evaluated translation fidelity by performing a sensitivity analysis between input parameters and output descriptors, as similar sensitivities between models of a common species indicates similar biological mechanisms underlying model behavior. Successful translation between models, especially those from different lineages, will increase confidence in their predictive power.
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Bell, Michael M., and Elizabeth M. Cherry. "Computational Cardiac Electrophysiology: Implementing Mathematical Models of Cardiomyocytes to Simulate Action Potentials of the Heart." In Methods in Molecular Biology. Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2572-8_5.

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Yamamoto, Kei, Sophie Fischer-Holzhausen, Maria P. Fjeldstad, and Mary M. Maleckar. "Ordinary Differential Equation-based Modeling of Cells in Human Cartilage." In Computational Physiology. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05164-7_3.

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AbstractChondrocytes produce the extracellular cartilage matrix required for smooth joint mobility. As cartilage is not vascularised, and chondrocytes are not innervated by the nervous system, chondrocytes are therefore generally considered non-excitable. However, chondrocytes do express a range of ion channels, ion pumps, and receptors involved in cell homeostasis and cartilage maintenance. Dysfunction in these ion channels and pumps has been linked to degenerative disorders such as arthritis. Because the electrophysiological properties of chondrocytes are difficult to measure experimentally, mathematical modelling can instead be used to investigate the regulation of ionic currents. Such models can provide insight into the finely tuned parameters underlying fluctuations in membrane potential and cell behaviour in healthy and pathological conditions. Here, we introduce an open-source, intuitive, and extendable mathematical model of chondrocyte electrophysiology, implementing key proteins involved in regulating the membrane potential. Because of the inherent biological variability of cells and their physiological ranges of ionic concentrations, we describe a population of models that provides a robust computational representation of the biological data. This permits parameter variability in a manner mimicking biological variation, and we present a selection of parameter sets that suitably represent experimental data. Our mathematical model can be used to efficiently investigate the ionic currents underlying chondrocyte behaviour.
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Larsen, Erik Hviid, and Jens Nørkær Sørensen. "Stationary and Nonstationary Ion and Water Flux Interactions in Kidney Proximal Tubule: Mathematical Analysis of Isosmotic Transport by a Minimalistic Model." In Reviews of Physiology, Biochemistry and Pharmacology. Springer International Publishing, 2019. http://dx.doi.org/10.1007/112_2019_16.

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AbstractOur mathematical model of epithelial transport (Larsen et al. Acta Physiol. 195:171–186, 2009) is extended by equations for currents and conductance of apical SGLT2. With independent variables of the physiological parameter space, the model reproduces intracellular solute concentrations, ion and water fluxes, and electrophysiology of proximal convoluted tubule. The following were shown: Water flux is given by active Na+ flux into lateral spaces, while osmolarity of absorbed fluid depends on osmotic permeability of apical membranes. Following aquaporin “knock-out,” water uptake is not reduced but redirected to the paracellular pathway. Reported decrease in epithelial water uptake in aquaporin-1 knock-out mouse is caused by downregulation of active Na+ absorption. Luminal glucose stimulates Na+ uptake by instantaneous depolarization-induced pump activity (“cross-talk”) and delayed stimulation because of slow rise in intracellular [Na+]. Rate of fluid absorption and flux of active K+ absorption would have to be attuned at epithelial cell level for the [K+] of the absorbate being in the physiological range of interstitial [K+]. Following unilateral osmotic perturbation, time course of water fluxes between intraepithelial compartments provides physical explanation for the transepithelial osmotic permeability being orders of magnitude smaller than cell membranes’ osmotic permeability. Fluid absorption is always hyperosmotic to bath. Deviation from isosmotic absorption is increased in presence of glucose contrasting experimental studies showing isosmotic transport being independent of glucose uptake. For achieving isosmotic transport, the cost of Na+ recirculation is predicted to be but a few percent of the energy consumption of Na+/K+ pumps.
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Henriquez, Craig S., Joseph V. Tranquillo, David Weinstein, Edward W. Hsu, and Christopher R. Johnson. "Three-dimensional Propagation in Mathematic Models: Integrative Model of the Mouse Heart." In Cardiac Electrophysiology. Elsevier, 2004. http://dx.doi.org/10.1016/b0-7216-0323-8/50033-6.

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Leigh, R. John, and David S. Zee. "The Saccadic System." In The Neurology of Eye Movements. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199969289.003.0004.

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This chapter reviews the behavioral properties of rapid eye movements, ranging from quick phases of nystagmus to cognitively controlled saccades, and their neural substrate. Properties of various types of saccades are described, including express saccades, memory-guided saccades, antisaccades, and saccades during visual search and reading. Current concepts of regions important for the generation of saccades are reviewed, integrating results of functional imaging and electrophysiology, including brainstem burst neurons and omnipause neurons, the superior colliculus, frontal eye field, supplementary eye field, dorsolateral prefrontal cortex, cingulate cortex, posterior parietal cortex, parietal eye field, thalamus, pulvinar, caudate, substantia nigra pars reticulata, subthalamic nucleus, cerebellar dorsal vermis, and fastigial nucleus. Saccade adaptation to novel visual demands is discussed, and the interaction between saccades and eyelid movements (blinks). Mathematical models of saccades are discussed. Clinical and laboratory evaluation of saccades and the pathophysiology of saccadic disorders, from slow saccades to opsoclonus, are reviewed.
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Conference papers on the topic "Electrophysiology - Mathematical models"

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Ushenin, K. S., A. Dokuchaev, S. M. Magomedova, O. V. Sopov, V. V. Kalinin, and O. Solovyova. "Models of human heart and torso electrophysiology verified against clinical data." In Mathematical Biology and Bioinformatics. IMPB RAS - Branch of KIAM RAS, 2018. http://dx.doi.org/10.17537/icmbb18.41.

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Corrias, A., and B. Rodriguez. "A novel biophysically-detailed mathematical model of rabbit Purkinje cell electrophysiology." In 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010). IEEE, 2010. http://dx.doi.org/10.1109/iembs.2010.5626614.

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