Observability and synchronization of neuron models.
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Christophe Letellier | Luis A Aguirre | L. A. Aguirre | Leonardo L Portes | C. Letellier | L. Portes
[1] Sang-Yoon Kim,et al. Coupling-induced population synchronization in an excitatory population of subthreshold Izhikevich neurons , 2013, Cognitive Neurodynamics.
[2] A. Isidori. Nonlinear Control Systems , 1985 .
[3] Bruce J. Gluckman,et al. Reconstructing Mammalian Sleep Dynamics with Data Assimilation , 2012, PLoS Comput. Biol..
[4] G. P. King,et al. Extracting qualitative dynamics from experimental data , 1986 .
[5] J. Hindmarsh,et al. A model of neuronal bursting using three coupled first order differential equations , 1984, Proceedings of the Royal Society of London. Series B. Biological Sciences.
[6] Michael Ghil,et al. Multivariate singular spectrum analysis and the road to phase synchronization. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.
[7] O. Rössler. An equation for continuous chaos , 1976 .
[8] A. Krener,et al. Nonlinear controllability and observability , 1977 .
[9] Luis A Aguirre,et al. Matrix formulation and singular-value decomposition algorithm for structured varimax rotation in multivariate singular spectrum analysis. , 2016, Physical review. E.
[10] Sylvain Mangiarotti,et al. Topological analysis for designing a suspension of the Hénon map , 2015 .
[11] Bernard Friedland,et al. Controllability Index Based on Conditioning Number , 1975 .
[12] Eugene M. Izhikevich,et al. Simple model of spiking neurons , 2003, IEEE Trans. Neural Networks.
[13] Christophe Letellier,et al. Symbolic observability coefficients for univariate and multivariate analysis. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[14] C. Letellier,et al. Symbolic computations of nonlinear observability. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.
[15] M. Ghil,et al. Monte Carlo Singular Spectrum Analysis (SSA) Revisited: Detecting Oscillator Clusters in Multivariate Datasets , 2015 .
[16] Joël M. H. Karel,et al. Quantifying Neural Oscillatory Synchronization: A Comparison between Spectral Coherence and Phase-Locking Value Approaches , 2016, PloS one.
[17] Steven J. Schiff,et al. Neural Control Engineering: The Emerging Intersection Between Control Theory and Neuroscience , 2011 .
[18] Luis A. Aguirre,et al. Observability of multivariate differential embeddings , 2005 .
[19] J. NAGUMOt,et al. An Active Pulse Transmission Line Simulating Nerve Axon , 2006 .
[20] L. A. Aguirre,et al. Investigating observability properties from data in nonlinear dynamics. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.
[21] A. Hodgkin,et al. A quantitative description of membrane current and its application to conduction and excitation in nerve , 1990 .
[22] Jürgen Kurths,et al. Nonlinear Dynamical System Identification from Uncertain and Indirect Measurements , 2004, Int. J. Bifurc. Chaos.
[23] R. Kálmán. On the general theory of control systems , 1959 .
[24] M. Hasler,et al. Synchronization in Pulse-Coupled Networks of Bursting Neurons , 2005 .
[25] Sean N. Brennan,et al. Observability and Controllability of Nonlinear Networks: The Role of Symmetry , 2013, Physical review. X.
[26] Eugene M. Izhikevich,et al. Which model to use for cortical spiking neurons? , 2004, IEEE Transactions on Neural Networks.
[27] Daniel Chicharro,et al. Monitoring spike train synchrony , 2012, Journal of neurophysiology.
[28] Luis A Aguirre,et al. Enhancing multivariate singular spectrum analysis for phase synchronization: The role of observability. , 2016, Chaos.
[29] Michael Ghil,et al. ADVANCED SPECTRAL METHODS FOR CLIMATIC TIME SERIES , 2002 .
[30] L. A. Aguirre,et al. Impact of the recorded variable on recurrence quantification analysis of flows , 2014 .
[31] Christophe Letellier,et al. Relation between observability and differential embeddings for nonlinear dynamics. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[32] R. FitzHugh. Impulses and Physiological States in Theoretical Models of Nerve Membrane. , 1961, Biophysical journal.
[33] G. Edelman,et al. Large-scale model of mammalian thalamocortical systems , 2008, Proceedings of the National Academy of Sciences.
[34] Bharat Bhushan Sharma,et al. Synchronization of a set of coupled chaotic FitzHugh–Nagumo and Hindmarsh–Rose neurons with external electrical stimulation , 2016 .
[35] Jean-Pierre Barbot,et al. Influence of the singular manifold of nonobservable states in reconstructing chaotic attractors. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.
[36] Daniel Chicharro,et al. Time-resolved and time-scale adaptive measures of spike train synchrony , 2010, Journal of Neuroscience Methods.
[37] Joshua W. Brown,et al. The tale of the neuroscientists and the computer: why mechanistic theory matters , 2014, Front. Neurosci..
[38] Luis A. Aguirre,et al. On the non-equivalence of observables in phase-space reconstructions from recorded time series , 1998 .
[39] Luis A. Aguirre,et al. A nonlinear correlation function for selecting the delay time in dynamical reconstructions , 1995 .
[40] Luis A. Aguirre,et al. Investigating nonlinear dynamics from time series: The influence of symmetries and the choice of observables. , 2002, Chaos.
[41] Bin Deng,et al. Analysis and application of neuronal network controllability and observability. , 2017, Chaos.
[42] Constantinos Siettos,et al. Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools , 2016, Wiley interdisciplinary reviews. Systems biology and medicine.
[43] O. Kinouchi,et al. A brief history of excitable map-based neurons and neural networks , 2013, Journal of Neuroscience Methods.
[44] L. A. Aguirre,et al. Controllability and synchronizability: Are they related? , 2016 .
[45] S. Boccaletti,et al. Observability coefficients for predicting the class of synchronizability from the algebraic structure of the local oscillators. , 2016, Physical review. E.
[46] Martin Hasler,et al. Synchronization of bursting neurons: what matters in the network topology. , 2005, Physical review letters.