Impact of Network Structure and Cellular Response on Spike Time Correlations
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Eric Shea-Brown | Yu Hu | Kresimir Josic | James Trousdale | Eric T. Shea-Brown | K. Josić | Yu Hu | James Trousdale | E. Shea-Brown
[1] Eric Shea-Brown,et al. Correlation and synchrony transfer in integrate-and-fire neurons: basic properties and consequences for coding. , 2008, Physical review letters.
[2] E E Fetz,et al. Relation between shapes of post‐synaptic potentials and changes in firing probability of cat motoneurones , 1983, The Journal of physiology.
[3] J. White,et al. Channel noise in neurons , 2000, Trends in Neurosciences.
[4] M. J. Richardson,et al. Dynamics of populations and networks of neurons with voltage-activated and calcium-activated currents. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[5] Alexander S. Ecker,et al. Decorrelated Neuronal Firing in Cortical Microcircuits , 2010, Science.
[6] M. Diamond,et al. The Role of Spike Timing in the Coding of Stimulus Location in Rat Somatosensory Cortex , 2001, Neuron.
[7] J. Elgin. The Fokker-Planck Equation: Methods of Solution and Applications , 1984 .
[8] Kamiar Rahnama Rad,et al. Mean-Field Approximations for Coupled Populations of Generalized Linear Model Spiking Neurons with Markov Refractoriness , 2009, Neural Computation.
[9] Wei Wu,et al. A new look at state-space models for neural data , 2010, Journal of Computational Neuroscience.
[10] Fabrizio Gabbiani,et al. Principles of spike train analysis , 1996 .
[11] Nicolas Brunel,et al. From Spiking Neuron Models to Linear-Nonlinear Models , 2011, PLoS Comput. Biol..
[12] L. Ricciardi,et al. The Ornstein-Uhlenbeck process as a model for neuronal activity , 1979, Biological Cybernetics.
[13] Jianfeng Feng,et al. Computational neuroscience , 1986, Behavioral and Brain Sciences.
[14] Jaime de la Rocha,et al. Supplementary Information for the article ‘ Correlation between neural spike trains increases with firing rate ’ , 2007 .
[15] P. Dayan,et al. Supporting Online Material Materials and Methods Som Text Figs. S1 to S9 References the Asynchronous State in Cortical Circuits , 2022 .
[16] Benjamin Lindner,et al. Comparative study of different integrate-and-fire neurons: spontaneous activity, dynamical response, and stimulus-induced correlation. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[17] P. Latham,et al. Synergy, Redundancy, and Independence in Population Codes, Revisited , 2005, The Journal of Neuroscience.
[18] Mitchell Glickstein,et al. Foundations of the neuron doctrine , 1993, Medical History.
[19] Alexandre Pouget,et al. Insights from a Simple Expression for Linear Fisher Information in a Recurrently Connected Population of Spiking Neurons , 2011, Neural Computation.
[20] Sooyoung Chung,et al. Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex , 2005, Nature.
[21] Nicolas Brunel,et al. Fast Global Oscillations in Networks of Integrate-and-Fire Neurons with Low Firing Rates , 1999, Neural Computation.
[22] Michael J. Berry,et al. Synergy, Redundancy, and Independence in Population Codes , 2003, The Journal of Neuroscience.
[23] Haim Sompolinsky,et al. Erratum: Population coding in neuronal systems with correlated noise [Phys. Rev. E 64, 051904 (2001)] , 2002 .
[24] Brent Doiron,et al. Theory of oscillatory firing induced by spatially correlated noise and delayed inhibitory feedback. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[25] Wulfram Gerstner,et al. Noise and the PSTH Response to Current Transients: I. General Theory and Application to the Integrate-and-Fire Neuron , 2001, Journal of Computational Neuroscience.
[26] Frances S. Chance,et al. Effects of synaptic noise and filtering on the frequency response of spiking neurons. , 2001, Physical review letters.
[27] Marc Timme,et al. Synaptic Scaling in Combination with Many Generic Plasticity Mechanisms Stabilizes Circuit Connectivity , 2011, Front. Comput. Neurosci..
[28] Timothy A. Machado,et al. Functional connectivity in the retina at the resolution of photoreceptors , 2010, Nature.
[29] Ehud Zohary,et al. Correlated neuronal discharge rate and its implications for psychophysical performance , 1994, Nature.
[30] Alex Roxin,et al. The Role of Degree Distribution in Shaping the Dynamics in Networks of Sparsely Connected Spiking Neurons , 2011, Front. Comput. Neurosci..
[31] E T Rolls,et al. Correlations and the encoding of information in the nervous system , 1999, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[32] Ad Aertsen,et al. Functional consequences of correlated excitatory and inhibitory conductances in cortical networks , 2010, Journal of Computational Neuroscience.
[33] Steven J. Cox,et al. Mathematics for Neuroscientists , 2010 .
[34] Xiao-Jing Wang,et al. Mean-Field Theory of Irregularly Spiking Neuronal Populations and Working Memory in Recurrent Cortical Networks , 2003 .
[35] M. J. Richardson,et al. Firing-rate response of linear and nonlinear integrate-and-fire neurons to modulated current-based and conductance-based synaptic drive. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[36] Brent Doiron,et al. Spatial Profile and Differential Recruitment of GABAB Modulate Oscillatory Activity in Auditory Cortex , 2009, The Journal of Neuroscience.
[37] Aaditya V Rangan. Diagrammatic expansion of pulse-coupled network dynamics. , 2009, Physical review letters.
[38] W. Bair,et al. Correlated Firing in Macaque Visual Area MT: Time Scales and Relationship to Behavior , 2001, The Journal of Neuroscience.
[39] Aaditya V Rangan,et al. Diagrammatic expansion of pulse-coupled network dynamics in terms of subnetworks. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[40] Thomas K. Berger,et al. A synaptic organizing principle for cortical neuronal groups , 2011, Proceedings of the National Academy of Sciences.
[41] Idan Segev,et al. Methods in Neuronal Modeling , 1988 .
[42] H. Risken. Fokker-Planck Equation , 1996 .
[43] Jose-Manuel Alonso,et al. Factors determining the precision of the correlated firing generated by a monosynaptic connection in the cat visual pathway , 2005, The Journal of physiology.
[44] W. J. Nowack. Methods in Neuronal Modeling , 1991, Neurology.
[45] R. G. Medhurst,et al. Topics in the Theory of Random Noise , 1969 .
[46] Theoden I. Netoff,et al. Synchronization from Second Order Network Connectivity Statistics , 2011, Front. Comput. Neurosci..
[47] Eric Shea-Brown,et al. Stimulus-Dependent Correlations and Population Codes , 2008, Neural Computation.
[48] S. Swain. Handbook of Stochastic Methods for Physics, Chemistry and the Natural Sciences , 1984 .
[49] W. Newsome,et al. The Variable Discharge of Cortical Neurons: Implications for Connectivity, Computation, and Information Coding , 1998, The Journal of Neuroscience.
[50] André Longtin,et al. Delayed excitatory and inhibitory feedback shape neural information transmission. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[51] Eric Shea-Brown,et al. Time scales of spike-train correlation for neural oscillators with common drive. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[52] Maurice J Chacron,et al. Noise shaping in neural populations. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.
[53] M. J. Richardson,et al. Rate response of neurons subject to fast or frozen noise: from stochastic and homogeneous to deterministic and heterogeneous populations. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.
[54] P. Kirkwood. On the use and interpretation of cross-correlation measurements in the mammalian central nervous system , 1979, Journal of Neuroscience Methods.
[55] Hongbo Jia,et al. In vivo two-photon imaging of sensory-evoked dendritic calcium signals in cortical neurons , 2011, Nature Protocols.
[56] Stefan Rotter,et al. How Structure Determines Correlations in Neuronal Networks , 2011, PLoS Comput. Biol..
[57] Peter Dayan,et al. The Effect of Correlated Variability on the Accuracy of a Population Code , 1999, Neural Computation.
[58] W. Newsome,et al. Estimates of the Contribution of Single Neurons to Perception Depend on Timescale and Noise Correlation , 2009, The Journal of Neuroscience.
[59] O. Sporns,et al. Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.
[60] L Schimansky-Geier,et al. Transmission of noise coded versus additive signals through a neuronal ensemble. , 2001, Physical review letters.
[61] M. Cohen,et al. Measuring and interpreting neuronal correlations , 2011, Nature Neuroscience.
[62] H. Sompolinsky,et al. Population coding in neuronal systems with correlated noise. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.
[63] D. Q. Nykamp,et al. A mathematical framework for inferring connectivity in probabilistic neuronal networks. , 2007, Mathematical biosciences.
[64] Charles R. Johnson,et al. Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.
[65] P. Latham,et al. Retinal ganglion cells act largely as independent encoders , 2001, Nature.
[66] A. Hawkes. Point Spectra of Some Mutually Exciting Point Processes , 1971 .
[67] R. Romo,et al. Correlated Neuronal Discharges that Increase Coding Efficiency during Perceptual Discrimination , 2003, Neuron.
[68] Bard Ermentrout,et al. When inhibition not excitation synchronizes neural firing , 1994, Journal of Computational Neuroscience.
[69] A. Hawkes. Spectra of some self-exciting and mutually exciting point processes , 1971 .
[70] P. Johannesma,et al. Diffusion Models for the Stochastic Activity of Neurons , 1968 .
[71] A. Pouget,et al. Neural correlations, population coding and computation , 2006, Nature Reviews Neuroscience.
[72] Hilbert J. Kappen,et al. Input-Driven Oscillations in Networks with Excitatory and Inhibitory Neurons with Dynamic Synapses , 2007, Neural Computation.
[73] Sen Song,et al. Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits , 2005, PLoS biology.
[74] Nicolas Brunel,et al. How Connectivity, Background Activity, and Synaptic Properties Shape the Cross-Correlation between Spike Trains , 2009, The Journal of Neuroscience.
[75] Alain Destexhe,et al. Conductance-Based Integrate-and-Fire Models , 1997, Neural Computation.
[76] Anthony N. Burkitt,et al. A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic Input , 2006, Biological Cybernetics.
[77] D. Hansel,et al. How Spike Generation Mechanisms Determine the Neuronal Response to Fluctuating Inputs , 2003, The Journal of Neuroscience.
[78] Tosio Kato. Perturbation theory for linear operators , 1966 .
[79] K. Vahala. Handbook of stochastic methods for physics, chemistry and the natural sciences , 1986, IEEE Journal of Quantum Electronics.
[80] R. Kass,et al. Multiple neural spike train data analysis: state-of-the-art and future challenges , 2004, Nature Neuroscience.