From the statistics of connectivity to the statistics of spike times in neuronal networks
暂无分享,去创建一个
Eric Shea-Brown | Brent Doiron | Michael A Buice | Gabriel Koch Ocker | Yu Hu | Eric T. Shea-Brown | M. Buice | B. Doiron | K. Josić | Yu Hu | G. K. Ocker | R. Rosenbaum | E. Shea-Brown
[1] Carson C. Chow,et al. Correlations, fluctuations, and stability of a finite-size network of coupled oscillators. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[2] Ifije E. Ohiorhenuan,et al. Sparse coding and high-order correlations in fine-scale cortical networks , 2010, Nature.
[3] Kevin L. Briggman,et al. Wiring specificity in the direction-selectivity circuit of the retina , 2011, Nature.
[4] Srdjan Ostojic,et al. Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons , 2014, Nature Neuroscience.
[5] 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.
[6] R. Yuste,et al. Dense Inhibitory Connectivity in Neocortex , 2011, Neuron.
[7] Brent Doiron,et al. Spatial Profile and Differential Recruitment of GABAB Modulate Oscillatory Activity in Auditory Cortex , 2009, The Journal of Neuroscience.
[8] Alois Schlögl,et al. Synaptic mechanisms of pattern completion in the hippocampal CA3 network , 2016, Science.
[9] M. A. Smith,et al. The spatial structure of correlated neuronal variability , 2016, Nature Neuroscience.
[10] C. Petersen,et al. The Excitatory Neuronal Network of the C2 Barrel Column in Mouse Primary Somatosensory Cortex , 2009, Neuron.
[11] Benjamin Lindner,et al. Spike-count distribution in a neuronal population under weak common stimulation. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.
[12] Stefan Rotter,et al. How Structure Determines Correlations in Neuronal Networks , 2011, PLoS Comput. Biol..
[13] Pascal Wallisch,et al. Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate , 2016, The Journal of Neuroscience.
[14] L. Pinneo. On noise in the nervous system. , 1966, Psychological review.
[15] Alexander S. Ecker,et al. On the Structure of Neuronal Population Activity under Fluctuations in Attentional State , 2015, The Journal of Neuroscience.
[16] William R. Gray Roncal,et al. Saturated Reconstruction of a Volume of Neocortex , 2015, Cell.
[17] Wulfram Gerstner,et al. A History of Spike-Timing-Dependent Plasticity , 2011, Front. Syn. Neurosci..
[18] H. Sompolinsky,et al. The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks , 2016, Neuron.
[19] Michael A Buice,et al. Beyond mean field theory: statistical field theory for neural networks , 2013, Journal of statistical mechanics.
[20] Sompolinsky,et al. Theory of correlations in stochastic neural networks. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
[21] Matthieu Gilson,et al. Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks IV , 2009, Biological Cybernetics.
[22] Tatjana Tchumatchenko,et al. Temporal pairwise spike correlations fully capture single-neuron information , 2016, Nature Communications.
[23] Christian K. Machens,et al. Efficient codes and balanced networks , 2016, Nature Neuroscience.
[24] Carson C. Chow,et al. Kinetic theory of coupled oscillators. , 2006, Physical review letters.
[25] D. Fitzpatrick,et al. Orientation Selectivity and the Arrangement of Horizontal Connections in Tree Shrew Striate Cortex , 1997, The Journal of Neuroscience.
[26] A. Aertsen,et al. Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding , 2010, Nature Reviews Neuroscience.
[27] Haim Sompolinsky,et al. Chaotic Balanced State in a Model of Cortical Circuits , 1998, Neural Computation.
[28] Alex Roxin,et al. The Role of Degree Distribution in Shaping the Dynamics in Networks of Sparsely Connected Spiking Neurons , 2011, Front. Comput. Neurosci..
[29] Benjamin Lindner,et al. Slow fluctuations in recurrent networks of spiking neurons. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.
[30] Moritz Helias,et al. The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent Dynamics , 2013, PLoS Comput. Biol..
[31] Alexander S. Ecker,et al. Improved Estimation and Interpretation of Correlations in Neural Circuits , 2015, PLoS Comput. Biol..
[32] Brent Doiron,et al. The mechanics of state-dependent neural correlations , 2016, Nature Neuroscience.
[33] Brent Doiron,et al. Balanced neural architecture and the idling brain , 2014, Front. Comput. Neurosci..
[34] Eric Shea-Brown,et al. Impact of Network Structure and Cellular Response on Spike Time Correlations , 2011, PLoS Comput. Biol..
[35] Robert Rosenbaum,et al. Highly connected neurons spike less frequently in balanced networks. , 2016, Physical review. E.
[36] Brett J. Graham,et al. Anatomy and function of an excitatory network in the visual cortex , 2016, Nature.
[37] Steffen Prohaska,et al. Large-Scale Automated Histology in the Pursuit of Connectomes , 2011, The Journal of Neuroscience.
[38] Moritz Helias,et al. A unified view on weakly correlated recurrent networks , 2013, Front. Comput. Neurosci..
[39] Eric Shea-Brown,et al. A Simple Mechanism for Beyond-Pairwise Correlations in Integrate-and-Fire Neurons , 2015, The Journal of Mathematical Neuroscience (JMN).
[40] J. Cowan,et al. Field-theoretic approach to fluctuation effects in neural networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[41] Eric Shea-Brown,et al. Linking structure and activity in nonlinear spiking networks , 2016, bioRxiv.
[42] Rava Azeredo da Silveira,et al. Structures of Neural Correlation and How They Favor Coding , 2016, Neuron.
[43] Benjamin Lindner,et al. Statistical structure of neural spiking under non-Poissonian or other non-white stimulation , 2015, Journal of Computational Neuroscience.
[44] Wulfram Gerstner,et al. Mathematical formulations of Hebbian learning , 2002, Biological Cybernetics.
[45] David Hansel,et al. Asynchronous Rate Chaos in Spiking Neuronal Circuits , 2015, bioRxiv.
[46] R. Kempter,et al. Hebbian learning and spiking neurons , 1999 .
[47] Brent Doiron,et al. Training and spontaneous reinforcement of neuronal assemblies by spike timing plasticity , 2016 .
[48] D. R. Muir,et al. Functional organization of excitatory synaptic strength in primary visual cortex , 2015, Nature.
[49] J. Lund,et al. Anatomical substrates for functional columns in macaque monkey primary visual cortex. , 2003, Cerebral cortex.
[50] P. Dayan,et al. Supporting Online Material Materials and Methods Som Text Figs. S1 to S9 References the Asynchronous State in Cortical Circuits , 2022 .
[51] Jaime de la Rocha,et al. Supplementary Information for the article ‘ Correlation between neural spike trains increases with firing rate ’ , 2007 .
[52] H. Sompolinsky,et al. Chaos in Neuronal Networks with Balanced Excitatory and Inhibitory Activity , 1996, Science.
[53] Steven J. Cox,et al. Mathematics for Neuroscientists , 2010 .
[54] Eric Shea-Brown,et al. Correlation and synchrony transfer in integrate-and-fire neurons: basic properties and consequences for coding. , 2008, Physical review letters.
[55] Nicolas Brunel,et al. Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons , 2000, Journal of Computational Neuroscience.
[56] Nicolas Brunel,et al. From Spiking Neuron Models to Linear-Nonlinear Models , 2011, PLoS Comput. Biol..
[57] K. Harris,et al. Ultrastructural Analysis of Hippocampal Neuropil from the Connectomics Perspective , 2010, Neuron.
[58] Alexander S. Ecker,et al. State Dependence of Noise Correlations in Macaque Primary Visual Cortex , 2014, Neuron.
[59] Francesca Mastrogiuseppe,et al. Intrinsically-generated fluctuating activity in excitatory-inhibitory networks , 2016, PLoS Comput. Biol..
[60] Eero P. Simoncelli,et al. Partitioning neuronal variability , 2014, Nature Neuroscience.
[61] Emery N. Brown,et al. State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data , 2012, PLoS Comput. Biol..
[62] B. Doiron,et al. Balanced Networks of Spiking Neurons with Spatially Dependent Recurrent Connections , 2013, 1308.6014.
[63] Brent Doiron,et al. Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses , 2015, PLoS Comput. Biol..
[64] Theoden I. Netoff,et al. Synchronization from Second Order Network Connectivity Statistics , 2011, Front. Comput. Neurosci..
[65] Stefan Rotter,et al. Cumulants of Hawkes point processes. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.
[66] Stefan Rotter,et al. Interplay between Graph Topology and Correlations of Third Order in Spiking Neuronal Networks , 2016, PLoS Comput. Biol..
[67] Jonathan Novak,et al. Three lectures on free probability , 2012, 1205.2097.
[68] 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.
[69] D. Plenz,et al. The organizing principles of neuronal avalanches: cell assemblies in the cortex? , 2007, Trends in Neurosciences.
[70] Benjamin Lindner,et al. Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity , 2014, Front. Comput. Neurosci..
[71] Eric Shea-Brown,et al. Local paths to global coherence: cutting networks down to size. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.
[72] Srinivas C. Turaga,et al. Connectomic reconstruction of the inner plexiform layer in the mouse retina , 2013, Nature.
[73] Moritz Helias,et al. Decorrelation of Neural-Network Activity by Inhibitory Feedback , 2012, PLoS Comput. Biol..
[74] T. Harkany,et al. Pyramidal cell communication within local networks in layer 2/3 of rat neocortex , 2003, The Journal of physiology.
[75] Michael J. Berry,et al. Searching for Collective Behavior in a Large Network of Sensory Neurons , 2013, PLoS Comput. Biol..
[76] Thomas K. Berger,et al. A synaptic organizing principle for cortical neuronal groups , 2011, Proceedings of the National Academy of Sciences.
[77] Nicolas Brunel,et al. How Connectivity, Background Activity, and Synaptic Properties Shape the Cross-Correlation between Spike Trains , 2009, The Journal of Neuroscience.
[78] M. Cohen,et al. Measuring and interpreting neuronal correlations , 2011, Nature Neuroscience.
[79] Yoram Burak,et al. Shaping Neural Circuits by High Order Synaptic Interactions , 2016, PLoS Comput. Biol..
[80] Maxwell H. Turner,et al. Direction-Selective Circuits Shape Noise to Ensure a Precise Population Code , 2016, Neuron.
[81] M. A. Smith,et al. Spatial and Temporal Scales of Neuronal Correlation in Primary Visual Cortex , 2008, The Journal of Neuroscience.
[82] D. Feldman. The Spike-Timing Dependence of Plasticity , 2012, Neuron.
[83] Yu Hu,et al. The Sign Rule and Beyond: Boundary Effects, Flexibility, and Noise Correlations in Neural Population Codes , 2013, PLoS Comput. Biol..
[84] W. Bair,et al. Correlated Firing in Macaque Visual Area MT: Time Scales and Relationship to Behavior , 2001, The Journal of Neuroscience.
[85] Michael A. Buice,et al. Systematic Fluctuation Expansion for Neural Network Activity Equations , 2009, Neural Computation.
[86] Aaditya V Rangan. Diagrammatic expansion of pulse-coupled network dynamics. , 2009, Physical review letters.
[87] Sen Song,et al. Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits , 2005, PLoS biology.
[88] Stefan Rotter,et al. Recurrent interactions in spiking networks with arbitrary topology. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.
[89] Brent Doiron,et al. Oscillatory activity in electrosensory neurons increases with the spatial correlation of the stochastic input stimulus. , 2004, Physical review letters.
[90] T. Sejnowski. On the stochastic dynamics of neuronal interaction , 1976, Biological Cybernetics.
[91] D. Amit,et al. Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. , 1997, Cerebral cortex.
[92] Arthur W. Wetzel,et al. Network anatomy and in vivo physiology of visual cortical neurons , 2011, Nature.
[93] Michael A. Buice,et al. Dynamic Finite Size Effects in Spiking Neural Networks , 2013, PLoS Comput. Biol..
[94] A. Pouget,et al. Information-limiting correlations , 2014, Nature Neuroscience.
[95] D. McCormick,et al. Waking State: Rapid Variations Modulate Neural and Behavioral Responses , 2015, Neuron.
[96] A. Hawkes. Spectra of some self-exciting and mutually exciting point processes , 1971 .
[97] Eric Shea-Brown,et al. Motif statistics and spike correlations in neuronal networks , 2012, BMC Neuroscience.