Higher-Order Interactions Characterized in Cortical Activity
暂无分享,去创建一个
[1] W. Singer,et al. Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties , 1989, Nature.
[2] S. Bressler,et al. Episodic multiregional cortical coherence at multiple frequencies during visual task performance , 1993, Nature.
[3] E. Vaadia,et al. Spatiotemporal firing patterns in the frontal cortex of behaving monkeys. , 1993, Journal of neurophysiology.
[4] C. Koch,et al. Recurrent excitation in neocortical circuits , 1995, Science.
[5] A. Aertsen,et al. Dynamics of neuronal interactions in monkey cortex in relation to behavioural events , 1995, Nature.
[6] A. Aertsen,et al. Spike synchronization and rate modulation differentially involved in motor cortical function. , 1997, Science.
[7] Wolf Singer,et al. Neuronal Synchrony: A Versatile Code for the Definition of Relations? , 1999, Neuron.
[8] F. Varela,et al. Perception's shadow: long-distance synchronization of human brain activity , 1999, Nature.
[9] Shun-ichi Amari,et al. Information geometry on hierarchy of probability distributions , 2001, IEEE Trans. Inf. Theory.
[10] Shun-ichi Amari,et al. Information-Geometric Measure for Neural Spikes , 2002, Neural Computation.
[11] Yutaka Sakai,et al. Synchronous Firing and Higher-Order Interactions in Neuron Pool , 2003, Neural Computation.
[12] Eric B. Baum,et al. What is thought? , 2003 .
[13] John M. Beggs,et al. Neuronal Avalanches in Neocortical Circuits , 2003, The Journal of Neuroscience.
[14] A. Destexhe,et al. A method to estimate synaptic conductances from membrane potential fluctuations. , 2004, Journal of neurophysiology.
[15] M. DeWeese,et al. Non-Gaussian Membrane Potential Dynamics Imply Sparse, Synchronous Activity in Auditory Cortex , 2006, The Journal of Neuroscience.
[16] Michael J. Berry,et al. Weak pairwise correlations imply strongly correlated network states in a neural population , 2005, Nature.
[17] D. Plenz,et al. Inverted-U Profile of Dopamine–NMDA-Mediated Spontaneous Avalanche Recurrence in Superficial Layers of Rat Prefrontal Cortex , 2006, The Journal of Neuroscience.
[18] Jonathon Shlens,et al. The Structure of Multi-Neuron Firing Patterns in Primate Retina , 2006, The Journal of Neuroscience.
[19] O. Kinouchi,et al. Optimal dynamical range of excitable networks at criticality , 2006, q-bio/0601037.
[20] D. Plenz,et al. The organizing principles of neuronal avalanches: cell assemblies in the cortex? , 2007, Trends in Neurosciences.
[21] S. Kauffman,et al. Measures for information propagation in Boolean networks , 2007 .
[22] Shan Yu,et al. A Small World of Neuronal Synchrony , 2008, Cerebral cortex.
[23] D. Plenz,et al. Homeostasis of neuronal avalanches during postnatal cortex development in vitro , 2008, Journal of Neuroscience Methods.
[24] John M. Beggs,et al. A Maximum Entropy Model Applied to Spatial and Temporal Correlations from Cortical Networks In Vitro , 2008, The Journal of Neuroscience.
[25] D. Plenz,et al. Neuronal avalanches organize as nested theta- and beta/gamma-oscillations during development of cortical layer 2/3 , 2008, Proceedings of the National Academy of Sciences.
[26] Maik C. Stüttgen,et al. Psychophysical and neurometric detection performance under stimulus uncertainty , 2008, Nature Neuroscience.
[27] Jason Wolfe,et al. Sparse temporal coding of elementary tactile features during active whisker sensation , 2009, Nature Neuroscience.
[28] Haim Sompolinsky,et al. Stimulus-Dependent Correlations in Threshold-Crossing Spiking Neurons , 2009, Neural Computation.
[29] Takeshi Kaneko,et al. Recurrent Infomax Generates Cell Assemblies, Neuronal Avalanches, and Simple Cell-Like Selectivity , 2009, Neural Computation.
[30] Woodrow L. Shew,et al. Neuronal Avalanches Imply Maximum Dynamic Range in Cortical Networks at Criticality , 2009, The Journal of Neuroscience.
[31] Jonathon Shlens,et al. The Structure of Large-Scale Synchronized Firing in Primate Retina , 2009, The Journal of Neuroscience.
[32] Stefano Panzeri,et al. The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[33] Alexander S. Ecker,et al. Generating Spike Trains with Specified Correlation Coefficients , 2009, Neural Computation.
[34] D. Plenz,et al. Spontaneous cortical activity in awake monkeys composed of neuronal avalanches , 2009, Proceedings of the National Academy of Sciences.
[35] O. Sporns,et al. Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.
[36] Peter E. Latham,et al. Pairwise Maximum Entropy Models for Studying Large Biological Systems: When They Can Work and When They Can't , 2008, PLoS Comput. Biol..
[37] S. Leibler,et al. Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods , 2009, Proceedings of the National Academy of Sciences.
[38] Michael Okun,et al. The Subthreshold Relation between Cortical Local Field Potential and Neuronal Firing Unveiled by Intracellular Recordings in Awake Rats , 2010, The Journal of Neuroscience.
[39] Jonathan D. Victor,et al. Information-geometric measure of 3-neuron firing patterns characterizes scale-dependence in cortical networks , 2011, Journal of Computational Neuroscience.
[40] Ifije E. Ohiorhenuan,et al. Sparse coding and high-order correlations in fine-scale cortical networks , 2010, Nature.
[41] Dietmar Plenz,et al. Hierarchical Interaction Structure of Neural Activities in Cortical Slice Cultures , 2010, The Journal of Neuroscience.
[42] D. Plenz,et al. Coherence Potentials: Loss-Less, All-or-None Network Events in the Cortex , 2010, PLoS biology.
[43] M. Nicolelis,et al. Spike Avalanches Exhibit Universal Dynamics across the Sleep-Wake Cycle , 2010, PloS one.
[44] Fredric M. Wolf,et al. Frontiers in Computational Neuroscience Materials and Methods Measures of Correlation , 2022 .
[45] W. Singer,et al. Neuronal avalanches in spontaneous activity in vivo. , 2010, Journal of neurophysiology.
[46] R. Segev,et al. Sparse low-order interaction network underlies a highly correlated and learnable neural population code , 2011, Proceedings of the National Academy of Sciences.
[47] Randy M. Bruno,et al. Effects and Mechanisms of Wakefulness on Local Cortical Networks , 2011, Neuron.
[48] Woodrow L. Shew,et al. Information Capacity and Transmission Are Maximized in Balanced Cortical Networks with Neuronal Avalanches , 2010, The Journal of Neuroscience.
[49] M. Bethge,et al. Common input explains higher-order correlations and entropy in a simple model of neural population activity. , 2011, Physical review letters.
[50] R. Segev,et al. The Architecture of Functional Interaction Networks in the Retina , 2011, The Journal of Neuroscience.
[51] Andreas Klaus,et al. Statistical Analyses Support Power Law Distributions Found in Neuronal Avalanches , 2011, PloS one.