Input nonlinearities can shape beyond-pairwise correlations and improve information transmission by neural populations.
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[1] Geoffrey E. Hinton,et al. Deep Boltzmann Machines , 2009, AISTATS.
[2] Shan Yu,et al. Higher-Order Interactions Characterized in Cortical Activity , 2011, The Journal of Neuroscience.
[3] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[4] A. Destexhe,et al. Synaptic background activity enhances the responsiveness of neocortical pyramidal neurons. , 2000, Journal of neurophysiology.
[5] Jonathon Shlens,et al. The Structure of Large-Scale Synchronized Firing in Primate Retina , 2009, The Journal of Neuroscience.
[6] E. Jaynes. Information Theory and Statistical Mechanics , 1957 .
[7] Eric Shea-Brown,et al. Stimulus-Dependent Correlations and Population Codes , 2008, Neural Computation.
[8] Wolfgang Maass,et al. Computing with spiking neurons , 1999 .
[9] Bartlett W. Mel. Synaptic integration in an excitable dendritic tree. , 1993, Journal of neurophysiology.
[10] Ifije E. Ohiorhenuan,et al. Sparse coding and high-order correlations in fine-scale cortical networks , 2010, Nature.
[11] Eric Shea-Brown,et al. When do microcircuits produce beyond-pairwise correlations? , 2014, Front. Comput. Neurosci..
[12] Alexandre Pouget,et al. Insights from a Simple Expression for Linear Fisher Information in a Recurrently Connected Population of Spiking Neurons , 2011, Neural Computation.
[13] Bruno A. Olshausen,et al. Modeling Higher-Order Correlations within Cortical Microcolumns , 2014, PLoS Comput. Biol..
[14] M. DeWeese,et al. Non-Gaussian Membrane Potential Dynamics Imply Sparse, Synchronous Activity in Auditory Cortex , 2006, The Journal of Neuroscience.
[15] Daniel L. Ruderman,et al. Origins of scaling in natural images , 1996, Vision Research.
[16] Yu Hu,et al. The Sign Rule and Beyond: Boundary Effects, Flexibility, and Noise Correlations in Neural Population Codes , 2013, PLoS Comput. Biol..
[17] Gasper Tkacik,et al. Optimal population coding by noisy spiking neurons , 2010, Proceedings of the National Academy of Sciences.
[18] Shun-ichi Amari,et al. Information geometry on hierarchy of probability distributions , 2001, IEEE Trans. Inf. Theory.
[19] 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.
[20] T. Hromádka,et al. Sparse Representation of Sounds in the Unanesthetized Auditory Cortex , 2008, PLoS biology.
[21] David Pfau,et al. Dead leaves and the dirty ground: low-level image statistics in transmissive and occlusive imaging environments. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.
[22] Michael J. Berry,et al. Searching for Collective Behavior in a Large Network of Sensory Neurons , 2013, PLoS Comput. Biol..
[23] W. Bialek,et al. Statistical thermodynamics of natural images. , 2008, Physical review letters.
[24] Michael J. Berry,et al. Weak pairwise correlations imply strongly correlated network states in a neural population , 2005, Nature.
[25] Eric Shea-Brown,et al. A Simple Mechanism for Beyond-Pairwise Correlations in Integrate-and-Fire Neurons , 2015, The Journal of Mathematical Neuroscience (JMN).
[26] Vijay Balasubramanian,et al. Natural Images from the Birthplace of the Human Eye , 2011, PloS one.
[27] Eero P. Simoncelli,et al. Natural image statistics and neural representation. , 2001, Annual review of neuroscience.
[28] Michael Robert DeWeese,et al. A Sparse Coding Model with Synaptically Local Plasticity and Spiking Neurons Can Account for the Diverse Shapes of V1 Simple Cell Receptive Fields , 2011, PLoS Comput. Biol..
[29] R. Quian Quiroga. Principles of neural coding. , 2011, Current biology : CB.
[30] David R. Brillinger,et al. Empirical examination of the threshold model of neuron firing , 1979, Biological Cybernetics.
[31] Nelson Spruston,et al. Synaptic amplification by dendritic spines enhances input cooperativity , 2012, Nature.
[32] Yutaka Sakai,et al. Synchronous Firing and Higher-Order Interactions in Neuron Pool , 2003, Neural Computation.
[33] Michael J. Berry,et al. Network information and connected correlations. , 2003, Physical review letters.
[34] Geoffrey E. Hinton,et al. OPTIMAL PERCEPTUAL INFERENCE , 1983 .
[35] Haim Sompolinsky,et al. Nonlinear Population Codes , 2004, Neural Computation.
[36] Jonathon Shlens,et al. The Structure of Multi-Neuron Firing Patterns in Primate Retina , 2006, The Journal of Neuroscience.
[37] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[38] Konrad P Kording,et al. How advances in neural recording affect data analysis , 2011, Nature Neuroscience.
[39] Alexander S. Ecker,et al. The Effect of Noise Correlations in Populations of Diversely Tuned Neurons , 2011, The Journal of Neuroscience.
[40] 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.
[41] Elad Schneidman,et al. Stimulus-dependent Maximum Entropy Models of Neural Population Codes , 2012, PLoS Comput. Biol..
[42] Michael I. Jordan,et al. Advances in Neural Information Processing Systems 30 , 1995 .
[43] Christopher J. Bishop,et al. Pulsed Neural Networks , 1998 .
[44] L. Abbott,et al. Responses of neurons in primary and inferior temporal visual cortices to natural scenes , 1997, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[45] Ehud Zohary,et al. Correlated neuronal discharge rate and its implications for psychophysical performance , 1994, Nature.
[46] W. Wildman,et al. Theoretical Neuroscience , 2014 .
[47] R. Rosenfeld. Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.
[48] Eric Shea-Brown,et al. Triplet correlations among similarly tuned cells impact population coding , 2015, Front. Comput. Neurosci..
[49] Aapo Hyvärinen,et al. Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS) , 2010 .
[50] A. Pouget,et al. Neural correlations, population coding and computation , 2006, Nature Reviews Neuroscience.
[51] Joel Zylberberg,et al. Inhibitory Interneurons Decorrelate Excitatory Cells to Drive Sparse Code Formation in a Spiking Model of V1 , 2013, The Journal of Neuroscience.
[52] M. Bethge,et al. Common input explains higher-order correlations and entropy in a simple model of neural population activity. , 2011, Physical review letters.
[53] Michael Robert DeWeese,et al. Sparse Coding Models Can Exhibit Decreasing Sparseness while Learning Sparse Codes for Natural Images , 2013, PLoS Comput. Biol..
[54] Bartlett W. Mel,et al. Computational subunits in thin dendrites of pyramidal cells , 2004, Nature Neuroscience.
[55] B. Kampa,et al. Synaptic integration in dendritic trees. , 2005, Journal of neurobiology.
[56] F. Rieke,et al. Noise correlations improve response fidelity and stimulus encoding , 2010, Nature.
[57] R. Millane,et al. Effects of occlusion, edges, and scaling on the power spectra of natural images. , 2005, Journal of the Optical Society of America. A, Optics, image science, and vision.
[58] William Bialek,et al. Statistics of Natural Images: Scaling in the Woods , 1993, NIPS.