Information Distortion and Neural Coding

Keywords

Coding (social sciences), Artificial neural network, Computer science, Neural coding, Algorithm

References

• Representation of sensory information in the cricket cercal sensory system. II. Information theoretic calculation of system accuracy and optimal tuning-curve widths of four primary interneurons.滋規 田中, 文哲 魏, 尚武 佐藤 — 1991
• Information Theory: 1948-1998 - Guest EditorialSergio Verdú — 1998
• Information theoretic analysis of dynamical encoding by four identified primary sensory interneurons in the cricket cercal system.Frédéric E. Theunissen, J. Cooper Roddey, Steven M. Stufflebeam — 1996
• Entropy and Information TheoryRobert M. Gray — 1990
• Neural networks for pattern recognitionBishop, Christopher M. 1959- — 1995
• Temporal Coding of Visual Information in the ThalamusPamela Reinagel, R. Clay Reid — 2000
• Vector quantization and signal compressionA. Gersho, Robert M. Gray — 1991
• Effects of adaptation on neural coding by primary sensory interneurons in the cricket cercal system.Heather Clague, Frédéric E. Theunissen, John P. Miller — 1997
• Analyzing Sensory Systems with the Information Distortion FunctionAlexander G. Dimitrov, J. Philip Miller — 2000
• On the rationale of maximum-entropy methodsE. T. Jaynes — 1982
• Noise, neural codes and cortical organization.Michael N. Shadlen, William T. Newsome — 1994
• Neural coding and decoding: communication channels and quantizationAlexander G. Dimitrov, J. Philip Miller — 2001
• Spikes: Exploring the Neural CodeFred Rieke, Davd Warland, Rob de Ruyter van Steveninck — 1996
• Entropy and Information in Neural Spike TrainsSteven Strong, R. Köberle, Rob R. de Ruyter van Steveninck — 1996
• Receptive fields, binocular interaction and functional architecture in the cat's visual cortexDavid H. Hubel, T. N. Wiesel — 1962
• Representation of sensory information in the cricket cercal sensory system. I. Response properties of the primary interneurons.J. P. Miller, Gwen A. Jacobs, Frédéric E. Theunissen — 1991
• Information Theory and StatisticsC. C. Craig, S. Kullback — 1960
• The information bottleneck methodPiasini, Eugenio, Fernando C. N. Pereira, William Bialek — 2000
• Elements of Information TheoryThomas M. Cover, Joy A. Thomas — 2001
• A mathematical theory of communicationClaude E. Shannon — 1948

Cited by

• Characterization of the neural codebook in an invertebrate sensory systemZane Aldworth — 2007
• Characterizing the fine structure of a neural sensory code through information distortionAlexander G. Dimitrov, Graham I. Cummins, Aditi Baker — 2011
• Symmetry breaking in soft clustering decoding of neural codesAlexander G. Dimitrov, Albert E. Parker, Tomáš Gedeon — 2009
• Cross-partition clustering: revealing corresponding themes across related datasetsZvika Marx, Ido Dagan, Eli Shamir — 2011
• The Mathematical Structure of Information Bottleneck MethodsTomáš Gedeon, Albert E. Parker, Alexander G. Dimitrov — 2012
• A Generalized Framework for Revealing Analogous Themes across Related TopicsZvika Marx, Ido Dagan, Eli Shamir — 2005
• Bifurcation Structure of a Class of SN-invariant Constrained Optimization ProblemsAlbert E. Parker, Tom� Gedeon — 2004
• Annealing and the normalized N-cutTomáš Gedeon, Albert E. Parker, Collette Campion — 2008
• Annealing and the Rate Distortion ProblemAlbert E. Parker, Tomáv S. Gedeon, Alexander G. Dimitrov — 2002
• Estimation of Entropy and Mutual InformationLiam Paninski — 2003
• SYMMETRY BREAKING BIFURCATIONS OF THE INFORMATION DISTORTIONAlbert E. Parker — 2003
• Modelling Semantic Role Pausibility in Human Sentence ProcessingUlrike Padó, Matthew W. Crocker, Frank Keller — 2006
• A Probabilistic Model of Semantic Plausibility in Sentence ProcessingUlrike Padó, Matthew W. Crocker, Frank Keller — 2009
• Analysis of neural coding through quantization with an information-based distortion measureAlexander G. Dimitrov, John P. Miller, Tomáš Gedeon — 2003
• An Information Theoretic Approach to the Study of Auditory CodingGal Chechik — 2003
• Autonomous cricket biosensors for acoustic localizationT. Mulcahey — 2010
• Stagewise LassoPeng Zhao, Bin Yu — 2007
• The Lack of Convexity of the Relevance-Compression FunctionAlbert E. Parker, Tomáš Gedeon, Alexander G. Dimitrov — 2022
• Symmetry-Breaking Bifurcations of the Information Bottleneck and Related ProblemsAlbert E. Parker, Alexander G. Dimitrov — 2022
• Analysis of neural coding using quantization with an information-based distortion measureA. Dimitrov, John P. Miller, Tomáš Gedeon — 2002

Related papers

• Elements of Information TheoryThomas M. Cover, Joy A. Thomas — 2001
• Agglomerative Information BottleneckNoam Slonim, Naftali Tishby — 1999
• Neural coding and decoding: communication channels and quantizationAlexander G. Dimitrov, J. Philip Miller — 2001
• Deterministic annealing for clustering, compression, classification, regression, and related optimization problemsKenneth Rose — 1998
• On the rationale of maximum-entropy methodsE. T. Jaynes — 1982
• A mathematical theory of communicationClaude E. Shannon — 1948
• Singularities and groups in bifurcation theoryMartin Golubitsky, Ian Stewart, David G. Schaeffer — 1985
• Analysis of neural coding through quantization with an information-based distortion measureAlexander G. Dimitrov, John P. Miller, Tomáš Gedeon — 2003