Finite State Automata Resulting from Temporal Information Maximization and a Temporal Learning Rule
暂无分享,去创建一个
[1] Daniel P. F. Sturdy,et al. The connectivity of the brain: multi-level quantitative analysis , 1995, Biological Cybernetics.
[2] Anders Krogh,et al. Introduction to the theory of neural computation , 1994, The advanced book program.
[3] Naftali Tishby,et al. Hidden Markov modelling of simultaneously recorded cells in the associative cortex of behaving monkeys , 1997 .
[4] Günther Palm,et al. Detecting higher-order interactions among the spiking events in a group of neurons , 1995, Biological Cybernetics.
[5] Thomas Wennekers,et al. Spatial and Temporal Stochastic Interaction in Neuronal Assemblies , 2003 .
[6] Eero P. Simoncelli,et al. Natural image statistics and neural representation. , 2001, Annual review of neuroscience.
[7] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[8] H Barlow,et al. Redundancy reduction revisited , 2001, Network.
[9] Penio S. Penev,et al. Local feature analysis: A general statistical theory for object representation , 1996 .
[10] M. Studený,et al. The Multiinformation Function as a Tool for Measuring Stochastic Dependence , 1998, Learning in Graphical Models.
[11] Haim Sompolinsky,et al. Learning Input Correlations through Nonlinear Temporally Asymmetric Hebbian Plasticity , 2003, The Journal of Neuroscience.
[12] Zhaoping Li,et al. Toward a Theory of the Striate Cortex , 1994, Neural Computation.
[13] Tj Sejnowski,et al. Neural Codes and Distributed Representations , 1999 .
[14] G. Edelman,et al. A measure for brain complexity: relating functional segregation and integration in the nervous system. , 1994, Proceedings of the National Academy of Sciences of the United States of America.
[15] Y. Dan,et al. Spike-timing-dependent synaptic modification induced by natural spike trains , 2002, Nature.
[16] D. O. Hebb,et al. The organization of behavior , 1988 .
[17] Moshe Abeles,et al. Corticonics: Neural Circuits of Cerebral Cortex , 1991 .
[18] Adrienne L. Fairhall,et al. Efficiency and ambiguity in an adaptive neural code , 2001, Nature.
[19] R Linsker,et al. From basic network principles to neural architecture: emergence of spatial-opponent cells. , 1986, Proceedings of the National Academy of Sciences of the United States of America.
[20] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[21] M K Habib,et al. Dynamics of neuronal firing correlation: modulation of "effective connectivity". , 1989, Journal of neurophysiology.
[22] W Singer,et al. Visual feature integration and the temporal correlation hypothesis. , 1995, Annual review of neuroscience.
[23] A. Aertsen,et al. Neuronal assemblies , 1989, IEEE Transactions on Biomedical Engineering.
[24] William Bialek,et al. Spikes: Exploring the Neural Code , 1996 .
[25] G Tononi,et al. Measures of degeneracy and redundancy in biological networks. , 1999, Proceedings of the National Academy of Sciences of the United States of America.
[26] Nihat Ay,et al. Locality of Global Stochastic Interaction in Directed Acyclic Networks , 2002, Neural Computation.
[27] J L Gallant,et al. Sparse coding and decorrelation in primary visual cortex during natural vision. , 2000, Science.
[28] Ay Nihat,et al. Information Geometry on Complexity and Stochastic Interaction , 2001 .
[29] R Linsker,et al. From basic network principles to neural architecture: emergence of orientation-selective cells. , 1986, Proceedings of the National Academy of Sciences of the United States of America.
[30] R Linsker,et al. From basic network principles to neural architecture: emergence of orientation columns. , 1986, Proceedings of the National Academy of Sciences of the United States of America.
[31] E. Vaadia,et al. Spatiotemporal firing patterns in the frontal cortex of behaving monkeys. , 1993, Journal of neurophysiology.
[32] Gal Chechik,et al. Spike-Timing-Dependent Plasticity and Relevant Mutual Information Maximization , 2003, Neural Computation.
[33] Ad Aertsen,et al. Editorial: Cell Assemblies , 2003 .
[34] Thomas Wennekers,et al. A temporal learning rule in recurrent systems supports high spatio-temporal stochastic interactions , 2006, Neurocomputing.
[35] G. Palm. Neural Assemblies , 1982, Studies of Brain Function.
[36] Reinhard Eckhorn,et al. Neural mechanisms of scene segmentation: recordings from the visual cortex suggest basic circuits for linking field models , 1999, IEEE Trans. Neural Networks.
[37] Jeffrey D. Ullman,et al. Introduction to Automata Theory, Languages and Computation , 1979 .
[38] Naftali Tishby,et al. Cortical activity flips among quasi-stationary states. , 1995, Proceedings of the National Academy of Sciences of the United States of America.
[39] Shun-ichi Amari,et al. Information geometry on hierarchy of probability distributions , 2001, IEEE Trans. Inf. Theory.
[40] Thomas Wennekers,et al. Dynamical properties of strongly interacting Markov chains , 2003, Neural Networks.
[41] Lucas C. Parra,et al. Maximising Sensitivity in a Spiking Network , 2004, NIPS.
[42] Terrence J. Sejnowski,et al. Neural codes and distributed representations: foundations of neural computation , 1999 .
[43] A. J. Bell,et al. A Unifying Information-Theoretic Framework for Independent Component Analysis , 2000 .
[44] Olaf Sporns,et al. Connectivity and complexity: the relationship between neuroanatomy and brain dynamics , 2000, Neural Networks.
[45] Shun-ichi Amari,et al. Information-Geometric Measure for Neural Spikes , 2002, Neural Computation.
[46] Kathryn B. Laskey,et al. Neural Coding: Higher-Order Temporal Patterns in the Neurostatistics of Cell Assemblies , 2000, Neural Computation.
[47] G. Bi,et al. Synaptic modification by correlated activity: Hebb's postulate revisited. , 2001, Annual review of neuroscience.