Dynamic state estimation based on Poisson spike trains—towards a theory of optimal encoding
暂无分享,去创建一个
[1] Terrence J. Sejnowski,et al. Neuronal Tuning: To Sharpen or Broaden? , 1999, Neural Computation.
[2] S. Denéve,et al. Neural processing as causal inference , 2011, Current Opinion in Neurobiology.
[3] Yonina C. Eldar,et al. Bayesian Filtering in Spiking Neural Networks: Noise, Adaptation, and Multisensory Integration , 2009, Neural Computation.
[4] Gasper Tkacik,et al. Optimal population coding by noisy spiking neurons , 2010, Proceedings of the National Academy of Sciences.
[5] Matthias Bethge,et al. Optimal Short-Term Population Coding: When Fisher Information Fails , 2002, Neural Computation.
[6] C. Gardiner. Handbook of Stochastic Methods , 1983 .
[7] Peter Dayan,et al. Encoding and Decoding Spikes for Dynamic Stimuli , 2008, Neural Computation.
[8] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[9] B. Rozovskii,et al. The Oxford Handbook of Nonlinear Filtering , 2011 .
[10] Nicolas Brunel,et al. Mutual Information, Fisher Information, and Population Coding , 1998, Neural Computation.
[11] B. McNaughton,et al. Place cells, head direction cells, and the learning of landmark stability , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[12] Daniel Pérez Palomar,et al. Representation of Mutual Information Via Input Estimates , 2007, IEEE Transactions on Information Theory.
[13] Sophie Denève,et al. Spike-Based Population Coding and Working Memory , 2011, PLoS Comput. Biol..
[14] P. Dayan,et al. Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials , 2010, Nature Neuroscience.
[15] Alex K. Susemihl,et al. Analytical Results for the Error in Filtering of Gaussian Processes , 2011, NIPS.
[16] Shlomo Shamai,et al. Mutual Information and Conditional Mean Estimation in Poisson Channels , 2004, IEEE Transactions on Information Theory.
[17] Donald L. Snyder,et al. Filtering and detection for doubly stochastic Poisson processes , 1972, IEEE Trans. Inf. Theory.
[18] David Holcman,et al. Time scale of diffusion in molecular and cellular biology , 2014 .
[19] Denis Fize,et al. Speed of processing in the human visual system , 1996, Nature.
[20] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[21] C E Shannon,et al. The mathematical theory of communication. 1963. , 1997, M.D. computing : computers in medical practice.
[22] Peter Dayan,et al. Fast Population Coding , 2007, Neural Computation.
[23] Donald L. Snyder,et al. Random Point Processes in Time and Space , 1991 .
[24] Neri Merhav. Optimum Estimation via Gradients of Partition Functions and Information Measures: A Statistical-Mechanical Perspective , 2011, IEEE Transactions on Information Theory.
[25] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[26] D. Knill,et al. The Bayesian brain: the role of uncertainty in neural coding and computation , 2004, Trends in Neurosciences.
[27] Alexander S. Ecker,et al. Reassessing optimal neural population codes with neurometric functions , 2011, Proceedings of the National Academy of Sciences.
[28] J. O'Keefe,et al. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. , 1971, Brain research.
[29] Y. Gutfreund,et al. Adaptation in the auditory space map of the barn owl. , 2006, Journal of neurophysiology.
[30] C. E. SHANNON,et al. A mathematical theory of communication , 1948, MOCO.
[31] Joseph J Atick,et al. Could information theory provide an ecological theory of sensory processing? , 2011, Network.
[32] S. Swain. Handbook of Stochastic Methods for Physics, Chemistry and the Natural Sciences , 1984 .
[33] Matthias Bethge,et al. Bayesian Population Decoding of Spiking Neurons , 2009, Frontiers Comput. Neurosci..
[34] Demosthenis Teneketzis,et al. Optimal Design of Sequential Real-Time Communication Systems , 2009, IEEE Transactions on Information Theory.
[35] C. W. Gardiner,et al. Handbook of stochastic methods - for physics, chemistry and the natural sciences, Second Edition , 1986, Springer series in synergetics.
[36] Matteo Carandini,et al. Coding of stimulus sequences by population responses in visual cortex , 2009, Nature Neuroscience.
[37] Alexandre Pouget,et al. Insights from a Simple Expression for Linear Fisher Information in a Recurrently Connected Population of Spiking Neurons , 2011, Neural Computation.
[38] Ron Meir,et al. Error-Based Analysis of Optimal Tuning Functions Explains Phenomena Observed in Sensory Neurons , 2010, Front. Comput. Neurosci..
[39] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[40] E. Salinas,et al. Perceptual decision making in less than 30 milliseconds , 2010, Nature Neuroscience.
[41] M. Ernst,et al. Humans integrate visual and haptic information in a statistically optimal fashion , 2002, Nature.
[42] Petros G. Voulgaris,et al. On optimal ℓ∞ to ℓ∞ filtering , 1995, Autom..
[43] Christian P. Robert,et al. The Bayesian choice : from decision-theoretic foundations to computational implementation , 2007 .
[44] Tsachy Weissman,et al. Mutual information, relative entropy, and estimation in the Poisson channel , 2010, 2011 IEEE International Symposium on Information Theory Proceedings.