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Nirenberg S, Latham PE (2003) Decoding neuronal spike trains: how important are correlations? Proc Natl Acad Sci U S A 100:7348-53 [PubMed]

References and models cited by this paper

References and models that cite this paper

Amari S, Nakahara H (2006) Correlation and independence in the neural code. Neural Comput 18:1259-67 [Journal] [PubMed]
Klam F, Zemel RS, Pouget A (2008) Population coding with motion energy filters: the impact of correlations. Neural Comput 20:146-75 [Journal] [PubMed]
Masuda N, Doiron B, Longtin A, Aihara K (2005) Coding of temporally varying signals in networks of spiking neurons with global delayed feedback. Neural Comput 17:2139-75 [Journal] [PubMed]
Michel MM, Jacobs RA (2006) The costs of ignoring high-order correlations in populations of model neurons. Neural Comput 18:660-82 [Journal] [PubMed]
Montemurro MA, Senatore R, Panzeri S (2007) Tight data-robust bounds to mutual information combining shuffling and model selection techniques. Neural Comput 19:2913-57 [Journal] [PubMed]
Shlens J, Kennel MB, Abarbanel HD, Chichilnisky EJ (2007) Estimating information rates with confidence intervals in neural spike trains. Neural Comput 19:1683-719 [Journal] [PubMed]
Simmonds B, Chacron MJ (2015) Activation of parallel fiber feedback by spatially diffuse stimuli reduces signal and noise correlations via independent mechanisms in a cerebellum-like structure. PLoS Comput Biol 11:e1004034 [Journal] [PubMed]
   ELL pyramidal neuron (Simmonds and Chacron 2014) [Model]
(7 refs)