Azhar F, Anderson WS. (2012). Predicting single-neuron activity in locally connected networks. Neural computation. 24 [PubMed]

• Network model with neocortical architecture (Anderson et al 2007,2012; Azhar et al 2012) [Model]

Béhuret S, Deleuze C, Gomez L, Frégnac Y, Bal T. (2013). Cortically-controlled population stochastic facilitation as a plausible substrate for guiding sensory transfer across the thalamic gateway PLoS computational biology. 9 [PubMed]

• A Model Circuit of Thalamocortical Convergence (Behuret et al. 2013) [Model]

Cayco-Gajic NA, Clopath C, Silver RA. (2017). Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks. Nature communications. 8 [PubMed]

• Sparse connectivity is required for decorrelation, pattern separation (Cayco-Gajic et al 2017) [Model]

Hjorth J, Blackwell KT, Kotaleski JH. (2009). Gap junctions between striatal fast-spiking interneurons regulate spiking activity and synchronization as a function of cortical activity. The Journal of neuroscience : the official journal of the Society for Neuroscience. 29 [PubMed]

• Gap junction coupled network of striatal fast spiking interneurons (Hjorth et al. 2009) [Model]

Hong S, Ratté S, Prescott SA, De Schutter E. (2012). Single neuron firing properties impact correlation-based population coding. The Journal of neuroscience : the official journal of the Society for Neuroscience. 32 [PubMed]

• A model for how correlation depends on the neuronal excitability type (Hong et al. 2012) [Model]

Klam F, Zemel RS, Pouget A. (2008). Population coding with motion energy filters: the impact of correlations. Neural computation. 20 [PubMed]

Marre O, El Boustani S, Frégnac Y, Destexhe A. (2009). Prediction of spatiotemporal patterns of neural activity from pairwise correlations. Physical review letters. 102 [PubMed]

• Maximum entropy model to predict spatiotemporal spike patterns (Marre et al. 2009) [Model]

Montemurro MA, Senatore R, Panzeri S. (2007). Tight data-robust bounds to mutual information combining shuffling and model selection techniques. Neural computation. 19 [PubMed]

Rossant C, Leijon S, Magnusson AK, Brette R. (2011). Sensitivity of noisy neurons to coincident inputs. The Journal of neuroscience : the official journal of the Society for Neuroscience. 31 [PubMed]

• Sensitivity of noisy neurons to coincident inputs (Rossant et al. 2011) [Model]

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 computational biology. 11 [PubMed]

• ELL pyramidal neuron (Simmonds and Chacron 2014) [Model]

Swindale NV. (2008). Feedback decoding of spatially structured population activity in cortical maps. Neural computation. 20 [PubMed]

Wang HP, Spencer D, Fellous JM, Sejnowski TJ. (2010). Synchrony of thalamocortical inputs maximizes cortical reliability. Science (New York, N.Y.). 328 [PubMed]