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•	Reliability of spike timing is a general property of spiking model neurons (Brette & Guigon 2003) [Model]

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Goldman MS (2004) Enhancement of information transmission efficiency by synaptic failures. Neural Comput 16:1137-62 [Journal] [PubMed]

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Klein DJ, Simon JZ, Depireux DA, Shamma SA (2006) Stimulus-invariant processing and spectrotemporal reverse correlation in primary auditory cortex. J Comput Neurosci 20:111-36 [Journal] [PubMed]

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•	Nonlinear neuronal computation based on physiologically plausible inputs (McFarland et al. 2013) [Model]

Montemurro MA, Panzeri S, Maravall M, Alenda A, Bale MR, Brambilla M, Petersen RS (2007) Role of precise spike timing in coding of dynamic vibrissa stimuli in somatosensory thalamus. J Neurophysiol 98:1871-82 [Journal] [PubMed]

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Paninski L, Pillow JW, Simoncelli EP (2004) Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model. Neural Comput 16:2533-61 [Journal] [PubMed]

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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]

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•	Stochastic layer V pyramidal neuron: interpulse interval coding and noise (Singh & Levy 2017) [Model]

Thiel A, Greschner M, Ammermüller J (2006) The temporal structure of transient ON/OFF ganglion cell responses and its relation to intra-retinal processing. J Comput Neurosci 21:131-51 [Journal] [PubMed]

Van Rossum MC (2001) The transient precision of integrate and fire neurons: effect of background activity and noise. J Comput Neurosci 10:303-11 [Journal] [PubMed]

Wheeler DW, Kullmann PH, Horn JP (2004) Estimating use-dependent synaptic gain in autonomic ganglia by computational simulation and dynamic-clamp analysis. J Neurophysiol 92:2659-71 [Journal] [PubMed]

•	Sympathetic neuron (Wheeler et al 2004) [Model]