Aumentado-Armstrong T, Metzen MG, Sproule MK, Chacron MJ. (2015). Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli. PLoS computational biology. 11 [PubMed]

• Midbrain torus semicircularis neuron model (Aumentado-Armstrong et al. 2015) [Model]

Brette R, Guigon E. (2003). Reliability of spike timing is a general property of spiking model neurons. Neural computation. 15 [PubMed]

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

Guyonneau R, VanRullen R, Thorpe SJ. (2005). Neurons tune to the earliest spikes through STDP. Neural computation. 17 [PubMed]

Jacobson GA et al. (2005). Subthreshold voltage noise of rat neocortical pyramidal neurones. The Journal of physiology. 564 [PubMed]

Jolivet R et al. (2008). A benchmark test for a quantitative assessment of simple neuron models. Journal of neuroscience methods. 169 [PubMed]

• Spike Response Model simulator (Jolivet et al. 2004, 2006, 2008) [Model]

Kobayashi R, Tsubo Y, Shinomoto S. (2009). Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold. Frontiers in computational neuroscience. 3 [PubMed]

• Multi-timescale adaptive threshold model (Kobayashi et al 2009) (NEURON) [Model]
• Multi-timescale adaptive threshold model (Kobayashi et al 2009) [Model]

Kretzberg J, Warzecha AK, Egelhaaf M. (2001). Neural coding with graded membrane potential changes and spikes. Journal of computational neuroscience. 11 [PubMed]

Lestienne R. (2001). Spike timing, synchronization and information processing on the sensory side of the central nervous system. Progress in neurobiology. 65 [PubMed]

London M, Roth A, Beeren L, Häusser M, Latham PE. (2010). Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex. Nature. 466 [PubMed]

• Perturbation sensitivity implies high noise and suggests rate coding in cortex (London et al. 2010) [Model]

Lytton WW, Hines ML. (2005). Independent variable time-step integration of individual neurons for network simulations. Neural computation. 17 [PubMed]

• Local variable time step method (Lytton, Hines 2005) [Model]

Marre O, Yger P, Davison AP, Frégnac Y. (2009). Reliable recall of spontaneous activity patterns in cortical networks. The Journal of neuroscience : the official journal of the Society for Neuroscience. 29 [PubMed]

Miller CS, Johnson DH, Schroeter JP, Myint L, Glantz RM. (2003). Visual responses of crayfish ocular motoneurons: an information theoretical analysis. Journal of computational neuroscience. 15 [PubMed]

Nelken I, Chechik G, Mrsic-Flogel TD, King AJ, Schnupp JW. (2005). Encoding stimulus information by spike numbers and mean response time in primary auditory cortex. Journal of computational neuroscience. 19 [PubMed]

Reeke GN, Coop AD. (2004). Estimating the temporal interval entropy of neuronal discharge. Neural computation. 16 [PubMed]

Ros E, Carrillo R, Ortigosa EM, Barbour B, Agís R. (2006). Event-driven simulation scheme for spiking neural networks using lookup tables to characterize neuronal dynamics. Neural computation. 18 [PubMed]

Tang AC, Bartels AM, Sejnowski TJ. (1997). Effects of cholinergic modulation on responses of neocortical neurons to fluctuating input. Cerebral cortex (New York, N.Y. : 1991). 7 [PubMed]

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

Zeldenrust F, Chameau PJ, Wadman WJ. (2013). Reliability of spike and burst firing in thalamocortical relay cells. Journal of computational neuroscience. 35 [PubMed]

• Reliability of Morris-Lecar neurons with added T, h, and AHP currents (Zeldenrust et al. 2013) [Model]