Antunes G, De Schutter E. (2012). A stochastic signaling network mediates the probabilistic induction of cerebellar long-term depression. The Journal of neuroscience : the official journal of the Society for Neuroscience. 32 [PubMed]

• Cerebellar long-term depression (LTD) (Antunes and De Schutter 2012) [Model]

Badoual M et al. (2006). Biophysical and phenomenological models of multiple spike interactions in spike-timing dependent plasticity. International journal of neural systems. 16 [PubMed]

• Biophysical and phenomenological models of spike-timing dependent plasticity (Badoual et al. 2006) [Model]

Bono J, Clopath C. (2017). Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level. Nature communications. 8 [PubMed]

• Modeling dendritic spikes and plasticity (Bono and Clopath 2017) [Model]

Cai Y, Gavornik JP, Cooper LN, Yeung LC, Shouval HZ. (2007). Effect of stochastic synaptic and dendritic dynamics on synaptic plasticity in visual cortex and hippocampus. Journal of neurophysiology. 97 [PubMed]

Clopath C, Büsing L, Vasilaki E, Gerstner W. (2010). Connectivity reflects coding: a model of voltage-based STDP with homeostasis. Nature neuroscience. 13 [PubMed]

• Voltage-based STDP synapse (Clopath et al. 2010) [Model]

Costa RP, Froemke RC, Sjöström PJ, van Rossum MC. (2015). Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning. eLife. 4 [PubMed]

• Memory savings through unified pre- and postsynaptic STDP (Costa et al 2015) [Model]

Cutsuridis V, Cobb S, Graham BP. (2010). Encoding and retrieval in a model of the hippocampal CA1 microcircuit. Hippocampus. 20 [PubMed]

• Encoding and retrieval in a model of the hippocampal CA1 microcircuit (Cutsuridis et al. 2009) [Model]

Deneve S. (2008). Bayesian spiking neurons II: learning. Neural computation. 20 [PubMed]

Gerkin RC, Lau PM, Nauen DW, Wang YT, Bi GQ. (2007). Modular competition driven by NMDA receptor subtypes in spike-timing-dependent plasticity. Journal of neurophysiology. 97 [PubMed]

• STDP and NMDAR Subunits (Gerkin et al. 2007) [Model]

Graupner M, Brunel N. (2007). STDP in a bistable synapse model based on CaMKII and associated signaling pathways. PLoS computational biology. 3 [PubMed]

• CaMKII system exhibiting bistability with respect to calcium (Graupner and Brunel 2007) [Model]

Graupner M, Brunel N. (2012). Calcium-based plasticity model explains sensitivity of synaptic changes to spike pattern, rate, and dendritic location. Proceedings of the National Academy of Sciences of the United States of America. 109 [PubMed]

Gütig R, Sompolinsky H. (2009). Time-warp-invariant neuronal processing. PLoS biology. 7 [PubMed]

• Time-warp-invariant neuronal processing (Gutig & Sompolinsky 2009) [Model]

Morrison A, Aertsen A, Diesmann M. (2007). Spike-timing-dependent plasticity in balanced random networks. Neural computation. 19 [PubMed]

Muller L, Brette R, Gutkin B. (2011). Spike-timing dependent plasticity and feed-forward input oscillations produce precise and invariant spike phase-locking. Frontiers in computational neuroscience. 5 [PubMed]

• STDP and oscillations produce phase-locking (Muller et al. 2011) [Model]

Sadeh S, Clopath C, Rotter S. (2015). Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity. PLoS computational biology. 11 [PubMed]

• Functional balanced networks with synaptic plasticity (Sadeh et al, 2015) [Model]

Tamosiunaite M, Porr B, Wörgötter F. (2007). Self-influencing synaptic plasticity: recurrent changes of synaptic weights can lead to specific functional properties. Journal of computational neuroscience. 23 [PubMed]

• Self-influencing synaptic plasticity (Tamosiunaite et al. 2007) [Model]

Urakubo H, Honda M, Froemke RC, Kuroda S. (2008). Requirement of an allosteric kinetics of NMDA receptors for spike timing-dependent plasticity. The Journal of neuroscience : the official journal of the Society for Neuroscience. 28 [PubMed]

• An allosteric kinetics of NMDARs in STDP (Urakubo et al. 2008) [Model]