Brader JM, Senn W, Fusi S. (2007). Learning real-world stimuli in a neural network with spike-driven synaptic dynamics. Neural computation. 19 [PubMed]
Clopath C, Ziegler L, Vasilaki E, Büsing L, Gerstner W. (2008). Tag-trigger-consolidation: a model of early and late long-term-potentiation and depression. PLoS computational biology. 4 [PubMed]
Curti E, Mongillo G, La Camera G, Amit DJ. (2004). Mean field and capacity in realistic networks of spiking neurons storing sparsely coded random memories. Neural computation. 16 [PubMed]
Molter C, Salihoglu U, Bersini H. (2007). The road to chaos by time-asymmetric Hebbian learning in recurrent neural networks. Neural computation. 19 [PubMed]
Senn W, Fusi S. (2005). Learning only when necessary: better memories of correlated patterns in networks with bounded synapses. Neural computation. 17 [PubMed]
Soltani A, Wang XJ. (2006). A biophysically based neural model of matching law behavior: melioration by stochastic synapses. The Journal of neuroscience : the official journal of the Society for Neuroscience. 26 [PubMed]
Sterratt DC, Graham B, Gillies A, Willshaw D. (2011). Principles of Computational Modelling in Neuroscience, Cambridge University Press.
Toyoizumi T, Pfister JP, Aihara K, Gerstner W. (2007). Optimality model of unsupervised spike-timing-dependent plasticity: synaptic memory and weight distribution. Neural computation. 19 [PubMed]