Models that contain the Model Concept : STDP

(Spike Timing Dependent Plasticity: the relative timing of spikes in pre- and post-synaptic neurons can induce long term potentiation or depression at their shared synapse(s) and neighboring synapses.)
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1. A simple model of neuromodulatory state-dependent synaptic plasticity (Pedrosa and Clopath, 2016)
2. Adaptive robotic control driven by a versatile spiking cerebellar network (Casellato et al. 2014)
3. An allosteric kinetics of NMDARs in STDP (Urakubo et al. 2008)
4. Biophysical and phenomenological models of spike-timing dependent plasticity (Badoual et al. 2006)
5. CA1 pyramidal neuron: synaptic plasticity during theta cycles (Saudargiene et al. 2015)
6. Calcium influx during striatal upstates (Evans et al. 2013)
7. Calcium response prediction in the striatal spines depending on input timing (Nakano et al. 2013)
8. Cancelling redundant input in ELL pyramidal cells (Bol et al. 2011)
9. Computing with neural synchrony (Brette 2012)
10. Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015)
11. Cortico-striatal plasticity in medium spiny neurons (Gurney et al 2015)
12. Diffusive homeostasis in a spiking network model (Sweeney et al. 2015)
13. Effects of increasing CREB on storage and recall processes in a CA1 network (Bianchi et al. 2014)
14. Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011)
15. Encoding and retrieval in a model of the hippocampal CA1 microcircuit (Cutsuridis et al. 2009)
16. Endocannabinoid dynamics gate spike-timing dependent depression and potentiation (Cui et al 2016)
17. Fast convergence of cerebellar learning (Luque et al. 2015)
18. Formation of synfire chains (Jun and Jin 2007)
19. Inhibitory plasticity balances excitation and inhibition (Vogels et al. 2011)
20. Learning spatial transformations through STDP (Davison, Frégnac 2006)
21. Linking STDP and Dopamine action to solve the distal reward problem (Izhikevich 2007)
22. Memory savings through unified pre- and postsynaptic STDP (Costa et al 2015)
23. Microsaccades and synchrony coding in the retina (Masquelier et al. 2016)
24. Modeling dendritic spikes and plasticity (Bono and Clopath 2017)
25. Modeling dentate granule cells heterosynaptic plasticity using STDP-BCM rule (Jedlicka et al. 2015)
26. Motor system model with reinforcement learning drives virtual arm (Dura-Bernal et al 2017)
27. NMDA subunit effects on Calcium and STDP (Evans et al. 2012)
28. Optimal spatiotemporal spike pattern detection by STDP (Masquelier 2017)
29. Oscillations, phase-of-firing coding and STDP: an efficient learning scheme (Masquelier et al. 2009)
30. Polychronization: Computation With Spikes (Izhikevich 2005)
31. Pyramidal neuron conductances state and STDP (Delgado et al. 2010)
32. Relative spike time coding and STDP-based orientation selectivity in V1 (Masquelier 2012)
33. Reproducing infra-slow oscillations with dopaminergic modulation (Kobayashi et al 2017)
34. Reward modulated STDP (Legenstein et al. 2008)
35. Self-influencing synaptic plasticity (Tamosiunaite et al. 2007)
36. Sensorimotor cortex reinforcement learning of 2-joint virtual arm reaching (Neymotin et al. 2013)
37. Simulated cortical color opponent receptive fields self-organize via STDP (Eguchi et al., 2014)
38. Spikes,synchrony,and attentive learning by laminar thalamocort. circuits (Grossberg & Versace 2007)
39. Stability of complex spike timing-dependent plasticity in cerebellar learning (Roberts 2007)
40. STDP allows fast rate-modulated coding with Poisson-like spike trains (Gilson et al. 2011)
41. STDP and NMDAR Subunits (Gerkin et al. 2007)
42. STDP depends on dendritic synapse location (Letzkus et al. 2006)
43. STDP promotes synchrony of inhibitory networks in the presence of heterogeneity (Talathi et al 2008)
44. Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013)
45. Theta phase precession in a model CA3 place cell (Baker and Olds 2007)
46. Voltage-based STDP synapse (Clopath et al. 2010)

Re-display model names with descriptions