scholarly journals Spike-timing dependent plasticity and homeostasis: Composition of two different synaptic learning mechanism

Author(s):  
Wörgötter Florentin
2008 ◽  
Vol 21 (9) ◽  
pp. 1318-1327 ◽  
Author(s):  
QingXiang Wu ◽  
Thomas Martin McGinnity ◽  
Liam Maguire ◽  
Ammar Belatreche ◽  
Brendan Glackin

2017 ◽  
Vol 44 (5) ◽  
pp. 0508002
Author(s):  
李强 Li Qiang ◽  
王智 Wang Zhi ◽  
崔粲 Cui Can ◽  
乐燕思 Le Yansi ◽  
宋晓佳 Song Xiaojia ◽  
...  

2019 ◽  
Author(s):  
Margarita Anisimova ◽  
Bas van Bommel ◽  
Marina Mikhaylova ◽  
J. Simon Wiegert ◽  
Thomas G. Oertner ◽  
...  

AbstractSpike-timing-dependent plasticity (STDP) is a candidate mechanism for information storage in the brain. However, it has been practically impossible to assess the long-term consequences of STDP because recordings from postsynaptic neurons last at most one hour. Here we introduce an optogenetic method to, with millisecond precision, independently control action potentials in two neuronal populations with light. We apply this method to study spike-timing-dependent plasticity (oSTDP) in the hippocampus and reproduce previous findings that depression or potentiation depend on the sequence of pre- and postsynaptic spiking. However, 3 days after induction, oSTDP results in potentiation regardless of the exact temporal sequence, frequency or number of pairings. Blocking activity between induction and readout prevented the synaptic potentiation, indicating that strengthened synapses have to be used to get strong. Our findings indicate that STDP potentiates synapses and that the change in synaptic strength persist to behaviorally relevant timescales.


2006 ◽  
Vol 18 (10) ◽  
pp. 2414-2464 ◽  
Author(s):  
Peter A. Appleby ◽  
Terry Elliott

In earlier work we presented a stochastic model of spike-timing-dependent plasticity (STDP) in which STDP emerges only at the level of temporal or spatial synaptic ensembles. We derived the two-spike interaction function from this model and showed that it exhibits an STDP-like form. Here, we extend this work by examining the general n-spike interaction functions that may be derived from the model. A comparison between the two-spike interaction function and the higher-order interaction functions reveals profound differences. In particular, we show that the two-spike interaction function cannot support stable, competitive synaptic plasticity, such as that seen during neuronal development, without including modifications designed specifically to stabilize its behavior. In contrast, we show that all the higher-order interaction functions exhibit a fixed-point structure consistent with the presence of competitive synaptic dynamics. This difference originates in the unification of our proposed “switch” mechanism for synaptic plasticity, coupling synaptic depression and synaptic potentiation processes together. While three or more spikes are required to probe this coupling, two spikes can never do so. We conclude that this coupling is critical to the presence of competitive dynamics and that multispike interactions are therefore vital to understanding synaptic competition.


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