scholarly journals Spike-Timing-Dependent Plasticity, Learning Rules

Author(s):  
Walter Senn ◽  
Jean-Pascal Pfister
2012 ◽  
Vol 24 (5) ◽  
pp. 1109-1146 ◽  
Author(s):  
Todd K. Leen ◽  
Robert Friel

Online machine learning rules and many biological spike-timing-dependent plasticity (STDP) learning rules generate jump process Markov chains for the synaptic weights. We give a perturbation expansion for the dynamics that, unlike the usual approximation by a Fokker-Planck equation (FPE), is well justified. Our approach extends the related system size expansion by giving an expansion for the probability density as well as its moments. We apply the approach to two observed STDP learning rules and show that in regimes where the FPE breaks down, the new perturbation expansion agrees well with Monte Carlo simulations. The methods are also applicable to the dynamics of stochastic neural activity. Like previous ensemble analyses of STDP, we focus on equilibrium solutions, although the methods can in principle be applied to transients as well.


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.


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