Spike-timing-dependent plasticity and reliability optimization: The role of neuron dynamics

Authors:
R. Rossi Pool;G. Mato
Affiliations:
-;-
Venue:
Neural Computation
Year:
2011

Citing 9
Cited 0

Asynchronous states and the emergence of synchrony in large networks of interacting excitatory and inhibitory neurons

Neural Computation
Spike-timing-dependent plasticity and relevant mutual information maximization

Neural Computation
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,

Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
On the Phase Reduction and Response Dynamics of Neural Oscillator Populations

Neural Computation
Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning

Neural Computation
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems

Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
Reliability and stochastic synchronization in type I vs. type II neural oscillators

Neurocomputing
Reducing the Variability of Neural Responses: A Computational Theory of Spike-Timing-Dependent Plasticity

Neural Computation
Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution

Neural Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Plastic changes in synaptic efficacy can depend on the time ordering of presynaptic and postsynaptic spikes. This phenomenon is called spike-timing-dependent plasticity (STDP). One of the most striking aspects of this plasticity mechanism is that the STDP windows display a great variety of forms in different parts of the nervous system. We explore this issue from a theoretical point of view. We choose as the optimization principle the minimization of conditional entropy or maximization of reliability in the transmission of information. We apply this principle to two types of postsynaptic dynamics, designated type I and type II. The first is characterized as being an integrator, while the second is a resonator. We find that, depending on the parameters of the models, the optimization principle can give rise to a wide variety of STDP windows, such as antisymmetric Hebbian, predominantly depressing or symmetric with one positive region and two lateral negative regions. We can relate each of these forms to the dynamical behavior of the different models. We also propose experimental tests to assess the validity of the optimization principle.