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Spiking Neuron Models: Single Neurons, Populations, Plasticity
A comparison of single and two-dimensional neuron models for spiking neuron models and models of Synaptic Plasticity shows that the former are superior to the latter, while the latter are better suited to population models.
Spiking Neuron Models
Adaptive exponential integrate-and-fire model as an effective description of neuronal activity.
The authors' simple model predicts correctly the timing of 96% of the spikes of the detailed model in response to injection of noisy synaptic conductances and has enough expressive power to reproduce qualitatively several electrophysiological classes described in vitro.
Neuronal Dynamics: From Single Neurons To Networks And Models Of Cognition
This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of computational and theoretical neuroscience.
Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity
A triplet rule is examined, a rule which considers sets of three spikes and is possible to fit experimental data from visual cortical slices as well as from hippocampal cultures and can be mapped to a Bienenstock–Cooper–Munro learning rule.
A neuronal learning rule for sub-millisecond temporal coding
A modelling study based on computer simulations of a neuron in the laminar nucleus of the barn owl shows that the necessary degree of coherence in the signal arrival times can be attained during ontogenetic development by virtue of an unsupervised hebbian learning rule.
Hebbian learning and spiking neurons
A correlation-based ~‘‘Hebbian’’ ! learning rule at a spike level with millisecond resolution is formulated, mathematically analyzed, and compared with learning in a firing-rate description. The…
Phenomenological models of synaptic plasticity based on spike timing
This document reviews phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP), and focuses on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables.
Connectivity reflects coding: a model of voltage-based STDP with homeostasis
A model of spike timing–dependent plasticity (STDP) in which synaptic changes depend on presynaptic spike arrival and the postsynaptic membrane potential, filtered with two different time constants is created and found that the plasticity rule led not only to development of localized receptive fields but also to connectivity patterns that reflect the neural code.