Doesspike-timing-dependent synaptic plasticity couple or decouple neurons firing in synchrony?
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Small assemblies of Fitzhugh-Nagumo neural oscillators are used to study a type of threshold coupling coming from biology where it is used to model synapses. Phase locking and coincidence detection is modelled in the two most simple coupling configurations ...
In timing-based neural codes, neurons have to emit action potentials at precise moments in time. We use a supervised learning paradigm to derive a synaptic update rule that optimizes via gradient ascent the likelihood of postsynaptic firing at one or sever ...
The short-term plasticity of synaptic transmission between excitatory neurons within a barrel of layer 4 rat somatosensory neocortex was investigated. Action potentials in presynaptic neurons at frequencies ranging from 1 to 100 Hz evoked depressing postsy ...
The synaptic drive from neuronal populations varies considerably over short time scales. Such changes in the presynaptic rate trigger many temporal processes absent under steady-state conditions. This paper examines the differential impact of pyramidal cel ...
The precise times of occurrence of individual pre- and postsynaptic action potentials are known to play a key role in the modification of synaptic efficacy. Based on stimulation protocols of two synaptically connected neurons, we infer an algorithm that re ...
Maximization of information transmission by a spiking-neuron model predicts changes of synaptic connections that depend on timing of pre- and postsynaptic spikes and on the postsynaptic membrane potential. Under the assumption of Poisson firing statistics, ...
We study analytically a model of long-term synaptic plasticity where synaptic changes are triggered by presynaptic spikes, postsynaptic spikes, and the time differences between pre- and postsynaptic spikes. We show that plasticity can lead to an intrinsic ...
Synaptic transmission in the neocortex is dynamic, such that the magnitude of the postsynaptic response changes with the history of the presynaptic activity. Therefore each response carries information about the temporal structure of the preceding presynap ...
Reduced models of neuronal activity such as Integrate-and-Fire models allow a description of neuronal dynamics in simple, intuitive terms and are easy to simulate numerically. We present a method to fit an Integrate-and-Fire-type model of neuronal activity ...
Synaptic plasticity is thought to be the neuronal correlate of learning. Moreover, modification of synapses contributes to the activity-dependent homeostatic maintenance of neurons and neural networks. In this chapter, we review theories of synaptic plasti ...