International audienceSynaptic transmission is transiently adjusted on a spike-by-spike basis, with the adjustments persisting from hundreds of milliseconds up to seconds. Such a short-term plasticity has been suggested to significantly augment the computational capabilities of neuronal networks by enhancing their dynamical repertoire. In this chapter, after reviewing the basic physiology of chemical synaptic transmission, we present a general framework-inspired by the quantal model-to build simple, yet quantitatively accurate models of repetitive synaptic transmission. We also discuss different methods to obtain estimates of the model's parameters from experimental recordings. Next, we show that, indeed, new dynamical regimes appear in the...
Fast information transmission in neural networks is heavily influenced by short-term synaptic plasti...
3 figuresIn this paper we present a simple microscopic stochastic model describing short term plasti...
The ability to acquire and maintain appropriate representations of time-varying, sequential stimulus...
International audienceSynaptic transmission is transiently adjusted on a spike-by-spike basis, with ...
Experimental data have consistently revealed that the neuronal connection weight, which models the e...
We develop a minimal time-continuous model for use-dependent synap-tic short-term plasticity that ca...
Synaptic transmission ishighlydependentonrecent activity andcan lead todepressionor facilitationof s...
In the current paper it is proposed that short-term plasticity and dynamic changes in the balance of...
textabstractSynaptic transmission is highly dependent on recent activity and can lead to depression ...
International audienceIn this paper we present a simple microscopic stochastic model describing shor...
Continuous attractor models of working-memory store continuous-valued information in continuous stat...
Learning and memory storage is believed to occur at the synaptic connections between neurons. Durin...
We investigate the implications of the recently observed short term synaptic depression (STD) occurr...
Far from being static transmission units, synapses are highly dynamical elements that change over mu...
Distinct synapses influence one another when they undergo changes, with unclear consequences for neu...
Fast information transmission in neural networks is heavily influenced by short-term synaptic plasti...
3 figuresIn this paper we present a simple microscopic stochastic model describing short term plasti...
The ability to acquire and maintain appropriate representations of time-varying, sequential stimulus...
International audienceSynaptic transmission is transiently adjusted on a spike-by-spike basis, with ...
Experimental data have consistently revealed that the neuronal connection weight, which models the e...
We develop a minimal time-continuous model for use-dependent synap-tic short-term plasticity that ca...
Synaptic transmission ishighlydependentonrecent activity andcan lead todepressionor facilitationof s...
In the current paper it is proposed that short-term plasticity and dynamic changes in the balance of...
textabstractSynaptic transmission is highly dependent on recent activity and can lead to depression ...
International audienceIn this paper we present a simple microscopic stochastic model describing shor...
Continuous attractor models of working-memory store continuous-valued information in continuous stat...
Learning and memory storage is believed to occur at the synaptic connections between neurons. Durin...
We investigate the implications of the recently observed short term synaptic depression (STD) occurr...
Far from being static transmission units, synapses are highly dynamical elements that change over mu...
Distinct synapses influence one another when they undergo changes, with unclear consequences for neu...
Fast information transmission in neural networks is heavily influenced by short-term synaptic plasti...
3 figuresIn this paper we present a simple microscopic stochastic model describing short term plasti...
The ability to acquire and maintain appropriate representations of time-varying, sequential stimulus...