Add to ORKGWe apply to oscillatory networks a class of learning rules in which synaptic weights change proportional to pre- and post-synaptic activity, with a kernel A(tau) measuring the effect for a postsynaptic spike a timer after the presynaptic one. The resulting synaptic matrices have an outer-product form in which the oscillating patterns are represented as complex vectors. In a simple model, the even part of A(tau) enhances the resonant response to learned stimulus by reducing the effective damping, while the odd part determines the frequency of oscillation. We relate our model to the olfactory cortex and hippocampus and their presumed roles in forming associative memories and input representations
International audienceRecent experiments have established that information can be encoded in the spi...
Recent experiments have shown that neocortical synapses exhibit both short-term plasticity and spike...
Recent experiments have established that information can be encoded in the spike times of neurons re...
We apply to oscillatory networks a class of learning rules in which synaptic weights change proporti...
We study a model of generalized-Hebbian learning in asymmetric oscillatory neural networks modeling ...
In a biologically plausible but computationally simplified integrate-and-fire neuronal population, i...
In a biologically plausible but computationally simplified integrate-and-fire neuronal population, i...
Recent experimental observations of spike-timing-dependent synaptic plasticity (STDP) have revitaliz...
The persistent modification of synaptic efficacy as a function of the rela-tive timing of pre- and p...
The influence of a weight-dependent spike-timing dependent plasticity (STDP) rule on the temporal ev...
The synaptic plasticity rules that sculpt a neural network architecture are key elements to understa...
We introduce a model of generalized Hebbian learning and retrieval in oscillatory neural networks mo...
It is widely believed that sensory and motor processing in the brain is based on simple computationa...
Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks o...
Associative learning requires mapping between complex stimuli and behavioural responses. When multip...
International audienceRecent experiments have established that information can be encoded in the spi...
Recent experiments have shown that neocortical synapses exhibit both short-term plasticity and spike...
Recent experiments have established that information can be encoded in the spike times of neurons re...
We apply to oscillatory networks a class of learning rules in which synaptic weights change proporti...
We study a model of generalized-Hebbian learning in asymmetric oscillatory neural networks modeling ...
In a biologically plausible but computationally simplified integrate-and-fire neuronal population, i...
In a biologically plausible but computationally simplified integrate-and-fire neuronal population, i...
Recent experimental observations of spike-timing-dependent synaptic plasticity (STDP) have revitaliz...
The persistent modification of synaptic efficacy as a function of the rela-tive timing of pre- and p...
The influence of a weight-dependent spike-timing dependent plasticity (STDP) rule on the temporal ev...
The synaptic plasticity rules that sculpt a neural network architecture are key elements to understa...
We introduce a model of generalized Hebbian learning and retrieval in oscillatory neural networks mo...
It is widely believed that sensory and motor processing in the brain is based on simple computationa...
Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks o...
Associative learning requires mapping between complex stimuli and behavioural responses. When multip...
International audienceRecent experiments have established that information can be encoded in the spi...
Recent experiments have shown that neocortical synapses exhibit both short-term plasticity and spike...
Recent experiments have established that information can be encoded in the spike times of neurons re...