Spike Timing Dependant Plasticity (STDP) is a biologically-based Hebbian reinforcement
learning rule for the unsupervised training of synaptic weights in spiking neural networks …

Recent modeling of spike-timing-dependent plasticity indicates that plasticity involves as a
third factor a local dendritic potential, besides pre-and postsynaptic firing times. We present …

We present an effective model for timing-dependent synaptic plasticity (STDP) in terms of
two interacting traces, corresponding to the fraction of activated NMDA receptors and the …

Neural networks can generate spatiotemporal patterns of spike activity. Sequential activity
learning and retrieval have been observed in many brain areas, and eg is crucial for coding …

Recent studies show that the precise timing of presynaptic inputs and postsynaptic action
potentials influences the strength and sign of synaptic plasticity. In this issue of Neuron …

We studied the self-organization of memory-related activity through spike-timing-dependent
plasticity (STDP). Relatively short time windows (∼ 10 ms) for the plasticity rule give rise to …

Although spike-timing-dependent plasticity (STDP) is well characterized when pre-and
postsynaptic spikes are paired with a given time lag, how this generalizes for more complex …

SUMMARY 1 Synaptic plasticity is thought to underlie learning and memory formation in the
brain. However, how synaptic plasticity is induced during these processes remains …

Spike-timing–dependent plasticity (STDP) is considered as a primary mechanism underlying
formation of new memories during learning. Despite the growing interest in activity …

For my master thesis in physics, I spent my days in an experimental lab working with
electronics, liquid nitrogen, vacuum pumps, and tiny semiconductor lasers. It seemed every …