In this review, we compare methods for temporal sequence learning (TSL) across the
disciplines machine-control, classical conditioning, neuronal models for TSL as well as …

Spiking neurons are very flexible computational modules, which can implement with
different values of their adjustable synaptic parameters an enormous variety of different …

Sensory experience is essential for the refinement of neuronal circuits during development
and for learning and memory in the adult brain. Such experience-dependent plasticity is …

While classical experiments on spike-timing dependent plasticity analyzed synaptic changes
as a function of the timing of pairs of pre-and postsynaptic spikes, more recent experiments …

We postulate that a simple, three-state synaptic switch governs changes in synaptic strength
at individual synapses. Under this switch rule, we show that a variety of experimental results …

Hippocampal area CA3 has been one of the most intensively studied brain regions for
computer models of epileptiform activity. As physiological studies begin to extend outward to …

The brain is a remarkable computational “device” which works very well in tasks still well
beyond the computational capabilities of even the most powerful machines. It is a rich …

Recent studies show that synaptic modification depends critically on the relative spike timing
of pre-and postsynaptic neurons. Here we explore the functional implications of spike timing …

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 …

A Mechanistic Model of Calcium-Dependent Synaptic Plasticity Page 1 A Mechanistic Model of
Calcium-Dependent Synaptic Plasticity by Luk Chong Yeung B.Sc. Universidade de Sao Paulo …