Hebb's postulate provided a crucial framework to understand synaptic alterations underlying learning and memory. Hebb's theory proposed that neurons that fire together, also wire together, which provided the logical framework for the strengthening of synapses. Weakening of synapses was however addressed by "not being strengthened", and it was only later that the active decrease of synaptic strength was introduced through the discovery of long-term depression caused by low frequency stimulation of the presynaptic neuron. In 1994, it was found that the precise relative timing of pre and postynaptic spikes determined not only the magnitude, but also the direction of synaptic alterations when two neurons are active together. Neurons that fire together may therefore not necessarily wire together if the precise timing of the spikes involved are not tighly correlated. In the subsequent 15 years, Spike Timing Dependent Plasticity (STDP) has been found in multiple brain brain regions and in many different species. The size and shape of the time windows in which positive and negative changes can be made vary for different brain regions, but the core principle of spike timing dependent changes remain. A large number of theoretical studies have also been conducted during this period that explore the computational function of this driving principle and STDP algorithms have become the main learning algorithm when modeling neural networks. This Research Topic will bring together all the key experimental and theoretical research on STDP.
This book covers a range of models, circuits and systems built with memristor devices and networks in applications to neural networks. It is divided into three parts: (1) Devices, (2) Models and (3) Applications.
The annual Computational Neuroscience Meeting (CNS) began in 1990 as a small workshop called Analysis and Modeling of Neural Systems. The goal of the workshop was to explore the boundary between neuroscience and computation.
This thesis work consists in a theoretical and computational study of a recently-indentified type of synaptic plasticity, called "spike-timing dependent plasticity" (STDP).
This volume will explore the most recent findings on cellular mechanisms of inhibitory plasticity and its functional role in shaping neuronal circuits, their rewiring in response to experience, drug addiction and in neuropathology.
This book is intended as a text for a one-semester course on Mathematical and Computational Neuroscience for upper-level undergraduate and beginning graduate students of mathematics, the natural sciences, engineering, or computer science.
This Handbook presents all aspects of memristor networks in an easy to read and tutorial style.
In Byrne, J. and Berry, W., eds, Neural Models of Plasticity, pp. 266–306. Academic Press, San Diego, CA. Brown, T. H., Zador, A. M., Mainen, Z. F., and Claiborne, B. J. (1991) Hebbian modifications in hippocampal neurons.
This volume is devoted mainly to anatomical and functional development of neural circuits and neural systems and cognitive development.
Spiking Neural Network Learning, Benchmarking, Programming and Executing
This is the second time that I have had the honor of opening an interna tional symposium dedicated to the functions of the hippocampus here in Pecs.