Spike-timing dependent plasticity

Spike-timing dependent plasticity PDF Author: Henry Markram
Publisher: Frontiers E-books
ISBN: 2889190439
Category :
Languages : en
Pages : 575

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Book Description
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.

Spike-timing dependent plasticity

Spike-timing dependent plasticity PDF Author: Henry Markram
Publisher: Frontiers E-books
ISBN: 2889190439
Category :
Languages : en
Pages : 575

Get Book Here

Book Description
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.

Memristor and Memristive Neural Networks

Memristor and Memristive Neural Networks PDF Author: Alex James
Publisher: BoD – Books on Demand
ISBN: 9535139479
Category : Computers
Languages : en
Pages : 326

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Book Description
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 resistive switching property is an important aspect of the memristors, and there are several designs of this discussed in this book, such as in metal oxide/organic semiconductor nonvolatile memories, nanoscale switching and degradation of resistive random access memory and graphene oxide-based memristor. The modelling of the memristors is required to ensure that the devices can be put to use and improve emerging application. In this book, various memristor models are discussed, from a mathematical framework to implementations in SPICE and verilog, that will be useful for the practitioners and researchers to get a grounding on the topic. The applications of the memristor models in various neuromorphic networks are discussed covering various neural network models, implementations in A/D converter and hierarchical temporal memories.

Encyclopedia of Computational Neuroscience

Encyclopedia of Computational Neuroscience PDF Author: Dieter Jaeger
Publisher:
ISBN: 9781461473206
Category : Computational neuroscience
Languages : en
Pages :

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Book Description


Neuronal Dynamics

Neuronal Dynamics PDF Author: Wulfram Gerstner
Publisher: Cambridge University Press
ISBN: 1107060834
Category : Computers
Languages : en
Pages : 591

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Book Description
This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.

Inhibitory Synaptic Plasticity

Inhibitory Synaptic Plasticity PDF Author: Melanie A. Woodin
Publisher: Springer Science & Business Media
ISBN: 1441969780
Category : Medical
Languages : en
Pages : 191

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Book Description
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. Inhibitory Synaptic Plasticity will be of particular interest to neuroscientists and neurophysiologists.

Synaptic Plasticity in the Hippocampus

Synaptic Plasticity in the Hippocampus PDF Author: Helmut L. Haas
Publisher: Springer Science & Business Media
ISBN: 364273202X
Category : Medical
Languages : en
Pages : 219

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Book Description
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. It was a pleasure to greet the participants in the hope that their valuable contributions will make this meeting a tradition in this town. As one of the hosts of the symposium, I had the sorrowful duty to remind you of the absence of a dear colleague, Professor Graham God dard. His tragic and untimely death represents the irreparable loss of both a friend and an excellent researcher. This symposium is dedicated to his memory. If I compare the topics of the lectures of this symposium with those of the previous one, a striking difference becomes apparent. A dominating tendency of the previous symposium was to attempt to define hippocam pal function or to offer data relevant to supporting or rejecting existing theoretical positions. No such tendency is reflected in the titles of the present symposium, in which most of the contributions deal with hip pocampal phenomena at the most elementary level. Electrical, biochemi cal, biophysical, and pharmacological events at the synaptic, membrane, or intracellular level are analyzed without raising the question of what kind of integral functions these elementary phenomena are a part of.

Spiking Neural Network Learning, Benchmarking, Programming and Executing

Spiking Neural Network Learning, Benchmarking, Programming and Executing PDF Author: Guoqi Li
Publisher: Frontiers Media SA
ISBN: 2889637670
Category :
Languages : en
Pages : 234

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Book Description


Spiking Neuron Models

Spiking Neuron Models PDF Author: Wulfram Gerstner
Publisher: Cambridge University Press
ISBN: 9780521890793
Category : Computers
Languages : en
Pages : 498

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Book Description
Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.

Handbook of Memristor Networks

Handbook of Memristor Networks PDF Author: Leon Chua
Publisher: Springer Nature
ISBN: 331976375X
Category : Computers
Languages : en
Pages : 1357

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Book Description
This Handbook presents all aspects of memristor networks in an easy to read and tutorial style. Including many colour illustrations, it covers the foundations of memristor theory and applications, the technology of memristive devices, revised models of the Hodgkin-Huxley Equations and ion channels, neuromorphic architectures, and analyses of the dynamic behaviour of memristive networks. It also shows how to realise computing devices, non-von Neumann architectures and provides future building blocks for deep learning hardware. With contributions from leaders in computer science, mathematics, electronics, physics, material science and engineering, the book offers an indispensable source of information and an inspiring reference text for future generations of computer scientists, mathematicians, physicists, material scientists and engineers working in this dynamic field.

An Introduction to Modeling Neuronal Dynamics

An Introduction to Modeling Neuronal Dynamics PDF Author: Christoph Börgers
Publisher: Springer
ISBN: 3319511718
Category : Mathematics
Languages : en
Pages : 445

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Book Description
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. An undergraduate introduction to differential equations is more than enough mathematical background. Only a slim, high school-level background in physics is assumed, and none in biology. Topics include models of individual nerve cells and their dynamics, models of networks of neurons coupled by synapses and gap junctions, origins and functions of population rhythms in neuronal networks, and models of synaptic plasticity. An extensive online collection of Matlab programs generating the figures accompanies the book.