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Tutorial on Neural Systems Modeling

Tutorial on Neural Systems Modeling
Author: Thomas J. Anastasio
Publisher: Sinauer
Total Pages: 0
Release: 2010-03-01
Genre: Medical
ISBN: 9780878933396

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For students of neuroscience and cognitive science who wish to explore the functioning of the brain further, but lack an extensive background in computer programming or maths, this new book makes neural systems modelling truly accessible. Short, simple MATLAB computer programs give readers all the experience necessary to run their own simulations.


How to Build a Brain

How to Build a Brain
Author: Chris Eliasmith
Publisher: Oxford University Press
Total Pages: 475
Release: 2013-04-16
Genre: Psychology
ISBN: 0199794693

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How to Build a Brain provides a detailed exploration of a new cognitive architecture - the Semantic Pointer Architecture - that takes biological detail seriously, while addressing cognitive phenomena. Topics ranging from semantics and syntax, to neural coding and spike-timing-dependent plasticity are integrated to develop the world's largest functional brain model.


An Overview of Spiking Neural Networks

An Overview of Spiking Neural Networks
Author: Garima Mittal
Publisher: GRIN Verlag
Total Pages: 3
Release: 2020-09-01
Genre: Computers
ISBN: 334623813X

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Seminar paper from the year 2018 in the subject Computer Sciences - Artificial Intelligence, grade: 1,3, University of Tubingen, language: English, abstract: This work gives an introduction to SNNs and the underlying biological concepts. It gives an overview and comparison of some of the more commonly used SNN models. It discusses the scope of SNNs and some of the areas where they have been applied so far. Spiking neural networks or SNNs are inspired by the biological neuron. They are the next step towards the goal of replicating the mammalian brain in computational speed, efficiency and energy consumption. First generation artificial neural networks (ANNs) or Perceptron use a [0,1] binary threshold function to approximate digital input and allow for linear classification. Second generation ANNs like multi-layer perceptron, feed-forward and recurrent neural networks use continuous activation functions like sigmoid which can approximate analog functions. Spiking neural networks, introduced by Hopfield in 1995, are third generation ANNs and aim at higher biological plausibilty than the first and second generations by including time intrinsically. They use the precise firing times of neurons to code information. SNNs are modelled on the biological neuron. It is therefore important to understand the basic biological concepts underlying SNNs.


Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence
Author: Nikola K. Kasabov
Publisher: Springer
Total Pages: 738
Release: 2018-08-29
Genre: Technology & Engineering
ISBN: 3662577151

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Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.


Spiking Neuron Models

Spiking Neuron Models
Author: Wulfram Gerstner
Publisher: Cambridge University Press
Total Pages: 498
Release: 2002-08-15
Genre: Computers
ISBN: 9780521890793

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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.


SpiNNaker - A Spiking Neural Network Architecture

SpiNNaker - A Spiking Neural Network Architecture
Author: Steve Furber
Publisher: NowOpen
Total Pages: 352
Release: 2020-03-15
Genre:
ISBN: 9781680836523

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This books tells the story of the origins of the world's largest neuromorphic computing platform, its development and its deployment, and the immense software development effort that has gone into making it openly available and accessible to researchers and students the world over


Principles of Computational Modelling in Neuroscience

Principles of Computational Modelling in Neuroscience
Author: David Sterratt
Publisher: Cambridge University Press
Total Pages: 553
Release: 2023-10-05
Genre: Science
ISBN: 1108483143

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Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.


Pulsed Neural Networks

Pulsed Neural Networks
Author: Wolfgang Maass
Publisher: MIT Press
Total Pages: 414
Release: 2001-01-26
Genre: Computers
ISBN: 9780262632218

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Most practical applications of artificial neural networks are based on a computational model involving the propagation of continuous variables from one processing unit to the next. In recent years, data from neurobiological experiments have made it increasingly clear that biological neural networks, which communicate through pulses, use the timing of the pulses to transmit information and perform computation. This realization has stimulated significant research on pulsed neural networks, including theoretical analyses and model development, neurobiological modeling, and hardware implementation. This book presents the complete spectrum of current research in pulsed neural networks and includes the most important work from many of the key scientists in the field. Terrence J. Sejnowski's foreword, "Neural Pulse Coding," presents an overview of the topic. The first half of the book consists of longer tutorial articles spanning neurobiology, theory, algorithms, and hardware. The second half contains a larger number of shorter research chapters that present more advanced concepts. The contributors use consistent notation and terminology throughout the book. Contributors Peter S. Burge, Stephen R. Deiss, Rodney J. Douglas, John G. Elias, Wulfram Gerstner, Alister Hamilton, David Horn, Axel Jahnke, Richard Kempter, Wolfgang Maass, Alessandro Mortara, Alan F. Murray, David P. M. Northmore, Irit Opher, Kostas A. Papathanasiou, Michael Recce, Barry J. P. Rising, Ulrich Roth, Tim Schönauer, Terrence J. Sejnowski, John Shawe-Taylor, Max R. van Daalen, J. Leo van Hemmen, Philippe Venier, Hermann Wagner, Adrian M. Whatley, Anthony M. Zador


Neuronal Dynamics

Neuronal Dynamics
Author: Wulfram Gerstner
Publisher: Cambridge University Press
Total Pages: 591
Release: 2014-07-24
Genre: Computers
ISBN: 1107060834

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


The NEURON Book

The NEURON Book
Author: Nicholas T. Carnevale
Publisher: Cambridge University Press
Total Pages: 399
Release: 2006-01-12
Genre: Medical
ISBN: 1139447831

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The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.