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Modeling Brain Function: The World of Attractor Neural Networks by Daniel J. Amit

Modeling Brain Function: The World of Attractor Neural Networks Daniel J. Amit ebook
Page: 263
Format: pdf
ISBN: 0521361001, 9780521361002
Publisher: Cambridge University Press

"Our research focused on the mechanisms at work in the neural system that forms these hexagonal patterns," he said. Modeling Brain Function: The World of Attractor Neural Networks by. Citation: Kanamaru T, Fujii H, Aihara K (2013) Deformation of Attractor Landscape via Cholinergic Presynaptic Modulations: A Computational Study Using a Phase Neuron Model. Quasi-attractors can also be found in the field of chaotic associative memory in neural networks [16]–[25], in which patterns stored in the network become quasi-attractors and the network exhibits transitive dynamics between stored patterns. Neural Networks : - Google Books . The first author on the paper was graduate student Cristina The brain is made up of vast numbers of neurons connected together into networks, and the attractor network is a theoretical model of how patterns of connected neurons can give rise to brain activity by collectively working together. [Ami], Amit, D.J., Modeling Brain Function : The World of Attractor Neural Networks, Cambridge University Press, Cambridge, UK, 1989. An Introduction to Neural Networks - James A. The construction of the world's largest functional brain model and large-scale, real-time hardware simulations rely on the same mathematical and neuromorphic methods. Can generate neural networks with attractor states that. Advanced Series in Dynamical Systems 8, World Scientific. The work pursued here is coordinated with a parallel application that focuses on neural network systems, but the dependencies are arranged to make the present article the main and the more self-contained work, to serve as a conceptual frame and a technical background for the network project.