Imposing Biological Constraints onto an Abstract Neocortical Attractor Network Model

DOI10.1162/neco.2007.19.7.1871zbMath1136.92007OpenAlexW2077116346WikidataQ48158844 ScholiaQ48158844MaRDI QIDQ5457587

Christopher Johansson, Anders Lansner

Publication date: 14 April 2008

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco.2007.19.7.1871

zbMATH Keywords

connectivitysynaptic inputprobabilistic stability analysis

Mathematics Subject Classification ID

Neural biology (92C20) Neural networks for/in biological studies, artificial life and related topics (92B20)

Related Items (5)

Storing structured sparse memories in a multi-modular cortical network model ⋮ Efficient Associative Computation with Discrete Synapses ⋮ Neural Associative Memory with Optimal Bayesian Learning ⋮ Reducing a cortical network to a Potts model yields storage capacity estimates ⋮ Short term memory properties of sensory neural architectures

Cites Work

• Towards cortex sized artificial neural systems
• On associative memory
• Towards a theory of cell assemblies
• Global and local synchrony of coupled neurons in small-world networks
• Localized activity profiles and storage capacity of rate-based autoassociative networks
• Short- and long-range connections in autoassociative memory
• A model of cortical associative memory based on a horizontal network of connected columns
• Mean-field theory for the Q-state Potts-glass neural network with biased patterns

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