A biologically motivated and analytically soluble model of collective oscillations in the cortex. II: Application to binding and pattern segmentation

DOI10.1007/BF00239622zbMath0802.92005OpenAlexW2091954631MaRDI QIDQ1337301

J. Leo van Hemmen, Wulfram Gerstner, Ursula Fuentes, Raphael Ritz

Publication date: 4 December 1994

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00239622

zbMATH Keywords

network topologieshierarchical networkpattern separationspike response modelasymmetric Hebbian ruleauto-associative network of spiking neuronscontext-sensitive bindingfeature linkingfeedforward and feedback connectionsnetwork composed of two hemispherespostsynaptic neuronspostsynaptic potentialstructureless fully connected systemthreshold process

Mathematics Subject Classification ID

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

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Cites Work

• Chemical oscillations, waves, and turbulence
• Sensory segmentation with coupled neural oscillators
• Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns
• A biologically motivated and analytically soluble model of collective oscillations in the cortex. I. Theory of weak locking
• Hierarchical model of memory and memory loss
• Neural networks and physical systems with emergent collective computational abilities.

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