Memories as bifurcations: realization by collective dynamics of spiking neurons under stochastic inputs

DOI10.1016/J.NEUNET.2014.07.005zbMath1368.92034OpenAlexW2026603943WikidataQ48603908 ScholiaQ48603908MaRDI QIDQ889357

Kunihiko Kaneko, Tomoki Kurikawa

Publication date: 6 November 2015

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

Full work available at URL: https://doi.org/10.1016/j.neunet.2014.07.005

zbMATH Keywords

associative memorydynamical systems theoryspontaneous activityspiking neuron model

Mathematics Subject Classification ID

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

Cites Work

• Clustering, coding, switching, hierarchical ordering, and control in a network of chaotic elements
• Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons.
• Neuronal Computations with Stochastic Network States
• Spiking Neuron Models
• Spike-Driven Synaptic Dynamics Generating Working Memory States
• Neurons with graded response have collective computational properties like those of two-state neurons.
• Chaotic itinerancy

This page was built for publication: Memories as bifurcations: realization by collective dynamics of spiking neurons under stochastic inputs