Dynamic Integrative Synaptic Plasticity Explains the Spacing Effect in the Transition from Short- to Long-Term Memory

DOI10.1162/NECO_A_01227zbMath1429.92014OpenAlexW2974071639WikidataQ90124171 ScholiaQ90124171MaRDI QIDQ5214397

Terry Elliott

Publication date: 7 February 2020

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

Full work available at URL: https://eprints.soton.ac.uk/431975/1/spacing.pdf

zbMATH Keywords

dynamic integrative synaptic plasticityshort- to long-term memory transition

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Memory and learning in psychology (91E40)

Cites Work

• Unnamed Item
• The Rise and Fall of Memory in a Model of Synaptic Integration
• Temporal Dynamics of Rate-Based Synaptic Plasticity Rules in a Stochastic Model of Spike-Timing-Dependent Plasticity
• Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs
• Taming Fluctuations in a Stochastic Model of Spike-Timing-Dependent Plasticity
• Neural networks and physical systems with emergent collective computational abilities.
• The Enhanced Rise and Delayed Fall of Memory in a Model of Synaptic Integration: Extension to Discrete State Synapses
• Variations on the Theme of Synaptic Filtering: A Comparison of Integrate-and-Express Models of Synaptic Plasticity for Memory Lifetimes
• Mean First Passage Memory Lifetimes by Reducing Complex Synapses to Simple Synapses
• Memory Nearly on a Spring: A Mean First Passage Time Approach to Memory Lifetimes
• Memory Capacity for Sequences in a Recurrent Network with Biological Constraints

This page was built for publication: Dynamic Integrative Synaptic Plasticity Explains the Spacing Effect in the Transition from Short- to Long-Term Memory