Computational modelling of memory retention from synapse to behaviour

DOI10.1088/1742-5468/2013/03/P03007zbMath1456.92038OpenAlexW2095153658MaRDI QIDQ3301546

Maria Shippi, Mark C. W. Van Rossum

Publication date: 11 August 2020

Published in: Journal of Statistical Mechanics: Theory and Experiment (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1088/1742-5468/2013/03/p03007

Mathematics Subject Classification ID

Neural biology (92C20)

Uses Software

• darch

Cites Work

• Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I: Input selectivity-strengthening correlated input pathways
• Phenomenological models of synaptic plasticity based on spike timing
• A simplified neuron model as a principal component analyzer
• Hebbian spike-driven synaptic plasticity for learning patterns of mean firing rates
• Reducing the Dimensionality of Data with Neural Networks
• Modeling Brain Function
• Constraints on learning in dynamic synapses
• Neural networks and physical systems with emergent collective computational abilities.

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