Published March 1, 2013 | Version v1
Journal article

Computational modelling of memory retention from synapse to behaviour

  • 1. Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB (United Kingdom)

Description

One of our most intriguing mental abilities is the capacity to store information and recall it from memory. Computational neuroscience has been influential in developing models and concepts of learning and memory. In this tutorial review we focus on the interplay between learning and forgetting. We discuss recent advances in the computational description of the learning and forgetting processes on synaptic, neuronal, and systems levels, as well as recent data that open up new challenges for statistical physicists. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1742-5468/2013/03/P03007

Additional details

Publishing Information

Journal Title
Journal of Statistical Mechanics
Journal Volume
2013
Journal Issue
03
Journal Page Range
[13 p.]
ISSN
1742-5468

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
46011301
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
CAPACITY; COMPUTERIZED SIMULATION; INFORMATION; LEARNING; MATHEMATICAL MODELS; RETENTION; REVIEWS; STATISTICAL MECHANICS
Descriptors DEC
DOCUMENT TYPES; MECHANICS; SIMULATION