Published March 1, 2013
| Version v1
Journal article
Computational modelling of memory retention from synapse to behaviour
Creators
- 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/P03007Additional details
Identifiers
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