
From synapse to network: models of information storage and retrieval in neural circuits.
The mechanisms of information storage and retrieval in brain circuits are still the subject of debate. It is widely believed that information is stored at least in part through changes in synaptic connectivity in networks that encode this information and that these changes lead in turn to modifications of network dynamics, such that the stored information can be retrieved at a later time. Here, we review recent progress in deriving synaptic plasticity rules from experimental data and in understanding how plasticity rules affect the dynamics of recurrent networks. We show that the dynamics generated by such networks exhibit a large degree of diversity, depending on parameters, similar to experimental observations in vivo during delayed response tasks.
Duke Scholars
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Related Subject Headings
- Synapses
- Neuronal Plasticity
- Neural Networks, Computer
- Nerve Net
- Models, Neurological
- Information Storage and Retrieval
- 3209 Neurosciences
- 1702 Cognitive Sciences
- 1109 Neurosciences
Citation

Published In
DOI
EISSN
Publication Date
Volume
Start / End Page
Location
Related Subject Headings
- Synapses
- Neuronal Plasticity
- Neural Networks, Computer
- Nerve Net
- Models, Neurological
- Information Storage and Retrieval
- 3209 Neurosciences
- 1702 Cognitive Sciences
- 1109 Neurosciences