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  Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation

Tetzlaff, C., Kolodziejski, C., Timme, M., Tsodyks, M., & Woergoetter, F. (2013). Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation. PLoS Computational Biology, 9(10): e1003307. doi:10.1371/journal.pcbi.1003307.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0029-0FA1-A Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0029-0FA2-8
Genre: Journal Article

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 Creators:
Tetzlaff, Christian1, Author              
Kolodziejski, Christoph1, Author              
Timme, Marc1, Author              
Tsodyks, Misha, Author
Woergoetter, Florentin, Author
Affiliations:
1Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063295              

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 Abstract: Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a longterm storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling – a slow process usually associated with the maintenance of activity homeostasis – combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.

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Language(s): eng - English
 Dates: 2013-10-31
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: eDoc: 692250
DOI: 10.1371/journal.pcbi.1003307
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Title: PLoS Computational Biology
  Alternative Title : PLoS Comput. Biol.
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 9 (10) Sequence Number: e1003307 Start / End Page: - Identifier: -