Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation
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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 long-term 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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Studies using inducible and reversible NMDA receptor knockouts have demonstrated that NMDA receptor reactivation is required to sustain remote memory storage.
“Studies using inducible and reversible NMDA receptor knockouts have demonstrated that such NMDA receptor reactivation, which may also in part result from spontaneous neuronal activity, is required to sustain remote memory storage73,74.”
From The right time to learn: Mechanisms and optimization of spaced learning (2016) · cites this paper as [74]
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- Authors
- Tetzlaff, C., Kolodziejski, C., Timme, M., Tsodyks, M., & Wörgötter, F.
- Affiliations
- Bernstein Center for Computational Neuroscience Göttingen (DE)
- Weizmann Institute of Science (IL)
- Corresponding author
- Tetzlaff, Christian
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-10-31
- Volume
- 9
- Issue
- 10
- Pages
- e1003307
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC3814677
- OpenAlex
- W2055354495
- Cited by
- 54
- References
- 96
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 4 · 2023: 6 · 2022: 2 · 2021: 6 · 2020: 3 · 2019: 5 · 2018: 2 · 2017: 2 · 2016: 4 · 2015: 9 · 2014: 4
- FWCI
- 3.10
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- Max Planck Digital Library (submittedVersion)
- Figshare (submittedVersion, cc-by)
- GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
- GRO (submittedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- European Commission (270273)
- Bundesministerium für Bildung und Forschung (01GQ1005A, 01GQ1005B)
- Israel Science Foundation (FP7/2007-2013)
- Max-Planck-Gesellschaft (01GQ1005B)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- synaptic scaling, short-term memory, long-term memory, memory consolidation, synaptic plasticity, synaptic potentiation, memory storage, memory stability
- MeSH terms
- Memory, Short-Term, Models, Neurological, Neuronal Plasticity, Neurons, Synapses, Computational Biology, Memory, Long-Term
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