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Cited by 806Neuroscience and Neuropharmacology ResearchMemory and Neural MechanismsNeural dynamics and brain function

The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.

Synaptic Plasticity Forms and Functions

Magee, Jeffrey C., Grienberger, Christine·2020·Annual Review of Neuroscience
DOI 10.1146/annurev-neuro-090919-022842
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Abstract

Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long been considered an important component of learning and memory. Computational and engineering work corroborate the power of learning through the directed adjustment of connection weights. Here we review the fundamental elements of four broadly categorized forms of synaptic plasticity and discuss their functional capabilities and limitations. Although standard, correlation-based, Hebbian synaptic plasticity has been the primary focus of neuroscientists for decades, it is inherently limited. Three-factor plasticity rules supplement Hebbian forms with neuromodulation and eligibility traces, while true supervised types go even further by adding objectives and instructive signals. Finally, a recently discovered hippocampal form of synaptic plasticity combines the above elements, while leaving behind the primary Hebbian requirement. We suggest that the effort to determine the neural basis of adaptive behavior could benefit from renewed experimental and theoretical investigation of more powerful directed types of synaptic plasticity.

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  • Behavioral timescale synaptic plasticity (BTSP) is responsible for the rapid formation of hippocampal place fields.

    “behavioral timescale synaptic plasticity (BTSP) (103–106), which is responsible for the rapid formation of hippocampal place fields.”

    From Synaptic memory and CaMKII (2023) · cites this paper as [106]

  • BTSP is NMDAR dependent and, unlike classical LTP, has a coincidence time window of seconds rather than milliseconds.

    “It is NMDAR dependent, but unlike classical LTP the coincidence time window is seconds, not milliseconds.”

    From Synaptic memory and CaMKII (2023) · cites this paper as [106]

  • Aβ oligomers interfere with Hebbian plasticity, impairing LTP while enhancing LTD, thus biasing networks toward synaptic weakening.

    “Evidence suggests that Aβ oligomers interfere with Hebbian plasticity, impairing LTP while enhancing LTD, thus biasing networks toward synaptic weakening [85].”

    From Toward a Unified Framework in Molecular Neurobiology of Alzheimer’s Disease: Revisiting the Pathophysiological Hypotheses (2026) · cites this paper as [85]

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Metadata

Authors
Magee, J. C., & Grienberger, C.
Affiliations
Howard Hughes Medical Institute (US)
ORCID
Venue
Annual Review of Neuroscience
Publisher
Annual Reviews
Published
2020-07-08
Volume
43
Issue
1
Pages
95-117
ISSN
  • 0147-006X (ISSN-L)
  • 1545-4126
DOI
10.1146/annurev-neuro-090919-022842
OpenAlex
W3007169267
Cited by
806
References
30
Citations by year
2026: 108 · 2025: 227 · 2024: 185 · 2023: 129 · 2022: 95 · 2021: 50 · 2020: 12
FWCI
9.89
Type
journal article
Language
en
Open access
closed
Locations
  • Annual Review of Neuroscience (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords
synaptic plasticity, Hebbian plasticity, neuromodulation, eligibility traces, supervised learning, hippocampal synaptic plasticity, learning and memory, connection weight adjustment, adaptive behavior
MeSH terms
Animals, Humans, Learning, Memory, Synaptic Transmission, Neuronal Plasticity, Neurons, Synapses

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