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Synaptic plasticity: taming the beast
Abstract
Synaptic plasticity provides the basis for most models of learning, memory and development in neural circuits. To generate realistic results, synapse-specific Hebbian forms of plasticity, such as long-term potentiation and depression, must be augmented by global processes that regulate overall levels of neuronal and network activity. Regulatory processes are often as important as the more intensively studied Hebbian processes in determining the consequences of synaptic plasticity for network function. Recent experimental results suggest several novel mechanisms for regulating levels of activity in conjunction with Hebbian synaptic modification. We review three of them-synaptic scaling, spike-timing dependent plasticity and synaptic redistribution-and discuss their functional implications.
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“Many forms of correlation-based plasticity have now been described biologically, and each is likely to introduce its own unique destabilizing influences on neural circuit function (Abbott and Nelson 2000).”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Abbott and Nelson 2000
In the citing paper
“synapse-specific correlation-based plasticity mechanisms such as long-term potentiation (LTP) and depression (LTD) are widely thought to contribute to learning and information storage, but theoreticians have long appreciated that they generate a powerful destabilizing force on network function (Miller and MacKay 1994;Abbott and Nelson 2000).”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Abbott and Nelson 2000
In the citing paper
“The locus of change during homeostatic plasticity has important consequences for circuit function, because (for example) presynaptic changes in release probability will strongly affect short-term plasticity and thus the dynamics of information transfer across synapses, whereas a postsynaptic change in receptor accumulation can scale postsynaptic responsiveness without affecting the short-term”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Abbott and Nelson 2000
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Ren, Y., Milo, V., Wang, Z., Xu, H., Ielmini, D., Zhao, X., & Liu, Y. (2018) · Advanced Theory and Simulations · doi:10.1002/adts.201700035 · Cited by 41
“It should be noted that the particular anti-STDP characteristics was also observed in some biological systems [27], which points out that the shape of STDP curves is not crucial to achieve high performance in neuromorphic tasks [28].”
BackgroundA Taxonomy of Brain–Behavior Relationships After Stroke
Turkeltaub, P. E. (2019) · Journal of Speech Language and Hearing Research · doi:10.1044/2019_jslhr-l-rsnp-19-0032 · Cited by 39
“More broadly, any mechanism of plasticity that results in synaptic modifications (Abbott & Nelson, 2000), including axonal sprouting, could result in increased activity in spared networks already involved to some degree in a behavior.”
BackgroundCapogna, M., Castillo, P. E., & Maffei, A. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.14907 · Cited by 45
“In network models, the inhibitory engram mediated by ISP would stabilize network excitability while preserving relative differences at excitatory connections (Abbott & Nelson, 2000; Renart, Song, & Wang, 2003).”
BackgroundHow Is Homeostatic Plasticity Important in Epilepsy?
Swann, J. W., & Rho, J. M. (2014) · Advances in experimental medicine and biology · doi:10.1007/978-94-017-8914-1_10 · Cited by 44
Carvalho, T. P. (2011) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2011.00020 · Cited by 44
“INTEGRATIVE NEUROSCIENCE Associative forms of synaptic plasticity, including spike-timing-dependent plasticity (STDP; Abbott and Nelson, 2000; Dan and Poo, 2004), state that if neuron A consistently fires 10 ms before neuron B the synapse between them will be a strong one.”
BackgroundA reinforcement learning algorithm for spiking neural networks
Florian, R. V. (2005) · International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) · doi:10.1109/synasc.2005.13 · Cited by 41
“As in previous studies [31, 1], we model STDP as having an exponential dependence on the relative spike timing, and we consider that the effect of different spike pairs is additive.”
BackgroundResultFung, P., & Robinson, P. (2013) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2013.01.013 · Cited by 31
Andrews, R. K., Schabrun, S. M., Ridding, M. C., Galea, M. P., Hodges, P. W., & Chipchase, L. S. (2013) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-10-51 · Cited by 40
“If large increases in corticospinal excitability are induced by motor ES the potential exists for runaway excitability and destabilisation of cortical neuronal networks [48].”
BackgroundFunctional connectivity in a rhythmic inhibitory circuit using Granger causality
Kispersky, T. J., Gutierrez, G. J., & Marder, E. E. (2011) · Neural Systems & Circuits · doi:10.1186/2042-1001-1-9 · Cited by 44
“lity synaptic strength varies as a function of neuromodulation [2-5] and time-dependent processes such as facilitation and depression [1,6-8].”
BackgroundTime-course and mechanisms of homeostatic plasticity in layers 2/3 and 5 of the barrel cortex
Glazewski, S., Greenhill, S., & Fox, K. D. (2017) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2016.0150 · Cited by 34
“…scaling, a sub-class of mechanisms known as multiplicative synaptic scaling has the further property of maintaining the relative synaptic weights for each cell while restoring overall excitability, which has the additional benefit of not disrupting coding of information during homeostasis [17].”
Input-Specific Metaplasticity in the Visual Cortex Requires Homer1a-Mediated mGluR5 Signaling
Chokshi, V. B., Gao, M., Grier, B. D., Owens, A., Wang, H., Worley, P. F., & Lee, H. (2019) · Neuron · doi:10.1016/j.neuron.2019.08.017 · Cited by 40
“anisms to maintain network stability (Abbott and Nelson, 2000; Bear et al., 1987; Bienenstock et al., 1982; Cooper and Bear, 2012).”
Ramiro‐Cortés, Y., & Israely, I. (2013) · PLoS ONE · doi:10.1371/journal.pone.0071155 · Cited by 39
“Depending on the type of activity, dendritic inputs can undergo bidirectional modifications of synaptic weights [21,34,35].”
BackgroundOrganic All-Photonic Artificial Synapses Enabled by Anti-Stokes Photoluminescence
Chen, H., Hou, Y., Shi, Y., Zhang, Y., Wang, S., Peng, Q., & Huang, H. (2023) · Journal of the American Chemical Society · doi:10.1021/jacs.2c13471 · Cited by 40
Spiking neural networks on FPGA: A survey of methodologies and recent advancements
Karamimanesh, M., Abiri, E., Shahsavari, M., Hassanli, K., André, V. S., & Eshraghian, J. K. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107256 · Cited by 54
Hardware design of LIF with Latency neuron model with memristive STDP synapses
Acciarito, S., Cardarilli, G. C., Cristini, A., Nunzio, L. D., Fazzolari, R., Khanal, G. M., Re, M., & Susi, G. (2017) · Integration · doi:10.1016/j.vlsi.2017.05.006 · Cited by 39
“…and τ − are the time constants for potentiation and depression, respectively, and A + and A − are the maximum amplitudes Although STDP varies tremendously across synapse types and brain regions [49], a standard choice for these parameters, obtained by fitting the real case [50], is shown in Table 1.”
BackgroundMore than a sidekick: glia and homeostatic synaptic plasticity
Turrigiano, G. G. (2006) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2006.08.002 · Cited by 39
STDP Provides the Substrate for Igniting Synfire Chains by Spatiotemporal Input Patterns
Hosaka, R., Araki, O., & Ikeguchi, T. (2007) · Neural Computation · doi:10.1162/neco.2007.11-05-043 · Cited by 39
“…the pre- and postsynaptic action potentials in the cortices and the hippocampus; this is termed spike-timingdependent synaptic plasticity (STDP) (Abbott & Nelson, 2000; Markram, Lübke, Frotscher, & Sakmann, 1997; Bell, Han, Sugawara, & Grant, 1997; Bi & Poo, 1998; Zhang, Tao, Holt, Harris, &…”
An Improved Test for Detecting Multiplicative Homeostatic Synaptic Scaling
Kim, J., Tsien, R. W., & Alger, B. E. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037364 · Cited by 37
“This problem could be avoided by a uniform multiplicative scaling process, in which strengths of all the synapses subject to the same level of activity perturbation were altered by the same factor, as this would leave the relative synaptic strengths unaltered [2,3,6].”
BackgroundInfluential
Metadata
- Authors
- Abbott, L. F., & Nelson, S. B.
- Affiliations
- Brandeis University (US)
- Corresponding author
- Abbott, L. F.
- Venue
- Nature Neuroscience
- Published
- 2000-11
- Volume
- 3
- Issue
- S11
- Pages
- 1178-1183
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W1489333352
- Cited by
- 2,263
- References
- 51
- Citations by year
- 2026: 87 · 2025: 129 · 2024: 121 · 2023: 125 · 2022: 122 · 2021: 129 · 2020: 137 · 2019: 103 · 2018: 121 · 2017: 89 · 2016: 94 · 2015: 90 · 2014: 91 · 2013: 82 · 2012: 86
- FWCI
- 3.62
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01ey011116-07)
- National Institute of Mental Health (R01MH058754, MH58754)
- National Eye Institute (EY11116)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- synaptic plasticity, Hebbian plasticity, long-term potentiation, long-term depression, synaptic scaling, spike-timing-dependent plasticity, learning and memory, neural development
- MeSH terms
- Action Potentials, Animals, Humans, Models, Neurological, Nerve Net, Synaptic Transmission, Neuronal Plasticity, Neurons, Synapses, Receptors, Glutamate, Long-Term Potentiation
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