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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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BackgroundLearning Real-World Stimuli in a Neural Network with Spike-Driven Synaptic Dynamics
Brader, J. M., Senn, W., & Fusi, S. (2007) · Neural Computation · doi:10.1162/neco.2007.19.11.2881 · Cited by 375
“…of synaptic plasticity based on spike timing (STDP) have been studied both in recurrent neural networks and at the level of single synapses (see Abbott & Nelson, 2000; Kempter, Gerstner, & van Hemmen, 2001; Rubin, Lee, & Sompolinsky, 2001; Burkitt, Meffin, & Grayden, 2004), in which the authors…”
BackgroundDifferential Corticostriatal Plasticity during Fast and Slow Motor Skill Learning in Mice
Costa, R. M., Cohen, D., & Nicolelis, M. A. L. (2004) · Current Biology · doi:10.1016/j.cub.2004.06.053 · Cited by 373
Zenke, F., Agnes, E. J., & Wulfram Gerstner, B. (2015) · Nature Communications · doi:10.1038/ncomms7922 · Cited by 374
“equation (15)), Sj/i(t) are the pre/postsynaptic spike trains and G(t) is a quantity that linearly depends on the global secreted factor H(t).”
Introduction to spiking neural networks: Information processing, learning and applications
Ponulak, F., & Kasiński, A. (2011) · Acta Neurobiologiae Experimentalis · doi:10.55782/ane-2011-1862 · Cited by 379
“…scale: some processes, e.g. pulse paired facilitation, decay on the order of about 10–100 ms; other processes, such as long-term potentiation (LTP) or long-term depression (LTD), persist for hours, days, or longer (Lømo 1966, Magleby and Zengel 1976, Abbott and Nelson 2000, Citri and Malenka 2008).”
BackgroundJohn, R. A., Liu, F., Chien, N. A., Kulkarni, M. R., Zhu, C., Fu, Q., Basu, A., Liu, Z., & Mathews, N. (2018) · Advanced Materials · doi:10.1002/adma.201800220 · Cited by 364
Firing Rate Homeostasis in Visual Cortex of Freely Behaving Rodents
Hengen, K. B., Lambo, M. E., Hooser, S. D. V., Katz, D. B., & Turrigiano, G. G. (2013) · Neuron · doi:10.1016/j.neuron.2013.08.038 · Cited by 362
“It is widely agreed that neurons require some kind of homeostatic mechanism to prevent circuit instability and runaway synaptic potentiation during experience-dependent plasticity (Abbott and Nelson, 2000; Turrigiano and Nelson, 2004; Davis 2006; Marder and Goaillard, 2006; Pozo and Goda, 2010), but the exact form thi…”
BackgroundReinforcement Learning Through Modulation of Spike-Timing-Dependent Synaptic Plasticity
Florian, R. V. (2007) · Neural Computation · doi:10.1162/neco.2007.19.6.1468 · Cited by 376
“…(without considering the homeostatic mechanism introduced in section 2.2), we use an exponential dependence of plasticity on the relative spike timings , and we consider that the effect of different spike pairs is additive, as in previous studies (Song et al., 2000; Abbott & Nelson, 2000).”
MethodInfluentialConservation of total synaptic weight through balanced synaptic depression and potentiation
Royer, S., & Paré, D. (2003) · Nature · doi:10.1038/nature01530 · Cited by 351
“However, when such plastic synapses are incorporated into neural network models, stability problems may develop because the potentiation or depression of synapses increases the likelihood that they will be further strengthened or weakene”
BackgroundNeuromorphic device architectures with global connectivity through electrolyte gating.
Gkoupidenis, P., Koutsouras, D. A., & Malliaras, G. G. (2017) · Nature Communications · doi:10.1038/ncomms15448 · Cited by 353
Neuromorphic Engineering: From Biological to Spike‐Based Hardware Nervous Systems
Yang, J., Wang, R., Ren, Y., Mao, J., Wang, Z., Zhou, Y., & Han, S. (2020) · Advanced Materials · doi:10.1002/adma.202003610 · Cited by 362
Shaping the Optimal Repetition Interval for Cathodal Transcranial Direct Current Stimulation (tDCS)
Monte-Silva, K. K., Kuo, M., Liebetanz, D., Paulus, W., & Nitsche, M. A. (2010) · Journal of Neurophysiology · doi:10.1152/jn.00924.2009 · Cited by 350
Optimal Degrees of Synaptic Connectivity
Litwin-Kumar, A., Harris, K. D., Axel, R., Sompolinsky, H., & Abbott, L. F. (2017) · Neuron · doi:10.1016/j.neuron.2017.01.030 · Cited by 356
“The logic of experience-dependent circuit modifications is less clear in cerebral cortex, where densely connected neurons exhibit diverse forms of synaptic plasticity (Abbott and Nelson, 2000).”
Self-citationActivity-Dependent Synaptic Plasticity of a Chalcogenide Electronic Synapse for Neuromorphic Systems
Li, Y., Zhong, Y., Zhang, J., Xu, L., Wang, Q., Sun, H., Tong, H., Cheng, X., & Miao, X. (2014) · Scientific Reports · doi:10.1038/srep04906 · Cited by 344
A computational theory of hippocampal function, and tests of the theory: New developments
Kesner, R. P., & Rolls, E. T. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.11.009 · Cited by 347
“…furher, and the temporal asymmetry that may be present in LTP has een suggested as a mechanism that might provide some of the emporal properties that are necessary for the brain to store and ecall sequences (Abbott and Blum, 1996; Abbott and Nelson, 2000; arkram et al., 1998; Minai and Levy, 1993).”
Neural plasticity and behavior – sixty years of conceptual advances
Sweatt, J. D. (2016) · Journal of Neurochemistry · doi:10.1111/jnc.13580 · Cited by 364
Ielmini, D. (2018) · Microelectronic Engineering · doi:10.1016/j.mee.2018.01.009 · Cited by 341
Yan, X., Pei, Y., Chen, H., Zhao, J., Zhou, Z., Wang, H., Zhang, L., Wang, J., Li, X., Qin, C., et al. (2018) · Advanced Materials · doi:10.1002/adma.201805284 · Cited by 335
Malleability of Spike-Timing-Dependent Plasticity at the CA3–CA1 Synapse
Wittenberg, G. M., & Wang, S. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.5388-05.2006 · Cited by 334
“In other synapses, reversing the order of pairing so that the postsynaptic action potential precedes the presynaptic action potential leads to NMDA receptor-dependent long-term depression (Bi and Poo, 1998; Abbott and Nelson, 2000; Feldman, 2000).”
BackgroundAttention, short-term memory, and action selection: A unifying theory
Deco, G., & Rolls, E. T. (2005) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2005.08.004 · Cited by 324
“We describe now the specific implementation of the spikefrequency-adaptation mechanism that we used in the rulemodule: a short-term synaptic depression (Abbott and Nelson, 2000), following the details provided by Dayan and Abbot (2001, p.”
MethodCai, D., Deng, K., Mellado, W., Lee, J.-H., Ratan, R. R., & Filbin, M. T. (2002) · Neuron · doi:10.1016/s0896-6273(02)00826-7 · Cited by 313
“Blocking any ticity (Abbott and Nelson, 2000; Gnegy, 2000), which one pathway would diminish the total cAMP effect to also involves process outgrowth, it is reasonable to susbelow threshold, and inhibition would not be overcome. pect that polyamines might overcome inhibition by More reasonably,…”
BackgroundAdaptive oxide electronics: A review
Ha, S. D., & Ramanathan, S. (2011) · Journal of Applied Physics · doi:10.1063/1.3640806 · Cited by 308
Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake
Hengen, K. B., Pacheco, A. T., McGregor, J. N., Hooser, S. D. V., & Turrigiano, G. G. (2016) · Cell · doi:10.1016/j.cell.2016.01.046 · Cited by 302
“…is abundant theoretical and experimental evidence that network stability is achieved through homeostatic plasticity mechanisms that adjust synaptic and neuronal properties to stabilize some measure of average activity (Turrigiano et al., 1998; Abbott and Nelson, 2000; Turrigiano and Nelson, 2004).”
Coactivation and timing-dependent integration of synaptic potentiation and depression
Wang, H.-X., Gerkin, R. C., Nauen, D. W., & Bi, G. (2005) · Nature Neuroscience · doi:10.1038/nn1387 · Cited by 329
“In the recently characterized STDP, the polarity of synaptic modification depends on the precise timing of individual pre- and postsynaptic spike”
BackgroundFormation and maintenance of neuronal assemblies through synaptic plasticity
Litwin-Kumar, A., & Doiron, B. (2014) · Nature Communications · doi:10.1038/ncomms6319 · Cited by 311
Assessing the mechanisms of brain plasticity by transcranial magnetic stimulation
Jannati, A., Oberman, L. M., Rotenberg, A., & Pascual‐Leone, Á. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-022-01453-8 · Cited by 321
“, 200 paired pulses with an ISI of 10 ms), which can modulate inter-regional coupling according to spiketiming dependent plasticity mechanisms, including LTP-like plasticity [53, 54].”
Ling, H., Koutsouras, D. A., Kazemzadeh, S., van de Burgt, Y., Yan, F., & Gkoupidenis, P. (2020) · Applied Physics Reviews · doi:10.1063/1.5122249 · Cited by 301
Seo, K., Kim, I., Jung, S., Jo, M., Park, S., Park, J., Shin, J., Biju, K. P., Kong, J., Lee, K., et al. (2011) · Nanotechnology · doi:10.1088/0957-4484/22/25/254023 · Cited by 286
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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