Abstract
Activity-dependent synaptic plasticity has since long been proposed to represent the subcellular substrate of learning and memory, one of the most important behavioral processes through which we adapt to our environment. Despite the undisputed importance of synaptic plasticity for brain function, its exact contribution to learning processes in the context of cellular and connectivity modifications remains obscure. Causally bridging synaptic and behavioral modifications indeed remains limited by the available tools to measure and control synaptic strength and plasticity in vivo under behaviorally relevant conditions. After a brief summary of the current state of knowledge of the links between synaptic plasticity and learning, we will review and discuss the available and desired tools to progress in this endeavor.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Takeuchi, T., Duszkiewicz, A. J. & Morris, R. G. The synaptic plasticity and memory hypothesis: encoding, storage and persistence. Philos. Trans. R. Soc. Lond. B 369, 20130288 (2013).
Martin, S. J. & Morris, R. G. New life in an old idea: the synaptic plasticity and memory hypothesis revisited. Hippocampus 12, 609–636 (2002).
Collingridge, G. L., Kehl, S. J. & McLennan, H. Excitatory amino acids in synaptic transmission in the Schaffer collateral-commissural pathway of the rat hippocampus. J. Physiol. (Lond.) 334, 33–46 (1983).
Morris, R. G., Anderson, E., Lynch, G. S. & Baudry, M. Selective impairment of learning and blockade of long-term potentiation by an N-methyl-d-aspartate receptor antagonist, AP5. Nature 319, 774–776 (1986).
Bliss, T. V. & Lomo, T. Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. J. Physiol. (Lond.) 232, 331–356 (1973).
Silva, A. J., Paylor, R., Wehner, J. M. & Tonegawa, S. Impaired spatial learning in alpha-calcium-calmodulin kinase II mutant mice. Science 257, 206–211 (1992).
Silva, A. J., Stevens, C. F., Tonegawa, S. & Wang, Y. Deficient hippocampal long-term potentiation in alpha-calcium-calmodulin kinase II mutant mice. Science 257, 201–206 (1992).
Lisman, J. Criteria for identifying the molecular basis of the engram (CaMKII, PKMzeta). Mol. Brain 10, 55 (2017).
Whitlock, J. R., Heynen, A. J., Shuler, M. G. & Bear, M. F. Learning induces long-term potentiation in the hippocampus. Science 313, 1093–1097 (2006).
Ryan, T. J., Roy, D. S., Pignatelli, M., Arons, A. & Tonegawa, S. Memory. Engram cells retain memory under retrograde amnesia. Science 348, 1007–1013 (2015).
LeDoux, J. E. Emotion circuits in the brain. Annu. Rev. Neurosci. 23, 155–184 (2000).
Nabavi, S. et al. Engineering a memory with LTD and LTP. Nature 511, 348–352 (2014).
Tonegawa, S., Morrissey, M. D. & Kitamura, T. The role of engram cells in the systems consolidation of memory. Nat. Rev. Neurosci. 19, 485–498 (2018).
Rao-Ruiz, P., Yu, J., Kushner, S. A. & Josselyn, S. A. Neuronal competition: microcircuit mechanisms define the sparsity of the engram. Curr. Opin. Neurobiol. 54, 163–170 (2019).
Liu, X. et al. Optogenetic stimulation of a hippocampal engram activates fear memory recall. Nature 484, 381–385 (2012).
Han, J. H. et al. Selective erasure of a fear memory. Science 323, 1492–1496 (2009).
Bi, G. Q. & Poo, M. M. Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J. Neurosci. 18, 10464–10472 (1998).
Markram, H., Lübke, J., Frotscher, M. & Sakmann, B. Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science 275, 213–215 (1997).
Bienenstock, E. L., Cooper, L. N. & Munro, P. W. Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex. J. Neurosci. 2, 32–48 (1982).
Lüscher, C. & Malenka, R. C. NMDA receptor-dependent long-term potentiation and long-term depression (LTP/LTD). Cold Spring Harb. Perspect. Biol. 4, a005710 (2012).
Seibt, J. & Frank, M. G. Primed to sleep: the dynamics of synaptic plasticity across brain states. Front. Syst. Neurosci. 13, 2 (2019).
Yagishita, S. et al. A critical time window for dopamine actions on the structural plasticity of dendritic spines. Science 345, 1616–1620 (2014).
He, K. et al. Distinct eligibility traces for LTP and LTD in cortical synapses. Neuron 88, 528–538 (2015).
Bittner, K. C., Milstein, A. D., Grienberger, C., Romani, S. & Magee, J. C. Behavioral time scale synaptic plasticity underlies CA1 place fields. Science 357, 1033–1036 (2017).
Zarnadze, S. et al. Cell-specific synaptic plasticity induced by network oscillations. eLife 5, e14912 (2016).
Trimper, J. B., Galloway, C. R., Jones, A. C., Mandi, K. & Manns, J. R. Gamma oscillations in rat hippocampal subregions dentate gyrus, CA3, CA1, and subiculum underlie associative memory encoding. Cell Rep. 21, 2419–2432 (2017).
Larson, J., Munkácsy, E. & Theta-burst, L. T. P. Brain Res. 1621, 38–50 (2015).
Xu, H., Baracskay, P., O’Neill, J. & Csicsvari, J. Assembly responses of hippocampal CA1 place cells predict learned behavior in goal-directed spatial tasks on the radial eight-arm maze. Neuron 101, 119–132.e4 (2019).
Jadhav, S. P., Kemere, C., German, P. W. & Frank, L. M. Awake hippocampal sharp-wave ripples support spatial memory. Science 336, 1454–1458 (2012).
Dupret, D., O’Neill, J., Pleydell-Bouverie, B. & Csicsvari, J. The reorganization and reactivation of hippocampal maps predict spatial memory performance. Nat. Neurosci. 13, 995–1002 (2010).
Turi, G. F. et al. Vasoactive intestinal polypeptide-expressing interneurons in the hippocampus support goal-oriented spatial learning. Neuron 101, 1150–1165.e8 (2019).
Bittner, K. C. et al. Conjunctive input processing drives feature selectivity in hippocampal CA1 neurons. Nat. Neurosci. 18, 1133–1142 (2015).
Hollup, S. A., Molden, S., Donnett, J. G., Moser, M. B. & Moser, E. I. Accumulation of hippocampal place fields at the goal location in an annular watermaze task. J. Neurosci. 21, 1635–1644 (2001).
Dupret, D., O’Neill, J. & Csicsvari, J. Dynamic reconfiguration of hippocampal interneuron circuits during spatial learning. Neuron 78, 166–180 (2013).
Ramon y Cajal, S. Textura del Sistema Nervioso del Hombre y de los Vertebrados: Estudios Sobre el Plan Estructural y Composición Histológica de los Centros Nerviosos Adicionados de Consideraciones Fisiológicas Fundadas en los Nuevos Descubrimentos (Moya, 1899).
Segal, M. Dendritic spines: morphological building blocks of memory. Neurobiol. Learn. Mem. 138, 3–9 (2017).
Holtmaat, A. & Svoboda, K. Experience-dependent structural synaptic plasticity in the mammalian brain. Nat. Rev. Neurosci. 10, 647–658 (2009).
Harris, K. M. & Stevens, J. K. Dendritic spines of CA 1 pyramidal cells in the rat hippocampus: serial electron microscopy with reference to their biophysical characteristics. J. Neurosci. 9, 2982–2997 (1989).
Bourne, J. N. & Harris, K. M. Balancing structure and function at hippocampal dendritic spines. Annu. Rev. Neurosci. 31, 47–67 (2008).
Nimchinsky, E. A., Sabatini, B. L. & Svoboda, K. Structure and function of dendritic spines. Annu. Rev. Physiol. 64, 313–353 (2002).
Noguchi, J., Matsuzaki, M., Ellis-Davies, G. C. & Kasai, H. Spine-neck geometry determines NMDA receptor-dependent Ca2+ signaling in dendrites. Neuron 46, 609–622 (2005).
Nusser, Z. et al. Cell type and pathway dependence of synaptic AMPA receptor number and variability in the hippocampus. Neuron 21, 545–559 (1998).
Denk, W., Strickler, J. H. & Webb, W. W. Two-photon laser scanning fluorescence microscopy. Science 248, 73–76 (1990).
Feng, G. et al. Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP. Neuron 28, 41–51 (2000).
Trachtenberg, J. T. et al. Long-term in vivo imaging of experience-dependent synaptic plasticity in adult cortex. Nature 420, 788–794 (2002).
Maletic-Savatic, M., Malinow, R. & Svoboda, K. Rapid dendritic morphogenesis in CA1 hippocampal dendrites induced by synaptic activity. Science 283, 1923–1927 (1999).
Engert, F. & Bonhoeffer, T. Dendritic spine changes associated with hippocampal long-term synaptic plasticity. Nature 399, 66–70 (1999).
Nägerl, U. V., Willig, K. I., Hein, B., Hell, S. W. & Bonhoeffer, T. Live-cell imaging of dendritic spines by STED microscopy. Proc. Natl Acad. Sci. USA 105, 18982–18987 (2008).
Pfeiffer, T. et al. Chronic 2P-STED imaging reveals high turnover of dendritic spines in the hippocampus in vivo. eLife 7, e34700 (2018).
Hofer, S. B., Mrsic-Flogel, T. D., Bonhoeffer, T. & Hübener, M. Experience leaves a lasting structural trace in cortical circuits. Nature 457, 313–317 (2009).
El-Boustani, S. et al. Locally coordinated synaptic plasticity of visual cortex neurons in vivo. Science 360, 1349–1354 (2018).
Kuhlman, S. J., O’Connor, D. H., Fox, K. & Svoboda, K. Structural plasticity within the barrel cortex during initial phases of whisker-dependent learning. J. Neurosci. 34, 6078–6083 (2014).
Zong, W. et al. Fast high-resolution miniature two-photon microscopy for brain imaging in freely behaving mice. Nat. Methods 14, 713–719 (2017).
Meng, G. et al. High-throughput synapse-resolving two-photon fluorescence microendoscopy for deep-brain volumetric imaging in vivo. eLife 8, e40805 (2019).
Matsuzaki, M., Honkura, N., Ellis-Davies, G. C. & Kasai, H. Structural basis of long-term potentiation in single dendritic spines. Nature 429, 761–766 (2004).
Nakahata, Y. & Yasuda, R. Plasticity of spine structure: local signaling, translation and cytoskeletal reorganization. Front. Synaptic Neurosci. 10, 29 (2018).
Shi, S. H. et al. Rapid spine delivery and redistribution of AMPA receptors after synaptic NMDA receptor activation. Science 284, 1811–1816 (1999).
Hayashi, Y. et al. Driving AMPA receptors into synapses by LTP and CaMKII: requirement for GluR1 and PDZ domain interaction. Science 287, 2262–2267 (2000).
Zhang, Y., Cudmore, R. H., Lin, D. T., Linden, D. J. & Huganir, R. L. Visualization of NMDA receptor-dependent AMPA receptor synaptic plasticity in vivo. Nat. Neurosci. 18, 402–407 (2015).
Roth, R. H., Zhang, Y. & Huganir, R. L. Dynamic imaging of AMPA receptor trafficking in vitro and in vivo. Curr. Opin. Neurobiol. 45, 51–58 (2017).
Wakayama, S. et al. Chemical labelling for visualizing native AMPA receptors in live neurons. Nat. Commun. 8, 14850 (2017).
Schnell, E. et al. Direct interactions between PSD-95 and stargazin control synaptic AMPA receptor number. Proc. Natl Acad. Sci. USA 99, 13902–13907 (2002).
Bats, C., Groc, L. & Choquet, D. The interaction between Stargazin and PSD-95 regulates AMPA receptor surface trafficking. Neuron 53, 719–734 (2007).
Gray, N. W., Weimer, R. M., Bureau, I. & Svoboda, K. Rapid redistribution of synaptic PSD-95 in the neocortex in vivo. PLoS Biol. 4, e370 (2006).
Wegner, W., Mott, A. C., Grant, S. G. N., Steffens, H. & Willig, K. I. In vivo STED microscopy visualizes PSD95 sub-structures and morphological changes over several hours in the mouse visual cortex. Sci. Rep. 8, 219 (2018).
Tang, A. H. et al. A trans-synaptic nanocolumn aligns neurotransmitter release to receptors. Nature 536, 210–214 (2016).
Haas, K. T. et al. Pre-post synaptic alignment through neuroligin-1 tunes synaptic transmission efficiency. eLife 7, e31755 (2018).
Nair, D. et al. Super-resolution imaging reveals that AMPA receptors inside synapses are dynamically organized in nanodomains regulated by PSD95. J. Neurosci. 33, 13204–13224 (2013).
Lin, M. Z. & Schnitzer, M. J. Genetically encoded indicators of neuronal activity. Nat. Neurosci. 19, 1142–1153 (2016).
Chen, X., Leischner, U., Rochefort, N. L., Nelken, I. & Konnerth, A. Functional mapping of single spines in cortical neurons in vivo. Nature 475, 501–505 (2011).
Chen, T. W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).
Adam, Y. et al. Voltage imaging and optogenetics reveal behaviour-dependent changes in hippocampal dynamics. Nature 569, 413–417 (2019).
Lee, S. J., Escobedo-Lozoya, Y., Szatmari, E. M. & Yasuda, R. Activation of CaMKII in single dendritic spines during long-term potentiation. Nature 458, 299–304 (2009).
Kourrich, S., Rothwell, P. E., Klug, J. R. & Thomas, M. J. Cocaine experience controls bidirectional synaptic plasticity in the nucleus accumbens. J. Neurosci. 27, 7921–7928 (2007).
Sepulveda-Orengo, M. T., Lopez, A. V., Soler-Cedeño, O. & Porter, J. T. Fear extinction induces mGluR5-mediated synaptic and intrinsic plasticity in infralimbic neurons. J. Neurosci. 33, 7184–7193 (2013).
Rumpel, S., LeDoux, J., Zador, A. & Malinow, R. Postsynaptic receptor trafficking underlying a form of associative learning. Science 308, 83–88 (2005).
Humeau, Y. et al. A pathway-specific function for different AMPA receptor subunits in amygdala long-term potentiation and fear conditioning. J. Neurosci. 27, 10947–10956 (2007).
Houbaert, X. et al. Target-specific vulnerability of excitatory synapses leads to deficits in associative memory in a model of intellectual disorder. J. Neurosci. 33, 13805–13819 (2013).
Fosque, B. F. et al. Neural circuits. Labeling of active neural circuits in vivo with designed calcium integrators. Science 347, 755–760 (2015).
Dittman, J. & Ryan, T. A. Molecular circuitry of endocytosis at nerve terminals. Annu. Rev. Cell Dev. Biol. 25, 133–160 (2009).
Ferro, M. et al. Functional mapping of brain synapses by the enriching activity-marker SynaptoZip. Nat. Commun. 8, 1229 (2017).
Gubernator, N. G. et al. Fluorescent false neurotransmitters visualize dopamine release from individual presynaptic terminals. Science 324, 1441–1444 (2009).
Rodriguez, P. C. et al. Fluorescent dopamine tracer resolves individual dopaminergic synapses and their activity in the brain. Proc. Natl Acad. Sci. USA 110, 870–875 (2013).
Dunn, M. et al. Designing a norepinephrine optical tracer for imaging individual noradrenergic synapses and their activity in vivo. Nat. Commun. 9, 2838 (2018).
Marvin, J. S. et al. An optimized fluorescent probe for visualizing glutamate neurotransmission. Nat. Methods 10, 162–170 (2013).
Marvin, J. S. et al. Stability, affinity, and chromatic variants of the glutamate sensor iGluSnFR. Nat. Methods 15, 936–939 (2018).
Patriarchi, T. et al. Ultrafast neuronal imaging of dopamine dynamics with designed genetically encoded sensors. Science 360, eaat4422 (2018).
Sun, F. et al. A genetically encoded fluorescent sensor enables rapid and specific detection of dopamine in flies, fish, and mice. Cell 174, 481–496.e19 (2018).
Jing, M. et al. A genetically encoded fluorescent acetylcholine indicator for in vitro and in vivo studies. Nat. Biotechnol. 36, 726–737 (2018).
Barber, D. M. et al. Optical control of AMPA receptors using a photoswitchable quinoxaline-2,3-dione antagonist. Chem. Sci. 8, 611–615 (2017).
Klippenstein, V., Hoppmann, C., Ye, S., Wang, L. & Paoletti, P. Optocontrol of glutamate receptor activity by single side-chain photoisomerization. eLife 6, e25808 (2017).
Takemoto, K. et al. Optical inactivation of synaptic AMPA receptors erases fear memory. Nat. Biotechnol. 35, 38–47 (2017).
Lin, J. Y. et al. Optogenetic inhibition of synaptic release with chromophore-assisted light inactivation (CALI). Neuron 79, 241–253 (2013).
Hayashi-Takagi, A. et al. Labelling and optical erasure of synaptic memory traces in the motor cortex. Nature 525, 333–338 (2015).
Liu, Q. et al. A photoactivatable botulinum neurotoxin for inducible control of neurotransmission. Neuron 101, 863–875.e6 (2019).
Gobbo, F. et al. Activity-dependent expression of Channelrhodopsin at neuronal synapses. Nat. Commun. 8, 1629 (2017).
Giese, K. P., Fedorov, N. B., Filipkowski, R. K. & Silva, A. J. Autophosphorylation at Thr286 of the alpha calcium-calmodulin kinase II in LTP and learning. Science 279, 870–873 (1998).
Yamagata, Y. et al. Kinase-dead knock-in mouse reveals an essential role of kinase activity of Ca2+/calmodulin-dependent protein kinase IIalpha in dendritic spine enlargement, long-term potentiation, and learning. J. Neurosci. 29, 7607–7618 (2009).
Rossetti, T. et al. Memory erasure experiments indicate a critical role of CaMKII in memory storage. Neuron 96, 207–216.e2 (2017).
Murakoshi, H. et al. Kinetics of endogenous CaMKII required for synaptic plasticity revealed by optogenetic kinase inhibitor. Neuron 94, 690 (2017).
Kelleher, R. J. III, Govindarajan, A., Jung, H. Y., Kang, H. & Tonegawa, S. Translational control by MAPK signaling in long-term synaptic plasticity and memory. Cell 116, 467–479 (2004).
Diering, G. H. & Huganir, R. L. The AMPA receptor code of synaptic plasticity. Neuron 100, 314–329 (2018).
Nicoll, R. A. A brief history of long-term potentiation. Neuron 93, 281–290 (2017).
Clem, R. L. & Huganir, R. L. Calcium-permeable AMPA receptor dynamics mediate fear memory erasure. Science 330, 1108–1112 (2010).
Park, J. et al. CaMKII phosphorylation of TARPγ-8 is a mediator of LTP and learning and memory. Neuron 92, 75–83 (2016).
Choquet, D. Linking nanoscale dynamics of AMPA receptor organization to plasticity of excitatory synapses and learning. J. Neurosci. 38, 9318–9329 (2018).
Choquet, D. & Triller, A. The dynamic synapse. Neuron 80, 691–703 (2013).
Kennedy, M. J. & Ehlers, M. D. Organelles and trafficking machinery for postsynaptic plasticity. Annu. Rev. Neurosci. 29, 325–362 (2006).
Lledo, P. M., Zhang, X., Südhof, T. C., Malenka, R. C. & Nicoll, R. A. Postsynaptic membrane fusion and long-term potentiation. Science 279, 399–403 (1998).
Jurado, S. et al. LTP requires a unique postsynaptic SNARE fusion machinery. Neuron 77, 542–558 (2013).
Wu, D. et al. Postsynaptic synaptotagmins mediate AMPA receptor exocytosis during LTP. Nature 544, 316–321 (2017).
Collingridge, G. L., Peineau, S., Howland, J. G. & Wang, Y. T. Long-term depression in the CNS. Nat. Rev. Neurosci. 11, 459–473 (2010).
Awasthi, A. et al. Synaptotagmin-3 drives AMPA receptor endocytosis, depression of synapse strength, and forgetting. Science 363, eaav1483 (2019).
Kakegawa, W. et al. Optogenetic control of synaptic AMPA receptor endocytosis reveals roles of LTD in motor learning. Neuron 99, 985–998.e6 (2018).
Penn, A. C. et al. Hippocampal LTP and contextual learning require surface diffusion of AMPA receptors. Nature 549, 384–388 (2017).
Heine, M. et al. Surface mobility of postsynaptic AMPARs tunes synaptic transmission. Science 320, 201–205 (2008).
Dupuis, J. P. et al. Surface dynamics of GluN2B-NMDA receptors controls plasticity of maturing glutamate synapses. EMBO J. 33, 842–861 (2014).
Peng, X. et al. Cellular plasticity induced by anti-α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor encephalitis antibodies. Ann. Neurol. 77, 381–398 (2015).
Haselmann, H. et al. Human autoantibodies against the AMPA receptor subunit GluA2 induce receptor reorganization and memory dysfunction. Neuron 100, 91–105.e9 (2018).
Neubert, F. et al. Bioorthogonal click chemistry enables site-specific fluorescence labeling of functional NMDA receptors for super-resolution imaging. Angew. Chem. Int. Edn Engl. 57, 16364–16369 (2018).
Acknowledgements
We acknowledge the critical suggestions of A. Getz, F. Lanore and T. Bienvenu on this manuscript. We express our warmest thanks to the many outstanding members of our teams and collaborators that participated in the elaboration of these concepts. This work is currently supported by funding from the Ministère de l’Enseignement Supérieur et de la Recherche, Centre National de la Recherche Scientifique, ERC Grant #787340 Dyn-Syn-Mem, FRM Grant # DEQ20180339189 AMPA-MO-CO and the Conseil Régional de Nouvelle Aquitaine.
Author information
Authors and Affiliations
Contributions
D.C. and Y.H. generated the concepts, analyzed the bibliography and wrote the manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Peer review information: Nature Neuroscience thanks Denise Cai, Ryohei Yasuda and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Humeau, Y., Choquet, D. The next generation of approaches to investigate the link between synaptic plasticity and learning. Nat Neurosci 22, 1536–1543 (2019). https://doi.org/10.1038/s41593-019-0480-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41593-019-0480-6
This article is cited by
-
Towards a network-based operationalization of plasticity for predicting the transition from depression to mental health
Nature Mental Health (2024)
-
Cholecystokinin B receptor antagonists for the treatment of depression via blocking long-term potentiation in the basolateral amygdala
Molecular Psychiatry (2023)
-
Distributing task-related neural activity across a cortical network through task-independent connections
Nature Communications (2023)
-
Critically synchronized brain waves form an effective, robust and flexible basis for human memory and learning
Scientific Reports (2023)
-
CA3 hippocampal synaptic plasticity supports ripple physiology during memory consolidation
Nature Communications (2023)
