The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Activity-dependent scaling of quantal amplitude in neocortical neurons
Abstract
Information is stored in neural circuits through long-lasting changes in synaptic strengths. Most studies of information storage have focused on mechanisms such as long-term potentiation and depression (LTP and LTD), in which synaptic strengths change in a synapse-specific manner. In contrast, little attention has been paid to mechanisms that regulate the total synaptic strength of a neuron. Here we describe a new form of synaptic plasticity that increases or decreases the strength of all of a neuron's synaptic inputs as a function of activity. Chronic blockade of cortical culture activity increased the amplitude of miniature excitatory postsynaptic currents (mEPSCs) without changing their kinetics. Conversely, blocking GABA (gamma-aminobutyric acid)-mediated inhibition initially raised firing rates, but over a 48-hour period mESPC amplitudes decreased and firing rates returned to close to control values. These changes were at least partly due to postsynaptic alterations in the response to glutamate, and apparently affected each synapse in proportion to its initial strength. Such 'synaptic scaling' may help to ensure that firing rates do not become saturated during developmental changes in the number and strength of synaptic inputs, as well as stabilizing synaptic strengths during Hebbian modification and facilitating competition between synapses.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“There is compelling evidence from experiments in neuronal cultures that central neurons are able to maintain average firing rates around a homeostatic set point.”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Turrigiano et al. 1998
In the citing paper
“One such mechanism is synaptic scaling, which allows neurons to detect changes in their own firing rates through a set of calcium-dependent sensors that then regulate receptor trafficking to increase or decrease the accumulation of glutamate receptors at synaptic sites.”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Turrigiano et al. 1998
In the citing paper
“When cortical or hippocampal neurons are induced to fire more than normal, over many hours firing returns to baseline levels, and similarly, if neuronal firing is reduced over time, neurons compensate and again firing is restored (Fig. 1A) (Turrigiano et al. 1998;Burrone et al. 2002).”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Turrigiano et al. 1998
In the citing paper
“Synaptic scaling was first identified in cultured neocortical neurons, where it was observed that perturbing network activity generated compensatory changes in synaptic strength that were in the right direction to restore average firing rates to baseline values (Turrigiano et al. 1998).”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Turrigiano et al. 1998
In the citing paper
“by measuring minis arising from many synapses onto the same neuron, it was observed that modulating network activity induced uniform increases or decreases in the entire mini amplitude distribution, in effect scaling postsynaptic strength up or down (Turrigiano et al. 1998;Desai et al. 2002;Gainey et al. 2009).”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Turrigiano et al. 1998
In the citing paper
“Interestingly, the same manipulation (activity blockade using TTX or AMPAR antagonists) that only affects mini amplitude in young cultures (Turrigiano et al. 1998;Wierenga et al. 2005) can also induce changes in mini frequency and in presynaptic release probability in older neuronal cultures (Wierenga et al. 2006), through a process that involves postsynaptic hyperpolarization and a drop in”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Turrigiano et al. 1998
In the citing paper
“Synaptic scaling has now been shown in a variety of central neurons both in vitro and in vivo, including neocortical and hippocampal pyramidal neurons and spinal neurons (O'Brien et al. 1998;Turrigiano et al. 1998;Desai et al. 2002;Stellwagen and Malenka 2006;Goel and Lee 2007;Kim and Tsien 2008;Knogler et al. 2010).”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Turrigiano et al. 1998
In the citing paper
“Although in neocortical networks the net effects of changes in excitation and inhibition appear to be homeostatic (Rutherford et al. 1998;Turrigiano et al. 1998;Maffei et al. 2004), different classes of inhibitory synapse are regulated differently by lowered activity.”
From Homeostatic Synaptic Plasticity: Local and Global Mechanisms for Stabilizing Neuronal Function (2012) · cites this paper as Turrigiano et al. 1998
In the citing paper
“In response to chronic hyperactivity or hypoactivity, neurons can engage homeostatic scaling-down or scaling-up respectively, in which the strength of excitatory synapses on a neuron is globally modified to maintain neuronal activity in a physiological range (O'Brien et al., 1998, Turrigiano et al., 1998, Turrigiano, 2008).”
From The AMPA Receptor Code of Synaptic Plasticity (2018) · cites this paper as Turrigiano et al., 1998
In the citing paper
“Sample sizes were initially determined based on prior work using social interaction54,65 and intrinsic physiology62, no formal statistical methods were used to pre-determine sample sizes.”
From Insular cortex mediates approach and avoidance responses to social affective stimuli (2018) · cites this paper as [62]
Citations
Cites
Bienenstock, E., Cooper, L., & Munro, P. (1982) · The Journal of Neuroscience · doi:10.1523/jneurosci.02-01-00032.1982 · Cited by 2,896
Liao, D., Hessler, N. A., & Malinow, R. (1995) · Nature · doi:10.1038/375400a0 · Cited by 1,365
Regulatory phosphorylation of AMPA-type glutamate receptors by CaM-KII during long-term potentiation
Barria, A., Muller, D., Derkach, V., Griffith, L. C., & Soderling, T. R. (1997) · Science · doi:10.1126/science.276.5321.2042 · Cited by 1,049
Impulse activity and the patterning of connections during cns development
Shatz, C. J. (1990) · Neuron · doi:10.1016/0896-6273(90)90333-b · Cited by 766
A study of supersensitivity in denervated mammalian skeletal muscle
Axelsson, J., & Thesleff, S. (1959) · The Journal of Physiology · doi:10.1113/jphysiol.1959.sp006233 · Cited by 732
A Physiological Mechanism for Hebb's Postulate of Learning
Stent, G. S. (1973) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.70.4.997 · Cited by 710
Mechanisms Underlying Long-Term Potentiation of Synaptic Transmission
Madison, D. V., Malenka, R. C., & Nicoll, R. A. (1991) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.14.030191.002115 · Cited by 617
Maturation of a Central Glutamatergic Synapse
Wu, G.-Y., Malinow, R., & Cline, H. T. (1996) · Science · doi:10.1126/science.274.5289.972 · Cited by 546
Linden, D. J., & Connor, J. A. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001535 · Cited by 519
The formation and maturation of synapses in the visual cortex of the rat. II. Quantitative analysis
Blue, M. E., & Parnavelas, J. G. (1983) · Journal of Neurocytology · doi:10.1007/bf01181531 · Cited by 506
Research works printed but not linked: 2
- Hebb, D. O. The Organization of Behavior: a Neurophysiological Theory (Wiley, New York, 1949).
- Axelsson, J. & Thesleff, S. Astudy of supersensitivity in denervated mammalian skeletal muscle. J.Physiol. (Lond.) 149, 178–193 (1957).
Cited by
Sorted by citations
Items 2,101–2,200 of 2,247
Synaptic plasticity and learning and memory
Cooke, S. F., & Chaloner, F. A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-15754-7.00044-4
Mayzel, J., & Schneidman, E. (2024) · eLife · doi:10.7554/elife.96566.3.sa2
Koesters, A. G., Rich, M. M., & Engisch, K. L. (2025) · eLife · doi:10.7554/elife.90261.3
Efficient coding explains neural response homeostasis and stimulus-specific adaptationPreprint
Young, E. J., & Ahmadian, Y. (2025) · eLife · doi:10.7554/elife.104746.1
Efficient coding explains neural response homeostasis and stimulus-specific adaptationPreprint
Young, E. J., & Ahmadian, Y. (2025) · eLife · doi:10.7554/elife.104746
Vlachos, P. E., & Triesch, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.10.648137
Premature vision drives aberrant development of response properties in primary visual cortexPreprint
Griswold, S. V., & Hooser, S. D. V. (2025) · eLife · doi:10.7554/elife.106513.1
Diering, G. H. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2506039122
Parallel synapses with transmission nonlinearities enhance neuronal classification capacity
Song, Y., & Benna, M. K. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012285
Cell-Type-Specific Synaptic Scaling Mechanisms Differentially Contribute to Associative Learning
Veneto, F., Kepçe, A., Wu, Y. K., & Gjorgjieva, J. (2026) · Journal of Neuroscience · doi:10.1523/jneurosci.0987-25.2026
Unreliable homeostatic action potential broadening in cultured dissociated neuronsPreprint
Ritzau‐Jost, A., Rajayer, S. R., Nerlich, J., Maciąg, F., John, A., Russier, M., Sabater, V. G., Steiger, L. J., Coq, J., Eilers, J., et al. (2025) · eLife · doi:10.1101/2025.05.09.653135
Koesters, A. G., Rich, M. M., & Engisch, K. L. (2025) · eLife · doi:10.7554/elife.90261.4
Talbi, R., Stincic, T. L., Lynch, N. A., Torres, E., Ferrari, K., Hae, C. J., Medve, E., Walec, K. D., Zdon, S. T., Pereira, S. A., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.25.661567
Unreliable homeostatic action potential broadening in cultured dissociated neuronsPreprint
Ritzau‐Jost, A., Rajayer, S. R., Nerlich, J., Maciąg, F., John, A., Russier, M., Sabater, V. G., Steiger, L. J., Coq, J., Eilers, J., et al. (2025) · eLife · doi:10.7554/elife.106995
Unreliable homeostatic action potential broadening in cultured dissociated neuronsPreprint
Ritzau‐Jost, A., Rajayer, S. R., Nerlich, J., Maciąg, F., John, A., Russier, M., Sabater, V. G., Steiger, L. J., Coq, J., Eilers, J., et al. (2025) · eLife · doi:10.7554/elife.106995.1
Premature vision drives aberrant development of response properties in primary visual cortexPreprint
Griswold, S. V., & Hooser, S. D. V. (2025) · eLife · doi:10.7554/elife.106513.2
Experience-Dependent Intrinsic Plasticity in Layer IV of Barrel Cortex at Whisking Onset
Shallow, M. C., Tian, L., Higashikubo, B. T., Lin, H., Lefton, K. B., Chen, S., Dougherty, J. D., Culver, J. P., Lambo, M. E., & Hengen, K. B. (2025) · eNeuro · doi:10.1523/eneuro.0252-25.2025
Tau controls NMDA receptor trafficking during homeostatic synaptic plasticityPreprint
Yong, X. L. H., Stefanoska, K., Kwan, W. C., Irons, I., Padmanabhan, P., Samokhina, E., Kneynsberg, A., Dehorter, N., Ittner, A., Götz, J., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.28.667139
Emergence of Balanced Cortical Activity via Calcium-Regulated Synaptic HomeostasisPreprint
van Vreewsijk, C., & Farkhooi, F. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.04.674182
Kosche, G., Fratzl, A., Munz, M., & Roska, B. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.13.672380
Efficient coding explains neural response homeostasis and stimulus-specific adaptationPreprint
Young, E. J., & Ahmadian, Y. (2025) · eLife · doi:10.7554/elife.104746.2
Feedforward extraction of behaviorally significant information by neocortical columns
Favorov, O. V., & Kurşun, O. (2025) · Frontiers in Neural Circuits · doi:10.3389/fncir.2025.1615232
A network of Bayesian agents for reward prediction and noise tolerance
Gandolfi, D., Tincani, M., Boiani, G. M., Benatti, L., Zanotti, T., Pezzulo, G., Pagnoni, G., Puglisi, F. M., & Mapelli, J. (2025) · iScience · doi:10.1016/j.isci.2025.113813
Fritz, I., Wang, F., Chirif, R., Malakasis, N., Gjorgjieva, J., & Castro, A. F. (2025) · eLife · doi:10.7554/elife.108643
Roy, A., & Prescott, S. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.10.693436 · Cited by 1
Intrinsic Stabilization of Output Rates by Spike-Time Dependent Hebbian Learning
Kempter, R., Wulfram Gerstner, B., & Hemmen, J. L. V. (1999)
Changes in synaptic proteins in hippocampal area CA1 of a rat learned helpless model of depression
Bieler, M. (2013) · BIBSYS Brage (BIBSYS (Norway))
Molecular mechanisms of synaptic plasticity in adult mammalian sensory cortex
He, H. (2007) · University Libraries (University of Maryland)
Intercellular Communication and Heterosynaptic Metaplasticity in the Rodent Hippocampus
Jones, O. D. (2014) · Otago University Research Archive (University of Otago)
Investigating the relationship between anxiety and tinnitus development in a rodent model
Zimdahl, J. W. (2024) · UWA Profiles and Research Repository (University of Western Australia) · doi:10.26182/qxv2-1b40
Sousouri, G. (2021) · Zurich Open Repository and Archive (University of Zurich) · doi:10.3929/ethz-b-000481360
Cain, S. M., Alles, S. R. A., Gopaul, R., Bernier, L.-P., Yung, A. C., Bauman, A., Yang, Y., Baker, G. B., Kozłowski, P., MacVicar, B. A., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26635494
Variations in Neuronal Population Activity across Behaviors, Brain Regions, and Disease
Chockanathan, U., & Padmanabhan, K. (2022) · UR Research (University of Rochester)
Hand use affects somatotopy, but does somatotopy affect hand performance?
Li, Z. (2024) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)
Molecular mechanisms underlying the role of SynGAP in cognition and synaptopathies
Gou, G., & Molecular, U. A. D. B. D. D. B. I. D. B. (2019) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)
The role of interferon gamma in cortical synaptic plasticity and behavioural output
Abuzgaya, M. (2023) · eScholarship@McGill (McGill) · doi:10.82308/16664
Modélisation de la structure et dynamique corticale avec application en apprentissage machine
Brodeur, S. (2020) · Knowledge UdeS (Institutional Deposit of the University of Sherbrooke)
Fritz, I., Wang, F., Chirif, R., Malakasis, N., Gjorgjieva, J., & Castro, A. F. (2025) · eLife · doi:10.7554/elife.108643.1
Exploring Plasticity Mechanisms in Learning and Memory: An Insight into Alzheimer’s Disease
Juweria, M., Azim, N., & Nguyen, Q. (2025) · UTSC s Journal of Natural Sciences · doi:10.33137/jns.v4i1.43407
In vivo AGO-APP for cell-type- and compartment-specific miRNA profiling in the mouse brain
Surbhi, S., Erni, A., Vincenzi, F., Tessier, B., Venugopal, V., Meister, G., Favereaux, A., Cremer, H., & Béclin, C. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.101267
Effects of Introducing Synaptic Scaling on Spiking Neural Network Learning
Touda, S., & Okuno, H. (2025) · International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) · doi:10.1109/iciibms66230.2025.11316732
Vilches‐Herrando, E., Bey, G. R., Hernández, R. G., Gento‐Caro, Á., Pastor, Á. M., Campos‐Caro, A., González‐Forero, D., & Moreno‐López, B. (2026) · Acta Physiologica · doi:10.1111/apha.70158
Distinct NMDA Receptor Pools Determine Diverse Forms of Cortical PlasticityPreprint
Rannio, S., Lubembele, K., Ko, C. B., Cherepacha, N., Li, V., Moffat, G. L., Alageswaran, S., Thomazeau, A., Luján, R., & Sjöström, P. J. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.14.705915
Absence of homeostatic downscaling in dentate gyrus granule cellsPreprint
Jones, O. D., Benjamin, K., Empson, R. M., & Abraham, W. C. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.13.705706
Ujas, T. A., Tavakoli, N. S., Yanev, P. G., Torres, V. O., Turchan-Cholewo, J. T., Kong, X., Plautz, E. J., Bachstetter, A. D., Monson, N. L., Volk, L. J., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.02.709034
Alcantara‐Gonzalez, D., Santiago, E., & Peña‐Ortega, F. (2026) · Frontiers in Dementia · doi:10.3389/frdem.2026.1738954
High-resolution transcranial direct current stimulation in drug-resistant epilepsy
Denoyer, Y. (2019) · theses.fr (ABES)
Kruse, P., Schob, C., Schwabe, K., & Lenz, M. (2026) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2026.1764324
A neuromorphic safety monitor for verifiable runtime assurance in stochastic control loops
Kaczmarek, S. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.133215
Fahey, G. C., Ippolito, S. J., & Matthews, G. I. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.133419
Kaddatz, H., Wenzel, L., Pril, E., Meien, S., Harz, V., Burkert, L., Behrangi, N., Zimmermann, A., Frintrop, L., Amor, S., et al. (2026) · Acta Neuropathologica · doi:10.1007/s00401-026-03000-x
Cortical plasticity, dynamic neural fields and self-organization
Detorakis, G. (2013) · theses.fr (ABES) · doi:10.70675/24f5cabaz818dz44f0za66cz4145d2354bf5
induction non-invasive d'une plasticité de la commande ventilatoire chez l'humain sain
Nierat, M. (2014) · theses.fr (ABES) · doi:10.70675/c6ef905cz69f1z433cz90a9z03800fb00a74
Soula, A. (2017) · theses.fr (ABES) · doi:10.70675/4de7a893za0efz441dz85bdzc5773884ca0f
Synaptic plasticity rule between parallel fibres and Purkinje cells in the cerebellum
Bouvier, G. (2015) · theses.fr (ABES) · doi:10.70675/d52a1caez11b0z4385z81d1zcb8bb70574d7
Short and long term synaptic plasticities via action potential shape modulation in cortical networks
Zbili, M. (2016) · theses.fr (ABES) · doi:10.70675/8d69ea15zc169z4647z9d8fzb4dc36702f4a
Étude du rôle perceptivo-mnésique du lobe temporal médial par les potentiels évoqués intracérébraux
Krieg, J. (2016) · theses.fr (ABES) · doi:10.70675/ac0f1691zf61fz470ezaf19z61ac1ba38340
Learning efficient signal representation in sparse spike-coding networks
Maraš, M. (2019) · theses.fr (ABES) · doi:10.70675/1c258a24z1787z4e9cz9823z848d8095638f
From AMPAR lateral diffusion to whisker perception : a new model for cortical remapping
Campelo, T. (2019) · theses.fr (ABES) · doi:10.70675/522bd21az83c3z4251z9e4dz4955a2c5c273
Stimulation électrique transcrânienne multisite dans l'épilepsie pharmaco-résistante
Denoyer, Y. (2019) · theses.fr (ABES) · doi:10.70675/0c55a83dz3729z4ee8zb7c9zd03118d26e81
Altérations de la connectivité corticale au cours de périodes critiques du développement
Druart, M. (2020) · theses.fr (ABES) · doi:10.70675/b4f48d73za850z42b2z8dadzfad47d4f0a69
Transport intracellulaire des récepteurs AMPA et régulation par leurs protéines associées
Bonnet, C. (2021) · theses.fr (ABES) · doi:10.70675/a51a45f6zee8cz4c6az85a5z8b01dfd87159
Sarazin, M. (2021) · theses.fr (ABES) · doi:10.70675/bbd73c82z58a3z46c2za17cz56614cc8acbd
Physiopathologie des comas isoélectriques : de l’EEG au neurone
Carton‐Leclercq, A. (2023) · theses.fr (ABES) · doi:10.70675/7e9150a6z8959z43baza4b4zcaf0222fc163
Abdallah, N. H.-B. (2020) · theses.fr (ABES) · doi:10.70675/f33c8cd2z87e6z4346zbfcez57d516772a52
Investigating the effects of noise trauma across a cortical column in the primary auditory cortex
Parameshwarappa, V. (2021) · theses.fr (ABES) · doi:10.70675/e6313028zc7afz4eaezae9bzd2f128cbe692
Sengupta, R. (2026) · IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) · doi:10.1109/iatmsi68868.2026.11465241
Hunter, D. (2023) · theses.fr (ABES) · doi:10.70675/ae0cf321z922dz4431z8e9czca6cbf457b2e
Socio-communicative and nucleus accumbens core dysfunctions in fragile X syndrome
Giua, G. (2023) · theses.fr (ABES) · doi:10.70675/e45d048ez2538z4905zba74z1de16201406a
Hebbian and Homeostatic plasticity in the adult visual cortex
Prosper, A. (2025) · theses.fr (ABES) · doi:10.70675/62138cf3zacbdz46b0z8e1azecbeaf4bb955
Marco, I. D., Sansevero, G., Berardi, N., & Sale, A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.13.718078
Linde, J. (2026) · RWTH Publications (RWTH Aachen) · doi:10.18154/rwth-2026-01788
Rundo, F., Spata, M. O., Pino, C., Calabretta, M., Messina, A. A., Rundo, M., & Battiato, S. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.132490
Cell Density Impacts Population Activity in Human iPSC-Derived Neural Networks
Uzun, Y. S., Santos, R., Marchetto, M. C., & Padmanabhan, K. (2026) · eNeuro · doi:10.1523/eneuro.0176-24.2026
Temporal Dynamics of Cortical State Plasticity Following Adult Vision LossPreprint
Djerourou, I., Ptito, M., & Vanni, M. P. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.21.719808
Gemo, E., Bonnin, M., & Corinto, F. (2026) · Neuromorphic Computing and Engineering · doi:10.1088/2634-4386/ae66b3
Peng, Y.-J., Yu, D., Li, X., Wang, X. J., Jia, Y., & Yang, L. (2026) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2026.118465
Fundamental questions on closed-loop neuromodulation: a control theory perspective
Wang, M., Zhang, L., Liang, Z., & Huang, G. (2026) · Cognitive Neurodynamics · doi:10.1007/s11571-026-10452-0
When can neuronal activity-dependent homeostatic plasticity maintain circuit-level properties?
Stolting, L., & Beer, R. D. (2026) · Journal of Computational Neuroscience · doi:10.1007/s10827-026-00936-7
Rank Dependency of Rescaled Pruning in Recurrent Neural NetworksPreprint
Wang, A. Q., Kim, S. H., & Choi, H. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.30.728930
Α new analog self-repairing algorithm based on a novel tripartite synapse circuit
Ranjbar, M., Karimi, G., Khosravi, A., & Abbott, D. (2026) · Results in Engineering · doi:10.1016/j.rineng.2026.111492
Metadata
- Authors
- Turrigiano, G. G., Leslie, K. R., Desai, N. S., Rutherford, L. C., & Nelson, S. B.
- Affiliations
- Brandeis University (US)
- Corresponding author
- Turrigiano, Gina G.
- Venue
- Nature
- Published
- 1998-02
- Volume
- 391
- Issue
- 6670
- Pages
- 892-896
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W1514853588
- Semantic Scholar
- a2bfdaf93cc88c5d56c9b08b910e2e9e1fcfed40
- Cited by
- 2,226
- References
- 30
- Citations by year
- 2026: 53 · 2025: 96 · 2024: 86 · 2023: 76 · 2022: 91 · 2021: 107 · 2020: 110 · 2019: 89 · 2018: 101 · 2017: 97 · 2016: 74 · 2015: 115 · 2014: 91 · 2013: 118 · 2012: 84
- FWCI
- 18.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- 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 scaling, miniature excitatory postsynaptic currents, neocortical neurons, synaptic plasticity, GABAergic inhibition, glutamate response, firing rate, Hebbian learning, synaptic competition, long-term potentiation and depression, cortical development
- MeSH terms
- Animals, Bicuculline, Cells, Cultured, Membrane Potentials, Synaptic Transmission, Neuronal Plasticity, Tetrodotoxin, Visual Cortex, 2-Amino-5-phosphonovalerate, Receptors, N-Methyl-D-Aspartate, Pyramidal Cells, alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid, Excitatory Amino Acid Antagonists, Glutamic Acid, GABA Antagonists, Rats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
