The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks
Critical network states and neural plasticity enable adaptive behavior in dynamic environments, supporting efficient information processing and experience-dependent learning. Synaptic-weight-based Hebbian plasticity and homeostatic synaptic scaling are key mechanisms that enable memory while stabili...
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eLife Sciences Publications Ltd
2025-07-01
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| Online Access: | https://elifesciences.org/articles/88376 |
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| author | Han Lu Sandra Diaz-Pier Maximilian Lenz Andreas Vlachos |
| author_facet | Han Lu Sandra Diaz-Pier Maximilian Lenz Andreas Vlachos |
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| description | Critical network states and neural plasticity enable adaptive behavior in dynamic environments, supporting efficient information processing and experience-dependent learning. Synaptic-weight-based Hebbian plasticity and homeostatic synaptic scaling are key mechanisms that enable memory while stabilizing network dynamics. However, the role of structural plasticity as a homeostatic mechanism remains less consistently reported, particularly under activity inhibition, leading to an incomplete understanding of its functional impact. In this study, we combined live-cell microscopy of eGFP-labeled neurons in mouse organotypic entorhinal-hippocampal tissue cultures (Thy1-eGFP mice of both sexes) with computational modeling to investigate how synapse-number-based structural plasticity responds to activity perturbations and interacts with homeostatic synaptic scaling. Tracking individual dendritic segments, we found that inhibiting excitatory neurotransmission does not monotonically regulate dendritic spine density. Specifically, inhibition of AMPA receptors with 200 nM 2,3-dioxo-6-nitro-7-sulfamoyl-benzo[f]quinoxaline (NBQX) increased spine density, whereas complete AMPA receptor blockade with 50 μM NBQX reduced it. Motivated by these findings, we developed network simulations incorporating a biphasic structural plasticity rule governing activity-dependent synapse formation. These simulations showed that the biphasic rule maintains neural activity homeostasis under stimulation and permits either synapse formation or synapse loss depending on the degree of activity deprivation. Homeostatic synaptic scaling further modulated recurrent connectivity, network activity, and structural plasticity outcomes. It reduced stimulation-triggered synapse loss by downscaling synaptic weights and rescued silencing-induced synapse loss by upscaling recurrent input, thus reactivating silent neurons. The interaction between these mechanisms provides a mechanistic explanation for divergent findings in the literature. In summary, homeostatic synaptic scaling and homeostatic structural plasticity dynamically compete and compensate for each other, ensuring efficient and robust control of firing rate homeostasis. |
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| publishDate | 2025-07-01 |
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| spelling | doaj-art-5c9b8f8d02a94bdea04c2e29a52f3cc82025-07-04T12:00:20ZengeLife Sciences Publications LtdeLife2050-084X2025-07-011210.7554/eLife.88376The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networksHan Lu0https://orcid.org/0000-0002-3508-2208Sandra Diaz-Pier1https://orcid.org/0000-0002-3168-5394Maximilian Lenz2https://orcid.org/0000-0003-3147-4949Andreas Vlachos3https://orcid.org/0000-0002-2646-3770Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Center BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany; Simulation and Data Lab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, Forschungszentrum Jülich GmbH, Jülich, GermanySimulation and Data Lab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, Forschungszentrum Jülich GmbH, Jülich, GermanyDepartment of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Institute of Neuroanatomy and Cell Biology, Hannover Medical School, Hannover, GermanyDepartment of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Center BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany; Center for Basics in Neuromodulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, GermanyCritical network states and neural plasticity enable adaptive behavior in dynamic environments, supporting efficient information processing and experience-dependent learning. Synaptic-weight-based Hebbian plasticity and homeostatic synaptic scaling are key mechanisms that enable memory while stabilizing network dynamics. However, the role of structural plasticity as a homeostatic mechanism remains less consistently reported, particularly under activity inhibition, leading to an incomplete understanding of its functional impact. In this study, we combined live-cell microscopy of eGFP-labeled neurons in mouse organotypic entorhinal-hippocampal tissue cultures (Thy1-eGFP mice of both sexes) with computational modeling to investigate how synapse-number-based structural plasticity responds to activity perturbations and interacts with homeostatic synaptic scaling. Tracking individual dendritic segments, we found that inhibiting excitatory neurotransmission does not monotonically regulate dendritic spine density. Specifically, inhibition of AMPA receptors with 200 nM 2,3-dioxo-6-nitro-7-sulfamoyl-benzo[f]quinoxaline (NBQX) increased spine density, whereas complete AMPA receptor blockade with 50 μM NBQX reduced it. Motivated by these findings, we developed network simulations incorporating a biphasic structural plasticity rule governing activity-dependent synapse formation. These simulations showed that the biphasic rule maintains neural activity homeostasis under stimulation and permits either synapse formation or synapse loss depending on the degree of activity deprivation. Homeostatic synaptic scaling further modulated recurrent connectivity, network activity, and structural plasticity outcomes. It reduced stimulation-triggered synapse loss by downscaling synaptic weights and rescued silencing-induced synapse loss by upscaling recurrent input, thus reactivating silent neurons. The interaction between these mechanisms provides a mechanistic explanation for divergent findings in the literature. In summary, homeostatic synaptic scaling and homeostatic structural plasticity dynamically compete and compensate for each other, ensuring efficient and robust control of firing rate homeostasis.https://elifesciences.org/articles/88376homeostatic plasticitysynaptic scalingstructural plasticityspiking neural networksorganotypic slice cultures |
| spellingShingle | Han Lu Sandra Diaz-Pier Maximilian Lenz Andreas Vlachos The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks eLife homeostatic plasticity synaptic scaling structural plasticity spiking neural networks organotypic slice cultures |
| title | The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks |
| title_full | The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks |
| title_fullStr | The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks |
| title_full_unstemmed | The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks |
| title_short | The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks |
| title_sort | interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks |
| topic | homeostatic plasticity synaptic scaling structural plasticity spiking neural networks organotypic slice cultures |
| url | https://elifesciences.org/articles/88376 |
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