Neuropilin-2/PlexinA3 Receptors Associate with GluA1 and Mediate Sema3F-Dependent Homeostatic Scaling in Cortical Neurons
Qiang WangShu‐Ling ChiuEleftheria KoropouliIngie HongSarah MitchellTeresa EaswaranNatalie R. HamiltonAhleah S. GustinaQianwen ZhuDavid D. GintyRichard L. HuganirAlex L. Kolodkin
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Homeostatic plasticity
Synaptic scaling
Homeostasis
Brain development, sensory information processing, and learning and memory processes depend on Hebbian forms of synaptic plasticity, and on the remodeling and pruning of synaptic connections. Neurons in networks implicated in these processes carry out their functions while facing constant perturbation; homeostatic responses are therefore required to maintain neuronal activity within functional ranges for proper brain function. Here, we will review in vitro and in vivo studies demonstrating that several mechanisms underlie homeostatic plasticity of excitatory synapses, and identifying participant molecular players. Emerging evidence suggests a link between disrupted homeostatic synaptic plasticity and neuropsychiatric and neurologic disorders. Hebbian forms of synaptic plasticity, such as long-term potentiation (LTP), induce long-lasting changes in synaptic strength, which can be destabilizing and drive activity to saturation. Conversely, homeostatic plasticity operates to compensate for prolonged activity changes, stabilizing neuronal firing within a dynamic physiological range. We review mechanisms underlying homeostatic plasticity, and address how neurons integrate distinct forms of plasticity for proper brain function. This article is part of a mini review series: "Synaptic Function and Dysfunction in Brain Diseases".
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Homeostatic synaptic plasticity remains an enigmatic form of synaptic plasticity. Increasing interest on the topic has fuelled a surge of recent studies that have identified key molecular players and the signaling pathways involved. However, the new findings also highlight our lack of knowledge concerning some of the basic properties of homeostatic synaptic plasticity. In this review we address how homeostatic mechanisms balance synaptic strengths between the presynaptic and the postsynaptic terminals and across synapses that share the same postsynaptic neuron.
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Homeostatic plasticity
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Both theoretical and experimental research has indicated that the synaptic strength between neurons in a network needs to be properly fine-tuned and controlled by homeostatic mechanisms to ensure proper network function. One such mechanism that has been extensively characterized is synaptic homeostatic plasticity or global synaptic scaling. This mechanism refers to the bidirectional ability of all synapses impinging on a neuron to actively compensate for changes in the neuron's overall excitability. Here, using a combination of electrophysiological, two-photon glutamate uncaging and imaging methods, we show that mature individual synapses, independent of neighboring synapses, have the ability to autonomously sense their level of activity and actively compensate for it in a homeostatic-like fashion. This synapse-specific homeostatic plasticity, similar to global synaptic plasticity, requires the immediate early gene Arc. Together, our results document an extra level of regulation of synaptic function that bears important computational consequences on information storage in the brain.
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Abstract The ability of synapses to modify their functional properties and adjust the amount of neurotransmitter release at their terminals is essential for formation of appropriate neural circuits during development and crucial for higher brain functions throughout life. Many forms of synaptic plasticity can adjust synaptic strength down (depression) or up (potentiation); however, depending on the cellular context as the forces of change act upon the synapse, other synaptic mechanisms are activated to resist change. This form of synaptic plasticity is generally referred to as homeostatic synaptic plasticity. Accumulating experimental evidence indicates that translational mechanisms play a critical role in the regulation of homeostatic synaptic plasticity. This chapter will review studies that contribute to this body of evidence, including a role for the target of rapamycin in the retrograde regulation of synaptic homeostasis.
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Theoretical and computational frameworks for synaptic plasticity and learning have a long and cherished history, with few parallels within the well-established literature for plasticity of voltage-gated ion channels. In this study, we derive rules for plasticity in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, and assess the synergy between synaptic and HCN channel plasticity in establishing stability during synaptic learning. To do this, we employ a conductance-based model for the hippocampal pyramidal neuron, and incorporate synaptic plasticity through the well-established Bienenstock-Cooper-Munro (BCM)-like rule for synaptic plasticity, wherein the direction and strength of the plasticity is dependent on the concentration of calcium influx. Under this framework, we derive a rule for HCN channel plasticity to establish homeostasis in synaptically-driven firing rate, and incorporate such plasticity into our model. In demonstrating that this rule for HCN channel plasticity helps maintain firing rate homeostasis after bidirectional synaptic plasticity, we observe a linear relationship between synaptic plasticity and HCN channel plasticity for maintaining firing rate homeostasis. Motivated by this linear relationship, we derive a calcium-dependent rule for HCN-channel plasticity, and demonstrate that firing rate homeostasis is maintained in the face of synaptic plasticity when moderate and high levels of cytosolic calcium influx induced depression and potentiation of the HCN-channel conductance, respectively. Additionally, we show that such synergy between synaptic and HCN-channel plasticity enhances the stability of synaptic learning through metaplasticity in the BCM-like synaptic plasticity profile. Finally, we demonstrate that the synergistic interaction between synaptic and HCN-channel plasticity preserves robustness of information transfer across the neuron under a rate-coding schema. Our results establish specific physiological roles for experimentally observed plasticity in HCN channels accompanying synaptic plasticity in hippocampal neurons, and uncover potential links between HCN-channel plasticity and calcium influx, dynamic gain control and stable synaptic learning.
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Homeostatic plasticity is considered to maintain activity in neuronal circuits within a functional range. In the absence of homeostatic plasticity neuronal activity is prone to be destabilized because Hebbian plasticity mechanisms induce positive feedback change. Several studies on homeostatic plasticity assumed the existence of a process for monitoring neuronal activity on a time scale of hours and adjusting synaptic efficacy by scaling up and down. However, the underlying mechanism still remains unclear. Excitatory synaptic efficacy is associated with the size of the dendritic spine, and dendritic spine size fluctuates even after neuronal activity is silenced. These fluctuations could be a non-Hebbian form of synaptic plasticity that serves such a homeostatic function. This study proposed and analyzed a synaptic plasticity model incorporating random fluctuations and soft-bounded Hebbian plasticity at excitatory synapses, and found that the proposed model can prevent excessive changes in neuronal activity by scaling synaptic efficacy up and down. Soft-bounded Hebbian plasticity suppresses strong synapses, thereby scaling synapses down and preventing runaway excitation. Random fluctuations diffuse synaptic efficacy, thereby scaling synapses up and preventing neurons from falling silent. The proposed model acts as a form of homeostatic plasticity, regardless of neuronal activity monitoring.
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Synaptic plasticity, a change in the efficacy of synaptic signaling, is a key property of synaptic communication that is vital to many brain functions. Hebbian forms of long-lasting synaptic plasticity—long-term potentiation (LTP) and long-term depression (LTD)—have been well studied and are considered to be the cellular basis for particular types of memory. Recently, homeostatic synaptic plasticity, a compensatory form of synaptic strength change, has attracted attention as a cellular mechanism that counteracts changes brought about by LTP and LTD to help stabilize neuronal network activity. New findings on the cellular mechanisms and molecular players of the two forms of plasticity are uncovering the interplay between them in individual neurons.
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Homeostatic plasticity in mammalian central nervous system is considered to maintain activity in neuronal circuits within a functional range. In the absence of homeostatic plasticity neuronal activity is prone to be destabilized because correlation-based synaptic modification, Hebbian plasticity, induces positive feedback change. Several studies on homeostatic plasticity assumed the existence of a process for monitoring neuronal activity and adjusting synaptic efficacy on a time scale of hours, but its biological mechanism still remains unclear. Excitatory synaptic efficacy is associated with the size of a post-synaptic element, dendritic spine, and the size of the dendritic spine fluctuates even after neuronal activity is silenced. These fluctuations could be a non-Hebbian form of synaptic plasticity that serves such a homeostatic function. This study proposed and analyzed a synaptic plasticity model incorporating random fluctuations and Hebbian plasticity at excitatory synapses, and found that it prevents excessive changes in neuronal activity by adjusting synaptic efficacy. Random fluctuations do not monitor neuronal activity, but their relative influence depends on neuronal activity. The proposed synaptic plasticity model acts as a form of homeostatic plasticity, regardless of neuronal activity monitoring. Thus, random fluctuations play an important role in homeostatic plasticity and contribute to development and functions of neural networks.
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