Explore the vast range of titles available.

It has become widely accepted that homeostatic and Hebbian plasticity mechanisms work hand in glove to refine neural circuit function. Nonetheless, our understanding of how these fundamentally distinct forms of plasticity compliment (and under some circumstances interfere with) each other remains rudimentary. Here, I describe some of the recent progress of the field, as well as some of the deep puzzles that remain. These include unravelling the spatial and temporal scales of different homeostatic and Hebbian mechanisms, determining which aspects of network function are under homeostatic control, and understanding when and how homeostatic and Hebbian mechanisms must be segregated within neural circuits to prevent interference. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.

Studies of brain network connectivity improved understanding on brain changes and adaptation in response to different pathologies. Synaptic plasticity, the ability of neurons to modify their connections, is involved in brain network remodeling following different types of brain damage (e.g., vascular, neurodegenerative, inflammatory). Although synaptic plasticity mechanisms have been extensively elucidated, how neural plasticity can shape network organization is far from being completely understood. Similarities existing between synaptic plasticity and principles governing brain network organization could be helpful to define brain network properties and reorganization profiles after damage. In this review, we discuss how different forms of synaptic plasticity, including homeostatic and anti-homeostatic mechanisms, could be directly involved in generating specific brain network characteristics. We propose that long-term potentiation could represent the neurophysiological basis for the formation of highly connected nodes (hubs). Conversely, homeostatic plasticity may contribute to stabilize network activity preventing poor and excessive connectivity in the peripheral nodes. In addition, synaptic plasticity dysfunction may drive brain network disruption in neuropsychiatric conditions such as Alzheimer’s disease and schizophrenia. Optimal network architecture, characterized by efficient information processing and resilience, and reorganization after damage strictly depend on the balance between these forms of plasticity.

Synapses are complex because they perform multiple functions, including at least six mechanistically different forms of plasticity. Here, I comment on recent developments regarding these processes. (i) Short-term potentiation (STP), a Hebbian process that requires small amounts of synaptic input, appears to make strong contributions to some forms of working memory. (ii) The rules for long-term potentiation (LTP) induction in CA3 have been clarified: induction does not depend obligatorily on backpropagating sodium spikes but, rather, on dendritic branch-specific N-methyl-d-aspartate (NMDA) spikes. (iii) Late LTP, a process that requires a dopamine signal (and is therefore neoHebbian), is mediated by trans-synaptic growth of the synapse, a growth that occurs about an hour after LTP induction. (iv) LTD processes are complex and include both homosynaptic and heterosynaptic forms. (v) Synaptic scaling produced by changes in activity levels are not primarily cell-autonomous, but rather depend on network activity. (vi) The evidence for distance-dependent scaling along the primary dendrite is firm, and a plausible structural-based mechanism is suggested. Ideas about the mechanisms of synaptic function need to take into consideration newly emerging data about synaptic structure. Recent super-resolution studies indicate that glutamatergic synapses are modular (module size 70–80 nm), as predicted by theoretical work. Modules are trans-synaptic structures and have high concentrations of postsynaptic density-95 (PSD-95) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor. These modules function as quasi-independent loci of AMPA-mediated transmission and may be independently modifiable, suggesting a new understanding of quantal transmission. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity.’

We review a body of theoretical and experimental research on Hebbian and homeostatic plasticity, starting from a puzzling observation: while homeostasis of synapses found in experiments is a slow compensatory process, most mathematical models of synaptic plasticity use rapid compensatory processes (RCPs). Even worse, with the slow homeostatic plasticity reported in experiments, simulations of existing plasticity models cannot maintain network stability unless further control mechanisms are implemented. To solve this paradox, we suggest that in addition to slow forms of homeostatic plasticity there are RCPs which stabilize synaptic plasticity on short timescales. These rapid processes may include heterosynaptic depression triggered by episodes of high postsynaptic firing rate. While slower forms of homeostatic plasticity are not sufficient to stabilize Hebbian plasticity, they are important for fine-tuning neural circuits. Taken together we suggest that learning and memory rely on an intricate interplay of diverse plasticity mechanisms on different timescales which jointly ensure stability and plasticity of neural circuits. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.

Homeostasis is indispensable to counteract the destabilizing effects of Hebbian plasticity. Although it is commonly assumed that homeostasis modulates synaptic strength, membrane excitability, and firing rates, its role at the neural circuit and network level is unknown. Here, we identify changes in higher-order network properties of freely behaving rodents during prolonged visual deprivation. Strikingly, our data reveal that functional pairwise correlations and their structure are subject to homeostatic regulation. Using a computational model, we demonstrate that the interplay of different plasticity and homeostatic mechanisms can capture the initial drop and delayed recovery of firing rates and correlations observed experimentally. Moreover, our model indicates that synaptic scaling is crucial for the recovery of correlations and network structure, while intrinsic plasticity is essential for the rebound of firing rates, suggesting that synaptic scaling and intrinsic plasticity can serve distinct functions in homeostatically regulating network dynamics.

Synapses undergo rapid activity-dependent plasticity to store information, which when left uncompensated can lead to destabilization of neural function. It has been well documented that homeostatic changes, which operate at a slower time scale, are required to maintain stability of neural networks. While there are many mechanisms that can endow homeostatic control, sliding threshold and synaptic scaling are unique in that they operate by providing homeostatic control of synaptic strength. The former mechanism operates by adjusting the threshold for synaptic plasticity, while the latter mechanism directly alters the gain of synapses. Both modes of homeostatic synaptic plasticity have been studied across various preparations from reduced systems, such as neuronal cultures, to intact circuitry. While most of the cellular and molecular mechanisms of homeostatic synaptic plasticity have been worked out using reduced preparations, there are unique challenges present in intact circuitry , which deserve further consideration. For example, in an intact circuit, neurons receive distinct set of inputs across their dendritic tree which carry unique information. Homeostatic synaptic plasticity needs to operate without compromising processing of these distinct set of inputs to preserve information processing while maintaining network stability. In this mini review, we will summarize unique features of homeostatic synaptic plasticity, and discuss how sliding threshold and synaptic scaling may act across different activity regimes to provide homeostasis.

Protein turnover, the net result of protein synthesis and degradation, enables cells to remodel their proteomes in response to internal and external cues. Previously, we analyzed protein turnover rates in cultured brain cells under basal neuronal activity and found that protein turnover is influenced by subcellular localization, protein function, complex association, cell type of origin, and by the cellular environment (Dörrbaum et al., 2018). Here, we advanced our experimental approach to quantify changes in protein synthesis and degradation, as well as the resulting changes in protein turnover or abundance in rat primary hippocampal cultures during homeostatic scaling. Our data demonstrate that a large fraction of the neuronal proteome shows changes in protein synthesis and/or degradation during homeostatic up- and down-scaling. More than half of the quantified synaptic proteins were regulated, including pre- as well as postsynaptic proteins with diverse molecular functions.

Norepinephrine (NE) is a neuromodulator that in multiple ways regulates the activity of neuronal and non-neuronal cells. NE participates in the rapid modulation of cortical circuits and cellular energy metabolism, and on a slower time scale in neuroplasticity and inflammation. Of the multiple sources of NE in the brain, the locus coeruleus (LC) plays a major role in noradrenergic signaling. Processes from the LC primarily release NE over widespread brain regions via non-junctional varicosities. We here review the actions of NE in astrocytes, microglial cells, and neurons based on the idea that the overarching effect of signaling from the LC is to maximize brain power, which is accomplished via an orchestrated cellular response involving most, if not all cell types in CNS.

Homeostatic synaptic scaling is a negative feedback response to fluctuations in synaptic strength induced by developmental or learning-related processes, which maintains neuronal activity stable. Although several components of the synaptic scaling apparatus have been characterized, the intrinsic regulatory mechanisms promoting scaling remain largely unknown. MicroRNAs may contribute to posttranscriptional control of mRNAs implicated in different stages of synaptic scaling, but their role in these mechanisms is still undervalued. Here, we report that chronic blockade of glutamate receptors of the AMPA and NMDA types in hippocampal neurons in culture induces changes in the neuronal mRNA and miRNA transcriptomes, leading to synaptic upscaling. Specifically, we show that synaptic activity blockade persistently down-regulates miR-186-5p. Moreover, we describe a conserved miR-186-5p-binding site within the 3'UTR of the mRNA encoding the AMPA receptor GluA2 subunit, and demonstrate that GluA2 is a direct target of miR-186-5p. Overexpression of miR-186 decreased GluA2 surface levels, increased synaptic expression of GluA2-lacking AMPA receptors, and blocked synaptic scaling, whereas inhibition of miR-186-5p increased GluA2 surface levels and the amplitude and frequency of AMPA receptor-mediated currents, and mimicked excitatory synaptic scaling induced by synaptic inactivity. Our findings elucidate an activity-dependent miRNA-mediated mechanism for regulation of AMPA receptor expression.

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.