Synaptic plasticity, the putative basis of learning and memory formation, manifests in various forms and across different timescales. Here we show that the interaction of Hebbian homosynaptic ...plasticity with rapid non-Hebbian heterosynaptic plasticity is, when complemented with slower homeostatic changes and consolidation, sufficient for assembly formation and memory recall in a spiking recurrent network model of excitatory and inhibitory neurons. In the model, assemblies were formed during repeated sensory stimulation and characterized by strong recurrent excitatory connections. Even days after formation, and despite ongoing network activity and synaptic plasticity, memories could be recalled through selective delay activity following the brief stimulation of a subset of assembly neurons. Blocking any component of plasticity prevented stable functioning as a memory network. Our modelling results suggest that the diversity of plasticity phenomena in the brain is orchestrated towards achieving common functional goals.
Growing experimental evidence shows that both homeostatic and Hebbian synaptic plasticity can be expressed presynaptically as well as postsynaptically. In this review, we start by discussing this ...evidence and methods used to determine expression loci. Next, we discuss the functional consequences of this diversity in pre- and postsynaptic expression of both homeostatic and Hebbian synaptic plasticity. In particular, we explore the functional consequences of a biologically tuned model of pre- and postsynaptically expressed spike-timing-dependent plasticity complemented with postsynaptic homeostatic control. The pre- and postsynaptic expression in this model predicts (i) more reliable receptive fields and sensory perception, (ii) rapid recovery of forgotten information (memory savings), and (iii) reduced response latencies, compared with a model with postsynaptic expression only. Finally, we discuss open questions that will require a considerable research effort to better elucidate how the specific locus of expression of homeostatic and Hebbian plasticity alters synaptic and network computations.
This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.
Learning is primarily mediated by activity-dependent modifications of synaptic strength within neuronal circuits. We discovered that place fields in hippocampal area CA1 are produced by a synaptic ...potentiation notably different from Hebbian plasticity. Place fields could be produced in vivo in a single trial by potentiation of input that arrived seconds before and after complex spiking. The potentiated synaptic input was not initially coincident with action potentials or depolarization. This rule, named behavioral time scale synaptic plasticity, abruptly modifies inputs that were neither causal nor close in time to postsynaptic activation. In slices, five pairings of subthreshold presynaptic activity and calcium (Ca2+) plateau potentials produced a large potentiation with an asymmetric seconds-long time course. This plasticity efficiently stores entire behavioral sequences within synaptic weights to produce predictive place cell activity.
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’.
Synaptic connections undergo activity-dependent plasticity during development and learning, as well as homeostatic re-adjustment to ensure stability. Little is known about the relationship between ...these processes, particularly in vivo. We addressed this with novel quantal resolution imaging of transmission during locomotive behavior at glutamatergic synapses of the Drosophila larval neuromuscular junction. We find that two motor input types, Ib and Is, provide distinct forms of excitatory drive during crawling and differ in key transmission properties. Although both inputs vary in transmission probability, active Is synapses are more reliable. High-frequency firing “wakes up” silent Ib synapses and depresses Is synapses. Strikingly, homeostatic compensation in presynaptic strength only occurs at Ib synapses. This specialization is associated with distinct regulation of postsynaptic CaMKII. Thus, basal synaptic strength, short-term plasticity, and homeostasis are determined input-specifically, generating a functional diversity that sculpts excitatory transmission and behavioral function.
•Quantal resolution imaging of synaptic transmission achieved at the fly larval NMJ•Synapses of Ib and Is motor inputs differ in basal transmission and plasticity•Homeostatic plasticity is input specific and input autonomous•Unique transmission and plasticity sculpt contribution of motor inputs to behavior
This study brings quantal resolution imaging of synaptic transmission to the intact behaving animal and discovers that short-term synaptic plasticity and synaptic homeostasis differ between inputs onto a common postsynaptic target to create diversity in drive for locomotor behavior.
Homeostatic synaptic plasticity is a stabilizing mechanism engaged by neural circuits in response to prolonged perturbation of network activity. The non-Hebbian nature of homeostatic synaptic ...plasticity is thought to contribute to network stability by preventing “runaway” Hebbian plasticity at individual synapses. However, whether blocking homeostatic synaptic plasticity indeed induces runaway Hebbian plasticity in an intact neural circuit has not been explored. Furthermore, how compromised homeostatic synaptic plasticity impacts animal learning remains unclear. Here, we show in mice that the experience of an enriched environment (EE) engaged homeostatic synaptic plasticity in hippocampal circuits, thereby reducing excitatory synaptic transmission. This process required RARα, a nuclear retinoic acid receptor that doubles as a cytoplasmic retinoic acid-induced postsynaptic regulator of protein synthesis. Blocking RARα-dependent homeostatic synaptic plasticity during an EE experience by ablating RARα signaling induced runaway Hebbian plasticity, as evidenced by greatly enhanced long-term potentiation (LTP). As a consequence, RARα deletion in hippocampal circuits during an EE experience resulted in enhanced spatial learning but suppressed learning flexibility. In the absence of RARα, moreover, EE experience superactivated mammalian target of rapamycin (mTOR) signaling, causing a shift in protein translation that enhanced the expression levels of AMPA-type glutamate receptors. Treatment of mice with the mTOR inhibitor rapamycin during an EE experience not only restored normal AMPA-receptor expression levels but also reversed the increases in runaway Hebbian plasticity and learning after hippocampal RARα deletion. Thus, our findings reveal an RARα- and mTOR-dependent mechanism by which homeostatic plasticity controls Hebbian plasticity and learning.
Brain-derived neurotrophic factor (BDNF) is one of the most distributed and extensively studied neurotrophins in the mammalian brain. BDNF signals through the tropomycin receptor kinase B (TrkB) and ...the low affinity p75 neurotrophin receptor (p75NTR). BDNF plays an important role in proper growth, development, and plasticity of glutamatergic and GABAergic synapses and through modulation of neuronal differentiation, it influences serotonergic and dopaminergic neurotransmission. BDNF acts as paracrine and autocrine factor, on both pre-synaptic and post-synaptic target sites. It is crucial in the transformation of synaptic activity into long-term synaptic memories. BDNF is considered an instructive mediator of functional and structural plasticity in the central nervous system (CNS), influencing dendritic spines and, at least in the hippocampus, the adult neurogenesis. Changes in the rate of adult neurogenesis and in spine density can influence several forms of learning and memory and can contribute to depression-like behaviors. The possible roles of BDNF in neuronal plasticity highlighted in this review focus on the effect of antidepressant therapies on BDNF-mediated plasticity. Moreover, we will review data that illustrate the role of BDNF as a potent protective factor that is able to confer protection against neurodegeneration, in particular in Alzheimer's disease. Finally, we will give evidence of how the involvement of BDNF in the pathogenesis of brain glioblastoma has emerged, thus opening new avenues for the treatment of this deadly cancer.
Numerous studies demonstrate that neuroinflammation is a key player in the progression of Alzheimer’s disease (AD). Interleukin (IL)-1β is a main inducer of inflammation and therefore a prime target ...for therapeutic options. The inactive IL-1β precursor requires processing by the the nucleotide-binding oligomerization domain-like receptor family, pyrin domain containing 3 (NLRP3) inflammasome into a mature and active form. Studies have shown that IL-1β is up-regulated in brains of patients with AD, and that genetic inactivation of the NLRP3 inflammasome improves behavioral tests and synaptic plasticity phenotypes in a murine model of the disease. In the present study, we analyzed the effect of pharmacological inhibition of the NLRP3 inflammasome using dapansutrile (OLT1177), an oral NLRP3-specific inhibitor that is safe in humans. Six-month-old WT and APP/PS1 mice were fed with standard mouse chow or OLT1177-enriched chow for 3 mo. The Morris water maze test revealed an impaired learning and memory ability of 9-mo-old APP/PS1 mice (P = 0.001), which was completely rescued by OLT1177 fed to mice (P = 0.008 to untreated APP/PS1). Furthermore, our findings revealed that 3 mo of OLT1177 diet can rescue synaptic plasticity in this mouse model of AD (P = 0.007 to untreated APP/PS1). In addition, microglia were less activated (P = 0.07) and the number of plaques was reduced in the cortex (P = 0.03) following NLRP3 inhibition with OLT1177 administration. We also observed an OLT1177 dose-dependent normalization of plasma metabolic markers of AD to those of WT mice. This study suggests the therapeutic potential of treating neuroinflammation with an oral inhibitor of the NLRP3 inflammasome.
ABSTRACT
Interest in individual differences in animal behavioural plasticities has surged in recent years, but research in this area has been hampered by semantic confusion as different investigators ...use the same terms (e.g. plasticity, flexibility, responsiveness) to refer to different phenomena. The first goal of this review is to suggest a framework for categorizing the many different types of behavioural plasticities, describe examples of each, and indicate why using reversibility as a criterion for categorizing behavioural plasticities is problematic. This framework is then used to address a number of timely questions about individual differences in behavioural plasticities. One set of questions concerns the experimental designs that can be used to study individual differences in various types of behavioural plasticities. Although within‐individual designs are the default option for empirical studies of many types of behavioural plasticities, in some situations (e.g. when experience at an early age affects the behaviour expressed at subsequent ages), ‘replicate individual’ designs can provide useful insights into individual differences in behavioural plasticities. To date, researchers using within‐individual and replicate individual designs have documented individual differences in all of the major categories of behavioural plasticities described herein. Another important question is whether and how different types of behavioural plasticities are related to one another. Currently there is empirical evidence that many behavioural plasticities e.g. contextual plasticity, learning rates, IIV (intra‐individual variability), endogenous plasticities, ontogenetic plasticities) can themselves vary as a function of experiences earlier in life, that is, many types of behavioural plasticity are themselves developmentally plastic. These findings support the assumption that differences among individuals in prior experiences may contribute to individual differences in behavioural plasticities observed at a given age. Several authors have predicted correlations across individuals between different types of behavioural plasticities, i.e. that some individuals will be generally more plastic than others. However, empirical support for most of these predictions, including indirect evidence from studies of relationships between personality traits and plasticities, is currently sparse and equivocal. The final section of this review suggests how an appreciation of the similarities and differences between different types of behavioural plasticities may help theoreticians formulate testable models to explain the evolution of individual differences in behavioural plasticities and the evolutionary and ecological consequences of individual differences in behavioural plasticities.
We compare the circuit and cellular mechanisms for homeostatic plasticity that have been discovered in rodent somatosensory (S1) and visual (V1) cortex. Both areas use similar mechanisms to restore ...mean firing rate after sensory deprivation. Two time scales of homeostasis are evident, with distinct mechanisms. Slow homeostasis occurs over several days, and is mediated by homeostatic synaptic scaling in excitatory networks and, in some cases, homeostatic adjustment of pyramidal cell intrinsic excitability. Fast homeostasis occurs within less than 1 day, and is mediated by rapid disinhibition, implemented by activity-dependent plasticity in parvalbumin interneuron circuits. These processes interact with Hebbian synaptic plasticity to maintain cortical firing rates during learned adjustments in sensory representations.
This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.
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