AMPA receptor trafficking and its role in heterosynaptic plasticity

Synapse-type-specific competitive Hebbian learning forms functional recurrent networks

Cortical networks exhibit complex stimulus-response patterns that are based on specific recurrent interactions between neurons. For example, the balance between excitatory and inhibitory currents has been identified as a central component of cortical computations. However, it remains unclear how the required synaptic connectivity can emerge in developing circuits where synapses between excitatory and inhibitory neurons are simultaneously plastic. Using theory and modeling, we propose that a wide range of cortical response properties can arise from a single plasticity paradigm that acts simultaneously at all excitatory and inhibitory connections-Hebbian learning that is stabilized by the synapse-type-specific competition for a limited supply of synaptic resources. In plastic recurrent circuits, this competition enables the formation and decorrelation of inhibition-balanced receptive fields. Networks develop an assembly structure with stronger synaptic connections between similarly tuned excitatory and inhibitory neurons and exhibit response normalization and orientation-specific center-surround suppression, reflecting the stimulus statistics during training. These results demonstrate how neurons can self-organize into functional networks and suggest an essential role for synapse-type-specific competitive learning in the development of cortical circuits.

Ceftriaxone Modulates Ubiquitination of α-Amino-3-Hydroxy-5-Methyl-4-Isoxazole Propionic Acid Receptors to Improve Long-Term Potentiation Impairment Induced by Exogenous β-Amyloid in a Glutamate Transporter-1 Dependent Manner

Α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors (AMPARs) are crucial for properties of synaptic plasticity, such as long-term potentiation (LTP). LTP impairment can occur early in the onset of Alzheimer's disease (AD). The downregulation or decreased abundance of AMPAR expression in the postsynaptic membrane is closely associated with LTP impairment. Ceftriaxone (Cef) can improve LTP impairment in the early stages of AD in a mouse model. The purpose of this study was to explore the mechanism underlying this process from the aspects of AMPAR expression and ubiquitination degree. In this study, we found that β-amyloid (Aβ) treatment induced hippocampal LTP impairment and AMPAR downregulation and ubiquitination. Cef pretreatment ameliorated Aβ-induced hippocampal LTP impairment, reduced AMPAR ubiquitination, and increased AMPAR expression, especially in the plasma membrane, in Aβ-treated mice. Administration of USP46 siRNA and DHK (a specific blocker of glutamate transporter-1) significantly inhibited the above effects of Cef, suggesting a role for anti-AMPAR ubiquitination and upregulation of glutamate transporter-1 (GLT-1) in the Cef-induced improvements mentioned above. The above findings demonstrate that pretreatment with Cef effectively mitigated Aβ-induced impairment of hippocampal LTP by suppressing the ubiquitination process of AMPARs in a GLT-1-dependent manner. These results provide novel insights into the underlying mechanisms elucidating the anti-AD by Cef.

Changes in miR-134-3p expression and zDHHC3-AMPARs axis in association with aluminum neurotoxicity

Aluminum (Al) is a neurotoxic substance associated with cognitive dysfunction and neurodegenerative diseases, such as Alzheimer's disease, but the mechanisms for aluminum neurotoxicity remain to be identified. In this work, we try to investigate a novel potential biomarker of cognitive dysfunction following aluminum exposure and the mechanism involved. Recently, miR-134-3p was reported as a novel regulator of cognitive function. To address this, we investigate the expression level of miR-134-3p in plasma from 280 aluminum factory workers and analyzed the correlation between miRNA-134-3p, blood Al concentration, and Montreal Cognitive Assessment Scale (MoCA scale) score. The results implied that occupational aluminum exposure elevated miR-134-3p expression in the plasma of workers accompanied by cognitive impairment. Our experiment studies using both animal models and PC12 cells validated the upregulation of miR-134-3p caused by aluminum. In addition, we identified that palmitoylation enzyme zDHHC3 was the target of miR-134-3p, and the decreasing AMPAR receptor (AMPAR) trafficking was related to the learning and memory impairment induced by aluminum. More importantly, using transfection and interference approaches in PC12 cells, inhibition of miR-134-3p resulted in a recovery of zDHHC3-AMPARs axis to a certain extent in response to aluminum. In summary, miR-134-3p was found to be involved in aluminum neurotoxicity by targeting zDHHC3-AMPARs axis and could serve as a potential biomarker or helpful target.

Selective breeding for physical inactivity produces cognitive deficits via altered hippocampal mitochondrial and synaptic function

Physical inactivity is the 4th leading cause of death globally and has been shown to significantly increase the risk for developing Alzheimer's Disease (AD). Recent work has demonstrated that exercise prior to breeding produces heritable benefits to the brains of offspring, suggesting that the physical activity status of previous generations could play an important role in one's brain health and their subsequent risk for neurodegenerative diseases. Thus, our study aimed to test the hypothesis that selective breeding for physical inactivity, or for high physical activity, preference produces heritable deficits and enhancements to brain health, respectively. To evaluate this hypothesis, male and female sedentary Low Voluntary Runners (LVR), wild type (WT), and High Voluntary Runner (HVR) rats underwent cognitive behavioral testing, analysis of hippocampal neurogenesis and mitochondrial respiration, and molecular analysis of the dentate gyrus. These analyses revealed that selecting for physical inactivity preference has produced major detriments to cognition, brain mitochondrial respiration, and neurogenesis in female LVR while female HVR display enhancements in brain glucose metabolism and hippocampal size. On the contrary, male LVR and HVR showed very few differences in these parameters relative to WT. Overall, we provide evidence that selective breeding for physical inactivity has a heritable and detrimental effect on brain health and that the female brain appears to be more susceptible to these effects. This emphasizes the importance of remaining physically active as chronic intergenerational physical inactivity likely increases susceptibility to neurodegenerative diseases for both the inactive individual and their offspring.

Computational insights into mRNA and protein dynamics underlying synaptic plasticity rules

Recent advances in experimental techniques provide an unprecedented peek into the intricate molecular dynamics inside synapses and dendrites. The experimental insights into the molecular turnover revealed that such processes as diffusion, active transport, spine uptake, and local protein synthesis could dynamically modulate the copy numbers of plasticity-related molecules in synapses. Subsequently, theoretical models were designed to understand the interaction of these processes better and to explain how local synaptic plasticity cues can up or down-regulate the molecular copy numbers across synapses. In this review, we discuss the recent advances in experimental techniques and computational models to highlight how these complementary approaches can provide insight into molecular cross-talk across synapses, ultimately allowing us to develop biologically-inspired neural network models to understand brain function.

Crosstalk between biochemical signalling network architecture and trafficking governs AMPAR dynamics in synaptic plasticity

Synaptic plasticity involves modification of both biochemical and structural components of neurons. Many studies have revealed that the change in the number density of the glutamatergic receptor AMPAR at the synapse is proportional to synaptic weight update; an increase in AMPAR corresponds to strengthening of synapses while a decrease in AMPAR density weakens synaptic connections. The dynamics of AMPAR are thought to be regulated by upstream signalling, primarily the calcium-CaMKII pathway, trafficking to and from the synapse, and influx from extrasynaptic sources. Previous work in the field of deterministic modelling of CaMKII dynamics has assumed bistable kinetics, while experiments and rule-based modelling have revealed that CaMKII dynamics can be either monostable or ultrasensitive. This raises the following question: how does the choice of model assumptions involving CaMKII dynamics influence AMPAR dynamics at the synapse? To answer this question, we have developed a set of models using compartmental ordinary differential equations to systematically investigate contributions of different signalling and trafficking variations, along with their coupled effects, on AMPAR dynamics at the synaptic site. We find that the properties of the model including network architecture describing different stability features of CaMKII and parameters that capture the endocytosis and exocytosis of AMPAR significantly affect the integration of fast upstream species by slower downstream species. Furthermore, we predict that the model outcome, as determined by bound AMPAR at the synaptic site, depends on (1) the choice of signalling model (bistable CaMKII or monostable CaMKII dynamics), (2) trafficking versus influx contributions and (3) frequency of stimulus. KEY POINTS: The density of AMPA receptors (AMPARs) at the postsynaptic density of the synapse provides a readout of synaptic plasticity, which involves crosstalk between complex biochemical signalling networks including CaMKII dynamics and trafficking pathways including exocytosis and endocytosis. Here we build a model that integrates CaMKII dynamics and AMPAR trafficking to explore this crosstalk. We compare different models of CaMKII that result in monostable or bistable kinetics and their impact on AMPAR dynamics. Our results show that AMPAR density depends on the coupling between aspects of biochemical signalling and trafficking. Specifically, assumptions regarding CaMKII dynamics and its stability features can alter AMPAR density at the synapse. Our model also predicts that the kinetics of trafficking versus influx of AMPAR from the extrasynaptic space can further impact AMPAR density. Thus, the contributions of both signalling and trafficking should be considered in computational models.

Dendritic spine morphology regulates calcium-dependent synaptic weight change

Dendritic spines act as biochemical computational units and must adapt their responses according to their activation history. Calcium influx acts as the first signaling step during postsynaptic activation and is a determinant of synaptic weight change. Dendritic spines also come in a variety of sizes and shapes. To probe the relationship between calcium dynamics and spine morphology, we used a stochastic reaction-diffusion model of calcium dynamics in idealized and realistic geometries. We show that despite the stochastic nature of the various calcium channels, receptors, and pumps, spine size and shape can modulate calcium dynamics and subsequently synaptic weight updates in a deterministic manner. Through a series of exhaustive simulations and analyses, we found that the calcium dynamics and synaptic weight change depend on the volume-to-surface area of the spine. The relationships between calcium dynamics and spine morphology identified in idealized geometries also hold in realistic geometries, suggesting that there are geometrically determined deterministic relationships that may modulate synaptic weight change.

The Shaping of AMPA Receptor Surface Distribution by Neuronal Activity

Neurotransmission is critically dependent on the number, position, and composition of receptor proteins on the postsynaptic neuron. Of these, α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors (AMPARs) are responsible for the majority of postsynaptic depolarization at excitatory mammalian synapses following glutamate release. AMPARs are continually trafficked to and from the cell surface, and once at the surface, AMPARs laterally diffuse in and out of synaptic domains. Moreover, the subcellular distribution of AMPARs is shaped by patterns of activity, as classically demonstrated by the synaptic insertion or removal of AMPARs following the induction of long-term potentiation (LTP) and long-term depression (LTD), respectively. Crucially, there are many subtleties in the regulation of AMPARs, and exactly how local and global synaptic activity drives the trafficking and retention of synaptic AMPARs of different subtypes continues to attract attention. Here we will review how activity can have differential effects on AMPAR distribution and trafficking along with its subunit composition and phosphorylation state, and we highlight some of the controversies and remaining questions. As the AMPAR field is extensive, to say the least, this review will focus primarily on cellular and molecular studies in the hippocampus. We apologise to authors whose work could not be cited directly owing to space limitations.

Constrained plasticity reserve as a natural way to control frequency and weights in spiking neural networks

Biological neurons have adaptive nature and perform complex computations involving the filtering of redundant information. However, most common neural cell models, including biologically plausible, such as Hodgkin-Huxley or Izhikevich, do not possess predictive dynamics on a single-cell level. Moreover, the modern rules of synaptic plasticity or interconnections weights adaptation also do not provide grounding for the ability of neurons to adapt to the ever-changing input signal intensity. While natural neuron synaptic growth is precisely controlled and restricted by protein supply and recycling, weight correction rules such as widely used STDP are efficiently unlimited in change rate and scale. The present article introduces new mechanics of interconnection between neuron firing rate homeostasis and weight change through STDP growth bounded by abstract protein reserve, controlled by the intracellular optimization algorithm. We show how these cellular dynamics help neurons filter out the intense noise signals to help neurons keep a stable firing rate. We also examine that such filtering does not affect the ability of neurons to recognize the correlated inputs in unsupervised mode. Such an approach might be used in the machine learning domain to improve the robustness of AI systems.

Differential role of pre- and postsynaptic neurons in the activity-dependent control of synaptic strengths across dendrites

Neurons receive a large number of active synaptic inputs from their many presynaptic partners across their dendritic tree. However, little is known about how the strengths of individual synapses are controlled in balance with other synapses to effectively encode information while maintaining network homeostasis. This is in part due to the difficulty in assessing the activity of individual synapses with identified afferent and efferent connections for a synapse population in the brain. Here, to gain insights into the basic cellular rules that drive the activity-dependent spatial distribution of pre- and postsynaptic strengths across incoming axons and dendrites, we combine patch-clamp recordings with live-cell imaging of hippocampal pyramidal neurons in dissociated cultures and organotypic slices. Under basal conditions, both pre- and postsynaptic strengths cluster on single dendritic branches according to the identity of the presynaptic neurons, thus highlighting the ability of single dendritic branches to exhibit input specificity. Stimulating a single presynaptic neuron induces input-specific and dendritic branchwise spatial clustering of presynaptic strengths, which accompanies a widespread multiplicative scaling of postsynaptic strengths in dissociated cultures and heterosynaptic plasticity at distant synapses in organotypic slices. Our study provides evidence for a potential homeostatic mechanism by which the rapid changes in global or distant postsynaptic strengths compensate for input-specific presynaptic plasticity.

Competition for synaptic building blocks shapes synaptic plasticity

Changes in the efficacies of synapses are thought to be the neurobiological basis of learning and memory. The efficacy of a synapse depends on its current number of neurotransmitter receptors. Recent experiments have shown that these receptors are highly dynamic, moving back and forth between synapses on time scales of seconds and minutes. This suggests spontaneous fluctuations in synaptic efficacies and a competition of nearby synapses for available receptors. Here we propose a mathematical model of this competition of synapses for neurotransmitter receptors from a local dendritic pool. Using minimal assumptions, the model produces a fast multiplicative scaling behavior of synapses. Furthermore, the model explains a transient form of heterosynaptic plasticity and predicts that its amount is inversely related to the size of the local receptor pool. Overall, our model reveals logistical tradeoffs during the induction of synaptic plasticity due to the rapid exchange of neurotransmitter receptors between synapses.