Synaptic plasticity of NMDA receptors: mechanisms and functional implications

Beyond their well-established role as triggers for LTP and LTD of fast synaptic transmission mediated by AMPA receptors, an expanding body of evidence indicates that NMDA receptors (NMDARs) themselves are also dynamically regulated and subject to activity-dependent long-term plasticity. NMDARs can significantly contribute to information transfer at synapses particularly during periods of repetitive activity. It is also increasingly recognized that NMDARs participate in dendritic synaptic integration and are critical for generating persistent activity of neural assemblies. Here we review recent advances on the mechanisms and functional consequences of NMDAR plasticity. Given the unique biophysical properties of NMDARs, synaptic plasticity of NMDAR-mediated transmission emerges as a particularly powerful mechanism for the fine tuning of information encoding and storage throughout the brain.     

Astrocytes optimize the synaptic transmission of information

Chemical synapses transmit information via the release of neurotransmitter-filled vesicles from the presynaptic terminal. Using computational modeling, we predict that the limited availability of neurotransmitter resources in combination with the spontaneous release of vesicles limits the maximum degree of enhancement of synaptic transmission. This gives rise to an optimal tuning that depends on the number of active zones. There is strong experimental evidence that astrocytes that enwrap synapses can modulate the probabilities of vesicle release through bidirectional signaling and hence regulate synaptic transmission. For low-fidelity hippocampal synapses, which typically have only one or two active zones, the predicted optimal values lie close to those determined by experimentally measured astrocytic feedback, suggesting that astrocytes optimize synaptic transmission of information.     

Anatomical circuitry of lateral inhibition in the eye of the horseshoe crab, Limulus polyphemus

Lengthy uninterrupted series of sections of the neural plexus in the compound eye of the horseshoe crab, Limulus polyphemus, have been used to reconstruct all the arborizations and their synaptic interconnections in a neuropil knot. This one microglomerulus contains the axons of 19 retinular cells, which pass by without contacts; 13 efferent fibres with 44 synapses to and from eccentric cell collaterals; and arborizations from 54 eccentric cells with 577 synapses. Eccentric cell axons are devoid of synaptic input. Their collaterals ramify in synaptic knots and subserve both pre- and postsynaptic functions simultaneously. Arborizations near the axon of origin have a highly branched pattern (up to 20 bifurcations), a high synaptic input: output ratio (up to about 9:1), and high synaptic density (a maximum of 12 per micrometre of neurite length). The opposite extreme is represented by sparsely branched eccentric cell collaterals distant from their axons of origin with very little synaptic input and sparse output. Spatially graded lateral inhibition is the apparent outcome of a radially decreasing distribution of inhibitory synapses on the arborizations of eccentric cell collaterals combined with possible decremental signal transmission in the plexus. The synaptic analysis has a bearing on most physiological aspects of lateral inhibition that have been studied in the Limulus eye. Implied in the results is the suggestion that synapse formation is an intrinsic property of the presynaptic element, but that the connectivity is governed by the electrical activity of target neurons.     

大鼠初级传入纤维与脊髓背角神经元间的动作电序列的突触传递

外周感觉神经元通过动作电位序列对信号进行编码,这些动作电位序列经过突触传递最终到达脑部。但是各种脉冲序列如何通过神经元之间的化学突触进行传递依然是一个悬而未决的问题。研究了初级传入A6纤维与背角神经元之间各种动作电位序列的突触传递过程。用于刺激的规则,周期、随机脉冲序列由短簇脉冲或单个脉冲构成。定义“事件”(event)为峰峰问期(intefspike interval)小于或等于规定阈值的最长动作电位串,然后从脉冲序列中提取事件间间期(interevent interval,IEI)。用时间,IEI图与回归映射的方法分析IEI序列,结果表明在突触后输出脉冲序列中可以检测到突触前脉冲序列的主要时间结构特征,特别是在短簇脉冲作为刺激单位时。通过计算输入与输出脉冲序列的互信息,发现短簇脉冲可以更可靠地跨突触传递由输入序列携带的神经信息。这些结果表明外周输入脉冲序列的主要时间结构特征可以跨突触传递,在突触传递神经信息的过程中短簇脉冲更为有效。这一研究在从突触传递角度探索神经信息编码方面迈出了一步。     

Signal propagation in feedforward neuronal networks with unreliable synapses

In this paper, we systematically investigate both the synfire propagation and firing rate propagation in feedforward neuronal network coupled in an all-to-all fashion. In contrast to most earlier work, where only reliable synaptic connections are considered, we mainly examine the effects of unreliable synapses on both types of neural activity propagation in this work. We first study networks composed of purely excitatory neurons. Our results show that both the successful transmission probability and excitatory synaptic strength largely influence the propagation of these two types of neural activities, and better tuning of these synaptic parameters makes the considered network support stable signal propagation. It is also found that noise has significant but different impacts on these two types of propagation. The additive Gaussian white noise has the tendency to reduce the precision of the synfire activity, whereas noise with appropriate intensity can enhance the performance of firing rate propagation. Further simulations indicate that the propagation dynamics of the considered neuronal network is not simply determined by the average amount of received neurotransmitter for each neuron in a time instant, but also largely influenced by the stochastic effect of neurotransmitter release. Second, we compare our results with those obtained in corresponding feedforward neuronal networks connected with reliable synapses but in a random coupling fashion. We confirm that some differences can be observed in these two different feedforward neuronal network models. Finally, we study the signal propagation in feedforward neuronal networks consisting of both excitatory and inhibitory neurons, and demonstrate that inhibition also plays an important role in signal propagation in the considered networks.     

Catenins: playing both sides of the synapse

Synapses of the central nervous system (CNS) are specialized cell-cell junctions that mediate intercellular signal transmission from one neuron to another. The directional nature of signal relay requires synaptic contacts to be morphologically asymmetric with distinct protein components, while changes in synaptic communication during neural network formation require synapses to be plastic. Synapse morphology and plasticity require a dynamic actin cytoskeleton. Classical cadherins, which are junctional proteins associated with the actin cytoskeleton, localize to synapses and regulate synaptic adhesion, stability and remodeling. The major intracellular components of cadherin junctions are the catenin proteins, and increasing evidence suggests that cadherin-catenin complexes modulate an array of synaptic processes. Here we review the role of catenins in regulating the development of pre- and postsynaptic compartments and function in synaptic plasticity, with particular focus on their role in regulating the actin cytoskeleton.     

Gap junctions

Electrical coupling through gap junctions constitutes a mode of signal transmission between neurons (electrical synaptic transmission). Originally discovered in invertebrates and in lower vertebrates, electrical synapses have recently been reported in immature and adult mammalian nervous systems. This has renewed the interest in understanding the role of electrical synapses in neural circuit function and signal processing. The present review focuses on the role of gap junctions in shaping the dynamics of neural networks by forming electrical synapses between neurons. Electrical synapses have been shown to be important elements in coincidence detection mechanisms and they can produce complex input-output functions when arranged in combination with chemical synapses. We postulate that these synapses may also be important in redefining neuronal compartments, associating anatomically distinct cellular structures into functional units. The original view of electrical synapses as static connecting elements in neural circuits has been revised and a considerable amount of evidence suggests that electrical synapses substantially affect the dynamics of neural circuits.     

Neural pathways and innervation of cnidocytes in tentacles of sea anemones

Our previously published studies are here reviewed detailing neuro-cnidocyte synapses, demonstrating putative neurotransmitter substances, and identifying complex neural pathways in sea anemones. Synapses were traced to their contacts on nematocytes and spirocytes by transmission electron microscopy of serial thin sections of tentacles. In five animals, cells containing microbasic p-mastigophores had synapses with clear vesicles, whereas cells containing basitrichous isorhizas had synapses with dense-cored vesicles, providing preliminary evidence for a selectivity of neurotransmitter types for different nematocysts. Either clear or dense-cored synaptic vesicles were also present at neuro-spirocyte contacts. Antho-RFamide immunoreactivity occurred in some anthozoan synaptic vesicles and immunogold labeling of serotonin was found at a neuro-spirocyte synapse. Neural pathways included direct innervation of spirocytes by sensory cells, sequential neuro-neuro-spirocyte and neuro-neuro-nematocyte synapses and reciprocal synapses involving axons of both sensory cells and ganglion cells. Such synaptic patterns resemble neuro-effector pathways found in higher animals and lay to rest the independent effector hypothesis for cnidocyte discharge in tentacles of sea anemones.     

Robust spatial working memory through homeostatic synaptic scaling in heterogeneous cortical networks

The concept of bell-shaped persistent neural activity represents a cornerstone of the theory for the internal representation of analog quantities, such as spatial location or head direction. Previous models, however, relied on the unrealistic assumption of network homogeneity. We investigate this issue in a network model where fine tuning of parameters is destroyed by heterogeneities in cellular and synaptic properties. Heterogeneities result in the loss of stored spatial information in a few seconds. Accurate encoding is recovered when a homeostatic mechanism scales the excitatory synapses to each cell to compensate for the heterogeneity in cellular excitability and synaptic inputs. Moreover, the more realistic model produces a wide diversity of tuning curves, as commonly observed in recordings from prefrontal neurons. We conclude that recurrent attractor networks in conjunction with appropriate homeostatic mechanisms provide a robust, biologically plausible theoretical framework for understanding the neural circuit basis of spatial working memory.     

Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways

The dynamics of cerebellar neuronal networks is controlled by the underlying building blocks of neurons and synapses between them. For which, the computation of Purkinje cells (PCs), the only output cells of the cerebellar cortex, is implemented through various types of neural pathways interactively routing excitation and inhibition converged to PCs. Such tuning of excitation and inhibition, coming from the gating of specific pathways as well as short-term plasticity (STP) of the synapses, plays a dominant role in controlling the PC dynamics in terms of firing rate and spike timing. PCs receive cascade feedforward inputs from two major neural pathways: the first one is the feedforward excitatory pathway from granule cells (GCs) to PCs; the second one is the feedforward inhibition pathway from GCs, via molecular layer interneurons (MLIs), to PCs. The GC-PC pathway, together with short-term dynamics of excitatory synapses, has been a focus over past decades, whereas recent experimental evidence shows that MLIs also greatly contribute to controlling PC activity. Therefore, it is expected that the diversity of excitation gated by STP of GC-PC synapses, modulated by strong inhibition from MLI-PC synapses, can promote the computation performed by PCs. However, it remains unclear how these two neural pathways are interacted to modulate PC dynamics. Here using a computational model of PC network installed with these two neural pathways, we addressed this question to investigate the change of PC firing dynamics at the level of single cell and network. We show that the nonlinear characteristics of excitatory STP dynamics can significantly modulate PC spiking dynamics mediated by inhibition. The changes in PC firing rate, firing phase, and temporal spike pattern, are strongly modulated by these two factors in different ways. MLIs mainly contribute to variable delays in the postsynaptic action potentials of PCs while modulated by excitation STP. Notably, the diversity of synchronization and pause response in the PC network is governed not only by the balance of excitation and inhibition, but also by the synaptic STP, depending on input burst patterns. Especially, the pause response shown in the PC network can only emerge with the interaction of both pathways. Together with other recent findings, our results show that the interaction of feedforward pathways of excitation and inhibition, incorporated with synaptic short-term dynamics, can dramatically regulate the PC activities that consequently change the network dynamics of the cerebellar circuit.     

Presynaptic function

Changing the strength of synapses is key to the adaptive modifications of what neuronal circuits compute. Unsurprisingly, many different mechanisms have evolved to alter synaptic strength. Some of these mechanisms depend on the history of synaptic use, others reflect the activity of modulatory neurons that are controlled through neural computations, and still others involve more global measures of neural activity. The molecular machinery synapses use to convey information from one neuron to the next not only plays an essential part in brain function but also is at the basis of processes that are vital to all cells. Because membrane fusion events at synapses are so precisely controlled, synapses offer an especially favorable system in which to study these basic processes. Here, I review some of the recent progress that has been made in understanding both how synaptic strength is regulated and how fundamental cell biological mechanisms are used to accomplish neuronal intercommunication.     

Voltage-gated calcium channels

Voltage-gated calcium (Ca(2+)) channels are key transducers of membrane potential changes into intracellular Ca(2+) transients that initiate many physiological events. There are ten members of the voltage-gated Ca(2+) channel family in mammals, and they serve distinct roles in cellular signal transduction. The Ca(V)1 subfamily initiates contraction, secretion, regulation of gene expression, integration of synaptic input in neurons, and synaptic transmission at ribbon synapses in specialized sensory cells. The Ca(V)2 subfamily is primarily responsible for initiation of synaptic transmission at fast synapses. The Ca(V)3 subfamily is important for repetitive firing of action potentials in rhythmically firing cells such as cardiac myocytes and thalamic neurons. This article presents the molecular relationships and physiological functions of these Ca(2+) channel proteins and provides information on their molecular, genetic, physiological, and pharmacological properties.     

On Optical Detection of Densely Labeled Synapses in Neuropil and Mapping Connectivity with Combinatorially Multiplexed Fluorescent Synaptic Markers

We propose a new method for mapping neural connectivity optically, by utilizing Cre/Lox system Brainbow to tag synapses of different neurons with random mixtures of different fluorophores, such as GFP, YFP, etc., and then detecting patterns of fluorophores at different synapses using light microscopy (LM). Such patterns will immediately report the pre- and post-synaptic cells at each synaptic connection, without tracing neural projections from individual synapses to corresponding cell bodies. We simulate fluorescence from a population of densely labeled synapses in a block of hippocampal neuropil, completely reconstructed from electron microscopy data, and show that high-end LM is able to detect such patterns with over 95% accuracy. We conclude, therefore, that with the described approach neural connectivity in macroscopically large neural circuits can be mapped with great accuracy, in scalable manner, using fast optical tools, and straightforward image processing. Relying on an electron microscopy dataset, we also derive and explicitly enumerate the conditions that should be met to allow synaptic connectivity studies with high-resolution optical tools.     

Synaptic energy use and supply

Neuronal computation is energetically expensive. Consequently, the brain's limited energy supply imposes constraints on its information processing capability. Most brain energy is used on synaptic transmission, making it important to understand how energy is provided to and used by synapses. We describe how information transmission through presynaptic terminals and postsynaptic spines is related to their energy consumption, assess which mechanisms normally ensure an adequate supply of ATP to these structures, consider the influence of synaptic plasticity and changing brain state on synaptic energy use, and explain how disruption of the energy supply to synapses leads to neuropathology.     

Emergence of resonances in neural systems: the interplay between adaptive threshold and short-term synaptic plasticity

In this work we study the detection of weak stimuli by spiking (integrate-and-fire) neurons in the presence of certain level of noisy background neural activity. Our study has focused in the realistic assumption that the synapses in the network present activity-dependent processes, such as short-term synaptic depression and facilitation. Employing mean-field techniques as well as numerical simulations, we found that there are two possible noise levels which optimize signal transmission. This new finding is in contrast with the classical theory of stochastic resonance which is able to predict only one optimal level of noise. We found that the complex interplay between adaptive neuron threshold and activity-dependent synaptic mechanisms is responsible for this new phenomenology. Our main results are confirmed by employing a more realistic FitzHugh-Nagumo neuron model, which displays threshold variability, as well as by considering more realistic stochastic synaptic models and realistic signals such as poissonian spike trains.     

Membrane parameters,signal transmission,and the design of a graded potential neuron

1. The large monopolar cells (LMCs) of the fly, Calliphora vicina, visual system transmit graded potentials over distances of up to 1.0 mm. An electrical model was constructed to investigate the design principles relating their membrane parameters to signal transmission and filtering. 2. Using existing anatomical measurements, a cable model (van Hateren 1986) was fitted to the measured intracellular responses of the cells to injected current. The LMC has three functional components: a distal synaptic zone of low impedance, an axon with high specific membrane resistance (greater than 50.10(5) M omega.micron 2), and a high impedance proximal terminal. These components interact to transmit information efficiently. The low input impedance synaptic zone charges and discharges the axon rapidly, ensuring a good frequency response. The high resistance axon conducts signals with little decrement. The model shows that graded potential transmission in LMCs selectively filters synaptic noise and predicts the changes in response waveform that occur during transmission. 3. The parameters of the model were adjusted to determine the relative costs and benefits of alternative cable designs. The design used in LMCs is the most expensive and the most effective. It requires the largest currents to generate responses but transmits signals with least decrement. Parallel neurons in the fly visual system have fewer input synapses and this could low-pass filter their graded response.     

内源性大麻素系统对皮层下运动中枢的调控作用

以往研究已证明,内源性大麻素系统广泛存在于中枢和外周神经组织中,并作为逆向信号分子在突触信号传递中发挥重要调节作用。本文就内源性大麻素系统对皮层下运动中枢的调控作用及相关机制进行综述,以期系统地论述皮层下运动中枢在躯体运动、动作选择和运动技能学习等高级神经活动过程中的突触和神经环路机制,并为相关疾病的治疗和靶向药物开发提供理论依据。     

Activity-dependent regulation of synaptic size in Drosophila neuromuscular junctions

One of the fundamental questions in neural development is how neurons form synapses of the appropriate size for the efficient transfer of information across neural circuits. Here we investigated the mechanisms that bring about the size correlation between synapses and postsynaptic cells during development of Drosophila neuromuscular junctions (NMJs). To do this, we made use of a unique system in which two neighboring muscles (M6 and M7) are innervated by the same neurons. In mature NMJs, synaptic size on M6 is normally larger than that on M7, in accordance with the difference in muscle volume; this ensures the same extent of contraction of both muscles, and we refer to this correspondence as "matching". We found that matching was apparent in larvae 8 h after hatching, but not in newly hatched larvae despite the difference in muscle volume. When sensory inputs were suppressed by the expression of tetanus toxin in sensory neurons, matching did not occur, although synapses were able to grow. Matching was also suppressed by the inhibition of motoneuronal activity. These results suggest that matching is induced by regulating the rate of synaptic growth on M6 and M7 in an experience- and activity-dependent manner. It seems most likely that retrograde signals from the postsynaptic to the presynaptic cell convey the information about muscle cell size. We thus examined whether a candidate of retrograde signaling in NMJs, BMP signaling, is involved in matching. However, there was no effect on matching in BMP type II receptor gene mutants, suggesting that other experience-driven mechanisms besides BMP signaling are involved in the proper development of synapses.