Less means more: inhibition of spontaneous firing triggers persistent increases in excitability

Modulation of intrinsic excitability is an alternative to classical synaptic plasticity for implementing activity-dependent changes in neuronal networks. In this issue of Neuron, Nelson et al. reveal a new form of plasticity of intrinsic excitability that can be triggered rapidly when synaptic inhibition reduces spontaneous firing, resulting in persistent enhancement of firing rate and neuronal gain.     

Role of the endoplasmic reticulum in synaptic transmission

Neurons possess a complex morphology spanning long distances and a large number of subcellular specializations such as presynaptic terminals and dendritic spines. This structural complexity is essential for maintenance of synaptic junctions and associated electrical as well as biochemical signaling events. Given the structural and functional complexity of neurons, neuronal endoplasmic reticulum is emerging as a key regulator of neuronal function, in particular synaptic signaling. Neuronal endoplasmic reticulum mediates calcium signaling, calcium and lipid homeostasis, vesicular trafficking, and proteostasis events that underlie autonomous functions of numerous subcellular compartments. However, based on its geometric complexity spanning the whole neuron, endoplasmic reticulum also integrates the activity of these autonomous compartments across the neuron and coordinates their interactions with the soma. In this article, we review recent work regarding neuronal endoplasmic reticulum function and its relationship to neurotransmission and plasticity.     

体外培养的神经元网络可塑性

神经元网络是大脑执行高级认知行为的结构基础,研究证明学习记忆及神经退行性疾病与神经元网络可塑性密切相关。因此,揭示调控和改变神经元网络可塑性的机制对理解神经系统信息交互以及疾病治疗具有重大意义。目前,基于微电极阵列（microelectrode array, MEA）培养的神经元网络是体外探究学习和记忆机制的理想模型,同时针对该模型的研究为预防和治疗神经退行性疾病提供了独特的视角。本文综述了基于MEA采集体外培养神经元网络的放电信号来构建功能网络的相关研究,分别从二维神经元网络和三维脑类器官发育,以及开环和闭环电刺激对神经元网络可塑性影响的角度,总结了体外培养神经元网络可塑性的相关研究,最后对该方向的应用前景进行了展望。     

Learning-Induced Synchronization and Plasticity of a Developing Neural Network

Learning-induced synchronization of a neural network at various developing stages is studied by computer simulations using a pulse-coupled neural network model in which the neuronal activity is simulated by a one-dimensional map. Two types of Hebbian plasticity rules are investigated and their differences are compared. For both models, our simulations show a logarithmic increase in the synchronous firing frequency of the network with the culturing time of the neural network. This result is consistent with recent experimental observations. To investigate how to control the synchronization behavior of a neural network after learning, we compare the occurrence of synchronization for four networks with different designed patterns under the influence of an external signal. The effect of such a signal on the network activity highly depends on the number of connections between neurons. We discuss the synaptic plasticity and enhancement effects for a random network after learning at various developing stages.     

Wiring and firing neuronal networks: endocannabinoids take center stage

Endocannabinoids (eCBs) function as retrograde messengers at both excitatory and inhibitory synapses, and control various forms of synaptic plasticity in the adult brain. The molecular machinery required for specific eCB functions during synaptic plasticity is well established. However, eCB signaling plays surprisingly fundamental roles in controlling the acquisition of neuronal identity during CNS development. Recent work suggests that selective recruitment of regulatory signaling networks to CB1 cannabinoid receptors dictates neuronal state-change decisions. In addition, the spatial localization and temporal precision of eCB actions emerges as a novel organizer in developing neuronal networks. Current challenges include fitting novel molecular candidates into regulatory eCB signaling pathways, and defining the temporal dynamics of context-dependent signaling mechanisms underpinning particular neuronal specification events.     

Communication between neurons and astrocytes: relevance to the modulation of synaptic and network activity

Neuromodulation is a fundamental process in the brain that regulates synaptic transmission, neuronal network activity and behavior. Emerging evidence demonstrates that astrocytes, a major population of glial cells in the brain, play previously unrecognized functions in neuronal modulation. Astrocytes can detect the level of neuronal activity and release chemical transmitters to influence neuronal function. For example, recent findings show that astrocytes play crucial roles in the control of Hebbian plasticity, the regulation of neuronal excitability and the induction of homeostatic plasticity. This review discusses the importance of astrocyte-to-neuron signaling in different aspects of neuronal function from the activity of single synapses to that of neuronal networks.     

Reelin induces EphB activation

The integration of newborn neurons into functional neuronal networks requires migration of cells to their final position in the developing brain, the growth and arborization of neuronal processes and the formation of synaptic contacts with other neurons. A central player among the signals that coordinate this complex sequence of differentiation events is the secreted glycoprotein Reelin, which also modulates synaptic plasticity, learning and memory formation in the adult brain. Binding of Reelin to ApoER2 and VLDL receptor, two members of the LDL receptor family, initiates a signaling cascade involving tyrosine phosphorylation of the intracellular cytoplasmic adaptor protein Disabled-1, which targets the neuronal cytoskeleton and ultimately controls the positioning of neurons throughout the developing brain. However, it is possible that Reelin signals interact with other receptor-mediated signaling cascades to regulate different aspects of brain development and plasticity. EphB tyrosine kinases regulate cell adhesion and repulsion-dependent processes via bidirectional signaling through ephrin B transmembrane proteins. Here, we demonstrate that Reelin binds to the extracellular domains of EphB transmembrane proteins, inducing receptor clustering and activation of EphB forward signaling in neurons, independently of the ''classical'' Reelin receptors, ApoER2 and VLDLR. Accordingly, mice lacking EphB1 and EphB2 display a positioning defect of CA3 hippocampal pyramidal neurons, similar to that in Reelin-deficient mice, and this cell migration defect depends on the kinase activity of EphB proteins. Together, our data provide biochemical and functional evidence for signal integration between Reelin and EphB forward signaling.     

Retrograde regulation in the CNS; neuron-specific interpretations of TGF-beta signaling

Retrograde signals influence neuronal survival, differentiation, synaptogenesis, and plasticity. Several recent papers describe novel roles for the well-studied TGF-beta pathway in retrograde synaptic signaling. While each dissects spatial and molecular aspects of TGF-beta signaling in a specific synaptic context, together these studies demonstrate that a specific retrograde signal may be interpreted in diverse, neuron-specific ways. Thus, a neuron's intrinsic properties and its other extrinsic signaling inputs determine its cellular and genomic response to TGF-beta.     

Excitement and synchronization of small-world neuronal networks with short-term synaptic plasticity

Excitement and synchronization of electrically and chemically coupled Newman-Watts (NW) small-world neuronal networks with a short-term synaptic plasticity described by a modified Oja learning rule are investigated. For each type of neuronal network, the variation properties of synaptic weights are examined first. Then the effects of the learning rate, the coupling strength and the shortcut-adding probability on excitement and synchronization of the neuronal network are studied. It is shown that the synaptic learning suppresses the over-excitement, helps synchronization for the electrically coupled network but impairs synchronization for the chemically coupled one. Both the introduction of shortcuts and the increase of the coupling strength improve synchronization and they are helpful in increasing the excitement for the chemically coupled network, but have little effect on the excitement of the electrically coupled one.     

The Role of Type 4 Phosphodiesterases in Generating Microdomains of cAMP: Large Scale Stochastic Simulations

Cyclic AMP (cAMP) and its main effector Protein Kinase A (PKA) are critical for several aspects of neuronal function including synaptic plasticity. Specificity of synaptic plasticity requires that cAMP activates PKA in a highly localized manner despite the speed with which cAMP diffuses. Two mechanisms have been proposed to produce localized elevations in cAMP, known as microdomains: impeded diffusion, and high phosphodiesterase (PDE) activity. This paper investigates the mechanism of localized cAMP signaling using a computational model of the biochemical network in the HEK293 cell, which is a subset of pathways involved in PKA-dependent synaptic plasticity. This biochemical network includes cAMP production, PKA activation, and cAMP degradation by PDE activity. The model is implemented in NeuroRD: novel, computationally efficient, stochastic reaction-diffusion software, and is constrained by intracellular cAMP dynamics that were determined experimentally by real-time imaging using an Epac-based FRET sensor (H30). The model reproduces the high concentration cAMP microdomain in the submembrane region, distinct from the lower concentration of cAMP in the cytosol. Simulations further demonstrate that generation of the cAMP microdomain requires a pool of PDE4D anchored in the cytosol and also requires PKA-mediated phosphorylation of PDE4D which increases its activity. The microdomain does not require impeded diffusion of cAMP, confirming that barriers are not required for microdomains. The simulations reported here further demonstrate the utility of the new stochastic reaction-diffusion algorithm for exploring signaling pathways in spatially complex structures such as neurons.     

Control of neuronal excitability by GSK-3beta: Epilepsy and beyond

Glycogen synthase kinase 3beta (GSK-3β) is an enzyme with a variety of cellular functions in addition to the regulation of glycogen metabolism. In the central nervous system, different intracellular signaling pathways converge on GSK-3β through a cascade of phosphorylation events that ultimately control a broad range of neuronal functions in the development and adulthood. In mice, genetically removing or increasing GSK-3β cause distinct functional and structural neuronal phenotypes and consequently affect cognition. Precise control of GSK-3β activity is important for such processes as neuronal migration, development of neuronal morphology, synaptic plasticity, excitability, and gene expression. Altered GSK-3β activity contributes to aberrant plasticity within neuronal circuits leading to neurological, psychiatric disorders, and neurodegenerative diseases. Therapeutically targeting GSK-3β can restore the aberrant plasticity of neuronal networks at least in animal models of these diseases. Although the complete repertoire of GSK-3β neuronal substrates has not been defined, emerging evidence shows that different ion channels and their accessory proteins controlling excitability, neurotransmitter release, and synaptic transmission are regulated by GSK-3β, thereby supporting mechanisms of synaptic plasticity in cognition. Dysregulation of ion channel function by defective GSK-3β activity sustains abnormal excitability in the development of epilepsy and other GSK-3β-linked human diseases.     

The back and forth of dendritic plasticity

Synapses are located throughout the often-elaborate dendritic tree of central neurons. Hebbian models of plasticity require temporal association between synaptic input and neuronal output to produce long-term potentiation of excitatory transmission. Recent studies have highlighted how active dendritic spiking mechanisms control this association. Here, we review new work showing that associative synaptic plasticity can be generated without neuronal output and that the interplay between neuronal architecture and the active electrical properties of the dendritic tree regulates synaptic plasticity.     

Modelling the modulation of cortical Up-Down state switching by astrocytes

Up-Down synchronization in neuronal networks refers to spontaneous switches between periods of high collective firing activity (Up state) and periods of silence (Down state). Recent experimental reports have shown that astrocytes can control the emergence of such Up-Down regimes in neural networks, although the molecular or cellular mechanisms that are involved are still uncertain. Here we propose neural network models made of three populations of cells: excitatory neurons, inhibitory neurons and astrocytes, interconnected by synaptic and gliotransmission events, to explore how astrocytes can control this phenomenon. The presence of astrocytes in the models is indeed observed to promote the emergence of Up-Down regimes with realistic characteristics. Our models show that the difference of signalling timescales between astrocytes and neurons (seconds versus milliseconds) can induce a regime where the frequency of gliotransmission events released by the astrocytes does not synchronize with the Up and Down phases of the neurons, but remains essentially stable. However, these gliotransmission events are found to change the localization of the bifurcations in the parameter space so that with the addition of astrocytes, the network enters a bistability region of the dynamics that corresponds to Up-Down synchronization. Taken together, our work provides a theoretical framework to test scenarios and hypotheses on the modulation of Up-Down dynamics by gliotransmission from astrocytes.     

Proteomics in the study of hippocampal plasticity

Synaptic plasticity is the dynamic regulation of the strength of synaptic communication between nerve cells. It is central to neuronal development as well as experience-dependent remodeling of the adult nervous system as occurs during memory formation. Aberrant forms of synaptic plasticity also accompany a variety of neurological and psychiatric diseases, and unraveling the biological basis of synaptic plasticity has been a major goal in neurobiology research. The biochemical and structural mechanisms underlying different forms of synaptic plasticity are complex, involving multiple signaling cascades, reconfigurations of structural proteins and the trafficking of synaptic proteins. As such, proteomics should be a valuable tool in dissecting the molecular events underlying normal and disease-related forms of plasticity. In fact, progress in this area has been disappointingly slow. We discuss the particular challenges associated with proteomic interrogation of synaptic plasticity processes and outline ways in which we believe proteomics may advance the field over the next few years. We pay particular attention to technical advances being made in small sample proteomics and the advent of proteomic imaging in studying brain plasticity.     

HillTau: A fast,compact abstraction for model reduction in biochemical signaling networks

Signaling networks mediate many aspects of cellular function. The conventional, mechanistically motivated approach to modeling such networks is through mass-action chemistry, which maps directly to biological entities and facilitates experimental tests and predictions. However such models are complex, need many parameters, and are computationally costly. Here we introduce the HillTau form for signaling models. HillTau retains the direct mapping to biological observables, but it uses far fewer parameters, and is 100 to over 1000 times faster than ODE-based methods. In the HillTau formalism, the steady-state concentration of signaling molecules is approximated by the Hill equation, and the dynamics by a time-course tau. We demonstrate its use in implementing several biochemical motifs, including association, inhibition, feedforward and feedback inhibition, bistability, oscillations, and a synaptic switch obeying the BCM rule. The major use-cases for HillTau are system abstraction, model reduction, scaffolds for data-driven optimization, and fast approximations to complex cellular signaling.     

Mutation of the Protein Kinase C Site in Borna Disease Virus Phosphoprotein Abrogates Viral Interference with Neuronal Signaling and Restores Normal Synaptic Activity

Understanding the pathogenesis of infection by neurotropic viruses represents a major challenge and may improve our knowledge of many human neurological diseases for which viruses are thought to play a role. Borna disease virus (BDV) represents an attractive model system to analyze the molecular mechanisms whereby a virus can persist in the central nervous system (CNS) and lead to altered brain function, in the absence of overt cytolysis or inflammation. Recently, we showed that BDV selectively impairs neuronal plasticity through interfering with protein kinase C (PKC)–dependent signaling in neurons. Here, we tested the hypothesis that BDV phosphoprotein (P) may serve as a PKC decoy substrate when expressed in neurons, resulting in an interference with PKC-dependent signaling and impaired neuronal activity. By using a recombinant BDV with mutated PKC phosphorylation site on P, we demonstrate the central role of this protein in BDV pathogenesis. We first showed that the kinetics of dissemination of this recombinant virus was strongly delayed, suggesting that phosphorylation of P by PKC is required for optimal viral spread in neurons. Moreover, neurons infected with this mutant virus exhibited a normal pattern of phosphorylation of the PKC endogenous substrates MARCKS and SNAP-25. Finally, activity-dependent modulation of synaptic activity was restored, as assessed by measuring calcium dynamics in response to depolarization and the electrical properties of neuronal networks grown on microelectrode arrays. Therefore, preventing P phosphorylation by PKC abolishes viral interference with neuronal activity in response to stimulation. Our findings illustrate a novel example of viral interference with a differentiated neuronal function, mainly through competition with the PKC signaling pathway. In addition, we provide the first evidence that a viral protein can specifically interfere with stimulus-induced synaptic plasticity in neurons.     

Self-stabilization of neuronal networks

Between the extreme views concerning ontogenesis (genetic vs. environmental determination), we use a moderate approach: a somehow pre-established neuronal model network reacts to activity deviations (reflecting input to be compensated), and stabilizes itself during a complex feed-back process. Morphogenesis is based on an algorithm formalizing the compensation theory of synaptogenesis (Wolff and Wagner 1983). This algorithm is applied to randomly connected McCulloch-Pitts networks that are able to maintain oscillations of their activity patterns over time. The algorithm can lead to networks which are morphogenetically stable but preserve self-maintained oscillations in activity. This is in contrast to most of the current models of synaptogenesis and synaptic modification based on Hebbian rules of plasticity. Hebbian networks are morphogenetically unstable without additional assumptions. The effects of compensation on structural and functional properties of the networks are described. It is concluded that the compensation theory of synaptogenesis can account for the development of morphogenetically stable neuronal networks out of randomly connected networks via selective stabilization and elimination of synapses.The logic of the compensation algorithm is based on experimental results. The present paper shows that the compensation theory can not only predict the behavior of synaptic populations (Wagner and Wolff, in preparation), but it can also describe the behavior of neurons interconnected in a network, with the resulting additional system properties. The neuronal interactions-leading to equilibrium in certain cases-are a self-organizing process in the sense that all decisions are performed on the individual cell level without knowing the overall network situation or goal.