A Calcium-Dependent Plasticity Rule for HCN Channels Maintains Activity Homeostasis and Stable Synaptic Learning

Theoretical and computational frameworks for synaptic plasticity and learning have a long and cherished history, with few parallels within the well-established literature for plasticity of voltage-gated ion channels. In this study, we derive rules for plasticity in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, and assess the synergy between synaptic and HCN channel plasticity in establishing stability during synaptic learning. To do this, we employ a conductance-based model for the hippocampal pyramidal neuron, and incorporate synaptic plasticity through the well-established Bienenstock-Cooper-Munro (BCM)-like rule for synaptic plasticity, wherein the direction and strength of the plasticity is dependent on the concentration of calcium influx. Under this framework, we derive a rule for HCN channel plasticity to establish homeostasis in synaptically-driven firing rate, and incorporate such plasticity into our model. In demonstrating that this rule for HCN channel plasticity helps maintain firing rate homeostasis after bidirectional synaptic plasticity, we observe a linear relationship between synaptic plasticity and HCN channel plasticity for maintaining firing rate homeostasis. Motivated by this linear relationship, we derive a calcium-dependent rule for HCN-channel plasticity, and demonstrate that firing rate homeostasis is maintained in the face of synaptic plasticity when moderate and high levels of cytosolic calcium influx induced depression and potentiation of the HCN-channel conductance, respectively. Additionally, we show that such synergy between synaptic and HCN-channel plasticity enhances the stability of synaptic learning through metaplasticity in the BCM-like synaptic plasticity profile. Finally, we demonstrate that the synergistic interaction between synaptic and HCN-channel plasticity preserves robustness of information transfer across the neuron under a rate-coding schema. Our results establish specific physiological roles for experimentally observed plasticity in HCN channels accompanying synaptic plasticity in hippocampal neurons, and uncover potential links between HCN-channel plasticity and calcium influx, dynamic gain control and stable synaptic learning.     

Neuron-astrocyte signaling in the development and plasticity of neural circuits

Emerging evidence indicates that signaling between perisynaptic astrocytes and neurons at the tripartite synapse plays an important role during the critical period when neural circuits are formed and refined. Cross-talk between astrocytes and neurons during development mediates synaptogenesis, synapse elimination and structural plasticity through a variety of secreted and contact-dependent signals. Recent live imaging studies reveal a dynamic and cooperative interplay between astrocytes and neurons at synapses that is guided by a variety of molecular cues. A unifying theme from these recent findings is that astrocytes can promote the development and plasticity of synaptic circuits. Insight into the molecular mechanisms by which astrocytes regulate the wiring of the brain during development could lead to new therapeutic strategies to promote repair and rewiring of neural circuits in the mature brain following CNS injury and neurodegenerative disease.     

Glial calcium signaling and neuron-glia communication

The existence of bidirectional signaling between astrocytes and neurons has revealed an important active role of astrocytes in the physiology of the nervous system. As a consequence, there is a new concept of the synaptic physiology-"the tripartite synapse", where astrocytes exchange information with the pre- and postsynaptic elements and participate as dynamic regulatory elements in neurotransmission. The control of the Ca2+ excitability in astrocytes is a key element in this loop of information exchange. The ability of astrocytes to respond to neuronal activity and discriminate between the activity of different synapses, the modulation of the astrocytic cellular excitability by the synaptic activity, and the expression of cellular intrinsic properties indicate that astrocytes are endowed with cellular computational characteristics that process synaptic information. Therefore, we propose that astrocytes can be considered as cellular elements involved in the information processing by the nervous system.     

锥体神经元的连接模式对突触后局部电位的依赖

脑皮层的功能连接模式与突触可塑性密切相关,受突触空间分布和刺激模式等多种因素的影响。尽管越来越多的证据表明突触可塑性不仅受突触后动作电位而且还受突触后局部树突电位的影响,但是目前尚不清楚神经元的功能连接模式是否和怎样依赖于突触后局部电位的。为此,本文建立了一个无需硬边界设置的、突触后局部膜电位依赖的可塑性模型。该模型具有突触强度的自平衡能力并且能够再现多种突触可塑性实验结果。基于该模型对两个锥体神经元的功能连接模式进行仿真的结果表明,当突触后局部电位都处于亚阈值时两个神经元无功能连接,如果一个神经元的突触后膜电位高于阈值电位则产生向该神经元的单向连接,当两个神经元的突触后膜电位都超过阈值电位时则产生双向连接,说明突触后局部膜电位分布是神经元功能连接模式形成的关键。研究结果加深了神经网络连接模式形成机制的理解,对学习和记忆的研究具有重要意义。     

Acquiring new information in a neuronal network: from Hebb's concept to homeostatic plasticity

Synaptic plasticity is the cellular mechanism underlying the phenomena of learning and memory. Much of the research on synaptic plasticity is based on the postulate of Hebb (1949) who proposed that, when a neuron repeatedly takes part in the activation of another neuron, the efficacy of the connections between these neurons is increased. Plasticity has been extensively studied, and often demonstrated through the processes of LTP (Long Term Potentiation) and LTD (Long Term Depression), which represent an increase and a decrease of the efficacy of long-term synaptic transmission. This review summarizes current knowledge concerning the cellular mechanisms of LTP and LTD, whether at the level of excitatory synapses, which have been the most studied, or at the level of inhibitory synapses. However, if we consider neuronal networks rather than the individual synapses, the consequences of synaptic plasticity need to be considered on a large scale to determine if the activity of networks are changed or not. Homeostatic plasticity takes into account the mechanisms which control the efficacy of synaptic transmission for all the synaptic inputs of a neuron. Consequently, this new concept deals with the coordinated activity of excitatory and inhibitory networks afferent to a neuron which maintain a controlled level of excitability during the acquisition of new information related to the potentiation or to the depression of synaptic efficacy. We propose that the protocols of stimulation used to induce plasticity at the synaptic level set up a "homeostatic potentiation" or a "homeostatic depression" of excitation and inhibition at the level of the neuronal networks. The coordination between excitatory and inhibitory circuits allows the neuronal networks to preserve a level of stable activity, thus avoiding episodes of hyper- or hypo-activity during the learning and memory phases.     

Glia-derived D-serine controls NMDA receptor activity and synaptic memory

The NMDA receptor is a key player in excitatory transmission and synaptic plasticity in the central nervous system. Its activation requires the binding of both glutamate and a co-agonist like D-serine to its glycine site. As D-serine is released exclusively by astrocytes, we studied the physiological impact of the glial environment on NMDA receptor-dependent activity and plasticity. To this end, we took advantage of the changing astrocytic ensheathing of neurons occurring in the supraoptic nucleus during lactation. We provide direct evidence that in this hypothalamic structure the endogenous co-agonist of NMDA receptors is D-serine and not glycine. Consequently, the degree of astrocytic coverage of neurons governs the level of glycine site occupancy on the NMDA receptor, thereby affecting their availability for activation and thus the activity dependence of long-term synaptic changes. Such a contribution of astrocytes to synaptic metaplasticity fuels the emerging concept that astrocytes are dynamic partners of brain signaling.     

Reshaping neuron-glial communication at hippocampal synapses

Neuron-glial interactions in the nervous system are of fundamental importance to many processes including neural migration,axon guidance, myelination and synaptic transmission. At synapses in the CNS, the physiological and structural relationship between neurons and astrocytes is particularly complex. The juxtaposition of astrocytic membranes with presynaptic and postsynaptic elements is important for regulating synaptic transmission and plasticity. Recent investigations demonstrate that the morphology of both neuronal and glial components show rapid, continuous structural remodeling in the hippocampus.These physical modifications are likely to have a significant functional impact upon neurotransmission and indicate that there modeling of astrocytic morphology might be crucial for the dynamic regulation of the synapse and its microenvironment. In this review, we focus on the structural complexities of astrocyte-synapse interactions in the hippocampus and their implications for understanding synaptic physiology, behavior and disease.     

神经胶质细胞与突触可塑性研究新进展

突触的可塑性是研究学习与记忆的基础,很长时间以来人们对突触的可塑性研究主要集中在神经元和突触上;而胶质细胞的作用较少受到注意。最近的研究发现胶质细胞也参与突触的构成并影响突触的活动。研究表明中枢神经系统中的胶质细胞包括星形胶质细胞、小胶质细胞和少突胶质细胞可分别通过谷氨酸、丝氨酸、甘氨酸、ATP等信号调节突触的可塑性,从而为突触的可塑性研究提供了新的思路和方向,并有助于阐明突触的发生以及学习与记忆的机制。     

Modulation of hippocampal plasticity in learning and memory

Synaptic plasticity plays a central role in the study of neural mechanisms of learning and memory. Plasticity rules are not invariant over time but are under neuromodulatory control, enabling behavioral states to influence memory formation. Neuromodulation controls synaptic plasticity at network level by directing information flow, at circuit level through changes in excitation/inhibition balance, and at synaptic level through modulation of intracellular signaling cascades. Although most research has focused on modulation of principal neurons, recent progress has uncovered important roles for interneurons in not only routing information, but also setting conditions for synaptic plasticity. Moreover, astrocytes have been shown to both gate and mediate plasticity. These additional mechanisms must be considered for a comprehensive mechanistic understanding of learning and memory.     

The influence of the astrocyte field on neuronal dynamics and synchronization

Astrocytes can sense local synaptic release of glutamate by metabotropic glutamate receptors. Receptor activation in turn can mediate transient increases of astrocytic intracellular calcium concentration through inositol 1,4,5-trisphosphate production. Notably, the perturbation of calcium concentration can propagate to other adjacent astrocytes. Astrocytic calcium signaling can therefore be linked to synaptic information transfer between neurons. On the other hand, astrocytes can also modulate neuronal activity by feeding back onto synaptic terminals in a fashion that depends on their intracellular calcium concentration. Thus, astrocytes can also be active partners in neuronal network activity. The aim of our study is to provide a computationally simple network model of mutual neuron–astrocyte interactions, in order to investigate the possible roles of astrocytes in neuronal network dynamics. In particular, we focus on the information entropy of neuronal firing of the whole network, considering how it could be affected by neuron–glial interactions.     

The Formation of Multi-synaptic Connections by the Interaction of Synaptic and Structural Plasticity and Their Functional Consequences

Cortical connectivity emerges from the permanent interaction between neuronal activity and synaptic as well as structural plasticity. An important experimentally observed feature of this connectivity is the distribution of the number of synapses from one neuron to another, which has been measured in several cortical layers. All of these distributions are bimodal with one peak at zero and a second one at a small number (3–8) of synapses.In this study, using a probabilistic model of structural plasticity, which depends on the synaptic weights, we explore how these distributions can emerge and which functional consequences they have.We find that bimodal distributions arise generically from the interaction of structural plasticity with synaptic plasticity rules that fulfill the following biological realistic constraints: First, the synaptic weights have to grow with the postsynaptic activity. Second, this growth curve and/or the input-output relation of the postsynaptic neuron have to change sub-linearly (negative curvature). As most neurons show such input-output-relations, these constraints can be fulfilled by many biological reasonable systems.Given such a system, we show that the different activities, which can explain the layer-specific distributions, correspond to experimentally observed activities.Considering these activities as working point of the system and varying the pre- or postsynaptic stimulation reveals a hysteresis in the number of synapses. As a consequence of this, the connectivity between two neurons can be controlled by activity but is also safeguarded against overly fast changes.These results indicate that the complex dynamics between activity and plasticity will, already between a pair of neurons, induce a variety of possible stable synaptic distributions, which could support memory mechanisms.     

Long Lasting Protein Synthesis- and Activity-Dependent Spine Shrinkage and Elimination after Synaptic Depression

Neuronal circuits modify their response to synaptic inputs in an experience-dependent fashion. Increases in synaptic weights are accompanied by structural modifications, and activity dependent, long lasting growth of dendritic spines requires new protein synthesis. When multiple spines are potentiated within a dendritic domain, they show dynamic structural plasticity changes, indicating that spines can undergo bidirectional physical modifications. However, it is unclear whether protein synthesis dependent synaptic depression leads to long lasting structural changes. Here, we investigate the structural correlates of protein synthesis dependent long-term depression (LTD) mediated by metabotropic glutamate receptors (mGluRs) through two-photon imaging of dendritic spines on hippocampal pyramidal neurons. We find that induction of mGluR-LTD leads to robust and long lasting spine shrinkage and elimination that lasts for up to 24 hours. These effects depend on signaling through group I mGluRs, require protein synthesis, and activity. These data reveal a mechanism for long lasting remodeling of synaptic inputs, and offer potential insights into mental retardation.     

Anatomical aspects of glia-synapse interaction: the perisynaptic glial sheath consists of a specialized astrocyte compartment.

Amongst several forms of glia-neuronal communication, glia-synaptic interaction appears particularly interesting in the light of the well-known examples of two-way signaling between neurons and astrocytes. We review recent structural and physiological evidence showing that the structural correlate of glia-synaptic interaction is the peripheral astrocyte process (PAP) positioned next to the synaptic cleft. The structural and functional properties of these processes suggest that the PAP represents a separate astroglial compartment, in particular since it is characterized by the restricted localization of the actin-binding ERM protein ezrin. The structural properties of PAPs and this protein form the basis of rapid morphological changes of PAPs. The physiological relevance of PAP plasticity is illustrated by the example of the suprachiasmatic nucleus, where astrocytes display a high degree of activity-dependent plasticity reflecting circadian time.     

Role of delayed nonsynaptic neuronal plasticity in long-term associative memory

BACKGROUND: It is now well established that persistent nonsynaptic neuronal plasticity occurs after learning and, like synaptic plasticity, it can be the substrate for long-term memory. What still remains unclear, though, is how nonsynaptic plasticity contributes to the altered neural network properties on which memory depends. Understanding how nonsynaptic plasticity is translated into modified network and behavioral output therefore represents an important objective of current learning and memory research. RESULTS: By using behavioral single-trial classical conditioning together with electrophysiological analysis and calcium imaging, we have explored the cellular mechanisms by which experience-induced nonsynaptic electrical changes in a neuronal soma remote from the synaptic region are translated into synaptic and circuit level effects. We show that after single-trial food-reward conditioning in the snail Lymnaea stagnalis, identified modulatory neurons that are extrinsic to the feeding network become persistently depolarized between 16 and 24 hr after training. This is delayed with respect to early memory formation but concomitant with the establishment and duration of long-term memory. The persistent nonsynaptic change is extrinsic to and maintained independently of synaptic effects occurring within the network directly responsible for the generation of feeding. Artificial membrane potential manipulation and calcium-imaging experiments suggest a novel mechanism whereby the somal depolarization of an extrinsic neuron recruits command-like intrinsic neurons of the circuit underlying the learned behavior. CONCLUSIONS: We show that nonsynaptic plasticity in an extrinsic modulatory neuron encodes information that enables the expression of long-term associative memory, and we describe how this information can be translated into modified network and behavioral output.     

Self-influencing synaptic plasticity: Recurrent changes of synaptic weights can lead to specific functional properties

Recent experimental results suggest that dendritic and back-propagating spikes can influence synaptic plasticity in different ways (Holthoff, 2004; Holthoff et al., 2005). In this study we investigate how these signals could interact at dendrites in space and time leading to changing plasticity properties at local synapse clusters. Similar to a previous study (Saudargiene et al., 2004) we employ a differential Hebbian learning rule to emulate spike-timing dependent plasticity and investigate how the interaction of dendritic and back-propagating spikes, as the post-synaptic signals, could influence plasticity. Specifically, we will show that local synaptic plasticity driven by spatially confined dendritic spikes can lead to the emergence of synaptic clusters with different properties. If one of these clusters can drive the neuron into spiking, plasticity may change and the now arising global influence of a back-propagating spike can lead to a further segregation of the clusters and possibly the dying-off of some of them leading to more functional specificity. These results suggest that through plasticity being a spatial and temporal local process, the computational properties of dendrites or complete neurons can be substantially augmented. Action Editor: Wulfram Gerstner     

Modeling synaptic transmission of the tripartite synapse

The tripartite synapse denotes the junction of a pre- and postsynaptic neuron modulated by a synaptic astrocyte. Enhanced transmission probability and frequency of the postsynaptic current-events are among the significant effects of the astrocyte on the synapse as experimentally characterized by several groups. In this paper we provide a mathematical framework for the relevant synaptic interactions between neurons and astrocytes that can account quantitatively for both the astrocytic effects on the synaptic transmission and the spontaneous postsynaptic events. Inferred from experiments, the model assumes that glutamate released by the astrocytes in response to synaptic activity regulates store-operated calcium in the presynaptic terminal. This source of calcium is distinct from voltage-gated calcium influx and accounts for the long timescale of facilitation at the synapse seen in correlation with calcium activity in the astrocytes. Our model predicts the inter-event interval distribution of spontaneous current activity mediated by a synaptic astrocyte and provides an additional insight into a novel mechanism for plasticity in which a low fidelity synapse gets transformed into a high fidelity synapse via astrocytic coupling.     

Bidirectional plasticity gated by hyperpolarization controls the gain of postsynaptic firing responses at central vestibular nerve synapses

Linking synaptic plasticity with behavioral learning requires understanding how synaptic efficacy influences postsynaptic firing in neurons whose role in behavior is understood. Here, we examine plasticity at a candidate site of motor learning: vestibular nerve synapses onto neurons that mediate reflexive movements. Pairing nerve activity with changes in postsynaptic voltage induced bidirectional synaptic plasticity in vestibular nucleus projection neurons: long-term potentiation relied on calcium-permeable AMPA receptors and postsynaptic hyperpolarization, whereas long-term depression relied on NMDA receptors and postsynaptic depolarization. Remarkably, both forms of plasticity uniformly scaled synaptic currents evoked by pulse trains, and these changes in synaptic efficacy were translated into linear increases or decreases in postsynaptic firing responses. Synapses onto local inhibitory neurons were also plastic but expressed only long-term depression. Bidirectional, linear gain control of vestibular nerve synapses onto projection neurons provides a plausible mechanism for motor learning underlying adaptation of vestibular reflexes.     

Astrocyte-induced Synaptogenesis Is Mediated by Transforming Growth Factor �� Signaling through Modulation of d-Serine Levels in Cerebral Cortex Neurons

Assembly of synapses requires proper coordination between pre- and postsynaptic elements. Identification of cellular and molecular events in synapse formation and maintenance is a key step to understand human perception, learning, memory, and cognition. A key role for astrocytes in synapse formation and function has been proposed. Here, we show that transforming growth factor β (TGF-β) signaling is a novel synaptogenic pathway for cortical neurons induced by murine and human astrocytes. By combining gain and loss of function approaches, we show that TGF-β1 induces the formation of functional synapses in mice. Further, TGF-β1-induced synaptogenesis involves neuronal activity and secretion of the co-agonist of the NMDA receptor, d-serine. Manipulation of d-serine signaling, by either genetic or pharmacological inhibition, prevented the TGF-β1 synaptogenic effect. Our data show a novel molecular mechanism that might impact synaptic function and emphasize the evolutionary aspect of the synaptogenic property of astrocytes, thus shedding light on new potential therapeutic targets for synaptic deficit diseases.     

Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?

Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.