Synaptic Plasticity Enables Adaptive Self-Tuning Critical Networks

During rest, the mammalian cortex displays spontaneous neural activity. Spiking of single neurons during rest has been described as irregular and asynchronous. In contrast, recent in vivo and in vitro population measures of spontaneous activity, using the LFP, EEG, MEG or fMRI suggest that the default state of the cortex is critical, manifested by spontaneous, scale-invariant, cascades of activity known as neuronal avalanches. Criticality keeps a network poised for optimal information processing, but this view seems to be difficult to reconcile with apparently irregular single neuron spiking. Here, we simulate a 10,000 neuron, deterministic, plastic network of spiking neurons. We show that a combination of short- and long-term synaptic plasticity enables these networks to exhibit criticality in the face of intrinsic, i.e. self-sustained, asynchronous spiking. Brief external perturbations lead to adaptive, long-term modification of intrinsic network connectivity through long-term excitatory plasticity, whereas long-term inhibitory plasticity enables rapid self-tuning of the network back to a critical state. The critical state is characterized by a branching parameter oscillating around unity, a critical exponent close to -3/2 and a long tail distribution of a self-similarity parameter between 0.5 and 1.     

Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector

Hebbian changes of excitatory synapses are driven by and further enhance correlations between pre- and postsynaptic activities. Hence, Hebbian plasticity forms a positive feedback loop that can lead to instability in simulated neural networks. To keep activity at healthy, low levels, plasticity must therefore incorporate homeostatic control mechanisms. We find in numerical simulations of recurrent networks with a realistic triplet-based spike-timing-dependent plasticity rule (triplet STDP) that homeostasis has to detect rate changes on a timescale of seconds to minutes to keep the activity stable. We confirm this result in a generic mean-field formulation of network activity and homeostatic plasticity. Our results strongly suggest the existence of a homeostatic regulatory mechanism that reacts to firing rate changes on the order of seconds to minutes.     

Self-organization in Balanced State Networks by STDP and Homeostatic Plasticity

Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a balanced neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network.     

SynGAP Regulates Protein Synthesis and Homeostatic Synaptic Plasticity in Developing Cortical Networks

Disrupting the balance between excitatory and inhibitory neurotransmission in the developing brain has been causally linked with intellectual disability (ID) and autism spectrum disorders (ASD). Excitatory synapse strength is regulated in the central nervous system by controlling the number of postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs). De novo genetic mutations of the synaptic GTPase-activating protein (SynGAP) are associated with ID and ASD. SynGAP is enriched at excitatory synapses and genetic suppression of SynGAP increases excitatory synaptic strength. However, exactly how SynGAP acts to maintain synaptic AMPAR content is unclear. We show here that SynGAP limits excitatory synaptic strength, in part, by suppressing protein synthesis in cortical neurons. The data presented here from in vitro, rat and mouse cortical networks, demonstrate that regulation of translation by SynGAP involves ERK, mTOR, and the small GTP-binding protein Rheb. Furthermore, these data show that GluN2B-containing NMDARs and the cognitive kinase CaMKII act upstream of SynGAP and that this signaling cascade is required for proper translation-dependent homeostatic synaptic plasticity of excitatory synapses in developing cortical networks.     

Signaling Pathways Involved in Striatal Synaptic Plasticity are Sensitive to Temporal Pattern and Exhibit Spatial Specificity

The basal ganglia is a brain region critically involved in reinforcement learning and motor control. Synaptic plasticity in the striatum of the basal ganglia is a cellular mechanism implicated in learning and neuronal information processing. Therefore, understanding how different spatio-temporal patterns of synaptic input select for different types of plasticity is key to understanding learning mechanisms. In striatal medium spiny projection neurons (MSPN), both long term potentiation (LTP) and long term depression (LTD) require an elevation in intracellular calcium concentration; however, it is unknown how the post-synaptic neuron discriminates between different patterns of calcium influx. Using computer modeling, we investigate the hypothesis that temporal pattern of stimulation can select for either endocannabinoid production (for LTD) or protein kinase C (PKC) activation (for LTP) in striatal MSPNs. We implement a stochastic model of the post-synaptic signaling pathways in a dendrite with one or more diffusionally coupled spines. The model is validated by comparison to experiments measuring endocannabinoid-dependent depolarization induced suppression of inhibition. Using the validated model, simulations demonstrate that theta burst stimulation, which produces LTP, increases the activation of PKC as compared to 20 Hz stimulation, which produces LTD. The model prediction that PKC activation is required for theta burst LTP is confirmed experimentally. Using the ratio of PKC to endocannabinoid production as an index of plasticity direction, model simulations demonstrate that LTP exhibits spine level spatial specificity, whereas LTD is more diffuse. These results suggest that spatio-temporal control of striatal information processing employs these Gq coupled pathways.     

AMPA受体的磷酸化与突触可塑性

突触可塑性在学习记忆中发挥了重要作用,AMPA(α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid,AMPA)受体功能和运输的调节是突触可塑性机制研究的重要环节。在突触可塑性发生过程中,激酶和磷酸酶能够调节AMPA受体C末端的磷酸化水平,进而影响AMPA受体运输。对于AMPA受体磷酸化的研究能够加深我们对突触可塑性机制的理解。     

Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites

In the last decade dendrites of cortical neurons have been shown to nonlinearly combine synaptic inputs by evoking local dendritic spikes. It has been suggested that these nonlinearities raise the computational power of a single neuron, making it comparable to a 2-layer network of point neurons. But how these nonlinearities can be incorporated into the synaptic plasticity to optimally support learning remains unclear. We present a theoretically derived synaptic plasticity rule for supervised and reinforcement learning that depends on the timing of the presynaptic, the dendritic and the postsynaptic spikes. For supervised learning, the rule can be seen as a biological version of the classical error-backpropagation algorithm applied to the dendritic case. When modulated by a delayed reward signal, the same plasticity is shown to maximize the expected reward in reinforcement learning for various coding scenarios. Our framework makes specific experimental predictions and highlights the unique advantage of active dendrites for implementing powerful synaptic plasticity rules that have access to downstream information via backpropagation of action potentials.     

Coordination of Protein Phosphorylation and Dephosphorylation in Synaptic Plasticity

A central theme in nervous system function is equilibrium: synaptic strengths wax and wane, neuronal firing rates adjust up and down, and neural circuits balance excitation with inhibition. This push/pull regulatory theme carries through to the molecular level at excitatory synapses, where protein function is controlled through phosphorylation and dephosphorylation by kinases and phosphatases. However, these opposing enzymatic activities are only part of the equation as scaffolding interactions and assembly of multi-protein complexes are further required for efficient, localized synaptic signaling. This review will focus on coordination of postsynaptic serine/threonine kinase and phosphatase signaling by scaffold proteins during synaptic plasticity.     

Structural Components of Synaptic Plasticity and Memory Consolidation

Consolidation of implicit memory in the invertebrate Aplysia and explicit memory in the mammalian hippocampus are associated with remodeling and growth of preexisting synapses and the formation of new synapses. Here, we compare and contrast structural components of the synaptic plasticity that underlies these two distinct forms of memory. In both cases, the structural changes involve time-dependent processes. Thus, some modifications are transient and may contribute to early formative stages of long-term memory, whereas others are more stable, longer lasting, and likely to confer persistence to memory storage. In addition, we explore the possibility that trans-synaptic signaling mechanisms governing de novo synapse formation during development can be reused in the adult for the purposes of structural synaptic plasticity and memory storage. Finally, we discuss how these mechanisms set in motion structural rearrangements that prepare a synapse to strengthen the same memory and, perhaps, to allow it to take part in other memories as a basis for understanding how their anatomical representation results in the enhanced expression and storage of memories in the brain.Santiago Ramón y Cajal (1894) used the insights provided by his remarkable light microscopic observations of neurons selectively stained with the Golgi method to propose the first cellular theory of memory storage as an anatomical change in the functional connections between nerve cells, later called synapses (Sherrington 1897). For most of the last century, chemical synapses were thought to convey information in only one direction—from the presynaptic to the postsynaptic neuron. It now is clear that synaptic transmission is a bidirectional and self-modifiable form of cell–cell communication (Peters et al. 1976; Jessell and Kandel 1993). This appreciation of reciprocal signaling between pre- and postsynaptic elements is consistent with other forms of intercellular communication and provides a conceptual framework for understanding memory-induced changes in the structure of the synapse. Indeed, an increasing body of evidence suggests that trans-synaptic signaling and coordinated recruitment of pre- and postsynaptic mechanisms underlie consolidation of both implicit and explicit forms of memory storage (Marrone 2005; Hawkins et al. 2006; Bailey et al. 2008).Studies in a variety of systems have found that molecular mechanisms of consolidation and long-term storage of memory begin at the level of the synapse. Existing proteins are modified, signals are sent back to the nucleus so that specific genes are expressed, and gene products are transported back to the synapse where the local synthesis of new protein is triggered to allow for the remodeling, addition, and elimination of synapses (Bailey and Kandel 1985; Bailey et al. 1996; Kandel 2001; Bourne and Harris 2008, 2012). These structural components of synaptic plasticity are thought to represent a cellular change that contributes to both implicit and explicit memory consolidation (Greenough and Bailey 1988; Bailey and Kandel 1993; Bailey et al. 2005; Bourne and Harris 2008, 2012). The association between alterations in the structure and/or number of synapses and memory storage has led to numerous studies regarding the signaling pathways that might couple molecular changes to structural changes. In addition, parallel homeostatic mechanisms have been identified that can trigger synaptic scaling, which serves to stabilize the strengthened synapses while weakening or eliminating other synapses, thus providing specificity during memory consolidation (Bourne and Harris 2011; Schacher and Hu 2014).In this review, we compare and contrast structural changes at the synapse during both implicit and explicit memory consolidation, as well as the molecular signaling pathways that initiate the learning-induced structural changes versus those that serve to maintain these changes over time. Toward that end, we will focus on two experimental model systems and several prototypic forms of synaptic plasticity that we have worked on and that have been extensively studied as representative examples of memory storage: long-term habituation and sensitization of the gill-withdrawal reflex in Aplysia. These are examples of implicit memory consolidation and hippocampal-based long-term potentiation (LTP) and long-term depression (LTD), as candidate mechanisms for the synaptic plasticity underlying explicit memory storage in mammals. These will serve as useful points of comparison to consider similarities, differences, and still-existing limitations in our understanding of the functional significance of the structural synaptic plasticity recruited during the consolidation of both implicit and explicit forms of memory.     

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.     

Inflammation Subverts Hippocampal Synaptic Plasticity in Experimental Multiple Sclerosis

Abnormal use-dependent synaptic plasticity is universally accepted as the main physiological correlate of memory deficits in neurodegenerative disorders. It is unclear whether synaptic plasticity deficits take place during neuroinflammatory diseases, such as multiple sclerosis (MS) and its mouse model, experimental autoimmune encephalomyelitis (EAE). In EAE mice, we found significant alterations of synaptic plasticity rules in the hippocampus. When compared to control mice, in fact, hippocampal long-term potentiation (LTP) induction was favored over long-term depression (LTD) in EAE, as shown by a significant rightward shift in the frequency–synaptic response function. Notably, LTP induction was also enhanced in hippocampal slices from control mice following interleukin-1β (IL-1β) perfusion, and both EAE and IL-1β inhibited GABAergic spontaneous inhibitory postsynaptic currents (sIPSC) without affecting glutamatergic transmission and AMPA/NMDA ratio. EAE was also associated with selective loss of GABAergic interneurons and with reduced gamma-frequency oscillations in the CA1 region of the hippocampus. Finally, we provided evidence that microglial activation in the EAE hippocampus was associated with IL-1β expression, and hippocampal slices from control mice incubated with activated microglia displayed alterations of GABAergic transmission similar to those seen in EAE brains, through a mechanism dependent on enhanced IL-1β signaling. These data may yield novel insights into the basis of cognitive deficits in EAE and possibly of MS.     

Synaptic Vesicle Proteins and Neuronal Plasticity in Adrenergic Neurons

The neurons in the superior cervical ganglion are active in plasticity and re-modelling in order to adapt to requirements. However, so far, only a few studies dealing with synaptic vesicle related proteins during adaptive processes have been published. In the present paper, changes in content and expression of the synaptic vesicle related proteins in the neurons after decentralization (cutting the cervical sympathetic trunk) or axotomy (cutting the internal and external carotid nerves) were studied. Immunofluorescence studies were carried out using antibodies and antisera against integral membrane proteins, vesicle associated proteins, NPY, and the enzymes TH and PNMT. For colocalization studies, the sections were simultaneously double labelled. Confocal laser scanning microscopy was used for colocalization studies as well as for semi-quantification analysis, using the computer software. Westen blot analysis, in situ 3'-end DNA labelling, and in situ hybridization were also employed. After decentralization of the ganglia several of the synaptic vesicle proteins (synaptotagmin I, synaptophysin, SNAP-25, CLC and GAP-43) were increased in the iris nerve terminal network, but with different time patterns, while TH-immunoreactivity had clearly decreased. In the ganglia, these proteins had decreased at 1 day after decentralization, probably due to degeneration of the pre-ganglionic nerve fibres and terminals. At later intervals, these proteins, except SNAP-25, had increased in the nerve fibre bundles and re-appeared in nerve fibres outlining the principal neurons.     

Regulation of AMPA Receptor Activity, Synaptic Targeting and Recycling: Role in Synaptic Plasticity

The alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors for the neurotransmitter glutamate are oligomeric structures responsible for most fast excitatory responses in the central nervous system. The activity of AMPA receptors can be directly regulated by protein phosphorylation, which may also affect the interaction with intracellular proteins and, consequently, their recycling and localization to defined postsynaptic sites. This review focuses on recent advances in understanding the dynamic regulation of AMPA receptors, on a short- and long-term basis, and its implications in synaptic plasticity.     

Thematic Minireview Series: Molecular Mechanisms of Synaptic Plasticity

The human brain contains ∼86 billion neurons, which are precisely organized in specific brain regions and nuclei. High fidelity synaptic communication between subsets of neurons in specific circuits is required for most human behaviors, and is often disrupted in neuropsychiatric disorders. The presynaptic axon terminals of one neuron release neurotransmitters that activate receptors on multiple postsynaptic neuron targets to induce electrical and chemical responses. Typically, postsynaptic neurons integrate signals from multiple presynaptic neurons at thousands of synaptic inputs to control downstream communication to the next neuron in the circuit. Importantly, the strength (or efficiency) of signal transmission at each synapse can be modulated on time scales ranging up to the lifetime of the organism. This “synaptic plasticity” leads to changes in overall neuronal circuit activity, resulting in behavioral modifications. This series of minireviews will focus on recent advances in our understanding of the molecular and cellular mechanisms that control synaptic plasticity.     

Proteolytic Remodeling of the Synaptic Cell Adhesion Molecules (CAMs) by Metzincins in Synaptic Plasticity

Cell adhesion molecules participate in the formation, maturation, function and plasticity of synaptic connections. The growing body of evidence indicates that in the regulation of the synaptic plasticity, in which these molecules play pivotal role, also the proteolytic processes are involved. This review focuses on extracellular proteolysis of the cell adhesion molecules by specific subgroup of the matrix metalloproteinases, a disintegrin and metalloproteases and a disintegrin and metalloproteinase with thrombospondin motifs, jointly referred to as metzincins, in driving coordinated synaptic structural and functional modifications underlying synaptic plasticity in the adult brain.     

Modulation of Hippocampus-Dependent Learning and Synaptic Plasticity by Nicotine

A long-standing relationship between nicotinic acetylcholine receptors (nAChRs) and cognition exists. Drugs that act at nAChRs can have cognitive-enhancing effects and diseases that disrupt cognition such as Alzheimer's disease and schizophrenia are associated with altered nAChR function. Specifically, hippocampus-dependent learning is particularly sensitive to the effects of nicotine. However, the effects of nicotine on hippocampus-dependent learning vary not only with the doses of nicotine used and whether nicotine is administered acutely, chronically, or withdrawn after chronic nicotine treatment but also vary across different hippocampus-dependent tasks such as the Morris water maze, the radial arm maze, and contextual fear conditioning. In addition, nicotine has variable effects across different types of hippocampal long-term potentiation (LTP). Because different types of hippocampus-dependent learning and LTP involve different neural and molecular substrates, comparing the effects of nicotine across these paradigms can yield insights into the mechanisms that may underlie the effects of nicotine on learning and memory and aid in understanding the variable effects of nicotine on cognitive processes. This review compares and contrasts the effects of nicotine on hippocampus-dependent learning and LTP and briefly discusses how the effects of nicotine on learning could contribute to nicotine addiction.