Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell

The rules of synaptic integration in pyramidal cells remain obscure, in part due to conflicting interpretations of existing experimental data. To clarify issues, we developed a CA1 pyramidal cell model calibrated with a broad spectrum of in vitro data. Using simultaneous dendritic and somatic recordings and combining results for two different response measures (peak versus mean EPSP), two different stimulus formats (single shock versus 50 Hz trains), and two different spatial integration conditions (within versus between-branch summation), we found that the cell's subthreshold responses to paired inputs are best described as a sum of nonlinear subunit responses, where the subunits correspond to different dendritic branches. In addition to suggesting a new type of experiment and providing testable predictions, our model shows how conclusions regarding synaptic arithmetic can be influenced by an array of seemingly innocuous experimental design choices.     

Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model

In vivo, cortical pyramidal cells are bombarded by asynchronous synaptic input arising from ongoing network activity. However, little is known about how such ‘background’ synaptic input interacts with nonlinear dendritic mechanisms. We have modified an existing model of a layer 5 (L5) pyramidal cell to explore how dendritic integration in the apical dendritic tuft could be altered by the levels of network activity observed in vivo. Here we show that asynchronous background excitatory input increases neuronal gain and extends both temporal and spatial integration of stimulus-evoked synaptic input onto the dendritic tuft. Addition of fast and slow inhibitory synaptic conductances, with properties similar to those from dendritic targeting interneurons, that provided a ‘balanced’ background configuration, partially counteracted these effects, suggesting that inhibition can tune spatio-temporal integration in the tuft. Excitatory background input lowered the threshold for NMDA receptor-mediated dendritic spikes, extended their duration and increased the probability of additional regenerative events occurring in neighbouring branches. These effects were also observed in a passive model where all the non-synaptic voltage-gated conductances were removed. Our results show that glutamate-bound NMDA receptors arising from ongoing network activity can provide a powerful spatially distributed nonlinear dendritic conductance. This may enable L5 pyramidal cells to change their integrative properties as a function of local network activity, potentially allowing both clustered and spatially distributed synaptic inputs to be integrated over extended timescales.     

Signal integration on the dendrites of a pyramidal neuron model

This paper studied the synaptic and dendritic integration with different spatial distributions of synapses on the dendrites of a biophysically-detailed layer 5 pyramidal neuron model. It has been observed that temporally synchronous and spatially clustered synaptic inputs make dendrites perform a highly nonlinear integration. The effect of clustering degree of synaptic distribution on neuronal responsiveness is investigated by changing the number of top apical dendrites where active synapses are allocated. The neuron shows maximum responsiveness to synaptic inputs which have an intermediate clustering degree of spatial distribution, indicating complex interactions among dendrites with the existence of nonlinear synaptic and dendritic integrations.     

NMDA receptor-mediated dendritic spikes and coincident signal amplification

Dendrites of cortical neurons possess active conductances, which contribute to the nonlinear processing of synaptic information. Recently it has been shown that basal dendrites can generate highly localized spikes mediated by NMDA receptor channels. These spikes may serve as a powerful mechanism to detect and amplify synchronously activated spatially clustered excitatory synaptic inputs in individual dendritic segments, and may enable parallel processing in several integrative dendritic subunits.     

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks

Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns.     

Computational roles of intrinsic synaptic dynamics

Conventional theories assume that long-term information storage in the brain is implemented by modifying synaptic efficacy. Recent experimental findings challenge this view by demonstrating that dendritic spine sizes, or their corresponding synaptic weights, are highly volatile even in the absence of neural activity. Here, we review previous computational works on the roles of these intrinsic synaptic dynamics. We first present the possibility for neuronal networks to sustain stable performance in their presence, and we then hypothesize that intrinsic dynamics could be more than mere noise to withstand, but they may improve information processing in the brain.     

Dependence of Transformation of Intrinsic Rhythmic Impulse Activity of Neurons on Spatio-Temporal Organization of Synaptic Actions on Dendrites: A Simulation Study

The aim of the study to elucidate the biophysical mechanisms able to determine specific transformations of the patterns of output signals of neurons (neuronal impulse codes) depending on the spatio-temporal organization of synaptic actions coming to the dendrites. We studied mathematical models of the neocortical layer 5 pyramidal neurons built according to the results of computer reconstruction of their dendritic arborizations and experimental data on the voltage-dependent conductivities of their dendritic membrane. This work is a continuation of our previous studies that showed the existence of certain relations between the complexity of neural impulse codes, on the one hand, and the complexity, size, metrical asymmetry of branching, and nonlinear membrane properties of the dendrites, on the other hand. This relation determines synchronous (with some phase shifts) or asynchronous transitions of asymmetrical dendritic subtrees between high and low depolarization states during the generation of output impulse patterns in response to distributed tonic activation of dendritic inputs. In this work we demonstrate the first time that the appearance and pattern of transformations of complex periodical impulse trains at the neuron’s output associated with receiving a short series of presynaptic action potentials are determined not only by the time of arrival of such a series, but also by their spatial addressing to asymmetric dendritic subtrees; the latter, in this case, may be in the same (synchronous transitions) or different (asynchronous transitions) electrical states. Biophysically, this phenomenon is based on a significant excess of the driving potential for a synaptic excitatory current in low-depolarization regions, as compared with that in high-depolarization dendritic regions receiving phasic synaptic stimuli. These findings open a novel aspect of the functioning of neurons and neuronal networks.     

The dual role of the extracellular matrix in synaptic plasticity and homeostasis

Recent studies have deepened our understanding of multiple mechanisms by which extracellular matrix (ECM) molecules regulate various aspects of synaptic plasticity and have strengthened a link between the ECM and learning and memory. New findings also support the view that the ECM is important for homeostatic processes, such as scaling of synaptic responses, metaplasticity and stabilization of synaptic connectivity. Activity-dependent modification of the ECM affects the formation of dendritic filopodia and the growth of dendritic spines. Thus, the ECM has a dual role as a promoter of structural and functional plasticity and as a degradable stabilizer of neural microcircuits. Both of these aspects are likely to be important for mental health.     

A peptide mimetic targeting trans-homophilic NCAM binding sites promotes spatial learning and neural plasticity in the hippocampus

The key roles played by the neural cell adhesion molecule (NCAM) in plasticity and cognition underscore this membrane protein as a relevant target to develop cognitive-enhancing drugs. However, NCAM is a structurally and functionally complex molecule with multiple domains engaged in a variety of actions, which raise the question as to which NCAM fragment should be targeted. Synthetic NCAM mimetic peptides that mimic NCAM sequences relevant to specific interactions allow identification of the most promising targets within NCAM. Recently, a decapeptide ligand of NCAM--plannexin, which mimics a homophilic trans-binding site in Ig2 and binds to Ig3--was developed as a tool for studying NCAM's trans-interactions. In this study, we investigated plannexin's ability to affect neural plasticity and memory formation. We found that plannexin facilitates neurite outgrowth in primary hippocampal neuronal cultures and improves spatial learning in rats, both under basal conditions and under conditions involving a deficit in a key plasticity-promoting posttranslational modification of NCAM, its polysialylation. We also found that plannexin enhances excitatory synaptic transmission in hippocampal area CA1, where it also increases the number of mushroom spines and the synaptic expression of the AMPAR subunits GluA1 and GluA2. Altogether, these findings provide compelling evidence that plannexin is an important facilitator of synaptic functional, structural and molecular plasticity in the hippocampal CA1 region, highlighting the fragment in NCAM's Ig3 module where plannexin binds as a novel target for the development of cognition-enhancing drugs.     

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.     

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.     

Calmodulin-dependent protein kinase II

One of the most important mechanisms for regulating neuronal functions is through second messenger cascades that control protein kinases and the subsequent phosphorylation of substrate proteins. Ca2+/calmodulin-dependent protein kinase II (CaM-kinase II) is the most abundant protein kinase in mammalian brain tissues, and the alpha-subunit of this kinase is the major protein and enzymatic molecule of synaptic junctions in many brain regions. CaM-kinase II regulates itself through a complex autophosphorylation mechanism whereby it becomes calcium-independent following its initial activation. This property has implicated CaM-kinase II as a potential molecular switch at central nervous system (CNS) synapses. Recent studies have suggested that CaM-kinase II is involved in many diverse phenomena such as epilepsy, sensory deprivation, ischemia, synapse formation, synaptic transmission, long-term potentiation, learning, and memory. During brain development, the expression of CaM-kinase II at both protein and mRNA levels coincides with the active periods of synapse formation and, therefore, factors regulating the genes encoding kinase subunits may play a role in the cell-to-cell recognition events that underlie neuronal differentiation and the establishment of mature synaptic functions. Recent findings have demonstrated that the mRNA encoding the alpha-subunit of CaM-kinase II is localized in neuronal dendrites. Current speculation suggests that the localized translation of dendritic mRNAs encoding specific synaptic proteins may be responsible for producing synapse-specific changes associated with the processing, storage, and retrieval of information in neural networks.     

Linking Macroscopic with Microscopic Neuroanatomy Using Synthetic Neuronal Populations

Dendritic morphology has been shown to have a dramatic impact on neuronal function. However, population features such as the inherent variability in dendritic morphology between cells belonging to the same neuronal type are often overlooked when studying computation in neural networks. While detailed models for morphology and electrophysiology exist for many types of single neurons, the role of detailed single cell morphology in the population has not been studied quantitatively or computationally. Here we use the structural context of the neural tissue in which dendritic trees exist to drive their generation in silico. We synthesize the entire population of dentate gyrus granule cells, the most numerous cell type in the hippocampus, by growing their dendritic trees within their characteristic dendritic fields bounded by the realistic structural context of (1) the granule cell layer that contains all somata and (2) the molecular layer that contains the dendritic forest. This process enables branching statistics to be linked to larger scale neuroanatomical features. We find large differences in dendritic total length and individual path length measures as a function of location in the dentate gyrus and of somatic depth in the granule cell layer. We also predict the number of unique granule cell dendrites invading a given volume in the molecular layer. This work enables the complete population-level study of morphological properties and provides a framework to develop complex and realistic neural network models.     

Activity-dependent dendritic spine structural plasticity is regulated by small GTPase Rap1 and its target AF-6

Activity-dependent remodeling of dendritic spines is essential for neural circuit development and synaptic plasticity, but the mechanisms that coordinate synaptic structural and functional plasticity are not well understood. Here we investigate the signaling pathways that enable excitatory synapses to undergo activity-dependent structural modifications. We report that activation of NMDA receptors in cultured cortical neurons induces spine morphogenesis and activation of the small GTPase Rap1. Rap1 bimodally regulates spine morphology: activated Rap1 recruits the PDZ domain-containing protein AF-6 to the plasma membrane and induces spine neck elongation, while inactive Rap1 dissociates AF-6 from the membrane and induces spine enlargement. Rap1 also regulates spine content of AMPA receptors: thin spines induced by Rap1 activation have reduced GluR1-containing AMPA receptor content, while large spines induced by Rap1 inactivation are rich in AMPA receptors. These results identify a signaling pathway that regulates activity-dependent synaptic structural plasticity and coordinates it with functional plasticity.     

Structural basis of neurohormonal control of gastric secretory activity

Distances between neural, endocrinal and working cells in the gastric wall tissue do not exceed some hundreds nm, i. e. they are within limits of the physiological parameters for the effect of biologically active substances diffusely spreading along the interstitium. A structural scheme of the neurohormonal regulatory mechanism is suggested, basing on the author's data and those of the literature. Combination of producer-mediator-cells and target-cells united by the interstitial gap, along which biologically active substances are transported, serves as its base. Mast cells--mobile endocrinic glands--and neural terminals of various modality may serve as a source for changing the modulatory tonus in the given tissue area. The cells producing mediators (neural and endocrine) are, in their turn, target-cells for other biologically active substances getting into the interstitium. The whole structure can be compared with the synaptic system, where the membranes of the producer-mediator-cells serve as the presynaptic pole, while the membranes of the target-cells play the role of the postsynaptic pole. The interstitial gap performes the part of the synaptic gap. In this peculiar diffuse synapse, the membranes of neural and endocrine cells serve as pre- and postsynaptic membranes simultaneously.     

Afadin Is Required for Maintenance of Dendritic Structure and Excitatory Tone

The dendritic field of a neuron, which is determined by both dendritic architecture and synaptic strength, defines the synaptic input of a cell. Once established, a neuron''s dendritic field is thought to remain relatively stable throughout a cell''s lifetime. Perturbations in a dendritic structure or excitatory tone of a cell and thus its dendritic field are cellular alterations thought to be correlated with a number of psychiatric disorders. Although several proteins are known to regulate the development of dendritic arborization, much less is known about the mechanisms that maintain dendritic morphology and synaptic strength. In this study, we find that afadin, a component of N-cadherin·β-catenin·α-N-catenin adhesion complexes, is required for the maintenance of established dendritic arborization and synapse number. We further demonstrate that afadin directly interacts with AMPA receptors and that loss of this protein reduces the surface expression of GluA1- and GluA2-AMPA receptor subunits. Collectively, these data suggest that afadin is required for the maintenance of dendritic structure and excitatory tone.     

MiR‐134‐dependent regulation of Pumilio‐2 is necessary for homeostatic synaptic depression

Neurons employ a set of homeostatic plasticity mechanisms to counterbalance altered levels of network activity. The molecular mechanisms underlying homeostatic plasticity in response to increased network excitability are still poorly understood. Here, we describe a sequential homeostatic synaptic depression mechanism in primary hippocampal neurons involving miRNA‐dependent translational regulation. This mechanism consists of an initial phase of synapse elimination followed by a reinforcing phase of synaptic downscaling. The activity‐regulated microRNA miR‐134 is necessary for both synapse elimination and the structural rearrangements leading to synaptic downscaling. Results from miR‐134 inhibition further uncover a differential requirement for GluA1/2 subunits for the functional expression of homeostatic synaptic depression. Downregulation of the miR‐134 target Pumilio‐2 in response to chronic activity, which selectively occurs in the synapto‐dendritic compartment, is required for miR‐134‐mediated homeostatic synaptic depression. We further identified polo‐like kinase 2 (Plk2) as a novel target of Pumilio‐2 involved in the control of GluA2 surface expression. In summary, we have described a novel pathway of homeostatic plasticity that stabilizes neuronal circuits in response to increased network activity.     

Structural homeostasis: compensatory adjustments of dendritic arbor geometry in response to variations of synaptic input

As the nervous system develops, there is an inherent variability in the connections formed between differentiating neurons. Despite this variability, neural circuits form that are functional and remarkably robust. One way in which neurons deal with variability in their inputs is through compensatory, homeostatic changes in their electrical properties. Here, we show that neurons also make compensatory adjustments to their structure. We analysed the development of dendrites on an identified central neuron (aCC) in the late Drosophila embryo at the stage when it receives its first connections and first becomes electrically active. At the same time, we charted the distribution of presynaptic sites on the developing postsynaptic arbor. Genetic manipulations of the presynaptic partners demonstrate that the postsynaptic dendritic arbor adjusts its growth to compensate for changes in the activity and density of synaptic sites. Blocking the synthesis or evoked release of presynaptic neurotransmitter results in greater dendritic extension. Conversely, an increase in the density of presynaptic release sites induces a reduction in the extent of the dendritic arbor. These growth adjustments occur locally in the arbor and are the result of the promotion or inhibition of growth of neurites in the proximity of presynaptic sites. We provide evidence that suggest a role for the postsynaptic activity state of protein kinase A in mediating this structural adjustment, which modifies dendritic growth in response to synaptic activity. These findings suggest that the dendritic arbor, at least during early stages of connectivity, behaves as a homeostatic device that adjusts its size and geometry to the level and the distribution of input received. The growing arbor thus counterbalances naturally occurring variations in synaptic density and activity so as to ensure that an appropriate level of input is achieved.     

Neurons and their synaptic organization in the visual cortex of the rat

Summary Cells in the visual cortex (area 17) of adult rats were impregnated by the rapid Golgi method and characterized by light microscopy. Selected cells were then sectioned for electron microscopy and their cytological characteristics and the pattern of synapses on their cell bodies and dendrites were studied Twelve classical pyramidal cells from layers II–VI, two pyramid-like cells from layer VI, two inverted pyramidal cells from layers V and VI, ten spine-free non-pyramidal cells from layers II–VI and two spinous non-pyramidal cells from layer IV were examined.The cytoplasmic features of the identified cells, where these could be discerned, corresponded to those previously reported for the different cell types in conventionally prepared tissue. Pyramidal Cells received exclusively type 2 synaptic contacts on their cell bodies, type 1 contacts on their dendritic spines and a mixture of synaptic types (type II predominating) on their shafts, where synaptic density was relatively low. This pattern of synaptic contacts was consistent for all portions of the dendritic tree; inverted pyramidal cells and pyramid-like cells showed the same synaptic organization as classical pyramids. The axon collaterals of pyramidal cells established type I contacts with dendritic spines (or, rarely, shafts) of unknown origin. Non-Pyramidal Cells received both type 1 and type 2 contacts (the former predominating) on their cell bodies and dendrites. The spinous variety also received type I contacts on their dendritic spines. Axon terminal of spine-free non-pyramidal cells established type II synaptic contacts with dendritic shafts of unknown origin. The similarity in synaptic organization between the spine-free and spinous non-pyramidal cells examined in this study suggest that the latter correspond to the sparsely spinous stellate cells rather than to the spinous stellate cells of cat and monkey visual cortex.We thank the Medical Research Council for financial support     

β-adducin (Add2) KO mice show synaptic plasticity, motor coordination and behavioral deficits accompanied by changes in the expression and phosphorylation levels of the α- and γ-adducin subunits

Adducins are a family of proteins found in cytoskeleton junctional complexes, which bind and regulate actin filaments and actin-spectrin complexes. In brain, adducin is expressed at high levels and is identified as a constituent of synaptic structures, such as dendritic spines and growth cones of neurons. Adducin-induced changes in dendritic spines are involved in activity-dependent synaptic plasticity processes associated with learning and memory, but the mechanisms underlying these functions remain to be elucidated. Here, β-adducin knockout (KO) mice were used to obtain a deeper insight into the role of adducin in these processes. We showed that β-adducin KO mice showed behavioral, motor coordination and learning deficits together with an altered expression and/or phosphorylation levels of α-adducin and γ-adducin. We found that β-adducin KO mice exhibited deficits in learning and motor performances associated with an impairment of long-term potentiation (LTP) and long-term depression (LTD) in the hippocampus. These effects were accompanied by a decrease in phosphorylation of adducin, a reduction in α-adducin expression levels and upregulation of γ-adducin in hippocampus, cerebellum and neocortex of mutant mice. In addition, we found that the mRNA encoding β-adducin is also located in dendrites, where it may participate in the fine modulation of LTP and LTD. These results strongly suggest coordinated expression and phosphorylation of adducin subunits as a key mechanism underlying synaptic plasticity, motor coordination performance and learning behaviors.