The dynamical stability of reverberatory neural circuits

The concept of reverberation proposed by Lorente de Nó and Hebb is key to understanding strongly recurrent cortical networks. In particular, synaptic reverberation is now viewed as a likely mechanism for the active maintenance of working memory in the prefrontal cortex. Theoretically, this has spurred a debate as to how such a potentially explosive mechanism can provide stable working-memory function given the synaptic and cellular mechanisms at play in the cerebral cortex. We present here new evidence for the participation of NMDA receptors in the stabilization of persistent delay activity in a biophysical network model of conductance-based neurons. We show that the stability of working-memory function, and the required NMDA/AMPA ratio at recurrent excitatory synapses, depend on physiological properties of neurons and synaptic interactions, such as the time constants of excitation and inhibition, mutual inhibition between interneurons, differential NMDA receptor participation at excitatory projections to pyramidal neurons and interneurons, or the presence of slow intrinsic ion currents in pyramidal neurons. We review other mechanisms proposed to enhance the dynamical stability of synaptically generated attractor states of a reverberatory circuit. This recent work represents a necessary and significant step towards testing attractor network models by cortical electrophysiology.     

A hemicord locomotor network of excitatory interneurons: a simulation study

Locomotor burst generation is simulated using a full-scale network model of the unilateral excitatory interneuronal population. Earlier small-scale models predicted that a population of excitatory neurons would be sufficient to produce burst activity, and this has recently been experimentally confirmed. Here we simulate the hemicord activity induced under various experimental conditions, including pharmacological activation by NMDA and AMPA as well as electrical stimulation. The model network comprises a realistic number of cells and synaptic connectivity patterns. Using similar distributions of cellular and synaptic parameters, as have been estimated experimentally, a large variation in dynamic characteristics like firing rates, burst, and cycle durations were seen in single cells. On the network level an overall rhythm was generated because the synaptic interactions cause partial synchronization within the population. This network rhythm not only emerged despite the distributed cellular parameters but relied on this variability, in particular, in reproducing variations of the activity during the cycle and showing recruitment in interneuronal populations. A slow rhythm (0.4–2 Hz) can be induced by tonic activation of NMDA-sensitive channels, which are voltage dependent and generate depolarizing plateaus. The rhythm emerges through a synchronization of bursts of the individual neurons. A fast rhythm (4–12 Hz), induced by AMPA, relies on spike synchronization within the population, and each burst is composed of single spikes produced by different neurons. The dynamic range of the fast rhythm is limited by the ability of the network to synchronize oscillations and depends on the strength of synaptic connections and the duration of the slow after hyperpolarization. The model network also produces prolonged bouts of rhythmic activity in response to brief electrical activations, as seen experimentally. The mutual excitation can sustain long-lasting activity for a realistic set of synaptic parameters. The bout duration depends on the strength of excitatory synaptic connections, the level of persistent depolarization, and the influx of Ca²⁺ ions and activation of Ca²⁺-dependent K⁺ current.     

受体、突触和记忆

大脑中神经元突触间的信号传递是由许多神经递质受体介导的。在过去,Richard L．Huganir实验室一直致力于神经递质受体功能调节的分子机制。而最近,该实验室又聚焦到大脑中一种最主要的兴奋性受体的研究——谷氨酸受体。谷氨酸受体主要可以分为两大类：AMPA受体和NMDA受体。AMPA受体主要介导了快速的兴奋性突触传递;而NMDA受体则在神经可塑性和发育中起到重要作用。实验发现,AMPA受体和NMDA受体都可以被一系列的蛋白激酶磷酸化,而磷酸化的水平则直接影响了这些受体的功能特性,包括通道电导和受体膜定位等。AMPA受体磷酸化的水平同时还在学习和记忆的细胞模型中发生改变,如长时程增强（LTP）和长时程抑制（LTD）。此外,AMPA受体中GluR1亚单位的磷酸化对于各种形式的可塑性以及空间记忆的维持有重要的作用。实验室主要研究突触部位谷氨酸受体在亚细胞水平的定位和聚集的分子机制。最近,一系列可以直接或间接与AMPA和NMDA受体相互作用的蛋白质得以发现,其中包括一个新发现的蛋白家族GRIPs（glutamate receptor interacting proteins）。GRIPs可以直接和AMPA受体的GluR2／3亚单位的C端结合。GRIPs包含7个PDZ结构域,可以介导蛋白与蛋白直接的相互连接,从而把各个AMPA受体交互连接在一起并与其他蛋白相连。另外,GluR2亚单位的c端还可以和兴奋性突触中的蛋白激酶C结合蛋白（PICK1）的PDZ结构域相互作用。另外,GluR2亚单位的C端也可以与一种参与膜融合的蛋白NSF相互作用。这些与AMPA受体相互作用的蛋白质对于受体在膜上的运输以及定位有至关重要的作用。同时,受体与PICK1和GRIP的结合对于小脑运动学习中的LTD有重要作用。总体上说,该实验室发现了一系列可以调节神经递质受体功能的分子机制,这些工作提示受体功能的调节可能是?     

Effects of neuromodulation in a cortical network model of object working memory dominated by recurrent inhibition

Experimental evidence suggests that the maintenance of an item in working memory is achieved through persistent activity in selective neural assemblies of the cortex. To understand the mechanisms underlying this phenomenon, it is essential to investigate how persistent activity is affected by external inputs or neuromodulation. We have addressed these questions using a recurrent network model of object working memory. Recurrence is dominated by inhibition, although persistent activity is generated through recurrent excitation in small subsets of excitatory neurons.Our main findings are as follows. (1) Because of the strong feedback inhibition, persistent activity shows an inverted U shape as a function of increased external drive to the network. (2) A transient external excitation can switch off a network from a selective persistent state to its spontaneous state. (3) The maintenance of the sample stimulus in working memory is not affected by intervening stimuli (distractors) during the delay period, provided the stimulation intensity is not large. On the other hand, if stimulation intensity is large enough, distractors disrupt sample-related persistent activity, and the network is able to maintain a memory only of the last shown stimulus. (4) A concerted modulation of GABA _A and NMDA conductances leads to a decrease of spontaneous activity but an increase of persistent activity; the enhanced signal-to-noise ratio is shown to increase the resistance of the network to distractors. (5) Two mechanisms are identified that produce an inverted U shaped dependence of persistent activity on modulation. The present study therefore points to several mechanisms that enhance the signal-to-noise ratio in working memory states. These mechanisms could be implemented in the prefrontal cortex by dopaminergic projections from the midbrain.     

Rules of engagement: factors that regulate activity-dependent synaptic plasticity during neural network development

Overproduction and pruning during development is a phenomenon that can be observed in the number of organisms in a population, the number of cells in many tissue types, and even the number of synapses on individual neurons. The sculpting of synaptic connections in the brain of a developing organism is guided by its personal experience, which on a neural level translates to specific patterns of activity. Activity-dependent plasticity at glutamatergic synapses is an integral part of neuronal network formation and maturation in developing vertebrate and invertebrate brains. As development of the rodent forebrain transitions away from an over-proliferative state, synaptic plasticity undergoes modification. Late developmental changes in synaptic plasticity signal the establishment of a more stable network and relate to pronounced perceptual and cognitive abilities. In large part, activation of glutamate-sensitive N-methyl-d-aspartate (NMDA) receptors regulates synaptic stabilization during development and is a necessary step in memory formation processes that occur in the forebrain. A developmental change in the subunits that compose NMDA receptors coincides with developmental modifications in synaptic plasticity and cognition, and thus much research in this area focuses on NMDA receptor composition. We propose that there are additional, equally important developmental processes that influence synaptic plasticity, including mechanisms that are upstream (factors that influence NMDA receptors) and downstream (intracellular processes regulated by NMDA receptors) from NMDA receptor activation. The goal of this review is to summarize what is known and what is not well understood about developmental changes in functional plasticity at glutamatergic synapses, and in the end, attempt to relate these changes to maturation of neural networks.     

Comparing fluctuations of synaptic responses mediated via AMPA and NMDA receptor channels--implications for synaptic plasticity

Glutamate-releasing synapses are essential in fast neuronal signalling. Plasticity at these synapses is important for learning and memory as well as for the activity-dependent control of neuronal development. We have evaluated the trial-to-trial fluctuations of excitatory postsynaptic currents mediated by glutamate receptors of the AMPA and NMDA types in CA1 pyramidal cells. By using the whole cell patch clamp technique in brain slices from young rats, we have demonstrated that the relative variability of AMPA and NMDA receptor mediated responses, expressed as the coefficient of variation, is similar for these two types of responses [Brain Res. 800 (1998) 253-259]. The present paper summarizes and discusses these results in relation to current theories on hippocampal synaptic plasticity, especially with regard to the ideas of glutamate spillover and silent synapses. Our finding of a correspondence between AMPA and NMDA responses with respect to fluctuations is compatible with our previous finding of equal relative changes of the two during activity induced synaptic plasticity. However, the results argue against the glutamate spillover model according to which the effect of glutamate--and hence the induction of plasticity--may spread unspecifically between synapses. But how can silent synapses become functional if no spread of glutamate occurs and no initial signal is present to trigger the functionalization? Is it necessary that NMDA responses are present at these synapses, which are then silent merely with respect to AMPA receptors, or do other alternatives exist? Our discussion aims to elucidate these questions.     

Activation of synaptic NMDA receptors induces membrane insertion of new AMPA receptors and LTP in cultured hippocampal neurons

Long-term potentiation (LTP) of excitatory transmission in the hippocampus likely contributes to learning and memory. The mechanisms underlying LTP at these synapses are not well understood, although phosphorylation and redistribution of AMPA receptors may be responsible for this form of synaptic plasticity. We show here that miniature excitatory postsynaptic currents (mEPSCs) in cultured hippocampal neurons reliably demonstrate LTP when postsynaptic NMDA receptors are briefly stimulated with glycine. LTP of these synapses is accompanied by a rapid insertion of native AMPA receptors and by increased clustering of AMPA receptors at the surface of dendritic membranes. Both LTP and glycine-facilitated AMPA receptor insertion are blocked by intracellular tetanus toxin (TeTx), providing evidence that AMPA receptors are inserted into excitatory synapses via a SNARE-dependent exocytosis during LTP.     

Distinct modes of AMPA receptor suppression at developing synapses by GluN2A and GluN2B: single-cell NMDA receptor subunit deletion in vivo

During development there is an activity-dependent switch in synaptic N-Methyl-D-aspartate (NMDA) receptor subunit composition from predominantly GluN2B to GluN2A, though the precise role of this?switch remains unknown. By deleting GluN2 subunits in single neurons during synaptogenesis, we find that both GluN2B and GluN2A suppress AMPA receptor expression, albeit by distinct means. Similar to GluN1, GluN2B deletion increases the number of functional synapses, while GluN2A deletion increases the strength of unitary connections without affecting the number of functional synapses. We propose a model of excitatory synapse maturation in which baseline activation of GluN2B-containing receptors prevents premature synapse maturation until correlated activity allows induction of functional synapses. This activity also triggers the switch to GluN2A, which dampens further potentiation. Furthermore, we analyze the subunit composition of synaptic NMDA receptors in CA1 pyramidal cells, provide electrophysiological evidence for?a large population of synaptic triheteromeric receptors, and estimate the subunit-dependent open probability.     

Conductance-based refractory density model of primary visual cortex

A layered continual population model of primary visual cortex has been constructed, which reproduces a set of experimental data, including postsynaptic responses of single neurons on extracellular electric stimulation and spatially distributed activity patterns in response to visual stimulation. In the model, synaptically interacting excitatory and inhibitory neuronal populations are described by a conductance-based refractory density approach. Populations of two-compartment excitatory and inhibitory neurons in cortical layers 2/3 and 4 are distributed in the 2-d cortical space and connected by AMPA, NMDA and GABA type synapses. The external connections are pinwheel-like, according to the orientation of a stimulus. Intracortical connections are isotropic local and patchy between neurons with similar orientations. The model proposes better temporal resolution and more detailed elaboration than conventional mean-field models. In comparison to large network simulations, it excludes a posteriori statistical data manipulation and provides better computational efficiency and minimal parametrization.     

Oscillatory neurocomputing with ring attractors: a network architecture for mapping locations in space onto patterns of neural synchrony

Theories of neural coding seek to explain how states of the world are mapped onto states of the brain. Here, we compare how an animal''s location in space can be encoded by two different kinds of brain states: population vectors stored by patterns of neural firing rates, versus synchronization vectors stored by patterns of synchrony among neural oscillators. It has previously been shown that a population code stored by spatially tuned ‘grid cells’ can exhibit desirable properties such as high storage capacity and strong fault tolerance; here it is shown that similar properties are attainable with a synchronization code stored by rhythmically bursting ‘theta cells’ that lack spatial tuning. Simulations of a ring attractor network composed from theta cells suggest how a synchronization code might be implemented using fewer neurons and synapses than a population code with similar storage capacity. It is conjectured that reciprocal connections between grid and theta cells might control phase noise to correct two kinds of errors that can arise in the code: path integration and teleportation errors. Based upon these analyses, it is proposed that a primary function of spatially tuned neurons might be to couple the phases of neural oscillators in a manner that allows them to encode spatial locations as patterns of neural synchrony.     

Working Memory Cells' Behavior May Be Explained by Cross-Regional Networks with Synaptic Facilitation

Neurons in the cortex exhibit a number of patterns that correlate with working memory. Specifically, averaged across trials of working memory tasks, neurons exhibit different firing rate patterns during the delay of those tasks. These patterns include: 1) persistent fixed-frequency elevated rates above baseline, 2) elevated rates that decay throughout the tasks memory period, 3) rates that accelerate throughout the delay, and 4) patterns of inhibited firing (below baseline) analogous to each of the preceding excitatory patterns. Persistent elevated rate patterns are believed to be the neural correlate of working memory retention and preparation for execution of behavioral/motor responses as required in working memory tasks. Models have proposed that such activity corresponds to stable attractors in cortical neural networks with fixed synaptic weights. However, the variability in patterned behavior and the firing statistics of real neurons across the entire range of those behaviors across and within trials of working memory tasks are typical not reproduced. Here we examine the effect of dynamic synapses and network architectures with multiple cortical areas on the states and dynamics of working memory networks. The analysis indicates that the multiple pattern types exhibited by cells in working memory networks are inherent in networks with dynamic synapses, and that the variability and firing statistics in such networks with distributed architectures agree with that observed in the cortex.     

A new regime for highly robust gamma oscillation with co-exist of accurate and weak synchronization in excitatory–inhibitory networks

A great number of biological experiments show that gamma oscillation occurs in many brain areas after the presentation of stimulus. The neural systems in these brain areas are highly heterogeneous. Specifically, the neurons and synapses in these neural systems are diversified; the external inputs and parameters of these neurons and synapses are heterogeneous. How the gamma oscillation generated in such highly heterogeneous networks remains a challenging problem. Aiming at this problem, a highly heterogeneous complex network model that takes account of many aspects of real neural circuits was constructed. The network model consists of excitatory neurons and fast spiking interneurons, has three types of synapses (GABA_A, AMPA, and NMDA), and has highly heterogeneous external drive currents. We found a new regime for robust gamma oscillation, i.e. the oscillation in inhibitory neurons is rather accurate but the oscillation in excitatory neurons is weak, in such highly heterogeneous neural networks. We also found that the mechanism of the oscillation is a mixture of interneuron gamma (ING) and pyramidal-interneuron gamma (PING). We explained the mixture ING and PING mechanism in a consistent-way by a compound post-synaptic current, which has a slowly rising-excitatory stage and a sharp decreasing-inhibitory stage.     

Bidirectional synaptic plasticity regulated by phosphorylation of stargazin-like TARPs

Synaptic plasticity involves protein phosphorylation cascades that alter the density of AMPA-type glutamate receptors at excitatory synapses; however, the crucial phosphorylated substrates remain uncertain. Here, we show that the AMPA receptor-associated protein stargazin is quantitatively phosphorylated and that stargazin phosphorylation promotes synaptic trafficking of AMPA receptors. Synaptic NMDA receptor activity can induce both stargazin phosphorylation, via activation of CaMKII and PKC, and stargazin dephosphorylation, by activation of PP1 downstream of PP2B. At hippocampal synapses, long-term potentiation and long-term depression require stargazin phosphorylation and dephosphorylation, respectively. These results establish stargazin as a critical substrate in the bidirectional control of synaptic strength, which is thought to underlie aspects of learning and memory.     

The barista on the bus: cellular and synaptic mechanisms for visual recognition memory

Our ability to recognize that something is familiar, often referred to as visual recognition memory, has been correlated with a reduction in neural activity in the perirhinal cortex. In this issue of Neuron, Griffiths et al. now provide evidence that this form of memory requires AMPA receptor endocytosis and long-term depression of excitatory synapses in this brain area.     

NMDA receptor-dependent activation of the small GTPase Rab5 drives the removal of synaptic AMPA receptors during hippocampal LTD

The activity-dependent removal of AMPA receptors from synapses underlies long-term depression in hippocampal excitatory synapses. In this study, we have investigated the role of the small GTPase Rab5 during this process. We propose that Rab5 is a critical link between the signaling cascades triggered by LTD induction and the machinery that executes the activity-dependent removal of AMPA receptors. We have found that Rab5 activation drives the specific internalization of synaptic AMPA receptors in a clathrin-dependent manner and that this activity is required for LTD. Interestingly, Rab5 does not participate in the constitutive cycling of AMPA receptors. Rab5 is able to remove both GluR1 and GluR2 AMPA receptor subunits, leading to GluR1 dephosphorylation. Importantly, NMDA receptor-dependent LTD induction produces a rapid and transient increase of active (GTP bound) Rab5. We propose a model in which synaptic activity leads to Rab5 activation, which in turn drives the removal of AMPA receptors from synapses.     

NMDA受体参与小鼠的前额扣带回的神经突触传递

谷氨酸性突触是哺乳动物神经系统的主要兴奋性突触。在正常条件下,大多数的突触反应是由谷氨酸的AMPA受体传递的。NMDA受体在静息电位下为镁离子抑制。在被激活时,NMDA受体主要参与突触的可塑性变化。但是,许多NMDA受体拮抗剂在全身或局部注射时能产生行为效应,提示NMDA受体可能参与静息状态的生理功能。此文中,我们在离体的前额扣带回脑片上进行电生理记录,发现NMDA受体参与前额扣带回的突触传递。在重复刺激或近于生理性温度时,NMDA受体传递的反应更为明显。本文直接显示了NMDA受体参与前额扣带回的突触传递,并提示NMDA受体在前额扣带回中起着调节神经元兴奋的重要作用。     

The hippocampus is coupled with the default network during memory retrieval but not during memory encoding

The brain's default mode network (DMN) is activated during internally-oriented tasks and shows strong coherence in spontaneous rest activity. Despite a surge of recent interest, the functional role of the DMN remains poorly understood. Interestingly, the DMN activates during retrieval of past events but deactivates during encoding of novel events into memory. One hypothesis is that these opposing effects reflect a difference between attentional orienting towards internal events, such as retrieved memories, vs. external events, such as to-be-encoded stimuli. Another hypothesis is that hippocampal regions are coupled with the DMN during retrieval but decoupled from the DMN during encoding. The present fMRI study investigated these two hypotheses by combining a resting-state coherence analysis with a task that measured the encoding and retrieval of both internally-generated and externally-presented events. Results revealed that the main DMN regions were activated during retrieval but deactivated during encoding. Counter to the internal orienting hypothesis, this pattern was not modulated by whether memory events were internal or external. Consistent with the hippocampal coupling hypothesis, the hippocampus behaved like other DMN regions during retrieval but not during encoding. Taken together, our findings clarify the relationship between the DMN and the neural correlates of memory retrieval and encoding.     

Intrinsic and network rhythmogenesis in a reduced traub model for CA3 neurons

We have developed a two-compartment, eight-variable model of a CA3 pyramidal cell as a reduction of a complex 19-compartment cable model [Traub et al, 1991]. Our reduced model segregates the fast currents for sodium spiking into a proximal, soma-like, compartment and the slower calcium and calcium-mediated currents into a dendrite-like compartment. In each model periodic bursting gives way to repetitive soma spiking as somatic injected current increases. Steady dendritic stimulation can produce periodic bursting of significantly higher frequency (8–20 Hz) than can steady somatic input (<8 Hz). Bursting in our model occurs only for an intermediate range of electronic coupling conductance. It depends on the segregation of channel types and on the coupling current that flows back-and-forth between compartments. When the soma and dendrite are tightly coupled electrically, our model reduces to a single compartment and does not burst. Network simulations with our model using excitatory AMPA and NMDA synapses (without inhibition) give results similar to those obtained with the complex cable model [Traub et al, 1991; Traub et al, 1992]. Brief stimulation of a single cell in a resting network produces multiple synchronized population bursts, with fast AMPA synapses providing the dominant synchronizing mechanism. The number of bursts increases with the level of maximal NMDA conductance. For high enough maximal NMDA conductance synchronized bursting repeats indefinitely. We find that two factors can cause the cells to desynchronize when AMPA synapses are blocked: heterogeneity of properties amongst cells and intrinsically chaotic burst dynamics. But even when cells are identical, they may synchronize only approximately rather than exactly. Since our model has a limited number of parameters and variables, we have studied its cellular and network dynamics computationally with relative ease and over wide parameter ranges. Thereby, we identify some qualitative features that parallel or are distinguished from those of other neuronal systems; e.g., we discuss how bursting here differs from that in some classical models.     

Kalirin-7 controls activity-dependent structural and functional plasticity of dendritic spines

Activity-dependent rapid structural and functional modifications of central excitatory synapses contribute to synapse maturation, experience-dependent plasticity, and learning and memory and are associated with neurodevelopmental and psychiatric disorders. However, the signal transduction mechanisms that link glutamate receptor activation to intracellular effectors that accomplish structural and functional plasticity are not well understood. Here we report that NMDA receptor activation in pyramidal neurons causes CaMKII-dependent phosphorylation of the guanine-nucleotide exchange factor (GEF) kalirin-7 at residue threonine 95, regulating its GEF activity, leading to activation of small GTPase Rac1 and rapid enlargement of existing spines. Kalirin-7 also interacts with AMPA receptors and controls their synaptic expression. By demonstrating that kalirin expression and spine localization are required for activity-dependent spine enlargement and enhancement of AMPAR-mediated synaptic transmission, our study identifies a signaling pathway that controls structural and functional spine plasticity.     

A self-organizing neural network model for the development of complex cells

On the basis of recent neurophysiological findings on the mammalian visual cortex, a selforganizing neural network model is proposed for the understanding of the development of complex cells. The model is composed of two kinds of connections from LGN cells to a complex cell. One is direct excitatory connections and the other is indirect inhibitory connections via simple cells. Inhibitory synapses between simple cells and complex cells are assumed to be modifiable. The model was simulated on a computer to confirm its behavior.