Synaptic plasticity, memory and the hippocampus: a neural network approach to causality

Two facts about the hippocampus have been common currency among neuroscientists for several decades. First, lesions of the hippocampus in humans prevent the acquisition of new episodic memories; second, activity-dependent synaptic plasticity is a prominent feature of hippocampal synapses. Given this background, the hypothesis that hippocampus-dependent memory is mediated, at least in part, by hippocampal synaptic plasticity has seemed as cogent in theory as it has been difficult to prove in practice. Here we argue that the recent development of transgenic molecular devices will encourage a shift from mechanistic investigations of synaptic plasticity in single neurons towards an analysis of how networks of neurons encode and represent memory, and we suggest ways in which this might be achieved. In the process, the hypothesis that synaptic plasticity is necessary and sufficient for information storage in the brain may finally be validated.     

Gamma神经振荡产生机制及其功能研究进展

Gamma神经振荡的频率在30～100 Hz之间,存在于动物和人类大脑的多个区域,如丘脑、体感皮层以及海马等部位,在各个尺度水平上都可被检测到.抑制性中间神经元组成的神经网络是产生此高频节律性活动的主要条件之一.皮层的gamma神经振荡与丘脑-皮层系统有关.Gamma神经振荡具有易化突触可塑性和调节神经网络的作用,主要参与感觉特征绑定、选择性注意以及记忆等高级功能.     

Asymptotics applied to a neural network

A mathematical model of neural processing is proposed which incorporates a theory for the storage of information. The model consists of a network of neurons that linearly processes incoming neural activity. The network stores the input by modifying the synaptic properties of all of its neurons. The model lends support to a distributive theory of memory using synaptic modification. The dynamics of the processing and storage are represented by a discrete system. Asymptotic analysis is applied to the system to show the learning capabilities of the network under constant input. Results are also given to predict the network's ability to learn periodic input, and input subjected to small random fluctuations.     

Progress in neural plasticity

The year 2009 marks the tenth anniversary of the founding of Institute of Neuroscience (ION) in the Shanghai campus of Chinese Academy of Sciences.     

Gamma band neural synchronization deficits for auditory steady state responses in bipolar disorder patients

Periodic auditory click stimulation has been reported to elicit an auditory steady state response (ASSR). The ASSR has been suggested to reflect the efficiency of γ-amino butyric acid (GABA) inhibitory interneuronal activity. Although a potential role for GABAergic dysfunction has been previously proposed, the role of neural synchronization in the ASSR in people with bipolar disorder (BD) has received little attention. In the current study, we investigated ASSRs to 20 Hz, 30 Hz, 40 Hz and 80 Hz click trains in BD patients. A total of 14 (4 males) BD patients and 25 (10 males) healthy controls participated in this study. ASSRs were obtained using whole-head 306-channel magnetoencephalography to calculate, ASSR power values and phase locking factors (PLF). BD patients exhibited significantly reduced mean ASSR power and PLF values bilaterally at frequencies of 30, 40, and 80 Hz (p<0.05 for these frequencies). At 20 Hz, bipolar patients showed no significant reduction in mean ASSR power and PLF values. There was a significant negative correlation between 80 Hz-ASSR-power values obtained from the right hemisphere and scores on the Hamilton Depression Rating Scale (rho = −0.86, p = 0.0003). The current study showed reduced low and high gamma band ASSR power and PLF bilaterally with no significant beta band ASSR reduction in BD patients. BD patients are characterized by deficits in gamma band oscillations, which may be associated with GABA inhibitory interneuronal activity dysfunction.     

Vector analysis in a neural network

The responses of single units in the optic lobe of the blowfly Phormia terraenovae have been investigated using micro-electrode techniques and computer generation of optical stimulation. In order to test the idea that single units perform a “neural vector analysis” the optical stimulation was designed in such a way that the mathematical vector analytic capacity of the neurones could be investigated by using a single luminous dot moving in the proper way. The integrative mechanism of the neurone could be studied by using two dots moving in such a way that the inhibitory and excitatory components of the stimulus were related in precise ways. The data verify the notion of “neural vector analysis” and open the way for an analysis of motion perception and perceptual constancies on the basis of neural mechanisms.     

Sequential binding of calcium leads to dimerization in neural cadherin

Neural cadherin (N-cadherin) is a calcium-dependent homophilic cell-adhesive molecule and critical for synaptogenesis and synapse maintenance. The extracellular region plays an important role in cadherin-mediated cell adhesion and has five tandemly repeated ectodomains (EC1-EC5) with three calcium-binding sites situated between each of these domains. Adhesive dimer formation is significantly dependent on binding of calcium such that mutations in the calcium-binding sites adversely affect cell adhesion. To investigate the relative significance of the calcium-binding sites at the EC1-EC2 interface in calcium-induced dimerization, we mutated three important amino acids, D134, D136, and D103, in NCAD12, a construct containing EC1 and EC2. Spectroscopic and chromatographic experiments showed that all three mutations affected calcium binding and dimerization. Mutation of D134, a bidentate chelator in site 3, severely impaired the binding of calcium to all three sites. These findings confirm that binding to site 3 is required for binding to occur at site 2 and site 1. Interestingly, while the D103A mutation diminished only the affinity for calcium, it completely eliminated dimerization. Equilibrium dialysis experiments showed a stoichiometry of 3 at 2 mM calcium for D103A, but no dimerization was apparent even at 10 mM calcium. These results indicate that calcium binding alone is not sufficient for dimerization but requires cooperativity between calcium-binding sites. In summary, our findings confirm that the calcium-binding sites are occupied sequentially in the order of site 3, then site 2 and site 1, and that cooperativity between site 2 and site 1 is essential for formation of adhesive dimers by N-cadherin.     

Concanavalin A binding to oligosaccharide chain leads to alterations in properties of band 3

Anion transport activity and thermotropic behavior of Band 3 are found to be altered after binding of concanavalin (Con A) to human erythrocyte ghosts and isolated Band 3. At lower Con A concentration, the rate coefficients of anion transport enhance with increasing Con A concentration, while noticeable changes of the largest calorimetric endotherm of human erythrocyte membranes termed the C transition (Band 3) can not be observed. With 50 micrograms/ml of Con A, the rate coefficient of Con A-modified ghosts increases 34.4% in comparison with that of normal ghosts. Binding of Con A in lower concentration to ghosts bring about increase of fluidity of lipid which maybe contribute to increase anion transport via Band 3. At higher Con A concentration, the C transition tend to lower temperature with increase in Con A concentration, the C transition is shifted from 69.25 degrees C to 66.25 degrees C with 2.5 mg/ml Con A. It is suggested that the Con A-modified Band 3 possess a looser structure than normal one.     

Variable expansin expression in Arabidopsis leads to different growth responses

Expansins have long been implicated in the control of cell wall extensibility. However, despite ample evidence supporting a role for these proteins in the endogenous mechanism of plant growth, there are also examples in the literature where the outcome of altered expansin gene expression is difficult to reconcile with a simplistic causal linkage to growth promotion. To investigate this problem, we report on the analysis of transgenic Arabidopsis plants in which a heterologous cucumber expansin can be inducibly overexpressed. Our results indicate that the effects of expansin expression on growth depend on the degree of induction of expansin expression and the developmental pattern of organ growth. They support the role of expansin in directional cell expansion. They are also consistent with the idea that excess expansin might itself impede normal activities of cell wall modifications, culminating in both growth promotion and repression depending on the degree of expression.     

Selection in a fluctuating environment leads to decreased genetic variation and facilitates the evolution of phenotypic plasticity

Changes in the environment are expected to induce changes in the quantitative genetic variation, which influences the ability of a population to adapt to environmental change. Furthermore, environmental changes are not constant in time, but fluctuate. Here, we investigate the effect of rapid, continuous and/or fluctuating temperature changes in the seed beetle Callosobruchus maculatus, using an evolution experiment followed by a split-brood experiment. In line with expectations, individuals responded in a plastic way and had an overall higher potential to respond to selection after a rapid change in the environment. After selection in an environment with increasing temperature, plasticity remained unchanged (or decreased) and environmental variation decreased, especially when fluctuations were added; these results were unexpected. As expected, the genetic variation decreased after fluctuating selection. Our results suggest that fluctuations in the environment have major impact on the response of a population to environmental change; in a highly variable environment with low predictability, a plastic response might not be beneficial and the response is genetically and environmentally canalized resulting in a low potential to respond to selection and low environmental sensitivity. Interestingly, we found greater variation for phenotypic plasticity after selection, suggesting that the potential for plasticity to evolve is facilitated after exposure to environmental fluctuations. Our study highlights that environmental fluctuations should be considered when investigating the response of a population to environmental change.     

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.     

Emergence of gamma motor activity in an artificial neural network model of the corticospinal system

Muscle spindle discharge during active movement is a function of mechanical and neural parameters. Muscle length changes (and their derivatives) represent its primary mechanical, fusimotor drive its neural component. However, neither the action nor the function of fusimotor and in particular of γ-drive, have been clearly established, since γ-motor activity during voluntary, non-locomotor movements remains largely unknown. Here, using a computational approach, we explored whether γ-drive emerges in an artificial neural network model of the corticospinal system linked to a biomechanical antagonist wrist simulator. The wrist simulator included length-sensitive and γ-drive-dependent type Ia and type II muscle spindle activity. Network activity and connectivity were derived by a gradient descent algorithm to generate reciprocal, known target α-motor unit activity during wrist flexion-extension (F/E) movements. Two tasks were simulated: an alternating F/E task and a slow F/E tracking task. Emergence of γ-motor activity in the alternating F/E network was a function of α-motor unit drive: if muscle afferent (together with supraspinal) input was required for driving α-motor units, then γ-drive emerged in the form of α-γ coactivation, as predicted by empirical studies. In the slow F/E tracking network, γ-drive emerged in the form of α-γ dissociation and provided critical, bidirectional muscle afferent activity to the cortical network, containing known bidirectional target units. The model thus demonstrates the complementary aspects of spindle output and hence γ-drive: i) muscle spindle activity as a driving force of α-motor unit activity, and ii) afferent activity providing continuous sensory information, both of which crucially depend on γ-drive.     

Chronic arthritis leads to disturbances in the bone collagen network

Introduction

In this study we used a mice model of chronic arthritis to evaluate if bone fragility induced by chronic inflammation is associated with an imbalance in bone turnover and also a disorganization of the bone type I collagen network.

Methods

Serum, vertebrae and femur bones were collected from eight-month-old polyarthritis SKG mice and controls. Strength of the femoral bones was evaluated using three-point bending tests and density was assessed with a pycnometer. Bone turnover markers carboxy-terminal collagen cross-linking telopeptides (CTX-I) and amino-terminal propeptide of type I procollagen (PINP) were measured in serum. The organization and density of bone collagen were analyzed in vertebrae using second-harmonic generation (SHG) imaging with a two-photon microscope and trabecular bone microstructure was assessed by scanning electron microscope (SEM).

Results

Femoral bones of SKG mice revealed increased fragility expressed by deterioration of mechanical properties, namely altered stiffness (P = 0.007) and reduced strength (P = 0.006), when compared to controls. Accordingly, inter-trabecular distance and trabecular thickness as observed by SEM were reduced in SKG mice. PINP was significantly higher in arthritic mice (9.18 ± 3.21 ng/ml) when compared to controls (1.71 ± 0.53 ng/ml, P < 0.001). Bone resorption marker CTX-I was 9.67 ± 3.18 ng/ml in arthritic SKG mice compared to 6.23 ± 4.11 ng/ml in controls (P = 0.176). The forward-to-backward signal ratio measured by SHG was higher in SKG animals, reflecting disorganized matrix and loose collagen structure, compared to controls.

Conclusions

We have shown for the first time that chronic arthritis by itself impairs bone matrix architecture, probably due to disturbed bone remodeling and increased collagen turnover. This effect might predispose patients to bone fragility fractures.     

Anti-Hebbian learning in a non-linear neural network

The Hebbian rule (Hebb 1949), coupled with an appropriate mechanism to limit the growth of synaptic weights, allows a neuron to learn to respond to the first principal component of the distribution of its input signals (Oja 1982). Rubner and Schulten (1990) have recently suggested the use of an anti-Hebbian rule in a network with hierarchical lateral connections. When applied to neurons with linear response functions, this model allows additional neurons to learn to respond to additional principal components (Rubner and Tavan 1989). Here we apply the model to neurons with non-linear response functions characterized by a threshold and a transition width. We propose local, unsupervised learning rules for the threshold and the transition width, and illustrate the operation of these rules with some simple examples. A network using these rules sorts the input patterns into classes, which it identifies by a binary code, with the coarser structure coded by the earlier neurons in the hierarchy.     

Fungal network responses to grazing

Mycelial networks operate on scales from microscopic to many m² and naturally persist for extended periods. As fungi exhibit highly adaptive development, it is important to test behavioural responses on natural substrata with realistic nutrient levels across a range of spatial scales and extended time periods. Here we quantified network responses over 7.5 months in large (57 × 57 cm) microcosms to test whether grazing shifts the network to a more resilient architecture. Resource limitation constrained any ability to respond at all, with both grazed and ungrazed networks gradually thinning out over time. Added resources sustained further exploratory growth, but only transiently increased cross-connectivity and network resilience, when tested by simulated damage in silico. Grazed networks were initially weaker and emergence of new exploratory growth was curtailed. However, increased interstitial proliferation led to new cross-links, consolidating the existing mycelial network and increasing the resilience of the network to further attack.     

Lack of beta1 integrins in enteric neural crest cells leads to a Hirschsprung-like phenotype

The enteric nervous system arises mainly from vagal and sacral neural crest cells that colonise the gut between 9.5 and 14 days of development in mice. Using the Cre-LoxP system, we removed beta1 integrins in the neural crest cells when they emerge from the neural tube. beta1-null enteric neural crest cells fail to colonise the gut completely, leading to an aganglionosis of the descending colon, which resembles the human Hirschsprung's disease. Moreover, beta1-null enteric neural crest cells form abnormal aggregates in the gut wall, leading to a severe alteration of the ganglia network organisation. Organotypic cultures of gut explants reveal that beta1-null enteric neural crest cells show impaired adhesion on extracellular matrix and enhanced intercellular adhesion properties. They display migration defects in collagen gels and gut tissue environments. We also provide evidence that beta1 integrins are required for the villi innervation in the small intestine. Our findings highlight the crucial roles played by beta1 integrins at various steps of enteric nervous system development.     

Optimal mate choice in a neural network

The tactics of mate choice was studied by means of a simple neural network model. A female was assessing 6 or 43 males and optimal choice was assumed to be the largest male of the set of males visited. This was run over a set of variances in male traits from very low as in fluctuating asymmetry to very high as in ornaments. This was done in two ways: by estimating the mean number of visits to each male before the optimal choice was done, or the probability of choosing the largest male given the constraints of five visits. When an error was introduced in perception the number of visits was very high if variance was low, but levelled off and reached an asymptote at fairly low levels of variance, i.e. variance among males is important only up to a certain level. When the number of visits was constrained the probability of choosing the right male increased with increasing variance. When asymmetry was evaluated the chance of finding the "best" male in five visits was very low (<10%) for the 6-male case, and it never happened in the 43-male case.     

Early neural responses to strength training

The neural adaptations that accompany strength training have yet to be fully determined. Here we sought to address this topic by testing the idea that strength training might share similar mechanisms with some forms of motor learning. Since ballistic motor learning is accompanied by a shift in muscle twitches induced by transcranial magnetic stimulation (TMS) toward the training direction, we sought to investigate if these changes also occur after single isometric strength training sessions with various contraction duration and rate of force development characteristics (i.e., brief or sustained ballistic contractions or slow, sustained contractions). Twitch force resultant vectors and motor-evoked potentials (MEPs) induced by TMS were measured before and after single sessions of strength training involving the forearm muscles. Participants (n = 12) each performed three training protocols (each consisting of 4 sets of 10 repetitions) and served as their own control in a counterbalanced order. All three training protocols caused a significant (P < 0.05) shift in TMS-induced twitch force resultant vectors toward the training direction, followed by a gradual shift back toward the pretraining direction. The strongest effect was found when training involved both ballistic and sustained force components. There were no large or consistent changes in the direction of twitches evoked by motor nerve stimulation for any of the three training protocols. We suggest that these early neural responses to strength training, which share similar corticospinal changes to motor learning, might reflect an important process that precedes more long-term neural adaptation that ultimately enhance strength.     

The neurochip: promoting plasticity with a neural implant

A new discovery suggests that converting the brain's own natural activity into electrical stimuli that are delivered back into another brain region can induce long-term plastic change. This discovery could provide a powerful and useful addition to therapeutic uses of brain-machine interfaces.     

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.