Juvenile hormone drives the maturation of spontaneous mushroom body neural activity and learned behavior

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Molecular cloning and characterization of neural activity-related RING finger protein (NARF): a new member of the RBCC family is a candidate for the partner of myosin V

Activity-dependent synaptic plasticity has been thought to be a cellular basis of memory and learning. The late phase of long-term potentiation (L-LTP), distinct from the early phase, lasts for up to 6 h and requires de novo synthesis of mRNA and protein. Many LTP-related genes are enhanced in the hippocampus during pentyrenetetrazol (PTZ)- and kainate (KA)-mediated neural activation. In this study, mice were administered intraperitoneal injections of PTZ 10 times, once every 48 h, and showed an increase in seizure indexes. Genes related to plasticity were efficiently induced in the mouse hippocampus. We used a PCR-based cDNA subtraction method to isolate genes that are expressed in the hippocampus of repeatedly PTZ-treated mice. One of these genes, neural activity-related RING finger protein (NARF), encodes a new protein containing a RING finger, B-box zinc finger, coiled-coil (RBCC domain) and beta-propeller (NHL) domain, and is predominantly expressed in the brain, especially in the hippocampus. In addition, KA up-regulated the expression of NARF mRNA in the hippocampus. This increase correlated with the activity of the NMDA receptor. By analysis using GFP-fused NARF, the protein was found to localize in the cytoplasm. Enhanced green fluorescent protein-fused NARF was also localized in the neurites and growth cones in neuronal differentiated P19 cells. The C-terminal beta-propeller domain of NARF interacts with myosin V, which is one of the most abundant myosin isoforms in neurons. The NARF protein increases in hippocampal and cerebellar neurons after PTZ-induced seizure. These observations indicated that NARF expression is enhanced by seizure-related neural activities, and NARF may contribute to the alteration of neural cellular mechanisms along with myosin V.     

Abnormal Neurovascular Control during Sympathoexcitation in Obesity

Objective: We tested the hypothesis that muscle sympathetic nerve activity (MSNA) and forearm vascular resistance (FVR) would be augmented during mental stress or cold pressor test in healthy obese individuals compared with healthy lean individuals. Research Methods and Procedures: Twenty‐nine healthy obese women and 12 age‐matched healthy lean women were involved in the study. MSNA was directly measured from the peroneal nerve using microneurography. Forearm blood flow was measured by venous occlusion plethysmography. Blood pressure (BP) was monitored noninvasively by an automatic BP cuff, and heart rate (HR) was measured by electrocardiogram. Stroop color word test was performed for 4 minutes, and the cold pressor test was performed for 2 minutes. Results: Baseline MSNA and FVR were greater in the obese group than in the lean group. BP and HR were similar between groups. During mental stress, MSNA and FVR were greater in obese individuals than in lean individuals, although the magnitude of response was similar between groups. BP and HR similarly increased in obese and lean individuals. During the cold pressor test, MSNA, FVR, and BP were greater in obese individuals, but the magnitude of response was similar between groups. HR increased similarly during the cold pressor test in both obese and lean individuals. Discussion: Obesity increases MSNA and FVR during mental stress and the cold pressor test. This inappropriate neurovascular control can be expected to have an adverse effect on the risk factors for cardiovascular events and, hence, should be considered in the treatment of obese patients.     

Regional variation in neurovascular coupling and why we still lack a Rosetta Stone

Functional magnetic resonance imaging (fMRI) is the dominant tool in cognitive neuroscience although its relation to underlying neural activity, particularly in the human brain, remains largely unknown. A major research goal, therefore, has been to uncover a ‘Rosetta Stone’ providing direct translation between the blood oxygen level-dependent (BOLD) signal, the local field potential and single-neuron activity. Here, I evaluate the proposal that BOLD signal changes equate to changes in gamma-band activity, which in turn may partially relate to the spiking activity of neurons. While there is some support for this idea in sensory cortices, findings in deeper brain structures like the hippocampus instead suggest both regional and frequency-wise differences. Relatedly, I consider four important factors in linking fMRI to neural activity: interpretation of correlations between these signals, regional variability in local vasculature, distributed neural coding schemes and varying fMRI signal quality. Novel analytic fMRI techniques, such as multivariate pattern analysis (MVPA), employ the distributed patterns of voxels across a brain region to make inferences about information content rather than whether a small number of voxels go up or down relative to baseline in response to a stimulus. Although unlikely to provide a Rosetta Stone, MVPA, therefore, may represent one possible means forward for better linking BOLD signal changes to the information coded by underlying neural activity.This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity’.     

Inhibition of cortical neural networks using infrared laser

The aim of the present study is to optimize parameters for inhibiting neuronal activity safely and investigating thermal inhibition of rat cortex neural networks in vitro by continuous infrared (IR) laser. Rat cortex neurons were cultured on multi‐electrode arrays until neural networks were formed with spontaneous neural activity. Neurons were then irradiated to inhibit the activity of the networks using different powers of 1550 nm IR laser light. A finite element heating model, calibrated by the open glass pipette method, was used to calculate temperature increases at different laser irradiation intensities. A damage signal ratio (DSR) was evaluated to avoid excessive heating that may damage cells. The DSR predicted that cortex neurons should be safe at temperatures up to 49.6°C for 30 seconds, but experiments suggested that cortex neurons should not be exposed to temperatures over 46°C for 30 seconds. Neural response experiments showed that the inhibition of neural activity is temperature dependent. The normal neural activity could be inhibited safely with an inhibition degree up to 80% and induced epileptiform activity could be suppressed. These results show that continuous IR laser radiations provide a possible way to safely inhibit the neural network activity.      

The Autapse: A Simple Illustration of Short-Term Analog Memory Storage by Tuned Synaptic Feedback

According to a popular hypothesis, short-term memories are stored as persistent neural activity maintained by synaptic feedback loops. This hypothesis has been formulated mathematically in a number of recurrent network models. Here we study an abstraction of these models, a single neuron with a synapse onto itself, or autapse. This abstraction cannot simulate the way in which persistent activity patterns are distributed over neural populations in the brain. However, with proper tuning of parameters, it does reproduce the continuously graded, or analog, nature of many examples of persistent activity. The conditions for tuning are derived for the dynamics of a conductance-based model neuron with a slow excitatory autapse. The derivation uses the method of averaging to approximate the spiking model with a nonspiking, reduced model. Short-term analog memory storage is possible if the reduced model is approximately linear and if its feedforward bias and autapse strength are precisely tuned.     

Activity‐dependent regulation of synaptic size in Drosophila neuromuscular junctions

One of the fundamental questions in neural development is how neurons form synapses of the appropriate size for the efficient transfer of information across neural circuits. Here we investigated the mechanisms that bring about the size correlation between synapses and postsynaptic cells during development of Drosophila neuromuscular junctions (NMJs). To do this, we made use of a unique system in which two neighboring muscles (M6 and M7) are innervated by the same neurons. In mature NMJs, synaptic size on M6 is normally larger than that on M7, in accordance with the difference in muscle volume; this ensures the same extent of contraction of both muscles, and we refer to this correspondence as “matching”. We found that matching was apparent in larvae 8 h after hatching, but not in newly hatched larvae despite the difference in muscle volume. When sensory inputs were suppressed by the expression of tetanus toxin in sensory neurons, matching did not occur, although synapses were able to grow. Matching was also suppressed by the inhibition of motoneuronal activity. These results suggest that matching is induced by regulating the rate of synaptic growth on M6 and M7 in an experience‐ and activity‐dependent manner. It seems most likely that retrograde signals from the postsynaptic to the presynaptic cell convey the information about muscle cell size. We thus examined whether a candidate of retrograde signaling in NMJs, BMP signaling, is involved inmatching. However, there was no effect on matching inBMP type II receptor gene mutants, suggesting thatother experience‐driven mechanisms besides BMP signaling are involved in the proper development of synapses. © 2006 Wiley Periodicals, Inc. J Neurobiol, 2006     

A single-cell model to study changes in neuronal fractal dimension

Many methods have been developed to quantify neuronal morphology: measurement of neurite length, neurite number, etc. However, none of these approaches provides a comprehensive view of the complexity of neuronal morphology. In this work we have analyzed the evaluation of fractal dimension (D) as a tool to represent and quantify changes in complexity of the dendritic arbor, in in vitro cultures grown under low-density conditions. Neurons grown in isolation developed a bipolar morphology corresponding to a fractal dimension close to the unit. The analysis showed that neuronal complexity increased when cells were incubated with a depolarizing potassium concentration and there was a correlation with an increase in fractal dimension (D5 mM KCl = 1.08 +/- 0.01, D25 mM KCl =1.25 +/- 0.01). We conclude that fractal dimension is a suitable parameter to quantify changes in neuronal morphological complexity.     

Modularity and robustness of frontal cortical networks

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Spiking behavior and epileptiform oscillations in a discrete model of cortical neural networks

Summary We investigate the phenomenon of epileptiform activity using a discrete model of cortical neural networks. Our model is reduced to the elementary features of neurons and assumes simplified dynamics of action potentials and postsynaptic potentials. The discrete model provides a comparably high simulation speed which allows the rendering of phase diagrams and simulations of large neural networks in reasonable time. Further the reduction to the basic features of neurons provides insight into the essentials of a possible mechanism of epilepsy. Our computer simulations suggest that the detailed dynamics of postsynaptic and action potentials are not indispensable for obtaining epileptiform behavior on the system level. The simulation results of autonomously evolving networks exhibit a regime in which the network dynamics spontaneously switch between fluctuating and oscillating behavior and produce isolated network spikes without external stimulation. Inhibitory neurons have been found to play an important part in the synchronization of neural firing: an increased number of synapses established by inhibitory neurons onto other neurons induces a transition to the spiking regime. A decreased frequency accompanying the hypersynchronous population activity has only occurred with slow inhibitory postsynaptic potentials.     

核纤层蛋白B1的功能及其在神经系统疾病和肿瘤中的研究新进展

核纤层蛋白B1 (Lamin B1)是核纤层蛋白家族重要成员之一,其主要功能在于维持细胞核骨架完整性,并通过影响染色体分布、基因表达及DNA损伤修复等参与细胞的增殖和衰老。其表达异常与多种疾病有关,如神经系统疾病(神经管畸形,ADLD)及肿瘤(胰腺癌)等,是潜在的药物靶点和肿瘤标志物。对Lamin B1功能的深入研究,将有助于对相关神经系统疾病和肿瘤发生发展的分子机制的了解并为治疗靶点研究提供新方向。     

Use of a perfusion technique for measurements of respiratory activity in cultured cells

Summary A method for measuring respiratory activity in anchorage-dependent cultured cells has been developed. This method is based on a technique that permits the perfusion of standard plastic culture dishes with attached cells. Basal respiratory activities were studied in two continuous cell lines of neural origin, neuroblastoma C1300 clone 41A₃ and glioma 138MG. As compared to traditional measurements on detached cells, a fourfold increase in value was obtained. Investigations on membrane permeability suggested that the observed difference could be attributed to alterations in cell membrane integrity. Pretreatment with dibutyryl cyclic AMP, known to induce a morphological and biochemical differentiation in C1300 and 138MG cells, caused in both cell lines an enhanced respiration. This work was supported by grants from the National Swedish Board for Technical Development (grant 82-5025).     

Neuronal p38α mediates age‐associated neural stem cell exhaustion and cognitive decline

Neuronal activity regulates cognition and neural stem cell (NSC) function. The molecular pathways limiting neuronal activity during aging remain largely unknown. In this work, we show that p38MAPK activity increases in neurons with age. By using mice expressing p38α‐lox and CamkII‐Cre alleles (p38α?‐N), we demonstrate that genetic deletion of p38α in neurons suffices to reduce age‐associated elevation of p38MAPK activity, neuronal loss and cognitive decline. Moreover, aged p38α?‐N mice present elevated numbers of NSCs in the hippocampus and the subventricular zone. These results reveal novel roles for neuronal p38MAPK in age‐associated NSC exhaustion and cognitive decline.     

Analytical and Simulation Results for Stochastic Fitzhugh-Nagumo Neurons and Neural Networks

An analytical approach is presented for determining the response of a neuron or of the activity in a network of connected neurons, represented by systems of nonlinear ordinary stochastic differential equations—the Fitzhugh-Nagumo system with Gaussian white noise current. For a single neuron, five equations hold for the first- and second-order central moments of the voltage and recovery variables. From this system we obtain, under certain assumptions, five differential equations for the means, variances, and covariance of the two components. One may use these quantities to estimate the probability that a neuron is emitting an action potential at any given time. The differential equations are solved by numerical methods. We also perform simulations on the stochastic Fitzugh-Nagumo system and compare the results with those obtained from the differential equations for both sustained and intermittent deterministic current inputs withsuperimposed noise. For intermittent currents, which mimic synaptic input, the agreement between the analytical and simulation results for the moments is excellent. For sustained input, the analytical approximations perform well for small noise as there is excellent agreement for the moments. In addition, the probability that a neuron is spiking as obtained from the empirical distribution of the potential in the simulations gives a result almost identical to that obtained using the analytical approach. However, when there is sustained large-amplitude noise, the analytical method is only accurate for short time intervals. Using the simulation method, we study the distribution of the interspike interval directly from simulated sample paths. We confirm that noise extends the range of input currents over which (nonperiodic) spike trains may exist and investigate the dependence of such firing on the magnitude of the mean input current and the noise amplitude. For networks we find the differential equations for the means, variances, and covariances of the voltage and recovery variables and show how solving them leads to an expression for the probability that a given neuron, or given set of neurons, is firing at time t. Using such expressions one may implement dynamical rules for changing synaptic strengths directly without sampling. The present analytical method applies equally well to temporally nonhomogeneous input currents and is expected to be useful for computational studies of information processing in various nervous system centers.     

睡眠剥夺中感觉运动皮层和视觉皮层神经活动及警觉水平的改变

在睡眠剥夺(sleep deprivation, SD)过程中,人类大脑的神经活动和警觉水平如何受到影响,尤其是感觉运动和视觉系统,目前仍是研究的热点。静息状态功能磁共振成像(resting state functional magnetic resonance imaging,rfMRI)作为一种反映人脑自发活动的非侵入式成像技术,在睡眠剥夺的研究中得到了广泛应用。本研究采用9次重复rfMRI和心理运动警觉任务(psychomotor vigilance task,PVT),以探索23名志愿者在整个36小时的睡眠剥夺过程中神经活动和警觉水平的变化。我们采用基于PVT的平均反应时间(mean reaction time, MRT)和失效率(lapses ratio, LR)评估警觉水平的变化。我们采用基于rfMRI的区域同质性(region homogeneity,ReHo)和低频波动幅度(amplitude of low frequency fluctuation,ALFF)评估大脑神经活动变化。结果表明,感觉运动网络(sensorimotor network, SMN)和视觉区域(visual network, VN)是受到睡眠剥夺影响最严重的区域。我们采用组独立成分分析(Group Independent component analysis, GICA)将视觉相关区域划分为视觉I区、视觉II区、视觉关联区,并从解剖自动标记(Anatomical automatic labeling,AAL)模板中提取运动感觉相关区域,包括中央前/中央后回、中央旁小叶和辅助运动区。我们发现,睡眠剥夺后16 - 30小时脑神经活动及警惕性下降。我们采用2×3重复测量方差分析,探讨睡眠压力、昼夜节律及其交互作用对感觉运动相关和视觉相关脑区神经活动的影响。我们观察到睡眠压力与交互作用对感觉运动相关区域和视觉相关区域有显著影响。我们采用皮尔逊相关系数评估警觉水平变化与感觉运动相关和视觉相关脑区神经活动变化的关系。睡眠剥夺期间所有感觉运动相关区域的神经活动变化与警觉变化均存在显著的相关关系。我们的研究结果证实,睡眠剥夺从第一天24：00开始改变SMN和VN的警戒水平和神经活动,睡眠压力和昼夜节律在睡眠剥夺期间调节SMN和VN的神经活动。此外,昼夜节律的效应受到睡眠压力的显著调节。感觉运动相关区域和视觉相关区域的增强导致他们远程连接的减弱,这可能是睡眠剥夺期间响应时间变慢的原因。