Ultrastructural changes to rat hippocampus in pentylenetetrazol- and kainic acid-induced status epilepticus: A study using electron microscopy

A pentylenetetrazol (PTZ)-induced status epilepticus model in rats was used in the study. The brains were studied one month after treatment. Ultrastructural observations using electron microscopy performed on the neurons, glial cells, and synapses, in the hippocampal CA1 region of epileptic brains, demonstrated the following major changes over normal control brain tissue. (i) There is ultrastructural alterations in some neurons, glial cells and synapses in the hippocampal CA1 region. (ii) The destruction of cellular organelles and peripheral, partial or even total chromatolysis in some pyramidal cells and in interneurons are observed. Several astrocytes are proliferated or activated. Presynaptic terminals with granular vesicles and degenerated presynaptic profiles are rarely observed. (iii) The alterations observed are found to be dependent on the frequency of seizure activities following the PTZ treatment. It was observed that if seizure episodes are frequent and severe, the ultrastructure of hippocampal area is significantly changed. Interestingly, the ultrastructure of CA1 area is found to be only moderately altered if seizure episodes following the status epilepticus are rare and more superficial; (iv) alterations in mitochondria and dendrites are among the most common ultrastructural changes seen, suggesting cell stress and changes to cellular metabolism. These morphological changes, observed in brain neurons in status epilepticus, are a reflection of epileptic pathophysiology. Further studies at the chemical and molecular level of neurotransmitter release, such as at the level of porosomes (secretory portals) at the presynaptic membrane, will further reveal molecular details of these changes.     

Inferring Excitatory and Inhibitory Connections in Neuronal Networks

The comprehension of neuronal network functioning, from most basic mechanisms of signal transmission to complex patterns of memory and decision making, is at the basis of the modern research in experimental and computational neurophysiology. While mechanistic knowledge of neurons and synapses structure increased, the study of functional and effective networks is more complex, involving emergent phenomena, nonlinear responses, collective waves, correlation and causal interactions. Refined data analysis may help in inferring functional/effective interactions and connectivity from neuronal activity. The Transfer Entropy (TE) technique is, among other things, well suited to predict structural interactions between neurons, and to infer both effective and structural connectivity in small- and large-scale networks. To efficiently disentangle the excitatory and inhibitory neural activities, in the article we present a revised version of TE, split in two contributions and characterized by a suited delay time. The method is tested on in silico small neuronal networks, built to simulate the calcium activity as measured via calcium imaging in two-dimensional neuronal cultures. The inhibitory connections are well characterized, still preserving a high accuracy for excitatory connections prediction. The method could be applied to study effective and structural interactions in systems of excitable cells, both in physiological and in pathological conditions.     

Model architecture for associative memory in a neural network of spiking neurons

A synaptic connectivity model is assembled on a spiking neuron network aiming to build up a dynamic pattern recognition system. The connection architecture includes gap junctions and both inhibitory and excitatory chemical synapses based on Hebb’s hypothesis. The network evolution resulting from external stimulus is sampled in a properly defined frequency space. Neurons’ responses to different current injections are mapped onto a subspace using Principal Component Analysis. Departing from the base attractor, related to a quiescent state, different external stimuli drive the network to different fixed points through specific trajectories in this subspace.     

去势对成年雄性斑胸草雀HVC-RA突触可塑性的影响

应用在体电生理方法研究了去势前后成年雄性斑胸草雀发声运动通路中HVC-RA 突触的可塑性变化,进一步探讨雄激素在调节鸣唱行为中的作用和机制.结果表明：低频刺激可引起 HVC-RA突触群体峰电位幅度的短时程抑制(Short-term depression, STD),高频刺激可引起群体峰电位幅度的长时程抑制(Long-term depression, LTD).而去势后30 d,鸣曲稳定时再给予同样的条件刺激,发现无论低频或高频刺激,HVC-RA 突触的短时程抑制和长时程抑制现象同时消失.研究结果显示：鸣曲稳定性可能依赖于HVC-RA通路的突触可塑性,雄激素在维持鸣曲稳定过程中发挥重要作用.     

具有动态突触的Hopfield时滞神经网络的稳定性分析

在研究Hopfield神经网络时,通常把连接权视为常数;但实际上神经元间的突触是随时间变化的。文章运用拓扑度理论和Liapunov泛函方法,研究具有动态突触的Hopfield时滞神经网络平衡点的存在性和全局吸引性,得到了平衡点存在的简单的代数判据。     

Vibrational resonance in neuron populations with hybrid synapses

In this paper, vibrational resonance in excitable neuron populations with synapses is investigated by numerical simulation. In particular, the effect of the hybrid synapses on the signal detection and transmission in neural system is studied. Different topologies from regular and random networks to small-world networks are considered to analyze the dependence of vibrational resonance on the network structure and parameters. It is shown that there exists an optimal amplitude of high-frequency driving, enhancing the response of coupled neuron populations to a subthreshold signal. We find that chemical synaptic coupling is more efficient than the electrical coupling in signal detection and electrical synaptic coupling is better in signal transmission. Neuron populations with hybrid synapses compromise the merits of the two types of coupling and have an advantage in information communication.     

Neuronal activation increases the density of eukaryotic translation initiation factor 4E mRNA clusters in dendrites of cultured hippocampal neurons

Activity-dependent dendritic translation in CNS neurons is important for the synapse-specific provision of proteins that may be necessary for strengthening of synaptic connections. A major rate-limiting factor during protein synthesis is the availability of eukaryotic translation initiation factor 4E (eIF4E), an mRNA 5''-cap-binding protein. In this study we show by fluorescence in situ hybridization (FISH) that the mRNA for eIF4E is present in the dendrites of cultured rat hippocampal neurons. Under basal culture conditions, 58.7 ± 11.6% of the eIF4E mRNA clusters localize with or immediately adjacent to PSD-95 clusters. Neuronal activation with KCl (60 mM, 10 min) very significantly increases the number of eIF4E mRNA clusters in dendrites by 50.1 and 74.5% at 2 and 6 h after treatment, respectively. In addition, the proportion of eIF4E mRNA clusters that localize with PSD-95 increases to 74.4 ± 7.7% and 77.8 ± 7.6% of the eIF4E clusters at 2 and 6 h after KCl treatment, respectively. Our results demonstrate the presence of eIF4E mRNA in dendrites and an activity-dependent increase of these clusters at synaptic sites. This provides a potential mechanism by which protein translation at synapses may be enhanced in response to synaptic stimulation.     

Molecular organization and signal transduction at intermembrane junctions

Surfaces create an environment in which multiple forces conspire together to yield a wealth of complex chemical processes. This is especially true of cell membranes, whose fluidity and flexibility enables responsive feedback with surface chemical interactions in ways not generally seen with inorganic materials. Spatial pattern formation of cell-surface proteins at intermembrane junctions provides many beautiful examples of these phenomena, and is also emerging as a functional aspect of intercellular signaling. Correspondingly, the study of interactions of cell-membrane surfaces is attracting significant attention from cell biologists and physical chemists alike. This convergence is fueled be recent, exquisite observations of protein pattern formation events within living immunological synapses along with parallel advances in membrane reconstitution, manipulation, and imaging technologies.     

Neuromorphic Liquids,Colloids, and Gels: A Review

Advances in flexible electronic devices and robotic software require that sensors and controllers be virtually devoid of traditional electronic components, be deformable and stretch-resistant. Liquid electronic devices that mimic biological synapses would make an ideal core component for flexible liquid circuits. This is due to their unbeatable features such as flexibility, reconfiguration, fault tolerance. To mimic synaptic functions in fluids we need to imitate dynamics and complexity similar to those that occurring in living systems. Mimicking ionic movements are considered as the simplest platform for implementation of neuromorphic in material computing systems. We overview a series of experimental laboratory prototypes where neuromorphic systems are implemented in liquids, colloids and gels.     

猫舌感觉传入神经形成主要类型突触的研究

目的：研究舌传入神经形成的突触类型及分布规律,探讨舌传人纤维形成的主要类型突触。方法：按传入纤维性质和终止核团,分4个单项组：快适应纤维终止于三叉神经脊束核组（FA-VS）,快适应纤维终止于三叉神经脑桥核组（FA-VP）,慢适应纤维终止于三叉神经脊束核组（SA-VS）。慢适应纤维终止于三叉神经脑桥核组（SA-VP）;4个复合组：快适应纤维组（FA）,慢适应纤维组（SA）,三叉神经脊束核组（VS）,三叉神经脑桥核组（VP）组。在确定了脑干内的舌传入纤维后进行细胞内注射,电镜连续切片观察,分析突触类型。结果：突触按组成数目分单纯型、中间型和复杂型3种类型。各组中问型突触出现频率最多,组间数据较接近;单纯型和复杂型突触出现频率相对较少,组问数据较分散;FA-VS组单纯型出现频率最多,SA-VP复杂型出现频率最多;各组单纯型突触增、减时其复杂型突触相应减、增。结论：中间型突触为主要类型突触;单纯型和复杂型突触为辅助型突触;单纯型和复杂型突触有完全相反的势态分布;单纯型和复杂型突触也有相应增、减分布规律。