Analysis of cultured neuronal networks using intraburst firing characteristics

It is an open question whether neuronal networks, cultured on multielectrode arrays, retain any capability to usefully process information (learning and memory). A necessary prerequisite for learning is that stimulation can induce lasting changes in the network. To observe these changes, one needs a method to describe the network in sufficient detail, while stable in normal circumstances. We analyzed the spontaneous bursting activity that is encountered in dissociated cultures of rat neocortical cells. Burst profiles (BPs) were made by estimating the instantaneous array-wide firing frequency. The shape of the BPs was found to be stable on a time scale of hours. Spatiotemporal detail is provided by analyzing the instantaneous firing frequency per electrode. The resulting phase profiles (PPs) were estimated by aligning BPs to their peak spiking rate over a period of 15 min. The PPs reveal a stable spatiotemporal pattern of activity during bursts over a period of several hours, making them useful for plasticity and learning studies. We also show that PPs can be used to estimate conditional firing probabilities. Doing so, yields an approach in which network bursting behavior and functional connectivity can be studied.     

Spontaneous Calcium Transients in Cultured Cortical Networks During Development

Spontaneous neuronal activity plays an important role in the development of the brain. Developmental changes in the spontaneous activity pattern of neuronal networks in vitro have been extensively studied by using the microelectrode array (MEA) recording system. However, little is known about the transition of spontaneous intracellular calcium dynamics, and the relationship between calcium transients and electrical activity during development. In the present paper, we carry out simultaneous recording of spontaneous electrical activity and intracellular calcium transients of rat cortical networks cultured on MEA. In one-week cultures, periodic synchronized bursts are observed and are followed by synchronized calcium transients. In three-week cultures, synchronized calcium transients are rarely observed despite the presence of highly complicated synchronized activity. Between these two states, in two-week cultures, slow, radial propagation of calcium waves independent of electrical activity is observed. Pharmacological treatments with the purinergic receptor antagonist suramin and gap junction blocker 18-$beta$ glycyrrhetinic acid reveal that the spontaneous radial calcium waves are mediated by the astrocytic network, and suggest that the astrocytic calcium waves can influence the electrical firing patterns of networks by locally affecting neuronal signaling. These results indicate that the various dynamics of intracellular calcium transients regulate the network maturation processes.      

Multiscale evolving complex network model of functional connectivity in neuronal cultures

Cultures of cortical neurons grown on multielectrode arrays exhibit spontaneous, robust, and recurrent patterns of highly synchronous activity called bursts. These bursts play a crucial role in the development and topological self-organization of neuronal networks. Thus, understanding the evolution of synchrony within these bursts could give insight into network growth and the functional processes involved in learning and memory. Functional connectivity networks can be constructed by observing patterns of synchrony that evolve during bursts. To capture this evolution, a modeling approach is adopted using a framework of emergent evolving complex networks and, through taking advantage of the multiple time scales of the system, aims to show the importance of sequential and ordered synchronization in network function.     

Characterizing the Complexity of Spontaneous Electrical Signals in Cultured Neuronal Networks Using Approximate Entropy

In this paper, neurons were cultured on a substrate above a multielectrode array, so the changes of electrophysiological activity patterns during development of the neuronal network or in response to environmental perturbations were monitored. But the complexity of these spontaneous activity patterns is not well understood. In order to solve the problem, a comprehensive method (approximate entropy (ApEn) in combination with a ldquosliding windowrdquo over the data) is introduced to quantify the complexity of four spontaneous activity patterns (sporadic spikes, tonic spikes, pseudobursts, and typical bursts) in cultured hippocampal neuronal networks. The results show that the dynamic curves of ApEn illustrate vivid differences between the four patterns and the values of ApEn fall into different ranges. Among these patterns, the complexity of tonic spikes is the highest while that of pseudobursts is the lowest. This suggests that the proposed method is a valid procedure for tracking the dynamic variation in neuronal signals and can distinguish the different firing patterns of neuronal networks in terms of their complexity.     

一个基于神经树结构的模式分类系统

目前，广泛应用于解决模式识别问题的方法有：分类树和层次前馈神经网络，本文提出了一种基于神经树结构的模式分类新方法，该方法使用小规模的神经网络作为分类树的节点，提取模式中非线性特征信息，实验结果表明，该方法一方面中以减小分类树用于模式识别产生的误差和分类树中节点的数目，另一方面可以缩短训练神经网络所需的时间。     

Neuronal network morphology and electrophysiologyof hippocampal neurons cultured on surface-treated multielectrode arrays

Toward the development of biocompatible surfaces for implantable electrode arrays and the creation of patterned neuronal networks, the impact of select biochemical substrates [poly-D-lysine (PDL), polyornithine (PO), polyethylenimine (PEI), and a basement membrane extract (BM)] on network morphology and spontaneous electrophysiological activity of dissociated hippocampal neurons was investigated. Cultured in serum-free Neurobasal medium at 100 000 cells/cm(2), neurons attached to each substrate. PDL, PO, and PEI induced little or no neuronal clustering and process fasciculation, whereas the addition of BM promoted these features. The ratios of somas to processes, and axons to dendrites, as determined by immunohistochemical staining and image analysis were comparable across all substrates. Spontaneous firing was recorded using planar multielectrode arrays (MEAs) at the third week in vitro for the two most divergent morphologies according to Euclidian cluster analysis, namely those induced by PO + BM and PEI. Mean spike amplitude, mean firing rate, median interspike interval (ISI), mean burst rate, and correlation index were analyzed and compared to morphological features. Synchronized bursting was highly correlated with neuronal clustering and process fasciculation. Spike amplitude was negatively correlated with thin branching which was most evident in neurons grown on PEI. These data indicate that factors, which influence adherence of neurons to surfaces, can profoundly impact both neuronal network morphology and electrophysiological activity in vitro.     

Analyzing the dynamics of online video popularity

Given the large volume of video content and the diversity of user attention, it is of great importance to understand the characteristics of online video popularity for technological, economic and social reasons. In this paper, based on the data collected from a leading online video service provider in China, namely Youku, the dynamics of online video popularity are analyzed in-depth from four key aspects: overall popularity distribution, individual popularity distribution, popularity evolution pattern and early-future popularity relationship. How the popularity of a set of newly upload videos distributes throughout the observation period is first studied. Then the notion of active days is proposed, and the per-day and per-hour popularity distributions of individual videos are carefully studied. Next, how the popularity of an individual video evolves over time is investigated. The evolution patterns are further defined according to the number and temporal locations of popularity bursts, in order to describe the popularity growth trend. At last, the linear relationship between early video popularity and future video popularity are examined on a log-log scale. The relationship is found to be largely impacted by the popularity evolution patterns. Therefore, the specialized models are proposed to describe the correlation according to the popularity evolution patterns. Experiment results show that specialized models can better fit the correlation than a general model. Above all, the analysis results in our work can provide direct help in practical for the interested parties of online video service such as service providers, online advisers, and network operators.     

Methodologies for characterizing traffic in wide area networks: Analysis and benchmarking

Since computer networks play an important role in distributed computing environments, an application's performance depends heavily on the quality of service provided by the communication networks. To ensure a high performance, the characteristics of wide area networks, WANs, must be well understood. This paper presents methodologies to characterize WAN traffic based on real measurements from Bellcore's backbone network that connects remote sites using dedicated T1 links. This paper also suggests some workload models that can be used for wide area network sizing and performance evaluation studies. It is found that the inter-site traffic pattern depends on the time of the day and the day of the week. Furthermore, the traffic between two sites is found to be reasonably symmetric, except for those sites designated as back-up sites. The coefficient of variation is used as a measure for the traffic burstiness and it is found to be 1·5 degree during working hours. The methods presented here are easy to use and cost-effective.     

Self-Folding Graphene-Based Interface for Brain-Like Modular 3D Tissue (Adv. Funct. Mater. 37/2023)

Electrophysiology of 3D neuronal cultures is of rapidly growing importance for revealing cellular communications associated with neurodevelopment and neurological diseases in their brain-like 3D environment. Despite that the brain also exhibits an inherent modular architecture that is essential for cortical processing, it remains challenging to interface a modular network consisting of multiple 3D neuronal tissues. Here, a self-folding graphene-based electrode array is proposed that enables to reconstruct modular 3D neuronal tissue and investigate firing dynamics among moduli. A graphene-sandwiched parylene-C film self-folds into a cylindrical structure within which living cells can be encapsulated. Culture of encapsulated cells inside the folded graphene enables to spontaneously construct 3D cell aggregates and ensure firm contact between the graphene surface and encapsulated cells. As the inner graphene surface can be utilized as an electrode, the reliable cell–electrode contact allows for long-term electrical recording from multiple 3D aggregates. Additionally, the modular network consisting of multiple 3D aggregates exhibits richer firing patterns than a conventional homogenous 2D network, which demonstrates that the approach enables measurements of firing dynamics in complex 3D neuronal networks. The deformable graphene electrode will be a powerful platform for investigating complex cellular communications in brain-like 3D cultures.     

On traffic scaling transformation at ingress optical burst switches

Ingress nodes in optical burst switching (OBS) networks are responsible for assembling burst from incoming packets and forwarding these bursts into the OBS network core. Changes in the statistical characteristics of a traffic stream at an ingress switch can affect the capacity of the network to provide quality of service. Therefore, the statistical characteristics of the output flow of an ingress node must be known for appropriate network dimensioning. This paper evaluates the impact of burst assembly mechanisms on the scaling properties of multifractal traffic flows. Results show that the factor most relevant in determining the nature of the output traffic flow is the relationship between the cut-off time scale of the input traffic and the time scale of assembly threshold. Moreover, a procedure for the detection of the cut-off scale of incoming traffic is introduced.     

Models for the generation of the motor output pattern in flying locusts

The motor output to the flight muscles of flying locusts is described briefly. Model neural networks that simulate many aspects of this output pattern are discussed. The model networks studied consisted of interconnected electronic analogs of unit patches of neural membrane. The analog units were designed by E. R. Lewis. The simplest network model, which we believe simulates the locust flight-control system reasonably well, consists of two groups of elements. The members of each group are mutually excitatory and produce bursts of impulses separated by rest periods. The two groups inhibit each other so that their bursts of activity alternate.     

Aligned microcontact printing of micrometer-scale poly-L-lysine structures for controlled growth of cultured neurons on planar microelectrode arrays

We describe a method for producing high-resolution chemical patterns on surfaces to control the attachment and growth of cultured neurons. Microcontact printing has been extended to allow the printing of micron-scale protein lines aligned to an underlying pattern of planar microelectrodes. Poly-L-lysine (PL) lines have been printed on the electrode array for electrical studies on cultured neural networks. Rat hippocampal neurons showed a high degree of attachment selectivity to the PL and produced neurites that faithfully grew onto the electrode recording sites.     

A system for MEA-based multisite stimulation

The capability for multisite stimulation is one of the biggest potential advantages of microelectrode arrays (MEAs). There remain, however, several technical problems which have hindered the development of a practical stimulation system. An important design goal is to allow programmable multisite stimulation, which produces minimal interference with simultaneous extracellular and patch or whole cell clamp recording. Here, we describe a multisite stimulation and recording system with novel interface circuit modules, in which preamplifiers and transistor transistor logic-driven solid-state switching devices are integrated. This integration permits PC-controlled remote switching of each substrate electrode. This allows not only flexible selection of stimulation sites, but also rapid switching of the selected sites between stimulation and recording, within 1.2 ms. This allowed almost continuous monitoring of extracellular signals at all the substrate-embedded electrodes, including those used for stimulation. In addition, the vibration-free solid-state switching made it possible to record whole-cell synaptic currents in one neuron, evoked from multiple sites in the network. We have used this system to visualize spatial propagation patterns of evoked responses in cultured networks of cortical neurons. This MEA-based stimulation system is a useful tool for studying neuronal signal processing in biological neuronal networks, as well as the process of synaptic integration within single neurons.     

Classification of action potentials in multi-unit intrafascicularrecordings using neural network pattern-recognition techniques

Neural network pattern-recognition techniques were applied to the problem of identifying the sources of action potentials in multi-unit neural recordings made from intrafascicular electrodes implanted in cats. The network was a three-layer connectionist machine that used digitized action potentials as input. On average, the network was able to reliably separate 6 or 7 units per recording. As the number of units present in the recording increased beyond this limit, the number separable by the network remained roughly constant. The results demonstrate the utility of neural networks for classifying neural activity in multi-unit recordings     

A control mechanism to prevent correlated message arrivals fromdegrading Signaling No. 7 network performance

Signaling System No. 7 (SS7) is designed to provide a connectionless transfer of signaling messages of reasonable length. Customers having access to user signaling bearer capabilities as specified in the ANSI T1.623 and CCITT Q.931 standards can send bursts of correlated messages (e.g., by doing a file transfer that results in the segmentation of a block of data into a number of consecutive signaling messages) through SS7 networks. These message bursts with short interarrival times could have an adverse impact on the delay performance of the SS7 networks. A control mechanism, credit manager, is investigated in this paper to regulate incoming traffic to the SS7 network by imposing appropriate time separation between messages when the incoming stream is too bursty. The credit manager has a credit bank where credits accrue at a fixed rate up to a prespecified credit bank capacity. This paper presents simulation results showing delay performance of the SS7 ISUP and TCAP message traffic with a range of correlated message traffic, and control parameters of the credit manager (i.e., credit generation rate and bank capacity) are determined that ensure the traffic entering the SS7 network is acceptable. The results show that control parameters can be set so that for any incoming traffic stream there is no detrimental impact on the SS7 ISUP and TCAP message delay, and the credit manager accepts a wide range of traffic patterns without causing significant delay     

Dynamic burst discarding scheme for deflection routing in optical burst switching networks

This paper proposes a dynamic burst discarding scheme for deflection routing in optical burst switching networks. In general, deflection routing is effective in lightly loaded situations, whereas it has a contrary effect in congested networks because deflected bursts accelerate network congestion. Thus deflection routing should be employed in lightly loaded networks. Incoming traffic, however, varies in time and location, so that temporal and/or local congestion cannot be avoided. Our proposed scheme resolves this problem in the following way. Each node autonomously detects congestion with local information, and bursts to be deflected are discarded in a probabilistic manner, based on the degree of detected congestion and the numbers of elapsed and remaining hops of those bursts. Simulation experiments show that when congestion happens temporarily, the proposed scheme reduces the burst loss probability, and it utilizes network resources efficiently when local congestion happens.     

OBS网络中的多BHP延迟调度算法

光突发交换 (Optical Burst Switching,OBS) 是下一代光网络中的有效核心交换技术之一。在OBS网络中,核心节点的调度方案是影响网络交换性能的重要因素。如何有效地对突发分组 (Burst) 进行合理调度,以减少丢包率正是关键问题所在。该文提出了一种多控制分组 (Burst Header Packet,BHP) 延迟调度算法,对于一个收集周期内到达的多个BHP所对应的突发数据,按照一定的方式对它们进行集中调度,实现对已预约资源的更改,使调度结果得到了优化。该算法根据不同的网络应用,可细化为4种具体的算法实现,以适用于不同的应用场景。仿真结果表明,该文提出的调度算法和已有算法相比,能够优化对突发分组的调度,提高对信道资源的有效使用,从而降低交换网络的丢包率。     

Adhesion and patterning of cortical neurons on polyethylenimine- and fluorocarbon-coated surfaces

Adhesion and patterning of cortical neurons was investigated on isolated islands of neuron-adhesive polyethylenimine (PEI) surrounded by a neuron-repellent fluorocarbon (FC) layer. In addition, the development of fasciculated neurites between the PEI-coated areas was studied over a time period of fifteen days. The patterns consisted of PEI-coated wells (diameter 150 microns, depth 0.5 micron) which were etched in a coating of fluorocarbon (FC) on top of polyimide (PI) coated glass. The separation distance between the PEI-coated wells were varied between 10 and 90 microns. This paper shows that chemical patterns of PEI and FC result in highly compliant patterns of adhering cortical neurons after one day in vitro. Interconnecting neurite fascicles between PEI-coated wells were especially present on patterns with a separation distance of 10 microns after eight days in vitro. A significant lower number of interconnecting neurite fascicles was observed on 20 microns separated patterns. Effective isolation of neurons into PEI-coated wells was achieved on patterns with a separation distance of 80 microns as no interconnecting neurite fascicles were observed.     

互联网智能路由架构及算法

突发流量在网络中非常普遍,会严重损害用户体验。突发流量往往能在短时间（如毫秒级别）内充满链路,导致网络拥塞和频繁分组丢失,端到端时延增加。传统路由算法要么是流量无关（如 OSPF（open shortest path first,开放式最短路径优先））的,无法对实时流量的变化做出调整;要么是集中式控制的（如线性规划）,面临求解时延过大而无法有效应对突发流量的问题。提出了一种新的智能路由算法解决突发流量的问题。一方面,提出的算法能利用机器学习强大的建模能力,通过对网络历史数据的挖掘来学习“隐式”的路由决策依据。另一方面,提出的算法能借助机器学习的快速推理能力降低决策时延,提高系统对突发流量的响应速度。实验结果表明,在真实流量数据集下,相比较其他路由算法,提出的智能路由算法能降低13%～70%的瓶颈链路利用率。     

湖北电信“九五”发展情况及“十五”发展展望

“九五”期间,湖北省电信业务发展及经济增长均创历史最高,投资规模扩大,通信能力增强,展望“十五”,湖北电信将加强基础电信网的建设,包括电话网,传输网,移动网,数据通信网,接入网和支撑网;加快信息平台和信息资源的开发,促进电信网向宽带多媒体信息网演变。