Detection of bursts in neuronal spike trains by the mean inter-spike interval method

Bursts are electrical spikes firing with a high frequency, which are the most important property in synaptic plasticity and information processing in the central nervous system. However, bursts are difficult to identify because bursting activities or patterns vary with physiological conditions or external stimuli. In this paper, a simple method automatically to detect bursts in spike trains is described. This method auto-adaptively sets a parameter (mean inter-spike interval) according to intrinsic properties of the detected burst spike trains, without any arbitrary choices or any operator judgment. When the mean value of several successive inter-spike intervals is not larger than the parameter, a burst is identified. By this method, bursts can be automatically extracted from different bursting patterns of cultured neurons on multi-electrode arrays, as accurately as by visual inspection. Furthermore, significant changes of burst variables caused by electrical stimulus have been found in spontaneous activity of neuronal network. These suggest that the mean inter-spike interval method is robust for detecting changes in burst patterns and characteristics induced by environmental alterations.     

A disinhibitory microcircuit for associative fear learning in the auditory cortex

Learning causes a change in how information is processed by neuronal circuits. Whereas synaptic plasticity, an important cellular mechanism, has been studied in great detail, we know much less about how learning is implemented at the level of neuronal circuits and, in particular, how interactions between distinct types of neurons within local networks contribute to the process of learning. Here we show that acquisition of associative fear memories depends on the recruitment of a disinhibitory microcircuit in the mouse auditory cortex. Fear-conditioning-associated disinhibition in auditory cortex is driven by foot-shock-mediated cholinergic activation of layer 1 interneurons, in turn generating inhibition of layer 2/3 parvalbumin-positive interneurons. Importantly, pharmacological or optogenetic block of pyramidal neuron disinhibition abolishes fear learning. Together, these data demonstrate that stimulus convergence in the auditory cortex is necessary for associative fear learning to complex tones, define the circuit elements mediating this convergence and suggest that layer-1-mediated disinhibition is an important mechanism underlying learning and information processing in neocortical circuits.     

Integration of quanta in cerebellar granule cells during sensory processing

To understand the computations performed by the input layers of cortical structures, it is essential to determine the relationship between sensory-evoked synaptic input and the resulting pattern of output spikes. In the cerebellum, granule cells constitute the input layer, translating mossy fibre signals into parallel fibre input to Purkinje cells. Until now, their small size and dense packing have precluded recordings from individual granule cells in vivo. Here we use whole-cell patch-clamp recordings to show the relationship between mossy fibre synaptic currents evoked by somatosensory stimulation and the resulting granule cell output patterns. Granule cells exhibited a low ongoing firing rate, due in part to dampening of excitability by a tonic inhibitory conductance mediated by GABA(A) (gamma-aminobutyric acid type A) receptors. Sensory stimulation produced bursts of mossy fibre excitatory postsynaptic currents (EPSCs) that summate to trigger bursts of spikes. Notably, these spike bursts were evoked by only a few quantal EPSCs, and yet spontaneous mossy fibre inputs triggered spikes only when inhibition was reduced. Our results reveal that the input layer of the cerebellum balances exquisite sensitivity with a high signal-to-noise ratio. Granule cell bursts are optimally suited to trigger glutamate receptor activation and plasticity at parallel fibre synapses, providing a link between input representation and memory storage in the cerebellum.     

Neuronal filtering of multiplexed odour representations

Neuronal activity patterns contain information in their temporal structure, indicating that information transfer between neurons may be optimized by temporal filtering. In the zebrafish olfactory bulb, subsets of output neurons (mitral cells) engage in synchronized oscillations during odour responses, but information about odour identity is contained mostly in non-oscillatory firing rate patterns. Using optogenetic manipulations and odour stimulation, we found that firing rate responses of neurons in the posterior zone of the dorsal telencephalon (Dp), a target area homologous to olfactory cortex, were largely insensitive to oscillatory synchrony of mitral cells because passive membrane properties and synaptic currents act as low-pass filters. Nevertheless, synchrony influenced spike timing. Moreover, Dp neurons responded primarily during the decorrelated steady state of mitral cell activity patterns. Temporal filtering therefore tunes Dp neurons to components of mitral cell activity patterns that are particularly informative about precise odour identity. These results demonstrate how temporal filtering can extract specific information from multiplexed neuronal codes.     

Firing patterns of long-term cultured neuronal network on multi-electrode array

Spontaneous neuronal activity plays an important role in the development and plasticity of brain. To explore the developmental changes in the firing pattern of the neuronal networks in vitro, the hippocampal neurons were cultured on the multi-microelectrode array dish for over 14 weeks and the spontaneous activity was recorded. The results showed that random firing was observed in the 1st week and transformed into synchronized activity after two weeks, then tightly synchronized activity appeared in week 2 to 7 and finally the activities transformed into the random firing pattern. These results suggested three stages in the long-term development of neuronal network in vitro: the stage for connection, the stage of synchronized activity and the mature stage. Synchronized firing shown by spontaneous activity was an important phenomenon in high density cultured neuronal network and transformed patterns during development.     

瓦斯传感网络时空数据的预处理

由于煤矿巷道环境恶劣,提高瓦斯传感网络数据可靠性十分重要。从利用传感网络数据的时空关联性出发,研究了基于时空融合的瓦斯传感网络数据的预处理方法。首先,给出了传感网络时间、空间颗粒的定义,提出了瓦斯传感网络时间、空间颗粒的划分方法。接着,论述了异常值检测,以及基于时空融合的瓦斯传感网络数据的平滑预处理方法。仿真结果表明,提出的瓦斯传感网络时空数据预处理方法是有效、合理的。     

Influence of prolonged optic flow stimuli on spontaneous activities of cat PMLS neurons

Changes in neuronal spontaneous activities after prolonged optic flow stimulation (using the three basic flow modes: translation, radiation and rotation) were investigated by extracellular single-unit recording in cortical area PMLS of the cat. The results showed that the evoked responses decreased with the prolongation of visual stimuli,and the spontaneous activities usually dropped to a lower level after the stimuli were withdrawn. Generally, the reduction in spontaneous activities was larger after adaptation in the preferred direction than in the non-preferred direction.This difference was much pronounced to translation stimuli,but relatively insignificant to radiation and rotation. These points suggest that non-specific fatigue may act as the key factor in adaptation to simple translation, while some kinds of more complicated, direction-specific mechanism may be involved in adaptation to the complex optic flow patterns. In addition, PMLS may play an important role in perception and adaptation to complex motion and the relevant motion after-effects.     

基于图Transformer网络的城市路网短时交通流预测模型

针对城市路网短时交通流预测问题,在考虑路网交通状态时空相关性基础上,提出一种基于图Transformer（graph transformer,Graformer）的预测方法。该方法将多条路段的交通状态预测问题转化为图节点状态预测问题,针对区分相同结构的空间路网结构图,本文将带有边的图同构网络（graph isomorphism network with edges,GINE）和Transformer网络相结合,对交通状态在路网层面的时空相关性进行建模,从而实现城市路网短时交通流预测。具体来说,Graformer模型首先利用长短期记忆网络（long short-term memory,LSTM）对交通数据的时序信息进行预处理,接着采用基于GINE与Transformer的全局注意力机制提取交通数据的空间特征,最后实现路网各路段交通流的同步预测。通过使用PeMS数据集进行实验验证,结果表明提出的Graformer模型在各项性能指标上均优于对比模型,证明了其作为一种可靠且高效的路网短时交通流预测方法的有效性。     

An ultra-sparse code underlies the generation of neural sequences in a songbird

Sequences of motor activity are encoded in many vertebrate brains by complex spatio-temporal patterns of neural activity; however, the neural circuit mechanisms underlying the generation of these pre-motor patterns are poorly understood. In songbirds, one prominent site of pre-motor activity is the forebrain robust nucleus of the archistriatum (RA), which generates stereotyped sequences of spike bursts during song and recapitulates these sequences during sleep. We show that the stereotyped sequences in RA are driven from nucleus HVC (high vocal centre), the principal pre-motor input to RA. Recordings of identified HVC neurons in sleeping and singing birds show that individual HVC neurons projecting onto RA neurons produce bursts sparsely, at a single, precise time during the RA sequence. These HVC neurons burst sequentially with respect to one another. We suggest that at each time in the RA sequence, the ensemble of active RA neurons is driven by a subpopulation of RA-projecting HVC neurons that is active only at that time. As a population, these HVC neurons may form an explicit representation of time in the sequence. Such a sparse representation, a temporal analogue of the 'grandmother cell' concept for object recognition, eliminates the problem of temporal interference during sequence generation and learning attributed to more distributed representations.     

Meridian-like character of reflex electromyogram activity in longissimus dorsi muscles

We studied the temporal and spacial character of the electromyogram (EMG) evoked by acupuncture in longissimus dorsi (LD) muscles of rat, and evaluated the effect of needling direction or local blockade on EMG propagation. When certain sites on LD muscle were acupunctured, asynchronous EMG could be activated not only at the acupunctured point, but also within the muscle region supplied by the adjacent 2–3 vertebral segments. The EMG evoked by stimulation on the borderline of aponeurosis and muscle venter was larger in amplitude than those on the other sites in the same vertebral segment. When the distance from the recorded site to stimulated site increased, the EMG amplitude decreased, and its latency prolonged. Acupuncture in an oblique direction toward rostral or caudal side of the muscle enhanced the EMG amplitude in the same direction. EMG activity was weakened and its propagation was blocked by local injection of procaine. These results indicated that the character of EMG propagation evoked by acupuncture was related to the mechanism of needle-feeling propagation along the meridian.     

基于双耦合驱动模型的时空混沌流密码系统

为提高时空混沌流密码系统的抗误码能力,该文研究了这一系统的误码扩散特性,得到驱动序列中多个误码的扩散范围与系统参数的关系。提出一种基于双耦合驱动模型的时空混沌流密码系统,利用相互耦合的混沌系统生成驱动序列,并在接收端进行误码检测处理,对模型结构、误码检测、误码处理作了详细的设计,达到提高系统抗误码能力的目的。理论分析和仿真结果表明,该文提出的双耦合驱动模型可以显著地提高时空混沌流密码系统的抗误码能力。     

High-fidelity transmission of sensory information by single cerebellar mossy fibre boutons

Understanding the transmission of sensory information at individual synaptic connections requires knowledge of the properties of presynaptic terminals and their patterns of firing evoked by sensory stimuli. Such information has been difficult to obtain because of the small size and inaccessibility of nerve terminals in the central nervous system. Here we show, by making direct patch-clamp recordings in vivo from cerebellar mossy fibre boutons-the primary source of synaptic input to the cerebellar cortex-that sensory stimulation can produce bursts of spikes in single boutons at very high instantaneous firing frequencies (more than 700 Hz). We show that the mossy fibre-granule cell synapse exhibits high-fidelity transmission at these frequencies, indicating that the rapid burst of excitatory postsynaptic currents underlying the sensory-evoked response of granule cells can be driven by such a presynaptic spike burst. We also demonstrate that a single mossy fibre can trigger action potential bursts in granule cells in vitro when driven with in vivo firing patterns. These findings suggest that the relay from mossy fibre to granule cell can act in a 'detonator' fashion, such that a single presynaptic afferent may be sufficient to transmit the sensory message. This endows the cerebellar mossy fibre system with remarkable sensitivity and high fidelity in the transmission of sensory information.     

Early motor activity drives spindle bursts in the developing somatosensory cortex

Sensorimotor coordination emerges early in development. The maturation period is characterized by the establishment of somatotopic cortical maps, the emergence of long-range cortical connections, heightened experience-dependent plasticity and spontaneous uncoordinated skeletal movement. How these various processes cooperate to allow the somatosensory system to form a three-dimensional representation of the body is not known. In the visual system, interactions between spontaneous network patterns and afferent activity have been suggested to be vital for normal development. Although several intrinsic cortical patterns of correlated neuronal activity have been described in developing somatosensory cortex in vitro, the in vivo patterns in the critical developmental period and the influence of physiological sensory inputs on these patterns remain unknown. We report here that in the intact somatosensory cortex of the newborn rat in vivo, spatially confined spindle bursts represent the first and only organized network pattern. The localized spindles are selectively triggered in a somatotopic manner by spontaneous muscle twitches, motor patterns analogous to human fetal movements. We suggest that the interaction between movement-triggered sensory feedback signals and self-organized spindle oscillations shapes the formation of cortical connections required for sensorimotor coordination.     

Exploring the epidemic transmission network of SARS in-out flow in mainland China

The changing spatiotemporal patterns of the individual susceptible-infected-symptomatic-treated-recovered epidemic process and the interactions of information/material flows between regions,along with the 2002-2003 Severe Acute Respiratory Syndrome(SARS) epidemiological investigation data in mainland China,including three typical locations of individuals(working unit/home address,onset location and reporting unit),are used to define the in-out flow of the SARS epidemic spread.Moreover,the input/output transmission networks of the SARS epidemic are built according to the definition of in-out flow.The spatiotemporal distribution of the SARS in-out flow,spatial distribution and temporal change of node characteristic parameters,and the structural characteristics of the SARS transmission networks are comprehensively and systematically explored.The results show that(1) Beijing and Guangdong had the highest risk of self-spread and output cases,and prevention/control measures directed toward self-spread cases in Beijing should have focused on the later period of the SARS epidemic;(2) the SARS transmission networks in mainland China had significant clustering characteristics,with two clustering areas of output cases centered in Beijing and Guangdong;(3) Guangdong was the original source of the SARS epidemic,and while the infected cases of most other provinces occurred mainly during the early period,there was no significant spread to the surrounding provinces;in contrast,although the input/output interactions between Beijing and the other provinces countrywide began during the mid-late epidemic period,SARS in Beijing showed a significant capacity for spatial spreading;(4) Guangdong had a significant range of spatial spreading throughout the entire epidemic period,while Beijing and its surrounding provinces formed a separate,significant range of high-risk spreading during the mid-late period;especially in late period,the influence range of Beijing’s neighboring provinces,such as Hebei,was even slightly larger than that of Beijing;and(5) the input network had a low-intensity spread capacity and middle-level influence range,while the output network had an extensive high-intensity spread capacity and influence range that covered almost the entire country,and this spread and influence indicated that significant clustering characteristics increased gradually.This analysis of the epidemic in-out flow and its corresponding transmission network helps reveal the potential spatiotemporal characteristics and evolvement mechanism of the SARS epidemic and provides more effective theoretical support for prevention and control measures.     

时空轨迹中隐含的周期性行为模式

将人类时空轨迹中隐含的信息进行可视化并转换为语义语言是公安工作的迫切需要。使用聚类算法将空间轨迹数据离散化,设计等间距抽样算法规整时间序列数据,从而将连续域上的时空轨迹数据表示为离散的二值序列,为使用离散傅里叶变换和循环自相关方法查找时空轨迹中隐含的周期性行为模式做好数据准备;并通过调整采样时间跨度以增强稀疏二值序列的周期性特征。实验表明可以有效提取时空轨迹中的周期性行为模式,而具有季节性和随机变化的行为模式也具有重要参考价值。案件的发生是由人的行为导致的,所以对人类时空轨迹的研究成果也可以应用于案件分析。     

基于编码调制视觉诱发电位脑机接口滤波算法的性能比较

脑机接口(brain-computer interface,BCI)的分类性能一定程度上取决于对脑电信号的预处理方法,这项研究提出了一种空域时域滤波的预处理方法,以解决人类视觉系统中的潜伏延迟对编码调制视觉诱发电位(c-VEP) BCI的目标识别性能的影响。基于一个平均信号和单次试验信号之间的最小均方误差(the least mean square error,LMSE)创建时域空域滤波器,并且通过最小绝对收缩和选择算子(the least absolute shrinkage and selection operator,LASSO)将稀疏约束应用于滤波器的权重系数,并用模板匹配法来对目标进行识别。将算法应用于由63比特的M序列及其循环移位序列调制的16个目标的c-VEP BCI,并与通用的空域滤波算法典型相关分析(CCA)及空域时域逆滤波算法进行比较。结果表明本研究所提出的算法在分类准确率方面优于其他两种算法。     

Attractor dynamics of network UP states in the neocortex

The cerebral cortex receives input from lower brain regions, and its function is traditionally considered to be processing that input through successive stages to reach an appropriate output. However, the cortical circuit contains many interconnections, including those feeding back from higher centres, and is continuously active even in the absence of sensory inputs. Such spontaneous firing has a structure that reflects the coordinated activity of specific groups of neurons. Moreover, the membrane potential of cortical neurons fluctuates spontaneously between a resting (DOWN) and a depolarized (UP) state, which may also be coordinated. The elevated firing rate in the UP state follows sensory stimulation and provides a substrate for persistent activity, a network state that might mediate working memory. Using two-photon calcium imaging, we reconstructed the dynamics of spontaneous activity of up to 1,400 neurons in slices of mouse visual cortex. Here we report the occurrence of synchronized UP state transitions ('cortical flashes') that occur in spatially organized ensembles involving small numbers of neurons. Because of their stereotyped spatiotemporal dynamics, we conclude that network UP states are circuit attractors--emergent features of feedback neural networks that could implement memory states or solutions to computational problems.     

培养神经元网络自发活动规律性和复杂度分析

采用近似熵（approximate entropy,ApEn）的新统计方法衡量神经元不同自发放电活动时间序列数据的规律性和复杂度,对多电极阵列上培养的海马神经元网络自发活动的复杂度进行研究．结果表明不同自发放电活动的近似熵动态变化曲线有明显差别．静息期时近似熵值范围1．0-1．2;典型爆发活动时近似熵值呈现迅速下降而后上升再下降小幅振荡（0．2-0．6）;而伪爆发活动时近似熵值在0．2—0．7范围,沿平行时间轴的某一直线上下波动;连续发放锋电位时近似熵值在0．8-0．9范围;而随机单发锋电位时近似熵值0．6—0．8范围．以上分析结果说明近似熵动态变化曲线能够体现爆发活动和锋电位发放过程的规律性和复杂度变化,并可以有效地识别培养神经元网络自发的不同电生理信号,因而在神经元电信号分析中有着潜在的应用价值．     

济阳拗陷页岩储层水平井裂缝扩展数值模拟

由于物理实验受到实验条件、数量的限制,难以对裂缝扩展规律开展大规模的研究。因此,在有了一定的岩石力学测试、页岩压裂破裂方式测试以及页岩压裂裂缝扩展物模试验的基础上,开展了页岩压裂裂缝起裂及扩展规律数值模拟研究。基于流固耦合Biot固结理论、Darcy渗流定律,采用最大拉伸强度准则和Mohr Coulomb准则损伤阈值进行单元损伤判断,引入全新的材料分布算法,建立了水力压裂裂缝扩展的有限元计算模型。进行了岩石样本的参数标定试验。采用有限元计算方法研究了地应力、页岩脆性指数、压裂液黏度和层理特征等关键物理参数对页岩裂缝扩展的影响。结果表明,当脆性指数较小时,水力裂缝主要沿最大主应力方向在页岩基质中扩展,难以转向形成复杂缝网。层理胶结强度较高时,水力作用即便在局部压开天然层理,也难以持续以大角度偏离,而只能形成比较单一的裂缝。地应力比、压裂液黏度越低,层理密度等特性越高时,裂纹网络越复杂。