Finer discrimination of brain activation with local multivariate distance

The organization of human brain function is diverse on different spatial scales. Various cognitive states are always represented as distinct activity patterns across the specific brain region on fine scales. Conventional univariate analysis of functional MRI data seeks to determine how a particular cognitive state is encoded in brain activity by analyzing each voxel separately without considering the fine-scale patterns information contained in the local brain regions. In this paper, a local multivariate distance mapping (LMDM) technique is proposed to detect the brain activation and to map the fine-scale brain activity patterns. LMDM directly represents the local brain activity with the patterns across multiple voxels rather than individual voxels, and it employs the multivariate distance between different patterns to discriminate the brain state on fine scales. Experiments with simulated and real fMRI data demonstrate that LMDM technique can dramatically increase the sensitivity of the detection for the fine-scale brain activity patterns which contain the subtle information of the experimental conditions.     

Odour-plume dynamics influence the brain's olfactory code

The neural computations used to represent olfactory information in the brain have long been investigated. Recent studies in the insect antennal lobe suggest that precise temporal and/or spatial patterns of activity underlie the recognition and discrimination of different odours, and that these patterns may be strengthened by associative learning. It remains unknown, however, whether these activity patterns persist when odour intensity varies rapidly and unpredictably, as often occurs in nature. Here we show that with naturally intermittent odour stimulation, spike patterns recorded from moth antennal-lobe output neurons varied predictably with the fine-scale temporal dynamics and intensity of the odour. These data support the hypothesis that olfactory circuits compensate for contextual variations in the stimulus pattern with high temporal precision. The timing of output neuron activity is constantly modulated to reflect ongoing changes in stimulus intensity and dynamics that occur on a millisecond timescale.     

静息态脑区的活动特征研究

静息态脑区的活动处于一种相对稳定的状态。但是,静息态机能性磁共振成像(functional Magnetic Resonance Imaging,fMRI)实验中,被试者可能会受到各种噪声的影响,因此,统计分析所得到的静息态脑区的活动强度和体素数都可能受此影响。为了更进一步研究静息态脑区的活动特点,分别对16名被试采集了8′14″的静息态fMRI数据,将这些数据按照时间等分为5个部分,对每个部分分别采用低频振幅方法进行分析。实验结果显示:楔前叶和后扣带皮层包含活动体素的个数随时间变化较小,处于一种相对稳定的状态;额内侧皮层和顶下小叶中活动体素个数随时间变化差异较大,处于不是很稳定的状态。实验结果表明,静息态脑区中,楔前叶和后扣带皮层对于外界噪声的干扰不敏感,额内侧皮层和顶下小叶对于外界噪声比较敏感。     

城市土地利用空间结构分析的尺度效应

以蛇口工业区为例，采用土地利用信息图的方法、引入均质度的概念研究了城市土地利用空间结构，分五种网格尺度讨论了均质度随网格大小变化的规律，研究表明，土地利用的均质度随着划分的网格尺度的变化而相应变化，信息单元的尺度越小，土地利用的均质度也越小．其原因是网格越大，越能掩盖零散分布的细小土地斑块，强化了区域内主要的土地利用类型；相反，随着网格的缩小，小地块的信息就可以逐渐提取出来，提取的土地利用信息变得复杂。     

脑疲劳状态下脑功能网络研究与分析

旨在研究连续长时间脑力活动引发的脑疲劳对大脑连接性的影响,探索大脑疲劳评价的客观指标.通过持续认知任务实验诱发脑疲劳,选用互相关方法对采集到的脑电信号进行了不同导联间时域关联特性分析,构建并比较分析了正常态和脑疲劳态的脑功能网络.最后基于复杂网络理论对脑功能网络的特征参数进行了统计分析.结果表明,持续认知任务后,主观感觉疲劳程度显著增加,脑功能网络的平均度、平均聚类系数和网络密度与正常态相比均显著降低,而平均路径长度显著增大.脑功能网络参数可以很好地反映脑疲劳后大脑的连接性变化情况.     

Functional specificity of local synaptic connections in neocortical networks

Neuronal connectivity is fundamental to information processing in the brain. Therefore, understanding the mechanisms of sensory processing requires uncovering how connection patterns between neurons relate to their function. On a coarse scale, long-range projections can preferentially link cortical regions with similar responses to sensory stimuli. But on the local scale, where dendrites and axons overlap substantially, the functional specificity of connections remains unknown. Here we determine synaptic connectivity between nearby layer 2/3 pyramidal neurons in vitro, the response properties of which were first characterized in mouse visual cortex in vivo. We found that connection probability was related to the similarity of visually driven neuronal activity. Neurons with the same preference for oriented stimuli connected at twice the rate of neurons with orthogonal orientation preferences. Neurons responding similarly to naturalistic stimuli formed connections at much higher rates than those with uncorrelated responses. Bidirectional synaptic connections were found more frequently between neuronal pairs with strongly correlated visual responses. Our results reveal the degree of functional specificity of local synaptic connections in the visual cortex, and point to the existence of fine-scale subnetworks dedicated to processing related sensory information.     

基于F-score的大数据公共空间模式选择方法

公共空间模式（CSP） 分析由于具有变换简单、实现快速等优点,被广泛应用于信息挖掘、脑电信号处理等大数据处理应用中.本文以基于脑电信号的人类认知状态分类识别为背景,研究一种基于Fisher 分数（Fscore）的特征评价与选择的CSP 构建方法.利用F-score 计算代价小、可以快速从高维数据中选择出有效信息和特征的优点,实现了对模式重要程度做出定量的表达;针对F-score 阈值确定困难、信息冗余、无法自适应实现等难点问题,提出了相应的解决方法.所提出方法在脑认知活动解析实验中,针对五类认知状态分类问题取得了92%的识别准确率.本方法为大数据的公共模式挖掘等问题供了一个强有力的新工具.     

Global and fine information coded by single neurons in the temporal visual cortex.

When we see a person's face, we can easily recognize their species, individual identity and emotional state. How does the brain represent such complex information? A substantial number of neurons in the macaque temporal cortex respond to faces. However, the neuronal mechanisms underlying the processing of complex information are not yet clear. Here we recorded the activity of single neurons in the temporal cortex of macaque monkeys while presenting visual stimuli consisting of geometric shapes, and monkey and human faces with various expressions. Information theory was used to investigate how well the neuronal responses could categorize the stimuli. We found that single neurons conveyed two different scales of facial information in their firing patterns, starting at different latencies. Global information, categorizing stimuli as monkey faces, human faces or shapes, was conveyed in the earliest part of the responses. Fine information about identity or expression was conveyed later, beginning on average 51 ms after global information. We speculate that global information could be used as a 'header' to prepare destination areas for receiving more detailed information.     

Fractals in Spatial Patterns of Vegetation Formations

Introduction The quantification of spatial patterns, a focal subject in ecological research, is used as a foundation for meas-urement and analysis of the quality of habitats and the biodiversity[1]. Historically, the dominant approach has been used to cho…     

视听工作记忆的相位同步与跨频耦合研究

为了深入了解视听工作记忆中的神经机制和节律耦合规律,采集了视听工作记忆任务脑电数据,通过时频分析确定关键节律及核心电极,并使用多变量模式分析确定关键时间段。theta相位同步在记忆呈现期至关重要,其中额颞叶同步参与听觉记忆,额顶叶同步参与视觉记忆,而theta和alpha的跨频耦合只在特定记忆模态的相关脑区有显著增强。工作记忆任务相关脑区通过远端theta同步协调中央执行功能,alpha同步协调记忆存储缓冲功能,theta-alpha耦合整合不同模态功能间的信息,揭示了视听模态工作记忆的部分神经机制。     

Effects of disinhibition on spatiotemporal pattern of neuronalfirst recruitment in neuronal networks

The propagation of neuronal activities is a key feature to understanding information processing in networks. The analysis based on first-spikes of bursts in turn plays an important role in the research of neuronal activity propagation. Our focus here is to investigate how spatiotemporal patterns of neuronal first-spikes are affected by disinhibition. Multi-electrode arrays were used to record stimulationevoked bursts of multiple neurons in randomly cultured neuronal networks. Both the precise timing of and the rank relationships between first-spikes were analyzed. Compared with evoked bursts in the network’s native state, the precise first-spike latencies in its disinhibited state are more consistent and the propagation of its bursting activities is much faster. Additional points of interest are that disinhibited neuronal networks can be evoked to generate stable and distinguishable neuronal first recruitment spatiotemporal patterns specific to the stimulation site, and that the disinhibition may cause the original spatiotemporal patterns to change in a heterogeneous manner with regards to different propagation pathways.     

应用多分辨率小波变换提取脑电信号异常节律

脑电信号是非平稳的随机信号，其中包含了大量的生理和疾病信息，对于医生判断脑都是否有器质性的病变具有重要作用。因此对脑电信号的分析和处理一直是人们努力研究的领域。考虑到小波变换良好的时频局部化特性，利用多分辨率小波变换方法来实现脑电信号异常节律的提取，脑电信号经多分辨率小波变换后所得到的各个尺度的信号不仅反映了信号的频率信息，即尺度越大，对应信号的频率越低，同时也反映了信号的时间信息，即反映此时的EEG状态，实验结果表明，选择合适的小波基，可以有效地提取脑电信号中的异常节律。     

Spatial scaling of microbial eukaryote diversity

Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity of life and the complexity of ecosystems. Although microorganisms may comprise much of the Earth's biodiversity and have critical roles in biogeochemistry and ecosystem functioning, little is known about their spatial diversification. Here we present quantitative estimates of microbial community turnover at local and regional scales using the largest spatially explicit microbial diversity data set available (> 10(6) sample pairs). Turnover rates were small across large geographical distances, of similar magnitude when measured within distinct habitats, and did not increase going from one vegetation type to another. The taxa-area relationship of these terrestrial microbial eukaryotes was relatively flat (slope z = 0.074) and consistent with those reported in aquatic habitats. This suggests that despite high local diversity, microorganisms may have only moderate regional diversity. We show how turnover patterns can be used to project taxa-area relationships up to whole continents. Taxa dissimilarities across continents and between them would strengthen these projections. Such data do not yet exist, but would be feasible to collect.     

分布式环境下的序列模式发现研究

提出一种称为DMSP(Distributed Mining of Sequential Patterns)的算法,以解决分布式环境下的序列模式挖掘问题．其主要思想是：利用前缀投影技术划分模式搜索空间,降低数据库的规模,生成局部序列模式;利用模式前缀指定选举站点降低通信开销;多线程异步运行,提高算法的并行性．实验结果显示：在具有海量数据的局域网环境中,DMSP算法的性能优于将数据集中后采用GSP算法65％以上．     

Spatial scale dictates the productivity-biodiversity relationship

The diversity of life is heterogeneously distributed across the Earth. A primary cause for this pattern is the heterogeneity in the amount of energy, or primary productivity (the rate of carbon fixed through photosynthesis), available to the biota in a given location. But the shape of the relationship between productivity and species diversity is highly variable. In many cases, the relationship is 'hump-shaped', where diversity peaks at intermediate productivity. In other cases, diversity increases linearly with productivity. A possible reason for this discrepancy is that data are often collected at different spatial scales. If the mechanisms that determine species diversity vary with spatial scale, then so would the shape of the productivity-diversity relationship. Here, we present evidence for scale-dependent productivity-diversity patterns in ponds. When the data were viewed at a local scale (among ponds), the relationship was hump-shaped, whereas when the same data were viewed at a regional scale (among watersheds), the relationship was positively linear. This dependence on scale results because dissimilarity in local species composition within regions increased with productivity.     

Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice

Internal brain states form key determinants for sensory perception, sensorimotor coordination and learning. A prominent reflection of different brain states in the mammalian central nervous system is the presence of distinct patterns of cortical synchrony, as revealed by extracellular recordings of the electroencephalogram, local field potential and action potentials. Such temporal correlations of cortical activity are thought to be fundamental mechanisms of neuronal computation. However, it is unknown how cortical synchrony is reflected in the intracellular membrane potential (V(m)) dynamics of behaving animals. Here we show, using dual whole-cell recordings from layer 2/3 primary somatosensory barrel cortex in behaving mice, that the V(m) of nearby neurons is highly correlated during quiet wakefulness. However, when the mouse is whisking, an internally generated state change reduces the V(m) correlation, resulting in a desynchronized local field potential and electroencephalogram. Action potential activity was sparse during both quiet wakefulness and active whisking. Single action potentials were driven by a large, brief and specific excitatory input that was not present in the V(m) of neighbouring cells. Action potential initiation occurs with a higher signal-to-noise ratio during active whisking than during quiet periods. Therefore, we show that an internal brain state dynamically regulates cortical membrane potential synchrony during behaviour and defines different modes of cortical processing.     

Analytical criteria for local activity of CNN with five state variables and application to Hyper-chaos synchronization Chua's circuit

The analytic criteria for the local activity theory in one-port cellular neural network (CNN) with five local state variables are presented. The application to a Hyper-chaos synchronization Chua's circuit (HCSCC) CNN with 1125 variables is studied. The bifurcation diagrams of the HCSCC CNN show that they are slightly different from the smoothed CNN with one or two ports and four state variables calculated earlier. The evolution of the patterns of the state variables of the HCSCC CNN is stimulated. Oscillatory patterns, chaotic patterns, convergent or divergent patterns may emerge if the selected cell parameters are located in the locally active domains but nearby or in the edge of chaos domain.     

思维容介态——关于思维对生命直接或间接进化作用的探析

本文是已发表的“自然容介态”“生命容介态”的深度延伸思考。思维是高级生命无与伦比的重要特征,它在自然界物质与能量、信息与信息态能量,以及物质与信息三种形式的容介态互变运动过程中,直接或间接地影响着生命的进化。遗传进化主要取决于主系肌朊线粒体的运动,而人类生物体的信任度反应高低、对于思维影像虚像的敏感程度,以及超常态清净思维的纯度等进化质量,则与个体脑容量和生命初始时是否形成异态多元的主系肌朊线粒体严重相关。任何思维形式都不能直接影响信息态空间,宇宙中不存在任何独立于物质生命之外的智慧活动,但高级生命体的主系肌朊线粒体对宇宙信息态空间的进化会有间接贡献。     

Drought sensitivity shapes species distribution patterns in tropical forests

Although patterns of tree species distributions along environmental gradients have been amply documented in tropical forests, mechanisms causing these patterns are seldom known. Efforts to evaluate proposed mechanisms have been hampered by a lack of comparative data on species' reactions to relevant axes of environmental variation. Here we show that differential drought sensitivity shapes plant distributions in tropical forests at both regional and local scales. Our analyses are based on experimental field assessments of drought sensitivity of 48 species of trees and shrubs, and on their local and regional distributions within a network of 122 inventory sites spanning a rainfall gradient across the Isthmus of Panama. Our results suggest that niche differentiation with respect to soil water availability is a direct determinant of both local- and regional-scale distributions of tropical trees. Changes in soil moisture availability caused by global climate change and forest fragmentation are therefore likely to alter tropical species distributions, community composition and diversity.