Neural activity predicts individual differences in visual working memory capacity

Contrary to our rich phenomenological visual experience, our visual short-term memory system can maintain representations of only three to four objects at any given moment. For over a century, the capacity of visual memory has been shown to vary substantially across individuals, ranging from 1.5 to about 5 objects. Although numerous studies have recently begun to characterize the neural substrates of visual memory processes, a neurophysiological index of storage capacity limitations has not yet been established. Here, we provide electrophysiological evidence for lateralized activity in humans that reflects the encoding and maintenance of items in visual memory. The amplitude of this activity is strongly modulated by the number of objects being held in the memory at the time, but approaches a limit asymptotically for arrays that meet or exceed storage capacity. Indeed, the precise limit is determined by each individual's memory capacity, such that the activity from low-capacity individuals reaches this plateau much sooner than that from high-capacity individuals. Consequently, this measure provides a strong neurophysiological predictor of an individual's capacity, allowing the demonstration of a direct relationship between neural activity and memory capacity.     

Dissociable neural mechanisms supporting visual short-term memory for objects

Using visual information to guide behaviour requires storage in a temporary buffer, known as visual short-term memory (VSTM), that sustains attended information across saccades and other visual interruptions. There is growing debate on whether VSTM capacity is limited to a fixed number of objects or whether it is variable. Here we report four experiments using functional magnetic resonance imaging that resolve this controversy by dissociating the representation capacities of the parietal and occipital cortices. Whereas representations in the inferior intra-parietal sulcus (IPS) are fixed to about four objects at different spatial locations regardless of object complexity, those in the superior IPS and the lateral occipital complex are variable, tracking the number of objects held in VSTM, and representing fewer than four objects as their complexity increases. These neural response patterns were observed during both VSTM encoding and maintenance. Thus, multiple systems act together to support VSTM: whereas the inferior IPS maintains spatial attention over a fixed number of objects at different spatial locations, the superior IPS and the lateral occipital complex encode and maintain a variable subset of the attended objects, depending on their complexity. VSTM capacity is therefore determined both by a fixed number of objects and by object complexity.     

框架效应认知机制的研究

为探讨框架效应的产生机制问题,文中设置两个实验分别考察工作记忆容量不同和认知负载不同条件下的框架效应.结果发现两个实验中均出现框架效应,但是工作记忆容量和认知负载并不影响框架效应的大小.这表明,框架效应主要是启发式系统起作用的结果.     

采用离散坐标法计算一维平行入射辐射问题

针对离散坐标法难以应用于平行入射辐射的问题，提出了一种简单有效的方法；在原有的离散坐标系列中，直接添加一个与平行入射辐射的方向重合的离散方向，并将该离散方向的加权取得极其微小（合如1）10^-200)，这一新的离散方向对于离散坐标系列的各阶段矩方程没有任何影响，因此可以任意地设置，这样无论平行入射辐射来自哪个方向，都可以被准确地捕捉到，并采用一个一维大气辐射问题对本方法进行了检验，计算结果与精确解吻合。     

Fusion of multispectral and panchromatic images using multirate filter banks

In this paper, an image fusion method based on the filter banks is proposed for merging a high-resolution panchromatic image and a low-resolution multispectral image. Firstly, the filter banks are designed to merge different signals with minimum distortion by using cosine modulation. Then, the filter banks-based image fusion is adopted to obtain a high-resolution multispectral image that combines the spectral characteristic of low-resolution data with the spatial resolution of the panchromatic image. Finally, two different experiments and corresponding performance analysis are presented. Experimental results indicate that the proposed approach outperforms the HIS transform, discrete wavelet transform and discrete wavelet frame.     

Dissociation between mental imagery and object recognition in a brain-damaged patient.

Visual imagery is the creation of mental representations that share many features with veridical visual percepts. Studies of normal and brain-damaged people reinforce the view that visual imagery and visual perception are mediated by a common neural substrate and activate the same representations. Thus, brain-damaged patients with intact vision who have an impairment in perception should have impaired visual imagery. Here we present evidence to the contrary from a patient with severely impaired object recognition (visual object agnosia) but with normal mental imagery. He draws objects in considerable detail from memory and uses information derived from mental images in a variety of tasks. In contrast, he cannot identify visually presented objects, even those he has drawn himself. He has normal visual acuity and intact perception of equally complex material in other domains. We conclude that rich internal representations can be activated to support visual imagery even when they cannot support visually mediated perception of objects.     

离散型生产线产能评估系统的设计与实现

以离散型生产线为研究对象,通过对其产能特点进行分析,设计并开发了离散型生产线产能评估系统。系统以工时法和粗糙集为理论依据,并应用ASP和SQLServer数据库作为开发平台。企业可以通过本系统快速、精确地进行生产线产能评估。     

Neural measures reveal individual differences in controlling access to working memory

The capacity of visual short-term memory is highly limited, maintaining only three to four objects simultaneously. This extreme limitation necessitates efficient mechanisms to select only the most relevant objects from the immediate environment to be represented in memory and to restrict irrelevant items from consuming capacity. Here we report a neurophysiological measure of this memory selection mechanism in humans that gauges an individual's efficiency at excluding irrelevant items from being stored in memory. By examining the moment-by-moment contents of visual memory, we observe that selection efficiency varies substantially across individuals and is strongly predicted by the particular memory capacity of each person. Specifically, high capacity individuals are much more efficient at representing only the relevant items than are low capacity individuals, who inefficiently encode and maintain information about the irrelevant items present in the display. These results provide evidence that under many circumstances low capacity individuals may actually store more information in memory than high capacity individuals. Indeed, this ancillary allocation of memory capacity to irrelevant objects may be a primary source of putative differences in overall storage capacity.     

面向微博用户的消费意图识别算法

利用迁移学习的方法, 融合京东问答平台数据与少量已标注的微博数据构建训练集, 提出一种基于注意力机制的双向长短期记忆神经网络(Attentional-Bi-LSTM)模型, 用于识别用户的隐性消费意图。针对显性意图识别问题, 提出一种结合TF-IDF (term frequency-inverse document frequency)与句法分析中动宾关系(VOB)的消费意图对象提取算法。实验结果表明, 通过将迁移京东问答平台的数据与微博数据相融合, 可以有效地扩充训练集, 在此基础上训练的神经网络分类模型具有较高的准确率和召回率; 融合VOB和TF-IDF的显性消费意图对象提取方法的准确率达到78.8%。     

一种基于离散点的真实感图形绘制算法

曲面造型通常所采用的是基于三角形或多边形的表示方法，该方法存在着一些不足之处，文中对真实感图形生成过程进行了研究，提出了一种基于离散点绘制景物的新方法。景物由一组离散点集合表示，每个离散点包括坐标、颜色、法线、深度等。论述了基于离散点的实体造型、取景变换、消隐和光照等，并且在实践中进行了验证。     

海量电子图书信息资源利用率均衡调度方法

为解决传统方法调度均衡性差,资源利用率低的弊端,提出一种新的海量电子图书信息资源利用率均衡调度方法。依据海量电子图书信息资源池中物理服务器的工作情况,对资源池运行工作进行判断,针对不饱和运行状态,通过分析资源利用率方差、资源利用率均衡度和整个资源利用率均衡度,建立均衡调度目标函数,采用蚁群算法对其进行求解决,获取最优调度策略。在资源池饱和的情况下,求出全部虚拟机资源的等待时间,选用等待时间最短的虚拟机执行当前海量电子图书网络用户请求资源。结果表明,所提方法调度结果和其他方法相比最均衡,只有少部分均衡性相对较差;对CPU和I/O资源利用率调度均衡性较好,对内存利用率调度均衡性相对较差,但和其他方法相比较好;对不同资源利用率均为95%～99%。可见所提方法对电子图书信息资源利用率调度均衡性好,有很高的竞争力和资源利用率。     

一种有效的数字内容保护系统证书吊销问题解决方案

现有数字内容保护系统在处理设备吊销同题时,都要求在设备中维护一个完整的证书吊销信息列表,对设备存储量的要求很高并且具有可预见的不完备性.本文通过对设备生命周期内所能连接的其他设备的总数加以限制,在设备中只需维护本地的合法设备和不合法设备列表.设备维护的本地列表对存储量的要求是一个小的常数,系统在不增加计算开销的同时可以对吊销信息进行完备处理.所提出的方法可以在家庭网络中统一部署,用来实现对系统吊销问题的统一处理.     

Theta-paced flickering between place-cell maps in the hippocampus

The ability to recall discrete memories is thought to depend on the formation of attractor states in recurrent neural networks. In such networks, representations can be reactivated reliably from subsets of the cues that were present when the memory was encoded, at the same time as interference from competing representations is minimized. Theoretical studies have pointed to the recurrent CA3 system of the hippocampus as a possible attractor network. Consistent with predictions from these studies, experiments have shown that place representations in CA3 and downstream CA1 tolerate small changes in the configuration of the environment but switch to uncorrelated representations when dissimilarities become larger. However, the kinetics supporting such network transitions, at the subsecond timescale, is poorly understood. Here we show in rats that instantaneous transformation of the spatial context does not change the hippocampal representation all at once but is followed by temporary bistability in the discharge activity of CA3 ensembles. Rather than sliding through a continuum of intermediate activity states, the CA3 network undergoes a short period of competitive flickering between preformed representations of the past and present environment before settling on the latter. Network flickers are extremely fast, often with complete replacement of the active ensemble from one theta cycle to the next. Within individual cycles, segregation is stronger towards the end, when firing starts to decline, pointing to the theta cycle as a temporal unit for expression of attractor states in the hippocampus. Repetition of pattern-completion processes across successive theta cycles may facilitate error correction and enhance discriminative power in the presence of weak and ambiguous input cues.     

Class-Based Garbage Collection in Object-Oriented Programming Environments

Many garbage collection algorithms have been proposed, but few address the special needs of long-running server programs. Server applications usually run for years and spawn many threads, so they create and discard thousands of objects. Therefore, efficient garbage collection is especially important for those applications. This paper presents a class-based garbage collector for object-oriented programming environments that classifies objects by their types to achieve better gradualness. Grouping objects of the same type into a group, with a limited type-lock, a mutator cache and the lease protocol will reduce memory fragmentation, which is especially important for the efficiency of long-running server applications. This class-based collector partitions the heap space by type, which provides better concurrency than the traditional mark-sweep collector, and its reusable garbaged object pool also reduces the object allocation overhead. This paper also discusses the implementation details, such as the mutator cache and the lease protocol, and techniques to achieve better accuracy.     

基于MaxEnt生态位模型预测木灵藓科三属植物在新疆的潜在分布区

木灵藓科植物是干旱、半干旱环境中常见的藓类植物,对温度和降水极为敏感.木灵藓科在中国的物种丰富度由东向西增加,在新疆的丰富度较高.木灵藓属(Orthotrichum)、显孔藓属(Lewinskya)、多胞藓属(Nyholmiella)是三个在新疆分布较为广泛的属.预测当前以及未来气候情景下这三个属在新疆的潜在分布范围,将为木灵藓科区系和多样性研究提供一定的参考依据,也能预判未来气候变化对新疆地区木灵藓属的分布影响.该文根据木灵藓属、显孔藓属、多胞藓属在新疆的125个地理采集样点和19个气候因子,运用MaxEnt模型预测了它们适生区,并分析这些气候因素对其分布范围的影响.结果显示：1) AUC值高达0.945,说明该模型能够很好地预测了三个属的适生区范围.Jackknife检验表明,影响三个属分布的主要气候因子为最湿季平均气温以及最干季降雨量,贡献率分别为24.5%、23.9%.2) 该三属主要分布在阿勒泰、塔城、中部天山山脉、哈密、喀什和克州等地区,在和田和巴州也有一定的分布.在21世纪50年代的气候情景下,这些属在阿尔泰和塔城的分布范围将扩大,而在喀什和巴州的则缩小.总体而言,在21世纪70年代的气候情景下,这三个属在新疆的潜在分布区面积比现在的有所缩小.该文以气候因子预测了木灵藓科在新疆当前和未来的潜在分布范围,今后的工作中,将考虑影响苔藓植物生长的地形、植被的类型等,以进一步提高预测结果的准确性.     

模糊神经网络的记忆

讨论了一种模糊神经网络实现记忆的条件和记忆的特点,并给出了样本组格子点分布的概念。通过定理,证明了在这种情况下,样本组可被模糊神经网络所记忆;证明了若样本组前n-1个样本和整个样本组的模糊矩阵的秩相等,则权向量不能调整, 否则会使模糊神经网络“丧失记忆”同时,也说明了选择记忆法所采用的选择方法中减少运算量,又可保证网络的记忆。     

Active set strategy of optimized extreme learning machine

Extreme learning machine （ELM） has been introduced as a simple and efficient learning approach for regression and classification applications. From the opti- mization point of view, optimized ELM is equivalent to SVM, but with less constraints in the optimization formu- lation and random ELM kernel. This paper introduces an active set based optimized ELM approach to solve bound constrained optimization problem in a straightforward way, which operates on a small working set of variables at each iteration. Thus, the constrained problem can be eventually solved by an unconstrained algorithm, and this enables us to establish a global convergence theory. The approach requires less time for quadratic programming solving and provides better generalization performance. In addition, the proposed approach with much smaller number of non- bound support values is significantly faster than SVM with active set strategy for large training data set.     

基于细粒度伪划分的多核私有Cache容量共享机制

针对多核私有Cache结构面临的容量失效问题,提出了一种基于细粒度伪划分的核间容量共享机制.通过在细粒度层次为每个Cache Bank设置加权饱和计数器阵列来统计和预测各线程的访存需求差异情况,控制各个处理器核在每个Cache Set上的私有域与共享域划分比例,并以此指导各处理器核上的牺牲块替换、溢出与接收决策,利用智能的核间容量借用机制来均衡处理器间访存需求差异,缓解多核私有Cache结构面临的容量失效问题.在体系结构级全系统模拟器上的实验结果表明,该机制能够有效改善多核私有Cache结构的容量失效问题,降低多线程应用程序的平均存储访问延迟.     

《大脑与认知》2004年—2007年工作记忆研究终述

对工作记忆的广度和容量的研究很多,本文阐述了几个观点：工作记忆中客体的呈现受过去经历的影响;情感的决定受工作记忆条件影响,高工作记忆条件下产生了一种＂目光短浅＂的决定风格;在时间判断任务中由于工作记忆过程的不同会产生的与年龄相关的差异。     

基于反射内存网的导航系统通讯技术

针对导航系统通讯对于实时性、可靠性、高速性的要求，提出了将反射内存网应用于导航通讯中．介绍了反射内存网的特点，阐述了反射内存网的工作原理与通信机制，并与传统计算机网络技术进行了比较．重点给出了反射内存网性能的测试方案和测试结果，并设计了一套基于反射内存网的测试软件．通过实验验证了反射内存网的基本性能，结果表明反射内存网可以满足导航系统通讯中的要求．