Higher-order activity beyond the word level: cortical dynamics of simple transitive sentence comprehension

Slow electrophysiological effects, which fluctuate throughout the course of a sentence, independent of transient responses to individual words, have been reported. However, this type of activity has scarcely been studied, and with only limited use of electrophysiological information, so that the brain areas in which these variations originate have not been clearly identified. To improve this state of affairs, a principal component analysis and a modern source analysis algorithm (LORETA) were applied to the slow activity underlying transitive sentence reading. Four components explained 97.3% of the variance. Of key interest was a slow variation that occurred throughout the entire sentence but peaked with the appearance of the verb. The main solution for this component was localized in prefrontal and temporal regions presumably involved in semantic sentence processing. This constitutes empirical evidence for cortical activity--related to semantic processes thought to be involved in thematic role assignment--developing throughout the sentence but presenting a conspicuous maximum with the appearance of the verb. This finding also highlights the central role of verb information in the understanding of transitive sentences.     

句子语义、代词和先行词的距离对代词加工的影响

考察了句子语义和代词与其先行词之间的距离对代词加工的影响。结果表明,语义是影响代词加工的主要因素。代词和先行词之间相隔的分句数而不是字数在一定程度上也影响代词加工。作者对这种距离效应的原因进行了讨论。     

Order-Constrained Solutions in <Emphasis Type="Italic">K</Emphasis>-Means Clustering: Even Better Than Being Globally Optimal

This paper proposes an order-constrained K-means cluster analysis strategy, and implements that strategy through an auxiliary quadratic assignment optimization heuristic that identifies an initial object order. A subsequent dynamic programming recursion is applied to optimally subdivide the object set subject to the order constraint. We show that although the usual K-means sum-of-squared-error criterion is not guaranteed to be minimal, a true underlying cluster structure may be more accurately recovered. Also, substantive interpretability seems generally improved when constrained solutions are considered. We illustrate the procedure with several data sets from the literature.     

基于多Agent的运动图像匹配任务分配策略研究

本文针对基于多Agent的运动图像匹配系统的任务分配策略进行了讨论,并结合遗传算法和模拟退火算法给出了一种新的基于多Agent的运动图像模式匹配系统的任务分配策略。     

ERP Evidence for the Rapid Assignment of an (Appropriate) Antecedent to PRO

Event-related brain potentials were recorded while subjects listened to sentences containing a controlled infinitival complement. Subject and object control items were used, both with 2 potential antecedents in the upper clause. Half of the sentences had a gender agreement violation between the null subject of the infinitival complement and an adjective predicated of it. The rapid detection of this anomaly would indicate that the parser had established the coreference relation between the null subject and an antecedent, and that the processor had rapidly consulted verb control information to select the proper antecedent of the null subject. The results showed that for both subject and object control items ungrammatical adjectives elicited a P600 effect. These data imply that the processor has coindexed the null subject with an antecedent, and that the antecedent has been selected on the basis of control information. These results are compatible with parsing models that emphasize the rapid influence of verb-specific information on sentence processing.     

Virtually overcoming grammar learning with 3D application of Loci mnemonics?

The importance of contextual information for memory organization has been advocated by memory research and ancient mnemonic techniques (e.g., method of loci), yet it remains overlooked in most current study environments. Here, German noun gender was presented to 48 participants without prior knowledge of German, either without or within a provided spatial context consisting of a simulated virtual environment that could be explored freely. The three main findings were: in addition to reduced forgetting rate, memory was significantly enhanced when acquisition had occurred with a spatial context than without, in immediate, and delayed cued recall, as well as in delayed free recall. Second, visualization ability predicted spatial context efficiency as a memory aid for cued recall. Lastly, performance of the method of loci‐based method correlated with its perceived efficiency. This is the first study to experimentally demonstrate the potential effectiveness of computer‐induced spatial context on grammar learning.     

Matrix reorganization and dynamic programming: Applications to paired comparisons and unidimensional seriation

A recursive dynamic programming strategy is discussed for optimally reorganizing the rows and simultaneously the columns of ann ×n proximity matrix when the objective function measuring the adequacy of a reorganization has a fairly simple additive structure. A number of possible objective functions are mentioned along with several numerical examples using Thurstone's paired comparison data on the relative seriousness of crime. Finally, the optimization tasks we propose to attack with dynamic programming are placed in a broader theoretical context of what is typically referred to as the quadratic assignment problem and its extension to cubic assignment.Partial support for this research was provided by NIJ Grant 80-IJ-CX-0061.     

A socially-based distributed self-organizing algorithm for holonic multi-agent systems: Case study in a task environment

Holonic multi-agent systems (HMASs) have recently attracted many researches in multi-agent systems community. Inspired from the multi-level and self-similar structures of social and biological system, holonic multi-agent systems have been widely used to model and solve complex real-world problems. The main concern in deploying HMASs is the problem of building the hierarchical holonic structure, called holarchy, and dynamically managing it during its lifetime. The way an HMAS is organized has a great impact on its applicability and performance. This paper proposes a self-organizing algorithm to build and manage the holoic structures in multi-agent systems. This algorithm is based on the local information of the agents about other agents they can communicate with. Using common social concepts, like skills, diversity, social exchange theory, and norms in definition of the algorithm, the outcomes of this research can be used in wide ranges of distributed applications. The proposed model is extensively tested in a task allocation problem; and its performance based on various design parameters is studied. Empirical results show that the proposed model properly increases the performance of the system in terms of effectiveness and efficiency.     

The effect of neighborhood frequency in reading: evidence with transposed-letter neighbors

Transposed-letter effects (e.g., jugde activates judge) pose serious models for models of visual-word recognition that use position-specific coding schemes. However, even though the evidence of transposed-letter effects with nonword stimuli is strong, the evidence for word stimuli is scarce and inconclusive. The present experiment examined the effect of neighborhood frequency during normal silent reading using transposed-letter neighbors (e.g., silver, sliver). Two sets of low-frequency words were created (equated in the number of substitution neighbors, word frequency, and number of letters), which were embedded in sentences. In one set, the target word had a higher frequency transposed-letter neighbor, and in the other set, the target word had no transposed-letter neighbors. An inhibitory effect of neighborhood frequency was observed in measures that reflect late processing in words (number of regressions back to the target word, and total time). We examine the implications of these findings for models of visual-word recognition and reading.