学龄期普通话特异性语言损伤儿童体习得——来自词汇体和语法体组合加工的证据

采用自定步速阅读范式，探讨了7~10岁普通话特异性语言损伤儿童对词汇体和语法体组合语义一致和不一致情况的加工表现。被试分为特异性语言损伤儿童，实龄匹配儿童和语言能力匹配儿童三组，结果表明7~10岁的特异性语言损伤儿童与年幼的语言能力匹配组儿童一样，词汇体和语法体一致条件下的加工快于不一致条件，两组儿童的表现均符合词汇体假设；与此不同，实龄匹配儿童的加工速度整体均快于以上两组儿童，且词汇体和语法体一致与不一致条件下的加工速度无显著差异。上述结果表明，普通话7~10岁特异性语言损伤儿童对词汇体和语法体组合合法性的习得仍不成熟，语法体的加工仍受词汇体影响，处于语法体能力发展的早期阶段。     

The temporal-relevance temporal-uncertainty model of prospective duration judgment

A model aimed at explaining prospective duration judgments in real life settings (as well as in the laboratory) is presented. The model is based on the assumption that situational meaning is continuously being extracted by humans’ perceptual and cognitive information processing systems. Time is one of the important dimensions of situational meaning. Based on the situational meaning, a value for Temporal Relevance is set. Temporal Relevance reflects the importance of temporal aspects for enabling adaptive behavior in a specific moment in time. When Temporal Relevance is above a certain threshold a prospective duration judgment process is evoked automatically. In addition, a search for relevant temporal information is taking place and its outcomes determine the level of Temporal Uncertainty which reflects the degree of knowledge one has regarding temporal aspects of the task to be performed. The levels of Temporal Relevance and Temporal Uncertainty determine the amount of attentional resources allocated for timing by the executive system. The merit of the model is in connecting timing processes with the ongoing general information processing stream. The model rests on findings in various domains which indicate that cognitive-relevance and self-relevance are powerful determinants of resource allocation policy. The feasibility of the model is demonstrated by analyzing various temporal phenomena. Suggestions for further empirical validation of the model are presented.     

Modeling the emergence of informational content by adaptive networks for temporal factorisation and criterial causation

Propagated activation of neurons through their network is an important process in the brain. Another crucial part of neural processing concerns adaptation over time of characteristics of this network such as connection strengths or excitability thresholds. This adaptation can be slow, as in learning from a multiple experiences, or it can be fast, as in memory formation. These adaptive network characteristics can be considered informational criteria for activation of a neuron. This then is viewed as a form of emergent information formation. Activation of neurons is determined by such information via a process termed criterial causation. In the current paper, the relationship of criterial causation with the principle of temporal factorisation for the dynamics of the world in general is explored. Temporal factorisation describes how the world represents information about its past in its present state, which then in turn determines the world’s future. In the paper, it is shown how these processes are analysed in more detail and modeled by (adaptive) network models.