Evolution: Journey or Random Walk?

Though early ideas of evolution saw it as progressive, most modern theories see it as a random walk. The theories of Richard Dawkins, Stephen Jay Gould, Edward O. Wilson, Stuart Kauffman, Steven Rose, and Robert Wesson are surveyed, showing their agreement on the fact of evolution but not on the mechanism. Evolution is an incomplete theory. Any theology should therefore be based only on its broadest features. Generally, evolution is the development of complex forms from simple ancestors. Within a Christian context, it can be seen as a journey toward the unification of all things in Christ, the ultimate complexity.     

Worlds within Worlds: Kabbalah and the New Scientific Paradigm

Beginning with relativity and quantum theory, the deterministic view that has dominated and shaped Western culture for more than 2,500 years has begun to unravel, leading to the emergence of a new paradigm. This new paradigm effectively reformulates the project of science, conceiving of existence as an interpenetrating web of coevolving, cocreative relationships. By exploring Kabbalah and the new scientific paradigm within the context of shared evolutionary principles, I seek to demonstrate a viable alternative to the prevailing deterministic worldview. By going beyond the limits of determinism and re–visioning existence as an evolutionary, emergent phenomenon, we can establish a new basis for an authentic dialogue between science and religion.     

关系复杂性对关系类别间接性学习的影响

以216名大学生为被试,使用关系复杂性变化的三种虚拟外星生物实验材料,创设个人功能预测的关系类别的间接性学习条件和参照性交流功能预测的关系类别的间接性学习条件,探讨关系复杂性对关系类别间接性学习的影响。结果发现:关系类别的功能预测间接性学习过程中,关系复杂性和学习条件的交互作用极其显著,具体来讲,关系复杂性对关系类别间接性学习的影响仅显著地表现在参照性交流关系类别间接性学习过程中;当学习材料为4特征复杂关系时,参照条件下被试功能预测成绩极其显著高于个人条件,当学习材料为6特征复杂关系加二阶同功能简单关系时,两种学习条件间不存在显著差异,当学习材料为6特征复杂关系加二阶异功能简单关系时,个人条件极其显著高于参照条件。     

The SNARC effect does not imply a mental number line

In this study, we directly contrast two approaches that have been proposed to explain the SNARC effect. The traditional direct mapping account suggests that a direct association exists between the position of a number on the mental number line and the location of the response. On the other hand, accounts are considered that propose an intermediate step in which numbers are categorized as either small or large between the number magnitude and the response representations. In a magnitude comparison task, we departed from the usual bimanual left/right response dimension and instead introduced the unimanual close/far dimension. A spatial-numerical association was observed: small numbers were associated with a close response, while large numbers were associated with a far response, regardless of the movement direction (left/right). We discuss why these results cannot be explained by assuming a direct mapping from the representation of numbers on a mental number line to response locations and discuss how the results can be explained by the alternative accounts.     

Parameters, Predictions, and Evidence in Computational Modeling: A Statistical View Informed by ACT-R

Model validation in computational cognitive psychology often relies on methods drawn from the testing of theories in experimental physics. However, applications of these methods to computational models in typical cognitive experiments can hide multiple, plausible sources of variation arising from human participants and from stochastic cognitive theories, encouraging a "model fixed, data variable" paradigm that makes it difficult to interpret model predictions and to account for individual differences. This article proposes a likelihood-based, "data fixed, model variable" paradigm in which models are treated as stochastic processes in experiments with participant-to-participant variation that can be applied to a broad range of mechanistic cognitive architectures. This article discusses the implementation and implications of this view in model validation, with a concrete focus on a simple class of ACT-R models of cognition. This article is not intended as a recipe for broad application of these preliminary, proof-of-concept methods, but as a framework for communication between statisticians searching for interesting problems in the cognitive modeling sphere, and cognitive modelers interested in generalizing from deterministic to stochastic model validation, in the face of random variation in human experimental data.     

Lexical categories at the edge of the word

Language acquisition may be one of the most difficult tasks that children face during development. They have to segment words from fluent speech, figure out the meanings of these words, and discover the syntactic constraints for joining them together into meaningful sentences. Over the past couple of decades, computational modeling has emerged as a new paradigm for gaining insights into the mechanisms by which children may accomplish these feats. Unfortunately, many of these models assume a computational complexity and linguistic knowledge likely to be beyond the abilities of developing young children. This article shows that, using simple statistical procedures, significant correlations exist between the beginnings and endings of a word and its lexical category in English, Dutch, French, and Japanese. Therefore, phonetic information can contribute to individuating higher level structural properties of these languages. This article also presents a simple 2-layer connectionist model that, once trained with an initial small sample of words labeled for lexical category, can infer the lexical category of a large proportion of novel words using only word-edge phonological information, namely the first and last phoneme of a word. The results suggest that simple procedures combined with phonetic information perceptually available to children provide solid scaffolding for emerging lexical categories in language development.     

论肿瘤免疫的复杂性

免疫系统是一个复杂自适应巨系统,它还具有开放复杂巨系统的所有特征。体内已建立的肿瘤是一个复杂适应系统,两者间的相互作用造就了肿瘤免疫的复杂性。本文从复杂性科学角度阐释肿瘤免疫,以期对肿瘤细胞免疫治疗的研究有所裨益。     

Minds, persons, and space: an fMRI investigation into the relational complexity of higher-order intentionality

Mental state reasoning or theory-of-mind has been the subject of a rich body of imaging research. Although such investigations routinely tap a common set of regions, the precise function of each area remains a contentious matter. With the help of functional magnetic resonance imaging (fMRI), we sought to determine which areas are involved when processing mental state or intentional metarepresentations by focusing on the relational aspect of such representations. Using non-intentional relational representations such as spatial relations between persons and between objects as a contrast, the results ascertained the involvement of the precuneus, the temporal poles, and the medial prefrontal cortex in the processing of intentional representations. In contrast, the anterior superior temporal sulcus and the left temporo-parietal junction were implicated when processing representations that refer to the presence of persons in relational contexts in general. The right temporo-parietal junction, however, was specifically activated for persons entering spatial relations. The level of representational complexity, a previously unexplored factor, was also found to modulate the neural response in some brain regions, such as the medial prefrontal cortex and the right temporo-parietal junction. These findings highlight the need to take into account the critical roles played by an extensive network of neural regions during mental state reasoning.     

团队作业特征研究现状与展望

团队作业特征是团队有效性模型中的重要输入变量,是团队绩效差异的贡献因素。作业特征在个体与团队层面的相关理论基础表明,团队作业特征包括技能多样性、作业同一性、作业重要性、反馈、自主性、作业互依性、作业复杂性七个核心要素。以此为基础介绍了作业特征在个体与团队层面的相关效应研究;团队作业特征模型测量、作业特征作用机制、作业特征要素的深入研究则可作为未来研究的重点     

平衡秤任务复杂性的事前与事后分析

任务复杂性的分析和评估是心理测量学和认知心理学都非常关注的重要主题。以264名小学四、五、六年级儿童为被试,平衡秤任务为研究材料,考察任务在未旋转时第一个因素上的载荷(事后分析)能否作为评价任务复杂性的一个指标,以及关系-表征复杂性模型对平衡秤任务复杂性分析(事前分析)的有效性两个问题。结果表明:平衡秤任务施测后所得所有项目的因素载荷与其难度之间没有显著正相关,即因素载荷的高低没有反映平衡秤任务复杂性的大小;而基于关系-表征复杂性模型对任务的事前分析所确定的任务等级复杂性和知识经验对任务难度的解释率为95.0%,可见,关系-表征复杂性模型提供的分析任务复杂性的思路和方法是较为合理的。