Restructuring partitioned knowledge: the role of recoordination in category learning

Knowledge restructuring refers to changes in the strategy with which people solve a given problem. Two types of knowledge restructuring are supported by existing category learning models. The first is a relearning process, which involves incremental updating of knowledge as learning progresses. The second is a recoordination process, which involves novel changes in the way existing knowledge is applied to the task. Whereas relearning is supported by both single- and multiple-module models of category learning, only multiple-module models support recoordination. To date, only relearning has been directly supported empirically. We report two category learning experiments that provide direct evidence of recoordination. People can fluidly alternate between different categorization strategies, and moreover, can reinstate an old strategy even after prolonged use of an alternative. The knowledge restructuring data are not well fit by a single-module model (ALCOVE). By contrast, a multiple-module model (ATRIUM) quantitatively accounts for recoordination. Low-level changes in the distribution of dimensional attention are shown to subsequently affect how ATRIUM coordinates its modular knowledge. We argue that learning about complex tasks occurs at the level of the partial knowledge elements used to generate a response strategy.     

High regularities in eye-movement patterns reveal the dynamics of the visual working memory allocation mechanism

With only two to five slots of visual working memory (VWM), humans are able to quickly solve complex visual problems to near optimal solutions. To explain the paradox between tightly constrained VWM and impressively complex human visual problem-solving ability, we propose several principles for dynamic VWM allocation. In particular, we propose that complex visual information is represented in a temporal manner using only a few slots of VWM that include global and local visual chunks. We built a model of human traveling salesman problem solving based on these principles of VWM allocation and tested the model with eye-movement data. Exactly as the model predicted, human eye movements during traveling salesman problem solving have precise quantitative regularities with regard to both the general statistical pattern of attentional fixations and how they vary across individuals with different VWM capacities. Even though VWM capacity is very limited, eye movements dynamically allocate VWM resources to both local and global information, enabling attention to fine details without loss of the big picture.     

创造力的脑结构与脑功能基础

从脑结构和脑功能两方面对创造力的脑神经基础进行了评述。就创造力的脑结构而言,尸体脑解剖研究表明创造力可能与顶叶与角回有关;活体脑结构成像研究则显示,创造力主要与额叶、扣带回以及皮下白质或灰质浓度有关。就创造力的脑功能而言,任务取向研究表明创造力任务主要激活了额叶和顶叶及少数其他皮层区域;而个体差异取向研究则表明创造力被试激活了右侧额叶、大脑皮层以及小脑的某些区域。未来研究需在加强脑结构影像研究基础上,注重从被试抽样和筛选等方面细化任务模式和个体差异模式的创造力研究,以获得更一致的结果。     

意识与注意的关系-注意对意识产生的充分性与必要性探析*

意识与注意的关系是目前研究的热点之一,但一直存在争论。本文系统梳理了意识与注意之间关系的观点演变,从早期认为意识依赖于注意,到近期认为意识与注意完全分离,还从神经学研究角度探讨了意识与注意的关系,并就两者关系提出了新的看法。     

模糊决策的认知神经机制

模糊决策是特殊、复杂的风险决策, 还是一种独立的决策类型, 是当前认知神经科学争论的热点问题。一系列的fMRI研究分别得出了不同结论, 但大多数证据支持模糊决策和风险决策之间存在分离, 模糊决策有其独特的决策机制; 模糊决策的认知神经机制也是一个亟待解决的问题。因此本研究拟应用事件相关电位技术、生物反馈技术和基因技术, 采用IGT和GDT任务范式, 通过网络成瘾人群和正常人群的对比研究, 去探索模糊决策和风险决策之间的分离; 应用事件相关电位技术和磁共振技术, 采用IGT范式和选瓶任务范式, 研究模糊决策的认知神经机制; 并从临床角度进一步验证上述结果。该项目的开展, 有助于拓广模糊决策的研究领域和视野, 对理解人类在模糊情境下的决策机制以及模糊决策和风险决策之间的关系, 具有重要的理论意义; 对临床上成瘾人群、脑损伤患者的认知诊断和治疗以及现实中企业和个人的决策, 具有重要的参考价值。     

Philosophy and Science Dialogue: Free Will

In this dialogue Derk Pereboom and Marcel Brass discuss the free will problem from the perspective of philosophy and cognitive neuroscience. First, they give their opinion on how the two disciplines contribute to the free will problem. While Pereboom is optimistic regarding the contribution of science, Brass is more pessimistic and questions the usefulness of an empirical approach to the question whether free will exists or not. Then they outline their position on the free will problem. The idea of a transcendental agent is discussed in more detail. Furthermore, it is discussed whether free will scepticism is a politically, socially, psychologically viable position. Pereboom argues that promoting the idea of free will scepticism can have a positive impact on retributive emotions and the political practice regarding retributive punishment. Brass argues that retributive emotions are deeply rooted in evolution and therefore difficult to change via high-level beliefs about free will. Finally, the future of the free will debate is discussed. Both agree that the dialogue between philosophy and psychology should be intensified. Philosophy can benefit from taking empirical research more seriously. Psychology and neuroscience can benefit from philosophy by appreciating the sophistication and conceptual clarity of the philosophical debate. Both have to find a common language and define common problems that can be tackled from both perspectives.     

Philosophy and Science Dialogue: Mental Causation

This paper is a dialogue between Thalia Wheatley and Terence Horgan. Horgan maintains that philosophy is a broadly empirical discipline, and that philosophical theorizing about how concepts work treats certain intuitions about proper concept-usage as empirical data. He holds that the possibility of strong multiple realizability undermines the psychophysical identity theory. He holds that the concept of causation is governed by implicit contextual parameters, and that this dissolves Kim’s problem of “causal exclusion.” He holds that the concept of free will is governed by implicit contextual parameters, and that free-will attributions are often true, in typical contexts, even if determinism is true. Thalia Wheatley holds that the concept of multiple realizability hinges on the level of abstraction discussed and that neuroscientific data does not yet support multiple realizability of mental states from specific, high resolution brain states. She also holds that compatibilism redefines the concept of free will in ways that bear little resemblance to the common understanding―that of being free to choose otherwise in the moment. She maintains that this folk understanding is incompatible with the brain as a physical system and is not rescued by concepts of context and capacity.     

A computational model of spatial visualization capacity

Visualizing spatial material is a cornerstone of human problem solving, but human visualization capacity is sharply limited. To investigate the sources of this limit, we developed a new task to measure visualization accuracy for verbally-described spatial paths (similar to street directions), and implemented a computational process model to perform it. In this model, developed within the Adaptive Control of Thought-Rational (ACT-R) architecture, visualization capacity is limited by three mechanisms. Two of these (associative interference and decay) are longstanding characteristics of ACT-R’s declarative memory. A third (spatial interference) is a new mechanism motivated by spatial proximity effects in our data. We tested the model in two experiments, one with parameter-value fitting, and a replication without further fitting. Correspondence between model and data was close in both experiments, suggesting that the model may be useful for understanding why visualizing new, complex spatial material is so difficult.     

Seeing is believing: the effect of brain images on judgments of scientific reasoning

Brain images are believed to have a particularly persuasive influence on the public perception of research on cognition. Three experiments are reported showing that presenting brain images with articles summarizing cognitive neuroscience research resulted in higher ratings of scientific reasoning for arguments made in those articles, as compared to articles accompanied by bar graphs, a topographical map of brain activation, or no image. These data lend support to the notion that part of the fascination, and the credibility, of brain imaging research lies in the persuasive power of the actual brain images themselves. We argue that brain images are influential because they provide a physical basis for abstract cognitive processes, appealing to people's affinity for reductionistic explanations of cognitive phenomena.