创造性思维的脑机制

创造性思维是创造性的核心。近年来,脑电和脑成像技术的发展为研究创造性思维的神经基础提供了有力的技术支持,对创造性思维的脑机制研究取得了较大进展。创造性思维的脑机制研究主要包括顿悟的脑机制、发散性思维的脑机制、远距离联想的脑机制、言语创造性和图画创造性的对比的脑机制研究。研究结果显示创造性思维需要多个脑区的参与,因不同的认知任务其关键脑区而有所不同。对创造性思维的脑机制研究进行了总结,对这些研究可能存在创造性思维究竟应该定义为“领域一般的”还是“领域特殊的”的解释进行了讨论,并指出了研究中可能存在的基线任务设置问题和未来研究中需要在研究手段、研究设计、研究领域等方面加以改进的建议     

人机交互过程中认知负荷的综合测评方法

设计模拟网络引擎搜索和心算双任务实验,分析主观评定、绩效测量和生理测量三类评估指标对认知负荷变化的敏感性;采用因素分析、BP神经网络和自组织神经网络三种建模方法,探索人机交互过程中认知负荷的综合评估建模方法。结果显示：心理努力、任务主观难度、注视时间、注视次数、主任务反应时、主任务正确率6个指标对认知负荷变化敏感;采用多维综合评估模型对双任务作业认知负荷进行测量总体上比采用单一评估指标的测量更为有效。BP网络和自组织神经网络两种神经网络模型对认知负荷的测量结果优于传统的因素分析方法     

Post‐traumatic functional recovery and reorganization in animal models: A theoretical and methodological challenge

Studies addressing cerebral functional localization face methodological and theoretical problems. Lesion experiments expect that when a functionally specialized structure is missing, its function can be deduced from the resulting impairments. Mostly, however, initial impairments are partially or fully eliminated through functional recovery. Apparently, such a recovery contradicts the notion of functional localization. In order to understand the mechanisms of recovery, improved methodology and a new theoretical framework are required. Insights into the mechanisms of recovery can be achieved by using “challenge” techniques, where functionally recovered individuals are exposed to organic and behavioral challenges, e.g. pharmacological manipulations or additional lesions, as well as modified test situations. Using such methods, a number of principles of functional recovery have emerged. We evaluate some of the available theories of post‐traumatic recovery against these principles and find that none of them can account for the principles. Finally, we present a new conceptual framework – the Reorganization of Elementary Functions (REF) model. This model reconceptualizes the term “function”, suggests mechanisms of post‐traumatic reorganizations, and resolves the contradiction between localization and functional recovery.     

"心理理论"的神经机制:来自脑成像的证据

"心理理论"是认知发展领域的研究热点之一,迄今已积累了大量行为研究的证据.心理理论具有领域特异的模块化认知机制,脑成像研究中也发现心理理论任务激活前额叶皮质等多个模块区域.论文阐述了真实表征与错误信念、心智互动等心理理论推理的神经机制,总结了该领域存在的问题并对今后研究的发展趋势进行了展望.     

Temperament, Development, and Personality

ABSTRACT— Understanding temperament is central to our understanding of development, and temperament constructs are linked to individual differences in both personality and underlying neural function. In this article, I review findings on the structure of temperament, its relation to the Big Five traits of personality, and its links to development and psychopathology. In addition, I discuss the relation of temperament to conscience, empathy, aggression, and the development of behavior problems, and describe the relation between effortful control and neural networks of executive attention. Finally, I present research on training executive attention.     

粗糙集和神经网络在心理测量中的应用

探讨当因素分析和多元回归方法的使用条件未得到满足时,是否可采用粗糙集方法进行观察变量的精简,以及是否可采用神经网络方法进行预测效度检验。理论分析了粗糙集和神经网络在心理测量中应用的可能性,并运用粗糙集对于人事干部胜任力评估数据进行分析,比较了7种离散化方法和2种约简算法构成的14种组合,发现当采用Manual方法进行离散化、遗传算法进行约简时,能够很好地对观测变量进行精简;运用概率神经网络能够比等级回归方法更好地进行预测效度检验。研究结果表明对于处理心理测量中的非等距变量,粗糙集和神经网络是非常有用的方法     

标量计时模型中的神经机制

标量计时模型中各阶段的神经机制有重叠也有分离。从当今认知神经科学的研究结果看,与内部时钟有关的神经结构有小脑、基底神经节、前额皮质、前运动辅助皮质及顶叶下回皮质等;与记忆阶段有关的神经结构有基底神经节、背外侧前额皮质、右侧额下皮质及外侧前运动皮质等;与决策阶段有关的神经结构有背外侧前额皮质、前扣带回、高级颞叶皮质和基底神经节等。文章还从神经机制角度论证了计时的标量特性,讨论了今后研究值得注意的三个问题,即研究结果的确定性、研究手段的局限性以及该模型的适用性     

假设形成与检验的神经机制

假设形成与检验是解决任何复杂问题的重要思维工具, 是人们发现规则, 形成概念, 建立假说, 获得知识的基础。为进一步考察这一思维能力的神经机制, 本项目在已有行为及脑电研究的基础上以“类别概括－规则发现”为研究范式, 给被试提供包含多个知觉维度的刺激, 要求被试通过知觉观察与反馈学习发现基于类别的规则(假设)。本项目重点考察被试在此任务中选择与收敛假设,以及加工否定(冲突)信息的脑机制, 并尝试揭示假设形成与检验的个体发展特征。     

Efficiency investigation from shallow to deep neural network techniques in human activity recognition

In the last years, several researchers measured different recognition rates with different artificial neural network (ANN) techniques on public data sets in the human activity recognition (HAR) problem. However an overall investigation does not exist in the literature and the efficiency of complex and deeper ANNs over shallow networks is not clear. The purpose of this paper is to investigate the recognition rate and time requirement of different kinds of ANN approaches in HAR. This work examines the performance of shallow ANN architectures with different hyper-parameters, ANN ensembles, binary ANN classifier groups, and convolutional neural networks on two public databases. Although the popularity of binary classifiers, classifier ensembles and deep learning have been significantly increasing, this study shows that shallow ANNs with appropriate hyper-parameters in combination with extracted features can reach similar or higher recognition rate in less time than other artificial neural network methods in HAR. With a well-tuned ANN we outperformed all previous results on two public databases. Consequently, instead of the more complex ANN techniques, the usage of simple ANN with two or three layers can be an appropriate choice for activity recognition.