亲社会行为的认知过程及脑神经基础

亲社会行为是指有利于他人和社会的行为,包括合作、分享、助人、安慰等。亲社会行为产生主要涉及几种认知过程:对他人行为和情绪的注意、社会信息加工、对结果的奖赏预期、社会规范表征、自我控制、以及社会信息整合与价值计算等。基于这些认知过程,研究发现,亲社会行为主要与前脑岛和前扣带回、默认网络背内侧子系统、奖赏系统以及前额叶皮层等神经区域有关,因此提出亲社会行为共同的认知-脑神经回路。未来可以对亲社会行为脑神经基础的共性、功能连接以及跨文化研究等方面做进一步探讨。     

语言和情境对具体概念感知运动仿真的影响

具体概念加工中的感知运动仿真是概念表征的核心加工过程。本研究系统探讨了语言因素(语言类型：第一语言和第二语言)和情境因素(知觉情境：空间知觉情境和语义知觉情境)对具体概念加工中感知运动仿真的影响。实验1采用语义相关判断范式探讨了第二语言加工过程中是否存在感知运动仿真, 以及第二语言中的仿真和第一语言中的仿真是否存在差异。研究发现, 第二语言加工中依然存在感知运动仿真, 但是第一语言的感知运动仿真具有一定的优势。实验2采用语义相关判断范式及其变式, 通过2个分实验分别探讨了个体加工概念时空间知觉信息和语义知觉信息对于概念表征过程中感知运动仿真的影响。研究发现, 无论是在较弱的空间信息知觉条件下还是在较浅的语义信息知觉条件下, 具体概念加工过程中都产生了感知运动仿真。本研究的发现弥补了知觉符号理论未对第二语言中的感知运动仿真提出针对性预测的不足, 表明感知运动仿真具有一定的跨语言稳定性。同时, 具体概念加工中的感知运动仿真不受空间信息和语义信息的调节, 这表明感知运动仿真能在一定程度上自动化产生。     

内隐序列学习表征机制探究：眼动证据

内隐序列学习的表征机制是内隐学习研究领域的基本问题, 还存在争议。采用眼动追踪技术, 通过3个实验探讨内隐序列学习的表征机制。结果发现, 知觉序列混合眼跳和反应序列混合眼跳条件下发生序列学习; 朝向眼跳和反向眼跳条件下发生序列学习; 有、无分心反向眼跳下发生序列学习, 两者序列学习量差异不显著。整个研究表明, 内隐序列学习的表征依赖于序列信息。     

Augmented language model with deep learning adaptation on sentiment analysis for E-learning recommendation

Sentiment Analysis is considered as an important research field in text mining, and is significant in recommendation systems and e-learning environments. This research proposes a new methodology of e-learning hybrid Recommendation System Based on Sentiment Analysis (RSBSA) by leveraging tailored Natural Language Processing (NLP) and Convolutional Neural Network (CNN) techniques, to recommend appropriate e-learning materials based on learner’s preferences. Integration is done on fine-grained sentiment analysis models, to classify text reviews of e-content posted on e-learning platform. Two enhanced language models based on ‘Continuous Bag of Word’ and ‘Skip-Gram’ are introduced. Moreover, three resilient language models based on the hybrid language techniques are developed to produce a superior vocabulary representation. These models were trained using various CNN models to predict ratings of resources from online reviews provided by learners. To accomplish this, a customizable dataset ‘ABHR-1′ is used, which is derived from e-content' reviews with corresponding ratings labeled [1–5]. The proposed models are evaluated and tested using ABHR-1 and two public datasets. According to the simulation results, Multiplication-Several-Channels-CNN model outperformed other models with an accuracy of 90.37 % for fine-grained sentiment classification on 5 discrete classes and the empirical results are compared.     

低社会经济地位影响自我调节的神经机制

自我调节是个体为了实现目标并适应不断变化的环境而监控和调节自己的认知、情绪和行为的能力, 在成就、人际交往和健康等各个领域发挥着作用, 被视为是人类成功和幸福的关键。然而, 大量研究发现个体的社会经济地位越低, 自我调节能力越差。为了提高低社会经济地位者的自我调节能力, 必须深入考察低社会经济地位影响自我调节的机制。神经科学为此提供了独特而重要的信息：低社会经济地位改变了背外侧前额叶皮层、扣带回、腹内侧前额叶、杏仁核、海马体、腹侧纹状体的结构和功能, 进而影响了自我调节的各个成分(认知调节、情绪调节、行为调节)。未来研究除了对神经机制中每条因果链进行更严格地考察外, 还应将神经生物学与发展心理学联系起来深入揭示不同发展阶段低社会经济地位对自我调节的独特影响机制, 并关注低社会经济地位者在神经和行为层面特定反应的适应性, 在此基础上开发出系统、持续、有效的干预方案。     

Frege Puzzles and Mental Files

This paper proposes a novel conception of mental files, aimed at addressing Frege puzzles. Classical Frege puzzles involve ignorance and discovery of identity. These may be addressed by accounting for a more basic way for identity to figure in thought—the treatment of beliefs by the believer as being about the same thing. This manifests itself in rational inferences that presuppose the identity of what the beliefs are about. Mental files help to provide a functional characterization of a mind capable of this presupposition, but more must be said to show how it may be rational. I argue that this can be done by drawing out the way in which mental files interact with a thinker's motivational states and so come to have normative functional properties. I show how this theory works better than some other treatments of mental files.