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。     

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。     

An effective daily box office prediction model based on deep neural networks

The task of the daily box office prediction model is to build a dynamic prediction model to rolling forecast daily box office. It is a complex task as the movie box office has a short life cycle, and the static data and dynamic data that affect the trend of box office are heterogeneous. This paper proposes an end-to-end deep learning model for daily box office prediction, called Deep-DBP which consists of temporal component and static characteristics component. The temporal component is the main component which uses LSTM to learn the temporal dependencies between data points. The static characteristics component is an auxiliary component and it integrates static characteristics to improve prediction effect. The Deep-DBP can overcome the problems that the ARIMA and traditional ANN model cannot solve. The structure of input and output proposed in the model can well handle short time series prediction problem. It is a successful case in dealing with multi-source and multi-view data, addition of static characteristics component reduces the prediction error by 7%. The prediction error of Deep-DBP is 30.1%, which is better than that of the previous model. The experiment proved that the more training data collected, the better the prediction effect.     

宽恕心理的行为测量及认知神经机制

宽恕是一个复杂的心理过程,被认为是对冒犯者的亲社会化转变的过程,包括认知、情绪、动机和行为上的改变。本文回顾了国内外宽恕心理的行为测量范式和认知神经机制研究相关的成果,发现宽恕心理的行为测量范式能够揭示宽恕相关的心理过程;认知神经机制的研究发现宽恕心理过程主要涉及负责社会认知、共情和认知控制等功能的脑区。未来的研究应关注宽恕心理行为测量范式的有效性和揭示内容的一致性、宽恕心理的认知和脑神经基础。     

视频游戏对认知能力的影响及其神经基础

视频游戏是一类需要借助视听设备并基于一定剧情进行操作的游戏。先前研究大多关注暴力视频游戏对攻击等负面行为的影响,但本文着重探讨视频游戏对个体认知能力的积极影响及内在神经基础,以辩证看待视频游戏对个体心理和行为的作用。本文对前人研究归纳梳理发现,视频游戏训练能使个体认知能力得到持久改善,同时论述了视频游戏中脑神经基础和奖赏预期对认知能力的调控作用。未来研究应在规范视频游戏训练技术的基础上,用其干预靶脑区以提升个体特定脑功能。