失用性失写的脑机制

失用性失写是指人们知道该如何书写, 但实际上却不会书写或错误书写的一种现象。失用性失写涉及的神经网络包括皮层与皮层连接、皮层与皮质下连接。其中前者包括额-顶叶相关脑区的连接、顶-枕叶相关脑区的连接以及额-顶-枕相关脑区的连接, 这些神经网络分别负责操作空间表征图像、回忆以及检索字母的形状等; 后者包括小脑与额-顶叶的连接、左丘脑-大脑皮质的连接以及纹状体-内囊-左额顶叶的连接等, 它们分别与图像输出程序、书写运动过程、操作指令的执行过程以及字素形成过程等有关。今后的研究应该集中在完善失用性失写的研究范式、深入探讨失用性失写的心理机制以及推动其康复工作的开展等方面。     

On simulating one-trial learning using morphological neural networks

“Learning once, remembering forever”, this wonderful cognitive phenomenon sometimes occurs in the learning process of human beings. Psychologists call this psychological phenomenon “one-trial learning”. The traditional artificial neural networks can simulate the psychological phenomenon of “implicit learning”, but can’t simulate the cognitive phenomenon of “one-trial learning”. Therefore, cognitive psychology gives a challenge to the traditional artificial neural networks. From two aspects of theory and practice in this paper, the possibility of simulating this kind of psychological phenomenon was explored by using morphological neural networks. This paper takes advantage of morphological associative memory networks to realize the simulation of “one-trial learning” for the first time, and gives 5 simulating practical examples. Theoretical analysis and simulation experiments show that the morphological associative memory networks are a higher effective machine learning method, and can better simulate the cognitive phenomenon of “one-trial learning”, therefore provide a theoretical basis and technological support for the study of intelligent science and cognitive science.     

An accurate and efficient multi-category edge detection method

Edge detection plays an important role in image processing. With the development of deep learning, the accuracy of edge detection has been greatly improved, and people have more requirements for edge detection tasks. Most edge detection algorithms are binary edge detection methods, but there are usually multiple categories of edges in an image. In this paper, we present an accurate multi-category edge detection network, the richer category-aware semantic edge detection network (R-CASENet). In order to make full use of convolutional neural network’s powerful feature expression capabilities, we attempt to use more information from feature maps for edge feature extraction and classification. Using the ResNet101 network as the backbone, firstly we merge the building blocks in different composite blocks and down-sample to obtain the feature maps. Then we fuse the feature maps in different composite blocks to obtain the final fused classifier. Experimental results show that R-CASENet can achieve state-of-the-art performance on the large SBD dataset. Furthermore, to get precise one-pixel width edges, we also propose an edge refinement network (ERN) structure. The proposed scheme is an end-to-end method and the proposed ERN can reduce redundant points and improve computational efficiency, especially for further image processing.     

Populations of spiking neurons for reservoir computing: Closed loop control of a compliant quadruped

Compliant robots can be more versatile than traditional robots, but their control is more complex. The dynamics of compliant bodies can however be turned into an advantage using the physical reservoir computing framework. By feeding sensor signals to the reservoir and extracting motor signals from the reservoir, closed loop robot control is possible. Here, we present a novel framework for implementing central pattern generators with spiking neural networks to obtain closed loop robot control. Using the FORCE learning paradigm, we train a reservoir of spiking neuron populations to act as a central pattern generator. We demonstrate the learning of predefined gait patterns, speed control and gait transition on a simulated model of a compliant quadrupedal robot.     

赌博障碍的认知功能缺陷及神经基础

赌博障碍是指持续且反复的赌博行为,给个人、家庭和社会都带来了严重后果,近年来受到越来越多研究者的关注。本研究总结了赌博障碍的认知功能缺陷及其神经基础,主要集中在如下四个方面：①认知扭曲、②奖赏和惩罚敏感性、③注意偏向和④决策。未来研究应多从认知神经科学角度深入探究赌博障碍的发生机制和发展过程,关注大脑结构变化及功能网络改变,并将其整合到一个统一的神经生物机制框架中,找到更加有效的干预和治疗手段。     

愉快面孔识别优势及其认知神经机制

愉快面孔识别优势表现为被试对高兴面孔比对其他情绪面孔的识别正确率更高、反应时更短。大量研究以简笔画和面孔图片为材料, 在情绪分类任务和视觉搜索任务中均发现这一优势。该优势存在诊断性价值假说、情绪独特性假说和出现频率假说三种不同的理论解释。近年来, 研究者采用ERP技术发现这一优势形成于反应选择阶段, 但其起始阶段尚无一致结论。未来可借助fMRI技术进一步研究其认知神经机制。     

视知觉学习的认知与神经机制研究

知觉学习是指由于训练或经验而引起的长期稳定的知觉变化,是一种内隐性的学习。近20年来,视知觉学习的大量研究结果提示大脑皮层的各个区域,甚至包括初级感觉皮层,在成熟之后仍然具有一定的可塑性。该文根据近年来的研究进展,对视知觉学习在大脑的什么地方,什么时候,以何种方式发生等热点问题进行了探讨。研究提示,视知觉学习涉及了包括初级视皮层在内的多个大脑皮层,并且存在一种自上而下的调控机制;视知觉学习可以在不同的时间尺度上发生,快速学习之后将伴随着慢速学习;通过视知觉学习,人们对于复杂物体的表征将从高级皮层区域移向低级皮层区域,任务执行也将趋于自动化     

持续性植物状态若干问题的探讨

明确意识的含义及意识障碍的分类是分析持续性植物状态的前提。根据多年临床经验对持续性植物状态的定义、评分标准、诊断与鉴别诊断进行深入割析。植物状态的研究取得相当进展,但从诊断、评分到治疗手段仍面临诸多困惑,而神经干细胞移植和神经电刺激术是未来希望所在。     

儿童行为抑制的生理机制研究述评

行为抑制指儿童不愿意接近陌生刺激,并带有害羞、恐惧和焦虑等消极情绪的气质类型,具有中等程度的稳定性和特定生理基础,对儿童日后情绪和行为发展具有较大影响。与非行为抑制个体相比,在特定的刺激条件下,行为抑制个体的杏仁核、纹状体和右前额区域的激活水平可能较高,心率和可的松水平也倾向于较高。目前,研究者已结合行为和生理学方法来探讨行为抑制的生理机制,取得了一些重要的进展。但是,也存在一些问题有待于进一步探讨。     

智商常态人群的智力个体差异研究述评

智力功能个体差异星正态分布有不同观点：g因素决定特殊能力分化程度差异论、因素搭配差异论;单一认知机能、认知机能系统中的一个或者几个认知机能缺陷影响智力功能差异论;认知发展理论的要素功能大小和要素关联关系强弱、结构差异论;文化活动结构差异和遗传进化的神经效率差异论;神经活动特性水平和神经活动区域效率差异、人格中介情景任务和人