Law,discipline and governance based on cognitive process simulation – analysis of legal forms in the modern rights relationship

People are becoming more and more humanized in the process of understanding the law. According to the right to discipline, the law has its own core setting factors, while some limits can't reach people's desire. Therefore, the legal and illegal mode of transcending rights is very important. In order to analyze the legal form of modern rights, in this paper, the cognitive learning and memory process of human brain were simulated through the artificial neural network and the understanding of human brain structure, and the role of law, discipline and governance was reflected. In the study, the structure and algorithm of the model neural network were optimized, the memory forgetting curve mechanism that can simulate the human brain was introduced, and thus the network recognition rate was improved. And in the algorithm, the calculation of matching degree was avoided, and the computational complexity was reduced to the sample. Then the sample was compared with the SOM, ART1, and PNN algorithms. The experimental simulation results show that the recognition speed of this sample is 1.9 times faster than that of ART1, 58 times than that of SOM, and 1.5 times than that of the PNN network.     

自我信息的反应抑制优势：来自神经振荡的证据

为探明个体对自我信息的反应抑制神经机制,记录了被试在完成面孔识别的停止信号任务时的脑电信号。神经振荡结果显示,反应任务中,加工自我面孔引发了更大的同步化δ节律和去同步化β节律;停止任务中,自我面孔引发了更大的去同步化β节律,特别在大脑前额区和中线上。表明,自我信息的反应抑制优势发生在抑制控制阶段,在于增强的β节律的去同步化促进了运动准备,提高了后续的动作抑制的速度。     

A predictive coding model of gaze shifts and the underlying neurophysiology

A comprehensive model of gaze control must account for a number of empirical observations at both the behavioural and neurophysiological levels. The computational model presented in this article can simulate the coordinated movements of the eye, head, and body required to perform horizontal gaze shifts. In doing so it reproduces the predictable relationships between the movements performed by these different degrees of freedom (DOFs) in the primate. The model also accounts for the saccadic undershoot that accompanies large gaze shifts in the biological visual system. It can also account for our perception of a stable external world despite frequent gaze shifts and the ability to perform accurate memory-guided and double-step saccades. The proposed model also simulates peri-saccadic compression: the mis-localization of a briefly presented visual stimulus towards the location that is the target for a saccade. At the neurophysiological level, the proposed model is consistent with the existence of cortical neurons tuned to the retinal, head-centred, body-centred, and world-centred locations of visual stimuli and cortical neurons that have gain-modulated responses to visual stimuli. Finally, the model also successfully accounts for peri-saccadic receptive field (RF) remapping which results in reduced responses to stimuli in the current RF location and an increased sensitivity to stimuli appearing at the location that will be occupied by the RF after the saccade. The proposed model thus offers a unified explanation for this seemingly diverse range of phenomena. Furthermore, as the proposed model is an implementation of the predictive coding theory, it offers a single computational explanation for these phenomena and relates gaze shifts to a wider framework for understanding cortical function.     

Multi-layer architecture for adaptive fuzzy inference system with a large number of input features

The Sugeno adaptive fuzzy neural network using training data is a good approximation to model different systems. The large number of adaptive neuro-fuzzy inference system (ANFIS) input features is a major challenge in using ANFIS and is not applicable with increased parameters. We present a solution for many input features solving modular problems; we created a multi-layer architecture of SUB-ANFIS (MLA-ANFIS) for this purpose. Different topologies were created with various combinations of multiple input features, and an error indicator was calculated for each combination of topologies. Finally, the best topology was chosen among the states with the highest possible performance. We implemented a multi-layered approach based on 365-day concrete compressive strength data with eight input features and the optimized MLA-ANFIS topology (5-3-1) for this purpose from different ANFIS topologies and neural networks. Finally, the results from five other datasets prove the impact of the proposed MLA-ANFIS approach compared to the neural network method.     

急性应激对威胁刺激注意定向和注意解除的影响:认知神经机制研究

急性应激和注意偏向是焦虑障碍和创伤后应激障碍发生和症状保持的两个重要因素。急性应激导致交感神经系统激活以及儿茶酚胺和糖皮质激素分泌增加,因而影响对威胁刺激的注意偏向。但是急性应激如何影响注意偏向中的注意定向和注意解除尚不清楚。本项目采用点探测任务、威胁线索空间提示任务,结合恐惧条件反射、眼动和事件相关电位技术,研究急性应激对注意定向和注意解除影响的认知神经机制。研究结果可为治疗焦虑和创伤后应激障碍提供支持,为公共卫生管理政策的制定提供建议。     

视频游戏中的化身认同

化身认同是个体在使用和体验游戏化身的过程中,自我知觉发生暂时性改变,并与化身在情绪和认知上的联系暂时加强的心理现象,它为理解化身效应提供了新视角。目前,化身认同的测量模型主要有三维和四维结构模型,其神经机制也得到初步揭示。影响化身认同的因素主要包括游戏自身特点和个体因素。影响效果方面,化身认同与游戏体验、游戏成瘾、攻击行为和自我同一性的关系是目前关注的焦点。未来的研究,仍需深入探讨化身认同的概念与结构,研发更加有效的测量工具,拓展研究方法,丰富研究变量,并加强应用研究。     

情节式未来思考中目标加工研究进展

情节式未来思考是个体将自我投射到未来以预先经历某事件的能力,个人目标加工在情节式未来思考中发挥着重要作用。目前对情节式未来思考中目标加工的行为学研究通常将其划分为目标过程模拟和目标结果模拟两种类型,以探究其对执行意图的影响为主;脑机制神经影像学研究则聚焦于默认网络的内侧前额叶和后扣带的重要作用,以及默认网络、额顶控制网络和奖赏区的协同作用。未来研究应进一步探讨情节式未来思考目标加工的形式、年龄差异及其与时间距离的关系。     

认知神经研究中的积极共情

积极共情指个体对他人积极情绪状态的理解和间接分享过程。虽然它与消极共情在产生过程中都依赖于镜像神经系统和心理理论系统的活动, 但是两者在产生难度上不同。对于积极共情情感如何在大脑中表征的, 不同的研究者观点各异：一些认为与消极共情一致, 都集中在脑岛及其相关脑区; 而另一些则认为是大脑的愉悦系统。关于积极共情影响因素的研究主要集中于共情主体和客体的关系方面。今后需要进一步了解积极共情在产生机制和情感表征上的特点, 拓展其影响因素的研究并展开对特质积极共情神经基础的探讨。     

不安全依恋者注意偏向的形成机制及神经基础

不安全依恋者的注意偏向是指依恋焦虑和回避个体对依恋信息产生或趋近或回避的注意偏好, 这一注意偏好使得个体形成了处理与依恋对象关系的特殊认知机制：依恋回避个体偏好采用防御性机制, 倾向于回避对依恋信息的注意; 依恋焦虑个体偏好采用夸大性机制, 倾向于夸大威胁性信息, 因而会积极寻求与依恋对象的亲近。不安全依恋者注意偏向的差异主要体现在情绪信息、痛觉感受和工作记忆三个方面; 加工阶段特征主要涉及P1、N1波等代表的注意自动加工和LPP波代表的注意控制加工; 脑网络上主要包括两个子网络, 即负责情绪评估的边缘系统和负责情绪调节的以前额叶为代表的神经网络。未来研究中更应该关注刺激物的生态效度, 检验依恋系统是否激活, 不安全依恋者注意偏向的自动加工和控制加工阶段的关系, 不安全依恋者注意偏向产生的分子遗传机制以及注意偏向的跨文化研究。