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.     

A computational analysis of general intelligence tests for evaluating cognitive development

The progression in several cognitive tests for the same subjects at different ages provides valuable information about their cognitive development. One question that has caught recent interest is whether the same approach can be used to assess the cognitive development of artificial systems. In particular, can we assess whether the ‘fluid’ or ‘crystallised’ intelligence of an artificial cognitive system is changing during its cognitive development as a result of acquiring more concepts? In this paper, we address several IQ tests problems (odd-one-out problems, Raven’s Progressive Matrices and Thurstone’s letter series) with a general learning system that is not particularly designed on purpose to solve intelligence tests. The goal is to better understand the role of the basic cognitive operational constructs (such as identity, difference, order, counting, logic, etc.) that are needed to solve these intelligence test problems and serve as a proof-of-concept for evaluation in other developmental problems. From here, we gain some insights into the characteristics and usefulness of these tests and how careful we need to be when applying human test problems to assess the abilities and cognitive development of robots and other artificial cognitive systems.     

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。     

The emergence of the ecological mind in Hua‐Yen/Kegon Buddhism and Jungian psychology

The complexity associated with deep interconnectedness in nature is beginning to be articulated and elaborated in the field of ecological studies. While some parallels to the psyche have been made and the field of Eco‐psychology has been developing, Jung's explicit contribution by way of the image of rhizomes has not been considered in detail. Philosopher Gilles Deleuze acknowledges borrowing the term from Jung, though he disagreed with Jung's Empedoclean use of the term. The paper presents some fundamental properties of rhizomes along with contemporary scientific research on mycorrhizal (fungal) networks. Comparisons are made, first with classical symbolic forms, demonstrating some overlap but also some differences. Then comparison of rhizomal networks is made to those found both in mammalian brains and in recent images of the ‘cosmic web’. While no hard conclusions can be drawn from these images, their remarkable similarities are suggestive of a need to reconsider what is meant by ‘intelligence’. The cosmic web is one of the largest structures in the known universe (clusters of galaxies which form into filaments and walls) with empty spaces in between. Exploration of the structure of this web leads to a discussion of dark matter and dark energy, current hot topics in science, probing into the mysteries of our ‘Big‐Bang’ cosmology. An additional comparison of the emerging image of the universe as a whole with the ancient Chinese Buddhist cosmological vision from the Hua‐Yen School (Kegon in Japan) again reveals profound parallels. The potential convergence of aspects of subjective, or meditative, explorations with objective scientific constructions is striking and offers links between East and West, as well as potential confirmation of the objective aspects of empathy.     

Diversity and Community: The Role of Agent‐Based Modeling

Community psychology involves several dialectics between potentially opposing ideals, such as theory and practice, rights and needs, and respect for human diversity and sense of community. Some recent papers in the American Journal of Community Psychology have examined the diversity‐community dialectic, some with the aid of agent‐based modeling and concepts from network science. This paper further elucidates these concepts and suggests that research in community psychology can benefit from a useful dialectic between agent‐based modeling and the real‐world concerns of community psychology.