The Cognitive Social Network in Dreams: Transitivity,Assortativity, and Giant Component Proportion Are Monotonic

For five individuals, a social network was constructed from a series of his or her dreams. Three important network measures were calculated for each network: transitivity, assortativity, and giant component proportion. These were monotonically related; over the five networks as transitivity increased, assortativity increased and giant component proportion decreased. The relations indicate that characters appear in dreams systematically. Systematicity likely arises from the dreamer's memory of people and their relations, which is from the dreamer's cognitive social network. But the dream social network is not a copy of the cognitive social network. Waking life social networks tend to have positive assortativity; that is, people tend to be connected to others with similar connectivity. Instead, in our sample of dream social networks assortativity is more often negative or near 0, as in online social networks. We show that if characters appear via a random walk, negative assortativity can result, particularly if the random walk is biased as suggested by remote associations.     

社交网站使用能带来社会资本吗?

社交网站旨在维系和发展个体的人际关系网络,而社会资本是个体人际关系中潜在的、可获得的益处或资源,因此社交网站使用和社会资本存在密切关系。然而,有关一般性社交网站使用行为与社会资本关系的研究结果并不一致。针对不同类型使用行为的研究发现,特定类型的社交网站使用行为对特定类型社会资本有积极影响。社交网站中自我表露行为是获取社会资本的一种必要的途径,关系维持行为、资源动员请求行为、隐私保护行为等均是个体获取社会资本的有效行为策略。最后,就社会资本定义、线上线下社会资本存在覆盖等问题进行了探讨。     

Orienting of attention: Then and now

It is nearly 35 years since I gave the 7th Sir Frederick Bartlett lecture at Oxford University. This was published as a paper entitled “Orienting of attention in the quarterly journal”. The topic was then primarily in psychology, but now equally often in neuroscience. This paper summarizes the background of the reaction time methods used in the original paper and findings that emerged later on the sensory consequences of orienting, mainly in the visual system. It then discusses the brain network that is the source of the sensory amplification and other brain networks that are involved in attention. Next, it reviews studies of the development of attentional networks in early life. Finally, it indicates how the new tools available to explore the human brain can lead to further progress.     

An adaptive temporal-causal network model to analyse extinction of communication over time

The persistence of information communicated between humans is difficult to measure as it is affected by many features. This paper presents an approach to computationally model the cognitive processes of information sharing to describe persistence or extinction of communication in Twitter over time. The adaptive mental network model explains, for example, how an individual can experience information overflow on a topic, and how this affects the sharing of information. Parameter tuning by Simulated Annealing is used to identify characteristics of the network model that fit to empirical data from Twitter. The data collected is related to the independentism in Catalunya, Spain, which is considered a global issue with repercussion in Europe.     

An adaptive network model for pain and pleasure through spicy food and its desensitization

This paper aims to map out the adaptive causal pathways of processes underlying capsaicin consumption and the desensitization process of the TRPV1 receptor as a feedback loop together with pain and pleasure perception. In order to map out these causal capsaicin pathways, adaptive causal network modeling was applied, which is a way of modeling biological, neural, mental and social processes from an adaptive causal modeling perspective.     

On the dynamics and adaptivity of mental processes: Relating adaptive dynamical systems and self-modeling network models by mathematical analysis

In this paper, it is addressed by mathematical analysis how network-oriented modeling relates to the dynamical systems perspective on mental processes. It has been mathematically proven that any dynamical system can be modeled as a temporal-causal network model and that any adaptive dynamical system (of any order) can be modeled by a self-modeling network (of the same order).     

The influence of social networks within sports teams on athletes’ eating and exercise psychopathology: A longitudinal study

Teammates have been found to have an impact on athletes’ eating and exercise psychopathology via multiple influence mechanisms (e.g., modelling, making critical comments). However, far less is known about the role of the team social network (i.e. the pattern and strength of relationships between teammates). This novel longitudinal study aimed to explore how athletes’ eating and exercise psychopathology becomes more (convergence) or less (divergence) similar to their teammates’ over time and to explore how this varies for male and female athletes. A second aim was to identify the role of team social network variables (e.g., popularity) in determining individuals’ levels of eating and exercise psychopathology. Athletes (N = 199, mean age 18 years, n = 123 female) from 20 teams/training groups completed a survey regarding their teammate relationships and eating/exercise psychopathology (Eating Disorder Inventory-2; Athlete Compulsive Exercise Test) at three time points over a 7-month period. Significant interaction effects between time and gender were noted for athlete team variability in eating and exercise psychopathology, where both convergence and divergence of eating and exercise psychopathology was evident. In addition, being well connected to teammates, acting as the bridge between groups of teammates or being part of a cohesive team were longitudinally associated with reduced exercise psychopathology. Disordered eating and exercise prevention strategies should look to harness the behavioural convergence effect demonstrated here, by encouraging healthy eating/exercise practices among teammates. Furthermore, coaches should foster cohesive teammate relationships and be aware of how an athlete’s social positioning within their team may affect their susceptibility to exercise psychopathology.     

元认知的神经机制:元认知功能、脑区与脑网络

元认知是指个体对当前进行的认知活动的监测和调节。通过对元认知神经机制研究的梳理,归纳出两条研究主线:一条主线以具体元认知加工的脑区激活研究为主,主要考察元认知与认知过程的分离及典型元认知加工的共享性和特异性。研究发现元认知加工主要与前额叶有关,还涉及脑岛、顶叶、颞叶和楔前叶等部分脑区。另一条主线探讨广泛的元认知功能与广泛大脑网络的相关。研究提出了大脑的“元认知网络”的概念,发现脑损伤或病变造成的元认知功能损伤与脑功能网络有关,而非固定在某一特定脑区。建议未来的研究应重视四个方面的研究:元认知加工的具体脑区和脑功能网络,元认知神经机制的分离,元认知脑功能的损伤和元认知训练的改善作用,以及基于神经机制研究的元认知模型的建构与修正。     

青少年友谊网络与受欺凌的共同变化关系：一项纵向社会网络分析研究

欺凌是一种涉及多类行为和多主体互动的群体过程, 但是已有研究很少在同伴的群体互动和关系变化过程中研究欺凌相关行为的发展。尤其是受欺凌作为一种被动承受而非主动选择的行为结果, 对其在同伴情境中的变化过程研究更为有限。本研究从青少年的友谊网络与其受欺凌的共变关系入手, 采用纵向社会网络分析法, 对来自26个班1406名学生进行为期1年的3个时间点(七年级末、八年级上学期末、八年级下学期末)的追踪研究, 结果发现：(1)受欺凌影响群体内友谊关系的建立：受欺凌水平高的青少年更难以与同伴建立朋友关系(同伴回避效应), 且更倾向于选择同样受欺凌水平高的个体作为朋友(同伴选择效应); (2)友谊关系影响受欺凌水平的变化：在群体中拥有更多朋友关系的青少年, 其受欺凌水平会逐渐降低(同伴保护效应); 但另一方面, 拥有高受欺凌水平朋友的青少年, 自己的受欺凌水平会随着时间呈增高趋势(同伴影响效应); (3)随着时间的发展, 女生的受欺凌水平比男生更容易降低(性别影响效应)。研究结果揭示了友谊网络和受欺凌的共变关系, 为校园欺凌群体干预提供启示。