Age-related associative deficits and the isolation effect

ABSTRACT

If all but one of the items in a list are similar (e.g., all black except one red), memory for the different item is enhanced (the isolation effect). Older adults generally show similar or smaller isolation effects compared to young adults, which has been attributed to age-related deficits in associative memory whereby older adults are less able to associate an isolated stimulus to its isolating feature. Experiment 1 examined the isolation effect for isolation based on spatial position, modality and color; in Experiment 2, the criterion for isolation was the associative relation between stimuli. The results consistently showed no differences between young and older participants in the magnitude of the isolation effect. Whilst age deficits in associative memory may act to reduce the isolation effect in older adults, age deficits in self-initiated processing and inhibitory functionality may counteract this reduction by enhancing the isolation effect in older adults.     

Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task

Human participants and recurrent (“connectionist”) neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular (“strong”) classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the Elsewhere Condition (Kiparsky, 1973). Previous connectionist accounts of related phenomena have often been vague about the nature of the networks’ encoding systems. We analyzed our network using dynamical systems theory, revealing topological and geometric properties that can be directly compared with the mechanisms of non‐connectionist, rule‐based accounts. The results reveal that the networks “contain” structures related to mechanisms posited by rule‐based models, partly vindicating the insights of these models. On the other hand, they support the one mechanism (OM), as opposed to the more than one mechanism (MOM), view of symbolic abstraction by showing how the appearance of MOM behavior can arise emergently from one underlying set of principles. The key new contribution of this study is to show that dynamical systems theory can allow us to explicitly characterize the relationship between the two perspectives in implemented models.     

Who victimizes whom and who defends whom? A multivariate social network analysis of victimization,aggression, and defending in early childhood

The aim of this research was to investigate the interplay between victim‐aggressor relationships and defending relationships in early childhood to test the proposition that young aggressors are less selective than older children in their choice of vulnerable targets. Cross‐sectional multivariate statistical social network analyses (Exponential Random Graph Models) for a sample of 177 preschoolers from seven classes, 5‐ to 7‐years‐old, revealed that boys were more aggressive than girls, toward both boys and girls, whereas defending relationships were most often same‐sex. There was significant reciprocity in aggression, indicating that it was more often bidirectional rather than unidirectional. In addition, aggressors clearly defended each other when they shared their targets of aggression, whereas a marginally significant trend appeared for defending between victims who were victimized by the same aggressors. Furthermore, teacher‐rated dominance was positively associated with children's involvement in both aggression and victimization, and teacher‐rated insecurity was associated with less aggression, but not with victimization. These findings suggest that those who are reported as being victimized may retaliate, or be aggressive themselves, and do not display some of the vulnerabilities reported among older groups of victims. The findings are in line with the proposition that young aggressors are less strategic than older children in targeting vulnerable victims. The network approach to peer victimization and defending contributes to understanding the social processes facilitating the development of aggression in early childhood.     

Dynamic Creative Interaction Networks and Team Creativity Evolution: A Longitudinal Study

To assess the dynamical effects of creative interaction networks on team creativity evolution, this paper elaborates a theoretical framework that links the key elements of creative interaction networks, including node, edge and network structure, to creativity in teams. The process of team creativity evolution is divided into four phases, including formation, growth, maturity and decline/restart. The importance of domain‐relevant knowledge, creativity‐relevant skill, interaction frequency, interaction length, network density and closeness centrality are emphasized in specific phases of team creativity evolution in a complex creative context. To test our assumptions, a longitudinal study of creative teams in a “Challenge Cup” Creative Business Plan Competition for university students is performed and the full networks of 17 creative entrepreneur teams are mapped. Both static comparison and dynamic analysis are conducted to analyze the relationship between creative interaction networks and team creativity evolution. For specific phases of team creativity evolution, we find confirmation of our predictions. The implications of dynamic creative interaction networks for all the phases of creative teams from formation to decline/restart are discussed.     

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.     

Do Disagreeable Political Discussion Networks Undermine Attitude Strength?

How attitudes change and affect behavior depends, in large part, on their strength. Strong attitudes are more resistant to persuasion and are more likely to produce attitude‐consistent behavior. But what influences attitude strength? In this article, we explore a widely discussed, but rarely investigated, factor: an individual's political discussion network. What prior work exists offers a somewhat mixed picture, finding sometimes that disagreeable networks weaken attitudes and other times that they strengthen attitudes. We use a novel national representative dataset to explore the relationship between disagreeable networks and attitude strength. We find, perhaps surprisingly, no evidence that disagreements in networks affect political attitude strength. We conclude by discussing likely reasons for our findings, which, in turn, provide a research agenda for the study of networks and attitude strength.     

Conceptualizing ‘social capital’ for health promotion in small local communities: a micro‐qualitative study

This paper reports on a micro‐qualitative case study of peoples' experiences of local community life in a south‐east English town. This material is used as the basis for a critical discussion of the suitability of Putnam's notion of social capital as a conceptual tool for the design and evaluation of ‘community strengthening’ policies and interventions. The study was motivated by a concern that too much debate about social capital has been conducted by academics and policy‐makers in a top‐down manner, with inadequate attention to the realities of life in the local communities that they refer to. Three‐hour semi‐structured interviews were conducted with 37 residents in two less affluent wards in our town of interest. Informants—half men and half women, and spread across the 15–75 age group—were encouraged to talk about their personal experiences of local community life. Interview findings are presented within the ‘norm’ categories of trust, neighbourliness and reciprocal help and support, and the ‘network’ categories of participation in informal networks, voluntary groupings and community activist groupings. Our case study points to a number of ways in which Putnam's concept needs to be refined if it is to inform ‘community strengthening’ policies and interventions in England. Far more notice needs to be taken of the role played by informal networks of friends and neighbours in the construction of local community life. Attention also needs to be given to the complex and shifting geographical spread of peoples' significant social networks. Putnam's conceptualization of cohesive local communities and his unitary notions of trust and local identity may also be unduly essentialist. In our particular communities of interest, they failed to capture the fluidity of local community norms and networks in a rapidly changing society. They also failed to do justice to the extent to which social distinctions—such as age, gender, ethnicity and housing tenure—shape and constrain the way in which people create, sustain and access social capital. Copyright © 2001 John Wiley & Sons, Ltd.     

Plagues,Pagans, and Christians: Differential Survival,Social Networks,and the Rise of Christianity

In his book, The Rise of Christianity, Rodney Stark argues that the early Christian church indirectly benefitted from the plagues that struck the early Roman Empire in the 2nd and 3rd centuries of the Common Era. In particular, he argues that the early church's doctrines concerning love, charity, and social service would have led Christians to enjoy higher survival rates than pagans, which would have left the social networks of the former relatively intact, while those of the latter in disarray. Moreover, since recruitment to new religious movements occurs largely through social ties, the probability that an average pagan would have converted to Christianity would have been greater after the plagues than before. In this article, we use computer modeling to test Stark's hypothesis. Not only do we find support for his hypothesis, we also show that higher survival rates for either group not only would have benefitted their respective social networks but also would have benefitted their competitor's social networks, highlighting how network effects often flow in multiple and unexpected ways. We conclude with suggestions for future research, in particular how scholars can build upon our analyses and explore alternative assumptions.     

Social support and verbal interaction are differentially associated with cognitive function in midlife and older age

Social engagement is associated with healthy aging and preserved cognition. Two dimensions of engagement, verbal interactions and perceived support, likely impact cognition via distinct mechanistic pathways. We explored the cognitive benefit of each construct among enrollees (N = 1,052, mean age = 60.2 years) in the Wisconsin Registry for Alzheimer’s Prevention study, who provide neuropsychological and sociobehavioral data at two-year intervals. Outcomes included six cognitive factor scores representing key domains of executive function and memory. Key predictors included self-reported perceived social support and weekly verbal interaction. Results indicated that after adjusting for lifestyle covariates, social support was positively associated with Speed and Flexibility and that verbal interactions were associated with Verbal Learning and Memory. These findings suggest that support, which may buffer stress, and verbal interaction, an accessible, aging-friendly form of environmental enrichment, are uniquely beneficial. Both are integral in the design of clinical and community interventions and programs that promote successful aging.     

Metamorphic malicious code behavior detection using probabilistic inference methods

Existing antivirus programs detect malicious code based on fixed signatures; therefore, they have limitations in detecting metamorphic malicious code that lacks signature information or possesses circumventing code inserted into it. Research on the methods for detecting this type of metamorphic malicious code primarily focuses on techniques that can detect code based on behavioral similarity to known malicious code. However, these techniques measure the degree of similarity with existing malicious code using API function call patterns. Therefore, they have certain disadvantages, such as low accuracy and large detection times. In this paper, we propose a method which can overcome the limitations of existing methods by using the FP-Growth algorithm, a data mining technique, and the Markov Logic Networks algorithm, a probabilistic inference method. To perform a comparative evaluation of the proposed method's malicious code behavior detection, we performed inference experiments using malicious code with an inserted code for random malicious behavior. We performed experiments to select optimal weights for each inference rule to improve our malicious code behavior inferences’ accuracy. The results of experiments, in which we performed a comparative evaluation with the General Bayesian Network, showed that the proposed method had an 8% higher classification performance.