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.     

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.     

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.     

Generating and sharing of market intelligence in sales teams: an economic social network perspective

In this research, we take a multimethod approach to shed light on the potential costs to sales teams that generate and share market intelligence (MI). First, we introduce an analytical model to propose the respective levels of effort that sales managers, experts, and team members spend generating and sharing MI. To test our propositions, we utilize social network data from 40 independent, business-to-business (B2B) sales teams, representing 287 salespeople. Interestingly, our results support the premise that team members become dependent (reduce MI efforts) when their sales manager or team expert shares MI among the team. We term this a “sharing tax” that sales managers and team experts pay when they share MI. Consequently, sales managers demonstrate greater MI-generation efforts the more they share MI. We also find that experts who share more (less) also show greater (lesser) MI-generation efforts, but only for teams where sales managers share low (high) levels of MI. In summary, our research innovatively conducts an empirical test of the Nash Equilibrium pattern of sales team effort to show that two critical team members, the sales manager and expert, are at a disadvantage when they share valuable MI.     

Semantic computations of truth based on associations already learned

This article sets forth a detailed theoretical proposal of how the truth of ordinary empirical statements, often atomic in form, is computed. The method of computation draws on psychological concepts such as those of associative networks and spreading activation, rather that the concepts of philosophical or logical theories of truth. Axioms for a restricted class of cases are given, as well as some detailed examples.