Human Cognitive Behavior Research Articles

Fast life histories, not pathogens, account for state-level variation in homicide, child maltreatment, and family ties in the U.S.

Parasite stress theory has recently been used to account for an array of cross-cultural differences in human cognition and social behavior, including in-group bias, interpersonal violence, child maltreatment, and religious adherence. Here, we re-assess the apparently ubiquitous effects of parasite stress on behavior observed in the U.S., using the cross-sectional, cross-population approach implemented by prior pathogen stress studies. Our results raise two challenges to previous findings. First, we show that the observed effects of pathogen stress in the U.S. data are due exclusively to one type of infectious disease – sexually transmitted diseases (STD) – while non-STD infections have no effect. Second, we find that controlling for life history measures of extrinsic risk and a fast life history erases the observed associations with family ties, interpersonal violence, child fatalities, and religious adherence. Thus, after appropriate variable specification, stratification, and control, U.S. cross-state population differences provide no support for the pathogen stress hypothesis in these various domains of behavior. Rather, the findings are more consistent with predictions from life history theory.

A Clifford algebraic analysis gives mathematical explanation of quantization of quantum theory and delineates a model of quantum reality in which information, primitive cognition entities and a principle of existence are intrinsically represented <i>ab initio</i>

The thesis of this paper is that Information, Cognition and a Principle of Existence are intrinsically structured in the quantum model of reality. We reach such evidence by using the Clifford algebra. We analyze quantization in some traditional cases of quantum mechanics and, in particular in quantum harmonic oscillator, orbital angular momentum and hydrogen atom. The results are confirmed analyzing human cognition behavior that evidences a very consistent agreement with the basic quantum mechanical foundations.

Extended information inference model for unsupervised categorization of web short texts

Traditional text-processing methods encounter significant performance degradation when they are applied to web short texts, with their inherent characteristics including feature sparseness, lack of sufficient hand-labelled training examples, domain dependence, and asyntactic expression. In this paper we propose a modified information inference model that can mimic human cognitive behaviour to categorize various web short texts in an unsupervised manner. The model is based on the conceptual space theory and hyperspace analogue to language (HAL) model, and it is a novel development in that it combines domain-specific knowledge and universal knowledge via a fusion mechanism for multiple HAL spaces. Moreover, in the realization of conceptual space, a concept is represented geometrically by a two-tuple of property sets, which can effectively improve the representation accuracy of the information contained in combined concepts. Two measurements of the relationship between concepts are used to implement the information inference for web short texts. The experimental evaluation of our model is conducted via three different tasks on web short text categorization, and the results indicate the applicability and usefulness of the proposed method.

Neurotrophic Effects of Serum- and Glucocorticoid-Inducible Kinase on Adult Murine Mesencephalic Dopamine Neurons

Mesencephalic dopamine neurons are central to many aspects of human cognition, motivational, and motor behavior, and they are uniquely vulnerable to degenerative neurologic disorders such as Parkinson's disease. There is growing evidence that in the mature brain these neurons not only remain responsive to neurotrophic support, but are dependent on it for viability and function. Little is known of the cellular signaling pathways that mediate this support, although some evidence suggests that protein kinase Akt/PKB may play such a role. Another candidate for such a role is serum- and glucocorticoid-inducible kinase (SGK), a member of the AGC kinase family that is closely related to Akt. We have herein examined the responsiveness of adult mouse dopamine neurons in vivo to overexpression of wild-type and a constitutively active form of SGK by use of viral vector transfer in normal mice and both before and after 6-OHDA lesion. We find that SGK induces a broad spectrum of neurotrophic effects on these neurons, including induction of neuronal hypertrophy, protection from both neuron death and neurotoxin-induced retrograde axonal degeneration, and axon regeneration. Given the diverse and robust effects of SGK on these neurons, and its abundant expression in them, we suggest that SGK, like closely related Akt, may play a role in their responsiveness to neurotrophic factors and in adult maintenance. It therefore offers a novel target for therapeutic development.

Emotions in strategic organization: Opportunities for impactful research

Following the emergence of the behavioral movement in economics and finance, there have been mounting calls for strategy scholars to expand and deepen what is called the field of behavioral strategy, in which cognitive and social psychology will be merged with strategic management theory and practice (Powell et al., 2011). The goal is to bring realistic assumptions about human cognition, emotion, and social behavior to the strategic management of organizations and thus to enrich strategy theory, empirical research, and real-world practice. Thanks to advancing research in social psychology and neuroscience, there has been a resurgence of scholarly interest in connecting micro-psychological phenomena to strategic outcomes (e.g., Hodgkinson and Healey, 2011; Huy, 2011; Powell et al., 2011). Levinthal (2011) noted that many strategic management challenges involve ill-specified alternatives and coarse-grained representations of strategic issues with a high level of uncertainty and ambiguity. Dealing adequately with these issues escapes neat optimizing algorithms, which has been the focus of the literature on judgment and decision-making. One type of psychological phenomenon, human emotion, has barely been integrated into strategy research, although mushrooming research on emotion has shown that it can have a potent influence on cognition and behavior, especially under conditions of uncertainty and ambiguity (see Elfenbein, 2007). This essay discusses how scholars in strategic organization can do future research to advance the field of behavioral strategy and, more specifically, how emotion can play an important role in this field. Indeed, affect-laden cognition has been part of strategic management research at least since the 1970s with influential concepts such as escalating commitment (Staw, 1976; Staw and Ross, 1987), strategic issues conceived as threats or opportunities (Jackson and Dutton, 1988; Staw et al., 1981), or top management hubris (Hayward and Hambrick, 1997; Hiller and Hambrick, 2005). How emotion plays a central role in influencing strategic processes started to be treated more explicitly at the periphery of the strategic management literature only about two decades later (e.g., Huy, 1999, 2002, 2005). One reason might be due to the growing legitimacy of emotion as a scientific phenomenon thanks to new technologies (e.g., the MRI scanner) that have given rise to neuroscience; neurologists have demonstrated the influence of emotions on individual-level thinking and behavior (e.g., Damasio, 1994). Moreover, emotion-based ability has been synthesized by the concept of emotional intelligence that has captured the imagination of many researchers and practitioners (Mayer and Salovey, 1997; Salovey and Mayer, 1990). 453107 SOQ10310.1177/1476127012453107HuyStrategic Organization 2012

Emotions in Strategic Organization: Opportunities for Impactful Research

Following the emergence of the behavioral movement in economics and finance, there have been mounting calls for strategy scholars to expand and deepen what is called as the field of behavioral strategy, in which cognitive and social psychology will be merged with strategic management theory and practice (Powell, Lovallo, & Fox, 2011). The goal is to bring realistic assumptions about human cognition, emotion, and social behavior to the strategic management of organizations and thus to enrich strategy theory, empirical research, and real world practice. Thanks to advancing research in social psychology and neuroscience, there has been a resurgence of scholarly interest in connecting micro psychological phenomena to strategic outcomes (e.g., Hodgkinson & Healey, 2011; Huy, 2011; Powell et al., 2011). Levinthal (2011) noted that many strategic management challenges involve ill-specified alternatives and coarse-grained representations of strategic issues with a high level of uncertainty and ambiguity. Dealing adequately with these issues escapes neat optimizing algorithms, which has been the focus of the literature on judgment and decision making. One type of psychological phenomenon, human emotion, has barely been integrated to strategy research, although mushrooming research on emotion has shown that emotion can have a potent influence on cognition and behavior, especially under conditions of uncertainty and ambiguity (see Elfenbein, 2007).

Mechanisms or metaphors? The emptiness of evolutionary psychological explanations

In recent decades, numerous psychological and sociological theories have been offered in the attempt to explain human cognition, motivation, and behavior in fundamentally evolutionary terms. Drawing inspiration from the Darwinian theory of natural selection, evolutionary approaches to social science argue that behavior arises primarily from underlying evolved psychological mechanisms and that the central task of social science is to identify and articulate the specific nature of such mechanisms. Much effort has been expended by evolutionary social scientists to definitively identify the various evolved psychological mechanisms that account for the diversity of human cognitive, emotional, and social behavior. We argue, however, that the search for evolved psychological mechanisms that adequately account for either the transmission of psychological entities (i.e., emotions, intentions, ideas, behaviors, etc.) across generations or the current existence of such entities cannot in principle succeed because evolutionary social science theorists have fundamentally mistaken their metaphors for mechanisms.

Modeling interaction using trust and recommendation in ubiquitous computing environment

Abstract To secure computing in pervasive environment, an adaptive trust and recommendation based access control model (based on human notion of trust) is proposed. The proposed model provides support to calculate direct as well as indirect trust based on recommendations. It handles situations (by itself) both in which the requesting entity has a past experience with the service and a stranger entity requesting to access the service without any past interaction with the service. It encompasses the ability to reason human cognitive behavior and has the capability to adjust in accordance with behavioral pattern changes. X-bar control chart is used to handle malicious recommendation. The defense mechanisms incorporated by proposed model against attacks such as bad mouthing attack, oscillating behavior attack and conflicting behavior attack are also demonstrated.

The Role of Beta-Frequency Neural Oscillations in Motor Control

Human sensorimotor and cognitive behavior is associated with changes in the oscillatory activity of the brain. For example, the integration of diverse aspects of a stimulus into a unitary percept is related to synchronized oscillations in the gamma range (30–100 Hz), while power in the alpha band

Designing products and services based on understanding human cognitive behavior

When technology development is conducted based only on a developer's idea, we face difficulties in realizing products and services that will be well accepted by people. This is because it is difficult for a developer to know precisely how various users think and feel while using products or receiving services under real life situations. In order to overcome these difficulties, we have developed cognitive chrono-ethnography (CCE) which is a new method to understand cognitive behavior under various situations. This method clarifies the cognitive behavior process by selecting “elite monitors” taking characteristics of target users into consideration, identifying “critical parameters” utilized in designing the products or services, recording the human behavior in real life situations under the control of the parameters, and retrospectively interviewing the participants. This method is applied in the early stages of synthesiological R&D processes oriented toward designing target products and services acceptable by people.

Designing products and services based on understanding human cognitive behavior

Designing products and services based on understanding human cognitive behavior

A Comprehensive and Adaptive Trust Model for Large-Scale P2P Networks

Based on human psychological cognitive behavior, a Comprehensive and Adaptive Trust (CAT) model for large-scale P2P networks is proposed. Firstly, an adaptive trusted decision-making method based on HEW (Historical Evidences Window) is proposed, which can not only reduce the risk and improve system efficiency, but also solve the trust forecasting problem when the direct evidences are insufficient. Then, direct trust computing method based on IOWA (Induced Ordered Weighted Averaging) operator and feedback trust converging mechanism based on DTT (Direct Trust Tree) are set up, which makes the model have a better scalability than previous studies. At the same time, two new parameters, confidence factor and feedback factor, are introduced to assign the weights to direct trust and feedback trust adaptively, which overcomes the shortage of traditional method, in which the weights are assigned by subjective ways. Simulation results show that, compared to the existing approaches, the proposed model has remarkable enhancements in the accuracy of trust decision-making and has a better dynamic adaptation capability in handling various dynamic behaviors of peers.

A Doctrine of Cognitive Informatics (CI)

Cognitive informatics (CI) is the transdisciplinary enquiry of cognitive and information sciences that investigates into the internal information processing mechanisms and processes of the brain and natural intelligence, and their engineering applications via an interdisciplinary approach. CI develops a coherent set of fundamental theories and denotational mathematics, which form the foundation for most information and knowledge based science and engineering disciplines such as computer science, cognitive science, neuropsychology, systems science, cybernetics, software engineering, knowledge engineering, and computational intelligence. This paper reviews the central doctrine of CI and its applications. The theoretical framework of CI is described on the architecture of CI and its denotational mathematic means. A set of theories and formal models of CI is presented in order to explore the natural and computational intelligence. A wide range of applications of CI are described in the areas of cognitive computers, cognitive properties of knowledge, simulations of human cognitive behaviors, cognitive complexity of software, autonomous agent systems, and computational intelligence.

Genes, Brains, and Language: An Epistemological Examination of how Genes can Underlie Human Cognitive Behavior

How do genes encode for the formation of morphological structures such as the brain? Can genetic material also encode for behavior such as cognition, language, or culture? For many years, evolutionary biologists as well as scholars who work within extrabiological fields such as psychology, linguistics, and archaeology could only answer the above two questions in a speculative manner. This is because until recently, empirical observations on how genes underlie anatomy or behavior were generally lacking. This situation has now changed. Several genes ( MCPH1-MCPH6) have been implicated in the regulation of brain size and a first gene (the FOXP2 gene) has been identified that might underlie linguistic behavior. These discoveries allow us to finally test some of the long-standing theoretical assumptions on how genes do or do not determine morphology and behavior.

Moral Fictionalism, Preference Moralization and Anti-Conservatism: Why Metaethical Error Theory Doesn't Imply Policy Quietism

The evolutionary explanation of human dispositions to prosocial behaviour and to moralization of such behaviour undermines the moral realist's belief in objective moral facts that hold independently of people's contingent desires. At the same time, advocacy of preferences for radical large-scale policy change is generally sure to be ineffective unless it is moralized. It may seem that this requires the economist who would advocate loud policies, but is also committed to a naturalistic account of human social and cognitive behaviour, to engage in wilful manipulation, morally hectoring people even when she knows that her doing so ought rationally to carry no persuasive force. Understanding the role of moralized preferences in the maintenance of the self, and in turn understanding the economic rationale of such self-maintenance, shows how and why preferences can be moralized by a believer in error theory without this implying hypocrisy or manipulation.

Toward the synthesis of human language behavior

Abstract : An attempt is made to show how the practical problems of programming a language machine lead to a particular set of hypotheses about human cognitive processes. The synthesis of cognitive behavior requires a listing of conditions necessary and sufficient to account for man's abilities: (1) symbolization of the impinging environment in terms of receptor-neuron activity; (2) abstraction of similarities and differences in the neural coding; (3) recoding some of these abstractions into adaptive muscular actions; and (4) remembering or forgetting those symbols whose adaptive utility has vanished. Each of these capabilities must be present in any system that synthesizes human cognitive behavior. All of these capabilities are required in the intelligent manipulation of language. (Author)

An approach for modeling human cognitive behavior in evacuation models

This paper aims to propose a method to assess human cognitive behavior in fire emergency evacuation situations. The simulation models currently available do not address this issue in an appropriate manner. If we do not consider cognitive aspects of the human being during the process of evacuation, the results provided by such models might be far from reality. The method is called “start of evacuation motion” analysis and is based on logic diagrams called continuous and single value networks (Process Safety Prog. 20 (2001) 1–10). The logic diagrams have shown to be a very powerful tool to analyze the cognitive aspects of human beings during a fire emergency situation. Questions like how the approach is used, where to find the input data necessary and what results are obtained are discussed.

Some challenges and grand challenges for computational intelligence

When the terms “intelligence” or “intelligent” are used by scientists, they are referring to a large collection of human cognitive behaviors— people thinking. When life scientists speak of the intelligence of animals, they are asking us to call to mind a set of human behaviors that they are asserting the animals are (or are not) capable of. When computer scientists speak of artificial intelligence, machine intelligence, intelligent agents, or (as I chose to do in the title of this essay) computational intelligence, we are also referring to that set of human behaviors. Although intelligence means people thinking, we might be able to replicate the same set of behaviors using computation. Indeed, one branch of modern cognitive psychology is based on the model that the human mind and brain are complex computational “engines,” that is, we ourselves are examples of computational intelligence. 2. Turing’s Vision and the Turing Test for Humanoid Behavior The idea, of course, is not new. It was discussed by Turing in the 1940s. In the play about Turing’s life, Breaking the Code [Whitemore 1987], Turing is shown visiting his old grammar school and delivering a talk to the boys, in which he offers a vision of the thinking computer. The memories of those of Turing’s colleagues of the 1940s who are still alive confirm that he spoke often of this vision. In 1950, he wrote of it, in a famous article [Turing 1950], in which he proposed a test (now called the Turing Test (TT)) for computational intelligence. In the test, a human judgment must be made concerning whether a set of observed behaviors is sufficiently similar to human behaviors that the same word—intelligent—can justifiably be used. The judgment is about behavior not mechanism. Computers are not like human brains, but if they perform the same acts and one performer (the human) is labeled intelligent, then the other must be labeled intelligent also. I have always liked the Turing Test because it gave a clear and tangible vision, was reasonably objective, and made concrete the tie to human behavior by using the unarticulated criteria of a human judge. Turing Award winner Jim Gray, who works in fields of Computer Science other than AI, appears to agree. His list of challenges for the future includes: “The Turing test: Win the imitation game 30% of the time.” Significantly, he adds: “Read and understand as well as a human. Think and write as well as a human,” [Gray 2003]. I will have more to say about necessary conditions for these human activities later. But there are problems with the Turing Test (TT). Human intelligence is very multidimensional. However, the judge must fuse all of these dimensions into a

Human sexual arousal: A modern behavioral approach.

Recent developments in the analysis of derived relational responding have contributed to the behavioral analysis of a wide range of complex human behaviors, including sexual behaviors. In particular, recent research has demonstrated that human sexual arousal patterns can emerge in the absence of a history of instrumental learning or stimulus association. These findings considerably expand the traditional behavioral approach to the analysis of human sexual arousal. The current paper provides an overview of the traditional behavioral approach to the analysis of sexual arousal, and outlines Relational Frame Theory as a modern behavioral approach to human language, cognition, and complex behavior in general. A relational frame approach to the analysis of human sexual arousal is then outlined and its interpretative power in dealing with a range of complex human sexual behavior is demonstrated.

An experimental study on estimating human error probability (HEP) parameters for PSA/HRA by using human model simulation

A framework of Human Error Probability (HEP) parameters, which is needed for Human Reliability Analysis (HRA) within a practice of Probabilistic Safety Assessment (PSA) of Nuclear Power Plant is first proposed. Then a laboratory experiment was conducted in order to construct a computer simulation model (human model) that describes human cognitive behaviour on detecting and diagnosing plant anomaly causes. An inter-comparison between experimental data and human model simulation was performed to estimate Human Cognitive Reliability (HCR) curves, in order to confirm the applicability of a human model for estimating these HEP parameters for PSA/HRA practice.