Air Force Research Laboratory Warfighter Readiness Research Division Participation in the 2008 IITSEC

DTIC Science & Technology

2008-12-15

of the underlying behaviors that led to each element being cited. The AFSC Human Factors Database listed all human factors cited in the Life...situations of increased pressure. Through an understanding of the causal factors of human behavior , and by analysis of one’s own behavioral patterns...JTAC training and overall lessons learned from modeling and simulation of the JTAC environment to include behavior scripting, artillery models

A Culture-Behavior-Brain Loop Model of Human Development.

PubMed

Han, Shihui; Ma, Yina

2015-11-01

Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Crowd Simulation Incorporating Agent Psychological Models, Roles and Communication

DTIC Science & Technology

2005-01-01

system (PMFserv) that implements human behavior models from a range of ability, stress, emotion , decision theoretic and motivation sources. An...autonomous agents, human behavior models, culture and emotions 1. Introduction There are many applications of computer animation and simulation where...We describe a new architecture to integrate a psychological model into a crowd simulation system in order to obtain believable emergent behaviors

Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

NASA Technical Reports Server (NTRS)

Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan

2014-01-01

Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

Making Organisms Model Human Behavior: Situated Models in North-American Alcohol Research, 1950-onwards

PubMed Central

Leonelli, Sabina; Ankeny, Rachel A.; Nelson, Nicole C.; Ramsden, Edmund

2014-01-01

Argument We examine the criteria used to validate the use of nonhuman organisms in North-American alcohol addiction research from the 1950s to the present day. We argue that this field, where the similarities between behaviors in humans and non-humans are particularly difficult to assess, has addressed questions of model validity by transforming the situatedness of non-human organisms into an experimental tool. We demonstrate that model validity does not hinge on the standardization of one type of organism in isolation, as often the case with genetic model organisms. Rather, organisms are viewed as necessarily situated: they cannot be understood as a model for human behavior in isolation from their environmental conditions. Hence the environment itself is standardized as part of the modeling process; and model validity is assessed with reference to the environmental conditions under which organisms are studied. PMID:25233743

Calibrating Bayesian Network Representations of Social-Behavioral Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitney, Paul D.; Walsh, Stephen J.

2010-04-08

While human behavior has long been studied, recent and ongoing advances in computational modeling present opportunities for recasting research outcomes in human behavior. In this paper we describe how Bayesian networks can represent outcomes of human behavior research. We demonstrate a Bayesian network that represents political radicalization research – and show a corresponding visual representation of aspects of this research outcome. Since Bayesian networks can be quantitatively compared with external observations, the representation can also be used for empirical assessments of the research which the network summarizes. For a political radicalization model based on published research, we show this empiricalmore » comparison with data taken from the Minorities at Risk Organizational Behaviors database.« less

A Qualitative Model of Human Interaction with Complex Dynamic Systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

A qualitative model of human interaction with complex dynamic systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

Dynamical aspects of behavior generation under constraints

PubMed Central

Harter, Derek; Achunala, Srinivas

2007-01-01

Dynamic adaptation is a key feature of brains helping to maintain the quality of their performance in the face of increasingly difficult constraints. How to achieve high-quality performance under demanding real-time conditions is an important question in the study of cognitive behaviors. Animals and humans are embedded in and constrained by their environments. Our goal is to improve the understanding of the dynamics of the interacting brain–environment system by studying human behaviors when completing constrained tasks and by modeling the observed behavior. In this article we present results of experiments with humans performing tasks on the computer under variable time and resource constraints. We compare various models of behavior generation in order to describe the observed human performance. Finally we speculate on mechanisms how chaotic neurodynamics can contribute to the generation of flexible human behaviors under constraints. PMID:19003514

Modeling driver behavior in a cognitive architecture.

PubMed

Salvucci, Dario D

2006-01-01

This paper explores the development of a rigorous computational model of driver behavior in a cognitive architecture--a computational framework with underlying psychological theories that incorporate basic properties and limitations of the human system. Computational modeling has emerged as a powerful tool for studying the complex task of driving, allowing researchers to simulate driver behavior and explore the parameters and constraints of this behavior. An integrated driver model developed in the ACT-R (Adaptive Control of Thought-Rational) cognitive architecture is described that focuses on the component processes of control, monitoring, and decision making in a multilane highway environment. This model accounts for the steering profiles, lateral position profiles, and gaze distributions of human drivers during lane keeping, curve negotiation, and lane changing. The model demonstrates how cognitive architectures facilitate understanding of driver behavior in the context of general human abilities and constraints and how the driving domain benefits cognitive architectures by pushing model development toward more complex, realistic tasks. The model can also serve as a core computational engine for practical applications that predict and recognize driver behavior and distraction.

Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

PubMed Central

Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

2016-01-01

Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

A case for human systems neuroscience.

PubMed

Gardner, J L

2015-06-18

Can the human brain itself serve as a model for a systems neuroscience approach to understanding the human brain? After all, how the brain is able to create the richness and complexity of human behavior is still largely mysterious. What better choice to study that complexity than to study it in humans? However, measurements of brain activity typically need to be made non-invasively which puts severe constraints on what can be learned about the internal workings of the brain. Our approach has been to use a combination of psychophysics in which we can use human behavioral flexibility to make quantitative measurements of behavior and link those through computational models to measurements of cortical activity through magnetic resonance imaging. In particular, we have tested various computational hypotheses about what neural mechanisms could account for behavioral enhancement with spatial attention (Pestilli et al., 2011). Resting both on quantitative measurements and considerations of what is known through animal models, we concluded that weighting of sensory signals by the magnitude of their response is a neural mechanism for efficient selection of sensory signals and consequent improvements in behavioral performance with attention. While animal models have many technical advantages over studying the brain in humans, we believe that human systems neuroscience should endeavor to validate, replicate and extend basic knowledge learned from animal model systems and thus form a bridge to understanding how the brain creates the complex and rich cognitive capacities of humans. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Formally verifying human–automation interaction as part of a system model: limitations and tradeoffs

PubMed Central

Bass, Ellen J.

2011-01-01

Both the human factors engineering (HFE) and formal methods communities are concerned with improving the design of safety-critical systems. This work discusses a modeling effort that leveraged methods from both fields to perform formal verification of human–automation interaction with a programmable device. This effort utilizes a system architecture composed of independent models of the human mission, human task behavior, human-device interface, device automation, and operational environment. The goals of this architecture were to allow HFE practitioners to perform formal verifications of realistic systems that depend on human–automation interaction in a reasonable amount of time using representative models, intuitive modeling constructs, and decoupled models of system components that could be easily changed to support multiple analyses. This framework was instantiated using a patient controlled analgesia pump in a two phased process where models in each phase were verified using a common set of specifications. The first phase focused on the mission, human-device interface, and device automation; and included a simple, unconstrained human task behavior model. The second phase replaced the unconstrained task model with one representing normative pump programming behavior. Because models produced in the first phase were too large for the model checker to verify, a number of model revisions were undertaken that affected the goals of the effort. While the use of human task behavior models in the second phase helped mitigate model complexity, verification time increased. Additional modeling tools and technological developments are necessary for model checking to become a more usable technique for HFE. PMID:21572930

Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research.

PubMed

Spruijt-Metz, Donna; Hekler, Eric; Saranummi, Niilo; Intille, Stephen; Korhonen, Ilkka; Nilsen, Wendy; Rivera, Daniel E; Spring, Bonnie; Michie, Susan; Asch, David A; Sanna, Alberto; Salcedo, Vicente Traver; Kukakfa, Rita; Pavel, Misha

2015-09-01

Adverse and suboptimal health behaviors and habits are responsible for approximately 40 % of preventable deaths, in addition to their unfavorable effects on quality of life and economics. Our current understanding of human behavior is largely based on static "snapshots" of human behavior, rather than ongoing, dynamic feedback loops of behavior in response to ever-changing biological, social, personal, and environmental states. This paper first discusses how new technologies (i.e., mobile sensors, smartphones, ubiquitous computing, and cloud-enabled processing/computing) and emerging systems modeling techniques enable the development of new, dynamic, and empirical models of human behavior that could facilitate just-in-time adaptive, scalable interventions. The paper then describes concrete steps to the creation of robust dynamic mathematical models of behavior including: (1) establishing "gold standard" measures, (2) the creation of a behavioral ontology for shared language and understanding tools that both enable dynamic theorizing across disciplines, (3) the development of data sharing resources, and (4) facilitating improved sharing of mathematical models and tools to support rapid aggregation of the models. We conclude with the discussion of what might be incorporated into a "knowledge commons," which could help to bring together these disparate activities into a unified system and structure for organizing knowledge about behavior.

Model of rhythmic ball bouncing using a visually controlled neural oscillator.

PubMed

Avrin, Guillaume; Siegler, Isabelle A; Makarov, Maria; Rodriguez-Ayerbe, Pedro

2017-10-01

The present paper investigates the sensory-driven modulations of central pattern generator dynamics that can be expected to reproduce human behavior during rhythmic hybrid tasks. We propose a theoretical model of human sensorimotor behavior able to account for the observed data from the ball-bouncing task. The novel control architecture is composed of a Matsuoka neural oscillator coupled with the environment through visual sensory feedback. The architecture's ability to reproduce human-like performance during the ball-bouncing task in the presence of perturbations is quantified by comparison of simulated and recorded trials. The results suggest that human visual control of the task is achieved online. The adaptive behavior is made possible by a parametric and state control of the limit cycle emerging from the interaction of the rhythmic pattern generator, the musculoskeletal system, and the environment. NEW & NOTEWORTHY The study demonstrates that a behavioral model based on a neural oscillator controlled by visual information is able to accurately reproduce human modulations in a motor action with respect to sensory information during the rhythmic ball-bouncing task. The model attractor dynamics emerging from the interaction between the neuromusculoskeletal system and the environment met task requirements, environmental constraints, and human behavioral choices without relying on movement planning and explicit internal models of the environment. Copyright © 2017 the American Physiological Society.

Designing Mouse Behavioral Tasks Relevant to Autistic-Like Behaviors

ERIC Educational Resources Information Center

Crawley, Jacqueline N.

2004-01-01

The importance of genetic factors in autism has prompted the development of mutant mouse models to advance our understanding of biological mechanisms underlying autistic behaviors. Mouse models of human neuropsychiatric diseases are designed to optimize (1) face validity, i.e., resemblance to the human symptoms; (2) construct validity, i.e.,…

Vision-based navigation in a dynamic environment for virtual human

NASA Astrophysics Data System (ADS)

Liu, Yan; Sun, Ji-Zhou; Zhang, Jia-Wan; Li, Ming-Chu

2004-06-01

Intelligent virtual human is widely required in computer games, ergonomics software, virtual environment and so on. We present a vision-based behavior modeling method to realize smart navigation in a dynamic environment. This behavior model can be divided into three modules: vision, global planning and local planning. Vision is the only channel for smart virtual actor to get information from the outside world. Then, the global and local planning module use A* and D* algorithm to find a way for virtual human in a dynamic environment. Finally, the experiments on our test platform (Smart Human System) verify the feasibility of this behavior model.

Explaining Human Behavior.

ERIC Educational Resources Information Center

Olson, Alton T.; And Others

The Deductive-Nomological (D-N) model of human behavior is useful and provides the most objective explanation when it is appropriate but it is not necessarily an all-inclusive statement. For instance, explaining human behavior is always an act that entails languages and theories that are value laden and reveal human choices; however the D-N model…

Rasmussen's model of human behavior in laparoscopy training.

PubMed

Wentink, M; Stassen, L P S; Alwayn, I; Hosman, R J A W; Stassen, H G

2003-08-01

Compared to aviation, where virtual reality (VR) training has been standardized and simulators have proven their benefits, the objectives, needs, and means of VR training in minimally invasive surgery (MIS) still have to be established. The aim of the study presented is to introduce Rasmussen's model of human behavior as a practical framework for the definition of the training objectives, needs, and means in MIS. Rasmussen distinguishes three levels of human behavior: skill-, rule-, and knowledge-based behaviour. The training needs of a laparoscopic novice can be determined by identifying the specific skill-, rule-, and knowledge-based behavior that is required for performing safe laparoscopy. Future objectives of VR laparoscopy trainers should address all three levels of behavior. Although most commercially available simulators for laparoscopy aim at training skill-based behavior, especially the training of knowledge-based behavior during complications in surgery will improve safety levels. However, the cost and complexity of a training means increases when the training objectives proceed from the training of skill-based behavior to the training of complex knowledge-based behavior. In aviation, human behavior models have been used successfully to integrate the training of skill-, rule-, and knowledge-based behavior in a full flight simulator. Understanding surgeon behavior is one of the first steps towards a future full-scale laparoscopy simulator.

Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes

PubMed Central

Fernández-Llatas, Carlos; Benedi, José-Miguel; García-Gómez, Juan M.; Traver, Vicente

2013-01-01

The analysis of human behavior patterns is increasingly used for several research fields. The individualized modeling of behavior using classical techniques requires too much time and resources to be effective. A possible solution would be the use of pattern recognition techniques to automatically infer models to allow experts to understand individual behavior. However, traditional pattern recognition algorithms infer models that are not readily understood by human experts. This limits the capacity to benefit from the inferred models. Process mining technologies can infer models as workflows, specifically designed to be understood by experts, enabling them to detect specific behavior patterns in users. In this paper, the eMotiva process mining algorithms are presented. These algorithms filter, infer and visualize workflows. The workflows are inferred from the samples produced by an indoor location system that stores the location of a resident in a nursing home. The visualization tool is able to compare and highlight behavior patterns in order to facilitate expert understanding of human behavior. This tool was tested with nine real users that were monitored for a 25-week period. The results achieved suggest that the behavior of users is continuously evolving and changing and that this change can be measured, allowing for behavioral change detection. PMID:24225907

Toward statistical modeling of saccadic eye-movement and visual saliency.

PubMed

Sun, Xiaoshuai; Yao, Hongxun; Ji, Rongrong; Liu, Xian-Ming

2014-11-01

In this paper, we present a unified statistical framework for modeling both saccadic eye movements and visual saliency. By analyzing the statistical properties of human eye fixations on natural images, we found that human attention is sparsely distributed and usually deployed to locations with abundant structural information. This observations inspired us to model saccadic behavior and visual saliency based on super-Gaussian component (SGC) analysis. Our model sequentially obtains SGC using projection pursuit, and generates eye movements by selecting the location with maximum SGC response. Besides human saccadic behavior simulation, we also demonstrated our superior effectiveness and robustness over state-of-the-arts by carrying out dense experiments on synthetic patterns and human eye fixation benchmarks. Multiple key issues in saliency modeling research, such as individual differences, the effects of scale and blur, are explored in this paper. Based on extensive qualitative and quantitative experimental results, we show promising potentials of statistical approaches for human behavior research.

Modeling human behaviors and reactions under dangerous environment.

PubMed

Kang, J; Wright, D K; Qin, S F; Zhao, Y

2005-01-01

This paper describes the framework of a real-time simulation system to model human behavior and reactions in dangerous environments. The system utilizes the latest 3D computer animation techniques, combined with artificial intelligence, robotics and psychology, to model human behavior, reactions and decision making under expected/unexpected dangers in real-time in virtual environments. The development of the system includes: classification on the conscious/subconscious behaviors and reactions of different people; capturing different motion postures by the Eagle Digital System; establishing 3D character animation models; establishing 3D models for the scene; planning the scenario and the contents; and programming within Virtools Dev. Programming within Virtools Dev is subdivided into modeling dangerous events, modeling character's perceptions, modeling character's decision making, modeling character's movements, modeling character's interaction with environment and setting up the virtual cameras. The real-time simulation of human reactions in hazardous environments is invaluable in military defense, fire escape, rescue operation planning, traffic safety studies, and safety planning in chemical factories, the design of buildings, airplanes, ships and trains. Currently, human motion modeling can be realized through established technology, whereas to integrate perception and intelligence into virtual human's motion is still a huge undertaking. The challenges here are the synchronization of motion and intelligence, the accurate modeling of human's vision, smell, touch and hearing, the diversity and effects of emotion and personality in decision making. There are three types of software platforms which could be employed to realize the motion and intelligence within one system, and their advantages and disadvantages are discussed.

Intelligent Systems Approach for Automated Identification of Individual Control Behavior of a Human Operator

NASA Technical Reports Server (NTRS)

Zaychik, Kirill B.; Cardullo, Frank M.

2012-01-01

Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.

Theoretical implications of the neurotic paradox as a problem in behavior theory: An experimental resolution

PubMed Central

Stampfl, Thomas G.

1987-01-01

Why do human phobias last for months or years when such behavior should undergo extinction? This failure of extinction or persistence of self-defeating behavior of human disorders was labeled by Mowrer as the neurotic paradox. The paradox is cited by an ever-increasing number of critics who challenge any laboratory-based learning model of human psychopathology. Laboratory research, of course, omits essential requirements in the analysis of behavior, and the principles derived from such analyses must be combined in order to explain complex human behavaior. Validation for a behavioral model can thus be achieved if (a) basic principles inferred from observation of humans treated with a laboratory-derived extinction procedure (e.g., implosive therapy) are combined with (b) principles examined in laboratory research that are combined to generate unique predictions that correspond to known features of human phobic behavior. The latter evidence is briefly reviewed in research demonstrating sustained responding over one thousand consecutive active avoidance responses with complete avoidance of the “phobic” CS for an initial single shock trial. Differential reinforcement for responses to early sequential stimuli depends on minimal work requirement, and reinforcement by timeout from avoidance. This combination of factors effectively precludes extinction to main conditioned aversive stimuli for nonhumans, as it does for human phobias. Support for a laboratory model of human phobia is thereby attained. PMID:22477974

Comparison of Object Recognition Behavior in Human and Monkey

PubMed Central

Rajalingham, Rishi; Schmidt, Kailyn

2015-01-01

Although the rhesus monkey is used widely as an animal model of human visual processing, it is not known whether invariant visual object recognition behavior is quantitatively comparable across monkeys and humans. To address this question, we systematically compared the core object recognition behavior of two monkeys with that of human subjects. To test true object recognition behavior (rather than image matching), we generated several thousand naturalistic synthetic images of 24 basic-level objects with high variation in viewing parameters and image background. Monkeys were trained to perform binary object recognition tasks on a match-to-sample paradigm. Data from 605 human subjects performing the same tasks on Mechanical Turk were aggregated to characterize “pooled human” object recognition behavior, as well as 33 separate Mechanical Turk subjects to characterize individual human subject behavior. Our results show that monkeys learn each new object in a few days, after which they not only match mean human performance but show a pattern of object confusion that is highly correlated with pooled human confusion patterns and is statistically indistinguishable from individual human subjects. Importantly, this shared human and monkey pattern of 3D object confusion is not shared with low-level visual representations (pixels, V1+; models of the retina and primary visual cortex) but is shared with a state-of-the-art computer vision feature representation. Together, these results are consistent with the hypothesis that rhesus monkeys and humans share a common neural shape representation that directly supports object perception. SIGNIFICANCE STATEMENT To date, several mammalian species have shown promise as animal models for studying the neural mechanisms underlying high-level visual processing in humans. In light of this diversity, making tight comparisons between nonhuman and human primates is particularly critical in determining the best use of nonhuman primates to further the goal of the field of translating knowledge gained from animal models to humans. To the best of our knowledge, this study is the first systematic attempt at comparing a high-level visual behavior of humans and macaque monkeys. PMID:26338324

A Formal Investigation of Human Spatial Control Skills: Mathematical Formalization, Skill Development, and Skill Assessment

NASA Astrophysics Data System (ADS)

Li, Bin

Spatial control behaviors account for a large proportion of human everyday activities from normal daily tasks, such as reaching for objects, to specialized tasks, such as driving, surgery, or operating equipment. These behaviors involve intensive interactions within internal processes (i.e. cognitive, perceptual, and motor control) and with the physical world. This dissertation builds on a concept of interaction pattern and a hierarchical functional model. Interaction pattern represents a type of behavior synergy that humans coordinates cognitive, perceptual, and motor control processes. It contributes to the construction of the hierarchical functional model that delineates humans spatial control behaviors as the coordination of three functional subsystems: planning, guidance, and tracking/pursuit. This dissertation formalizes and validates these two theories and extends them for the investigation of human spatial control skills encompassing development and assessment. Specifically, this dissertation first presents an overview of studies in human spatial control skills encompassing definition, characteristic, development, and assessment, to provide theoretical evidence for the concept of interaction pattern and the hierarchical functional model. The following, the human experiments for collecting motion and gaze data and techniques to register and classify gaze data, are described. This dissertation then elaborates and mathematically formalizes the hierarchical functional model and the concept of interaction pattern. These theories then enables the construction of a succinct simulation model that can reproduce a variety of human performance with a minimal set of hypotheses. This validates the hierarchical functional model as a normative framework for interpreting human spatial control behaviors. The dissertation then investigates human skill development and captures the emergence of interaction pattern. The final part of the dissertation applies the hierarchical functional model for skill assessment and introduces techniques to capture interaction patterns both from the top down using their geometric features and from the bottom up using their dynamical characteristics. The validity and generality of the skill assessment is illustrated using two the remote-control flight and laparoscopic surgical training experiments.

Combining Modeling and Gaming for Predictive Analytics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riensche, Roderick M.; Whitney, Paul D.

2012-08-22

Many of our most significant challenges involve people. While human behavior has long been studied, there are recent advances in computational modeling of human behavior. With advances in computational capabilities come increases in the volume and complexity of data that humans must understand in order to make sense of and capitalize on these modeling advances. Ultimately, models represent an encapsulation of human knowledge. One inherent challenge in modeling is efficient and accurate transfer of knowledge from humans to models, and subsequent retrieval. The simulated real-world environment of games presents one avenue for these knowledge transfers. In this paper we describemore » our approach of combining modeling and gaming disciplines to develop predictive capabilities, using formal models to inform game development, and using games to provide data for modeling.« less

Double dynamic scaling in human communication dynamics

NASA Astrophysics Data System (ADS)

Wang, Shengfeng; Feng, Xin; Wu, Ye; Xiao, Jinhua

2017-05-01

In the last decades, human behavior has been deeply understanding owing to the huge quantities data of human behavior available for study. The main finding in human dynamics shows that temporal processes consist of high-activity bursty intervals alternating with long low-activity periods. A model, assuming the initiator of bursty follow a Poisson process, is widely used in the modeling of human behavior. Here, we provide further evidence for the hypothesis that different bursty intervals are independent. Furthermore, we introduce a special threshold to quantitatively distinguish the time scales of complex dynamics based on the hypothesis. Our results suggest that human communication behavior is a composite process of double dynamics with midrange memory length. The method for calculating memory length would enhance the performance of many sequence-dependent systems, such as server operation and topic identification.

Consolidated Human Activity Database (CHAD) for use in human exposure and health studies and predictive models

EPA Pesticide Factsheets

EPA scientists have compiled detailed data on human behavior from 22 separate exposure and time-use studies into CHAD. The database includes more than 54,000 individual study days of detailed human behavior.

A fuzzy Bayesian network approach to quantify the human behaviour during an evacuation

NASA Astrophysics Data System (ADS)

Ramli, Nurulhuda; Ghani, Noraida Abdul; Ahmad, Nazihah

2016-06-01

Bayesian Network (BN) has been regarded as a successful representation of inter-relationship of factors affecting human behavior during an emergency. This paper is an extension of earlier work of quantifying the variables involved in the BN model of human behavior during an evacuation using a well-known direct probability elicitation technique. To overcome judgment bias and reduce the expert's burden in providing precise probability values, a new approach for the elicitation technique is required. This study proposes a new fuzzy BN approach for quantifying human behavior during an evacuation. Three major phases of methodology are involved, namely 1) development of qualitative model representing human factors during an evacuation, 2) quantification of BN model using fuzzy probability and 3) inferencing and interpreting the BN result. A case study of three inter-dependencies of human evacuation factors such as danger assessment ability, information about the threat and stressful conditions are used to illustrate the application of the proposed method. This approach will serve as an alternative to the conventional probability elicitation technique in understanding the human behavior during an evacuation.

Ergonomic Models of Anthropometry, Human Biomechanics and Operator-Equipment Interfaces

NASA Technical Reports Server (NTRS)

Kroemer, Karl H. E. (Editor); Snook, Stover H. (Editor); Meadows, Susan K. (Editor); Deutsch, Stanley (Editor)

1988-01-01

The Committee on Human Factors was established in October 1980 by the Commission on Behavioral and Social Sciences and Education of the National Research Council. The committee is sponsored by the Office of Naval Research, the Air Force Office of Scientific Research, the Army Research Institute for the Behavioral and Social Sciences, the National Aeronautics and Space Administration, and the National Science Foundation. The workshop discussed the following: anthropometric models; biomechanical models; human-machine interface models; and research recommendations. A 17-page bibliography is included.

On the Importance of Comparative Research for the Understanding of Human Behavior and Development: A Reply to Gottlieb & Lickliter (2004)

ERIC Educational Resources Information Center

Maestripieri, Dario

2005-01-01

Comparative behavioral research is important for a number of reasons and can contribute to the understanding of human behavior and development in many different ways. Research with animal models of human behavior and development can be a source not only of general principles and testable hypotheses but also of empirical information that may be…

Data-Driven Modeling of Target Human Behavior in Military Operations

DTIC Science & Technology

2014-03-12

Military Operations Elizabeth Mezzacappa, Ph.D. Gordon Cooke, MEME Gladstone Reid, MSBMS Robert DeMarco, MSBMS Charles Sheridan BA John...stress, and human behavior modeling and simulation issues. GORDON COOKE, MEME , is a Principal Investigator at the TBRL. He was also a Chief

A rationale for human operator pulsive control behavior

NASA Technical Reports Server (NTRS)

Hess, R. A.

1979-01-01

When performing tracking tasks which involve demanding controlled elements such as those with K/s-squared dynamics, the human operator often develops discrete or pulsive control outputs. A dual-loop model of the human operator is discussed, the dominant adaptive feature of which is the explicit appearance of an internal model of the manipulator-controlled element dynamics in an inner feedback loop. Using this model, a rationale for pulsive control behavior is offered which is based upon the assumption that the human attempts to reduce the computational burden associated with time integration of sensory inputs. It is shown that such time integration is a natural consequence of having an internal representation of the K/s-squared-controlled element dynamics in the dual-loop model. A digital simulation is discussed in which a modified form of the dual-loop model is shown to be capable of producing pulsive control behavior qualitively comparable to that obtained in experiment.

Intelligent systems approach for automated identification of individual control behavior of a human operator

NASA Astrophysics Data System (ADS)

Zaychik, Kirill B.

Acceptable results have been obtained using conventional techniques to model the generic human operator's control behavior. However, little research has been done in an attempt to identify an individual based on his/her control behavior. The main hypothesis investigated in this dissertation is that different operators exhibit different control behavior when performing a given control task. Furthermore, inter-person differences are manifested in the amplitude and frequency content of the non-linear component of the control behavior. Two enhancements to the existing models of the human operator, which allow personalization of the modeled control behavior, are presented in this dissertation. One of the proposed enhancements accounts for the "testing" control signals, which are introduced by an operator for more accurate control of the system and/or to adjust his/her control strategy. Such enhancement uses the Artificial Neural Network (ANN), which can be fine-tuned to model the "testing" control behavior of a given individual. The other model enhancement took the form of an equiripple filter (EF), which conditions the power spectrum of the control signal before it is passed through the plant dynamics block. The filter design technique uses Parks-McClellan algorithm, which allows parameterization of the desired levels of power at certain frequencies. A novel automated parameter identification technique (APID) was developed to facilitate the identification process of the parameters of the selected models of the human operator. APID utilizes a Genetic Algorithm (GA) based optimization engine called the Bit-climbing Algorithm (BCA). Proposed model enhancements were validated using the experimental data obtained at three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. Validation analysis involves comparison of the actual and simulated control activity signals. Validation criteria used in this dissertation is based on comparing Power Spectral Densities of the control signals against that of the Precision model of the human operator. This dissertation also addresses the issue of applying the proposed human operator model augmentation to evaluate the effectiveness of the motion feedback when simulating the actual pilot control behavior in a flight simulator. The proposed modeling methodology allows for quantitative assessments and prediction of the need for platform motion, while performing aircraft/pilot simulation studies.

Simulating Visual Attention Allocation of Pilots in an Advanced Cockpit Environment

NASA Technical Reports Server (NTRS)

Frische, F.; Osterloh, J.-P.; Luedtke, A.

2011-01-01

This paper describes the results of experiments conducted with human line pilots and a cognitive pilot model during interaction with a new 40 Flight Management System (FMS). The aim of these experiments was to gather human pilot behavior data in order to calibrate the behavior of the model. Human behavior is mainly triggered by visual perception. Thus, the main aspect was to setup a profile of human pilots' visual attention allocation in a cockpit environment containing the new FMS. We first performed statistical analyses of eye tracker data and then compared our results to common results of familiar analyses in standard cockpit environments. The comparison has shown a significant influence of the new system on the visual performance of human pilots. Further on, analyses of the pilot models' visual performance have been performed. A comparison to human pilots' visual performance revealed important improvement potentials.

Towards Assessing the Human Trajectory Planning Horizon

PubMed Central

Nitsch, Verena; Meinzer, Dominik; Wollherr, Dirk

2016-01-01

Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models. PMID:27936015

Towards Assessing the Human Trajectory Planning Horizon.

PubMed

Carton, Daniel; Nitsch, Verena; Meinzer, Dominik; Wollherr, Dirk

2016-01-01

Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models.

Integrating human and natural systems in community psychology: an ecological model of stewardship behavior.

PubMed

Moskell, Christine; Allred, Shorna Broussard

2013-03-01

Community psychology (CP) research on the natural environment lacks a theoretical framework for analyzing the complex relationship between human systems and the natural world. We introduce other academic fields concerned with the interactions between humans and the natural environment, including environmental sociology and coupled human and natural systems. To demonstrate how the natural environment can be included within CP's ecological framework, we propose an ecological model of urban forest stewardship action. Although ecological models of behavior in CP have previously modeled health behaviors, we argue that these frameworks are also applicable to actions that positively influence the natural environment. We chose the environmental action of urban forest stewardship because cities across the United States are planting millions of trees and increased citizen participation in urban tree planting and stewardship will be needed to sustain the benefits provided by urban trees. We used the framework of an ecological model of behavior to illustrate multiple levels of factors that may promote or hinder involvement in urban forest stewardship actions. The implications of our model for the development of multi-level ecological interventions to foster stewardship actions are discussed, as well as directions for future research to further test and refine the model.

Modeling Human Steering Behavior During Path Following in Teleoperation of Unmanned Ground Vehicles.

PubMed

Mirinejad, Hossein; Jayakumar, Paramsothy; Ersal, Tulga

2018-04-01

This paper presents a behavioral model representing the human steering performance in teleoperated unmanned ground vehicles (UGVs). Human steering performance in teleoperation is considerably different from the performance in regular onboard driving situations due to significant communication delays in teleoperation systems and limited information human teleoperators receive from the vehicle sensory system. Mathematical models capturing the teleoperation performance are a key to making the development and evaluation of teleoperated UGV technologies fully simulation based and thus more rapid and cost-effective. However, driver models developed for the typical onboard driving case do not readily address this need. To fill the gap, this paper adopts a cognitive model that was originally developed for a typical highway driving scenario and develops a tuning strategy that adjusts the model parameters in the absence of human data to reflect the effect of various latencies and UGV speeds on driver performance in a teleoperated path-following task. Based on data collected from a human subject test study, it is shown that the tuned model can predict both the trend of changes in driver performance for different driving conditions and the best steering performance of human subjects in all driving conditions considered. The proposed model with the tuning strategy has a satisfactory performance in predicting human steering behavior in the task of teleoperated path following of UGVs. The established model is a suited candidate to be used in place of human drivers for simulation-based studies of UGV mobility in teleoperation systems.

Simulating the Evolution of the Human Family: Cooperative Breeding Increases in Harsh Environments

PubMed Central

Smaldino, Paul E.; Newson, Lesley; Schank, Jeffrey C.; Richerson, Peter J.

2013-01-01

Verbal and mathematical models that consider the costs and benefits of behavioral strategies have been useful in explaining animal behavior and are often used as the basis of evolutionary explanations of human behavior. In most cases, however, these models do not account for the effects that group structure and cultural traditions within a human population have on the costs and benefits of its members' decisions. Nor do they consider the likelihood that cultural as well as genetic traits will be subject to natural selection. In this paper, we present an agent-based model that incorporates some key aspects of human social structure and life history. We investigate the evolution of a population under conditions of different environmental harshness and in which selection can occur at the level of the group as well as the level of the individual. We focus on the evolution of a socially learned characteristic related to individuals' willingness to contribute to raising the offspring of others within their family group. We find that environmental harshness increases the frequency of individuals who make such contributions. However, under the conditions we stipulate, we also find that environmental variability can allow groups to survive with lower frequencies of helpers. The model presented here is inevitably a simplified representation of a human population, but it provides a basis for future modeling work toward evolutionary explanations of human behavior that consider the influence of both genetic and cultural transmission of behavior. PMID:24278318

Simulating the evolution of the human family: cooperative breeding increases in harsh environments.

PubMed

Smaldino, Paul E; Newson, Lesley; Schank, Jeffrey C; Richerson, Peter J

2013-01-01

Verbal and mathematical models that consider the costs and benefits of behavioral strategies have been useful in explaining animal behavior and are often used as the basis of evolutionary explanations of human behavior. In most cases, however, these models do not account for the effects that group structure and cultural traditions within a human population have on the costs and benefits of its members' decisions. Nor do they consider the likelihood that cultural as well as genetic traits will be subject to natural selection. In this paper, we present an agent-based model that incorporates some key aspects of human social structure and life history. We investigate the evolution of a population under conditions of different environmental harshness and in which selection can occur at the level of the group as well as the level of the individual. We focus on the evolution of a socially learned characteristic related to individuals' willingness to contribute to raising the offspring of others within their family group. We find that environmental harshness increases the frequency of individuals who make such contributions. However, under the conditions we stipulate, we also find that environmental variability can allow groups to survive with lower frequencies of helpers. The model presented here is inevitably a simplified representation of a human population, but it provides a basis for future modeling work toward evolutionary explanations of human behavior that consider the influence of both genetic and cultural transmission of behavior.

Simulating Human Cognition in the Domain of Air Traffic Control

NASA Technical Reports Server (NTRS)

Freed, Michael; Johnston, James C.; Null, Cynthia H. (Technical Monitor)

1995-01-01

Experiments intended to assess performance in human-machine interactions are often prohibitively expensive, unethical or otherwise impractical to run. Approximations of experimental results can be obtained, in principle, by simulating the behavior of subjects using computer models of human mental behavior. Computer simulation technology has been developed for this purpose. Our goal is to produce a cognitive model suitable to guide the simulation machinery and enable it to closely approximate a human subject's performance in experimental conditions. The described model is designed to simulate a variety of cognitive behaviors involved in routine air traffic control. As the model is elaborated, our ability to predict the effects of novel circumstances on controller error rates and other performance characteristics should increase. This will enable the system to project the impact of proposed changes to air traffic control procedures and equipment on controller performance.

Monitoring and decision making by people in man machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.

1979-01-01

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Analysis of topological relationships and network properties in the interactions of human beings

PubMed Central

Chen, Xuebo; Sun, Qiubai; Huang, Tianyun

2017-01-01

In the animal world, various kinds of collective motions have been found and proven to be efficient ways of carrying out some activities such as searching for food and avoiding predators. Many scholars research the interactions of collective behaviors of human beings according to the rules of collective behaviors of animals. Based on the Lennard-Jones potential function and a self-organization process, our paper proposes a topological communication model to simulate the collective behaviors of human beings. In the results of simulations, we find various types of collective behavior and fission behavior and discover the threshold for the emergence of collective behavior, which is the range five to seven for the number of topology K. According to the analysis of network properties of the model, the in-degree of individuals is always equal to the number of topology. In the stable state, the out-degrees of individuals distribute around the value of the number of topology K, except that the out-degree of a single individual is approximately double the out-degrees of the other individuals. In addition, under different initial conditions, some features of different kinds of networks emerge from the model. We also find the leader and herd mentality effects in the characteristics of the behaviors of human beings in our model. Thus, this work could be used to discover how to promote the emergence of beneficial group behaviors and prevent the emergence of harmful behaviors. PMID:28832629

What Does Quantum Physics Have to Do with Behavior Disorders?

ERIC Educational Resources Information Center

Center, David B.

This paper argues that human agency as a causal factor in behavior must be considered in any model of behavior and behavior disorders. Since human agency is historically tied to the issue of consciousness, to argue that consciousness plays a causal role in behavior requires a plausible explanation of consciousness. This paper proposes that…

Models of Pilot Behavior and Their Use to Evaluate the State of Pilot Training

NASA Astrophysics Data System (ADS)

Jirgl, Miroslav; Jalovecky, Rudolf; Bradac, Zdenek

2016-07-01

This article discusses the possibilities of obtaining new information related to human behavior, namely the changes or progressive development of pilots' abilities during training. The main assumption is that a pilot's ability can be evaluated based on a corresponding behavioral model whose parameters are estimated using mathematical identification procedures. The mean values of the identified parameters are obtained via statistical methods. These parameters are then monitored and their changes evaluated. In this context, the paper introduces and examines relevant mathematical models of human (pilot) behavior, the pilot-aircraft interaction, and an example of the mathematical analysis.

Using ontologies to model human navigation behavior in information networks: A study based on Wikipedia.

PubMed

Lamprecht, Daniel; Strohmaier, Markus; Helic, Denis; Nyulas, Csongor; Tudorache, Tania; Noy, Natalya F; Musen, Mark A

The need to examine the behavior of different user groups is a fundamental requirement when building information systems. In this paper, we present Ontology-based Decentralized Search (OBDS), a novel method to model the navigation behavior of users equipped with different types of background knowledge. Ontology-based Decentralized Search combines decentralized search, an established method for navigation in social networks, and ontologies to model navigation behavior in information networks. The method uses ontologies as an explicit representation of background knowledge to inform the navigation process and guide it towards navigation targets. By using different ontologies, users equipped with different types of background knowledge can be represented. We demonstrate our method using four biomedical ontologies and their associated Wikipedia articles. We compare our simulation results with base line approaches and with results obtained from a user study. We find that our method produces click paths that have properties similar to those originating from human navigators. The results suggest that our method can be used to model human navigation behavior in systems that are based on information networks, such as Wikipedia. This paper makes the following contributions: (i) To the best of our knowledge, this is the first work to demonstrate the utility of ontologies in modeling human navigation and (ii) it yields new insights and understanding about the mechanisms of human navigation in information networks.

Using ontologies to model human navigation behavior in information networks: A study based on Wikipedia

PubMed Central

Lamprecht, Daniel; Strohmaier, Markus; Helic, Denis; Nyulas, Csongor; Tudorache, Tania; Noy, Natalya F.; Musen, Mark A.

2015-01-01

The need to examine the behavior of different user groups is a fundamental requirement when building information systems. In this paper, we present Ontology-based Decentralized Search (OBDS), a novel method to model the navigation behavior of users equipped with different types of background knowledge. Ontology-based Decentralized Search combines decentralized search, an established method for navigation in social networks, and ontologies to model navigation behavior in information networks. The method uses ontologies as an explicit representation of background knowledge to inform the navigation process and guide it towards navigation targets. By using different ontologies, users equipped with different types of background knowledge can be represented. We demonstrate our method using four biomedical ontologies and their associated Wikipedia articles. We compare our simulation results with base line approaches and with results obtained from a user study. We find that our method produces click paths that have properties similar to those originating from human navigators. The results suggest that our method can be used to model human navigation behavior in systems that are based on information networks, such as Wikipedia. This paper makes the following contributions: (i) To the best of our knowledge, this is the first work to demonstrate the utility of ontologies in modeling human navigation and (ii) it yields new insights and understanding about the mechanisms of human navigation in information networks. PMID:26568745

Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation

NASA Astrophysics Data System (ADS)

Hu, Yao; Quinn, Christopher J.; Cai, Ximing; Garfinkle, Noah W.

2017-11-01

For agent-based modeling, the major challenges in deriving agents' behavioral rules arise from agents' bounded rationality and data scarcity. This study proposes a "gray box" approach to address the challenge by incorporating expert domain knowledge (i.e., human intelligence) with machine learning techniques (i.e., machine intelligence). Specifically, we propose using directed information graph (DIG), boosted regression trees (BRT), and domain knowledge to infer causal factors and identify behavioral rules from data. A case study is conducted to investigate farmers' pumping behavior in the Midwest, U.S.A. Results show that four factors identified by the DIG algorithm- corn price, underlying groundwater level, monthly mean temperature and precipitation- have main causal influences on agents' decisions on monthly groundwater irrigation depth. The agent-based model is then developed based on the behavioral rules represented by three DIGs and modeled by BRTs, and coupled with a physically-based groundwater model to investigate the impacts of agents' pumping behavior on the underlying groundwater system in the context of coupled human and environmental systems.

Animal models of extinction-induced depression: loss of reward and its consequences.

PubMed

Huston, Joseph P; Silva, Maria A de Souza; Komorowski, Mara; Schulz, Daniela; Topic, Bianca

2013-11-01

The absence or loss of rewards or reinforcers holds a major role in the development of depression in humans. In spite of the prevalence of extinction-induced depression (EID) in humans, few attempts have been made to establish animal models thereof. Here we present the concept of extinction-related depression and summarize the results of two sets of studies in our attempt to create animal models of EID, one set based on extinction after positive reinforcement in the Skinner-box, the other on extinction after negative reinforcement - escape from water. We found various behaviors emitted during the extinction trials that responded to treatment with antidepressant drugs: Accordingly, the important behavioral marker for EID during extinction of escape from the water was immobility. During extinction after positive reinforcement the important indices for extinction-induced depression are the withdrawal from the former site of reward, biting behavior and rearing up on the hind legs. Avoidance behavior and biting may model aspects of human depressive behavior, which may include withdrawal or avoidance as well as aggressive-like behaviors. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cognitive Empathy and Emotional Empathy in Human Behavior and Evolution

ERIC Educational Resources Information Center

Smith, Adam

2006-01-01

This article presents 7 simple models of the relationship between cognitive empathy (mental perspective taking) and emotional empathy (the vicarious sharing of emotion). I consider behavioral outcomes of the models, arguing that, during human evolution, natural selection may have acted on variation in the relationship between cognitive empathy and…

International Space Station Human Behavior and Performance Competency Model: Volume II

NASA Technical Reports Server (NTRS)

Schmidt, Lacey

2008-01-01

This document further defines the behavioral markers identified in the document "Human Behavior and Performance Competency Model" Vol. I. The Human Behavior and Performance (HBP) competencies were recommended as requirements to participate in international long duration missions, and form the basis for determining the HBP training curriculum for long duration crewmembers. This document provides details, examples, knowledge areas, and affective skills to support the use of the HBP competencies in training and evaluation. This document lists examples and details specific to HBP competencies required of astronauts/cosmonauts who participate in ISS expedition and other international long-duration missions. Please note that this model does not encompass all competencies required. While technical competencies are critical for crewmembers, they are beyond the scope of this document. Additionally, the competencies in this model (and subsequent objectives) are not intended to limit the internal activities or training programs of any international partner.

THE INTERNAL ORGANIZATION OF COMPUTER MODELS OF COGNITIVE BEHAVIOR.

ERIC Educational Resources Information Center

BAKER, FRANK B.

IF COMPUTER PROGRAMS ARE TO SERVE AS USEFUL MODELS OF COGNITIVE BEHAVIOR, THEIR CREATORS MUST FACE THE NEED TO ESTABLISH AN INTERNAL ORGANIZATION FOR THEIR MODEL WHICH IMPLEMENTS THE HIGHER LEVEL COGNITIVE BEHAVIORS ASSOCIATED WITH THE HUMAN CAPACITY FOR SELF-DIRECTION, AUTOCRITICISM, AND ADAPTATION. PRESENT COMPUTER MODELS OF COGNITIVE BEHAVIOR…

Cultivating Curiosity: Integrating Hybrid Teaching in Courses in Human Behavior in the Social Environment

ERIC Educational Resources Information Center

Rodriguez-Keyes, Elizabeth; Schneider, Dana A.

2013-01-01

This study illustrates an experience of implementing a hybrid model for teaching human behavior in the social environment in an urban university setting. Developing a hybrid model in a BSW program arose out of a desire to reach students in a different way. Designed to promote curiosity and active learning, this particular hybrid model has students…

Behavioral impairments in animal models for zinc deficiency

PubMed Central

Hagmeyer, Simone; Haderspeck, Jasmin Carmen; Grabrucker, Andreas Martin

2015-01-01

Apart from teratogenic and pathological effects of zinc deficiency such as the occurrence of skin lesions, anorexia, growth retardation, depressed wound healing, altered immune function, impaired night vision, and alterations in taste and smell acuity, characteristic behavioral changes in animal models and human patients suffering from zinc deficiency have been observed. Given that it is estimated that about 17% of the worldwide population are at risk for zinc deficiency and that zinc deficiency is associated with a variety of brain disorders and disease states in humans, it is of major interest to investigate, how these behavioral changes will affect the individual and a putative course of a disease. Thus, here, we provide a state of the art overview about the behavioral phenotypes observed in various models of zinc deficiency, among them environmentally produced zinc deficient animals as well as animal models based on a genetic alteration of a particular zinc homeostasis gene. Finally, we compare the behavioral phenotypes to the human condition of mild to severe zinc deficiency and provide a model, how zinc deficiency that is associated with many neurodegenerative and neuropsychological disorders might modify the disease pathologies. PMID:25610379

Modeling social crowds. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Poyato, David; Soler, Juan

2016-09-01

The study of human behavior is a complex task, but modeling some aspects of this behavior is an even more complicated and exciting idea. From crisis management to decision making in evacuation protocols, understanding the complexity of humans in stress situations is more and more demanded in our society by obvious reasons [5,6,8,12]. In this context, [4] deals with crowd dynamics with special attention to evacuation.

Concept Analysis: Health-Promoting Behaviors Related to Human Papilloma Virus (HPV) Infection.

PubMed

McCutcheon, Tonna; Schaar, Gina; Parker, Karen L

2015-01-01

The concept of health-promoting behaviors incorporates ideas presented in the Ottawa Charter of Public Health and the nursing-based Health Promotion Model. Despite the fact that the concept of health-promoting behaviors has a nursing influence, literature suggests nursing has inadequately developed and used this concept within nursing practice. A further review of literature regarding health promotion behaviors and the human papilloma virus suggest a distinct gap in nursing literature. This article presents a concept analysis of health-promoting behaviors related to the human papilloma virus in order to encourage the application of the concept into nursing practice, promote continued nursing research regarding this concept, and further expand the application of health-promoting behaviors to other situations and populations within the nursing discipline. Attributes of health-promoting behaviors are presented and include empowerment, participation, community, and a positive concept of health. Antecedents, consequences, and empirical referents are also presented, as are model, borderline, and contrary cases to help clarify the concept. Recommendations for human papilloma virus health-promoting behaviors within the nursing practice are also provided. © 2014 Wiley Periodicals, Inc.

Model-based influences on humans' choices and striatal prediction errors.

PubMed

Daw, Nathaniel D; Gershman, Samuel J; Seymour, Ben; Dayan, Peter; Dolan, Raymond J

2011-03-24

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. Copyright © 2011 Elsevier Inc. All rights reserved.

Mathematical concepts for modeling human behavior in complex man-machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.; Rouse, W. B.

1979-01-01

Many human behavior (e.g., manual control) models have been found to be inadequate for describing processes in certain real complex man-machine systems. An attempt is made to find a way to overcome this problem by examining the range of applicability of existing mathematical models with respect to the hierarchy of human activities in real complex tasks. Automobile driving is chosen as a baseline scenario, and a hierarchy of human activities is derived by analyzing this task in general terms. A structural description leads to a block diagram and a time-sharing computer analogy.

Avian Models for Human Cognitive Neuroscience: A Proposal.

PubMed

Clayton, Nicola S; Emery, Nathan J

2015-06-17

Research on avian cognitive neuroscience over the past two decades has revealed the avian brain to be a better model for understanding human cognition than previously thought, despite differences in the neuroarchitecture of avian and mammalian brains. The brain, behavior, and cognition of songbirds have provided an excellent model of human cognition in one domain, namely learning human language and the production of speech. There are other important behavioral candidates of avian cognition, however, notably the capacity of corvids to remember the past and plan for the future, as well as their ability to think about another's perspective, and physical reasoning. We review this work and assess the evidence that the corvid brain can support such a cognitive architecture. We propose potential applications of these behavioral paradigms for cognitive neuroscience, including recent work on single-cell recordings and neuroimaging in corvids. Finally, we discuss their impact on understanding human developmental cognition. Copyright © 2015 Elsevier Inc. All rights reserved.

Human Behavior Based Exploratory Model for Successful Implementation of Lean Enterprise in Industry

ERIC Educational Resources Information Center

Sawhney, Rupy; Chason, Stewart

2005-01-01

Currently available Lean tools such as Lean Assessments, Value Stream Mapping, and Process Flow Charting focus on system requirements and overlook human behavior. A need is felt for a tool that allows one to baseline personnel, determine personnel requirements and align system requirements with personnel requirements. Our exploratory model--The…

Prioritizing Conservation of Ungulate Calving Resources in Multiple-Use Landscapes

PubMed Central

Dzialak, Matthew R.; Harju, Seth M.; Osborn, Robert G.; Wondzell, John J.; Hayden-Wing, Larry D.; Winstead, Jeffrey B.; Webb, Stephen L.

2011-01-01

Background Conserving animal populations in places where human activity is increasing is an ongoing challenge in many parts of the world. We investigated how human activity interacted with maternal status and individual variation in behavior to affect reliability of spatially-explicit models intended to guide conservation of critical ungulate calving resources. We studied Rocky Mountain elk (Cervus elaphus) that occupy a region where 2900 natural gas wells have been drilled. Methodology/Principal Findings We present novel applications of generalized additive modeling to predict maternal status based on movement, and of random-effects resource selection models to provide population and individual-based inference on the effects of maternal status and human activity. We used a 2×2 factorial design (treatment vs. control) that included elk that were either parturient or non-parturient and in areas either with or without industrial development. Generalized additive models predicted maternal status (parturiency) correctly 93% of the time based on movement. Human activity played a larger role than maternal status in shaping resource use; elk showed strong spatiotemporal patterns of selection or avoidance and marked individual variation in developed areas, but no such pattern in undeveloped areas. This difference had direct consequences for landscape-level conservation planning. When relative probability of use was calculated across the study area, there was disparity throughout 72–88% of the landscape in terms of where conservation intervention should be prioritized depending on whether models were based on behavior in developed areas or undeveloped areas. Model validation showed that models based on behavior in developed areas had poor predictive accuracy, whereas the model based on behavior in undeveloped areas had high predictive accuracy. Conclusions/Significance By directly testing for differences between developed and undeveloped areas, and by modeling resource selection in a random-effects framework that provided individual-based inference, we conclude that: 1) amplified selection or avoidance behavior and individual variation, as responses to increasing human activity, complicate conservation planning in multiple-use landscapes, and 2) resource selection behavior in places where human activity is predictable or less dynamic may provide a more reliable basis from which to prioritize conservation action. PMID:21297866

Alterations in choice behavior by manipulations of world model.

PubMed

Green, C S; Benson, C; Kersten, D; Schrater, P

2010-09-14

How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) "probability matching"-a consistent example of suboptimal choice behavior seen in humans-occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning.

New Integrated Modeling Capabilities: MIDAS' Recent Behavioral Enhancements

NASA Technical Reports Server (NTRS)

Gore, Brian F.; Jarvis, Peter A.

2005-01-01

The Man-machine Integration Design and Analysis System (MIDAS) is an integrated human performance modeling software tool that is based on mechanisms that underlie and cause human behavior. A PC-Windows version of MIDAS has been created that integrates the anthropometric character "Jack (TM)" with MIDAS' validated perceptual and attention mechanisms. MIDAS now models multiple simulated humans engaging in goal-related behaviors. New capabilities include the ability to predict situations in which errors and/or performance decrements are likely due to a variety of factors including concurrent workload and performance influencing factors (PIFs). This paper describes a new model that predicts the effects of microgravity on a mission specialist's performance, and its first application to simulating the task of conducting a Life Sciences experiment in space according to a sequential or parallel schedule of performance.

Acquiring neural signals for developing a perception and cognition model

NASA Astrophysics Data System (ADS)

Li, Wei; Li, Yunyi; Chen, Genshe; Shen, Dan; Blasch, Erik; Pham, Khanh; Lynch, Robert

2012-06-01

The understanding of how humans process information, determine salience, and combine seemingly unrelated information is essential to automated processing of large amounts of information that is partially relevant, or of unknown relevance. Recent neurological science research in human perception, and in information science regarding contextbased modeling, provides us with a theoretical basis for using a bottom-up approach for automating the management of large amounts of information in ways directly useful for human operators. However, integration of human intelligence into a game theoretic framework for dynamic and adaptive decision support needs a perception and cognition model. For the purpose of cognitive modeling, we present a brain-computer-interface (BCI) based humanoid robot system to acquire brainwaves during human mental activities of imagining a humanoid robot-walking behavior. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model. The BCI system consists of a data acquisition unit with an electroencephalograph (EEG), a humanoid robot, and a charge couple CCD camera. An EEG electrode cup acquires brainwaves from the skin surface on scalp. The humanoid robot has 20 degrees of freedom (DOFs); 12 DOFs located on hips, knees, and ankles for humanoid robot walking, 6 DOFs on shoulders and arms for arms motion, and 2 DOFs for head yaw and pitch motion. The CCD camera takes video clips of the human subject's hand postures to identify mental activities that are correlated to the robot-walking behaviors. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model.

Variables, Decisions, and Scripting in Construct

DTIC Science & Technology

2009-09-01

grounded in sociology and cognitive science which seeks to model the processes and situations by which humans interact and share information...Construct is an embodiment of constructuralism (Carley 1986), a theory which posits that human social structures and cognitive structures co-evolve so that...human cognition reflects human social behavior, and that human social behavior simultaneously influences cognitive processes. Recent work with

Human hippocampus arbitrates approach-avoidance conflict.

PubMed

Bach, Dominik R; Guitart-Masip, Marc; Packard, Pau A; Miró, Júlia; Falip, Mercè; Fuentemilla, Lluís; Dolan, Raymond J

2014-03-03

Animal models of human anxiety often invoke a conflict between approach and avoidance. In these, a key behavioral assay comprises passive avoidance of potential threat and inhibition, both thought to be controlled by ventral hippocampus. Efforts to translate these approaches to clinical contexts are hampered by the fact that it is not known whether humans manifest analogous approach-avoidance dispositions and, if so, whether they share a homologous neurobiological substrate. Here, we developed a paradigm to investigate the role of human hippocampus in arbitrating an approach-avoidance conflict under varying levels of potential threat. Across four experiments, subjects showed analogous behavior by adapting both passive avoidance behavior and behavioral inhibition to threat level. Using functional magnetic resonance imaging (fMRI), we observe that threat level engages the anterior hippocampus, the human homolog of rodent ventral hippocampus. Testing patients with selective hippocampal lesions, we demonstrate a causal role for the hippocampus with patients showing reduced passive avoidance behavior and inhibition across all threat levels. Our data provide the first human assay for approach-avoidance conflict akin to that of animal anxiety models. The findings bridge rodent and human research on passive avoidance and behavioral inhibition and furnish a framework for addressing the neuronal underpinnings of human anxiety disorders, where our data indicate a major role for the hippocampus. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

A new flexible plug and play scheme for modeling, simulating, and predicting gastric emptying

PubMed Central

2014-01-01

Background In-silico models that attempt to capture and describe the physiological behavior of biological organisms, including humans, are intrinsically complex and time consuming to build and simulate in a computing environment. The level of detail of description incorporated in the model depends on the knowledge of the system’s behavior at that level. This knowledge is gathered from the literature and/or improved by knowledge obtained from new experiments. Thus model development is an iterative developmental procedure. The objective of this paper is to describe a new plug and play scheme that offers increased flexibility and ease-of-use for modeling and simulating physiological behavior of biological organisms. Methods This scheme requires the modeler (user) first to supply the structure of the interacting components and experimental data in a tabular format. The behavior of the components described in a mathematical form, also provided by the modeler, is externally linked during simulation. The advantage of the plug and play scheme for modeling is that it requires less programming effort and can be quickly adapted to newer modeling requirements while also paving the way for dynamic model building. Results As an illustration, the paper models the dynamics of gastric emptying behavior experienced by humans. The flexibility to adapt the model to predict the gastric emptying behavior under varying types of nutrient infusion in the intestine (ileum) is demonstrated. The predictions were verified with a human intervention study. The error in predicting the half emptying time was found to be less than 6%. Conclusions A new plug-and-play scheme for biological systems modeling was developed that allows changes to the modeled structure and behavior with reduced programming effort, by abstracting the biological system into a network of smaller sub-systems with independent behavior. In the new scheme, the modeling and simulation becomes an automatic machine readable and executable task. PMID:24917054

Animal Models of Suicide Trait-Related Behaviors

PubMed Central

Malkesman, Oz; Pine, Daniel; Tragon, Tyson; Austin, Daniel R.; Henter, Ioline D.; Chen, Guang; Manji, Husseini K.

2009-01-01

Although antidepressants are at least moderately effective in treating major depressive disorder (MDD), concerns have arisen that selective serotonin reuptake inhibitors (SSRIs) are associated with suicidal thinking and behavior, especially in children, adolescents, and young adults. Virtually no experimental research in model systems has considered the mechanisms by which SSRIs may be associated with this potential side effect in some susceptible individuals. Suicide is a complex behavior that is, at best, complicated to study in humans and impossible to fully reproduce in an animal model. However, by investigating traits that show strong cross-species parallels as well as associations with suicide in humans, animal models may elucidate the mechanisms by which SSRIs are associated with suicidal thinking and behavior in the young. Traits linked with suicide in humans that can be successfully modeled in rodents include aggression, impulsivity, irritability, and hopelessness/helplessness. Differences in animal response to particular paradigms and to SSRIs across the lifespan are also discussed. Modeling these relevant traits in animals can help clarify the impact of SSRIs on these traits, suggesting avenues for reducing suicide risk in this vulnerable population. PMID:19269045

Modeling aspects of human memory for scientific study.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caudell, Thomas P.; Watson, Patrick; McDaniel, Mark A.

Working with leading experts in the field of cognitive neuroscience and computational intelligence, SNL has developed a computational architecture that represents neurocognitive mechanisms associated with how humans remember experiences in their past. The architecture represents how knowledge is organized and updated through information from individual experiences (episodes) via the cortical-hippocampal declarative memory system. We compared the simulated behavioral characteristics with those of humans measured under well established experimental standards, controlling for unmodeled aspects of human processing, such as perception. We used this knowledge to create robust simulations of & human memory behaviors that should help move the scientific community closermore » to understanding how humans remember information. These behaviors were experimentally validated against actual human subjects, which was published. An important outcome of the validation process will be the joining of specific experimental testing procedures from the field of neuroscience with computational representations from the field of cognitive modeling and simulation.« less

A framework for studying emotions across species.

PubMed

Anderson, David J; Adolphs, Ralph

2014-03-27

Since the 19th century, there has been disagreement over the fundamental question of whether "emotions" are cause or consequence of their associated behaviors. This question of causation is most directly addressable in genetically tractable model organisms, including invertebrates such as Drosophila. Yet there is ongoing debate about whether such species even have "emotions," as emotions are typically defined with reference to human behavior and neuroanatomy. Here, we argue that emotional behaviors are a class of behaviors that express internal emotion states. These emotion states exhibit certain general functional and adaptive properties that apply across any specific human emotions like fear or anger, as well as across phylogeny. These general properties, which can be thought of as "emotion primitives," can be modeled and studied in evolutionarily distant model organisms, allowing functional dissection of their mechanistic bases and tests of their causal relationships to behavior. More generally, our approach not only aims at better integration of such studies in model organisms with studies of emotion in humans, but also suggests a revision of how emotion should be operationalized within psychology and psychiatry. Copyright © 2014 Elsevier Inc. All rights reserved.

A Framework for Studying Emotions Across Phylogeny

PubMed Central

Anderson, David J.; Adolphs, Ralph

2014-01-01

Since the 19th century, there has been disagreement over the fundamental question of whether “emotions” are cause or consequence of their associated behaviors. This question of causation is most directly addressable in genetically tractable model organisms, including invertebrates such as Drosophila. Yet there is ongoing debate about whether such species even have “emotions,” since emotions are typically defined with reference to human behavior and neuroanatomy. Here we argue that emotional behaviors are a class of behaviors that express internal emotion states. These emotion states exhibit certain general functional and adaptive properties that apply across any specific human emotions like fear or anger, as well as across phylogeny. These general properties, which can be thought of as “emotion primitives”, can be modeled and studied in evolutionarily distant model organisms, allowing functional dissection of their mechanistic bases, and tests of their causal relationships to behavior. More generally, our approach aims not only at better integration of such studies in model organisms with studies of emotion in humans, but also suggests a revision of how emotion should be operationalized within psychology and psychiatry. PMID:24679535

Oxytocin Receptor Gene Polymorphisms Are Associated with Human Directed Social Behavior in Dogs (Canis familiaris)

PubMed Central

Lakatos, Gabriella; Pergel, Enikő; Turcsán, Borbála; Pluijmakers, Jolanda; Vas, Judit; Elek, Zsuzsanna; Brúder, Ildikó; Földi, Levente; Sasvári-Székely, Mária; Miklósi, Ádám; Rónai, Zsolt; Kubinyi, Enikő

2014-01-01

The oxytocin system has a crucial role in human sociality; several results prove that polymorphisms of the oxytocin receptor gene are related to complex social behaviors in humans. Dogs' parallel evolution with humans and their adaptation to the human environment has made them a useful species to model human social interactions. Previous research indicates that dogs are eligible models for behavioral genetic research, as well. Based on these previous findings, our research investigated associations between human directed social behaviors and two newly described (−212AG, 19131AG) and one known (rs8679684) single nucleotide polymorphisms (SNPs) in the regulatory regions (5′ and 3′ UTR) of the oxytocin receptor gene in German Shepherd (N = 104) and Border Collie (N = 103) dogs. Dogs' behavior traits have been estimated in a newly developed test series consisting of five episodes: Greeting by a stranger, Separation from the owner, Problem solving, Threatening approach, Hiding of the owner. Buccal samples were collected and DNA was isolated using standard protocols. SNPs in the 3′ and 5′ UTR regions were analyzed by polymerase chain reaction based techniques followed by subsequent electrophoresis analysis. The gene–behavior association analysis suggests that oxytocin receptor gene polymorphisms have an impact in both breeds on (i) proximity seeking towards an unfamiliar person, as well as their owner, and on (ii) how friendly dogs behave towards strangers, although the mediating molecular regulatory mechanisms are yet unknown. Based on these results, we conclude that similarly to humans, the social behavior of dogs towards humans is influenced by the oxytocin system. PMID:24454713

Oxytocin receptor gene polymorphisms are associated with human directed social behavior in dogs (Canis familiaris).

PubMed

Kis, Anna; Bence, Melinda; Lakatos, Gabriella; Pergel, Enikő; Turcsán, Borbála; Pluijmakers, Jolanda; Vas, Judit; Elek, Zsuzsanna; Brúder, Ildikó; Földi, Levente; Sasvári-Székely, Mária; Miklósi, Adám; Rónai, Zsolt; Kubinyi, Enikő

2014-01-01

The oxytocin system has a crucial role in human sociality; several results prove that polymorphisms of the oxytocin receptor gene are related to complex social behaviors in humans. Dogs' parallel evolution with humans and their adaptation to the human environment has made them a useful species to model human social interactions. Previous research indicates that dogs are eligible models for behavioral genetic research, as well. Based on these previous findings, our research investigated associations between human directed social behaviors and two newly described (-212AG, 19131AG) and one known (rs8679684) single nucleotide polymorphisms (SNPs) in the regulatory regions (5' and 3' UTR) of the oxytocin receptor gene in German Shepherd (N = 104) and Border Collie (N = 103) dogs. Dogs' behavior traits have been estimated in a newly developed test series consisting of five episodes: Greeting by a stranger, Separation from the owner, Problem solving, Threatening approach, Hiding of the owner. Buccal samples were collected and DNA was isolated using standard protocols. SNPs in the 3' and 5' UTR regions were analyzed by polymerase chain reaction based techniques followed by subsequent electrophoresis analysis. The gene-behavior association analysis suggests that oxytocin receptor gene polymorphisms have an impact in both breeds on (i) proximity seeking towards an unfamiliar person, as well as their owner, and on (ii) how friendly dogs behave towards strangers, although the mediating molecular regulatory mechanisms are yet unknown. Based on these results, we conclude that similarly to humans, the social behavior of dogs towards humans is influenced by the oxytocin system.

A visco-hyperelastic constitutive model for human spine ligaments.

PubMed

Jiang, Yugang; Wang, Yu; Peng, Xiongqi

2015-03-01

Human spine ligaments show a highly non-linear, strain rate dependent biomechanical behavior under tensile tests. A visco-hyperelastic fiber-reinforced constitutive model was accordingly developed for human ligaments, in which the energy density function is decomposed into two parts. The first part represents the elastic strain energy stored in the soft tissue, and the second part denotes the energy dissipated due to its inherent viscous characteristics. The model is applied to various human spinal ligaments including the anterior and posterior longitudinal ligaments, ligamentum flavum, capsular ligament, and interspinous ligament. Material parameters for each type of ligament were obtained by curve-fitting with corresponding experimental data available in the literature. The results indicate that the model presented here can properly characterize the visco-hyperelastic biomechanical behavior of human spine ligaments.

Discrimination of Complex Human Behavior by Pigeons (Columba livia) and Humans

PubMed Central

Qadri, Muhammad A. J.; Sayde, Justin M.; Cook, Robert G.

2014-01-01

The cognitive and neural mechanisms for recognizing and categorizing behavior are not well understood in non-human animals. In the current experiments, pigeons and humans learned to categorize two non-repeating, complex human behaviors (“martial arts” vs. “Indian dance”). Using multiple video exemplars of a digital human model, pigeons discriminated these behaviors in a go/no-go task and humans in a choice task. Experiment 1 found that pigeons already experienced with discriminating the locomotive actions of digital animals acquired the discrimination more rapidly when action information was available than when only pose information was available. Experiments 2 and 3 found this same dynamic superiority effect with naïve pigeons and human participants. Both species used the same combination of immediately available static pose information and more slowly perceived dynamic action cues to discriminate the behavioral categories. Theories based on generalized visual mechanisms, as opposed to embodied, species-specific action networks, offer a parsimonious account of how these different animals recognize behavior across and within species. PMID:25379777

Simple deterministic models and applications. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Yang, Hyun Mo

2015-12-01

Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.

Choices Matter, but How Do We Model Them?

NASA Astrophysics Data System (ADS)

Brelsford, C.; Dumas, M.

2017-12-01

Quantifying interactions between social systems and the physical environment we live within has long been a major scientific challenge. Humans have had such a large influence on our environment that it is no longer reasonable to consider the behavior of an ecological or hydrological system from a purely `physical' perspective: imagining a system that excludes the influence of human choices and behavior. Understanding the role that human social choices play in the energy water nexus is crucial for developing accurate models in that space. The relatively new field of socio-hydrology is making progress towards understanding the role humans play in hydrological systems. While this fact is now widely recognized across the many academic fields that study water systems, we have yet to develop a coherent set of theories for how to model the behavior of these complex and highly interdependent socio-hydrological systems. How should we conceptualize hydrological systems as socio-ecological systems (i.e. system with variables, states, parameters, actors who can control certain variables and a sense of the desirability of states) within which the rigorous study of feedbacks becomes possible? This talk reviews the state of knowledge of how social decisions around water consumption, allocation, and transport influence and are influenced by the physical hydrology that water also moves within. We cover recent papers in socio-hydrology, engineering, water law, and institutional analysis. There have been several calls within socio-hydrology to model human social behavior endogenously along with the hydrology. These improvements are needed across a range of spatial and temporal scales. We suggest two potential strategies for coupled models that allow endogenous water consumption behavior: a social first model which looks for empirical relationships between water consumption and allocation choices and the hydrological state, and a hydrology first model in which we look for regularities in how water regimes influence behavior, regional economies, or allocation institutions.

Our Social Roots: How Local Ecology Shapes Our Social Structures

NASA Astrophysics Data System (ADS)

Mace, Ruth

There is overwhelming evidence that wide-ranging aspects of human biology and human behavior can be considered as adaptations to different subsistence systems. Wider environmental and ecological correlates of behavioral and cultural traits are generally best understood as being mediated by differences in subsistence strategies. Modes of subsistence profoundly influence both human biology, as documented in genetic changes, and human social behavior and cultural norms, such as kinship, marriage, descent, wealth inheritance, and political systems. Thus both cultural and biological factors usually need to be considered together in studies of human evolutionary ecology, combined in specifically defined evolutionary models. Models of cultural adaptation to environmental conditions can be subjected to the same or similar tests that behavioral ecologists have used to seek evidence for adaptive behavior in other species. Phylogenetic comparative methods are proving useful, both for studying co-evolutionary hypotheses (cultural and/or gene-culture co-evolution), and for estimating ancestral states of prehistoric societies. This form of formal cross-cultural comparison is helping to put history back into anthropology, and helping us to understand cultural evolutionary processes at a number of levels.

Effects of Caffeine and Warrior Stress on Behavioral : An Animal Model

DTIC Science & Technology

2016-03-14

contributes invaluably to ethical and humane research. A special thank you to Erin Barry for providing statistical expertise and methodological support...of behavioral health in rats. Several ethical and logistical issues prevent the use of humans in true controlled experiments that manipulate stress...play in the development or maintenance of behavioral problems. There are ethical issues associated with exposing humans to high caffeine doses and

Genetic and non-genetic animal models for autism spectrum disorders (ASD).

PubMed

Ergaz, Zivanit; Weinstein-Fudim, Liza; Ornoy, Asher

2016-09-01

Autism spectrum disorder (ASD) is associated, in addition to complex genetic factors, with a variety of prenatal, perinatal and postnatal etiologies. We discuss the known animal models, mostly in mice and rats, of ASD that helps us to understand the etiology, pathogenesis and treatment of human ASD. We describe only models where behavioral testing has shown autistic like behaviors. Some genetic models mimic known human syndromes like fragile X where ASD is part of the clinical picture, and others are without defined human syndromes. Among the environmentally induced ASD models in rodents, the most common model is the one induced by valproic acid (VPA) either prenatally or early postnatally. VPA induces autism-like behaviors following single exposure during different phases of brain development, implying that the mechanism of action is via a general biological mechanism like epigenetic changes. Maternal infection and inflammation are also associated with ASD in man and animal models. Copyright © 2016 Elsevier Inc. All rights reserved.

Editorial: Cognitive Architectures, Model Comparison and AGI

NASA Astrophysics Data System (ADS)

Lebiere, Christian; Gonzalez, Cleotilde; Warwick, Walter

2010-12-01

Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly generating broadly intelligent behavior. In order to determine if progress is made, it is essential to be able to evaluate the behavior of complex computational models, especially those built on general cognitive architectures, and compare it to benchmarks of intelligent behavior such as human performance. Significant methodological challenges arise, however, when trying to extend approaches used to compare model and human performance from tightly controlled laboratory tasks to complex tasks involving more open-ended behavior. This paper describes a model comparison challenge built around a dynamic control task, the Dynamic Stocks and Flows. We present and discuss distinct approaches to evaluating performance and comparing models. Lessons drawn from this challenge are discussed in light of the challenge of using cognitive architectures to achieve Artificial General Intelligence.

The revolution that wasn't: a new interpretation of the origin of modern human behavior.

PubMed

Mcbrearty, S; Brooks, A S

2000-11-01

Proponents of the model known as the "human revolution" claim that modern human behaviors arose suddenly, and nearly simultaneously, throughout the Old World ca. 40-50 ka. This fundamental behavioral shift is purported to signal a cognitive advance, a possible reorganization of the brain, and the origin of language. Because the earliest modern human fossils, Homo sapiens sensu stricto, are found in Africa and the adjacent region of the Levant at >100 ka, the "human revolution" model creates a time lag between the appearance of anatomical modernity and perceived behavioral modernity, and creates the impression that the earliest modern Africans were behaviorally primitive. This view of events stems from a profound Eurocentric bias and a failure to appreciate the depth and breadth of the African archaeological record. In fact, many of the components of the "human revolution" claimed to appear at 40-50 ka are found in the African Middle Stone Age tens of thousands of years earlier. These features include blade and microlithic technology, bone tools, increased geographic range, specialized hunting, the use of aquatic resources, long distance trade, systematic processing and use of pigment, and art and decoration. These items do not occur suddenly together as predicted by the "human revolution" model, but at sites that are widely separated in space and time. This suggests a gradual assembling of the package of modern human behaviors in Africa, and its later export to other regions of the Old World. The African Middle and early Late Pleistocene hominid fossil record is fairly continuous and in it can be recognized a number of probably distinct species that provide plausible ancestors for H. sapiens. The appearance of Middle Stone Age technology and the first signs of modern behavior coincide with the appearance of fossils that have been attributed to H. helmei, suggesting the behavior of H. helmei is distinct from that of earlier hominid species and quite similar to that of modern people. If on anatomical and behavioral grounds H. helmei is sunk into H. sapiens, the origin of our species is linked with the appearance of Middle Stone Age technology at 250-300 ka. Copyright 2000 Academic Press.

Cross-species assessments of motor and exploratory behavior related to bipolar disorder.

PubMed

Henry, Brook L; Minassian, Arpi; Young, Jared W; Paulus, Martin P; Geyer, Mark A; Perry, William

2010-07-01

Alterations in exploratory behavior are a fundamental feature of bipolar mania, typically characterized as motor hyperactivity and increased goal-directed behavior in response to environmental cues. In contrast, abnormal exploration associated with schizophrenia and depression can manifest as prominent withdrawal, limited motor activity, and inattention to the environment. While motor abnormalities are cited frequently as clinical manifestations of these disorders, relatively few empirical studies have quantified human exploratory behavior. This article reviews the literature characterizing motor and exploratory behavior associated with bipolar disorder and genetic and pharmacological animal models of the illness. Despite sophisticated assessment of exploratory behavior in rodents, objective quantification of human motor activity has been limited primarily to actigraphy studies with poor cross-species translational value. Furthermore, symptoms that reflect the cardinal features of bipolar disorder have proven difficult to establish in putative animal models of this illness. Recently, however, novel tools such as the human behavioral pattern monitor provide multivariate translational measures of motor and exploratory activity, enabling improved understanding of the neurobiology underlying psychiatric disorders.

Unified underpinning of human mobility in the real world and cyberspace

NASA Astrophysics Data System (ADS)

Zhao, Yi-Ming; Zeng, An; Yan, Xiao-Yong; Wang, Wen-Xu; Lai, Ying-Cheng

2016-05-01

Human movements in the real world and in cyberspace affect not only dynamical processes such as epidemic spreading and information diffusion but also social and economical activities such as urban planning and personalized recommendation in online shopping. Despite recent efforts in characterizing and modeling human behaviors in both the real and cyber worlds, the fundamental dynamics underlying human mobility have not been well understood. We develop a minimal, memory-based random walk model in limited space for reproducing, with a single parameter, the key statistical behaviors characterizing human movements in both cases. The model is validated using relatively big data from mobile phone and online commerce, suggesting memory-based random walk dynamics as the unified underpinning for human mobility, regardless of whether it occurs in the real world or in cyberspace.

Retrospective revaluation in sequential decision making: a tale of two systems.

PubMed

Gershman, Samuel J; Markman, Arthur B; Otto, A Ross

2014-02-01

Recent computational theories of decision making in humans and animals have portrayed 2 systems locked in a battle for control of behavior. One system--variously termed model-free or habitual--favors actions that have previously led to reward, whereas a second--called the model-based or goal-directed system--favors actions that causally lead to reward according to the agent's internal model of the environment. Some evidence suggests that control can be shifted between these systems using neural or behavioral manipulations, but other evidence suggests that the systems are more intertwined than a competitive account would imply. In 4 behavioral experiments, using a retrospective revaluation design and a cognitive load manipulation, we show that human decisions are more consistent with a cooperative architecture in which the model-free system controls behavior, whereas the model-based system trains the model-free system by replaying and simulating experience.

A Dynamical Systems Model for Understanding Behavioral Interventions for Weight Loss

NASA Astrophysics Data System (ADS)

Navarro-Barrientos, J.-Emeterio; Rivera, Daniel E.; Collins, Linda M.

We propose a dynamical systems model that captures the daily fluctuations of human weight change, incorporating both physiological and psychological factors. The model consists of an energy balance integrated with a mechanistic behavioral model inspired by the Theory of Planned Behavior (TPB); the latter describes how important variables in a behavioral intervention can influence healthy eating habits and increased physical activity over time. The model can be used to inform behavioral scientists in the design of optimized interventions for weight loss and body composition change.

Interest-Driven Model for Human Dynamics

NASA Astrophysics Data System (ADS)

Shang, Ming-Sheng; Chen, Guan-Xiong; Dai, Shuang-Xing; Wang, Bing-Hong; Zhou, Tao

2010-04-01

Empirical observations indicate that the interevent time distribution of human actions exhibits heavy-tailed features. The queuing model based on task priorities is to some extent successful in explaining the origin of such heavy tails, however, it cannot explain all the temporal statistics of human behavior especially for the daily entertainments. We propose an interest-driven model, which can reproduce the power-law distribution of interevent time. The exponent can be analytically obtained and is in good accordance with the simulations. This model well explains the observed relationship between activities and power-law exponents, as reported recently for web-based behavior and the instant message communications.

Emergent collective decision-making: Control, model and behavior

NASA Astrophysics Data System (ADS)

Shen, Tian

In this dissertation we study emergent collective decision-making in social groups with time-varying interactions and heterogeneously informed individuals. First we analyze a nonlinear dynamical systems model motivated by animal collective motion with heterogeneously informed subpopulations, to examine the role of uninformed individuals. We find through formal analysis that adding uninformed individuals in a group increases the likelihood of a collective decision. Secondly, we propose a model for human shared decision-making with continuous-time feedback and where individuals have little information about the true preferences of other group members. We study model equilibria using bifurcation analysis to understand how the model predicts decisions based on the critical threshold parameters that represent an individual's tradeoff between social and environmental influences. Thirdly, we analyze continuous-time data of pairs of human subjects performing an experimental shared tracking task using our second proposed model in order to understand transient behavior and the decision-making process. We fit the model to data and show that it reproduces a wide range of human behaviors surprisingly well, suggesting that the model may have captured the mechanisms of observed behaviors. Finally, we study human behavior from a game-theoretic perspective by modeling the aforementioned tracking task as a repeated game with incomplete information. We show that the majority of the players are able to converge to playing Nash equilibrium strategies. We then suggest with simulations that the mean field evolution of strategies in the population resemble replicator dynamics, indicating that the individual strategies may be myopic. Decisions form the basis of control and problems involving deciding collectively between alternatives are ubiquitous in nature and in engineering. Understanding how multi-agent systems make decisions among alternatives also provides insight for designing decentralized control laws for engineering applications from mobile sensor networks for environmental monitoring to collective construction robots. With this dissertation we hope to provide additional methodology and mathematical models for understanding the behavior and control of collective decision-making in multi-agent systems.

Issues in Developing a Normative Descriptive Model for Dyadic Decision Making

NASA Technical Reports Server (NTRS)

Serfaty, D.; Kleinman, D. L.

1984-01-01

Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.

Neuropeptide Regulation of Social Attachment: The Prairie Vole Model

PubMed Central

Tabbaa, Manal; Paedae, Brennan; Liu, Yan; Wang, Zuoxin

2016-01-01

Social attachments are ubiquitous among humans and integral to human health. Although great efforts have been made to elucidate the neural underpinnings regulating social attachments, we still know relatively little about the neuronal and neurochemical regulation of social attachments. As a laboratory animal research model, the socially monogamous prairie vole (Microtus ochrogaster) displays behaviors paralleling human social attachments and thus has provided unique insights into the neural regulation of social behaviors. Research in prairie voles has particularly highlighted the significance of neuropeptidergic regulation of social behaviors, especially of the roles of oxytocin (OT) and vasopressin (AVP). This article aims to review these findings. We begin by discussing the role of the OT and AVP systems in regulating social behaviors relevant to social attachments, and thereafter restrict our discussion to studies in prairie voles. Specifically, we discuss the role of OT and AVP in adult mate attachments, biparental care, social isolation, and social buffering as informed by studies utilizing the prairie vole model. Not only do these studies offer insight into social attachments in humans, but they also point to dysregulated mechanisms in several mental disorders. We conclude by discussing these implications for human health. PMID:28135000

Grouping by proximity and the visual impression of approximate number in random dot arrays.

PubMed

Im, Hee Yeon; Zhong, Sheng-Hua; Halberda, Justin

2016-09-01

We address the challenges of how to model human perceptual grouping in random dot arrays and how perceptual grouping affects human number estimation in these arrays. We introduce a modeling approach relying on a modified k-means clustering algorithm to formally describe human observers' grouping behavior. We found that a default grouping window size of approximately 4° of visual angle describes human grouping judgments across a range of random dot arrays (i.e., items within 4° are grouped together). This window size was highly consistent across observers and images, and was also stable across stimulus durations, suggesting that the k-means model captured a robust signature of perceptual grouping. Further, the k-means model outperformed other models (e.g., CODE) at describing human grouping behavior. Next, we found that the more the dots in a display are clustered together, the more human observers tend to underestimate the numerosity of the dots. We demonstrate that this effect is independent of density, and the modified k-means model can predict human observers' numerosity judgments and underestimation. Finally, we explored the robustness of the relationship between clustering and dot number underestimation and found that the effects of clustering remain, but are greatly reduced, when participants receive feedback on every trial. Together, this work suggests some promising avenues for formal models of human grouping behavior, and it highlights the importance of a 4° window of perceptual grouping. Lastly, it reveals a robust, somewhat plastic, relationship between perceptual grouping and number estimation. Copyright © 2015 Elsevier Ltd. All rights reserved.

What every conservation biologist should know about economic theory.

PubMed

Gowdy, John; Hall, Charles; Klitgaard, Kent; Krall, Lisi

2010-12-01

The last century has seen the ascendance of a core economic model, which we will refer to as Walrasian economics. This model is driven by the psychological assumptions that humans act only in a self-referential and narrowly rational way and that production can be described as a self-contained circular flow between firms and households. These assumptions have critical implications for the way economics is used to inform conservation biology. Yet the Walrasian model is inconsistent with a large body of empirical evidence about actual human behavior, and it violates a number of basic physical laws. Research in behavioral science and neuroscience shows that humans are uniquely social animals and not self-centered rational economic beings. Economic production is subject to physical laws including the laws of thermodynamics and mass balance. In addition, some contemporary economic theory, spurred by exciting new research in human behavior and a wealth of data about the negative global impact of the human economy on natural systems, is moving toward a world view that places consumption and production squarely in its behavioral and biophysical context. We argue that abandoning the straightjacket of the Walrasian core is essential to further progress in understanding the complex, coupled interactions between the human economy and the natural world. We call for a new framework for economic theory and policy that is consistent with observed human behavior, recognizes the complex and frequently irreversible interaction between human and natural systems, and directly confronts the cumulative negative effects of the human economy on the Earth's life support systems. Biophysical economics and ecological economics are two emerging economic frameworks in this movement. © 2010 Society for Conservation Biology.

Model-based influences on humans’ choices and striatal prediction errors

PubMed Central

Daw, Nathaniel D.; Gershman, Samuel J.; Seymour, Ben; Dayan, Peter; Dolan, Raymond J.

2011-01-01

Summary The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. PMID:21435563

Complex Systems and Human Performance Modeling

DTIC Science & Technology

2013-12-01

human communication patterns can be implemented in a task network modeling tool. Although queues are a basic feature in many task network modeling...time. MODELING COMMUNICATIVE BEHAVIOR Barabasi (2010) argues that human communication patterns are “bursty”; that is, the inter-event arrival...Having implemented the methods advocated by Clauset et al. in C3TRACE, we have grown more confident that the human communication data discussed above

Marmosets: A Neuroscientific Model of Human Social Behavior

PubMed Central

Freiwald, Winrich A; Leopold, David A; Mitchell, Jude F; Silva, Afonso C; Wang, Xiaoqin

2016-01-01

The common marmoset (Callithrix jacchus) has garnered interest recently as a powerful model for the future of neuroscience research. Much of this excitement has centered on the species’ reproductive biology and compatibility with gene editing techniques, which together have provided a path for transgenic marmosets to contribute to the study of disease as well as basic brain mechanisms. In step with technical advances is the need to establish experimental paradigms that optimally tap into the marmosets’ behavioral and cognitive capacities. While conditioned task performance of a marmoset can compare unfavorably with rhesus monkey performance on conventional testing paradigms, marmosets’ social cognition and communication are more similar to that of humans. For example, marmosets are amongst only a handful of primates that, like humans, routinely pair bond and care cooperatively for their young. They are also notably pro-social and exhibit social cognitive abilities, such as imitation, that are rare outside of the Apes. In this review, we describe key facets of marmoset natural social behavior and demonstrate that emerging behavioral paradigms are well suited to isolate components of marmoset cognition that are highly relevant to humans. These approaches generally embrace natural behavior and communication, which has been rare in conventional primate testing, and thus allow for a new consideration of neural mechanisms underlying primate social cognition and communication. We anticipate that through parallel technical and paradigmatic advances, marmosets will become an essential model of human social behavior, including its dysfunction in nearly all neuropsychiatric disorders. PMID:27100195

Behavioral Phenotyping Assays for Genetic Mouse Models of Neurodevelopmental, Neurodegenerative, and Psychiatric Disorders.

PubMed

Sukoff Rizzo, Stacey J; Crawley, Jacqueline N

2017-02-08

Animal models offer heuristic research tools to understand the causes of human diseases and to identify potential treatments. With rapidly evolving genetic engineering technologies, mutations identified in a human disorder can be generated in the mouse genome. Phenotypic outcomes of the mutation are then explicated to confirm hypotheses about causes and to discover effective therapeutics. Most neurodevelopmental, neurodegenerative, and psychiatric disorders are diagnosed primarily by their prominent behavioral symptoms. Mouse behavioral assays analogous to the human symptoms have been developed to analyze the consequences of mutations and to evaluate proposed therapeutics preclinically. Here we describe the range of mouse behavioral tests available in the established behavioral neuroscience literature, along with examples of their translational applications. Concepts presented have been successfully used in other species, including flies, worms, fish, rats, pigs, and nonhuman primates. Identical strategies can be employed to test hypotheses about environmental causes and gene × environment interactions.

Statistical learning and adaptive decision-making underlie human response time variability in inhibitory control.

PubMed

Ma, Ning; Yu, Angela J

2015-01-01

Response time (RT) is an oft-reported behavioral measure in psychological and neurocognitive experiments, but the high level of observed trial-to-trial variability in this measure has often limited its usefulness. Here, we combine computational modeling and psychophysics to examine the hypothesis that fluctuations in this noisy measure reflect dynamic computations in human statistical learning and corresponding cognitive adjustments. We present data from the stop-signal task (SST), in which subjects respond to a go stimulus on each trial, unless instructed not to by a subsequent, infrequently presented stop signal. We model across-trial learning of stop signal frequency, P(stop), and stop-signal onset time, SSD (stop-signal delay), with a Bayesian hidden Markov model, and within-trial decision-making with an optimal stochastic control model. The combined model predicts that RT should increase with both expected P(stop) and SSD. The human behavioral data (n = 20) bear out this prediction, showing P(stop) and SSD both to be significant, independent predictors of RT, with P(stop) being a more prominent predictor in 75% of the subjects, and SSD being more prominent in the remaining 25%. The results demonstrate that humans indeed readily internalize environmental statistics and adjust their cognitive/behavioral strategy accordingly, and that subtle patterns in RT variability can serve as a valuable tool for validating models of statistical learning and decision-making. More broadly, the modeling tools presented in this work can be generalized to a large body of behavioral paradigms, in order to extract insights about cognitive and neural processing from apparently quite noisy behavioral measures. We also discuss how this behaviorally validated model can then be used to conduct model-based analysis of neural data, in order to help identify specific brain areas for representing and encoding key computational quantities in learning and decision-making.

Generous economic investments after basolateral amygdala damage.

PubMed

van Honk, Jack; Eisenegger, Christoph; Terburg, David; Stein, Dan J; Morgan, Barak

2013-02-12

Contemporary economic models hold that instrumental and impulsive behaviors underlie human social decision making. The amygdala is assumed to be involved in social-economic behavior, but its role in human behavior is poorly understood. Rodent research suggests that the basolateral amygdala (BLA) subserves instrumental behaviors and regulates the central-medial amygdala, which subserves impulsive behaviors. The human amygdala, however, typically is investigated as a single unit. If these rodent data could be translated to humans, selective dysfunction of the human BLA might constrain instrumental social-economic decisions and result in more impulsive social-economic choice behavior. Here we show that humans with selective BLA damage and a functional central-medial amygdala invest nearly 100% more money in unfamiliar others in a trust game than do healthy controls. We furthermore show that this generosity is not caused by risk-taking deviations in nonsocial contexts. Moreover, these BLA-damaged subjects do not expect higher returns or perceive people as more trustworthy, implying that their generous investments are not instrumental in nature. These findings suggest that the human BLA is essential for instrumental behaviors in social-economic interactions.

Cognitive Model of Trust Dynamics Predicts Human Behavior within and between Two Games of Strategic Interaction with Computerized Confederate Agents

PubMed Central

Collins, Michael G.; Juvina, Ion; Gluck, Kevin A.

2016-01-01

When playing games of strategic interaction, such as iterated Prisoner's Dilemma and iterated Chicken Game, people exhibit specific within-game learning (e.g., learning a game's optimal outcome) as well as transfer of learning between games (e.g., a game's optimal outcome occurring at a higher proportion when played after another game). The reciprocal trust players develop during the first game is thought to mediate transfer of learning effects. Recently, a computational cognitive model using a novel trust mechanism has been shown to account for human behavior in both games, including the transfer between games. We present the results of a study in which we evaluate the model's a priori predictions of human learning and transfer in 16 different conditions. The model's predictive validity is compared against five model variants that lacked a trust mechanism. The results suggest that a trust mechanism is necessary to explain human behavior across multiple conditions, even when a human plays against a non-human agent. The addition of a trust mechanism to the other learning mechanisms within the cognitive architecture, such as sequence learning, instance-based learning, and utility learning, leads to better prediction of the empirical data. It is argued that computational cognitive modeling is a useful tool for studying trust development, calibration, and repair. PMID:26903892

W(h)ither the Oracle? Cognitive biases and other human challenges of integrated environmental modeling

USGS Publications Warehouse

Glynn, Pierre D.; Ames, D.P.; Quinn, N. W. T.; Rizzoli, A.E.

2014-01-01

Integrated environmental modeling (IEM) can organize and increase our knowledge of the complex, dynamic ecosystems that house our natural resources and control the quality of our environments. Human behavior, however, must be taken into account. Human biases/heuristics reflect adaptation over our evolutionary past to frequently experienced situations that affected our survival and that provided sharply distinguished feedbacks at the level of the individual. Unfortunately, human behavior is not adapted to the more diffusely experienced, less frequently encountered, problems and issues that IEM typically seeks to address in the simulation of natural resources and environments. While seeking inspiration from the prophetic traditions of the Oracle of Delphi, several human biases are identified that may affect how the science base of IEM is assembled, and how IEM results are interpreted and used. These biases are supported by personal observations, and by the findings of behavioral scientists. A process for critical analysis is proposed that solicits explicit accounting and cognizance of potential human biases. A number of suggestions are made to address the human challenges of IEM, in addition to maintaining attitudes of watchful humility, open-mindedness, honesty, and transparent accountability. These include creating a new area of study in the behavioral biogeosciences, using structured processes for engaging the modeling and stakeholder community in IEM, and using “red teams” to increase resilience of IEM constructs and use.

A Formal Investigation of the Organization of Guidance Behavior: Implications for Humans and Autonomous Guidance

NASA Astrophysics Data System (ADS)

Kong, Zhaodan

Guidance behavior generated either by artificial agents or humans has been actively studied in the fields of both robotics and cognitive science. The goals of these two fields are different. The former is the automatic generation of appropriate or even optimal behavior, while the latter is the understanding of the underlying mechanism. Their challenges, though, are closely related, the most important one being the lack of a unified, formal and grounded framework where the guidance behavior can be modeled and studied. This dissertation presents such a framework. In this framework, guidance behavior is analyzed as the closed-loop dynamics of the whole agent-environment system. The resulting dynamics give rise to interaction patterns. The central points of this dissertation are that: first of all, these patterns, which can be explained in terms of symmetries that are inherent to the guidance behavior, provide building blocks for the organization of behavior; second, the existence of these patterns and humans' organization of their guidance behavior based on these patterns are the reasons that humans can generate successful behavior in spite of all the complexities involved in the planning and control. This dissertation first gives an overview of the challenges existing in both scientific endeavors, such as human and animal spatial behavior study, and engineering endeavors, such as autonomous guidance system design. It then lays out the foundation for our formal framework, which states that guidance behavior should be interpreted as the collection of the closed-loop dynamics resulting from the agent's interaction with the environment. The following, illustrated by examples of three different UAVs, shows that the study of the closed-loop dynamics should not be done without the consideration of vehicle dynamics, as is the common practice in some of the studies in both autonomous guidance and human behavior analysis. The framework, the core concepts of which are symmetries and interaction patterns, is then elaborated on with the example of Dubins' vehicle's guidance behavior. The dissertation then describes the details of the agile human guidance experiments using miniature helicopters, the technique that is developed for the analysis of the experimental data and the analysis results. The results confirm that human guidance behavior indeed exhibits invariance as defined by interaction patterns. Subsequently, the behavior in each interaction pattern is investigated using piecewise affine model identification. Combined, the results provide a natural and formal decomposition of the behavior that can be unified under a hierarchical hidden Markov model. By employing the languages of dynamical system and control and by adopting algorithms from system identification and machine learning, the framework presented in this dissertation provides a fertile ground where these different disciplines can meet. It also promises multiple potential directions where future research can be headed.

Economic demand predicts addiction-like behavior and therapeutic efficacy of oxytocin in the rat.

PubMed

Bentzley, Brandon S; Jhou, Thomas C; Aston-Jones, Gary

2014-08-12

Development of new treatments for drug addiction will depend on high-throughput screening in animal models. However, an addiction biomarker fit for rapid testing, and useful in both humans and animals, is not currently available. Economic models are promising candidates. They offer a structured quantitative approach to modeling behavior that is mathematically identical across species, and accruing evidence indicates economic-based descriptors of human behavior may be particularly useful biomarkers of addiction severity. However, economic demand has not yet been established as a biomarker of addiction-like behavior in animals, an essential final step in linking animal and human studies of addiction through economic models. We recently developed a mathematical approach for rapidly modeling economic demand in rats trained to self-administer cocaine. We show here that economic demand, as both a spontaneous trait and induced state, predicts addiction-like behavior, including relapse propensity, drug seeking in abstinence, and compulsive (punished) drug taking. These findings confirm economic demand as a biomarker of addiction-like behavior in rats. They also support the view that excessive motivation plays an important role in addiction while extending the idea that drug dependence represents a shift from initially recreational to compulsive drug use. Finally, we found that economic demand for cocaine predicted the efficacy of a promising pharmacotherapy (oxytocin) in attenuating cocaine-seeking behaviors across individuals, demonstrating that economic measures may be used to rapidly identify the clinical utility of prospective addiction treatments.

Economic demand predicts addiction-like behavior and therapeutic efficacy of oxytocin in the rat

PubMed Central

Bentzley, Brandon S.; Jhou, Thomas C.; Aston-Jones, Gary

2014-01-01

Development of new treatments for drug addiction will depend on high-throughput screening in animal models. However, an addiction biomarker fit for rapid testing, and useful in both humans and animals, is not currently available. Economic models are promising candidates. They offer a structured quantitative approach to modeling behavior that is mathematically identical across species, and accruing evidence indicates economic-based descriptors of human behavior may be particularly useful biomarkers of addiction severity. However, economic demand has not yet been established as a biomarker of addiction-like behavior in animals, an essential final step in linking animal and human studies of addiction through economic models. We recently developed a mathematical approach for rapidly modeling economic demand in rats trained to self-administer cocaine. We show here that economic demand, as both a spontaneous trait and induced state, predicts addiction-like behavior, including relapse propensity, drug seeking in abstinence, and compulsive (punished) drug taking. These findings confirm economic demand as a biomarker of addiction-like behavior in rats. They also support the view that excessive motivation plays an important role in addiction while extending the idea that drug dependence represents a shift from initially recreational to compulsive drug use. Finally, we found that economic demand for cocaine predicted the efficacy of a promising pharmacotherapy (oxytocin) in attenuating cocaine-seeking behaviors across individuals, demonstrating that economic measures may be used to rapidly identify the clinical utility of prospective addiction treatments. PMID:25071176

Learning rational temporal eye movement strategies.

PubMed

Hoppe, David; Rothkopf, Constantin A

2016-07-19

During active behavior humans redirect their gaze several times every second within the visual environment. Where we look within static images is highly efficient, as quantified by computational models of human gaze shifts in visual search and face recognition tasks. However, when we shift gaze is mostly unknown despite its fundamental importance for survival in a dynamic world. It has been suggested that during naturalistic visuomotor behavior gaze deployment is coordinated with task-relevant events, often predictive of future events, and studies in sportsmen suggest that timing of eye movements is learned. Here we establish that humans efficiently learn to adjust the timing of eye movements in response to environmental regularities when monitoring locations in the visual scene to detect probabilistically occurring events. To detect the events humans adopt strategies that can be understood through a computational model that includes perceptual and acting uncertainties, a minimal processing time, and, crucially, the intrinsic costs of gaze behavior. Thus, subjects traded off event detection rate with behavioral costs of carrying out eye movements. Remarkably, based on this rational bounded actor model the time course of learning the gaze strategies is fully explained by an optimal Bayesian learner with humans' characteristic uncertainty in time estimation, the well-known scalar law of biological timing. Taken together, these findings establish that the human visual system is highly efficient in learning temporal regularities in the environment and that it can use these regularities to control the timing of eye movements to detect behaviorally relevant events.

Genetic and Environmental Influences on Behavior: Capturing All the Interplay

ERIC Educational Resources Information Center

Johnson, Wendy

2007-01-01

Basic quantitative genetic models of human behavioral variation have made clear that individual differences in behavior cannot be understood without acknowledging the importance of genetic influences. Yet these basic models estimate average, population-level genetic and environmental influences, obscuring differences that might exist within the…

Measuring and Modeling Behavioral Decision Dynamics in Collective Evacuation

PubMed Central

Carlson, Jean M.; Alderson, David L.; Stromberg, Sean P.; Bassett, Danielle S.; Craparo, Emily M.; Guiterrez-Villarreal, Francisco; Otani, Thomas

2014-01-01

Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In a controlled laboratory setting, our results quantify several key factors influencing individual evacuation decision making in a controlled laboratory setting. The experiment includes tensions between broadcast and peer-to-peer information, and contrasts the effects of temporal urgency associated with the imminence of the disaster and the effects of limited shelter capacity for evacuees. Based on empirical measurements of the cumulative rate of evacuations as a function of the instantaneous disaster likelihood, we develop a quantitative model for decision making that captures remarkably well the main features of observed collective behavior across many different scenarios. Moreover, this model captures the sensitivity of individual- and population-level decision behaviors to external pressures, and systematic deviations from the model provide meaningful estimates of variability in the collective response. Identification of robust methods for quantifying human decisions in the face of risk has implications for policy in disasters and other threat scenarios, specifically the development and testing of robust strategies for training and control of evacuations that account for human behavior and network topologies. PMID:24520331

Wavelet-frequency analysis for the detection of discontinuities in switched system models of human balance.

PubMed

Nema, Salam; Kowalczyk, Piotr; Loram, Ian

2017-01-01

This paper is concerned with detecting the presence of switching behavior in experimentally obtained posturographic data sets by means of a novel algorithm that is based on a combination of wavelet analysis and Hilbert transform. As a test-bed for the algorithm, we first use a switched model of human balance control during quiet standing with known switching behavior in four distinct configurations. We obtain a time-frequency representation of a signal generated by our model system. We are then able to detect manifestations of discontinuities (switchings) in the signal as spiking behavior. The frequency of switchings, measured by means of our algorithm and detected in our models systems, agrees with the frequency of spiking behavior found in the experimentally obtained posturographic data. Copyright © 2016. Published by Elsevier B.V.

Head Motion Modeling for Human Behavior Analysis in Dyadic Interaction

PubMed Central

Xiao, Bo; Georgiou, Panayiotis; Baucom, Brian; Narayanan, Shrikanth S.

2015-01-01

This paper presents a computational study of head motion in human interaction, notably of its role in conveying interlocutors’ behavioral characteristics. Head motion is physically complex and carries rich information; current modeling approaches based on visual signals, however, are still limited in their ability to adequately capture these important properties. Guided by the methodology of kinesics, we propose a data driven approach to identify typical head motion patterns. The approach follows the steps of first segmenting motion events, then parametrically representing the motion by linear predictive features, and finally generalizing the motion types using Gaussian mixture models. The proposed approach is experimentally validated using video recordings of communication sessions from real couples involved in a couples therapy study. In particular we use the head motion model to classify binarized expert judgments of the interactants’ specific behavioral characteristics where entrainment in head motion is hypothesized to play a role: Acceptance, Blame, Positive, and Negative behavior. We achieve accuracies in the range of 60% to 70% for the various experimental settings and conditions. In addition, we describe a measure of motion similarity between the interaction partners based on the proposed model. We show that the relative change of head motion similarity during the interaction significantly correlates with the expert judgments of the interactants’ behavioral characteristics. These findings demonstrate the effectiveness of the proposed head motion model, and underscore the promise of analyzing human behavioral characteristics through signal processing methods. PMID:26557047

A Reverse-Translational Approach to Bipolar Disorder: Rodent and human studies in the Behavioral Pattern Monitor

PubMed Central

Young, Jared W.; Minassian, Arpi; Paulus, Martin P.; Geyer, Mark A.; Perry, William

2007-01-01

Mania is the defining feature of Bipolar Disorder (BD). There has been limited progress in understanding the neurobiological underpinnings of BD mania and developing novel therapeutics, in part due to a paucity of relevant animal models with translational potential. Hyperactivity is a cardinal symptom of mania, traditionally measured in humans using observer-rated scales. Multivariate assessment of unconditioned locomotor behavior using the rat Behavioral Pattern Monitor (BPM) developed in our laboratory has shown that hyperactivity includes complex multifaceted behaviors. The BPM has been used to demonstrate differential effects of drugs on locomotor activity and exploratory behavior in rats. Studies of genetically engineered mice in a mouse BPM have confirmed its utility as a cross-species tool. In a “reverse-translational” approach to this work, we developed the human BPM to characterize motor activity in BD patients. Increased activity, object interactions, and altered locomotor patterns provide multidimensional phenotypes to model in the rodent BPM. This unique approach to modeling BD provides an opportunity to identify the neurobiology underlying BD mania and test novel antimanic agents. PMID:17706782

Folk-Psychological Interpretation of Human vs. Humanoid Robot Behavior: Exploring the Intentional Stance toward Robots.

PubMed

Thellman, Sam; Silvervarg, Annika; Ziemke, Tom

2017-01-01

People rely on shared folk-psychological theories when judging behavior. These theories guide people's social interactions and therefore need to be taken into consideration in the design of robots and other autonomous systems expected to interact socially with people. It is, however, not yet clear to what degree the mechanisms that underlie people's judgments of robot behavior overlap or differ from the case of human or animal behavior. To explore this issue, participants ( N = 90) were exposed to images and verbal descriptions of eight different behaviors exhibited either by a person or a humanoid robot. Participants were asked to rate the intentionality, controllability and desirability of the behaviors, and to judge the plausibility of seven different types of explanations derived from a recently proposed psychological model of lay causal explanation of human behavior. Results indicate: substantially similar judgments of human and robot behavior, both in terms of (1a) ascriptions of intentionality/controllability/desirability and in terms of (1b) plausibility judgments of behavior explanations; (2a) high level of agreement in judgments of robot behavior - (2b) slightly lower but still largely similar to agreement over human behaviors; (3) systematic differences in judgments concerning the plausibility of goals and dispositions as explanations of human vs. humanoid behavior. Taken together, these results suggest that people's intentional stance toward the robot was in this case very similar to their stance toward the human.

Beat Keeping in a Sea Lion As Coupled Oscillation: Implications for Comparative Understanding of Human Rhythm.

PubMed

Rouse, Andrew A; Cook, Peter F; Large, Edward W; Reichmuth, Colleen

2016-01-01

Human capacity for entraining movement to external rhythms-i.e., beat keeping-is ubiquitous, but its evolutionary history and neural underpinnings remain a mystery. Recent findings of entrainment to simple and complex rhythms in non-human animals pave the way for a novel comparative approach to assess the origins and mechanisms of rhythmic behavior. The most reliable non-human beat keeper to date is a California sea lion, Ronan, who was trained to match head movements to isochronous repeating stimuli and showed spontaneous generalization of this ability to novel tempos and to the complex rhythms of music. Does Ronan's performance rely on the same neural mechanisms as human rhythmic behavior? In the current study, we presented Ronan with simple rhythmic stimuli at novel tempos. On some trials, we introduced "perturbations," altering either tempo or phase in the middle of a presentation. Ronan quickly adjusted her behavior following all perturbations, recovering her consistent phase and tempo relationships to the stimulus within a few beats. Ronan's performance was consistent with predictions of mathematical models describing coupled oscillation: a model relying solely on phase coupling strongly matched her behavior, and the model was further improved with the addition of period coupling. These findings are the clearest evidence yet for parity in human and non-human beat keeping and support the view that the human ability to perceive and move in time to rhythm may be rooted in broadly conserved neural mechanisms.

Automation effects in a multiloop manual control system

NASA Technical Reports Server (NTRS)

Hess, R. A.; Mcnally, B. D.

1986-01-01

An experimental and analytical study was undertaken to investigate human interaction with a simple multiloop manual control system in which the human's activity was systematically varied by changing the level of automation. The system simulated was the longitudinal dynamics of a hovering helicopter. The automation-systems-stabilized vehicle responses from attitude to velocity to position and also provided for display automation in the form of a flight director. The control-loop structure resulting from the task definition can be considered a simple stereotype of a hierarchical control system. The experimental study was complemented by an analytical modeling effort which utilized simple crossover models of the human operator. It was shown that such models can be extended to the description of multiloop tasks involving preview and precognitive human operator behavior. The existence of time optimal manual control behavior was established for these tasks and the role which internal models may play in establishing human-machine performance was discussed.

Relevance of Rodent Models of Depression in Clinical Practice: Can We Overcome the Obstacles in Translational Neuropsychiatry?

PubMed

Söderlund, Johan; Lindskog, Maria

2018-04-23

The diagnosis of a mental disorder generally depends on clinical observations and phenomenological symptoms reported by the patient. The definition of a given diagnosis is criteria based and relies on the ability to accurately interpret subjective symptoms and complex behavior. This type of diagnosis comprises a challenge to translate to reliable animal models, and these translational uncertainties hamper the development of new treatments. In this review, we will discuss how depressive-like behavior can be induced in rodents, and the relationship between these models and depression in humans. Specifically, we suggest similarities between triggers of depressive-like behavior in animal models and human conditions known to increase the risk of depression, for example exhaustion and bullying. Although we acknowledge the potential problems in comparing animal findings to human conditions, such comparisons are useful for understanding the complexity of depression, and we highlight the need to develop clinical diagnoses and animal models in parallel to overcome translational uncertainties.

Real-Time Monitoring and Prediction of the Pilot Vehicle System (PVS) Closed-Loop Stability

NASA Astrophysics Data System (ADS)

Mandal, Tanmay Kumar

Understanding human control behavior is an important step for improving the safety of future aircraft. Considerable resources are invested during the design phase of an aircraft to ensure that the aircraft has desirable handling qualities. However, human pilots exhibit a wide range of control behaviors that are a function of external stimulus, aircraft dynamics, and human psychological properties (such as workload, stress factor, confidence, and sense of urgency factor). This variability is difficult to address comprehensively during the design phase and may lead to undesirable pilot-aircraft interaction, such as pilot-induced oscillations (PIO). This creates the need to keep track of human pilot performance in real-time to monitor the pilot vehicle system (PVS) stability. This work focused on studying human pilot behavior for the longitudinal axis of a remotely controlled research aircraft and using human-in-the-loop (HuIL) simulations to obtain information about the human controlled system (HCS) stability. The work in this dissertation is divided into two main parts: PIO analysis and human control model parameters estimation. To replicate different flight conditions, this study included time delay and elevator rate limiting phenomena, typical of actuator dynamics during the experiments. To study human control behavior, this study employed the McRuer model for single-input single-output manual compensatory tasks. McRuer model is a lead-lag controller with time delay which has been shown to adequately model manual compensatory tasks. This dissertation presents a novel technique to estimate McRuer model parameters in real-time and associated validation using HuIL simulations to correctly predict HCS stability. The McRuer model parameters were estimated in real-time using a Kalman filter approach. The estimated parameters were then used to analyze the stability of the closed-loop HCS and verify them against the experimental data. Therefore, the main contribution of this dissertation is the design of an unscented Kalman filter-based algorithm to estimate McRuer model parameters in real time, and a framework to validate this algorithm for single-input single-output manual compensatory tasks to predict instabilities.

Animal Models in Sexual Medicine: The Need and Importance of Studying Sexual Motivation.

PubMed

Ventura-Aquino, Elisa; Paredes, Raúl G

2017-01-01

Many different animal models of sexual medicine have been developed, demonstrating the complexity of studying the many interactions that influence sexual responses. A great deal of effort has been invested in measuring sexual motivation using different behavioral models mainly because human behavior is more complex than any model can reproduce. To compare different animal models of male and female behaviors that measure sexual motivation as a key element in sexual medicine and focus on models that use a combination of molecular techniques and behavioral measurements. We review the literature to describe models that evaluate different aspects of sexual motivation. No single test is sufficient to evaluate sexual motivation. The best approach is to evaluate animals in different behavioral tests to measure the motivational state of the subject. Different motivated behaviors such as aggression, singing in the case of birds, and sexual behavior, which are crucial for reproduction, are associated with changes in mRNA levels of different receptors in brain areas that are important in the control of reproduction. Research in animal models is crucial to understand the complexity of sexual behavior and all the mechanisms that influence such an important aspect of human well-being to decrease the physiologic and psychological impact of sexual dysfunctions. In other cases, research in different models is necessary to understand and recognize, not cure, the variability of sexuality, such as asexuality, which is another form of sexual orientation. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

How do social norms influence prosocial development?

PubMed

House, Bailey R

2018-04-01

Humans are both highly prosocial and extremely sensitive to social norms, and some theories suggest that norms are necessary to account for uniquely human forms of prosocial behavior and cooperation. Understanding how norms influence prosocial behavior is thus essential if we are to describe the psychology and development of prosocial behavior. In this article I review recent research from across the social sciences that provides (1) a theoretical model of how norms influence prosocial behavior, (2) empirical support for the model based on studies with adults and children, and (3) predictions about the psychological mechanisms through which norms shape prosocial behavior. I conclude by discussing the need for future studies into how prosocial behavior develops through emerging interactions between culturally varying norms, social cognition, emotions, and potentially genes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling a flexible representation machinery of human concept learning.

PubMed

Matsuka, Toshihiko; Sakamoto, Yasuaki; Chouchourelou, Arieta

2008-01-01

It is widely acknowledged that categorically organized abstract knowledge plays a significant role in high-order human cognition. Yet, there are many unknown issues about the nature of how categories are internally represented in our mind. Traditionally, it has been considered that there is a single innate internal representation system for categorical knowledge, such as Exemplars, Prototypes, or Rules. However, results of recent empirical and computational studies collectively suggest that the human internal representation system is apparently capable of exhibiting behaviors consistent with various types of internal representation schemes. We, then, hypothesized that humans' representational system as a dynamic mechanism, capable of selecting a representation scheme that meets situational characteristics, including complexities of category structure. The present paper introduces a framework for a cognitive model that integrates robust and flexible internal representation machinery. Three simulation studies were conducted. The results showed that SUPERSET, our new model, successfully exhibited cognitive behaviors that are consistent with three main theories of the human internal representation system. Furthermore, a simulation study on social cognitive behaviors showed that the model was capable of acquiring knowledge with high commonality, even for a category structure with numerous valid conceptualizations.

Validation and implementation of a novel high-throughput behavioral phenotyping instrument for mice

PubMed Central

Brodkin, Jesse; Frank, Dana; Grippo, Ryan; Hausfater, Michal; Gulinello, Maria; Achterholt, Nils; Gutzen, Christian

2015-01-01

Background Behavioral assessment of mutant mouse models and novel candidate drugs is a slow and labor intensive process. This limitation produces a significant impediment to CNS drug discovery. New method By combining video and vibration analysis we created an automated system that provides the most detailed description of mouse behavior available. Our system (The Behavioral Spectrometer) allowed for the rapid assessment of behavioral abnormalities in the BTBR model of Autism, the restraint model of stress and the irritant model of inflammatory pain. Results We found that each model produced a unique alteration of the spectrum of behavior emitted by the mice. BTBR mice engaged in more grooming and less rearing behaviors. Prior restraint stress produced dramatic increases in grooming activity at the expense of locomotor behavior. Pain produced profound decreases in emitted behavior that were reversible with analgesic treatment. Comparison with existing method(s) We evaluated our system through a direct comparison on the same subjects with the current “gold standard” of human observation of video recordings. Using the same mice evaluated over the same range of behaviors, the Behavioral Spectrometer produced a quantitative categorization of behavior that was highly correlated with the scores produced by trained human observers (r=0.97). Conclusions Our results show that this new system is a highly valid and sensitive method to characterize behavioral effects in mice. As a fully automated and easily scalable instrument the Behavioral Spectrometer represents a high-throughput behavioral tool that reduces the time and labor involved in behavioral research. PMID:24384067

How to identify the most effective control measures based on disease-behavior coupled mechanisms?. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Sun, Gui-Quan; Jin, Zhen

2015-12-01

Modelling infectious diseases on complex networks is a significant tool to understand the transmission of epidemics in human society, and consequently it has commanded increasing attention in the community of mathematicians, physicists, epidemiologists, public health policy-makers and so on [1-4]. Human behavior responses are associated with the emergence of infectious disease, for instance, wearing masks [5], staying away from a thick crowd [6], cutting contacts with infected individuals [7] and receiving a vaccination [8]. However, infectious diseases and human behavior were often modeled as independent systems in the literature, despite the fact that in the real world they are often mutually influential on each other, and hence their coupling exerts significant impacts on disease spread [9,10].

Social work perspectives on human behavior.

PubMed

Wodarski, J S

1993-01-01

This manuscript addresses recent developments in human behavior research that are relevant to social work practice. Specific items addressed are biological aspects of behavior, life span development, cognitive variables, the self-efficacy learning process, the perceptual process, the exchange model, group level variables, macro level variables, and gender and ethnic-racial variables. Where relevant, specific applications to social work practice are provided.

Cross-species assessments of Motor and Exploratory Behavior related to Bipolar Disorder

PubMed Central

Henry, Brook L.; Minassian, Arpi; Young, Jared W.; Paulus, Martin P.; Geyer, Mark A.; Perry, William

2010-01-01

Alterations in exploratory behavior are a fundamental feature of bipolar mania, typically characterized as motor hyperactivity and increased goal-directed behavior in response to environmental cues. In contrast, abnormal exploration associated with schizophrenia and depression can manifest as prominent withdrawal, limited motor activity, and inattention to the environment. While motor abnormalities are cited frequently as clinical manifestations of these disorders, relatively few empirical studies have quantified human exploratory behavior. This article reviews the literature characterizing motor and exploratory behavior associated with bipolar disorder and genetic and pharmacological animal models of the illness. Despite sophisticated assessment of exploratory behavior in rodents, objective quantification of human motor activity has been limited primarily to actigraphy studies with poor cross-species translational value. Furthermore, symptoms that reflect the cardinal features of bipolar disorder have proven difficult to establish in putative animal models of this illness. Recently, however, novel tools such as the Human Behavioral Pattern Monitor provide multivariate translational measures of motor and exploratory activity, enabling improved understanding of the neurobiology underlying psychiatric disorders. PMID:20398694

Mind-Reading and Behavior-Reading against Agents with and without Anthropomorphic Features in a Competitive Situation

PubMed Central

Terada, Kazunori; Yamada, Seiji

2017-01-01

Humans use two distinct cognitive strategies separately to understand and predict other humans' behavior. One is mind-reading, in which an internal state such as an intention or an emotional state is assumed to be a source of a variety of behaviors. The other is behavior-reading, in which an actor's behavior is modeled based on stimulus-response associations without assuming internal states behind the behavior. We hypothesize that anthropomorphic features are key for an observer switching between these two cognitive strategies in a competitive situation. We provide support for this hypothesis through two studies using four agents with different appearances. We show that only a human agent was thought to possess both the ability to generate a variety of behaviors and internal mental states, such as minds and emotions (Study 1). We also show that humans used mixed (opposing) strategies against a human agent and exploitative strategies against the agents with mechanical appearances when they played a repeated zero-sum game (Study 2). Our findings show that humans understand that human behavior is varied; that humans have internal states, such as minds and emotions; that the behavior of machines is governed by a limited number of fixed rules; and that machines do not possess internal mental states. Our findings also suggest that the function of mind-reading is to trigger a strategy for use against agents with variable behavior and that humans exploit others who lack behavioral variability based on behavior-reading in a competitive situation. PMID:28736536

Invertebrate models of alcoholism.

PubMed

Scholz, Henrike; Mustard, Julie A

2013-01-01

For invertebrates to become useful models for understanding the genetic and physiological mechanisms of alcoholism related behaviors and the predisposition towards alcoholism, several general requirements must be fulfilled. The animal should encounter ethanol in its natural habitat, so that the central nervous system of the organism will have evolved mechanisms for responding to ethanol exposure. How the brain adapts to ethanol exposure depends on its access to ethanol, which can be regulated metabolically and/or by physical barriers. Therefore, a model organism should have metabolic enzymes for ethanol degradation similar to those found in humans. The neurons and supporting glial cells of the model organism that regulate behaviors affected by ethanol should share the molecular and physiological pathways found in humans, so that results can be compared. Finally, the use of invertebrate models should offer advantages over traditional model systems and should offer new insights into alcoholism-related behaviors. In this review we will summarize behavioral similarities and identified genes and mechanisms underlying ethanol-induced behaviors in invertebrates. This review mainly focuses on the use of the nematode Caenorhabditis elegans, the honey bee Apis mellifera and the fruit fly Drosophila melanogaster as model systems. We will discuss insights gained from those studies in conjunction with their vertebrate model counterparts and the implications for future research into alcoholism and alcohol-induced behaviors.

Computer modeling of human decision making

NASA Technical Reports Server (NTRS)

Gevarter, William B.

1991-01-01

Models of human decision making are reviewed. Models which treat just the cognitive aspects of human behavior are included as well as models which include motivation. Both models which have associated computer programs, and those that do not, are considered. Since flow diagrams, that assist in constructing computer simulation of such models, were not generally available, such diagrams were constructed and are presented. The result provides a rich source of information, which can aid in construction of more realistic future simulations of human decision making.

Collective Motion of Humans in Mosh and Circle Pits at Heavy Metal Concerts

NASA Astrophysics Data System (ADS)

Silverberg, Jesse L.; Bierbaum, Matthew; Sethna, James P.; Cohen, Itai

2013-05-01

Human collective behavior can vary from calm to panicked depending on social context. Using videos publicly available online, we study the highly energized collective motion of attendees at heavy metal concerts. We find these extreme social gatherings generate similarly extreme behaviors: a disordered gaslike state called a mosh pit and an ordered vortexlike state called a circle pit. Both phenomena are reproduced in flocking simulations demonstrating that human collective behavior is consistent with the predictions of simplified models.

A brief history of behavioral assessment following experimental traumatic brain injury in juveniles.

PubMed

Hartman, Richard E

2011-12-01

This review focuses on assessment of behavioral outcomes following traumatic brain injury in juvenile animal models. In the 15 years since the first publication in this field, the majority of studies have used rats roughly equivalent to human toddlers in terms of brain development. Few studies have tested ages closer to human neonates, and fewer have assessed ages closer to human adolescents. Closed head impact has been the most commonly used model, causing relatively consistent motor and cognitive deficits. Additionally, closed head impacts of a more severe nature have generally led to behavioral deficits of a more severe nature. Impact models (both closed and open skull) have produced more severe deficits in younger animals than in older animals, similar to patterns observed in juvenile humans with traumatic brain injury. In contrast, the fluid percussion model has produced relatively subtle deficits that did not get worse with a more severe injury and were worse for older animals than younger animals. Most of the studies have looked at relatively short postinjury time points, and none so far have assessed behavior in old adult animals injured as juveniles. The review ends with a discussion of possible directions for future animal research into juvenile traumatic brain injury.

A Social Episode Model of Human Sexual Behavior

ERIC Educational Resources Information Center

Meyer, Robert G.; Freeman, William M.

1976-01-01

A social episode model of sexual behavior is proposed with emphasis placed on arousal as a crucial variable. This model argues against a disease or deficiency concept of homosexuality. The authors hold a therapist should adequately respond to a valid sexual orientation request. (Author)

Understanding the heavy-tailed dynamics in human behavior

NASA Astrophysics Data System (ADS)

Ross, Gordon J.; Jones, Tim

2015-06-01

The recent availability of electronic data sets containing large volumes of communication data has made it possible to study human behavior on a larger scale than ever before. From this, it has been discovered that across a diverse range of data sets, the interevent times between consecutive communication events obey heavy-tailed power law dynamics. Explaining this has proved controversial, and two distinct hypotheses have emerged. The first holds that these power laws are fundamental, and arise from the mechanisms such as priority queuing that humans use to schedule tasks. The second holds that they are statistical artifacts which only occur in aggregated data when features such as circadian rhythms and burstiness are ignored. We use a large social media data set to test these hypotheses, and find that although models that incorporate circadian rhythms and burstiness do explain part of the observed heavy tails, there is residual unexplained heavy-tail behavior which suggests a more fundamental cause. Based on this, we develop a quantitative model of human behavior which improves on existing approaches and gives insight into the mechanisms underlying human interactions.

A Comparison of Natural Language Processing Methods for Automated Coding of Motivational Interviewing.

PubMed

Tanana, Michael; Hallgren, Kevin A; Imel, Zac E; Atkins, David C; Srikumar, Vivek

2016-06-01

Motivational interviewing (MI) is an efficacious treatment for substance use disorders and other problem behaviors. Studies on MI fidelity and mechanisms of change typically use human raters to code therapy sessions, which requires considerable time, training, and financial costs. Natural language processing techniques have recently been utilized for coding MI sessions using machine learning techniques, rather than human coders, and preliminary results have suggested these methods hold promise. The current study extends this previous work by introducing two natural language processing models for automatically coding MI sessions via computer. The two models differ in the way they semantically represent session content, utilizing either 1) simple discrete sentence features (DSF model) and 2) more complex recursive neural networks (RNN model). Utterance- and session-level predictions from these models were compared to ratings provided by human coders using a large sample of MI sessions (N=341 sessions; 78,977 clinician and client talk turns) from 6 MI studies. Results show that the DSF model generally had slightly better performance compared to the RNN model. The DSF model had "good" or higher utterance-level agreement with human coders (Cohen's kappa>0.60) for open and closed questions, affirm, giving information, and follow/neutral (all therapist codes); considerably higher agreement was obtained for session-level indices, and many estimates were competitive with human-to-human agreement. However, there was poor agreement for client change talk, client sustain talk, and therapist MI-inconsistent behaviors. Natural language processing methods provide accurate representations of human derived behavioral codes and could offer substantial improvements to the efficiency and scale in which MI mechanisms of change research and fidelity monitoring are conducted. Copyright © 2016 Elsevier Inc. All rights reserved.

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

NASA Technical Reports Server (NTRS)

Rungta, Neha; Brat, Guillaume; Clancey, William J.; Linde, Charlotte; Raimondi, Franco; Seah, Chin; Shafto, Michael

2013-01-01

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Scale dependent behavioral responses to human development by a large predator, the puma.

PubMed

Wilmers, Christopher C; Wang, Yiwei; Nickel, Barry; Houghtaling, Paul; Shakeri, Yasaman; Allen, Maximilian L; Kermish-Wells, Joe; Yovovich, Veronica; Williams, Terrie

2013-01-01

The spatial scale at which organisms respond to human activity can affect both ecological function and conservation planning. Yet little is known regarding the spatial scale at which distinct behaviors related to reproduction and survival are impacted by human interference. Here we provide a novel approach to estimating the spatial scale at which a top predator, the puma (Puma concolor), responds to human development when it is moving, feeding, communicating, and denning. We find that reproductive behaviors (communication and denning) require at least a 4× larger buffer from human development than non-reproductive behaviors (movement and feeding). In addition, pumas give a wider berth to types of human development that provide a more consistent source of human interference (neighborhoods) than they do to those in which human presence is more intermittent (arterial roads with speeds >35 mph). Neighborhoods were a deterrent to pumas regardless of behavior, while arterial roads only deterred pumas when they were communicating and denning. Female pumas were less deterred by human development than males, but they showed larger variation in their responses overall. Our behaviorally explicit approach to modeling animal response to human activity can be used as a novel tool to assess habitat quality, identify wildlife corridors, and mitigate human-wildlife conflict.

A Simple Exploration of Complexity at the Climate-Weather-Social-Conflict Nexus

NASA Astrophysics Data System (ADS)

Shaw, M.

2017-12-01

The conceptualization, exploration, and prediction of interplay between climate, weather, important resources, and social and economic - so political - human behavior is cast, and analyzed, in terms familiar from statistical physics and nonlinear dynamics. A simple threshold toy model is presented which emulates human tendencies to either actively engage in responses deriving, in part, from environmental circumstances or to maintain some semblance of status quo, formulated based on efforts drawn from the sociophysics literature - more specifically vis a vis a model akin to spin glass depictions of human behavior - with threshold/switching of individual and collective dynamics influenced by relatively more detailed weather and land surface model (hydrological) analyses via a land data assimilation system (a custom rendition of the NASA GSFC Land Information System). Parameters relevant to human systems' - e.g., individual and collective switching - sensitivity to hydroclimatology are explored towards investigation of overall system behavior; i.e., fixed points/equilibria, oscillations, and bifurcations of systems composed of human interactions and responses to climate and weather through, e.g., agriculture. We discuss implications in terms of conceivable impacts of climate change and associated natural disasters on socioeconomics, politics, and power transfer, drawing from relatively recent literature concerning human conflict.

Theory of Planned Behavior in the Classroom: An Examination of the Instructor Confirmation-Interaction Model

ERIC Educational Resources Information Center

Burns, Michael E.; Houser, Marian L.; Farris, Kristen LeBlanc

2018-01-01

The current study utilizes the theory of planned behavior (Ajzen "Organizational Behavior and Human Decision Processes," 50, 179-211 Ajzen 1991) to examine an instructor confirmation-interaction model in the instructional communication context to discover a means by which instructors might cultivate positive student attitudes and…

COREBA (cognition-oriented emergent behavior architecture)

NASA Astrophysics Data System (ADS)

Kwak, S. David

2000-06-01

Currently, many behavior implementation technologies are available for modeling human behaviors in Department of Defense (DOD) computerized systems. However, it is commonly known that any single currently adopted behavior implementation technology is not so capable of fully representing complex and dynamic human decision-making and cognition behaviors. The author views that the current situation can be greatly improved if multiple technologies are integrated within a well designed overarching architecture that amplifies the merits of each of the participating technologies while suppressing the limitations that are inherent with each of the technologies. COREBA uses an overarching behavior integration architecture that makes the multiple implementation technologies cooperate in a homogeneous environment while collectively transcending the limitations associated with the individual implementation technologies. Specifically, COREBA synergistically integrates Artificial Intelligence and Complex Adaptive System under Rational Behavior Model multi-level multi- paradigm behavior architecture. This paper will describe applicability of COREBA in DOD domain, behavioral capabilities and characteristics of COREBA and how the COREBA architectural integrates various behavior implementation technologies.

To Pass or Not to Pass: Modeling the Movement and Affordance Dynamics of a Pick and Place Task

PubMed Central

Lamb, Maurice; Kallen, Rachel W.; Harrison, Steven J.; Di Bernardo, Mario; Minai, Ali; Richardson, Michael J.

2017-01-01

Humans commonly engage in tasks that require or are made more efficient by coordinating with other humans. In this paper we introduce a task dynamics approach for modeling multi-agent interaction and decision making in a pick and place task where an agent must move an object from one location to another and decide whether to act alone or with a partner. Our aims were to identify and model (1) the affordance related dynamics that define an actor's choice to move an object alone or to pass it to their co-actor and (2) the trajectory dynamics of an actor's hand movements when moving to grasp, relocate, or pass the object. Using a virtual reality pick and place task, we demonstrate that both the decision to pass or not pass an object and the movement trajectories of the participants can be characterized in terms of a behavioral dynamics model. Simulations suggest that the proposed behavioral dynamics model exhibits features observed in human participants including hysteresis in decision making, non-straight line trajectories, and non-constant velocity profiles. The proposed model highlights how the same low-dimensional behavioral dynamics can operate to constrain multiple (and often nested) levels of human activity and suggests that knowledge of what, when, where and how to move or act during pick and place behavior may be defined by these low dimensional task dynamics and, thus, can emerge spontaneously and in real-time with little a priori planning. PMID:28701975

Validating Computational Human Behavior Models: Consistency and Accuracy Issues

DTIC Science & Technology

2004-06-01

includes a discussion of SME demographics, content, and organization of the datasets . This research generalizes data from two pilot studies and two base...meet requirements for validating the varied and complex behavioral models. Through a series of empirical studies , this research identifies subject...meet requirements for validating the varied and complex behavioral models. Through a series of empirical studies , this research identifies subject

Folk-Psychological Interpretation of Human vs. Humanoid Robot Behavior: Exploring the Intentional Stance toward Robots

PubMed Central

Thellman, Sam; Silvervarg, Annika; Ziemke, Tom

2017-01-01

People rely on shared folk-psychological theories when judging behavior. These theories guide people’s social interactions and therefore need to be taken into consideration in the design of robots and other autonomous systems expected to interact socially with people. It is, however, not yet clear to what degree the mechanisms that underlie people’s judgments of robot behavior overlap or differ from the case of human or animal behavior. To explore this issue, participants (N = 90) were exposed to images and verbal descriptions of eight different behaviors exhibited either by a person or a humanoid robot. Participants were asked to rate the intentionality, controllability and desirability of the behaviors, and to judge the plausibility of seven different types of explanations derived from a recently proposed psychological model of lay causal explanation of human behavior. Results indicate: substantially similar judgments of human and robot behavior, both in terms of (1a) ascriptions of intentionality/controllability/desirability and in terms of (1b) plausibility judgments of behavior explanations; (2a) high level of agreement in judgments of robot behavior – (2b) slightly lower but still largely similar to agreement over human behaviors; (3) systematic differences in judgments concerning the plausibility of goals and dispositions as explanations of human vs. humanoid behavior. Taken together, these results suggest that people’s intentional stance toward the robot was in this case very similar to their stance toward the human. PMID:29184519

Effects of human activity of breeding American Oystercatchers, Cumberland Island National Seashore, Georgia, USA

USGS Publications Warehouse

Sabine, J.B.; Meyers, J.M.; Moore, C.T.; Schweitzer, Sara H.

2008-01-01

Abstract.-Increased human use of coastal areas threatens the United States population of American Oystercatchers (Haematopus palliatus), a species of special concern. Biologists often attribute its low numbers and reproductive success to human disturbance, but the mechanism by which human presence reduces reproductive success is not well understood. During the 2003 and 2004 breeding seasons, 32 nesting attempts of American Oystercatchers were studied on Cumberland Island National Seashore (CINS). Behavior was examined with and without human activity in the area to determine how human activity affected behavior. The oystercatchers' behavioral responses (proportion time) were analyzed with and without human or intraspecific disturbances using mixed models regression analysis. Proportions of time human activities were present (137 m and vehicular activity should be minimized at current levels or less.

Development and Validation of a Bioreactor System for Dynamic Loading and Mechanical Characterization of Whole Human Intervertebral Discs in Organ Culture

PubMed Central

Walter, BA; Illien-Junger, S; Nasser, P; Hecht, AC; Iatridis, JC

2014-01-01

Intervertebral disc (IVD) degeneration is a common cause of back pain, and attempts to develop therapies are frustrated by lack of model systems that mimic the human condition. Human IVD organ culture models can address this gap, yet current models are limited since vertebral endplates are removed to maintain cell viability, physiological loading is not applied, and mechanical behaviors are not measured. This study aimed to (i) establish a method for isolating human IVDs from autopsy with intact vertebral endplates, and (ii) develop and validate an organ culture loading system for human or bovine IVDs. Human IVDs with intact endplates were isolated from cadavers within 48 hours of death and cultured for up to 21 days. IVDs remained viable with ~80% cell viability in nucleus and annulus regions. A dynamic loading system was designed and built with the capacity to culture 9 bovine or 6 human IVDs simultaneously while applying simulated physiologic loads (maximum force: 4kN) and measuring IVD mechanical behaviors. The loading system accurately applied dynamic loading regimes (RMS error <2.5N and total harmonic distortion <2.45%), and precisely evaluated mechanical behavior of rubber and bovine IVDs. Bovine IVDs maintained their mechanical behavior and retained >85% viable cells throughout the 3 week culture period. This organ culture loading system can closely mimic physiological conditions and be used to investigate response of living human and bovine IVDs to mechanical and chemical challenges and to screen therapeutic repair techniques. PMID:24725441

A Network Neuroscience of Human Learning: Potential To Inform Quantitative Theories of Brain and Behavior

PubMed Central

Bassett, Danielle S.; Mattar, Marcelo G.

2017-01-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. PMID:28259554

A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

PubMed

Bassett, Danielle S; Mattar, Marcelo G

2017-04-01

Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Energy and Environmental Drivers of Stress and Conflict in Multi scale Models of Human Social Behavior

DTIC Science & Technology

2017-10-31

Report: Energy and Environmental Drivers of Stress and Conflict in Multi-scale Models of Human Social Behavior The views, opinions and/or findings...RPPR Final Report as of 08-Feb-2018 Agreement Number: W911NF-12-1-0097 Organization: Santa Fe Institute of Science Title: Energy and...Article Title: Determinants of the Pace of Global Innovation in Energy Technologies Keywords: climage change, innovations in energy technologies

A stochastic dynamic model for human error analysis in nuclear power plants

NASA Astrophysics Data System (ADS)

Delgado-Loperena, Dharma

Nuclear disasters like Three Mile Island and Chernobyl indicate that human performance is a critical safety issue, sending a clear message about the need to include environmental press and competence aspects in research. This investigation was undertaken to serve as a roadmap for studying human behavior through the formulation of a general solution equation. The theoretical model integrates models from two heretofore-disassociated disciplines (behavior specialists and technical specialists), that historically have independently studied the nature of error and human behavior; including concepts derived from fractal and chaos theory; and suggests re-evaluation of base theory regarding human error. The results of this research were based on comprehensive analysis of patterns of error, with the omnipresent underlying structure of chaotic systems. The study of patterns lead to a dynamic formulation, serving for any other formula used to study human error consequences. The search for literature regarding error yielded insight for the need to include concepts rooted in chaos theory and strange attractors---heretofore unconsidered by mainstream researchers who investigated human error in nuclear power plants or those who employed the ecological model in their work. The study of patterns obtained from the rupture of a steam generator tube (SGTR) event simulation, provided a direct application to aspects of control room operations in nuclear power plant operations. In doing so, the conceptual foundation based in the understanding of the patterns of human error analysis can be gleaned, resulting in reduced and prevent undesirable events.

A roadmap to computational social neuroscience.

PubMed

Tognoli, Emmanuelle; Dumas, Guillaume; Kelso, J A Scott

2018-02-01

To complement experimental efforts toward understanding human social interactions at both neural and behavioral levels, two computational approaches are presented: (1) a fully parameterizable mathematical model of a social partner, the Human Dynamic Clamp which, by virtue of experimentally controlled interactions between Virtual Partners and real people, allows for emergent behaviors to be studied; and (2) a multiscale neurocomputational model of social coordination that enables exploration of social self-organization at all levels-from neuronal patterns to people interacting with each other. These complementary frameworks and the cross product of their analysis aim at understanding the fundamental principles governing social behavior.

Using Virtual Reality to Assess Ethical Decisions in Road Traffic Scenarios: Applicability of Value-of-Life-Based Models and Influences of Time Pressure.

PubMed

Sütfeld, Leon R; Gast, Richard; König, Peter; Pipa, Gordon

2017-01-01

Self-driving cars are posing a new challenge to our ethics. By using algorithms to make decisions in situations where harming humans is possible, probable, or even unavoidable, a self-driving car's ethical behavior comes pre-defined. Ad hoc decisions are made in milliseconds, but can be based on extensive research and debates. The same algorithms are also likely to be used in millions of cars at a time, increasing the impact of any inherent biases, and increasing the importance of getting it right. Previous research has shown that moral judgment and behavior are highly context-dependent, and comprehensive and nuanced models of the underlying cognitive processes are out of reach to date. Models of ethics for self-driving cars should thus aim to match human decisions made in the same context. We employed immersive virtual reality to assess ethical behavior in simulated road traffic scenarios, and used the collected data to train and evaluate a range of decision models. In the study, participants controlled a virtual car and had to choose which of two given obstacles they would sacrifice in order to spare the other. We randomly sampled obstacles from a variety of inanimate objects, animals and humans. Our model comparison shows that simple models based on one-dimensional value-of-life scales are suited to describe human ethical behavior in these situations. Furthermore, we examined the influence of severe time pressure on the decision-making process. We found that it decreases consistency in the decision patterns, thus providing an argument for algorithmic decision-making in road traffic. This study demonstrates the suitability of virtual reality for the assessment of ethical behavior in humans, delivering consistent results across subjects, while closely matching the experimental settings to the real world scenarios in question.

Using Virtual Reality to Assess Ethical Decisions in Road Traffic Scenarios: Applicability of Value-of-Life-Based Models and Influences of Time Pressure

PubMed Central

Sütfeld, Leon R.; Gast, Richard; König, Peter; Pipa, Gordon

2017-01-01

Self-driving cars are posing a new challenge to our ethics. By using algorithms to make decisions in situations where harming humans is possible, probable, or even unavoidable, a self-driving car's ethical behavior comes pre-defined. Ad hoc decisions are made in milliseconds, but can be based on extensive research and debates. The same algorithms are also likely to be used in millions of cars at a time, increasing the impact of any inherent biases, and increasing the importance of getting it right. Previous research has shown that moral judgment and behavior are highly context-dependent, and comprehensive and nuanced models of the underlying cognitive processes are out of reach to date. Models of ethics for self-driving cars should thus aim to match human decisions made in the same context. We employed immersive virtual reality to assess ethical behavior in simulated road traffic scenarios, and used the collected data to train and evaluate a range of decision models. In the study, participants controlled a virtual car and had to choose which of two given obstacles they would sacrifice in order to spare the other. We randomly sampled obstacles from a variety of inanimate objects, animals and humans. Our model comparison shows that simple models based on one-dimensional value-of-life scales are suited to describe human ethical behavior in these situations. Furthermore, we examined the influence of severe time pressure on the decision-making process. We found that it decreases consistency in the decision patterns, thus providing an argument for algorithmic decision-making in road traffic. This study demonstrates the suitability of virtual reality for the assessment of ethical behavior in humans, delivering consistent results across subjects, while closely matching the experimental settings to the real world scenarios in question. PMID:28725188

Deep-reasoning fault diagnosis - An aid and a model

NASA Technical Reports Server (NTRS)

Yoon, Wan Chul; Hammer, John M.

1988-01-01

The design and evaluation are presented for the knowledge-based assistance of a human operator who must diagnose a novel fault in a dynamic, physical system. A computer aid based on a qualitative model of the system was built to help the operators overcome some of their cognitive limitations. This aid differs from most expert systems in that it operates at several levels of interaction that are believed to be more suitable for deep reasoning. Four aiding approaches, each of which provided unique information to the operator, were evaluated. The aiding features were designed to help the human's casual reasoning about the system in predicting normal system behavior (N aiding), integrating observations into actual system behavior (O aiding), finding discrepancies between the two (O-N aiding), or finding discrepancies between observed behavior and hypothetical behavior (O-HN aiding). Human diagnostic performance was found to improve by almost a factor of two with O aiding and O-N aiding.

Behavioral Design Teams: The Next Frontier in Clinical Delivery Innovation?

PubMed

Robertson, Ted; Darling, Matthew; Leifer, Jennifer; Footer, Owen; Gordski, Dani

2017-11-01

A deep understanding of human behavior is critical to designing effective health care delivery models, tools, and processes. Currently, however, few mechanisms exist to systematically apply insights about human behavior to improve health outcomes. Behavioral design teams (BDTs) are a successful model for applying behavioral insights within an organization. Already operational within government, this model can be adapted to function in a health care setting. To explore how BDTs could be applied to clinical care delivery and review models for integrating these teams within health care organizations. Interviews with experts in clinical delivery innovation and applied behavioral science, as well as leaders of existing government BDTs. BDTs are most effective when they enjoy top-level executive support, are co-led by a domain expert and behavioral scientist, collaborate closely with key staff and departments, have access to data and IT support, and operate a portfolio of projects. BDTs could be embedded in health care organizations in multiple ways, including in or just below the CEO’s office, within a quality improvement unit, or within an internal innovation center. When running a portfolio, BDTs achieve a greater number and diversity of insights at lower costs. They also become a platform for strategic learning and scaling.

Implicit emotion regulation in adolescent girls: An exploratory investigation of Hidden Markov Modeling and its neural correlates.

PubMed

Steele, James S; Bush, Keith; Stowe, Zachary N; James, George A; Smitherman, Sonet; Kilts, Clint D; Cisler, Josh

2018-01-01

Numerous data demonstrate that distracting emotional stimuli cause behavioral slowing (i.e. emotional conflict) and that behavior dynamically adapts to such distractors. However, the cognitive and neural mechanisms that mediate these behavioral findings are poorly understood. Several theoretical models have been developed that attempt to explain these phenomena, but these models have not been directly tested on human behavior nor compared. A potential tool to overcome this limitation is Hidden Markov Modeling (HMM), which is a computational approach to modeling indirectly observed systems. Here, we administered an emotional Stroop task to a sample of healthy adolescent girls (N = 24) during fMRI and used HMM to implement theoretical behavioral models. We then compared the model fits and tested for neural representations of the hidden states of the most supported model. We found that a modified variant of the model posited by Mathews et al. (1998) was most concordant with observed behavior and that brain activity was related to the model-based hidden states. Particularly, while the valences of the stimuli themselves were encoded primarily in the ventral visual cortex, the model-based detection of threatening targets was associated with increased activity in the bilateral anterior insula, while task effort (i.e. adaptation) was associated with reduction in the activity of these areas. These findings suggest that emotional target detection and adaptation are accomplished partly through increases and decreases, respectively, in the perceived immediate relevance of threatening cues and also demonstrate the efficacy of using HMM to apply theoretical models to human behavior.

Implicit emotion regulation in adolescent girls: An exploratory investigation of Hidden Markov Modeling and its neural correlates

PubMed Central

Bush, Keith; Stowe, Zachary N.; James, George A.; Smitherman, Sonet; Kilts, Clint D.; Cisler, Josh

2018-01-01

Numerous data demonstrate that distracting emotional stimuli cause behavioral slowing (i.e. emotional conflict) and that behavior dynamically adapts to such distractors. However, the cognitive and neural mechanisms that mediate these behavioral findings are poorly understood. Several theoretical models have been developed that attempt to explain these phenomena, but these models have not been directly tested on human behavior nor compared. A potential tool to overcome this limitation is Hidden Markov Modeling (HMM), which is a computational approach to modeling indirectly observed systems. Here, we administered an emotional Stroop task to a sample of healthy adolescent girls (N = 24) during fMRI and used HMM to implement theoretical behavioral models. We then compared the model fits and tested for neural representations of the hidden states of the most supported model. We found that a modified variant of the model posited by Mathews et al. (1998) was most concordant with observed behavior and that brain activity was related to the model-based hidden states. Particularly, while the valences of the stimuli themselves were encoded primarily in the ventral visual cortex, the model-based detection of threatening targets was associated with increased activity in the bilateral anterior insula, while task effort (i.e. adaptation) was associated with reduction in the activity of these areas. These findings suggest that emotional target detection and adaptation are accomplished partly through increases and decreases, respectively, in the perceived immediate relevance of threatening cues and also demonstrate the efficacy of using HMM to apply theoretical models to human behavior. PMID:29489856

Epidemic forecasting is messier than weather forecasting: The role of human behavior and internet data streams in epidemic forecast

DOE PAGES

Moran, Kelly Renee; Fairchild, Geoffrey; Generous, Nicholas; ...

2016-11-14

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection andmore » Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. Here, we conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting.« less

Epidemic forecasting is messier than weather forecasting: The role of human behavior and internet data streams in epidemic forecast

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moran, Kelly Renee; Fairchild, Geoffrey; Generous, Nicholas

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection andmore » Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. Here, we conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting.« less

Epidemic Forecasting is Messier Than Weather Forecasting: The Role of Human Behavior and Internet Data Streams in Epidemic Forecast

PubMed Central

Moran, Kelly R.; Fairchild, Geoffrey; Generous, Nicholas; Hickmann, Kyle; Osthus, Dave; Priedhorsky, Reid; Hyman, James; Del Valle, Sara Y.

2016-01-01

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection and Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. We conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting. PMID:28830111

Validating models of target acquisition performance in the dismounted soldier context

NASA Astrophysics Data System (ADS)

Glaholt, Mackenzie G.; Wong, Rachel K.; Hollands, Justin G.

2018-04-01

The problem of predicting real-world operator performance with digital imaging devices is of great interest within the military and commercial domains. There are several approaches to this problem, including: field trials with imaging devices, laboratory experiments using imagery captured from these devices, and models that predict human performance based on imaging device parameters. The modeling approach is desirable, as both field trials and laboratory experiments are costly and time-consuming. However, the data from these experiments is required for model validation. Here we considered this problem in the context of dismounted soldiering, for which detection and identification of human targets are essential tasks. Human performance data were obtained for two-alternative detection and identification decisions in a laboratory experiment in which photographs of human targets were presented on a computer monitor and the images were digitally magnified to simulate range-to-target. We then compared the predictions of different performance models within the NV-IPM software package: Targeting Task Performance (TTP) metric model and the Johnson model. We also introduced a modification to the TTP metric computation that incorporates an additional correction for target angular size. We examined model predictions using NV-IPM default values for a critical model constant, V50, and we also considered predictions when this value was optimized to fit the behavioral data. When using default values, certain model versions produced a reasonably close fit to the human performance data in the detection task, while for the identification task all models substantially overestimated performance. When using fitted V50 values the models produced improved predictions, though the slopes of the performance functions were still shallow compared to the behavioral data. These findings are discussed in relation to the models' designs and parameters, and the characteristics of the behavioral paradigm.

Television and Human Behavior.

ERIC Educational Resources Information Center

Comstock, George; And Others

To compile a comprehensive review of English language scientific literature regarding the effects of television on human behavior, the authors of this book evaluated more than 2,500 books, articles, reports, and other documents. Rather than taking a traditional approach, the authors followed a new model for the retrieval and synthesis of…

A model of the human supervisor

NASA Technical Reports Server (NTRS)

Kok, J. J.; Vanwijk, R. A.

1977-01-01

A general model of the human supervisor's behavior is given. Submechanisms of the model include: the observer/reconstructor; decision-making; and controller. A set of hypothesis is postulated for the relations between the task variables and the parameters of the different submechanisms of the model. Verification of the model hypotheses is considered using variations in the task variables. An approach is suggested for the identification of the model parameters which makes use of a multidimensional error criterion. Each of the elements of this multidimensional criterion corresponds to a certain aspect of the supervisor's behavior, and is directly related to a particular part of the model and its parameters. This approach offers good possibilities for an efficient parameter adjustment procedure.

Recent advances in animal model experimentation in autism research.

PubMed

Tania, Mousumi; Khan, Md Asaduzzaman; Xia, Kun

2014-10-01

Autism, a lifelong neuro-developmental disorder is a uniquely human condition. Animal models are not the perfect tools for the full understanding of human development and behavior, but they can be an important place to start. This review focused on the recent updates of animal model research in autism. We have reviewed the publications over the last three decades, which are related to animal model study in autism. Animal models are important because they allow researchers to study the underlying neurobiology in a way that is not possible in humans. Improving the availability of better animal models will help the field to increase the development of medicines that can relieve disabling symptoms. Results from the therapeutic approaches are encouraging remarkably, since some behavioral alterations could be reversed even when treatment was performed on adult mice. Finding an animal model system with similar behavioral tendencies as humans is thus vital for understanding the brain mechanisms, supporting social motivation and attention, and the manner in which these mechanisms break down in autism. The ongoing studies should therefore increase the understanding of the biological alterations associated with autism as well as the development of knowledge-based treatments therapy for those struggling with autism. In this review, we have presented recent advances in research based on animal models of autism, raising hope for understanding the disease biology for potential therapeutic intervention to improve the quality of life of autism individuals.

Understanding human dynamics in microblog posting activities

NASA Astrophysics Data System (ADS)

Jiang, Zhihong; Zhang, Yubao; Wang, Hui; Li, Pei

2013-02-01

Human activity patterns are an important issue in behavior dynamics research. Empirical evidence indicates that human activity patterns can be characterized by a heavy-tailed inter-event time distribution. However, most researchers give an understanding by only modeling the power-law feature of the inter-event time distribution, and those overlooked non-power-law features are likely to be nontrivial. In this work, we propose a behavior dynamics model, called the finite memory model, in which humans adaptively change their activity rates based on a finite memory of recent activities, which is driven by inherent individual interest. Theoretical analysis shows a finite memory model can properly explain various heavy-tailed inter-event time distributions, including a regular power law and some non-power-law deviations. To validate the model, we carry out an empirical study based on microblogging activity from thousands of microbloggers in the Celebrity Hall of the Sina microblog. The results show further that the model is reasonably effective. We conclude that finite memory is an effective dynamics element to describe the heavy-tailed human activity pattern.

Mechanisms of social avoidance learning can explain the emergence of adaptive and arbitrary behavioral traditions in humans.

PubMed

Lindström, Björn; Olsson, Andreas

2015-06-01

Many nonhuman animals preferentially copy the actions of others when the environment contains predation risk or other types of danger. In humans, the role of social learning in avoidance of danger is still unknown, despite the fundamental importance of social learning for complex social behaviors. Critically, many social behaviors, such as cooperation and adherence to religious taboos, are maintained by threat of punishment. However, the psychological mechanisms allowing threat of punishment to generate such behaviors, even when actual punishment is rare or absent, are largely unknown. To address this, we used both computer simulations and behavioral experiments. First, we constructed a model where simulated agents interacted under threat of punishment and showed that mechanisms' (a) tendency to copy the actions of others through social learning, together with (b) the rewarding properties of avoiding a threatening punishment, could explain the emergence, maintenance, and transmission of large-scale behavioral traditions, both when punishment is common and when it is rare or nonexistent. To provide empirical support for our model, including the 2 mechanisms, we conducted 4 experiments, showing that humans, if threatened with punishment, are exceptionally prone to copy and transmit the behavior observed in others. Our results show that humans, similar to many nonhuman animals, use social learning if the environment is perceived as dangerous. We provide a novel psychological and computational basis for a range of human behaviors characterized by the threat of punishment, such as the adherence to cultural norms and religious taboos. (c) 2015 APA, all rights reserved).

Human Guidance Behavior Decomposition and Modeling

NASA Astrophysics Data System (ADS)

Feit, Andrew James

Trained humans are capable of high performance, adaptable, and robust first-person dynamic motion guidance behavior. This behavior is exhibited in a wide variety of activities such as driving, piloting aircraft, skiing, biking, and many others. Human performance in such activities far exceeds the current capability of autonomous systems in terms of adaptability to new tasks, real-time motion planning, robustness, and trading safety for performance. The present work investigates the structure of human dynamic motion guidance that enables these performance qualities. This work uses a first-person experimental framework that presents a driving task to the subject, measuring control inputs, vehicle motion, and operator visual gaze movement. The resulting data is decomposed into subspace segment clusters that form primitive elements of action-perception interactive behavior. Subspace clusters are defined by both agent-environment system dynamic constraints and operator control strategies. A key contribution of this work is to define transitions between subspace cluster segments, or subgoals, as points where the set of active constraints, either system or operator defined, changes. This definition provides necessary conditions to determine transition points for a given task-environment scenario that allow a solution trajectory to be planned from known behavior elements. In addition, human gaze behavior during this task contains predictive behavior elements, indicating that the identified control modes are internally modeled. Based on these ideas, a generative, autonomous guidance framework is introduced that efficiently generates optimal dynamic motion behavior in new tasks. The new subgoal planning algorithm is shown to generate solutions to certain tasks more quickly than existing approaches currently used in robotics.

Neurogenetics of Aggressive Behavior – Studies in Rodents

PubMed Central

Takahashi, Aki; Miczek, Klaus A.

2014-01-01

Aggressive behavior is observed in many animal species, such as insects, fish, lizards, frogs, and most mammals including humans. This wide range of conservation underscores the importance of aggressive behavior in the animals’ survival and fitness, and the likely heritability of this behavior. Although typical patterns of aggressive behavior differ between species, there are several concordances in the neurobiology of aggression among rodents, primates, and humans. Studies with rodent models may eventually help us to understand the neurogenetic architecture of aggression in humans. However, it is important to recognize the difference between the ecological and ethological significance of aggressive behavior (species-typical aggression) and maladaptive violence (escalated aggression) when applying the findings of aggression research using animal models to human or veterinary medicine. Well-studied rodent models for aggressive behavior in the laboratory setting include the mouse (Mus musculus), rat (Rattus norvegicus), hamster (Mesocricetus auratus), and prairie vole (Microtus ochrogaster). The neural circuits of rodent aggression have been gradually elucidated by several techniques e.g. immunohistochemistry of immediate-early gene (c-Fos) expression, intracranial drug microinjection, in vivo microdialysis, and optogenetics techniques. Also, evidence accumulated from the analysis of gene-knockout mice shows the involvement of several genes in aggression. Here we review the brain circuits that have been implicated in aggression, such as the hypothalamus, prefrontal cortex (PFC), dorsal raphe nucleus (DRN), nucleus accumbens (NAc), and olfactory system. We then discuss the roles of glutamate and γ-aminobutyric acid (GABA), major inhibitory and excitatory amino acids in the brain, as well as their receptors, in controlling aggressive behavior, focusing mainly on recent findings. At the end of this chapter, we discuss how genes can be identified that underlie individual differences in aggression, using the so-called forward genetics approach. PMID:24318936

Human Behavior: Do Animals Have the Answer

ERIC Educational Resources Information Center

Trotter, Robert J.

1974-01-01

Results of psychological experiments usinganimals are presented. Use of the animal-human analogy to generalize these findings to humans is discussed. Ethological studies are interpreted in light of the total environment and situation involved. The completeness of the ethological model compared to the animal-experimental model is discussed. (LS)

Integrating social science into empirical models of coupled human and natural systems

Treesearch

Jeffrey D. Kline; Eric M. White; A Paige Fischer; Michelle M. Steen-Adams; Susan Charnley; Christine S. Olsen; Thomas A. Spies; John D. Bailey

2017-01-01

Coupled human and natural systems (CHANS) research highlights reciprocal interactions (or feedbacks) between biophysical and socioeconomic variables to explain system dynamics and resilience. Empirical models often are used to test hypotheses and apply theory that represent human behavior. Parameterizing reciprocal interactions presents two challenges for social...

Putting the psychology back into psychological models: mechanistic versus rational approaches.

PubMed

Sakamoto, Yasuaki; Jones, Mattr; Love, Bradley C

2008-09-01

Two basic approaches to explaining the nature of the mind are the rational and the mechanistic approaches. Rational analyses attempt to characterize the environment and the behavioral outcomes that humans seek to optimize, whereas mechanistic models attempt to simulate human behavior using processes and representations analogous to those used by humans. We compared these approaches with regard to their accounts of how humans learn the variability of categories. The mechanistic model departs in subtle ways from rational principles. In particular, the mechanistic model incrementally updates its estimates of category means and variances through error-driven learning, based on discrepancies between new category members and the current representation of each category. The model yields a prediction, which we verify, regarding the effects of order manipulations that the rational approach does not anticipate. Although both rational and mechanistic models can successfully postdict known findings, we suggest that psychological advances are driven primarily by consideration of process and representation and that rational accounts trail these breakthroughs.

Alterations in choice behavior by manipulations of world model

PubMed Central

Green, C. S.; Benson, C.; Kersten, D.; Schrater, P.

2010-01-01

How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) “probability matching”—a consistent example of suboptimal choice behavior seen in humans—occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning. PMID:20805507

Personality from a cognitive-biological perspective

NASA Astrophysics Data System (ADS)

Neuman, Yair

2014-12-01

The term "personality" is used to describe a distinctive and relatively stable set of mental traits that aim to explain the organism's behavior. The concept of personality that emerged in human psychology has been also applied to the study of non-human organisms from birds to horses. In this paper, I critically review the concept of personality from an interdisciplinary perspective, and point to some ideas that may be used for developing a cognitive-biological theory of personality. Integrating theories and research findings from various fields such as cognitive ethnology, clinical psychology, and neuroscience, I argue that the common denominator of various personality theories are neural systems of threat/trust management and their emotional, cognitive, and behavioral dimensions. In this context, personality may be also conceived as a meta-heuristics both human and non-human organisms apply to model and predict the behavior of others. The paper concludes by suggesting a minimal computational model of personality that may guide future research.

Combining Human and Machine Intelligence to Derive Agents' Behavioral Rules for Groundwater Irrigation

NASA Astrophysics Data System (ADS)

Hu, Y.; Quinn, C.; Cai, X.

2015-12-01

One major challenge of agent-based modeling is to derive agents' behavioral rules due to behavioral uncertainty and data scarcity. This study proposes a new approach to combine a data-driven modeling based on the directed information (i.e., machine intelligence) with expert domain knowledge (i.e., human intelligence) to derive the behavioral rules of agents considering behavioral uncertainty. A directed information graph algorithm is applied to identifying the causal relationships between agents' decisions (i.e., groundwater irrigation depth) and time-series of environmental, socio-economical and institutional factors. A case study is conducted for the High Plains aquifer hydrological observatory (HO) area, U.S. Preliminary results show that four factors, corn price (CP), underlying groundwater level (GWL), monthly mean temperature (T) and precipitation (P) have causal influences on agents' decisions on groundwater irrigation depth (GWID) to various extents. Based on the similarity of the directed information graph for each agent, five clusters of graphs are further identified to represent all the agents' behaviors in the study area as shown in Figure 1. Using these five representative graphs, agents' monthly optimal groundwater pumping rates are derived through the probabilistic inference. Such data-driven relationships and probabilistic quantifications are then coupled with a physically-based groundwater model to investigate the interactions between agents' pumping behaviors and the underlying groundwater system in the context of coupled human and natural systems.

Comparing postnatal development of gonadal hormones and associated social behaviors in rats, mice, and humans.

PubMed

Bell, Margaret R

2018-05-14

Postnatal development includes dramatic changes in gonadal hormones and the many social behaviors they help regulate, both in rodents and humans. Parental care-seeking is the most salient social interaction in neonates and infants, play and pro-social behaviors are commonly studied in juveniles, and the development of aggression and sexual behavior begins in peripubertal stages but continues through late adolescence into adulthood. While parental behaviors are shown after reproductive success in adulthood, alloparenting behaviors are actually high in juveniles as well. These behaviors are sensitive to both early life organizational effects of gonadal hormones and later life activational regulation. However, changes in circulating gonadal hormones and the display of the above behaviors over development differs between rats, mice and humans. These endpoints are of interest to endocrinologist, toxicologists, neuroscientists because of their relevance to mental health disorders and their vulnerability to effects of endocrine disrupting chemical exposure. As such, the goal of this minireview is to succinctly describe and relate the postnatal development of gonadal hormones and social behaviors to each other, over time and across animal models. Ideally, this will help identify appropriate animal models and age ranges for continued study of both normative development and in contexts of environmental disruption.

Determinants of choice, and vulnerability and recovery in addiction.

PubMed

Lamb, R J; Maguire, David R; Ginsburg, Brett C; Pinkston, Jonathan W; France, Charles P

2016-06-01

Addiction may be viewed as choice governed by competing contingencies. One factor impacting choice, particularly as it relates to addiction, is sensitivity to delayed rewards. Discounting of delayed rewards influences addiction vulnerability because of competition between relatively immediate gains of drug use, e.g. intoxication, versus relatively remote gains of abstinence, e.g. family stability. Factors modifying delay sensitivity can be modeled in the laboratory. For instance, increased delay sensitivity can be similarly observed in adolescent humans and non-human animals. Similarly, genetic factors influence delay sensitivity in humans and animals. Recovery from addiction may also be viewed as choice behavior. Thus, reinforcing alternative behavior facilitates recovery because reinforcing alternative behavior decreases the frequency of using drugs. How reinforcing alternative behavior influences recovery can also be modeled in the laboratory. For instance, relapse risk decreases as abstinence duration increases, and this decreasing risk can be modeled in animals using choice procedures. In summary, addiction in many respects can be conceptualized as a problem of choice. Animal models of choice disorders stand to increase our understanding of the core processes that establish and maintain addiction and serve as a proving ground for development of novel treatments. Copyright © 2016 Elsevier B.V. All rights reserved.

Determinants of choice, and vulnerability and recovery in addiction

PubMed Central

Lamb, R.J.; Maguire, David R.; Ginsburg, Brett C.; Pinkston, Jonathan W.; France, Charles P.

2016-01-01

Addiction may be viewed as choice governed by competing contingencies. One factor impacting choice, particularly as it relates to addiction, is sensitivity to delayed rewards. Discounting of delayed rewards influences addiction vulnerability because of competition between relatively immediate gains of drug use, e.g. intoxication, versus relatively remote gains of abstinence, e.g. family stability. Factors modifying delay sensitivity can be modeled in the laboratory. For instance, increased delay sensitivity can be similarly observed in adolescent humans and non-human animals. Similarly, genetic factors influence delay sensitivity in humans and animals. Recovery from addiction may also be viewed as choice behavior. Thus, reinforcing alternative behavior facilitates recovery because reinforcing alternative behavior decreases the frequency of using drugs. How reinforcing alternative behavior influences recovery can also be modeled in the laboratory. For instance, relapse risk decreases as abstinence duration increases, and this decreasing risk can be modeled in animals using choice procedures. In summary, addiction in many respects can be conceptualized as a problem of choice. Animal models of choice disorders stand to increase our understanding of the core processes that establish and maintain addiction and serve as a proving ground for development of novel treatments. PMID:27083500

Modeling Humans as Reinforcement Learners: How to Predict Human Behavior in Multi-Stage Games

NASA Technical Reports Server (NTRS)

Lee, Ritchie; Wolpert, David H.; Backhaus, Scott; Bent, Russell; Bono, James; Tracey, Brendan

2011-01-01

This paper introduces a novel framework for modeling interacting humans in a multi-stage game environment by combining concepts from game theory and reinforcement learning. The proposed model has the following desirable characteristics: (1) Bounded rational players, (2) strategic (i.e., players account for one anothers reward functions), and (3) is computationally feasible even on moderately large real-world systems. To do this we extend level-K reasoning to policy space to, for the first time, be able to handle multiple time steps. This allows us to decompose the problem into a series of smaller ones where we can apply standard reinforcement learning algorithms. We investigate these ideas in a cyber-battle scenario over a smart power grid and discuss the relationship between the behavior predicted by our model and what one might expect of real human defenders and attackers.

A psychoanalytic model for human freedom and rationality.

PubMed

Macklin, R

1976-07-01

The nature and scope of freedom and rationality in man are explored in light of the problems posed by a deterministic framework for understanding and explaining human though, feeling, and behavior. It is argued that the sort of explanation afforded by a psychodynamic theory is fully compatible with attributing freedom and rationality to persons. In particular, psychoanalytic theory is able to account for the existence of causal laws governing all aspects of human behavior, while providing a schema by which we can distinguish rational from irrational behavior, and free acts from those that are unfree.

Predicting Networked Strategic Behavior via Machine Learning and Game Theory

DTIC Science & Technology

2015-01-13

The funding for this project was used to develop basic models, methodology and algorithms for the application of machine learning and related tools to settings in which strategic behavior is central. Among the topics studied was the development of simple behavioral models explaining and predicting human subject behavior in networked strategic experiments from prior work. These included experiments in biased voting and networked trading, among others.

Evaluation of the Interactionist Model of Socioeconomic Status and Problem Behavior: A Developmental Cascade across Generations

PubMed Central

Martin, Monica J.; Conger, Rand D.; Schofield, Thomas J.; Dogan, Shannon J.; Widaman, Keith F.; Donnellan, M. Brent; Neppl, Tricia K.

2010-01-01

The current multigenerational study evaluates the utility of the Interactionist Model of Socioeconomic Influence on human development (IMSI) in explaining problem behaviors across generations. The IMSI proposes that the association between socioeconomic status (SES) and human development involves a dynamic interplay that includes both social causation (SES influences human development) and social selection (individual characteristics affect SES). As part of the developmental cascade proposed by the IMSI, the findings from this investigation showed that G1 adolescent problem behavior predicted later G1 SES, family stress, and parental emotional investments, as well as the next generation of children's problem behavior. These results are consistent with a social selection view. Consistent with the social causation perspective, we found a significant relation between G1 SES and family stress, and in turn, family stress predicted G2 problem behavior. Finally, G1 adult SES predicted both material and emotional investments in the G2 child. In turn, emotional investments predicted G2 problem behavior, as did material investments. Some of the predicted pathways varied by G1 parent gender. The results are consistent with the view that processes of both social selection and social causation account for the association between SES and human development. PMID:20576188

Modeling the Impact of Motivation, Personality, and Emotion on Social Behavior

NASA Astrophysics Data System (ADS)

Miller, Lynn C.; Read, Stephen J.; Zachary, Wayne; Rosoff, Andrew

Models seeking to predict human social behavior must contend with multiple sources of individual and group variability that underlie social behavior. One set of interrelated factors that strongly contribute to that variability - motivations, personality, and emotions - has been only minimally incorporated in previous computational models of social behavior. The Personality, Affect, Culture (PAC) framework is a theory-based computational model that addresses this gap. PAC is used to simulate social agents whose social behavior varies according to their personalities and emotions, which, in turn, vary according to their motivations and underlying motive control parameters. Examples involving disease spread and counter-insurgency operations show how PAC can be used to study behavioral variability in different social contexts.

Suicide among animals: a review of evidence.

PubMed

Preti, Antonio

2007-12-01

Naturalists have not identified suicide in nonhuman species in field situations, despite intensive study of thousands of animal species. In this review, evidence on suicidal behavior among animals is analyzed to discover analogies with human suicidal behavior. Literature was retrieved by exploring Medline/PubMed and PsychINFO databases (1967-2007) and through manual literature searches. Keyword terms were "suicide or suicidal behavior" and "animal or animal behavior." Few empirical investigations have been carried out on this topic. Nevertheless, sparse evidence supports some resemblance between the self-endangering behavior observed in the animal kingdom, particularly in animals held in captivity or put under pressure by environmental challenges, and suicidal behavior among humans. Animal models have contributed to the study of both normal and pathological human behaviors: discovering some correlates of suicide among animals could be a valid contribution to the field.

Applying Social Psychological Models to Predicting HIV-Related Sexual Risk Behaviors Among African Americans

PubMed Central

Cochran, Susan D.; Mays, Vickie M.

2011-01-01

Existing models of attitude-behavior relationships, including the Health Belief Model, the Theory of Reasoned Action, and the Self-Efficacy Theory, are increasingly being used by psychologists to predict human immunodeficiency virus (HIV)-related risk behaviors. The authors briefly highlight some of the difficulties that might arise in applying these models to predicting the risk behaviors of African Americans. These social psychological models tend to emphasize the importance of individualistic, direct control of behavioral choices and deemphasize factors, such as racism and poverty, particularly relevant to that segment of the African American population most at risk for HIV infection. Applications of these models without taking into account the unique issues associated with behavioral choices within the African American community may fail to capture the relevant determinants of risk behaviors. PMID:23529205

3D abnormal behavior recognition in power generation

NASA Astrophysics Data System (ADS)

Wei, Zhenhua; Li, Xuesen; Su, Jie; Lin, Jie

2011-06-01

So far most research of human behavior recognition focus on simple individual behavior, such as wave, crouch, jump and bend. This paper will focus on abnormal behavior with objects carrying in power generation. Such as using mobile communication device in main control room, taking helmet off during working and lying down in high place. Taking account of the color and shape are fixed, we adopted edge detecting by color tracking to recognize object in worker. This paper introduces a method, which using geometric character of skeleton and its angle to express sequence of three-dimensional human behavior data. Then adopting Semi-join critical step Hidden Markov Model, weighing probability of critical steps' output to reduce the computational complexity. Training model for every behavior, mean while select some skeleton frames from 3D behavior sample to form a critical step set. This set is a bridge linking 2D observation behavior with 3D human joints feature. The 3D reconstruction is not required during the 2D behavior recognition phase. In the beginning of recognition progress, finding the best match for every frame of 2D observed sample in 3D skeleton set. After that, 2D observed skeleton frames sample will be identified as a specifically 3D behavior by behavior-classifier. The effectiveness of the proposed algorithm is demonstrated with experiments in similar power generation environment.

Animal models of speech and vocal communication deficits associated with psychiatric disorders

PubMed Central

Konopka, Genevieve; Roberts, Todd F.

2015-01-01

Disruptions in speech, language and vocal communication are hallmarks of several neuropsychiatric disorders, most notably autism spectrum disorders. Historically, the use of animal models to dissect molecular pathways and connect them to behavioral endophenotypes in cognitive disorders has proven to be an effective approach for developing and testing disease-relevant therapeutics. The unique aspects of human language when compared to vocal behaviors in other animals make such an approach potentially more challenging. However, the study of vocal learning in species with analogous brain circuits to humans may provide entry points for understanding this human-specific phenotype and diseases. Here, we review animal models of vocal learning and vocal communication, and specifically link phenotypes of psychiatric disorders to relevant model systems. Evolutionary constraints in the organization of neural circuits and synaptic plasticity result in similarities in the brain mechanisms for vocal learning and vocal communication. Comparative approaches and careful consideration of the behavioral limitations among different animal models can provide critical avenues for dissecting the molecular pathways underlying cognitive disorders that disrupt speech, language and vocal communication. PMID:26232298

A computational model of the human visual cortex

NASA Astrophysics Data System (ADS)

Albus, James S.

2008-04-01

The brain is first and foremost a control system that is capable of building an internal representation of the external world, and using this representation to make decisions, set goals and priorities, formulate plans, and control behavior with intent to achieve its goals. The computational model proposed here assumes that this internal representation resides in arrays of cortical columns. More specifically, it models each cortical hypercolumn together with its underlying thalamic nuclei as a Fundamental Computational Unit (FCU) consisting of a frame-like data structure (containing attributes and pointers) plus the computational processes and mechanisms required to maintain it. In sensory-processing areas of the brain, FCUs enable segmentation, grouping, and classification. Pointers stored in FCU frames link pixels and signals to objects and events in situations and episodes that are overlaid with meaning and emotional values. In behavior-generating areas of the brain, FCUs make decisions, set goals and priorities, generate plans, and control behavior. Pointers are used to define rules, grammars, procedures, plans, and behaviors. It is suggested that it may be possible to reverse engineer the human brain at the FCU level of fidelity using nextgeneration massively parallel computer hardware and software. Key Words: computational modeling, human cortex, brain modeling, reverse engineering the brain, image processing, perception, segmentation, knowledge representation

Following Human Footsteps: Proposal of a Decision Theory Based on Human Behavior

NASA Technical Reports Server (NTRS)

Mahmud, Faisal

2011-01-01

Human behavior is a complex nature which depends on circumstances and decisions varying from time to time as well as place to place. The way a decision is made either directly or indirectly related to the availability of the options. These options though appear at random nature, have a solid directional way for decision making. In this paper, a decision theory is proposed which is based on human behavior. The theory is structured with model sets that will show the all possible combinations for making a decision, A virtual and simulated environment is considered to show the results of the proposed decision theory

A coupled human-water system from a systems dynamics perspective

NASA Astrophysics Data System (ADS)

Kuil, Linda; Blöschl, Günter; Carr, Gemma

2013-04-01

Traditionally, models used in hydrological studies have frequently assumed stationarity. Moreover, human-induced water resources management activities are often included as external forcings in water cycle dynamics. However, considering humans' current impact on the water cycle in terms of a growing population, river basins increasingly being managed and a climate considerably changing, it has recently been questioned whether this is still correct. Furthermore, research directed at the evolution of water resources and society has shown that the components constituting the human-water system are changing interdependently. Goal of this study is therefore to approach water cycle dynamics from an integrated perspective in which humans are considered as endogenous forces to the system. The method used to model a coupled, urban human-water system is system dynamics. In system dynamics, particular emphasis is placed on feedback loops resulting in dynamic behavior. Time delays and non-linearity can relatively easily be included, making the method appropriate for studying complex systems that change over time. The approach of this study is as follows. First, a conceptual model is created incorporating the key components of the urban human-water system. Subsequently, only those components are selected that are both relevant and show causal loop behavior. Lastly, the causal narratives are translated into mathematical relationships. The outcome will be a simple model that shows only those characteristics with which we are able to explore the two-way coupling between the societal behavior and the water system we depend on.

An Empirical Human Controller Model for Preview Tracking Tasks.

PubMed

van der El, Kasper; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus Rene M; Mulder, Max

2016-11-01

Real-life tracking tasks often show preview information to the human controller about the future track to follow. The effect of preview on manual control behavior is still relatively unknown. This paper proposes a generic operator model for preview tracking, empirically derived from experimental measurements. Conditions included pursuit tracking, i.e., without preview information, and tracking with 1 s of preview. Controlled element dynamics varied between gain, single integrator, and double integrator. The model is derived in the frequency domain, after application of a black-box system identification method based on Fourier coefficients. Parameter estimates are obtained to assess the validity of the model in both the time domain and frequency domain. Measured behavior in all evaluated conditions can be captured with the commonly used quasi-linear operator model for compensatory tracking, extended with two viewpoints of the previewed target. The derived model provides new insights into how human operators use preview information in tracking tasks.

Effects of human recreation on the incubation behavior of American Oystercatchers

USGS Publications Warehouse

McGowan, C.P.; Simons, T.R.

2006-01-01

Human recreational disturbance and its effects on wildlife demographics and behavior is an increasingly important area of research. We monitored the nesting success of American Oystercatchers (Haematopus palliatus) in coastal North Carolina in 2002 and 2003. We also used video monitoring at nests to measure the response of incubating birds to human recreation. We counted the number of trips per hour made by adult birds to and from the nest, and we calculated the percent time that adults spent incubating. We asked whether human recreational activities (truck, all-terrain vehicle [ATV], and pedestrian traffic) were correlated with parental behavioral patterns. Eleven a priori models of nest survival and behavioral covariates were evaluated using Akaike's Information Criterion (AIC) to see whether incubation behavior influenced nest survival. Factors associated with birds leaving their nests (n = 548) included ATV traffic (25%), truck traffic (17%), pedestrian traffic (4%), aggression with neighboring oystercatchers or paired birds exchanging incubation duties (26%), airplane traffic (1%) and unknown factors (29%). ATV traffic was positively associated with the rate of trips to and away from the nest (??1 = 0.749, P < 0.001) and negatively correlated with percent time spent incubating (??1 = -0.037, P = 0.025). Other forms of human recreation apparently had little effect on incubation behaviors. Nest survival models incorporating the frequency of trips by adults to and from the nest, and the percentage of time adults spent incubating, were somewhat supported in the AIC analyses. A low frequency of trips to and from the nest and, counter to expectations, low percent time spent incubating were associated with higher daily nest survival rates. These data suggest that changes in incubation behavior might be one mechanism by which human recreation affects the reproductive success of American Oystercatchers.

A Pilot Model for the NASA Simplified Aid for EVA Rescue (SAFER) (Single-Axis Pitch Task)

NASA Astrophysics Data System (ADS)

Handley, Patrick Mark

This thesis defines, tests, and validates a descriptive pilot model for a single-axis pitch control task of the Simplified Aid for EVA Rescue (SAFER). SAFER is a small propulsive jetpack used by astronauts for self-rescue. Pilot model research supports development of improved self-rescue strategies and technologies through insights into pilot behavior.This thesis defines a multi-loop pilot model. The innermost loop controls the hand controller, the middle loop controls pitch rate, and the outer loop controls pitch angle. A human-in-the-loop simulation was conducted to gather data from a human pilot. Quantitative and qualitative metrics both indicate that the model is an acceptable fit to the human data. Fuel consumption was nearly identical; time to task completion matched very well. There is some evidence that the model responds faster to initial pitch rates than the human, artificially decreasing the model's time to task completion. This pilot model is descriptive, not predictive, of the human pilot. Insights are made into pilot behavior from this research. Symmetry implies that the human responds to positive and negative initial conditions with the same strategy. The human pilot appears indifferent to pitch angles within 0.5 deg, coasts at a constant pitch rate 1.09 deg/s, and has a reaction delay of 0.1 s.

Effects of HIV-1 on Cognition in Humanized NSG Mice

NASA Astrophysics Data System (ADS)

Akhter, Sidra Pervez

Host species specificity of human immunodeficiency virus (HIV) creates a challenge to study the pathology, diagnostic tools, and therapeutic agents. The closely related simian immunodeficiency virus and studies of neurocognitive impairments on transgenic animals expressing partial viral genome have significant limitations. The humanized mice model provides a small animal system in which a human immune system can be engrafted and immunopathobiology of HIV-1 infection can be studied. However, features of HIV-associated neurocognitive disorders (HAND) were not evaluated in this model. Open field activity test was selected to characterize behavior of original strain NOD/scid-IL-2Rgammac null (NSG) mice, effects of engraftment of human CD34+ hematopoietic stem cells (HSCs) and functional human immune system (huNSG), and finally, investigate the behavior changes induced by chronic HIV-1 infection. Long-term infected HuNSG mice showed the loss of working memory and increased anxiety in the open field. Additionally, these animals were utilized for evaluation of central nervous system metabolic and structural changes. Detected behavioral abnormalities are correlated with obtained neuroimaging and histological abnormalities published.

Assessing Autism-like Behavior in Mice: Variations in Social Interactions Among Inbred Strains.

PubMed Central

Bolivar, Valerie J.; Walters, Samantha R.; Phoenix, Jennifer L.

2007-01-01

Autism is a pervasive developmental disorder, with characteristics including impairments in reciprocal social interaction, impaired communication, and repetitive/stereotyped behaviors. Despite decades of research, the etiology of autism remains elusive. Thus, it is important that we pursue all avenues, in attempting to understand this complicated disorder. One such avenue is the development of animal models. While autism may be uniquely human, there are behavioral characteristics of the disorder that can be established in animal models. Evidence supports a genetic component for this disorder, and over the past few decades the mouse has been a highly valuable tool for the elucidation of pathways involved in many human disorders (e.g., Huntington’s disease). As a first step toward establishing a mouse model of autism, we studied same-sex social behavior in a number of inbred mouse strains. In Study 1, we examined intra-strain social behavior of male pairs after one mouse had 15 minutes prior exposure to the testing chamber. In Study 2, we evaluated intra-strain and inter-strain social behavior when both mice were naive to the testing chamber. The amount and type of social behavior seen differed between these studies, but overall there were general inbred strain differences in social behavior. Some strains were highly social (e.g., FVB/NJ, while others displayed low levels of social behavior (e.g., A/J, BTBR T+ tf/J). These strains may be useful in future genetic studies to determine specific genes involved in mouse social behavior, the findings of which should in turn help us to determine some of the genes involved in human social behavior and its disorders (e.g., autism). PMID:17097158

Validity Assessment of 5 Day Repeated Forced-Swim Stress to Model Human Depression in Young-Adult C57BL/6J and BALB/cJ Mice

PubMed Central

Zheng, Jia; Goodyear, Laurie J.

2016-01-01

The development of animal models with construct, face, and predictive validity to accurately model human depression has been a major challenge. One proposed rodent model is the 5 d repeated forced swim stress (5d-RFSS) paradigm, which progressively increases floating during individual swim sessions. The onset and persistence of this floating behavior has been anthropomorphically characterized as a measure of depression. This interpretation has been under debate because a progressive increase in floating over time may reflect an adaptive learned behavioral response promoting survival, and not depression (Molendijk and de Kloet, 2015). To assess construct and face validity, we applied 5d-RFSS to C57BL/6J and BALB/cJ mice, two mouse strains commonly used in neuropsychiatric research, and measured a combination of emotional, homeostatic, and psychomotor symptoms indicative of a depressive-like state. We also compared the efficacy of 5d-RFSS and chronic social defeat stress (CSDS), a validated depression model, to induce a depressive-like state in C57BL/6J mice. In both strains, 5d-RFSS progressively increased floating behavior that persisted for at least 4 weeks. 5d-RFSS did not alter sucrose preference, body weight, appetite, locomotor activity, anxiety-like behavior, or immobility behavior during a tail-suspension test compared with nonstressed controls. In contrast, CSDS altered several of these parameters, suggesting a depressive-like state. Finally, predictive validity was assessed using voluntary wheel running (VWR), a known antidepressant intervention. Four weeks of VWR after 5d-RFSS normalized floating behavior toward nonstressed levels. These observations suggest that 5d-RFSS has no construct or face validity but might have predictive validity to model human depression. PMID:28058270

Validity Assessment of 5 Day Repeated Forced-Swim Stress to Model Human Depression in Young-Adult C57BL/6J and BALB/cJ Mice.

PubMed

Mul, Joram D; Zheng, Jia; Goodyear, Laurie J

2016-01-01

The development of animal models with construct, face, and predictive validity to accurately model human depression has been a major challenge. One proposed rodent model is the 5 d repeated forced swim stress (5d-RFSS) paradigm, which progressively increases floating during individual swim sessions. The onset and persistence of this floating behavior has been anthropomorphically characterized as a measure of depression. This interpretation has been under debate because a progressive increase in floating over time may reflect an adaptive learned behavioral response promoting survival, and not depression (Molendijk and de Kloet, 2015). To assess construct and face validity, we applied 5d-RFSS to C57BL/6J and BALB/cJ mice, two mouse strains commonly used in neuropsychiatric research, and measured a combination of emotional, homeostatic, and psychomotor symptoms indicative of a depressive-like state. We also compared the efficacy of 5d-RFSS and chronic social defeat stress (CSDS), a validated depression model, to induce a depressive-like state in C57BL/6J mice. In both strains, 5d-RFSS progressively increased floating behavior that persisted for at least 4 weeks. 5d-RFSS did not alter sucrose preference, body weight, appetite, locomotor activity, anxiety-like behavior, or immobility behavior during a tail-suspension test compared with nonstressed controls. In contrast, CSDS altered several of these parameters, suggesting a depressive-like state. Finally, predictive validity was assessed using voluntary wheel running (VWR), a known antidepressant intervention. Four weeks of VWR after 5d-RFSS normalized floating behavior toward nonstressed levels. These observations suggest that 5d-RFSS has no construct or face validity but might have predictive validity to model human depression.

Using APEX to Model Anticipated Human Error: Analysis of a GPS Navigational Aid

NASA Technical Reports Server (NTRS)

VanSelst, Mark; Freed, Michael; Shefto, Michael (Technical Monitor)

1997-01-01

The interface development process can be dramatically improved by predicting design facilitated human error at an early stage in the design process. The approach we advocate is to SIMULATE the behavior of a human agent carrying out tasks with a well-specified user interface, ANALYZE the simulation for instances of human error, and then REFINE the interface or protocol to minimize predicted error. This approach, incorporated into the APEX modeling architecture, differs from past approaches to human simulation in Its emphasis on error rather than e.g. learning rate or speed of response. The APEX model consists of two major components: (1) a powerful action selection component capable of simulating behavior in complex, multiple-task environments; and (2) a resource architecture which constrains cognitive, perceptual, and motor capabilities to within empirically demonstrated limits. The model mimics human errors arising from interactions between limited human resources and elements of the computer interface whose design falls to anticipate those limits. We analyze the design of a hand-held Global Positioning System (GPS) device used for radical and navigational decisions in small yacht recalls. The analysis demonstrates how human system modeling can be an effective design aid, helping to accelerate the process of refining a product (or procedure).

Effects of HIV and Methamphetamine on Brain and Behavior: Evidence from Human Studies and Animal Models

PubMed Central

Soontornniyomkij, Virawudh; Kesby, James P.; Morgan, Erin E.; Bischoff-Grethe, Amanda; Minassian, Arpi; Brown, Gregory G.; Grant, Igor

2016-01-01

Methamphetamine (Meth) use is frequent among HIV-infected persons. Combined HIV and Meth insults may exacerbate neural injury in vulnerable neuroanatomic structures or circuitries in the brain, leading to increased behavioral disturbance and cognitive impairment. While acute and chronic effects of Meth in humans and animal models have been studied for decades, the neurobehavioral effects of Meth in the context of HIV infection are much less explored. In-depth understanding of the scope of neurobehavioral phenotypes and mechanisms in HIV/Meth intersection is needed. The present report summarizes published research findings, as well as unpublished data, in humans and animal models with regard to neurobehavioral disturbance, neuroimaging, and neuropathology, and in vitro experimental systems, with an emphasis on findings emerging from the National Institute on Drug Abuse (NIDA) funded Translational Methamphetamine AIDS Research Center (TMARC). Results from human studies and animal (primarily HIV-1 gp120 transgenic mouse) models thus far suggest that combined HIV and Meth insults increase the likelihood of neural injury in the brain. The neurobehavioral effects include cognitive impairment and increased tendencies toward impaired behavioral inhibition and social cognition. These impairments are relevant to behaviors that affect personal and social risks, e.g. worse medication adherence, riskier behaviors, and greater likelihood of HIV transmission. The underlying mechanisms may include electrochemical changes in neuronal circuitries, injury to white matter microstructures, synaptodendritic damage, and selective neuronal loss. Utilization of research methodologies that are valid across species is instrumental in generating new knowledge with clinical translational value. PMID:27484318

Effects of HIV and Methamphetamine on Brain and Behavior: Evidence from Human Studies and Animal Models.

PubMed

Soontornniyomkij, Virawudh; Kesby, James P; Morgan, Erin E; Bischoff-Grethe, Amanda; Minassian, Arpi; Brown, Gregory G; Grant, Igor

2016-09-01

Methamphetamine (Meth) use is frequent among HIV-infected persons. Combined HIV and Meth insults may exacerbate neural injury in vulnerable neuroanatomic structures or circuitries in the brain, leading to increased behavioral disturbance and cognitive impairment. While acute and chronic effects of Meth in humans and animal models have been studied for decades, the neurobehavioral effects of Meth in the context of HIV infection are much less explored. In-depth understanding of the scope of neurobehavioral phenotypes and mechanisms in HIV/Meth intersection is needed. The present report summarizes published research findings, as well as unpublished data, in humans and animal models with regard to neurobehavioral disturbance, neuroimaging, and neuropathology, and in vitro experimental systems, with an emphasis on findings emerging from the National Institute on Drug Abuse (NIDA) funded Translational Methamphetamine AIDS Research Center (TMARC). Results from human studies and animal (primarily HIV-1 gp120 transgenic mouse) models thus far suggest that combined HIV and Meth insults increase the likelihood of neural injury in the brain. The neurobehavioral effects include cognitive impairment and increased tendencies toward impaired behavioral inhibition and social cognition. These impairments are relevant to behaviors that affect personal and social risks, e.g. worse medication adherence, riskier behaviors, and greater likelihood of HIV transmission. The underlying mechanisms may include electrochemical changes in neuronal circuitries, injury to white matter microstructures, synaptodendritic damage, and selective neuronal loss. Utilization of research methodologies that are valid across species is instrumental in generating new knowledge with clinical translational value.

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users.

PubMed

Veksler, Vladislav D; Buchler, Norbou; Hoffman, Blaine E; Cassenti, Daniel N; Sample, Char; Sugrim, Shridat

2018-01-01

Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting.

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior

PubMed Central

Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-01-01

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information. PMID:29513219

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior.

PubMed

Groen, Iris Ia; Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-03-07

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information.

Genetic disruption of ankyrin-G in adult mouse forebrain causes cortical synapse alteration and behavior reminiscent of bipolar disorder.

PubMed

Zhu, Shanshan; Cordner, Zachary A; Xiong, Jiali; Chiu, Chi-Tso; Artola, Arabiye; Zuo, Yanning; Nelson, Andrew D; Kim, Tae-Yeon; Zaika, Natalya; Woolums, Brian M; Hess, Evan J; Wang, Xiaofang; Chuang, De-Maw; Pletnikov, Mikhail M; Jenkins, Paul M; Tamashiro, Kellie L; Ross, Christopher A

2017-09-26

Genome-wide association studies have implicated the ANK3 locus in bipolar disorder, a major human psychotic illness. ANK3 encodes ankyrin-G, which organizes the neuronal axon initial segment (AIS). We generated a mouse model with conditional disruption of ANK3 in pyramidal neurons of the adult forebrain (Ank-G cKO). This resulted in the expected loss of pyramidal neuron AIS voltage-gated sodium and potassium channels. There was also dramatic loss of markers of afferent GABAergic cartridge synapses, resembling the cortical microcircuitry changes in brains from psychotic patients, and suggesting disinhibition. Expression of c-fos was increased in cortical pyramidal neurons, consistent with increased neuronal activity due to disinhibition. The mice showed robust behavioral phenotypes reminiscent of aspects of human mania, ameliorated by antimania drugs lithium and valproate. Repeated social defeat stress resulted in repeated episodes of dramatic behavioral changes from hyperactivity to "depression-like" behavior, suggestive of some aspects of human bipolar disorder. Overall, we suggest that this Ank-G cKO mouse model recapitulates some of the core features of human bipolar disorder and indicates that cortical microcircuitry alterations during adulthood may be involved in pathogenesis. The model may be useful for studying disease pathophysiology and for developing experimental therapeutics.

A quantitative measure of the electrical activity of human rod photoreceptors using electroretinography.

PubMed

Hood, D C; Birch, D G

1990-10-01

An electrical potential recorded from the cornea, the a-wave of the ERG, is evaluated as a measure of human photoreceptor activity by comparing its behavior to a model derived from in vitro recordings from rod photoreceptors. The leading edge of the ERG exhibits both the linear and nonlinear behavior predicted by this model. The capability for recording the electrical activity of human photoreceptors in vivo opens new avenues for assessing normal and abnormal receptor activity in humans. Furthermore, the quantitative model of the receptor response can be used to isolate the inner retinal contribution, Granit's PII, to the gross ERG. Based on this analysis, the practice of using the trough-to-peak amplitude of the b-wave as a proxy for the amplitude of the inner nuclear layer activity is evaluated.

Conceptual models of information processing

NASA Technical Reports Server (NTRS)

Stewart, L. J.

1983-01-01

The conceptual information processing issues are examined. Human information processing is defined as an active cognitive process that is analogous to a system. It is the flow and transformation of information within a human. The human is viewed as an active information seeker who is constantly receiving, processing, and acting upon the surrounding environmental stimuli. Human information processing models are conceptual representations of cognitive behaviors. Models of information processing are useful in representing the different theoretical positions and in attempting to define the limits and capabilities of human memory. It is concluded that an understanding of conceptual human information processing models and their applications to systems design leads to a better human factors approach.

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning.

PubMed

Chung, Michael Jae-Yoon; Friesen, Abram L; Fox, Dieter; Meltzoff, Andrew N; Rao, Rajesh P N

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning

PubMed Central

Chung, Michael Jae-Yoon; Friesen, Abram L.; Fox, Dieter; Meltzoff, Andrew N.; Rao, Rajesh P. N.

2015-01-01

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration. PMID:26536366

Enhancing the Behaviorial Fidelity of Synthetic Entities with Human Behavior Models

DTIC Science & Technology

2004-05-05

reflecting the soldier’s extensive training. A civilian’s behavior in the same situation will be determined more by emotions , such as fear, and goals...of intelligent behavior , from path-planning to emotional effects, data on the environment must be gathered from the simulation to serve as sensor...model of decision-making based on emotional utility. AI.Implant takes a composite behavior -based approach to individual and crowd navigation

Homeostasis lighting control based on relationship between lighting environment and human behavior

NASA Astrophysics Data System (ADS)

Ueda, Risa; Mita, Akira

2015-03-01

Although each person has own preferences, living spaces which can respond to various preferences and needs have not become reality. Focusing on the lighting environments which influence on the impression of living spaces, this research aims to offer comfortable lighting environments for each resident by a flexible control. This research examines the relationship between lighting environments and human behaviors considering colored lights. In accord with the relationship, this research proposes an illuminance-color control system which flexibly changes spatial environments responding to human conditions. Firstly, the psychological evaluation was conducted in order to build human models for various environments. As a result, preferred lighting environments for each examinee were determined for particular behaviors. Moreover, satisfaction levels of lighting environments were calculated by using seven types of impression of the environments as parameters. The results were summarized as human models. Secondly, this research proposed "Homeostasis Lighting Control System", which employs the human models. Homeostasis lighting control system embodies the algorithm of homeostasis, which is one of the functions of the physiological adaptation. Human discomfort feelings are obtained automatically by the sensor agent robot. The system can offer comfortable lighting environments without controlling environments by residents autonomously based on the information from the robot. This research takes into accounts both illuminance and color. The robot communicates with the server which contains human models, then the system corresponds to individuals. Combining these three systems, the proposed system can effectively control the lighting environment. At last, the feasibility of the proposed system was verified by simulation experiments.

Oxytocin in animal models of autism spectrum disorder.

PubMed

Peñagarikano, Olga

2017-02-01

Autism spectrum disorder is a behavioral disorder characterized by impairments in social interaction and communication together with the presence of stereotyped behaviors and restricted interests. Although highly genetic, its etiology is complex which correlates with the extensive heterogeneity found in its clinical manifestation, adding to the challenge of understanding its pathophysiology and develop targeted pharmacotherapies. The neuropeptide oxytocin is part of a highly conserved system involved in the regulation of social behavior, and both animal and human research have shown that variation in the oxytocin system accounts for interindividual differences in the expression of social behaviors in mammals. In autism, recent studies in human patients and animal models are starting to reveal that alterations in the oxytocin system are more common than previously anticipated. Genetic variation in the key players involved in the system (i.e., oxytocin receptor, oxytocin, and CD38) has been found associated with autism in humans, and animal models of the disorder converge in an altered oxytocin system and/or dysfunction in oxytocin related biological processes. Furthermore, oxytocin administration exerts a behavioral and neurobiological response, and thus, the oxytocin system has become a promising potential therapeutical target for autism. Animal models represent a valuable tool to aid in the research into the potential therapeutic use of oxytocin. In this review, I aim to discuss the main findings related to oxytocin research in autism with a focus on findings in animal models. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 202-213, 2017. © 2016 Wiley Periodicals, Inc.

Intelligence: Real or artificial?

PubMed Central

Schlinger, Henry D.

1992-01-01

Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally referred to behavior-environment relations and not to inferred internal structures and processes. It is concluded that if workers in artificial intelligence are to succeed in their general goal, then they must design machines that are adaptive, that is, that can learn. Thus, artificial intelligence researchers must discard their essentialist model of natural intelligence and adopt a selectionist model instead. Such a strategic change should lead them to the science of behavior analysis. PMID:22477051

Modelling the human operator of slowly responding systems using linear models

NASA Technical Reports Server (NTRS)

Veldhuyzen, W.

1977-01-01

Control of slowly responding systems, such as, helmsman steering a large ship, is examined. It is shown that the describing function techniques are useful in analyzing the control behavior of the helmsman. Models are developed to describe the helmsman's control behavior. It is shown that the cross over model is applicable to the analysis of control of slowly responding systems.

Time of day and eating behaviors are associated with the composition and function of the human gastrointestinal microbiota.

PubMed

Kaczmarek, Jennifer L; Musaad, Salma Ma; Holscher, Hannah D

2017-11-01

Background: Preclinical research has shown that the gastrointestinal microbiota exhibits circadian rhythms and that the timing of food consumption can affect the composition and function of gut microbes. However, there is a dearth of knowledge on these relations in humans. Objective: We aimed to determine whether human gastrointestinal microbes and bacterial metabolites were associated with time of day or behavioral factors, including eating frequency, percentage of energy consumed early in the day, and overnight-fast duration. Design: We analyzed 77 fecal samples collected from 28 healthy men and women. Fecal DNA was extracted and sequenced to determine the relative abundances of bacterial operational taxonomic units (OTUs). Gas chromatography-mass spectroscopy was used to assess short-chain fatty acid concentrations. Eating frequency, percentage of energy consumed before 1400, and overnight-fast duration were determined from dietary records. Data were analyzed by linear mixed models or generalized linear mixed models, which controlled for fiber intake, sex, age, body mass index, and repeated sampling within each participant. Each OTU and metabolite were tested as the outcome in a separate model. Results: Acetate, propionate, and butyrate concentrations decreased throughout the day ( P = 0.006, 0.04, and 0.002, respectively). Thirty-five percent of bacterial OTUs were associated with time. In addition, relations were observed between gut microbes and eating behaviors, including eating frequency, early energy consumption, and overnight-fast duration. Conclusions: These results indicate that the human gastrointestinal microbiota composition and function vary throughout the day, which may be related to the circadian biology of the human body, the microbial community itself, or human eating behaviors. Behavioral factors, including timing of eating and overnight-fast duration, were also predictive of bacterial abundances. Longitudinal intervention studies are needed to determine causality of these biological and behavioral relations. This trial was registered at clinicaltrials.gov as NCT01925560. © 2017 American Society for Nutrition.

Assessing the agricultural costs of climate change: Combining results from crop and economic models

NASA Astrophysics Data System (ADS)

Howitt, R. E.

2016-12-01

Any perturbation to a resource system used by humans elicits both technical and behavioral changes. For agricultural production, economic criteria and their associated models are usually good predictors of human behavior in agricultural production. Estimation of the agricultural costs of climate change requires careful downscaling of global climate models to the level of agricultural regions. Plant growth models for the dominant crops are required to accurately show the full range of trade-offs and adaptation mechanisms needed to minimize the cost of climate change. Faced with the shifts in the fundamental resource base of agriculture, human behavior can either exacerbate or offset the impact of climate change on agriculture. In addition, agriculture can be an important source of increased carbon sequestration. However the effectiveness and timing of this sequestration depends on agricultural practices and farmer behavior. Plant growth models and economic models have been shown to interact in two broad fashions. First there is the direct embedding of a parametric representation plant growth simulations in the economic model production function. A second and more general approach is to have plant growth and crop process models interact with economic models as they are simulated. The development of more general wrapper programs that transfer information between models rapidly and efficiently will encourage this approach. However, this method does introduce complications in terms of matching up disparate scales both in time and space between models. Another characteristic behavioral response of agricultural production is the distinction between the intensive margin which considers the quantity of resource, for example fertilizer, used for a given crop, and the extensive margin of adjustment that measures how farmers will adjust their crop proportions in response to climate change. Ideally economic models will measure the response to both these margins of adjustment simultaneously. The paper will briefly discuss some examples of the direct embedding of results from plant growth models in economic models.

Identifying at-risk employees: A behavioral model for predicting potential insider threats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greitzer, Frank L.; Kangas, Lars J.; Noonan, Christine F.

A psychosocial model was developed to assess an employee’s behavior associated with an increased risk of insider abuse. The model is based on case studies and research literature on factors/correlates associated with precursor behavioral manifestations of individuals committing insider crimes. In many of these crimes, managers and other coworkers observed that the offenders had exhibited signs of stress, disgruntlement, or other issues, but no alarms were raised. Barriers to using such psychosocial indicators include the inability to recognize the signs and the failure to record the behaviors so that they could be assessed by a person experienced in psychosocial evaluations.more » We have developed a model using a Bayesian belief network with the help of human resources staff, experienced in evaluating behaviors in staff. We conducted an experiment to assess its agreement with human resources and management professionals, with positive results. If implemented in an operational setting, the model would be part of a set of management tools for employee assessment that can raise an alarm about employees who pose higher insider threat risks. In separate work, we combine this psychosocial model’s assessment with computer workstation behavior to raise the efficacy of recognizing an insider crime in the making.« less

Spatiotemporal property and predictability of large-scale human mobility

NASA Astrophysics Data System (ADS)

Zhang, Hai-Tao; Zhu, Tao; Fu, Dongfei; Xu, Bowen; Han, Xiao-Pu; Chen, Duxin

2018-04-01

Spatiotemporal characteristics of human mobility emerging from complexity on individual scale have been extensively studied due to the application potential on human behavior prediction and recommendation, and control of epidemic spreading. We collect and investigate a comprehensive data set of human activities on large geographical scales, including both websites browse and mobile towers visit. Numerical results show that the degree of activity decays as a power law, indicating that human behaviors are reminiscent of scale-free random walks known as Lévy flight. More significantly, this study suggests that human activities on large geographical scales have specific non-Markovian characteristics, such as a two-segment power-law distribution of dwelling time and a high possibility for prediction. Furthermore, a scale-free featured mobility model with two essential ingredients, i.e., preferential return and exploration, and a Gaussian distribution assumption on the exploration tendency parameter is proposed, which outperforms existing human mobility models under scenarios of large geographical scales.

Intelligent Entity Behavior Within Synthetic Environments. Chapter 3

NASA Technical Reports Server (NTRS)

Kruk, R. V.; Howells, P. B.; Siksik, D. N.

2007-01-01

This paper describes some elements in the development of realistic performance and behavior in the synthetic entities (players) which support Modeling and Simulation (M&S) applications, particularly military training. Modern human-in-the-loop (virtual) training systems incorporate sophisticated synthetic environments, which provide: 1. The operational environment, including, for example, terrain databases; 2. Physical entity parameters which define performance in engineered systems, such as aircraft aerodynamics; 3. Platform/system characteristics such as acoustic, IR and radar signatures; 4. Behavioral entity parameters which define interactive performance, including knowledge/reasoning about terrain, tactics; and, 5. Doctrine, which combines knowledge and tactics into behavior rule sets. The resolution and fidelity of these model/database elements can vary substantially, but as synthetic environments are designed to be compose able, attributes may easily be added (e.g., adding a new radar to an aircraft) or enhanced (e.g. Amending or replacing missile seeker head/ Electronic Counter Measures (ECM) models to improve the realism of their interaction). To a human in the loop with synthetic entities, their observed veridicality is assessed via engagement responses (e.g. effect of countermeasures upon a closing missile), as seen on systems displays, and visual (image) behavior. The realism of visual models in a simulation (level of detail as well as motion fidelity) remains a challenge in realistic articulation of elements such as vehicle antennae and turrets, or, with human figures; posture, joint articulation, response to uneven ground. Currently the adequacy of visual representation is more dependant upon the quality and resolution of the physical models driving those entities than graphics processing power per Se. Synthetic entities in M&S applications traditionally have represented engineered systems (e.g. aircraft) with human-in-the-loop performance characteristics (e.g. visual acuity) included in the system behavioral specification. As well, performance affecting human parameters such as experience level, fatigue and stress are coming into wider use (via AI approaches) to incorporate more uncertainty as to response type as well as performance (e.g. Where an opposing entity might go and what it might do, as well as how well it might perform).

Differential Contribution of Low- and High-level Image Content to Eye Movements in Monkeys and Humans.

PubMed

Wilming, Niklas; Kietzmann, Tim C; Jutras, Megan; Xue, Cheng; Treue, Stefan; Buffalo, Elizabeth A; König, Peter

2017-01-01

Oculomotor selection exerts a fundamental impact on our experience of the environment. To better understand the underlying principles, researchers typically rely on behavioral data from humans, and electrophysiological recordings in macaque monkeys. This approach rests on the assumption that the same selection processes are at play in both species. To test this assumption, we compared the viewing behavior of 106 humans and 11 macaques in an unconstrained free-viewing task. Our data-driven clustering analyses revealed distinct human and macaque clusters, indicating species-specific selection strategies. Yet, cross-species predictions were found to be above chance, indicating some level of shared behavior. Analyses relying on computational models of visual saliency indicate that such cross-species commonalities in free viewing are largely due to similar low-level selection mechanisms, with only a small contribution by shared higher level selection mechanisms and with consistent viewing behavior of monkeys being a subset of the consistent viewing behavior of humans. © The Author 2017. Published by Oxford University Press.

Differential Contribution of Low- and High-level Image Content to Eye Movements in Monkeys and Humans

PubMed Central

Wilming, Niklas; Kietzmann, Tim C.; Jutras, Megan; Xue, Cheng; Treue, Stefan; Buffalo, Elizabeth A.; König, Peter

2017-01-01

Abstract Oculomotor selection exerts a fundamental impact on our experience of the environment. To better understand the underlying principles, researchers typically rely on behavioral data from humans, and electrophysiological recordings in macaque monkeys. This approach rests on the assumption that the same selection processes are at play in both species. To test this assumption, we compared the viewing behavior of 106 humans and 11 macaques in an unconstrained free-viewing task. Our data-driven clustering analyses revealed distinct human and macaque clusters, indicating species-specific selection strategies. Yet, cross-species predictions were found to be above chance, indicating some level of shared behavior. Analyses relying on computational models of visual saliency indicate that such cross-species commonalities in free viewing are largely due to similar low-level selection mechanisms, with only a small contribution by shared higher level selection mechanisms and with consistent viewing behavior of monkeys being a subset of the consistent viewing behavior of humans. PMID:28077512

Behavioral Teratogenesis in Drosophila melanogaster.

PubMed

Mishra, Monalisa; Barik, Bedanta Kumar

2018-01-01

Developmental biology is a fascinating branch of science which helps us to understand the mechanism of development, thus the findings are used in various therapeutic approach. Drosophila melanogaster served as a model to find the key molecules that initiate and regulate the mechanism of development. Various genes, transcription factors, and signaling pathways helping in development are identified in Drosophila. Many toxic compounds, which can affect the development, are also recognized using Drosophila model. These compounds, which can affect the development, are named as a teratogen. Many teratogens identified using Drosophila may also act as a teratogen for a human being since 75% of conservation exist between the disease genes present in Drosophila and human. There are certain teratogens, which do not cause developmental defect if exposed during pregnancy, however; behavioral defect appears in later part of development. Such compounds are named as a behavioral teratogen. Thus, it is worthy to identify the potential behavioral teratogen using Drosophila model. Drosophila behavior is well studied in various developmental stages. This chapter describes various methods which can be employed to test behavioral teratogenesis in Drosophila.

Integrative approaches utilizing oxytocin to enhance prosocial behavior: from animal and human social behavior to autistic social dysfunction.

PubMed

Yamasue, Hidenori; Yee, Jason R; Hurlemann, René; Rilling, James K; Chen, Frances S; Meyer-Lindenberg, Andreas; Tost, Heike

2012-10-10

The prevalence of autism spectrum disorder (ASD) is as high as 1 in 100 individuals and is a heavy burden to society. Thus, identifying causes and treatments is imperative. Here, we briefly review the topics covered in our 2012 Society for Neuroscience Mini-Symposium entitled "Integrative Approaches Using Oxytocin to Enhance Prosocial Behavior: From Animal and Human Social Behavior to ASD's Social Dysfunction." This work is not meant to be a comprehensive review of oxytocin and prosocial behavior. Instead, we wish to share the newest findings on the effects of oxytocin on social behavior, the brain, and the social dysfunction of ASD at the molecular, genetic, systemic, and behavior levels, in varied subjects ranging from animal models to humans suffering from autism for the purpose of promoting further study for developing the clinical use of oxytocin in treating ASD.

Caenorhabditis elegans as a Model to Study the Molecular and Genetic Mechanisms of Drug Addiction

PubMed Central

Engleman, Eric A.; Katner, Simon N.; Neal-Beliveau, Bethany S.

2016-01-01

Drug addiction takes a massive toll on society. Novel animal models are needed to test new treatments and understand the basic mechanisms underlying addiction. Rodent models have identified the neurocircuitry involved in addictive behavior and indicate that rodents possess some of the same neurobiologic mechanisms that mediate addiction in humans. Recent studies indicate that addiction is mechanistically and phylogenetically ancient and many mechanisms that underlie human addiction are also present in invertebrates. The nematode Caenorhabditis elegans has conserved neurobiologic systems with powerful molecular and genetic tools and a rapid rate of development that enables cost-effective translational discovery. Emerging evidence suggests that C. elegans is an excellent model to identify molecular mechanisms that mediate drug-induced behavior and potential targets for medications development for various addictive compounds. C. elegans emit many behaviors that can be easily quantitated including some that involve interactions with the environment. Ethanol (EtOH) is the best-studied drug-of-abuse in C. elegans and at least 50 different genes/targets have been identified as mediating EtOH’s effects and polymorphisms in some orthologs in humans are associated with alcohol use disorders. C. elegans has also been shown to display dopamine and cholinergic system–dependent attraction to nicotine and demonstrate preference for cues previously associated with nicotine. Cocaine and methamphetamine have been found to produce dopamine-dependent reward-like behaviors in C. elegans. These behavioral tests in combination with genetic/molecular manipulations have led to the identification of dozens of target genes/systems in C. elegans that mediate drug effects. The one target/gene identified as essential for drug-induced behavioral responses across all drugs of abuse was the cat-2 gene coding for tyrosine hydroxylase, which is consistent with the role of dopamine neurotransmission in human addiction. Overall, C. elegans can be used to model aspects of drug addiction and identify systems and molecular mechanisms that mediate drug effects. The findings are surprisingly consistent with analogous findings in higher-level organisms. Further, model refinement is warranted to improve model validity and increase utility for medications development. PMID:26810004

Caenorhabditis elegans as a Model to Study the Molecular and Genetic Mechanisms of Drug Addiction.

PubMed

Engleman, Eric A; Katner, Simon N; Neal-Beliveau, Bethany S

2016-01-01

Drug addiction takes a massive toll on society. Novel animal models are needed to test new treatments and understand the basic mechanisms underlying addiction. Rodent models have identified the neurocircuitry involved in addictive behavior and indicate that rodents possess some of the same neurobiologic mechanisms that mediate addiction in humans. Recent studies indicate that addiction is mechanistically and phylogenetically ancient and many mechanisms that underlie human addiction are also present in invertebrates. The nematode Caenorhabditis elegans has conserved neurobiologic systems with powerful molecular and genetic tools and a rapid rate of development that enables cost-effective translational discovery. Emerging evidence suggests that C. elegans is an excellent model to identify molecular mechanisms that mediate drug-induced behavior and potential targets for medications development for various addictive compounds. C. elegans emit many behaviors that can be easily quantitated including some that involve interactions with the environment. Ethanol (EtOH) is the best-studied drug-of-abuse in C. elegans and at least 50 different genes/targets have been identified as mediating EtOH's effects and polymorphisms in some orthologs in humans are associated with alcohol use disorders. C. elegans has also been shown to display dopamine and cholinergic system-dependent attraction to nicotine and demonstrate preference for cues previously associated with nicotine. Cocaine and methamphetamine have been found to produce dopamine-dependent reward-like behaviors in C. elegans. These behavioral tests in combination with genetic/molecular manipulations have led to the identification of dozens of target genes/systems in C. elegans that mediate drug effects. The one target/gene identified as essential for drug-induced behavioral responses across all drugs of abuse was the cat-2 gene coding for tyrosine hydroxylase, which is consistent with the role of dopamine neurotransmission in human addiction. Overall, C. elegans can be used to model aspects of drug addiction and identify systems and molecular mechanisms that mediate drug effects. The findings are surprisingly consistent with analogous findings in higher-level organisms. Further, model refinement is warranted to improve model validity and increase utility for medications development. Copyright © 2016. Published by Elsevier Inc.

The eHealth Behavior Management Model: a stage-based approach to behavior change and management.

PubMed

Bensley, Robert J; Mercer, Nelda; Brusk, John J; Underhile, Ric; Rivas, Jason; Anderson, Judith; Kelleher, Deanne; Lupella, Melissa; de Jager, André C

2004-10-01

Although the Internet has become an important avenue for disseminating health information, theory-driven strategies for aiding individuals in changing or managing health behaviors are lacking. The eHealth Behavior Management Model combines the Transtheoretical Model, the behavioral intent aspect of the Theory of Planned Behavior, and persuasive communication to assist individuals in negotiating the Web toward stage-specific information. It is here - at the point of stage-specific information - that behavioral intent in moving toward more active stages of change occurs. The eHealth Behavior Management Model is applied in three demonstration projects that focus on behavior management issues: parent-child nutrition education among participants in the U.S. Department of Agriculture Special Supplemental Nutrition Program for Women, Infants and Children; asthma management among university staff and students; and human immunodeficiency virus prevention among South African women. Preliminary results have found the eHealth Behavior Management Model to be promising as a model for Internet-based behavior change programming. Further application and evaluation among other behavior and disease management issues are needed.

MSEE: Stochastic Cognitive Linguistic Behavior Models for Semantic Sensing

DTIC Science & Technology

2013-09-01

recognition, a Gaussian Process Dynamic Model with Social Network Analysis (GPDM-SNA) for a small human group action recognition, an extended GPDM-SNA...44  3.2. Small Human Group Activity Modeling Based on Gaussian Process Dynamic Model and Social Network Analysis (SN-GPDM...51  Approved for public release; distribution unlimited. 3 3.2.3. Gaussian Process Dynamical Model and

The Use of Behavior Models for Predicting Complex Operations

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2010-01-01

Modeling and simulation (M&S) plays an important role when complex human-system notions are being proposed, developed and tested within the system design process. National Aeronautics and Space Administration (NASA) as an agency uses many different types of M&S approaches for predicting human-system interactions, especially when it is early in the development phase of a conceptual design. NASA Ames Research Center possesses a number of M&S capabilities ranging from airflow, flight path models, aircraft models, scheduling models, human performance models (HPMs), and bioinformatics models among a host of other kinds of M&S capabilities that are used for predicting whether the proposed designs will benefit the specific mission criteria. The Man-Machine Integration Design and Analysis System (MIDAS) is a NASA ARC HPM software tool that integrates many models of human behavior with environment models, equipment models, and procedural / task models. The challenge to model comprehensibility is heightened as the number of models that are integrated and the requisite fidelity of the procedural sets are increased. Model transparency is needed for some of the more complex HPMs to maintain comprehensibility of the integrated model performance. This will be exemplified in a recent MIDAS v5 application model and plans for future model refinements will be presented.

Modeling How, When, and What Is Learned in a Simple Fault-Finding Task

ERIC Educational Resources Information Center

Ritter, Frank E.; Bibby, Peter A.

2008-01-01

We have developed a process model that learns in multiple ways while finding faults in a simple control panel device. The model predicts human participants' learning through its own learning. The model's performance was systematically compared to human learning data, including the time course and specific sequence of learned behaviors. These…

Cyberpsychology: a human-interaction perspective based on cognitive modeling.

PubMed

Emond, Bruno; West, Robert L

2003-10-01

This paper argues for the relevance of cognitive modeling and cognitive architectures to cyberpsychology. From a human-computer interaction point of view, cognitive modeling can have benefits both for theory and model building, and for the design and evaluation of sociotechnical systems usability. Cognitive modeling research applied to human-computer interaction has two complimentary objectives: (1) to develop theories and computational models of human interactive behavior with information and collaborative technologies, and (2) to use the computational models as building blocks for the design, implementation, and evaluation of interactive technologies. From the perspective of building theories and models, cognitive modeling offers the possibility to anchor cyberpsychology theories and models into cognitive architectures. From the perspective of the design and evaluation of socio-technical systems, cognitive models can provide the basis for simulated users, which can play an important role in usability testing. As an example of application of cognitive modeling to technology design, the paper presents a simulation of interactive behavior with five different adaptive menu algorithms: random, fixed, stacked, frequency based, and activation based. Results of the simulation indicate that fixed menu positions seem to offer the best support for classification like tasks such as filing e-mails. This research is part of the Human-Computer Interaction, and the Broadband Visual Communication research programs at the National Research Council of Canada, in collaboration with the Carleton Cognitive Modeling Lab at Carleton University.

Validating a behavioral economic approach to assess food demand: effects of body mass index, dietary restraint, and impulsivity.

PubMed

Reslan, Summar; Saules, Karen K; Greenwald, Mark K

2012-10-01

Behavioral economic theory is a useful framework for analyzing factors influencing choice, but the majority of human behavioral economic research has focused on drug choice. The behavioral economic choice paradigm may also be valuable for understanding food-maintained behavior. Our primary objective was two-fold: (1) Validate a human laboratory model of food-appetitive behavior, and (2) Assess the contribution of individual level factors that may differentially impact food choice behavior. Two studies were conducted. In Study 1, female subjects (N=17) participated in two consecutive food choice experimental sessions, whereas in Study 2, female subjects (N=21) participated in one concurrent food choice experimental session. During consecutive choice sessions (Study 1), demand for the more palatable food (i.e., high-sugar/high-fat) was more inelastic than the less palatable (i.e., low-sugar/low-fat) option. During concurrent choice sessions, demand for the more palatable food (i.e., high-sugar/high-fat) was more inelastic for restrained vs. unrestrained eaters, and for those who were overweight vs. normal weight. Demand for both palatable and less palatable choices was more elastic for high-impulsive vs. low-impulsive subjects. These findings suggest that the behavioral economic framework can be used successfully to develop a human laboratory model of food-appetitive behavior. Copyright © 2012 Elsevier Ltd. All rights reserved.

Information spreading on mobile communication networks: A new model that incorporates human behaviors

NASA Astrophysics Data System (ADS)

Ren, Fei; Li, Sai-Ping; Liu, Chuang

2017-03-01

Recently, there is a growing interest in the modeling and simulation based on real social networks among researchers in multi-disciplines. Using an empirical social network constructed from the calling records of a Chinese mobile service provider, we here propose a new model to simulate the information spreading process. This model takes into account two important ingredients that exist in real human behaviors: information prevalence and preferential spreading. The fraction of informed nodes when the system reaches an asymptotically stable state is primarily determined by information prevalence, and the heterogeneity of link weights would slow down the information diffusion. Moreover, the sizes of blind clusters which consist of connected uninformed nodes show a power-law distribution, and these uninformed nodes correspond to a particular portion of nodes which are located at special positions in the network, namely at the edges of large clusters or inside the clusters connected through weak links. Since the simulations are performed on a real world network, the results should be useful in the understanding of the influences of social network structures and human behaviors on information propagation.

Strategies for the Integration of Cough and Swallow to Maintain Airway Protection in Humans.

PubMed

Huff, Alyssa; Reed, Mitchell D; Smith, Barbara K; Brown, Edward H; Ovechkin, Alexander V; Pitts, Teresa

2018-06-20

Airway protective behaviors, like cough and swallow, deteriorate in many populations suffering from neurologic disorders. While coordination of these behaviors has been investigated in an animal model, it has not been tested in humans. We used a novel protocol, adapted from previous work in the cat, to assess cough and swallow independently and their coordination strategies in seven healthy males (26 ± 6 years). Surface electromyograms of the submental complex and external oblique complex, spirometry, and thoracic and abdominal wall kinematics, were used to evaluate the timing of swallow, cough, and breathing as well as lung volume (LV) during these behaviors. Unlike the cat, there was significant variability in the cough-swallow phase preference; however, there was a targeted LV range in which swallow occurred. These results give insight into the differences between the cat and human models in airway protective strategies related to the coordination of cough and swallow behaviors, allowing for better understanding of dystussia and dysphagia.

Developmental social isolation affects adult behavior, social interaction, and dopamine metabolite levels in zebrafish.

PubMed

Shams, Soaleha; Amlani, Shahid; Buske, Christine; Chatterjee, Diptendu; Gerlai, Robert

2018-01-01

The zebrafish is a social vertebrate and an excellent translational model for a variety of human disorders. Abnormal social behavior is a hallmark of several human brain disorders. Social behavioral problems can arise as a result of adverse early social environment. Little is known about the effects of early social isolation in adult zebrafish. We compared zebrafish that were isolated for either short (7 days) or long duration (180 days) to socially housed zebrafish, testing their behavior across ontogenesis (ages 10, 30, 60, 90, 120, 180 days), and shoal cohesion and whole-brain monoamines and their metabolites in adulthood. Long social isolation increased locomotion and decreased shoal cohesion and anxiety in the open-field in adult. Additionally, both short and long social isolation reduced dopamine metabolite levels in response to social stimuli. Thus, early social isolation has lasting effects in zebrafish, and may be employed to generate zebrafish models of human neuropsychiatric conditions. © 2017 Wiley Periodicals, Inc.

Toward Realism in Human Performance Simulation

DTIC Science & Technology

2004-01-01

toward the development of improved human-like performance of synthetic agents. However, several serious problems continue to challenge researchers and... developers . Developers have insufficient behavioral knowledge. To date, models of emotivity and behavior that have been commercialized still tend...Bindiganavale, 1999). There has even been significant development of architectures to produce animated characters that react appropriately to a small

The Reinforcement of Ableism: Normality, the Medical Model of Disability, and Humanism in Applied Behavior Analysis and ASD

ERIC Educational Resources Information Center

Shyman, Eric

2016-01-01

The field of educating individuals with Autism Spectrum Disorder has ever been rife with controversy regarding issues ranging from etiology and causation to effective intervention and education options. One such basis for controversy has been between humanism, and humanistic philosophical concepts, and its fundamental differences with behaviorism,…

Emergence of scaling in human-interest dynamics.

PubMed

Zhao, Zhi-Dan; Yang, Zimo; Zhang, Zike; Zhou, Tao; Huang, Zi-Gang; Lai, Ying-Cheng

2013-12-11

Human behaviors are often driven by human interests. Despite intense recent efforts in exploring the dynamics of human behaviors, little is known about human-interest dynamics, partly due to the extreme difficulty in accessing the human mind from observations. However, the availability of large-scale data, such as those from e-commerce and smart-phone communications, makes it possible to probe into and quantify the dynamics of human interest. Using three prototypical "Big Data" sets, we investigate the scaling behaviors associated with human-interest dynamics. In particular, from the data sets we uncover fat-tailed (possibly power-law) distributions associated with the three basic quantities: (1) the length of continuous interest, (2) the return time of visiting certain interest, and (3) interest ranking and transition. We argue that there are three basic ingredients underlying human-interest dynamics: preferential return to previously visited interests, inertial effect, and exploration of new interests. We develop a biased random-walk model, incorporating the three ingredients, to account for the observed fat-tailed distributions. Our study represents the first attempt to understand the dynamical processes underlying human interest, which has significant applications in science and engineering, commerce, as well as defense, in terms of specific tasks such as recommendation and human-behavior prediction.

Emergence of scaling in human-interest dynamics

NASA Astrophysics Data System (ADS)

Zhao, Zhi-Dan; Yang, Zimo; Zhang, Zike; Zhou, Tao; Huang, Zi-Gang; Lai, Ying-Cheng

2013-12-01

Human behaviors are often driven by human interests. Despite intense recent efforts in exploring the dynamics of human behaviors, little is known about human-interest dynamics, partly due to the extreme difficulty in accessing the human mind from observations. However, the availability of large-scale data, such as those from e-commerce and smart-phone communications, makes it possible to probe into and quantify the dynamics of human interest. Using three prototypical ``Big Data'' sets, we investigate the scaling behaviors associated with human-interest dynamics. In particular, from the data sets we uncover fat-tailed (possibly power-law) distributions associated with the three basic quantities: (1) the length of continuous interest, (2) the return time of visiting certain interest, and (3) interest ranking and transition. We argue that there are three basic ingredients underlying human-interest dynamics: preferential return to previously visited interests, inertial effect, and exploration of new interests. We develop a biased random-walk model, incorporating the three ingredients, to account for the observed fat-tailed distributions. Our study represents the first attempt to understand the dynamical processes underlying human interest, which has significant applications in science and engineering, commerce, as well as defense, in terms of specific tasks such as recommendation and human-behavior prediction.

Petri nets as a modeling tool for discrete concurrent tasks of the human operator. [describing sequential and parallel demands on human operators

NASA Technical Reports Server (NTRS)

Schumacher, W.; Geiser, G.

1978-01-01

The basic concepts of Petri nets are reviewed as well as their application as the fundamental model of technical systems with concurrent discrete events such as hardware systems and software models of computers. The use of Petri nets is proposed for modeling the human operator dealing with concurrent discrete tasks. Their properties useful in modeling the human operator are discussed and practical examples are given. By means of and experimental investigation of binary concurrent tasks which are presented in a serial manner, the representation of human behavior by Petri nets is demonstrated.

Observing Consistency in Online Communication Patterns for User Re-Identification.

PubMed

Adeyemi, Ikuesan Richard; Razak, Shukor Abd; Salleh, Mazleena; Venter, Hein S

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.

Mouse model systems to study sex chromosome genes and behavior: relevance to humans

PubMed Central

Cox, Kimberly H.; Bonthuis, Paul J.; Rissman, Emilie F.

2014-01-01

Sex chromosome genes directly influence sex differences in behavior. The discovery of the Sry gene on the Y chromosome (Gubbay et al., 1990; Koopman et al., 1990) substantiated the sex chromosome mechanistic link to sex differences. Moreover, the pronounced connection between X chromosome gene mutations and mental illness produces a strong sex bias in these diseases. Yet, the dominant explanation for sex differences continues to be the gonadal hormones. Here we review progress made on behavioral differences in mouse models that uncouple sex chromosome complement from gonadal sex. We conclude that many social and cognitive behaviors are modified by sex chromosome complement, and discuss the implications for human research. Future directions need to include identification of the genes involved and interactions with these genes and gonadal hormones. PMID:24388960

Longitudinal analysis of behavioral, neurophysiological, viral and immunological effects of SIV infection in rhesus monkeys.

PubMed

Gold, L H; Fox, H S; Henriksen, S J; Buchmeier, M J; Weed, M R; Taffe, M A; Huitrón-Resendiz, S; Horn, T F; Bloom, F E

1998-01-01

A model is proposed in which a neurovirulent, microglial-passaged, simian immunodeficiency virus (SIV) is used to produce central nervous system (CNS) pathology and behavioral deficits in rhesus monkeys reminiscent of those seen in humans infected with human immunodeficiency virus (HIV). The time course of disease progression was characterized by using functional measures of cognition and motor skill, as well as neurophysiologic monitoring. Concomitant assessment of immunological and virological parameters illustrated correspondence between impaired behavioral performance and viral pathogenesis. Convergent results were obtained from neuropathological findings indicative of significant CNS disease. In ongoing studies, this SIV model is being used to explore the behavioral sequelae of immunodeficiency virus infection, the viral and host factors leading to neurologic dysfunction, and to begin testing potential therapeutic agents.

[Comparisons of aggressive behavior for Tibetan Macaques (Macaca thibetana) to tourists from Mt. Huangshan, China].

PubMed

Ji, Huan; Li, Jin-Hua; Sun, Bing-Hua; Zhu, Yong

2010-08-01

To investigate the relationship between monkey-human aggressive behaviors and age/sex classes of monkey (initiator) and human (recipient), by using all-occurrence sampling and continuous recording, we evaluated the monkey-human aggressive behaviors between macaques (Macaca thibetana) and tourists at Mt. Huangshan in two periods (Nov.-Dec.2008 and Apr.-May 2009). After we divide the aggression into three types according to the dangerous level to tourists, some significant patterns were observed.Our observations indicate that Tibetan macaques respond differently to human according to the age/sex classes involved. On one hand, We found that the adult male monkeys tend to be more aggressive than expected (P<0.01), while the adult female monkeys and immature monkeys participated in AGIII behaviors (threat) less than expected (P<0.01); On the other hand, The adult male human received more aggressive behaviors than expected (P<0.01), while the adult female human and child received less aggressive in AGIII behaviors (threat) (P<0.01). Our results provide not only a scientific basis for the management advice that adult male monkeys and adult male human should be given special attention, but also a good management model of Huangshan for other primate tourist exploring places.

Integrating the Human Sciences to Evolve Effective Policies

PubMed Central

Biglan, Anthony; Cody, Christine

2012-01-01

This paper describes an evolutionary perspective on human development and wellbeing and contrasts it with the model of self-interest that is prominent in economics. The two approaches have considerably different implications for how human wellbeing might be improved. Research in psychology, prevention science, and neuroscience is converging on an evolutionary account of the importance of two contrasting suites of social behavior—prosociality vs. antisocial behaviors (crime, drug abuse, risky sexual behavior) and related problems such as depression. Prosociality of individuals and groups evolves in environments that minimize toxic biological and social conditions, promote and richly reinforce prosocial behavior and attitudes, limit opportunities for antisocial behavior, and nurture the pursuit of prosocial values. Conversely, antisocial behavior and related problems emerge in environments that are high in threat and conflict. Over the past 30 years, randomized trials have shown numerous family, school, and community interventions to prevent most problem behaviors and promote prosociality. Research has also shown that poverty and economic inequality are major risk factors for the development of problem behaviors. The paper describes policies that can reduce poverty and benefit youth development. Although it is clear that the canonical economic model of rational self-interest has made a significant contribution to the science of economics, the evidence reviewed here shows that it must be reconciled with an evolutionary perspective on human development and wellbeing if society is going to evolve public policies that advance the health and wellbeing of the entire population. PMID:23833332

Modelling decision-making by pilots

NASA Technical Reports Server (NTRS)

Patrick, Nicholas J. M.

1993-01-01

Our scientific goal is to understand the process of human decision-making. Specifically, a model of human decision-making in piloting modern commercial aircraft which prescribes optimal behavior, and against which we can measure human sub-optimality is sought. This model should help us understand such diverse aspects of piloting as strategic decision-making, and the implicit decisions involved in attention allocation. Our engineering goal is to provide design specifications for (1) better computer-based decision-aids, and (2) better training programs for the human pilot (or human decision-maker, DM).

Inference in the Wild: A Framework for Human Situation Assessment and a Case Study of Air Combat.

PubMed

McAnally, Ken; Davey, Catherine; White, Daniel; Stimson, Murray; Mascaro, Steven; Korb, Kevin

2018-06-24

Situation awareness is a key construct in human factors and arises from a process of situation assessment (SA). SA comprises the perception of information, its integration with existing knowledge, the search for new information, and the prediction of the future state of the world, including the consequences of planned actions. Causal models implemented as Bayesian networks (BNs) are attractive for modeling all of these processes within a single, unified framework. We elicited declarative knowledge from two Royal Australian Air Force (RAAF) fighter pilots about the information sources used in the identification (ID) of airborne entities and the causal relationships between these sources. This knowledge was represented in a BN (the declarative model) that was evaluated against the performance of 19 RAAF fighter pilots in a low-fidelity simulation. Pilot behavior was well predicted by a simple associative model (the behavioral model) with only three attributes of ID. Search for information by pilots was largely compensatory and was near-optimal with respect to the behavioral model. The average revision of beliefs in response to evidence was close to Bayesian, but there was substantial variability. Together, these results demonstrate the value of BNs for modeling human SA. Copyright © 2018 Cognitive Science Society, Inc.

Modelling human decision-making in coupled human and natural systems

NASA Astrophysics Data System (ADS)

Feola, G.

2012-12-01

A solid understanding of human decision-making is essential to analyze the complexity of coupled human and natural systems (CHANS) and inform policies to promote resilience in the face of environmental change. Human decisions drive and/or mediate the interactions and feedbacks, and contribute to the heterogeneity and non-linearity that characterize CHANS. However, human decision-making is usually over-simplistically modeled, whereby human agents are represented deterministically either as dumb or clairvoyant decision-makers. Decision-making models fall short in the integration of both environmental and human behavioral drivers, and concerning the latter, tend to focus on only one category, e.g. economic, cultural, or psychological. Furthermore, these models render a linear decision-making process and therefore fail to account for the recursive co-evolutionary dynamics in CHANS. As a result, these models constitute only a weak basis for policy-making. There is therefore scope and an urgent need for better approaches to human decision-making, to produce the knowledge that can inform vulnerability reduction policies in the face of environmental change. This presentation synthesizes the current state-of-the-art of modelling human decision-making in CHANS, with particular reference to agricultural systems, and delineates how the above mentioned shortcomings can be overcome. Through examples from research on pesticide use and adaptation to climate change, both based on the integrative agent-centered framework (Feola and Binder, 2010), the approach for an improved understanding of human agents in CHANS are illustrated. This entails: integrative approach, focus on behavioral dynamics more than states, feedbacks between individual and system levels, and openness to heterogeneity.

Predicting Exposure to Consumer-Products Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence and Empirically -Based Scheduling Models

EPA Science Inventory

Information on human behavior and consumer product use is important for characterizing exposures to chemicals in consumer products and in indoor environments. Traditionally, exposure-assessors have relied on time-use surveys to obtain information on exposure-related behavior. In ...

Human Parental Care: Universal Goals, Cultural Strategies, Individual Behavior.

ERIC Educational Resources Information Center

LeVine, Robert A.

1988-01-01

A model of parental behavior as adaptation in agrarian and urban-industrial societies is proposed and examined in light of the evidence in this volume. The model is based on the concept of parental investment strategies for allocating time, attention, and domestic resources to raising children. (RH)

PROBABILISTIC MODELING FOR ADVANCED HUMAN EXPOSURE ASSESSMENT

EPA Science Inventory

Human exposures to environmental pollutants widely vary depending on the emission patterns that result in microenvironmental pollutant concentrations, as well as behavioral factors that determine the extent of an individual's contact with these pollutants. Probabilistic human exp...

Personality from a cognitive-biological perspective.

PubMed

Neuman, Yair

2014-12-01

The term "personality" is used to describe a distinctive and relatively stable set of mental traits that aim to explain the organism's behavior. The concept of personality that emerged in human psychology has been also applied to the study of non-human organisms from birds to horses. In this paper, I critically review the concept of personality from an interdisciplinary perspective, and point to some ideas that may be used for developing a cognitive-biological theory of personality. Integrating theories and research findings from various fields such as cognitive ethnology, clinical psychology, and neuroscience, I argue that the common denominator of various personality theories are neural systems of threat/trust management and their emotional, cognitive, and behavioral dimensions. In this context, personality may be also conceived as a meta-heuristics both human and non-human organisms apply to model and predict the behavior of others. The paper concludes by suggesting a minimal computational model of personality that may guide future research. Copyright © 2014 Elsevier B.V. All rights reserved.

Development of a mathematical model of the human cardiovascular system: An educational perspective

NASA Astrophysics Data System (ADS)

Johnson, Bruce Allen

A mathematical model of the human cardiovascular system will be a useful educational tool in biological sciences and bioengineering classrooms. The goal of this project is to develop a mathematical model of the human cardiovascular system that responds appropriately to variations of significant physical variables. Model development is based on standard fluid statics and dynamics principles, pressure-volume characteristics of the cardiac cycle, and compliant behavior of blood vessels. Cardiac cycle phases provide the physical and logical model structure, and Boolean algebra links model sections. The model is implemented using VisSim, a highly intuitive and easily learned block diagram modeling software package. Comparisons of model predictions of key variables to published values suggest that the model reasonably approximates expected behavior of those variables. The model responds plausibly to variations of independent variables. Projected usefulness of the model as an educational tool is threefold: independent variables which determine heart function may be easily varied to observe cause and effect; the model is used in an interactive setting; and the relationship of governing equations to model behavior is readily viewable and intuitive. Future use of this model in classrooms may give a more reasonable indication of its value as an educational tool.* *This dissertation includes a CD that is multimedia (contains text and other applications that are not available in a printed format). The CD requires the following applications: CorelPhotoHouse, CorelWordPerfect, VisSinViewer (included on CD), Internet access.

Combined Economic and Hydrologic Modeling to Support Collaborative Decision Making Processes

NASA Astrophysics Data System (ADS)

Sheer, D. P.

2008-12-01

For more than a decade, the core concept of the author's efforts in support of collaborative decision making has been a combination of hydrologic simulation and multi-objective optimization. The modeling has generally been used to support collaborative decision making processes. The OASIS model developed by HydroLogics Inc. solves a multi-objective optimization at each time step using a mixed integer linear program (MILP). The MILP can be configured to include any user defined objective, including but not limited too economic objectives. For example, an estimated marginal value for water for crops and M&I use were included in the objective function to drive trades in a model of the lower Rio Grande. The formulation of the MILP, constraints and objectives, in any time step is conditional: it changes based on the value of state variables and dynamic external forcing functions, such as rainfall, hydrology, market prices, arrival of migratory fish, water temperature, etc. It therefore acts as a dynamic short term multi-objective economic optimization for each time step. MILP is capable of solving a general problem that includes a very realistic representation of the physical system characteristics in addition to the normal multi-objective optimization objectives and constraints included in economic models. In all of these models, the short term objective function is a surrogate for achieving long term multi-objective results. The long term performance for any alternative (especially including operating strategies) is evaluated by simulation. An operating rule is the combination of conditions, parameters, constraints and objectives used to determine the formulation of the short term optimization in each time step. Heuristic wrappers for the simulation program have been developed improve the parameters of an operating rule, and are initiating research on a wrapper that will allow us to employ a genetic algorithm to improve the form of the rule (conditions, constraints, and short term objectives) as well. In the models operating rules represent different models of human behavior, and the objective of the modeling is to find rules for human behavior that perform well in terms of long term human objectives. The conceptual model used to represent human behavior incorporates economic multi-objective optimization for surrogate objectives, and rules that set those objectives based on current conditions and accounting for uncertainty, at least implicitly. The author asserts that real world operating rules follow this form and have evolved because they have been perceived as successful in the past. Thus, the modeling efforts focus on human behavior in much the same way that economic models focus on human behavior. This paper illustrates the above concepts with real world examples.

Did warfare among ancestral hunter-gatherers affect the evolution of human social behaviors?

PubMed

Bowles, Samuel

2009-06-05

Since Darwin, intergroup hostilities have figured prominently in explanations of the evolution of human social behavior. Yet whether ancestral humans were largely "peaceful" or "warlike" remains controversial. I ask a more precise question: If more cooperative groups were more likely to prevail in conflicts with other groups, was the level of intergroup violence sufficient to influence the evolution of human social behavior? Using a model of the evolutionary impact of between-group competition and a new data set that combines archaeological evidence on causes of death during the Late Pleistocene and early Holocene with ethnographic and historical reports on hunter-gatherer populations, I find that the estimated level of mortality in intergroup conflicts would have had substantial effects, allowing the proliferation of group-beneficial behaviors that were quite costly to the individual altruist.

Modeling the drugs' passive transfer in the body based on their chromatographic behavior.

PubMed

Kouskoura, Maria G; Kachrimanis, Kyriakos G; Markopoulou, Catherine K

2014-11-01

One of the most challenging aims in modern analytical chemistry and pharmaceutical analysis is to create models for drugs' behavior based on simulation experiments. Since drugs' effects are closely related to their molecular properties, numerous characteristics of drugs are used in order to acquire a model of passive absorption and transfer in the human body. Importantly, such direction in innovative bioanalytical methodologies is also of stressful need in the area of personalized medicine to implement nanotechnological and genomics advancements. Simulation experiments were carried out by examining and interpreting the chromatographic behavior of 113 analytes/drugs (400 observations) in RP-HPLC. The dataset employed for this purpose included 73 descriptors which are referring to the physicochemical properties of the mobile phase mixture in different proportions, the physicochemical properties of the analytes and the structural characteristics of their molecules. A series of different software packages was used to calculate all the descriptors apart from those referring to the structure of analytes. The correlation of the descriptors with the retention time of the analytes eluted from a C4 column with an aqueous mobile phase was employed as dataset to introduce the behavior models in the human body. Their evaluation with a Partial Least Squares (PLS) software proved that the chromatographic behavior of a drug on a lipophilic stationary and a polar mobile phase is directly related to its drug-ability. At the same time, the behavior of an unknown drug in the human body can be predicted with reliability via the Artificial Neural Networks (ANNs) software. Copyright © 2014 Elsevier B.V. All rights reserved.

Development of mathematical models of environmental physiology

NASA Technical Reports Server (NTRS)

Stolwijk, J. A. J.; Mitchell, J. W.; Nadel, E. R.

1971-01-01

Selected articles concerned with mathematical or simulation models of human thermoregulation are presented. The articles presented include: (1) development and use of simulation models in medicine, (2) model of cardio-vascular adjustments during exercise, (3) effective temperature scale based on simple model of human physiological regulatory response, (4) behavioral approach to thermoregulatory set point during exercise, and (5) importance of skin temperature in sweat regulation.

Acute Neuroimmune Modulation Attenuates the Development of Anxiety-Like Freezing Behavior in an Animal Model of Traumatic Brain Injury

PubMed Central

Rodgers, Krista M.; Bercum, Florencia M.; McCallum, Danielle L.; Rudy, Jerry W.; Frey, Lauren C.; Johnson, Kirk W.; Watkins, Linda R.

2012-01-01

Abstract Chronic anxiety is a common and debilitating result of traumatic brain injury (TBI) in humans. While little is known about the neural mechanisms of this disorder, inflammation resulting from activation of the brain's immune response to insult has been implicated in both human post-traumatic anxiety and in recently developed animal models. In this study, we used a lateral fluid percussion injury (LFPI) model of TBI in the rat and examined freezing behavior as a measure of post-traumatic anxiety. We found that LFPI produced anxiety-like freezing behavior accompanied by increased reactive gliosis (reflecting neuroimmune inflammatory responses) in key brain structures associated with anxiety: the amygdala, insula, and hippocampus. Acute peri-injury administration of ibudilast (MN166), a glial cell activation inhibitor, suppressed both reactive gliosis and freezing behavior, and continued neuroprotective effects were apparent several months post-injury. These results support the conclusion that inflammation produced by neuroimmune responses to TBI play a role in post-traumatic anxiety, and that acute suppression of injury-induced glial cell activation may have promise for the prevention of post-traumatic anxiety in humans. PMID:22435644

The cognitive architecture of anxiety-like behavioral inhibition.

PubMed

Bach, Dominik R

2017-01-01

The combination of reward and potential threat is termed approach/avoidance conflict and elicits specific behaviors, including passive avoidance and behavioral inhibition (BI). Anxiety-relieving drugs reduce these behaviors, and a rich psychological literature has addressed how personality traits dominated by BI predispose for anxiety disorders. Yet, a formal understanding of the cognitive inference and planning processes underlying anxiety-like BI is lacking. Here, we present and empirically test such formalization in the terminology of reinforcement learning. We capitalize on a human computer game in which participants collect sequentially appearing monetary tokens while under threat of virtual "predation." First, we demonstrate that humans modulate BI according to experienced consequences. This suggests an instrumental implementation of BI generation rather than a Pavlovian mechanism that is agnostic about action outcomes. Second, an internal model that would make BI adaptive is expressed in an independent task that involves no threat. The existence of such internal model is a necessary condition to conclude that BI is under model-based control. These findings relate a plethora of human and nonhuman observations on BI to reinforcement learning theory, and crucially constrain the quest for its neural implementation. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

An integrated framework for detecting suspicious behaviors in video surveillance

NASA Astrophysics Data System (ADS)

Zin, Thi Thi; Tin, Pyke; Hama, Hiromitsu; Toriu, Takashi

2014-03-01

In this paper, we propose an integrated framework for detecting suspicious behaviors in video surveillance systems which are established in public places such as railway stations, airports, shopping malls and etc. Especially, people loitering in suspicion, unattended objects left behind and exchanging suspicious objects between persons are common security concerns in airports and other transit scenarios. These involve understanding scene/event, analyzing human movements, recognizing controllable objects, and observing the effect of the human movement on those objects. In the proposed framework, multiple background modeling technique, high level motion feature extraction method and embedded Markov chain models are integrated for detecting suspicious behaviors in real time video surveillance systems. Specifically, the proposed framework employs probability based multiple backgrounds modeling technique to detect moving objects. Then the velocity and distance measures are computed as the high level motion features of the interests. By using an integration of the computed features and the first passage time probabilities of the embedded Markov chain, the suspicious behaviors in video surveillance are analyzed for detecting loitering persons, objects left behind and human interactions such as fighting. The proposed framework has been tested by using standard public datasets and our own video surveillance scenarios.

Animal models of female sexual dysfunction: basic considerations on drugs, arousal, motivation and behavior.

PubMed

Ågmo, Anders

2014-06-01

Female sexual dysfunctions are a heterogeneous group of symptoms with unknown but probably varying etiology. Social factors may contribute both to the prevalence and to the origin of these dysfunctions. The present review focuses on female hypoactive sexual desire disorder, sexual arousal disorder and orgasmic disorder. These disorders are generally the most common, according to epidemiological studies, and they can all be considered as disorders of motivation. An incentive motivational model of sexual behavior, applicable to humans as well as to non-human animals, is described and the dysfunctions placed into the context of this model. It is shown that endocrine alterations as well as observable alterations in neurotransmitter activity are unlikely causes of the disorders. A potential role of learning is stressed. Nevertheless, the role of some transmitters in female rodent sexual behavior is analyzed, and compared to data from women, whenever such data are available. The conclusion is that there is no direct coincidence between effects on rodent copulatory behavior and sexual behavior in women. Based on these and other considerations, it is suggested that sexual approach behaviors rather than copulatory reflexes in rodents might be of some relevance for human sexual behavior, and perhaps even for predicting the effects of interventions, perhaps even the effects of drugs. Female copulatory behaviors, including the proceptive behaviors, are less appropriate. The common sexual dysfunctions in women are not problems with the performance of copulatory acts, but with the desire for such acts, by feeling aroused by such acts and experiencing the pleasure expected to be caused by such acts. Finally, it is questioned whether female sexual dysfunctions are appropriate targets for pharmacological treatment. © 2013.

A GPU-accelerated cortical neural network model for visually guided robot navigation.

PubMed

Beyeler, Michael; Oros, Nicolas; Dutt, Nikil; Krichmar, Jeffrey L

2015-12-01

Humans and other terrestrial animals use vision to traverse novel cluttered environments with apparent ease. On one hand, although much is known about the behavioral dynamics of steering in humans, it remains unclear how relevant perceptual variables might be represented in the brain. On the other hand, although a wealth of data exists about the neural circuitry that is concerned with the perception of self-motion variables such as the current direction of travel, little research has been devoted to investigating how this neural circuitry may relate to active steering control. Here we present a cortical neural network model for visually guided navigation that has been embodied on a physical robot exploring a real-world environment. The model includes a rate based motion energy model for area V1, and a spiking neural network model for cortical area MT. The model generates a cortical representation of optic flow, determines the position of objects based on motion discontinuities, and combines these signals with the representation of a goal location to produce motor commands that successfully steer the robot around obstacles toward the goal. The model produces robot trajectories that closely match human behavioral data. This study demonstrates how neural signals in a model of cortical area MT might provide sufficient motion information to steer a physical robot on human-like paths around obstacles in a real-world environment, and exemplifies the importance of embodiment, as behavior is deeply coupled not only with the underlying model of brain function, but also with the anatomical constraints of the physical body it controls. Copyright © 2015 Elsevier Ltd. All rights reserved.

Merging Empiricism and Humanism: Role of Social Validity in the School-Wide Positive Behavior Support Model

ERIC Educational Resources Information Center

Marchant, Michelle; Heath, Melissa Allen; Miramontes, Nancy Y.

2013-01-01

Criteria for evaluating behavior support programs are changing. Consumer-based educational and behavioral programs, such as School-Wide Positive Behavior Support (SWPBS), are particularly influenced by consumer opinion. Unfortunately, the need for and use of social validity measures have not received adequate attention in the empirical literature…

Applied behavior analysis: New directions from the laboratory

PubMed Central

Epling, W. Frank; Pierce, W. David

1983-01-01

Applied behavior analysis began when laboratory based principles were extended to humans inorder to change socially significant behavior. Recent laboratory findings may have applied relevance; however, the majority of basic researchers have not clearly communicated the practical implications of their work. The present paper samples some of the new findings and attempts to demonstrate their applied importance. Schedule-induced behavior which occurs as a by-product of contingencies of reinforcement is discussed. Possible difficulties in treatment and management of induced behaviors are considered. Next, the correlation-based law of effect and the implications of relative reinforcement are explored in terms of applied examples. Relative rate of reinforcement is then extended to the literature dealing with concurrent operants. Concurrent operant models may describe human behavior of applied importance, and several techniques for modification of problem behavior are suggested. As a final concern, the paper discusses several new paradigms. While the practical importance of these models is not clear at the moment, it may be that new practical advantages will soon arise. Thus, it is argued that basic research continues to be of theoretical and practical importance to applied behavior analysis. PMID:22478574

Analyzing the posting behaviors in news forums with incremental inter-event time

NASA Astrophysics Data System (ADS)

Sun, Zhi; Peng, Qinke; Lv, Jia; Zhong, Tao

2017-08-01

Online human behaviors are widely discussed in various fields. Three key factors, named priority, interest and memory are found crucial in human behaviors. Existing research mainly focuses on the identified and active users. However, the anonymous users and the inactive ones exist widely in news forums, whose behaviors do not receive enough attention. They cannot offer abundant postings like the others. It requires us to study posting behaviors of all the users including anonymous ones, identified ones, active ones and inactive ones in news forums only at the collective level. In this paper, the memory effects of the posting behaviors in news forums are investigated at the collective level. On the basis of the incremental inter-event time, a new model is proposed to describe the posting behaviors at the collective level. The results on twelve actual news events demonstrate the good performance of our model to describe the posting behaviors at the collective level in news forums. In addition, we find the symmetric incremental inter-event time distribution and the similar posting patterns in different durations.

Modeling human behavior in economics and social science.

PubMed

Dolfin, M; Leonida, L; Outada, N

2017-12-01

The complex interactions between human behaviors and social economic sciences is critically analyzed in this paper in view of possible applications of mathematical modeling as an attainable interdisciplinary approach to understand and simulate the aforementioned dynamics. The quest is developed along three steps: Firstly an overall analysis of social and economic sciences indicates the main requirements that a contribution of mathematical modeling should bring to these sciences; subsequently the focus moves to an overview of mathematical tools and to the selection of those which appear, according to the authors bias, appropriate to the modeling; finally, a survey of applications is presented looking ahead to research perspectives. Copyright © 2017 Elsevier B.V. All rights reserved.

Global Sensitivity Analysis for Large-scale Socio-hydrological Models using the Cloud

NASA Astrophysics Data System (ADS)

Hu, Y.; Garcia-Cabrejo, O.; Cai, X.; Valocchi, A. J.; Dupont, B.

2014-12-01

In the context of coupled human and natural system (CHNS), incorporating human factors into water resource management provides us with the opportunity to understand the interactions between human and environmental systems. A multi-agent system (MAS) model is designed to couple with the physically-based Republican River Compact Administration (RRCA) groundwater model, in an attempt to understand the declining water table and base flow in the heavily irrigated Republican River basin. For MAS modelling, we defined five behavioral parameters (κ_pr, ν_pr, κ_prep, ν_prep and λ) to characterize the agent's pumping behavior given the uncertainties of the future crop prices and precipitation. κ and ν describe agent's beliefs in their prior knowledge of the mean and variance of crop prices (κ_pr, ν_pr) and precipitation (κ_prep, ν_prep), and λ is used to describe the agent's attitude towards the fluctuation of crop profits. Notice that these human behavioral parameters as inputs to the MAS model are highly uncertain and even not measurable. Thus, we estimate the influences of these behavioral parameters on the coupled models using Global Sensitivity Analysis (GSA). In this paper, we address two main challenges arising from GSA with such a large-scale socio-hydrological model by using Hadoop-based Cloud Computing techniques and Polynomial Chaos Expansion (PCE) based variance decomposition approach. As a result, 1,000 scenarios of the coupled models are completed within two hours with the Hadoop framework, rather than about 28days if we run those scenarios sequentially. Based on the model results, GSA using PCE is able to measure the impacts of the spatial and temporal variations of these behavioral parameters on crop profits and water table, and thus identifies two influential parameters, κ_pr and λ. The major contribution of this work is a methodological framework for the application of GSA in large-scale socio-hydrological models. This framework attempts to find a balance between the heavy computational burden regarding model execution and the number of model evaluations required in the GSA analysis, particularly through an organic combination of Hadoop-based Cloud Computing to efficiently evaluate the socio-hydrological model and PCE where the sensitivity indices are efficiently estimated from its coefficients.

Developing Cognitive Models for Social Simulation from Survey Data

NASA Astrophysics Data System (ADS)

Alt, Jonathan K.; Lieberman, Stephen

The representation of human behavior and cognition continues to challenge the modeling and simulation community. The use of survey and polling instruments to inform belief states, issue stances and action choice models provides a compelling means of developing models and simulations with empirical data. Using these types of data to population social simulations can greatly enhance the feasibility of validation efforts, the reusability of social and behavioral modeling frameworks, and the testable reliability of simulations. We provide a case study demonstrating these effects, document the use of survey data to develop cognitive models, and suggest future paths forward for social and behavioral modeling.

Human adipose-derived stem cells ameliorate repetitive behavior, social deficit and anxiety in a VPA-induced autism mouse model.

PubMed

Ha, Sungji; Park, Hyunjun; Mahmood, Usman; Ra, Jeong Chan; Suh, Yoo-Hun; Chang, Keun-A

2017-01-15

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by impairments in social interaction and communication, and patients often display co-occurring repetitive behaviors. Although the global prevalence of ASD has increased over time, the etiology and treatments for ASD are poorly understood. Recently, some researchers have suggested that stem cells have therapeutic potential for ASD. Thus, in the present study, we investigated the therapeutic effects of human adipose-derived stem cells (hASCs), a kind of autologous mesenchymal stem cells (MSCs) isolated from adipose tissue, on valproic acid (VPA)-induced autism model mice. Human ASCs were injected into the neonatal pups (P2 or P3) intraventricularly and then we evaluated major behavior symptoms of ASD. VPA-treated mice showed increased repetitive behaviors, decreased social interactions and increased anxiety but these autistic behaviors were ameliorated through transplantation of hASCs. In addition, hASCs transplantation restored the alteration of phosphatase and tensin homolog (PTEN) expression and p-AKT/AKT ratio in the brains of VPA-induced ASD model mice. The decreased level of vascular endothelial growth factor (VEGF) and interleukin 10 (IL-10) by VPA were rescued in the brains of the hASC-injected VPA mice. With these results, we experimentally found hASCs' therapeutic effects on autistic phenotypes in a ASD model mice for the first time. This animal model system can be used to elucidate further mechanisms of therapeutic effects of hASCs in ASD. Copyright © 2016 Elsevier B.V. All rights reserved.

Simulations in Cyber-Security: A Review of Cognitive Modeling of Network Attackers, Defenders, and Users

PubMed Central

Veksler, Vladislav D.; Buchler, Norbou; Hoffman, Blaine E.; Cassenti, Daniel N.; Sample, Char; Sugrim, Shridat

2018-01-01

Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting. PMID:29867661

Human Behavior & Low Energy Architecture: Linking Environmental Adaptation, Personal Comfort, & Energy Use in the Built Environment

NASA Astrophysics Data System (ADS)

Langevin, Jared

Truly sustainable buildings serve to enrich the daily sensory experience of their human inhabitants while consuming the least amount of energy possible; yet, building occupants and their environmentally adaptive behaviors remain a poorly characterized variable in even the most "green" building design and operation approaches. This deficiency has been linked to gaps between predicted and actual energy use, as well as to eventual problems with occupant discomfort, productivity losses, and health issues. Going forward, better tools are needed for considering the human-building interaction as a key part of energy efficiency strategies that promote good Indoor Environmental Quality (IEQ) in buildings. This dissertation presents the development and implementation of a Human and Building Interaction Toolkit (HABIT), a framework for the integrated simulation of office occupants' thermally adaptive behaviors, IEQ, and building energy use as part of sustainable building design and operation. Development of HABIT begins with an effort to devise more reliable methods for predicting individual occupants' thermal comfort, considered the driving force behind the behaviors of focus for this project. A long-term field study of thermal comfort and behavior is then presented, and the data it generates are used to develop and validate an agent-based behavior simulation model. Key aspects of the agent-based behavior model are described, and its predictive abilities are shown to compare favorably to those of multiple other behavior modeling options. Finally, the agent-based behavior model is linked with whole building energy simulation in EnergyPlus, forming the full HABIT program. The program is used to evaluate the energy and IEQ impacts of several occupant behavior scenarios in the simulation of a case study office building for the Philadelphia climate. Results indicate that more efficient local heating/cooling options may be paired with wider set point ranges to yield up to 24/28% HVAC energy savings in the winter/summer while also reducing thermal unacceptability; however, it is shown that the source of energy being saved must be considered in each case, as local heating options end up replacing cheaper, more carbon-friendly gas heating with expensive, emissions-heavy plug load electricity. The dissertation concludes with a summary of key outcomes and suggests how HABIT may be further developed in the future.

Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders.

PubMed

Hsiao, Elaine Y; McBride, Sara W; Hsien, Sophia; Sharon, Gil; Hyde, Embriette R; McCue, Tyler; Codelli, Julian A; Chow, Janet; Reisman, Sarah E; Petrosino, Joseph F; Patterson, Paul H; Mazmanian, Sarkis K

2013-12-19

Neurodevelopmental disorders, including autism spectrum disorder (ASD), are defined by core behavioral impairments; however, subsets of individuals display a spectrum of gastrointestinal (GI) abnormalities. We demonstrate GI barrier defects and microbiota alterations in the maternal immune activation (MIA) mouse model that is known to display features of ASD. Oral treatment of MIA offspring with the human commensal Bacteroides fragilis corrects gut permeability, alters microbial composition, and ameliorates defects in communicative, stereotypic, anxiety-like and sensorimotor behaviors. MIA offspring display an altered serum metabolomic profile, and B. fragilis modulates levels of several metabolites. Treating naive mice with a metabolite that is increased by MIA and restored by B. fragilis causes certain behavioral abnormalities, suggesting that gut bacterial effects on the host metabolome impact behavior. Taken together, these findings support a gut-microbiome-brain connection in a mouse model of ASD and identify a potential probiotic therapy for GI and particular behavioral symptoms in human neurodevelopmental disorders. Copyright © 2013 Elsevier Inc. All rights reserved.

The Sunk Cost Effect in Pigeons and Humans

ERIC Educational Resources Information Center

Navarro, Anton D.; Fantino, Edmund

2005-01-01

The sunk cost effect is the increased tendency to persist in an endeavor once an investment of money, effort, or time has been made. To date, humans are the only animal in which this effect has been observed unambiguously. We developed a behavior-analytic model of the sunk cost effect to explore the potential for this behavior in pigeons as well…

Assessing Students' Understanding of Human Behavior: A Multidisciplinary Outcomes Based Approach for the Design and Assessment of an Academic Program Goal.

ERIC Educational Resources Information Center

Keith, Bruce; Meese, Michael J.; Efflandt, Scott; Malinowski, Jon C.; LeBoeuf, Joseph; Gallagher, Martha; Hurley, John; Green, Charles

2002-01-01

Presents a strategy for the curricular design and assessment of one multidisciplinary program goal: understanding human behavior. Discusses how to assess a desired outcome based on four specific areas: (1) organizational context; (2) articulation of a learning model; (3) program design and implementation; and (4) outcomes assessment. (Author/KDR)

Modeling and prediction of human word search behavior in interactive machine translation

NASA Astrophysics Data System (ADS)

Ji, Duo; Yu, Bai; Ma, Bin; Ye, Na

2017-12-01

As a kind of computer aided translation method, Interactive Machine Translation technology reduced manual translation repetitive and mechanical operation through a variety of methods, so as to get the translation efficiency, and played an important role in the practical application of the translation work. In this paper, we regarded the behavior of users' frequently searching for words in the translation process as the research object, and transformed the behavior to the translation selection problem under the current translation. The paper presented a prediction model, which is a comprehensive utilization of alignment model, translation model and language model of the searching words behavior. It achieved a highly accurate prediction of searching words behavior, and reduced the switching of mouse and keyboard operations in the users' translation process.

Stereotypic Behavior in Nonhuman Primates as a Model for the Human Condition

PubMed Central

Lutz, Corrine K.

2014-01-01

Stereotypies that develop spontaneously in nonhuman primates can provide an effective model for repetitive stereotyped behavior in people with neurodevelopmental or obsessive-compulsive disorders. The behaviors are similar in form, are similarly affected by environmental conditions, and are improved with similar treatment methods such as enrichment, training, and drug therapy. However, because of a greater number of commonalities in these factors, nonhuman primates may serve as a better model for stereotyped behavior in individuals with autism or intellectual disability than for compulsions in individuals with obsessive-compulsive disorder. Because animal models may not be exact in all features of the disorder being studied, it is important to investigate the strengths and weaknesses of using a nonhuman primate model for stereotyped behavior in people with psychological disorders. PMID:25225307

Human Performance Models of Pilot Behavior

NASA Technical Reports Server (NTRS)

Foyle, David C.; Hooey, Becky L.; Byrne, Michael D.; Deutsch, Stephen; Lebiere, Christian; Leiden, Ken; Wickens, Christopher D.; Corker, Kevin M.

2005-01-01

Five modeling teams from industry and academia were chosen by the NASA Aviation Safety and Security Program to develop human performance models (HPM) of pilots performing taxi operations and runway instrument approaches with and without advanced displays. One representative from each team will serve as a panelist to discuss their team s model architecture, augmentations and advancements to HPMs, and aviation-safety related lessons learned. Panelists will discuss how modeling results are influenced by a model s architecture and structure, the role of the external environment, specific modeling advances and future directions and challenges for human performance modeling in aviation.

Postnatal colonization with human "infant-type" Bifidobacterium species alters behavior of adult gnotobiotic mice.

PubMed

Luk, Berkley; Veeraragavan, Surabi; Engevik, Melinda; Balderas, Miriam; Major, Angela; Runge, Jessica; Luna, Ruth Ann; Versalovic, James

2018-01-01

Accumulating studies have defined a role for the intestinal microbiota in modulation of host behavior. Research using gnotobiotic mice emphasizes that early microbial colonization with a complex microbiota (conventionalization) can rescue some of the behavioral abnormalities observed in mice that grow to adulthood completely devoid of bacteria (germ-free mice). However, the human infant and adult microbiomes vary greatly, and effects of the neonatal microbiome on neurodevelopment are currently not well understood. Microbe-mediated modulation of neural circuit patterning in the brain during neurodevelopment may have significant long-term implications that we are only beginning to appreciate. Modulation of the host central nervous system by the early-life microbiota is predicted to have pervasive and lasting effects on brain function and behavior. We sought to replicate this early microbe-host interaction by colonizing gnotobiotic mice at the neonatal stage with a simplified model of the human infant gut microbiota. This model consortium consisted of four "infant-type" Bifidobacterium species known to be commensal members of the human infant microbiota present in high abundance during postnatal development. Germ-free mice and mice neonatally-colonized with a complex, conventional murine microbiota were used for comparison. Motor and non-motor behaviors of the mice were tested at 6-7 weeks of age, and colonization patterns were characterized by 16S ribosomal RNA gene sequencing. Adult germ-free mice were observed to have abnormal memory, sociability, anxiety-like behaviors, and motor performance. Conventionalization at the neonatal stage rescued these behavioral abnormalities, and mice colonized with Bifidobacterium spp. also exhibited important behavioral differences relative to the germ-free controls. The ability of Bifidobacterium spp. to improve the recognition memory of both male and female germ-free mice was a prominent finding. Together, these data demonstrate that the early-life gut microbiome, and human "infant-type" Bifidobacterium species, affect adult behavior in a strongly sex-dependent manner, and can selectively recapitulate the results observed when mice are colonized with a complex microbiota.

Of Mice and Men: Empirical Support for the Population-Based Social Epistasis Amplification Model (a Comment on ).

PubMed

Sarraf, Matthew Alexandar; Woodley Of Menie, Michael Anthony

2017-01-01

This commentary article offers new perspective on recent research investigating the behavioral and social ecological effects of a mutation related to autism spectrum disorders in mice. The authors explain the consistency of this research on mice with predictions advanced by a theory of the role of mutations in altering interorganismal gene-gene interactions (social epistasis) in social species including humans, known as the social epistasis amplification model. The potential significance of the mouse research for understanding contemporary human behavioral trends is explored.

Modeling and simulation of evacuation behavior using fuzzy logic in a goal finding application

NASA Astrophysics Data System (ADS)

Sharma, Sharad; Ogunlana, Kola; Sree, Swetha

2016-05-01

Modeling and simulation has been widely used as a training and educational tool for depicting different evacuation strategies and damage control decisions during evacuation. However, there are few simulation environments that can include human behavior with low to high levels of fidelity. It is well known that crowd stampede induced by panic leads to fatalities as people are crushed or trampled. Our proposed goal finding application can be used to model situations that are difficult to test in real-life due to safety considerations. It is able to include agent characteristics and behaviors. Findings of this model are very encouraging as agents are able to assume various roles to utilize fuzzy logic on the way to reaching their goals. Fuzzy logic is used to model stress, panic and the uncertainty of emotions. The fuzzy rules link these parts together while feeding into behavioral rules. The contributions of this paper lies in our approach of utilizing fuzzy logic to show learning and adaptive behavior of agents in a goal finding application. The proposed application will aid in running multiple evacuation drills for what-if scenarios by incorporating human behavioral characteristics that can scale from a room to building. Our results show that the inclusion of fuzzy attributes made the evacuation time of the agents closer to the real time drills.

Displacement activities as a behavioral measure of stress in nonhuman primates and human subjects.

PubMed

Troisi, Alfonso

2002-02-01

Traditionally, research on human stress has relied mostly on physiological and psychological measures with a relatively minor emphasis on the behavioral aspects of the phenomenon. Such an approach makes it difficult to develop valid animal models of the human stress syndrome. A promising approach to the study of the behavioral correlates of stress is to analyze those behavior patterns that ethologists have named displacement activities and that, in primates, consist mostly of self-directed behaviors. In both nonhuman primates and human subjects, displacement behavior appears in situations characterized by social tension and is likely to reflect increased autonomic arousal. Pharmacological studies of nonhuman primates have shown that the frequency of occurrence of displacement behavior is increased by anxiogenic compounds and decreased by anxiolytic drugs. Ethological studies of healthy persons and psychiatric patients during interviews have found that increased displacement behavior not only correlates with a subjective feeling state of anxiety and negative affect but also gives more veridical information about the subject's emotional state than verbal statements and facial expression. The measurement of displacement activities may be a useful complement to the physiological and psychological studies aimed at analyzing the correlates and consequences of stress.

New approaches to investigating social gestures in autism spectrum disorder

PubMed Central

2012-01-01

The combination of economic games and human neuroimaging presents the possibility of using economic probes to identify biomarkers for quantitative features of healthy and diseased cognition. These probes span a range of important cognitive functions, but one new use is in the domain of reciprocating social exchange with other humans - a capacity perturbed in a number of psychopathologies. We summarize the use of a reciprocating exchange game to elicit neural and behavioral signatures for subjects diagnosed with autism spectrum disorder (ASD). Furthermore, we outline early efforts to capture features of social exchange in computational models and use these to identify quantitative behavioral differences between subjects with ASD and matched controls. Lastly, we summarize a number of subsequent studies inspired by the modeling results, which suggest new neural and behavioral signatures that could be used to characterize subtle deficits in information processing during interactions with other humans. PMID:22958572

Sexual motivation is reflected by stimulus-dependent motor cortex excitability.

PubMed

Schecklmann, Martin; Engelhardt, Kristina; Konzok, Julian; Rupprecht, Rainer; Greenlee, Mark W; Mokros, Andreas; Langguth, Berthold; Poeppl, Timm B

2015-08-01

Sexual behavior involves motivational processes. Findings from both animal models and neuroimaging in humans suggest that the recruitment of neural motor networks is an integral part of the sexual response. However, no study so far has directly linked sexual motivation to physiologically measurable changes in cerebral motor systems in humans. Using transcranial magnetic stimulation in hetero- and homosexual men, we here show that sexual motivation modulates cortical excitability. More specifically, our results demonstrate that visual sexual stimuli corresponding with one's sexual orientation, compared with non-corresponding visual sexual stimuli, increase the excitability of the motor cortex. The reflection of sexual motivation in motor cortex excitability provides evidence for motor preparation processes in sexual behavior in humans. Moreover, such interrelationship links theoretical models and previous neuroimaging findings of sexual behavior. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

The Various Roles of Animal Models in Understanding Human Development

ERIC Educational Resources Information Center

Gottlieb, Gilbert; Lickliter, Robert

2004-01-01

In this article, the authors take a very conservative view of the contribution of animal models to an understanding of human development. We do not think that homologies can be readily documented with even our most closely related relatives' behavior and psychological functioning. The major contribution of animal models is their provision of food…

Modeling of the mechanical behavior of the human femur: Stress analysis and strain

NASA Astrophysics Data System (ADS)

Belaid, Dalila; Bouchoucha, Ali

2015-12-01

The strength of bone depends on its state of mineralization, its geometry, and even supported loads. The femur is the longest bone, the largest and strongest of the human skeleton. It provides standing and walking and running, due to its hip joints with the one side, and with the patella and tibia across. The approach of this paper is to numerically model the mechanical behavior of the femur to determine the stress and strain distribution field. Modeling is performed on the ANSYS software. The results show the influence of different positions of the femur in different cases of postures.

Animal models of serotonergic psychedelics.

PubMed

Hanks, James B; González-Maeso, Javier

2013-01-16

The serotonin 5-HT(2A) receptor is the major target of psychedelic drugs such as lysergic acid diethylamide (LSD), mescaline, and psilocybin. Serotonergic psychedelics induce profound effects on cognition, emotion, and sensory processing that often seem uniquely human. This raises questions about the validity of animal models of psychedelic drug action. Nonetheless, recent findings suggest behavioral abnormalities elicited by psychedelics in rodents that predict such effects in humans. Here we review the behavioral effects induced by psychedelic drugs in rodent models, discuss the translational potential of these findings, and define areas where further research is needed to better understand the molecular mechanisms and neuronal circuits underlying their neuropsychological effects.

Animal Models of Serotonergic Psychedelics

PubMed Central

2012-01-01

The serotonin 5-HT2A receptor is the major target of psychedelic drugs such as lysergic acid diethylamide (LSD), mescaline, and psilocybin. Serotonergic psychedelics induce profound effects on cognition, emotion, and sensory processing that often seem uniquely human. This raises questions about the validity of animal models of psychedelic drug action. Nonetheless, recent findings suggest behavioral abnormalities elicited by psychedelics in rodents that predict such effects in humans. Here we review the behavioral effects induced by psychedelic drugs in rodent models, discuss the translational potential of these findings, and define areas where further research is needed to better understand the molecular mechanisms and neuronal circuits underlying their neuropsychological effects. PMID:23336043

Identification of the feedforward component in manual control with predictable target signals.

PubMed

Drop, Frank M; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus M; Mulder, Max

2013-12-01

In the manual control of a dynamic system, the human controller (HC) often follows a visible and predictable reference path. Compared with a purely feedback control strategy, performance can be improved by making use of this knowledge of the reference. The operator could effectively introduce feedforward control in conjunction with a feedback path to compensate for errors, as hypothesized in literature. However, feedforward behavior has never been identified from experimental data, nor have the hypothesized models been validated. This paper investigates human control behavior in pursuit tracking of a predictable reference signal while being perturbed by a quasi-random multisine disturbance signal. An experiment was done in which the relative strength of the target and disturbance signals were systematically varied. The anticipated changes in control behavior were studied by means of an ARX model analysis and by fitting three parametric HC models: two different feedback models and a combined feedforward and feedback model. The ARX analysis shows that the experiment participants employed control action on both the error and the target signal. The control action on the target was similar to the inverse of the system dynamics. Model fits show that this behavior can be modeled best by the combined feedforward and feedback model.

Human development index, children's health-related quality of life and movement behaviors: a compositional data analysis.

PubMed

Dumuid, Dorothea; Maher, Carol; Lewis, Lucy K; Stanford, Tyman E; Martín Fernández, Josep Antoni; Ratcliffe, Julie; Katzmarzyk, Peter T; Barreira, Tiago V; Chaput, Jean-Philippe; Fogelholm, Mikael; Hu, Gang; Maia, José; Sarmiento, Olga L; Standage, Martyn; Tremblay, Mark S; Tudor-Locke, Catrine; Olds, Timothy

2018-06-01

Health-related quality of life has been related to physical activity, sedentary behavior, and sleep among children from developed nations. These relationships have rarely been assessed in developing nations, nor have behaviors been considered in their true context, as mutually exclusive and exhaustive parts of the movement behavior composition. This study aimed to explore whether children's health-related quality of life is related to their movement behavior composition and if the relationship differs according to human development index. Children aged 9-11 years (n = 5855), from the 12-nation cross-sectional observational International Study of Childhood Obesity, Lifestyle and the Environment 2011-2013, self-reported their health-related quality of life (KIDSCREEN-10). Daily movement behaviors were from 24-h, 7-day accelerometry. Isometric log-ratio mixed-effect linear models were used to calculate estimates for difference in health-related quality of life for the reallocation of time between daily movement behaviors. Children from countries of higher human development index reported stronger positive relationships between health-related quality of life and moderate-to-vigorous physical activity, relative to the remaining behaviors (r = 0.75, p = 0.005) than those from lower human development index countries. In the very high human development index strata alone, health-related quality of life was significantly related to the movement behavior composition (p = 0.005), with moderate-to-vigorous physical activity (relative to remaining behaviors) being positively associated with health-related quality of life. The relationship between children's health-related quality of life and their movement behaviors is moderated by their country's human development index. This should be considered when 24-h movement behavior guidelines are developed for children around the world.

Summary of human social, cultural, behavioral (HSCB) modeling for information fusion panel discussion

NASA Astrophysics Data System (ADS)

Blasch, Erik; Salerno, John; Kadar, Ivan; Yang, Shanchieh J.; Fenstermacher, Laurie; Endsley, Mica; Grewe, Lynne

2013-05-01

During the SPIE 2012 conference, panelists convened to discuss "Real world issues and challenges in Human Social/Cultural/Behavioral modeling with Applications to Information Fusion." Each panelist presented their current trends and issues. The panel had agreement on advanced situation modeling, working with users for situation awareness and sense-making, and HSCB context modeling in focusing research activities. Each panelist added different perspectives based on the domain of interest such as physical, cyber, and social attacks from which estimates and projections can be forecasted. Also, additional techniques were addressed such as interest graphs, network modeling, and variable length Markov Models. This paper summarizes the panelists discussions to highlight the common themes and the related contrasting approaches to the domains in which HSCB applies to information fusion applications.

Epidemic Forecasting is Messier Than Weather Forecasting: The Role of Human Behavior and Internet Data Streams in Epidemic Forecast.

PubMed

Moran, Kelly R; Fairchild, Geoffrey; Generous, Nicholas; Hickmann, Kyle; Osthus, Dave; Priedhorsky, Reid; Hyman, James; Del Valle, Sara Y

2016-12-01

Mathematical models, such as those that forecast the spread of epidemics or predict the weather, must overcome the challenges of integrating incomplete and inaccurate data in computer simulations, estimating the probability of multiple possible scenarios, incorporating changes in human behavior and/or the pathogen, and environmental factors. In the past 3 decades, the weather forecasting community has made significant advances in data collection, assimilating heterogeneous data steams into models and communicating the uncertainty of their predictions to the general public. Epidemic modelers are struggling with these same issues in forecasting the spread of emerging diseases, such as Zika virus infection and Ebola virus disease. While weather models rely on physical systems, data from satellites, and weather stations, epidemic models rely on human interactions, multiple data sources such as clinical surveillance and Internet data, and environmental or biological factors that can change the pathogen dynamics. We describe some of similarities and differences between these 2 fields and how the epidemic modeling community is rising to the challenges posed by forecasting to help anticipate and guide the mitigation of epidemics. We conclude that some of the fundamental differences between these 2 fields, such as human behavior, make disease forecasting more challenging than weather forecasting. Published by Oxford University Press for the Infectious Diseases Society of America 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Evaluating social defeat as a model for psychopathology in adult female rodents.

PubMed

Solomon, Matia B

2017-01-02

Social conflict is a predominant stressor in humans and is associated with increased risk for developing psychological illnesses including depression and anxiety. Overwhelmingly, more women suffer from these disorders, which may be due to increased stress sensitivity. Like humans, rodents experience a myriad of physiological and behavioral sequelae due to prolonged stress exposure. Although the motivation for social conflict may differ between humans and rodents, female rodents may provide an opportunity to explore the underlying mechanisms by which stress confers risk for psychopathology in women. Because most female rodents do not express spontaneous aggression, the majority of basic research examines the physiological and behavioral outcomes of social conflict in male rodents. However, there are instances where female rodents exhibit territorial (California mice and Syrian hamsters) and maternal aggression (rats, mice, and hamsters) creating a venue to examine sex differences in physiology and behavior in response to stress. While many studies rely upon nonsocial behavioral assays (e.g., elevated plus maze, forced swim test) to assess the impact of stress on emotionality, here we primarily focus on behavioral outcomes in social-based assays in rodents. This is critically important given that disruptions in social relationships can be a cause and consequence of neuropsychiatric diseases. Next, we briefly discuss how sex differences in the recruitment of neural circuitry and/or neurochemistry in response to stress may underlie sex differences in neuroendocrine and behavioral stress responses. Finally, the translational value of females in rodent stress models and considerations regarding behavioral interpretations of these models are discussed. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Pattern Separation and Goal-Directed Behavior in the Aged Canine

ERIC Educational Resources Information Center

Snigdha, Shikha; Yassa, Michael A.; deRivera, Christina; Milgram, Norton W.; Cotman, Carl W.

2017-01-01

The pattern separation task has recently emerged as a behavioral model of hippocampus function and has been used in several pharmaceutical trials. The canine is a useful model to evaluate a multitude of hippocampal-dependent cognitive tasks that parallel those in humans. Thus, this study was designed to evaluate the suitability of pattern…

[Representation and mathematical analysis of human crystalline lens].

PubMed

Tălu, Stefan; Giovanzana, Stefano; Tălu, Mihai

2011-01-01

The surface of human crystalline lens can be described and analyzed using mathematical models based on parametric representations, used in biomechanical studies and 3D solid modeling of the lens. The mathematical models used in lens biomechanics allow the study and the behavior of crystalline lens on variables and complex dynamic loads. Also, the lens biomechanics has the potential to improve the results in the development of intraocular lenses and cataract surgery. The paper presents the most representative mathematical models currently used for the modeling of human crystalline lens, both optically and biomechanically.

Devaluation and sequential decisions: linking goal-directed and model-based behavior

PubMed Central

Friedel, Eva; Koch, Stefan P.; Wendt, Jean; Heinz, Andreas; Deserno, Lorenz; Schlagenhauf, Florian

2014-01-01

In experimental psychology different experiments have been developed to assess goal–directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed vs. habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favor of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans. PMID:25136310

Optimized Assistive Human-Robot Interaction Using Reinforcement Learning.

PubMed

Modares, Hamidreza; Ranatunga, Isura; Lewis, Frank L; Popa, Dan O

2016-03-01

An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive controller is designed in the inner loop to make the unknown nonlinear robot behave like a prescribed robot impedance model as perceived by a human operator. In contrast to existing neural network and adaptive impedance-based control methods, no information of the task performance or the prescribed robot impedance model parameters is required in the inner loop. Then, a task-specific outer-loop controller is designed to find the optimal parameters of the prescribed robot impedance model to adjust the robot's dynamics to the operator skills and minimize the tracking error. The outer loop includes the human operator, the robot, and the task performance details. The problem of finding the optimal parameters of the prescribed robot impedance model is transformed into a linear quadratic regulator (LQR) problem which minimizes the human effort and optimizes the closed-loop behavior of the HRI system for a given task. To obviate the requirement of the knowledge of the human model, integral reinforcement learning is used to solve the given LQR problem. Simulation results on an x - y table and a robot arm, and experimental implementation results on a PR2 robot confirm the suitability of the proposed method.

Statistical physics of vaccination

NASA Astrophysics Data System (ADS)

Wang, Zhen; Bauch, Chris T.; Bhattacharyya, Samit; d'Onofrio, Alberto; Manfredi, Piero; Perc, Matjaž; Perra, Nicola; Salathé, Marcel; Zhao, Dawei

2016-12-01

Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination-one of the most important preventive measures of modern times-is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research.

Accommodating complexity and human behaviors in decision analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Backus, George A.; Siirola, John Daniel; Schoenwald, David Alan

2007-11-01

This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

A model of the human in a cognitive prediction task.

NASA Technical Reports Server (NTRS)

Rouse, W. B.

1973-01-01

The human decision maker's behavior when predicting future states of discrete linear dynamic systems driven by zero-mean Gaussian processes is modeled. The task is on a slow enough time scale that physiological constraints are insignificant compared with cognitive limitations. The model is basically a linear regression system identifier with a limited memory and noisy observations. Experimental data are presented and compared to the model.

Neural Mechanism for Stochastic Behavior During a Competitive Game

PubMed Central

Soltani, Alireza; Lee, Daeyeol; Wang, Xiao-Jing

2006-01-01

Previous studies have shown that non-human primates can generate highly stochastic choice behavior, especially when this is required during a competitive interaction with another agent. To understand the neural mechanism of such dynamic choice behavior, we propose a biologically plausible model of decision making endowed with synaptic plasticity that follows a reward-dependent stochastic Hebbian learning rule. This model constitutes a biophysical implementation of reinforcement learning, and it reproduces salient features of behavioral data from an experiment with monkeys playing a matching pennies game. Due to interaction with an opponent and learning dynamics, the model generates quasi-random behavior robustly in spite of intrinsic biases. Furthermore, non-random choice behavior can also emerge when the model plays against a non-interactive opponent, as observed in the monkey experiment. Finally, when combined with a meta-learning algorithm, our model accounts for the slow drift in the animal’s strategy based on a process of reward maximization. PMID:17015181

Balancing selfishness and norm conformity can explain human behavior in large-scale prisoner's dilemma games and can poise human groups near criticality

NASA Astrophysics Data System (ADS)

Realpe-Gómez, John; Andrighetto, Giulia; Nardin, Luis Gustavo; Montoya, Javier Antonio

2018-04-01

Cooperation is central to the success of human societies as it is crucial for overcoming some of the most pressing social challenges of our time; still, how human cooperation is achieved and may persist is a main puzzle in the social and biological sciences. Recently, scholars have recognized the importance of social norms as solutions to major local and large-scale collective action problems, from the management of water resources to the reduction of smoking in public places to the change in fertility practices. Yet a well-founded model of the effect of social norms on human cooperation is still lacking. Using statistical-physics techniques and integrating findings from cognitive and behavioral sciences, we present an analytically tractable model in which individuals base their decisions to cooperate both on the economic rewards they obtain and on the degree to which their action complies with social norms. Results from this parsimonious model are in agreement with observations in recent large-scale experiments with humans. We also find the phase diagram of the model and show that the experimental human group is poised near a critical point, a regime where recent work suggests living systems respond to changing external conditions in an efficient and coordinated manner.

Correlation between social proximity and mobility similarity.

PubMed

Fan, Chao; Liu, Yiding; Huang, Junming; Rong, Zhihai; Zhou, Tao

2017-09-20

Human behaviors exhibit ubiquitous correlations in many aspects, such as individual and collective levels, temporal and spatial dimensions, content, social and geographical layers. With rich Internet data of online behaviors becoming available, it attracts academic interests to explore human mobility similarity from the perspective of social network proximity. Existent analysis shows a strong correlation between online social proximity and offline mobility similarity, namely, mobile records between friends are significantly more similar than between strangers, and those between friends with common neighbors are even more similar. We argue the importance of the number and diversity of common friends, with a counter intuitive finding that the number of common friends has no positive impact on mobility similarity while the diversity plays a key role, disagreeing with previous studies. Our analysis provides a novel view for better understanding the coupling between human online and offline behaviors, and will help model and predict human behaviors based on social proximity.

NASA's Use of Human Behavior Models for Concept Development and Evaluation

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2012-01-01

Overview of NASA's use of computational approaches and methods to support research goals, of human performance models, with a focus on examples of the methods used in Code TH and TI at NASA Ames, followed by an in depth review of MIDAS' current FAA work.

Health, Supportive Environments, and the Reasonable Person Model

Treesearch

Stephen Kaplan; Rachel Kaplan

2003-01-01

The Reasonable Person Model is a conceptual framework that links environmental factors with human behavior. People are more reasonable, cooperative, helpful, and satisfied when the environment supports their basic informational needs. The same environmental supports are important factors in enhancing human health. We use this framework to identify the informational...

INTEGRATED PROBABILISTIC AND DETERMINISTIC MODELING TECHNIQUES IN ESTIMATING EXPOSURE TO WATER-BORNE CONTAMINANTS: PART 1 EXPOSURE MODELING

EPA Science Inventory

Exposure to contaminants originating in the domestic water supply is influenced by a number of factors, including human activities, water use behavior, and physical and chemical processes. The key role of human activities is very apparent in exposure related to volatile water-...

Integrative Analysis of Genetic, Genomic, and Phenotypic Data for Ethanol Behaviors: A Network-Based Pipeline for Identifying Mechanisms and Potential Drug Targets.

PubMed

Bogenpohl, James W; Mignogna, Kristin M; Smith, Maren L; Miles, Michael F

2017-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce nonbiased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA, and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x environmental interactions affecting brain functioning in health and disease.

INTEGRATIVE ANALYSIS OF GENETIC, GENOMIC AND PHENOTYPIC DATA FOR ETHANOL BEHAVIORS: A NETWORK-BASED PIPELINE FOR IDENTIFYING MECHANISMS AND POTENTIAL DRUG TARGETS

PubMed Central

Bogenpohl, James W.; Mignogna, Kristin M.; Smith, Maren L.; Miles, Michael F.

2016-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce non-biased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x environmental interactions affecting brain functioning in health and disease. PMID:27933543

Emergence of scaling in human-interest dynamics

PubMed Central

Zhao, Zhi-Dan; Yang, Zimo; Zhang, Zike; Zhou, Tao; Huang, Zi-Gang; Lai, Ying-Cheng

2013-01-01

Human behaviors are often driven by human interests. Despite intense recent efforts in exploring the dynamics of human behaviors, little is known about human-interest dynamics, partly due to the extreme difficulty in accessing the human mind from observations. However, the availability of large-scale data, such as those from e-commerce and smart-phone communications, makes it possible to probe into and quantify the dynamics of human interest. Using three prototypical “Big Data” sets, we investigate the scaling behaviors associated with human-interest dynamics. In particular, from the data sets we uncover fat-tailed (possibly power-law) distributions associated with the three basic quantities: (1) the length of continuous interest, (2) the return time of visiting certain interest, and (3) interest ranking and transition. We argue that there are three basic ingredients underlying human-interest dynamics: preferential return to previously visited interests, inertial effect, and exploration of new interests. We develop a biased random-walk model, incorporating the three ingredients, to account for the observed fat-tailed distributions. Our study represents the first attempt to understand the dynamical processes underlying human interest, which has significant applications in science and engineering, commerce, as well as defense, in terms of specific tasks such as recommendation and human-behavior prediction. PMID:24326949

Introduction of the human AVPR1A gene substantially alters brain receptor expression patterns and enhances aspects of social behavior in transgenic mice

PubMed Central

Charles, Rhonda; Sakurai, Takeshi; Takahashi, Nagahide; Elder, Gregory A.; Gama Sosa, Miguel A.; Young, Larry J.; Buxbaum, Joseph D.

2014-01-01

Central arginine vasopressin receptor 1A (AVPR1A) modulates a wide range of behaviors, including stress management and territorial aggression, as well as social bonding and recognition. Inter- and intra-species variations in the expression pattern of AVPR1A in the brain and downstream differential behavioral phenotypes have been attributed to differences in the non-coding regions of the AVPR1A gene, including polymorphic elements within upstream regulatory areas. Gene association studies have suggested a link between AVPR1A polymorphisms and autism, and AVPR1A has emerged as a potential pharmacological target for treatment of social cognitive impairments and mood and anxiety disorders. To further investigate the genetic mechanism giving rise to species differences in AVPR1A expression patterns and associated social behaviors, and to create a preclinical mouse model useful for screening drugs targeting AVPR1A, we engineered and extensively characterized bacterial artificial chromosome (BAC) transgenic mice harboring the entire human AVPR1A locus with the surrounding regulatory elements. Compared with wild-type animals, the humanized mice displayed a more widely distributed ligand-AVPR1A binding pattern, which overlapped with that of primates. Furthermore, humanized AVPR1A mice displayed increased reciprocal social interactions compared with wild-type animals, but no differences in social approach and preference for social novelty were observed. Aspects of learning and memory, specifically novel object recognition and spatial relocation recognition, were unaffected. The biological alterations in humanized AVPR1A mice resulted in the rescue of the prepulse inhibition impairments that were observed in knockout mice, indicating conserved functionality. Although further behavioral paradigms and additional cohorts need to be examined in humanized AVPR1A mice, the results demonstrate that species-specific variations in the genomic content of regulatory regions surrounding the AVPR1A locus are responsible for differential receptor protein expression patterns across species and that they are likely to contribute to species-specific behavioral variation. The humanized AVPR1A mouse is a potential preclinical model for further understanding the regulation of receptor gene expression and the impact of variation in receptor expression on behaviors, and should be useful for screening drugs targeting human AVPR1A, taking advantage of the expression of human AVPR1A in human-relevant brain regions. PMID:24924430

Mechanical characterization of human brain tissue.

PubMed

Budday, S; Sommer, G; Birkl, C; Langkammer, C; Haybaeck, J; Kohnert, J; Bauer, M; Paulsen, F; Steinmann, P; Kuhl, E; Holzapfel, G A

2017-01-15

Mechanics are increasingly recognized to play an important role in modulating brain form and function. Computational simulations are a powerful tool to predict the mechanical behavior of the human brain in health and disease. The success of these simulations depends critically on the underlying constitutive model and on the reliable identification of its material parameters. Thus, there is an urgent need to thoroughly characterize the mechanical behavior of brain tissue and to identify mathematical models that capture the tissue response under arbitrary loading conditions. However, most constitutive models have only been calibrated for a single loading mode. Here, we perform a sequence of multiple loading modes on the same human brain specimen - simple shear in two orthogonal directions, compression, and tension - and characterize the loading-mode specific regional and directional behavior. We complement these three individual tests by combined multiaxial compression/tension-shear tests and discuss effects of conditioning and hysteresis. To explore to which extent the macrostructural response is a result of the underlying microstructural architecture, we supplement our biomechanical tests with diffusion tensor imaging and histology. We show that the heterogeneous microstructure leads to a regional but not directional dependence of the mechanical properties. Our experiments confirm that human brain tissue is nonlinear and viscoelastic, with a pronounced compression-tension asymmetry. Using our measurements, we compare the performance of five common constitutive models, neo-Hookean, Mooney-Rivlin, Demiray, Gent, and Ogden, and show that only the isotropic modified one-term Ogden model is capable of representing the hyperelastic behavior under combined shear, compression, and tension loadings: with a shear modulus of 0.4-1.4kPa and a negative nonlinearity parameter it captures the compression-tension asymmetry and the increase in shear stress under superimposed compression but not tension. Our results demonstrate that material parameters identified for a single loading mode fail to predict the response under arbitrary loading conditions. Our systematic characterization of human brain tissue will lead to more accurate computational simulations, which will allow us to determine criteria for injury, to develop smart protection systems, and to predict brain development and disease progression. There is a pressing need to characterize the mechanical behavior of human brain tissue under multiple loading conditions, and to identify constitutive models that are able to capture the tissue response under these conditions. We perform a sequence of experimental tests on the same brain specimen to characterize the regional and directional behavior, and we supplement our tests with DTI and histology to explore to which extent the macrostructural response is a result of the underlying microstructure. Results demonstrate that human brain tissue is nonlinear and viscoelastic, with a pronounced compression-tension asymmetry, and we show that the multiaxial data can best be captured by a modified version of the one-term Ogden model. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Differences of acute versus chronic ethanol exposure on anxiety-like behavioral responses in zebrafish.

PubMed

Mathur, Priya; Guo, Su

2011-06-01

Zebrafish, a vertebrate model organism amenable to high throughput screening, is an attractive system to model and study the mechanisms underlying human diseases. Alcoholism and alcoholic medical disorders are among the most debilitating diseases, yet the mechanisms by which ethanol inflicts the disease states are not well understood. In recent years zebrafish behavior assays have been used to study learning and memory, fear and anxiety, and social behavior. It is important to characterize the effects of ethanol on zebrafish behavioral repertoires in order to successfully harvest the strength of zebrafish for alcohol research. One prominent effect of alcohol in humans is its effect on anxiety, with acute intermediate doses relieving anxiety and withdrawal from chronic exposure increasing anxiety, both of which have significant contributions to alcohol dependence. In this study, we assess the effects of both acute and chronic ethanol exposure on anxiety-like behaviors in zebrafish, using two behavioral paradigms, the Novel Tank Diving Test and the Light/Dark Choice Assay. Acute ethanol exposure exerted significant dose-dependent anxiolytic effects. However, withdrawal from repeated intermittent ethanol exposure disabled recovery from heightened anxiety. These results demonstrate that zebrafish exhibit different anxiety-like behavioral responses to acute and chronic ethanol exposure, which are remarkably similar to these effects of alcohol in humans. Because of the accessibility of zebrafish to high throughput screening, our results suggest that genes and small molecules identified in zebrafish will be of relevance to understand how acute versus chronic alcohol exposure have opposing effects on the state of anxiety in humans. Copyright © 2011 Elsevier B.V. All rights reserved.

Synthesizing animal and human behavior research via neural network learning theory.

PubMed

Tryon, W W

1995-12-01

Animal and human research have been "divorced" since approximately 1968. Several recent articles have tried to persuade behavior therapists of the merits of animal research. Three reasons are given concerning why disinterest in animal research is so widespread: (1) functional explanations are given for animals, and cognitive explanations are given for humans; (2) serial symbol manipulating models are used to explain human behavior; and (3) human learning was assumed, thereby removing it as something to be explained. Brain-inspired connectionist neural networks, collectively referred to as neural network learning theory (NNLT), are briefly described, and a spectrum of their accomplishments from simple conditioning through speech is outlined. Five benefits that behavior therapists can derive from NNLT are described. They include (a) enhanced professional identity derived from a comprehensive learning theory, (b) improved interdisciplinary collaboration both clinically and scientifically, (c) renewed perceived relevance of animal research, (d) access to plausible proximal causal mechanisms capable of explaining operant conditioning, and (e) an inherently developmental perspective.

Neural network model for survival and growth of Salmonella 8,20:-:z6 in ground chicken thigh meat during cold storage: extrapolation to other serotypes

USDA-ARS?s Scientific Manuscript database

Mathematical models that predict behavior of human bacterial pathogens in food are valuable tools for assessing and managing this risk to public health. A study was undertaken to develop a model for predicting behavior of Salmonella 8,20:-:z6 in chicken meat during cold storage and to determine how...

Development of a Navy Job-Specific Vocational Interest Model

DTIC Science & Technology

2006-12-01

The role of job satisfaction in absence behavior. Organizational Behavior and Human Performance , 19, 148-161. Jackofsky, E. F., & Peters, L. H. (1983...Guidance Quarterly, (December), 160-165. Spencer, D. G., & Steers, R. M. (1981). Performance as a moderator of the job- satisfaction -turnover relationship...Application of Process Model to Measurement of Career Choice Satisfaction .............. 9 Content Model of Vocational Interests: Constructs and Structures

Constitutive modeling of the human Anterior Cruciate Ligament (ACL) under uniaxial loading using viscoelastic prony series and hyperelastic five parameter Mooney-Rivlin model

NASA Astrophysics Data System (ADS)

Chakraborty, Souvik; Mondal, Debabrata; Motalab, Mohammad

2016-07-01

In this present study, the stress-strain behavior of the Human Anterior Cruciate Ligament (ACL) is studied under uniaxial loads applied with various strain rates. Tensile testing of the human ACL samples requires state of the art test facilities. Furthermore, difficulty in finding human ligament for testing purpose results in very limited archival data. Nominal Stress vs. deformation gradient plots for different strain rates, as found in literature, is used to model the material behavior either as a hyperelastic or as a viscoelastic material. The well-known five parameter Mooney-Rivlin constitutivemodel for hyperelastic material and the Prony Series model for viscoelastic material are used and the objective of the analyses comprises of determining the model constants and their variation-trend with strain rates for the Human Anterior Cruciate Ligament (ACL) material using the non-linear curve fitting tool. The relationship between the model constants and strain rate, using the Hyperelastic Mooney-Rivlin model, has been obtained. The variation of the values of each coefficient with strain rates, obtained using Hyperelastic Mooney-Rivlin model are then plotted and variation of the values with strain rates are obtained for all the model constants. These plots are again fitted using the software package MATLAB and a power law relationship between the model constants and strain rates is obtained for each constant. The obtained material model for Human Anterior Cruciate Ligament (ACL) material can be implemented in any commercial finite element software package for stress analysis.

Discrete-time pilot model. [human dynamics and digital simulation

NASA Technical Reports Server (NTRS)

Cavalli, D.

1978-01-01

Pilot behavior is considered as a discrete-time process where the decision making has a sequential nature. This model differs from both the quasilinear model which follows from classical control theory and from the optimal control model which considers the human operator as a Kalman estimator-predictor. An additional factor considered is that the pilot's objective may not be adequately formulated as a quadratic cost functional to be minimized, but rather as a more fuzzy measure of the closeness with which the aircraft follows a reference trajectory. All model parameters, in the digital program simulating the pilot's behavior, were successfully compared in terms of standard-deviation and performance with those of professional pilots in IFR configuration. The first practical application of the model was in the study of its performance degradation when the aircraft model static margin decreases.

Autism Spectrum Disorders: Translating human deficits into mouse behavior.

PubMed

Pasciuto, E; Borrie, S C; Kanellopoulos, A K; Santos, A R; Cappuyns, E; D'Andrea, L; Pacini, L; Bagni, C

2015-10-01

Autism Spectrum Disorders are a heterogeneous group of neurodevelopmental disorders, with rising incidence but little effective therapeutic intervention available. Currently two main clinical features are described to diagnose ASDs: impaired social interaction and communication, and repetitive behaviors. Much work has focused on understanding underlying causes of ASD by generating animal models of the disease, in the hope of discovering signaling pathways and cellular targets for drug intervention. Here we review how ASD behavioral phenotypes can be modeled in the mouse, the most common animal model currently in use in this field, and discuss examples of genetic mouse models of ASD with behavioral features that recapitulate various symptoms of ASD. Copyright © 2015 Elsevier Inc. All rights reserved.

Brief communication: Reaction to fire by savanna chimpanzees (Pan troglodytes verus) at Fongoli, Senegal: Conceptualization of "fire behavior" and the case for a chimpanzee model.

PubMed

Pruetz, Jill D; LaDuke, Thomas C

2010-04-01

The use and control of fire are uniquely human traits thought to have come about fairly late in the evolution of our lineage, and they are hypothesized to correlate with an increase in intellectual complexity. Given the relatively sophisticated cognitive abilities yet small brain size of living apes compared to humans and even early hominins, observations of wild chimpanzees' reactions to naturally occurring fire can help inform hypotheses about the likely responses of early hominins to fire. We use data on the behavior of savanna chimpanzees (Pan troglodytes verus) at Fongoli, Senegal during two encounters with wildfires to illuminate the similarities between great apes and humans regarding their reaction to fire. Chimpanzees' close relatedness to our lineage makes them phylogenetically relevant to the study of hominid evolution, and the open, hot and dry environment at Fongoli, similar to the savanna mosaic thought to characterize much of hominid evolution, makes these apes ecologically important as a living primate model as well. Chimpanzees at Fongoli calmly monitor wildfires and change their behavior in anticipation of the fire's movement. The ability to conceptualize the "behavior" of fire may be a synapomorphic trait characterizing the human-chimpanzee clade. If the cognitive underpinnings of fire conceptualization are a primitive hominid trait, hypotheses concerning the origins of the control and use of fire may need revision. We argue that our findings exemplify the importance of using living chimpanzees as models for better understanding human evolution despite recently published suggestions to the contrary. (c) 2009 Wiley-Liss, Inc.

Predicting Team Performance through Human Behavioral Sensing and Quantitative Workflow Instrumentation

DTIC Science & Technology

2016-07-27

make risk-informed decisions during serious games . Statistical models of intra- game performance were developed to determine whether behaviors in...specific facets of the gameplay workflow were predictive of analytical performance and games outcomes. A study of over seventy instrumented teams revealed...more accurate game decisions. 2 Keywords: Humatics · Serious Games · Human-System Interaction · Instrumentation · Teamwork · Communication Analysis

International Space Station Human Behavior and Performance Competency Model: Volume I

NASA Technical Reports Server (NTRS)

Schmidt, Lacey

2008-01-01

This document defines Human Behavior and Performance (HBP) competencies that are recommended to be included as requirements to participate in international long duration missions. They were developed in response to the Multilateral Crew Operations Panel (MMOP) request to develop HBP training requirements for the International Space Station (ISS). The competency model presented here was developed by the ITCB HBPT WG and forms the basis for determining the HBP training curriculum for long duration crewmembers. This document lists specific HBP competencies and behaviors required of astronauts/cosmonauts who participate in ISS expedition and other international longduration missions. Please note that this model does not encompass all competencies required. For example, outside the scope of this document are cognitive skills and abilities, including but not limited to concentration, memorization, perception, imagination, and thinking. It is assumed that these skills, which are crucial in terms of human behavior and performance, are considered during selection phase since such professionally significant qualities of the operator should be taken into consideration in order to ensure sufficient baseline levels that can be further improved during general astronaut training. Also, technical competencies, even though critical for crewmembers, are beyond the scope of this document. It should also be noted that the competencies in this model (and subsequent objectives) are not intended to limit the internal activities or training programs of any international partner.

Compassion and Caring: Missing Concepts in Social Studies Programs.

ERIC Educational Resources Information Center

Oliner, Pearl

1979-01-01

Current social studies programs do not include the study of prosocial behaviors such as altruism, generosity, and compassion. This omission legitimizes the view that human behaviors are self-serving. Curriculum developers should fashion programs which provide prosocial models and opportunities for students to conceptualize such behaviors and…

Selection of behavioral tasks and development of software for evaluation of Rhesus Monkey behavior during spaceflight

NASA Technical Reports Server (NTRS)

Rumbaugh, Duane M.; Washburn, David A.; Richardson, W. K.

1996-01-01

The results of several experiments were disseminated during this semiannual period. These publications and presented papers represent investigations of the continuity in psychological processes between monkeys and humans. Thus, each serves to support the animal model of behavior and performance research.

The Nature of Culture: an eight-grade model for the evolution and expansion of cultural capacities in hominins and other animals.

PubMed

Haidle, Miriam Noël; Bolus, Michael; Collard, Mark; Conard, Nicholas; Garofoli, Duilio; Lombard, Marlize; Nowell, April; Tennie, Claudio; Whiten, Andrew

2015-07-20

Tracing the evolution of human culture through time is arguably one of the most controversial and complex scholarly endeavors, and a broad evolutionary analysis of how symbolic, linguistic, and cultural capacities emerged and developed in our species is lacking. Here we present a model that, in broad terms, aims to explain the evolution and portray the expansion of human cultural capacities (the EECC model), that can be used as a point of departure for further multidisciplinary discussion and more detailed investigation. The EECC model is designed to be flexible, and can be refined to accommodate future archaeological, paleoanthropological, genetic or evolutionary psychology/behavioral analyses and discoveries. Our proposed concept of cultural behavior differentiates between empirically traceable behavioral performances and behavioral capacities that are theoretical constructs. Based largely on archaeological data (the 'black box' that most directly opens up hominin cultural evolution), and on the extension of observable problem-solution distances, we identify eight grades of cultural capacity. Each of these grades is considered within evolutionary-biological and historical-social trajectories. Importantly, the model does not imply an inevitable progression, but focuses on expansion of cultural capacities based on the integration of earlier achievements. We conclude that there is not a single cultural capacity or a single set of abilities that enabled human culture; rather, several grades of cultural capacity in animals and hominins expanded during our evolution to shape who we are today.

Observing Consistency in Online Communication Patterns for User Re-Identification

PubMed Central

Venter, Hein S.

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas. PMID:27918593

Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

PubMed

Cipresso, Pietro; Riva, Giuseppe

2015-01-01

There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

Consistent evolution in a pedestrian flow

NASA Astrophysics Data System (ADS)

Guan, Junbiao; Wang, Kaihua

2016-03-01

In this paper, pedestrian evacuation considering different human behaviors is studied by using a cellular automaton (CA) model combined with the snowdrift game theory. The evacuees are divided into two types, i.e. cooperators and defectors, and two different human behaviors, herding behavior and independent behavior, are investigated. It is found from a large amount of numerical simulations that the ratios of the corresponding evacuee clusters are evolved to consistent states despite 11 typically different initial conditions, which may largely owe to self-organization effect. Moreover, an appropriate proportion of initial defectors who are of herding behavior, coupled with an appropriate proportion of initial defectors who are of rationally independent thinking, are two necessary factors for short evacuation time.

The applied importance of research on the matching law

PubMed Central

Pierce, W. David; Epling, W. Frank

1995-01-01

In this essay, we evaluate the applied implications of two articles related to the matching law and published in the Journal of the Experimental Analysis of Behavior, May 1994. Building on Mace's (1994) criteria for increasing the applied relevance of basic research, we evaluate the applied implications of basic research studies. Research by Elsmore and McBride (1994) and Savastano and Fantino (1994) involve an extension of the behavioral model of choice. Elsmore and McBride used rats as subjects, but arranged a multioperant environment that resembles some of the complex contingencies of human behavior. Savastino and Fantino used human subjects and extended the matching law to ratio and interval contingencies. These experiments contribute to a growing body of knowledge on the matching law and its relevance for human behavior. PMID:16795866

Social interaction shapes babbling: Testing parallels between birdsong and speech

NASA Astrophysics Data System (ADS)

Goldstein, Michael H.; King, Andrew P.; West, Meredith J.

2003-06-01

Birdsong is considered a model of human speech development at behavioral and neural levels. Few direct tests of the proposed analogs exist, however. Here we test a mechanism of phonological development in human infants that is based on social shaping, a selective learning process first documented in songbirds. By manipulating mothers' reactions to their 8-month-old infants' vocalizations, we demonstrate that phonological features of babbling are sensitive to nonimitative social stimulation. Contingent, but not noncontingent, maternal behavior facilitates more complex and mature vocal behavior. Changes in vocalizations persist after the manipulation. The data show that human infants use social feedback, facilitating immediate transitions in vocal behavior. Social interaction creates rapid shifts to developmentally more advanced sounds. These transitions mirror the normal development of speech, supporting the predictions of the avian social shaping model. These data provide strong support for a parallel in function between vocal precursors of songbirds and infants. Because imitation is usually considered the mechanism for vocal learning in both taxa, the findings introduce social shaping as a general process underlying the development of speech and song.

Generation of transgenic monkeys with human inherited genetic disease.

PubMed

Chan, Anthony W S; Yang, Shang-Hsun

2009-09-01

Modeling human diseases using nonhuman primates including chimpanzee, rhesus, cynomolgus, marmoset and squirrel monkeys has been reported in the past decades. Due to the high similarity between nonhuman primates and humans, including genome constitution, cognitive behavioral functions, anatomical structure, metabolic, reproductive, and brain functions; nonhuman primates have played an important role in understanding physiological functions of the human body, clarifying the underlying mechanism of human diseases, and the development of novel treatments for human diseases. However, nonhuman primate research has been restricted to cognitive, behavioral, biochemical and pharmacological approaches of human diseases due to the limitation of gene transfer technology in nonhuman primates. The recent advancement in transgenic technology that has led to the generation of the first transgenic monkey in 2001 and a transgenic monkey model of Huntington's disease (HD) in 2008 has changed that focus. The creation of transgenic HD monkeys that replicate key pathological features of human HD patients further suggests the crucial role of nonhuman primates in the future development of biomedicine. These successes have opened the door to genetic manipulation in nonhuman primates and a new era in modeling human inherited genetic disorders. We focused on the procedures in creating transgenic Huntington's disease monkeys, but our work can be applied to transgenesis in other nonhuman primate species.

Human Facial Expressions as Adaptations:Evolutionary Questions in Facial Expression Research

PubMed Central

SCHMIDT, KAREN L.; COHN, JEFFREY F.

2007-01-01

The importance of the face in social interaction and social intelligence is widely recognized in anthropology. Yet the adaptive functions of human facial expression remain largely unknown. An evolutionary model of human facial expression as behavioral adaptation can be constructed, given the current knowledge of the phenotypic variation, ecological contexts, and fitness consequences of facial behavior. Studies of facial expression are available, but results are not typically framed in an evolutionary perspective. This review identifies the relevant physical phenomena of facial expression and integrates the study of this behavior with the anthropological study of communication and sociality in general. Anthropological issues with relevance to the evolutionary study of facial expression include: facial expressions as coordinated, stereotyped behavioral phenotypes, the unique contexts and functions of different facial expressions, the relationship of facial expression to speech, the value of facial expressions as signals, and the relationship of facial expression to social intelligence in humans and in nonhuman primates. Human smiling is used as an example of adaptation, and testable hypotheses concerning the human smile, as well as other expressions, are proposed. PMID:11786989

Quantitative comparisons of the acute neurotoxicity of toluene in rats and humans.

PubMed

Benignus, Vernon A; Boyes, William K; Kenyon, Elaina M; Bushnell, Philip J

2007-11-01

The behavioral and neurophysiological effects of acute exposure to toluene are the most thoroughly explored of all the hydrocarbon solvents. Behavioral effects have been experimentally studied in humans and other species, for example, rats. The existence of both rat and human dosimetric data offers the opportunity to quantitatively compare the relative sensitivity to acute toluene exposure. The purpose of this study was to fit dose-effect curves to existing data and to estimate the dose-equivalence equation (DEE) between rats and humans. The DEE gives the doses that produce the same magnitude of effect in the two species. Doses were brain concentrations of toluene estimated from physiologically based pharmacokinetic models. Human experiments measuring toluene effects on choice reaction time (CRT) were meta-analyzed. Rat studies employed various dependent variables: amplitude of visual-evoked potentials (VEPs), signal detection (SIGDET) accuracy (ACCU) and reaction time (RT), and escape-avoidance (ES-AV) behaviors. Comparison of dose-effect functions showed that human and rat sensitivity was practically the same for those two task regimens that exerted the least control over the behaviors being measured (VEP in rats and CRT in humans) and the sensitivity was progressively lower for SIGDET RT, SIGDET ACCU, and ES-AV behaviors in rats. These results suggested that the sensitivity to impairment by toluene depends on the strength of control over the measured behavior rather than on the species being tested. This interpretation suggests that (1) sensitivity to toluene would be equivalent in humans and rats if both species performed behaviors that were controlled to the same extent, (2) the most sensitive tests of neurobehavioral effects would be those in which least control is exerted on the behavior being measured, and (3) effects of toluene in humans may be estimated using the DEEs from rat studies despite differences in the amount of control exerted by the experimental regimen or differences in the behaviors under investigation.

Selectivity in early prosocial behavior

PubMed Central

Kuhlmeier, Valerie A.; Dunfield, Kristen A.; O’Neill, Amy C.

2014-01-01

Prosocial behavior requires expenditure of personal resources for the benefit of others, a fact that creates a “problem” when considering the evolution of prosociality. Models that address this problem have been developed, with emphasis typically placed on reciprocity. One model considers the advantages of being selective in terms of one’s allocation of prosocial behavior so as to improve the chance that one will be benefitted in return. In this review paper, we first summarize this “partner choice” model and then focus on prosocial development in the preschool years, where we make the case for selective partner choice in early instances of human prosocial behavior. PMID:25120526

Perinatal administration of aromatase inhibitors in rodents as animal models of human male homosexuality: similarities and differences.

PubMed

Olvera-Hernández, Sandra; Fernández-Guasti, Alonso

2015-01-01

In this chapter we briefly review the evidence supporting the existence of biological influences on sexual orientation. We focus on basic research studies that have affected the estrogen synthesis during the critical periods of brain sexual differentiation in male rat offspring with the use of aromatase inhibitors, such as 1,4,6-androstatriene-3,17 (ATD) and letrozole. The results after prenatal and/or postnatal treatment with ATD reveal that these animals, when adults, show female sexual responses, such as lordosis or proceptive behaviors, but retain their ability to display male sexual activity with a receptive female. Interestingly, the preference and sexual behavior of these rats vary depending upon the circadian rhythm.Recently, we have established that the treatment with low doses of letrozole during the second half of pregnancy produces male rat offspring, that when adults spend more time in the company of a sexually active male than with a receptive female in a preference test. In addition, they display female sexual behavior when forced to interact with a sexually experienced male and some typical male sexual behavior when faced with a sexually receptive female. Interestingly, these males displayed both sexual behavior patterns spontaneously, i.e., in absence of exogenous steroid hormone treatment. Most of these features correspond with those found in human male homosexuals; however, the "bisexual" behavior shown by the letrozole-treated rats may be related to a particular human population. All these data, taken together, permit to propose letrozole prenatal treatment as a suitable animal model to study human male homosexuality and reinforce the hypothesis that human sexual orientation is underlied by changes in the endocrine milieu during early development.

Artistic creativity and dementia.

PubMed

Miller, Zachary A; Miller, Bruce L

2013-01-01

Artistic ability and creativity are defining characteristics of human behavior. Behavioral neurology, as a specialty, believes that even the most complex behaviors can be modeled and understood as the summation of smaller cognitive functions. Literature from individuals with specific brain lesions has helped to map out these smaller regions of cognitive abilities. More recently, models based on neurodegenerative conditions, especially from the frontotemporal dementias, have allowed for greater nuanced investigations into the various functional anatomies necessary for artistic behavior and possibly the underlying networks that promote creativity. © 2013 Elsevier B.V. All rights reserved.

The insertion of human dynamics models in the flight control loops of V/STOL research aircraft. Appendix 2: The optimal control model of a pilot in V/STOL aircraft control loops

NASA Technical Reports Server (NTRS)

Zipf, Mark E.

1989-01-01

An overview is presented of research work focussed on the design and insertion of classical models of human pilot dynamics within the flight control loops of V/STOL aircraft. The pilots were designed and configured for use in integrated control system research and design. The models of human behavior that were considered are: McRuer-Krendel (a single variable transfer function model); and Optimal Control Model (a multi-variable approach based on optimal control and stochastic estimation theory). These models attempt to predict human control response characteristics when confronted with compensatory tracking and state regulation tasks. An overview, mathematical description, and discussion of predictive limitations of the pilot models is presented. Design strategies and closed loop insertion configurations are introduced and considered for various flight control scenarios. Models of aircraft dynamics (both transfer function and state space based) are developed and discussed for their use in pilot design and application. Pilot design and insertion are illustrated for various flight control objectives. Results of pilot insertion within the control loops of two V/STOL research aricraft (Sikorski Black Hawk UH-60A, McDonnell Douglas Harrier II AV-8B) are presented and compared against actual pilot flight data. Conclusions are reached on the ability of the pilot models to adequately predict human behavior when confronted with similar control objectives.

A Model for the Transfer of Perceptual-Motor Skill Learning in Human Behaviors

ERIC Educational Resources Information Center

Rosalie, Simon M.; Muller, Sean

2012-01-01

This paper presents a preliminary model that outlines the mechanisms underlying the transfer of perceptual-motor skill learning in sport and everyday tasks. Perceptual-motor behavior is motivated by performance demands and evolves over time to increase the probability of success through adaptation. Performance demands at the time of an event…

Collective learning dynamics in behavioral crowds. Comment on "Human behaviours in evacuation crowd dynamics: From modeling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Burini, D.

2016-09-01

A recent literature on crowd dynamics [9,10] has enlightened that the management of crisis situations needs models able to depict social behaviors and, in particular, the spread of emotional feelings such as stress by panic situation.

Explaining Entrepreneurial Behavior: Dispositional Personality Traits, Growth of Personal Entrepreneurial Resources, and Business Idea Generation

ERIC Educational Resources Information Center

Obschonka, Martin; Silbereisen, Rainer K.; Schmitt-Rodermund, Eva

2012-01-01

Applying a life-span approach of human development and using the example of science-based business idea generation, the authors used structural equation modeling to test a mediation model for predicting entrepreneurial behavior in a sample of German scientists (2 measurement occasions; Time 1, N = 488). It was found that recalled early…

Bridging the Gap between Physiology and Behavior: Evidence from the sSoTS Model of Human Visual Attention

ERIC Educational Resources Information Center

Mavritsaki, Eirini; Heinke, Dietmar; Allen, Harriet; Deco, Gustavo; Humphreys, Glyn W.

2011-01-01

We present the case for a role of biologically plausible neural network modeling in bridging the gap between physiology and behavior. We argue that spiking-level networks can allow "vertical" translation between physiological properties of neural systems and emergent "whole-system" performance--enabling psychological results to be simulated from…

Understanding cognition, choice, and behavior.

PubMed

Corcoran, K J

1995-09-01

Bandura (1995) suggests that a "crusade against the causal efficacy of human thought" exists. The present paper disputes that claim, suggesting that the quest which does exist involves an understanding of self-efficacy. Examined are Bandura's shifting definitions of self-efficacy, his misunderstandings of others' work, and implications of some of his attempts to defend the construct. In the remainder of the paper Rotter's Social Learning Theory is discussed as a model of human choice behavior which recognizes the contributions of both cognitive and behavioral traditions within psychology, and has proven to be of great heuristic value.

Early stress and human behavioral development: emerging evolutionary perspectives.

PubMed

Del Giudice, M

2014-08-01

Stress experienced early in life exerts a powerful, lasting influence on development. Converging empirical findings show that stressful experiences become deeply embedded in the child's neurobiology, with an astonishing range of long-term effects on cognition, emotion, and behavior. In contrast with the prevailing view that such effects are the maladaptive outcomes of 'toxic' stress, adaptive models regard them as manifestations of evolved developmental plasticity. In this paper, I offer a brief introduction to adaptive models of early stress and human behavioral development, with emphasis on recent theoretical contributions and emerging concepts in the field. I begin by contrasting dysregulation models of early stress with their adaptive counterparts; I then introduce life history theory as a unifying framework, and review recent work on predictive adaptive responses (PARs) in human life history development. In particular, I discuss the distinction between forecasting the future state of the environment (external prediction) and forecasting the future state of the organism (internal prediction). Next, I present the adaptive calibration model, an integrative model of individual differences in stress responsivity based on life history concepts. I conclude by examining how maternal-fetal conflict may shape the physiology of prenatal stress and its adaptive and maladaptive effects on postnatal development. In total, I aim to show how theoretical work from evolutionary biology is reshaping the way we think about the role of stress in human development, and provide researchers with an up-to-date conceptual map of this fascinating and rapidly evolving field.

Francis Bacon's behavioral psychology.

PubMed

MacDonald, Paul S

2007-01-01

Francis Bacon offers two accounts of the nature and function of the human mind: one is a medical-physical account of the composition and operation of spirits specific to human beings, the other is a behavioral account of the character and activities of individual persons. The medical-physical account is a run-of-the-mill version of the late Renaissance model of elemental constituents and humoral temperaments. The other, less well-known, behavioral account represents an unusual position in early modern philosophy. This theory espouses a form of behavioral psychology according to which (a) supposed mental properties are "hidden forms" best described in dispositional terms, (b) the true character of an individual can be discovered in his observable behavior, and (c) an "informed" understanding of these properties permits the prediction and control of human behavior. Both of Bacon's theories of human nature fall under his general notion of systematic science: his medical-physical theory of vital spirits is theoretical natural philosophy and his behavioral theory of disposition and expression is operative natural philosophy. Because natural philosophy as a whole is "the inquiry of causes and the production of effects," knowledge of human nature falls under the same two-part definition. It is an inquisition of forms that pertains to the patterns of minute motions in the vital spirits and the production of effects that pertains both to the way these hidden motions produce behavioral effects and to the way in which a skillful agent is able to produce desired effects in other persons' behavior. (c) 2007 Wiley Periodicals, Inc.

A question driven socio-hydrological modeling process

NASA Astrophysics Data System (ADS)

Garcia, M.; Portney, K.; Islam, S.

2016-01-01

Human and hydrological systems are coupled: human activity impacts the hydrological cycle and hydrological conditions can, but do not always, trigger changes in human systems. Traditional modeling approaches with no feedback between hydrological and human systems typically cannot offer insight into how different patterns of natural variability or human-induced changes may propagate through this coupled system. Modeling of coupled human-hydrological systems, also called socio-hydrological systems, recognizes the potential for humans to transform hydrological systems and for hydrological conditions to influence human behavior. However, this coupling introduces new challenges and existing literature does not offer clear guidance regarding model conceptualization. There are no universally accepted laws of human behavior as there are for the physical systems; furthermore, a shared understanding of important processes within the field is often used to develop hydrological models, but there is no such consensus on the relevant processes in socio-hydrological systems. Here we present a question driven process to address these challenges. Such an approach allows modeling structure, scope and detail to remain contingent on and adaptive to the question context. We demonstrate the utility of this process by revisiting a classic question in water resources engineering on reservoir operation rules: what is the impact of reservoir operation policy on the reliability of water supply for a growing city? Our example model couples hydrological and human systems by linking the rate of demand decreases to the past reliability to compare standard operating policy (SOP) with hedging policy (HP). The model shows that reservoir storage acts both as a buffer for variability and as a delay triggering oscillations around a sustainable level of demand. HP reduces the threshold for action thereby decreasing the delay and the oscillation effect. As a result, per capita demand decreases during periods of water stress are more frequent but less drastic and the additive effect of small adjustments decreases the tendency of the system to overshoot available supplies. This distinction between the two policies was not apparent using a traditional noncoupled model.

Unraveling dynamics of human physical activity patterns in chronic pain conditions

NASA Astrophysics Data System (ADS)

Paraschiv-Ionescu, Anisoara; Buchser, Eric; Aminian, Kamiar

2013-06-01

Chronic pain is a complex disabling experience that negatively affects the cognitive, affective and physical functions as well as behavior. Although the interaction between chronic pain and physical functioning is a well-accepted paradigm in clinical research, the understanding of how pain affects individuals' daily life behavior remains a challenging task. Here we develop a methodological framework allowing to objectively document disruptive pain related interferences on real-life physical activity. The results reveal that meaningful information is contained in the temporal dynamics of activity patterns and an analytical model based on the theory of bivariate point processes can be used to describe physical activity behavior. The model parameters capture the dynamic interdependence between periods and events and determine a `signature' of activity pattern. The study is likely to contribute to the clinical understanding of complex pain/disease-related behaviors and establish a unified mathematical framework to quantify the complex dynamics of various human activities.

Human Papillomavirus Vaccination at a Time of Changing Sexual Behavior

PubMed Central

Lazzarato, Fulvio; Brisson, Marc; Franceschi, Silvia

2016-01-01

Human papillomavirus (HPV) prevalence varies widely worldwide. We used a transmission model to show links between age-specific sexual patterns and HPV vaccination effectiveness. We considered rural India and the United States as examples of 2 heterosexual populations with traditional age-specific sexual behavior and gender-similar age-specific sexual behavior, respectively. We simulated these populations by using age-specific rates of sexual activity and age differences between sexual partners and found that transitions from traditional to gender-similar sexual behavior in women <35 years of age can result in increased (2.6-fold in our study) HPV16 prevalence. Our model shows that reductions in HPV16 prevalence are larger if vaccination occurs in populations before transitions in sexual behavior and that increased risk for HPV infection attributable to transition is preventable by early vaccination. Our study highlights the importance of using time-limited opportunities to introduce HPV vaccination in traditional populations before changes in age-specific sexual patterns occur. PMID:26691673

SlgA, encoded by the homolog of the human schizophrenia-associated gene PRODH, acts in clock neurons to regulate Drosophila aggression

PubMed Central

Zwarts, Liesbeth; Vulsteke, Veerle; Buhl, Edgar; Hodge, James J. L.

2017-01-01

ABSTRACT Mutations in the proline dehydrogenase gene PRODH are linked to behavioral alterations in schizophrenia and as part of DiGeorge and velo-cardio-facial syndromes, but the role of PRODH in their etiology remains unclear. Here, we establish a Drosophila model to study the role of PRODH in behavioral disorders. We determine the distribution of the Drosophila PRODH homolog slgA in the brain and show that knockdown and overexpression of human PRODH and slgA in the lateral neurons ventral (LNv) lead to altered aggressive behavior. SlgA acts in an isoform-specific manner and is regulated by casein kinase II (CkII). Our data suggest that these effects are, at least partially, due to effects on mitochondrial function. We thus show that precise regulation of proline metabolism is essential to drive normal behavior and we identify Drosophila aggression as a model behavior relevant for the study of the mechanisms that are impaired in neuropsychiatric disorders. PMID:28331058

Human Papillomavirus Vaccination at a Time of Changing Sexual Behavior.

PubMed

Baussano, Iacopo; Lazzarato, Fulvio; Brisson, Marc; Franceschi, Silvia

2016-01-01

Human papillomavirus (HPV) prevalence varies widely worldwide. We used a transmission model to show links between age-specific sexual patterns and HPV vaccination effectiveness. We considered rural India and the United States as examples of 2 heterosexual populations with traditional age-specific sexual behavior and gender-similar age-specific sexual behavior, respectively. We simulated these populations by using age-specific rates of sexual activity and age differences between sexual partners and found that transitions from traditional to gender-similar sexual behavior in women <35 years of age can result in increased (2.6-fold in our study) HPV16 prevalence. Our model shows that reductions in HPV16 prevalence are larger if vaccination occurs in populations before transitions in sexual behavior and that increased risk for HPV infection attributable to transition is preventable by early vaccination. Our study highlights the importance of using time-limited opportunities to introduce HPV vaccination in traditional populations before changes in age-specific sexual patterns occur.

A Bibliography of Research on the Influence of Irrelevant Information on Psychological Judgments

DTIC Science & Technology

1981-09-01

Kansas State University " I 00 -.HUMAN FACTORS TECHNICAL AREA C.3)(iiA € U.S. Army LUResearch Institute for the Behavioral and Social Sciences... Behavioral September 1981 and Social Sciences, 5001 Eisenhower Avenue, 13. NUMBER OF PAGES Alexandria, VA 22333 10 14. MONITORING AGENCY NAME & ADDRESS(if...81. Anderson, N. H., & Grant, D. A. A test of a statisticil learning theory model for two-choice behavior models with double stimulus events. Journal

Modeling of US Human Papillomavirus (HPV) Seroprevalence by Age and Sexual Behavior Indicates an Increasing Trend of HPV Infection Following the Sexual Revolution.

PubMed

Ryser, Marc D; Rositch, Anne; Gravitt, Patti E

2017-09-01

The United States has experienced an increase in the incidence of human papillomavirus (HPV)-related cancers that are not screen-detectable. It has been hypothesized, but not directly demonstrated, that this is due to increasing HPV prevalence in the unvaccinated population. Female self-reported numbers of lifetime sex partners and HPV serology from the National Health and Nutrition Examination Survey (NHANES) were used to develop mathematical models of sexual partner acquisition and antibody dynamics. Modeled trends in sexual behaviors were compared to incidence data for cervical adenocarcinoma, oropharyngeal cancer, and anal cancer. The age-specific HPV seroprevalence data were best explained by a partner acquisition model that explicitly accounted for cohort-dependent changes in sexual behavior. Estimates of the mean time to loss of natural antibodies varied by model, ranging from 49 to 145 years. Inferred trends in sexual behavior over the past decades paralleled the increasing incidence of HPV-related cancers in the United States. The findings suggest that lower HPV seroprevalence in older US women primarily reflects cohort-specific differences in sexual behaviors, and is only marginally attributable to immune waning with age. Our results emphasize the importance of continuing surveillance of sexual behaviors, alongside vaccine status, to predict future disease burden. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Using Apex To Construct CPM-GOMS Models

NASA Technical Reports Server (NTRS)

John, Bonnie; Vera, Alonso; Matessa, Michael; Freed, Michael; Remington, Roger

2006-01-01

process for automatically generating computational models of human/computer interactions as well as graphical and textual representations of the models has been built on the conceptual foundation of a method known in the art as CPM-GOMS. This method is so named because it combines (1) the task decomposition of analysis according to an underlying method known in the art as the goals, operators, methods, and selection (GOMS) method with (2) a model of human resource usage at the level of cognitive, perceptual, and motor (CPM) operations. CPM-GOMS models have made accurate predictions about behaviors of skilled computer users in routine tasks, but heretofore, such models have been generated in a tedious, error-prone manual process. In the present process, CPM-GOMS models are generated automatically from a hierarchical task decomposition expressed by use of a computer program, known as Apex, designed previously to be used to model human behavior in complex, dynamic tasks. An inherent capability of Apex for scheduling of resources automates the difficult task of interleaving the cognitive, perceptual, and motor resources that underlie common task operators (e.g., move and click mouse). The user interface of Apex automatically generates Program Evaluation Review Technique (PERT) charts, which enable modelers to visualize the complex parallel behavior represented by a model. Because interleaving and the generation of displays to aid visualization are automated, it is now feasible to construct arbitrarily long sequences of behaviors. The process was tested by using Apex to create a CPM-GOMS model of a relatively simple human/computer-interaction task and comparing the time predictions of the model and measurements of the times taken by human users in performing the various steps of the task. The task was to withdraw $80 in cash from an automated teller machine (ATM). For the test, a Visual Basic mockup of an ATM was created, with a provision for input from (and measurement of the performance of) the user via a mouse. The times predicted by the automatically generated model turned out to approximate the measured times fairly well (see figure). While these results are promising, there is need for further development of the process. Moreover, it will also be necessary to test other, more complex models: The actions required of the user in the ATM task are too sequential to involve substantial parallelism and interleaving and, hence, do not serve as an adequate test of the unique strength of CPM-GOMS models to accommodate parallelism and interleaving.

A Physiologically-Based Description of the Inhalation Pharmacokinetics of Styrene in Rats and Humans

DTIC Science & Technology

1983-01-01

model for rat were scaled to give a description of human kinetics and the predictions agreed closely with available data from the literature (Fig. 4...for predicting human kinetics from a data base in other mammalian species. The ability to anticipate kinetic behavior in humans could very much improve

Four factors underlying mouse behavior in an open field

PubMed Central

Tanaka, Shoji; Young, Jared W.; Halberstadt, Adam L.; Masten, Virginia L.; Geyer, Mark A.

2012-01-01

The observation of the locomotor and exploratory behaviors of rodents in an open field is one of the most fundamental methods used in the field of behavioral pharmacology. A variety of behaviors can be recorded automatically and can readily generate a multivariate pattern of pharmacological effects. Nevertheless, the optimal ways to characterize observed behaviors and concomitant drug effects are still under development. The aim of this study was to extract meaningful behavioral factors that could explain variations in the observed variables from mouse exploration. Behavioral data were recorded from male C57BL/6J mice (n = 268) using the Behavioral Pattern Monitor (BPM). The BPM data were subjected to the exploratory factor analysis. The factor analysis extracted four factors: activity, sequential organization, diversive exploration, and inspective exploration. The activity factor and the two types of exploration factors correlated positively with one another, while the sequential organization factor negatively correlated with the remaining factors. The extracted factor structure constitutes a behavioral model of mouse exploration. This model will provide a platform on which one can assess the effects of psychoactive drugs and genetic manipulations on mouse exploratory behavior. Further studies are currently underway to examine the factor structure of similar multivariate data sets from humans tested in a human BPM. PMID:22569582

Four factors underlying mouse behavior in an open field.

PubMed

Tanaka, Shoji; Young, Jared W; Halberstadt, Adam L; Masten, Virginia L; Geyer, Mark A

2012-07-15

The observation of the locomotor and exploratory behaviors of rodents in an open field is one of the most fundamental methods used in the field of behavioral pharmacology. A variety of behaviors can be recorded automatically and can readily generate a multivariate pattern of pharmacological effects. Nevertheless, the optimal ways to characterize observed behaviors and concomitant drug effects are still under development. The aim of this study was to extract meaningful behavioral factors that could explain variations in the observed variables from mouse exploration. Behavioral data were recorded from male C57BL/6J mice (n=268) using the Behavioral Pattern Monitor (BPM). The BPM data were subjected to the exploratory factor analysis. The factor analysis extracted four factors: activity, sequential organization, diversive exploration, and inspective exploration. The activity factor and the two types of exploration factors correlated positively with one another, while the sequential organization factor negatively correlated with the remaining factors. The extracted factor structure constitutes a behavioral model of mouse exploration. This model will provide a platform on which one can assess the effects of psychoactive drugs and genetic manipulations on mouse exploratory behavior. Further studies are currently underway to examine the factor structure of similar multivariate data sets from humans tested in a human BPM. Copyright © 2012 Elsevier B.V. All rights reserved.

BEYOND THE PALEOLITHIC PRESCRIPTION: INCORPORATING DIVERSITY AND FLEXIBILITY IN THE STUDY OF HUMAN DIET EVOLUTION

PubMed Central

Turner, Bethany L.; Thompson, Amanda L.

2014-01-01

Evolutionary paradigms of human health and nutrition center on the evolutionary discordance or “mismatch” model whereby human bodies, reflecting adaptations established in the Paleolithic era, are ill-suited to modern industrialized diets resulting in rapidly increasing rates of chronic metabolic disease. Whereas this model remains useful, we argue that its utility in explaining the evolution of human dietary tendencies is limited. The assumption that human diets are mismatched to our evolved biology implies that they are instinctual or genetically determined and rooted in the Paleolithic. We review current research indicating that human eating habits are primarily learned through behavioral, social and physiological mechanisms starting in utero and extending throughout the life course. Those adaptations that appear to be strongly genetic likely reflect Neolithic, rather than Paleolithic, adaptations and are significantly influenced by human niche-constructing behavior. Incorporating a broader understanding of the evolved mechanisms by which humans learn and imprint eating habits and the reciprocal effects of those habits on physiology would provide useful tools for structuring more lasting nutrition interventions. PMID:23865796

The curse of planning: dissecting multiple reinforcement-learning systems by taxing the central executive.

PubMed

Otto, A Ross; Gershman, Samuel J; Markman, Arthur B; Daw, Nathaniel D

2013-05-01

A number of accounts of human and animal behavior posit the operation of parallel and competing valuation systems in the control of choice behavior. In these accounts, a flexible but computationally expensive model-based reinforcement-learning system has been contrasted with a less flexible but more efficient model-free reinforcement-learning system. The factors governing which system controls behavior-and under what circumstances-are still unclear. Following the hypothesis that model-based reinforcement learning requires cognitive resources, we demonstrated that having human decision makers perform a demanding secondary task engenders increased reliance on a model-free reinforcement-learning strategy. Further, we showed that, across trials, people negotiate the trade-off between the two systems dynamically as a function of concurrent executive-function demands, and people's choice latencies reflect the computational expenses of the strategy they employ. These results demonstrate that competition between multiple learning systems can be controlled on a trial-by-trial basis by modulating the availability of cognitive resources.

The Evolution of a Connectionist Model of Situated Human Language Understanding

NASA Astrophysics Data System (ADS)

Mayberry, Marshall R.; Crocker, Matthew W.

The Adaptive Mechanisms in Human Language Processing (ALPHA) project features both experimental and computational tracks designed to complement each other in the investigation of the cognitive mechanisms that underlie situated human utterance processing. The models developed in the computational track replicate results obtained in the experimental track and, in turn, suggest further experiments by virtue of behavior that arises as a by-product of their operation.

Technical Advance: Live-imaging analysis of human dendritic cell migrating behavior under the influence of immune-stimulating reagents in an organotypic model of lung

PubMed Central

Nguyen Hoang, Anh Thu; Chen, Puran; Björnfot, Sofia; Högstrand, Kari; Lock, John G.; Grandien, Alf; Coles, Mark; Svensson, Mattias

2014-01-01

This manuscript describes technical advances allowing manipulation and quantitative analyses of human DC migratory behavior in lung epithelial tissue. DCs are hematopoietic cells essential for the maintenance of tissue homeostasis and the induction of tissue-specific immune responses. Important functions include cytokine production and migration in response to infection for the induction of proper immune responses. To design appropriate strategies to exploit human DC functional properties in lung tissue for the purpose of clinical evaluation, e.g., candidate vaccination and immunotherapy strategies, we have developed a live-imaging assay based on our previously described organotypic model of the human lung. This assay allows provocations and subsequent quantitative investigations of DC functional properties under conditions mimicking morphological and functional features of the in vivo parental tissue. We present protocols to set up and prepare tissue models for 4D (x, y, z, time) fluorescence-imaging analysis that allow spatial and temporal studies of human DCs in live epithelial tissue, followed by flow cytometry analysis of DCs retrieved from digested tissue models. This model system can be useful for elucidating incompletely defined pathways controlling DC functional responses to infection and inflammation in lung epithelial tissue, as well as the efficacy of locally administered candidate interventions. PMID:24899587

Commentary on: Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. Can the emerging domain of behavioral addictions bring a new reflection for the field of addictions, by stressing the issue of the context of addiction development?

PubMed

de Timary, Philippe; Philippot, Pierre

2015-09-01

This paper is a commentary to the article entitled: "Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research", by Billieux, Schimmenti, Khazaal, Maurage and Heeren (2015). In this manuscript, we commented on two aspects developed by the authors. Billieux et al. (2015) propose that the recent development of propositions of behavioral addiction is driven by an unwise application of an addiction model to excessive behaviors and rests on a confirmatory research strategy that does not question the psychological processes underlying the development of the conduct. They also show that applying a process driven strategy leads to a more appropriate description of the reality of the behavior and conduct, in particular by describing a variety of motivations for the excessive behavior, which is central to understanding the nature of the conduct. We believe that this new approach, which is fruitful to the emerging domain of behavioral addictions, could also apply to the domain of addictions in general. The latter is characterized by the application of a generic biological model, largely influenced by animal models, focusing on neurophysiological determinants of addiction. This approach may have decreased the attention paid to dimensions of addictions that are more specifically human. We will firstly briefly argue on the limitation of this neurophysiological addiction model for the field of excessive behavioral conducts. Secondly, we will argue for an approach centered on the differentiation of motivations and on the adaptive dimension of the behavior when it first developed and on the evocation of a transition where the conduct became independent of its original function. The emerging domain of behavioral addictions, where no animal model has been developed so far, may bring a new reflection that may apply to the domain of addictions in general, with a specific attention to human questions.

Modeling detour behavior of pedestrian dynamics under different conditions

NASA Astrophysics Data System (ADS)

Qu, Yunchao; Xiao, Yao; Wu, Jianjun; Tang, Tao; Gao, Ziyou

2018-02-01

Pedestrian simulation approach has been widely used to reveal the human behavior and evaluate the performance of crowd evacuation. In the existing pedestrian simulation models, the social force model is capable of predicting many collective phenomena. Detour behavior occurs in many cases, and the important behavior is a dominate factor of the crowd evacuation efficiency. However, limited attention has been attracted for analyzing and modeling the characteristics of detour behavior. In this paper, a modified social force model integrated by Voronoi diagram is proposed to calculate the detour direction and preferred velocity. Besides, with the consideration of locations and velocities of neighbor pedestrians, a Logit-based choice model is built to describe the detour direction choice. The proposed model is applied to analyze pedestrian dynamics in a corridor scenario with either unidirectional or bidirectional flow, and a building scenario in real-world. Simulation results show that the modified social force model including detour behavior could reduce the frequency of collision and deadlock, increase the average speed of the crowd, and predict more practical crowd dynamics with detour behavior. This model can also be potentially applied to understand the pedestrian dynamics and design emergent management strategies for crowd evacuations.

Amphetamine increases activity but not exploration in humans and mice

PubMed Central

Minassian, Arpi; Young, Jared W.; Cope, Zackary A.; Henry, Brook L.; Geyer, Mark A.; Perry, William

2015-01-01

Rationale Cross-species quantification of physiological behavior enables a better understanding of the biological systems underlying neuropsychiatric diseases such as Bipolar Disorder (BD). Cardinal symptoms of manic BD include increased motor activity and goal-directed behavior, thought to be related to increased catecholamine activity, potentially selective to dopamine homeostatic dysregulation. Objectives The objective of this study was to test whether acute administration of amphetamine, a norepinephrine/dopamine transporter inhibitor and dopamine releaser, would replicate the profile of activity and exploration observed in both humans with manic BD and mouse models of mania. Methods Healthy volunteers with no psychiatric history were randomized to a one-time dose of placebo (n=25), 10 mg d-amphetamine (n=18), or 20 mg amphetamine (n=23). 80 mice were administered one of 4 doses of d-amphetamine or vehicle. Humans and mice were tested in the Behavioral Pattern Monitor (BPM), which quantifies motor activity, exploratory behavior, and spatial patterns of behavior. Results In humans, the 20-mg dose of amphetamine increased motor activity as measured by acceleration without marked effects on exploration or spatial patterns of activity. In mice, amphetamine increased activity, decreased specific exploration, and caused straighter, one-dimensional movements in a dose-dependent manner. Conclusions Consistent with mice, amphetamine increased motoric activity in humans without increasing exploration. Given that BD patients exhibit heightened exploration, these data further emphasize the limitation of amphetamine-induced hyperactivity as a suitable model for BD. Further, these studies highlight the utility of cross-species physiological paradigms in validating biological mechanisms of psychiatric diseases. PMID:26449721

Animal models of human anxiety disorders: reappraisal from a developmental psychopathology vantage point.

PubMed

Lampis, Valentina; Maziade, Michel; Battaglia, Marco

2011-05-01

We are witnessing a tremendous expansion of strategies and techniques that derive from basic and preclinical science to study the fine genetic, epigenetic, and proteomic regulation of behavior in the laboratory animal. In this endeavor, animal models of psychiatric illness are becoming the almost exclusive domain of basic researchers, with lesser involvement of clinician researchers in their conceptual design, and transfer into practice of new paradigms. From the side of human behavioral research, the growing interest in gene-environment interplay and the fostering of valid endophenotypes are among the few substantial innovations in the effort of linking common mental disorders to cutting-edge clinical research questions. We argue that it is time for cross-fertilization between these camps. In this article, we a) observe that the "translational divide" can-and should-be crossed by having investigators from both the basic and the clinical sides cowork on simpler, valid "endophenotypes" of neurodevelopmental relevance; b) emphasize the importance of unambiguous physiological readouts, more than behavioral equivalents of human symptoms/syndromes, for animal research; c) indicate and discuss how this could be fostered and implemented in a developmental framework of reference for some common anxiety disorders and ultimately lead to better animal models of human mental disorders.

Punctuated equilibrium dynamics in human communications

NASA Astrophysics Data System (ADS)

Peng, Dan; Han, Xiao-Pu; Wei, Zong-Wen; Wang, Bing-Hong

2015-10-01

A minimal model based on network incorporating individual interactions is proposed to study the non-Poisson statistical properties of human behavior: individuals in system interact with their neighbors, the probability of an individual acting correlates to its activity, and all the individuals involved in action will change their activities randomly. The model reproduces varieties of spatial-temporal patterns observed in empirical studies of human daily communications, providing insight into various human activities and embracing a range of realistic social interacting systems, particularly, intriguing bimodal phenomenon. This model bridges priority queueing theory and punctuated equilibrium dynamics, and our modeling and analysis is likely to shed light on non-Poisson phenomena in many complex systems.

A Computational Model of Human Table Tennis for Robot Application

NASA Astrophysics Data System (ADS)

Mülling, Katharina; Peters, Jan

Table tennis is a difficult motor skill which requires all basic components of a general motor skill learning system. In order to get a step closer to such a generic approach to the automatic acquisition and refinement of table tennis, we study table tennis from a human motor control point of view. We make use of the basic models of discrete human movement phases, virtual hitting points, and the operational timing hypothesis. Using these components, we create a computational model which is aimed at reproducing human-like behavior. We verify the functionality of this model in a physically realistic simulation of a Barrett WAM.

Tandem internal models execute motor learning in the cerebellum.

PubMed

Honda, Takeru; Nagao, Soichi; Hashimoto, Yuji; Ishikawa, Kinya; Yokota, Takanori; Mizusawa, Hidehiro; Ito, Masao

2018-06-25

In performing skillful movement, humans use predictions from internal models formed by repetition learning. However, the computational organization of internal models in the brain remains unknown. Here, we demonstrate that a computational architecture employing a tandem configuration of forward and inverse internal models enables efficient motor learning in the cerebellum. The model predicted learning adaptations observed in hand-reaching experiments in humans wearing a prism lens and explained the kinetic components of these behavioral adaptations. The tandem system also predicted a form of subliminal motor learning that was experimentally validated after training intentional misses of hand targets. Patients with cerebellar degeneration disease showed behavioral impairments consistent with tandemly arranged internal models. These findings validate computational tandemization of internal models in motor control and its potential uses in more complex forms of learning and cognition. Copyright © 2018 the Author(s). Published by PNAS.

Modeling Interdependent and Periodic Real-World Action Sequences

PubMed Central

Kurashima, Takeshi; Althoff, Tim; Leskovec, Jure

2018-01-01

Mobile health applications, including those that track activities such as exercise, sleep, and diet, are becoming widely used. Accurately predicting human actions in the real world is essential for targeted recommendations that could improve our health and for personalization of these applications. However, making such predictions is extremely difficult due to the complexities of human behavior, which consists of a large number of potential actions that vary over time, depend on each other, and are periodic. Previous work has not jointly modeled these dynamics and has largely focused on item consumption patterns instead of broader types of behaviors such as eating, commuting or exercising. In this work, we develop a novel statistical model, called TIPAS, for Time-varying, Interdependent, and Periodic Action Sequences. Our approach is based on personalized, multivariate temporal point processes that model time-varying action propensities through a mixture of Gaussian intensities. Our model captures short-term and long-term periodic interdependencies between actions through Hawkes process-based self-excitations. We evaluate our approach on two activity logging datasets comprising 12 million real-world actions (e.g., eating, sleep, and exercise) taken by 20 thousand users over 17 months. We demonstrate that our approach allows us to make successful predictions of future user actions and their timing. Specifically, TIPAS improves predictions of actions, and their timing, over existing methods across multiple datasets by up to 156%, and up to 37%, respectively. Performance improvements are particularly large for relatively rare and periodic actions such as walking and biking, improving over baselines by up to 256%. This demonstrates that explicit modeling of dependencies and periodicities in real-world behavior enables successful predictions of future actions, with implications for modeling human behavior, app personalization, and targeting of health interventions. PMID:29780977

Information-Seeking Behavior in the Digital Age: A Multidisciplinary Study of Academic Researchers

ERIC Educational Resources Information Center

Ge, Xuemei

2010-01-01

This article focuses on how electronic information resources influence the information-seeking process in the social sciences and humanities. It examines the information-seeking behavior of scholars in these fields, and extends the David Ellis model of information-seeking behavior for social scientists, which includes six characteristics:…

Selection of behavioral tasks and development of software for evaluation of Rhesus Monkey behavior during spaceflight

NASA Technical Reports Server (NTRS)

Rumbaugh, Duane M.; Washburn, David A.; Richardson, W. K.

1995-01-01

The results of several experiments were disseminated during this semiannual period. This publication and each of these presented papers represent investigations of the continuity in psychological processes between monkeys and humans. Thus, each serves to support the animal model of behavior and performance research.

How Animal Models Inform Child and Adolescent Psychiatry

PubMed Central

Stevens, Hanna E.; Vaccarino, Flora M.

2015-01-01

Objective Every available approach should be utilized to advance the field of child and adolescent psychiatry. Biological systems are important for the behavioral problems of children. Close examination of non-human animals and the biology and behavior they share with humans is an approach that must be used to advance the clinical work of child psychiatry. Method We review here how model systems are used to contribute to significant insights into childhood psychiatric disorders. Model systems have not only demonstrated causality of risk factors for psychiatric pathophysiology but have also allowed child psychiatrists to think in different ways about risks for psychiatric disorders and multiple levels that might be the basis of recovery and prevention. Results We present examples of how animal systems are utilized to benefit child psychiatry, including through environmental, genetic, and acute biological manipulations. Animal model work has been essential in our current thinking about childhood disorders, including the importance of dose and timing of risk factors, specific features of risk factors that are significant, neurochemistry involved in brain functioning, molecular components of brain development, and the importance of cellular processes previously neglected in psychiatric theories. Conclusion Animal models have clear advantages and disadvantages that must both be considered for these systems to be useful. Coupled with increasingly sophisticated methods for investigating human behavior and biology, animal model systems will continue to make essential contributions to our field. PMID:25901771

Human performance cognitive-behavioral modeling: a benefit for occupational safety.

PubMed

Gore, Brian F

2002-01-01

Human Performance Modeling (HPM) is a computer-aided job analysis software methodology used to generate predictions of complex human-automation integration and system flow patterns with the goal of improving operator and system safety. The use of HPM tools has recently been increasing due to reductions in computational cost, augmentations in the tools' fidelity, and usefulness in the generated output. An examination of an Air Man-machine Integration Design and Analysis System (Air MIDAS) model evaluating complex human-automation integration currently underway at NASA Ames Research Center will highlight the importance to occupational safety of considering both cognitive and physical aspects of performance when researching human error.

Human performance cognitive-behavioral modeling: a benefit for occupational safety

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2002-01-01

Human Performance Modeling (HPM) is a computer-aided job analysis software methodology used to generate predictions of complex human-automation integration and system flow patterns with the goal of improving operator and system safety. The use of HPM tools has recently been increasing due to reductions in computational cost, augmentations in the tools' fidelity, and usefulness in the generated output. An examination of an Air Man-machine Integration Design and Analysis System (Air MIDAS) model evaluating complex human-automation integration currently underway at NASA Ames Research Center will highlight the importance to occupational safety of considering both cognitive and physical aspects of performance when researching human error.

Effect of human movement on airborne disease transmission in an airplane cabin: study using numerical modeling and quantitative risk analysis.

PubMed

Han, Zhuyang; To, Gin Nam Sze; Fu, Sau Chung; Chao, Christopher Yu-Hang; Weng, Wenguo; Huang, Quanyi

2014-08-06

Airborne transmission of respiratory infectious disease in indoor environment (e.g. airplane cabin, conference room, hospital, isolated room and inpatient ward) may cause outbreaks of infectious diseases, which may lead to many infection cases and significantly influences on the public health. This issue has received more and more attentions from academics. This work investigates the influence of human movement on the airborne transmission of respiratory infectious diseases in an airplane cabin by using an accurate human model in numerical simulation and comparing the influences of different human movement behaviors on disease transmission. The Eulerian-Lagrangian approach is adopted to simulate the dispersion and deposition of the expiratory aerosols. The dose-response model is used to assess the infection risks of the occupants. The likelihood analysis is performed as a hypothesis test on the input parameters and different human movement pattern assumptions. An in-flight SARS outbreak case is used for investigation. A moving person with different moving speeds is simulated to represent the movement behaviors. A digital human model was used to represent the detailed profile of the occupants, which was obtained by scanning a real thermal manikin using the 3D laser scanning system. The analysis results indicate that human movement can strengthen the downward transport of the aerosols, significantly reduce the overall deposition and removal rate of the suspended aerosols and increase the average infection risk in the cabin. The likelihood estimation result shows that the risk assessment results better fit the outcome of the outbreak case when the movements of the seated passengers are considered. The intake fraction of the moving person is significantly higher than most of the seated passengers. The infection risk distribution in the airplane cabin highly depends on the movement behaviors of the passengers and the index patient. The walking activities of the crew members and the seated passengers can significantly increase their personal infection risks. Taking the influence of the movement of the seated passengers and the index patient into consideration is necessary and important. For future studies, investigations on the behaviors characteristics of the passengers during flight will be useful and helpful for infection control.

Toward experimental validation of a model for human sensorimotor learning and control in teleoperation

NASA Astrophysics Data System (ADS)

Roth, Eatai; Howell, Darrin; Beckwith, Cydney; Burden, Samuel A.

2017-05-01

Humans, interacting with cyber-physical systems (CPS), formulate beliefs about the system's dynamics. It is natural to expect that human operators, tasked with teleoperation, use these beliefs to control the remote robot. For tracking tasks in the resulting human-cyber-physical system (HCPS), theory suggests that human operators can achieve exponential tracking (in stable systems) without state estimation provided they possess an accurate model of the system's dynamics. This internalized inverse model, however, renders a portion of the system state unobservable to the human operator—the zero dynamics. Prior work shows humans can track through observable linear dynamics, thus we focus on nonlinear dynamics rendered unobservable through tracking control. We propose experiments to assess the human operator's ability to learn and invert such models, and distinguish this behavior from that achieved by pure feedback control.

Stereotypic behavior in nonhuman primates as a model for the human condition.

PubMed

Lutz, Corrine K

2014-01-01

Stereotypies that develop spontaneously in nonhuman primates can provide an effective model for repetitive stereotyped behavior in people with neurodevelopmental or obsessive-compulsive disorders. The behaviors are similar in form, are similarly affected by environmental conditions, and are improved with similar treatment methods such as enrichment, training, and drug therapy. However, because of a greater number of commonalities in these factors, nonhuman primates may serve as a better model for stereotyped behavior in individuals with autism or intellectual disability than for compulsions in individuals with obsessive-compulsive disorder. Because animal models may not be exact in all features of the disorder being studied, it is important to investigate the strengths and weaknesses of using a nonhuman primate model for stereotyped behavior in people with psychological disorders. © The Author 2014. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A simple generative model of collective online behavior.

PubMed

Gleeson, James P; Cellai, Davide; Onnela, Jukka-Pekka; Porter, Mason A; Reed-Tsochas, Felix

2014-07-22

Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviors to population-level outcomes. In this paper, we introduce a simple generative model for the collective behavior of millions of social networking site users who are deciding between different software applications. Our model incorporates two distinct mechanisms: one is associated with recent decisions of users, and the other reflects the cumulative popularity of each application. Importantly, although various combinations of the two mechanisms yield long-time behavior that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent popularity of applications over their cumulative popularity. This demonstrates--even when using purely observational data without experimental design--that temporal data-driven modeling can effectively distinguish between competing microscopic mechanisms, allowing us to uncover previously unidentified aspects of collective online behavior.

A simple generative model of collective online behavior

PubMed Central

Gleeson, James P.; Cellai, Davide; Onnela, Jukka-Pekka; Porter, Mason A.; Reed-Tsochas, Felix

2014-01-01

Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviors to population-level outcomes. In this paper, we introduce a simple generative model for the collective behavior of millions of social networking site users who are deciding between different software applications. Our model incorporates two distinct mechanisms: one is associated with recent decisions of users, and the other reflects the cumulative popularity of each application. Importantly, although various combinations of the two mechanisms yield long-time behavior that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent popularity of applications over their cumulative popularity. This demonstrates—even when using purely observational data without experimental design—that temporal data-driven modeling can effectively distinguish between competing microscopic mechanisms, allowing us to uncover previously unidentified aspects of collective online behavior. PMID:25002470

Animal behavior as a conceptual framework for the study of obsessive-compulsive disorder (OCD).

PubMed

Eilam, David; Zor, Rama; Fineberg, Naomi; Hermesh, Haggai

2012-06-01

Research on affective disorders may benefit from the methodology of studying animal behavior, in which tools are available for qualitatively and quantitatively measuring and assessing behavior with as much sophistication and attention to detail as in the analysis of the brain. To illustrate this, we first briefly review the characteristics of obsessive-compulsive disorder (OCD), and then demonstrate how the quinpirole rat model is used as a conceptual model in studying human OCD patients. Like the rat model, the study of OCD in humans is based on video-telemetry, whereby observable, measurable, and relatively objective characteristics of OCD behavior may be extracted. In this process, OCD rituals are defined in terms of the space in which they are executed and the movements (acts) that are performed at each location or object in this space. Accordingly, OCD behavior is conceived of as comprising three hierarchical components: (i) rituals (as defined by the patients); (ii) visits to objects/locations in the environment at which the patient stops during the ritual; and (iii) acts performed at each object/location during visits. Scoring these structural components (behavioral units) is conveniently possible with readily available tools for behavioral description and analysis, providing quantitative and qualitative measures of the OCD hallmarks of repetition and addition, as well as the reduced functionality in OCD behavior. Altogether, the concept that was developed in the context of an animal model provides a useful tool that may facilitate OCD diagnosis, assessment and treatment, and may be similarly applied for other psychiatric disorders. Copyright © 2011 Elsevier B.V. All rights reserved.

An optimal state estimation model of sensory integration in human postural balance

NASA Astrophysics Data System (ADS)

Kuo, Arthur D.

2005-09-01

We propose a model for human postural balance, combining state feedback control with optimal state estimation. State estimation uses an internal model of body and sensor dynamics to process sensor information and determine body orientation. Three sensory modalities are modeled: joint proprioception, vestibular organs in the inner ear, and vision. These are mated with a two degree-of-freedom model of body dynamics in the sagittal plane. Linear quadratic optimal control is used to design state feedback and estimation gains. Nine free parameters define the control objective and the signal-to-noise ratios of the sensors. The model predicts statistical properties of human sway in terms of covariance of ankle and hip motion. These predictions are compared with normal human responses to alterations in sensory conditions. With a single parameter set, the model successfully reproduces the general nature of postural motion as a function of sensory environment. Parameter variations reveal that the model is highly robust under normal sensory conditions, but not when two or more sensors are inaccurate. This behavior is similar to that of normal human subjects. We propose that age-related sensory changes may be modeled with decreased signal-to-noise ratios, and compare the model's behavior with degraded sensors against experimental measurements from older adults. We also examine removal of the model's vestibular sense, which leads to instability similar to that observed in bilateral vestibular loss subjects. The model may be useful for predicting which sensors are most critical for balance, and how much they can deteriorate before posture becomes unstable.

Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1991-01-01

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.

The genesis and correction of unprofessional behavior in surgeons: The role of society, education and genetics.

PubMed

Talati, Jamsheer Jehangir

2016-05-01

Most surgeons are ethical. Increasingly, however, a variety of unprofessional behaviors are surfacing. Awareness of these behaviors and their causation is required to plan their eradication. To (i) identify the prevalent causes of unprofessional behaviors amongst surgeons; and (ii) suggest corrective interventions. Literature was searched and models constructed to interpret interrelationships between causes. Unprofessional behaviors extend beyond those frequently discussed, necessitating the term 'dysprofessionalism'. Causal influences arise from (i) an overpowering society; (ii) limited education and (iii) the underdeveloped state of human nature at birth. Societies corrupt by role-modeling avarice and encouraging industry-despite consequent pollution. Society brooks no interference. Surgeons are loath to oppose, resulting in an unprofessional silence. Surgical education based on best evidence is an indoctrination, with little opportunity to deploy alternatives. Evidence based guidelines increasingly risk errors, as publication fraud increases. Effective interaction with government/legislation is not taught. Human nature and our brain remain arrested in a stage of strongly stabilized evolutionary selection. Humans are born with larval brains requiring intense educational interventions. Genetic modification holds promise as it can circumvent birth in undeveloped states, and facilitate trans-generational transfer of knowledge. CRISPR/Cas-9 techniques make this possible, necessitating ethical discussion-an urgent issue. Reforming society would otherwise be an impossible task as behaviors cannot be taught in classrooms. Instances of dysprofessionalism are unlikely to diminish using current approaches. Discussion of the ethics of genetically modifying embryos is urgently needed, as this could provide a possible shortcut to positive changes in human behavior, but risks unwanted changes and misuse. Copyright © 2016 IJS Publishing Group Limited. Published by Elsevier Ltd. All rights reserved.

Modeling Pilot Behavior for Assessing Integrated Alert and Notification Systems on Flight Decks

NASA Technical Reports Server (NTRS)

Cover, Mathew; Schnell, Thomas

2010-01-01

Numerous new flight deck configurations for caution, warning, and alerts can be conceived; yet testing them with human-in-the-Ioop experiments to evaluate each one would not be practical. New sensors, instruments, and displays are being put into cockpits every day and this is particularly true as we enter the dawn of the Next Generation Air Transportation System (NextGen). By modeling pilot behavior in a computer simulation, an unlimited number of unique caution, warning, and alert configurations can be evaluated 24/7 by a computer. These computer simulations can then identify the most promising candidate formats to further evaluate in higher fidelity, but more costly, Human-in-the-Ioop (HITL) simulations. Evaluations using batch simulations with human performance models saves time, money, and enables a broader consideration of possible caution, warning, and alerting configurations for future flight decks.

LINEBACKER: LINE-speed Bio-inspired Analysis and Characterization for Event Recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oehmen, Christopher S.; Bruillard, Paul J.; Matzke, Brett D.

2016-08-04

The cyber world is a complex domain, with digital systems mediating a wide spectrum of human and machine behaviors. While this is enabling a revolution in the way humans interact with each other and data, it also is exposing previously unreachable infrastructure to a worldwide set of actors. Existing solutions for intrusion detection and prevention that are signature-focused typically seek to detect anomalous and/or malicious activity for the sake of preventing or mitigating negative impacts. But a growing interest in behavior-based detection is driving new forms of analysis that move the emphasis from static indicators (e.g. rule-based alarms or tripwires)more » to behavioral indicators that accommodate a wider contextual perspective. Similar to cyber systems, biosystems have always existed in resource-constrained hostile environments where behaviors are tuned by context. So we look to biosystems as an inspiration for addressing behavior-based cyber challenges. In this paper, we introduce LINEBACKER, a behavior-model based approach to recognizing anomalous events in network traffic and present the design of this approach of bio-inspired and statistical models working in tandem to produce individualized alerting for a collection of systems. Preliminary results of these models operating on historic data are presented along with a plugin to support real-world cyber operations.« less

Behavioral modeling of human choices reveals dissociable effects of physical effort and temporal delay on reward devaluation.

PubMed

Klein-Flügge, Miriam C; Kennerley, Steven W; Saraiva, Ana C; Penny, Will D; Bestmann, Sven

2015-03-01

There has been considerable interest from the fields of biology, economics, psychology, and ecology about how decision costs decrease the value of rewarding outcomes. For example, formal descriptions of how reward value changes with increasing temporal delays allow for quantifying individual decision preferences, as in animal species populating different habitats, or normal and clinical human populations. Strikingly, it remains largely unclear how humans evaluate rewards when these are tied to energetic costs, despite the surge of interest in the neural basis of effort-guided decision-making and the prevalence of disorders showing a diminished willingness to exert effort (e.g., depression). One common assumption is that effort discounts reward in a similar way to delay. Here we challenge this assumption by formally comparing competing hypotheses about effort and delay discounting. We used a design specifically optimized to compare discounting behavior for both effort and delay over a wide range of decision costs (Experiment 1). We then additionally characterized the profile of effort discounting free of model assumptions (Experiment 2). Contrary to previous reports, in both experiments effort costs devalued reward in a manner opposite to delay, with small devaluations for lower efforts, and progressively larger devaluations for higher effort-levels (concave shape). Bayesian model comparison confirmed that delay-choices were best predicted by a hyperbolic model, with the largest reward devaluations occurring at shorter delays. In contrast, an altogether different relationship was observed for effort-choices, which were best described by a model of inverse sigmoidal shape that is initially concave. Our results provide a novel characterization of human effort discounting behavior and its first dissociation from delay discounting. This enables accurate modelling of cost-benefit decisions, a prerequisite for the investigation of the neural underpinnings of effort-guided choice and for understanding the deficits in clinical disorders characterized by behavioral inactivity.

Behavioral Modeling of Human Choices Reveals Dissociable Effects of Physical Effort and Temporal Delay on Reward Devaluation

PubMed Central

Klein-Flügge, Miriam C.; Kennerley, Steven W.; Saraiva, Ana C.; Penny, Will D.; Bestmann, Sven

2015-01-01

There has been considerable interest from the fields of biology, economics, psychology, and ecology about how decision costs decrease the value of rewarding outcomes. For example, formal descriptions of how reward value changes with increasing temporal delays allow for quantifying individual decision preferences, as in animal species populating different habitats, or normal and clinical human populations. Strikingly, it remains largely unclear how humans evaluate rewards when these are tied to energetic costs, despite the surge of interest in the neural basis of effort-guided decision-making and the prevalence of disorders showing a diminished willingness to exert effort (e.g., depression). One common assumption is that effort discounts reward in a similar way to delay. Here we challenge this assumption by formally comparing competing hypotheses about effort and delay discounting. We used a design specifically optimized to compare discounting behavior for both effort and delay over a wide range of decision costs (Experiment 1). We then additionally characterized the profile of effort discounting free of model assumptions (Experiment 2). Contrary to previous reports, in both experiments effort costs devalued reward in a manner opposite to delay, with small devaluations for lower efforts, and progressively larger devaluations for higher effort-levels (concave shape). Bayesian model comparison confirmed that delay-choices were best predicted by a hyperbolic model, with the largest reward devaluations occurring at shorter delays. In contrast, an altogether different relationship was observed for effort-choices, which were best described by a model of inverse sigmoidal shape that is initially concave. Our results provide a novel characterization of human effort discounting behavior and its first dissociation from delay discounting. This enables accurate modelling of cost-benefit decisions, a prerequisite for the investigation of the neural underpinnings of effort-guided choice and for understanding the deficits in clinical disorders characterized by behavioral inactivity. PMID:25816114

Associations between parenting behavior and anxiety in a rodent model and a clinical sample: relationship to peripheral BDNF levels

PubMed Central

Dalle Molle, R; Portella, A K; Goldani, M Z; Kapczinski, F P; Leistner-Segala, S; Salum, G A; Manfro, G G; Silveira, P P

2012-01-01

Adverse early-life environment is associated with anxiety-like behaviors and disorders. Brain-derived neurotrophic factor (BDNF) is sensitive to this environment and could be a marker of underlying brain changes. We aimed at evaluating the development of anxiety-like behaviors in a rat model of early adversity, as well as the possible association with BDNF levels. Similar associations were investigated in a sample of adolescent humans. For the rat study, Wistar rat litters were divided into: early-life stress (ELS, limited access to nesting material) and control groups. Maternal behavior was observed from days 1 to 9 of life and, as adults, rats were subjected to behavioral testing and BDNF measurements in plasma, hippocampus, amygdala and periaqueductal gray. For the human study, 129 adolescents were evaluated for anxiety symptoms and perceived parental care. Serum BDNF levels and the Val66Met polymorphism of the BDNF gene were investigated. We found that ELS dams showed more pure contact, that is, contact with low care and high control, toward pups, and their adult offspring demonstrated higher anxiety-like behaviors and plasma BDNF. Also the pure contact correlated positively with adult peripheral BDNF. Similarly in humans, there was a positive correlation between maternal overprotection and serum BDNF only in Met carriers. We also found negative correlations between maternal warmth and separation anxiety, social phobia and school phobia. Finally, our translational approach revealed that ELS, mediated through variations in maternal care, is associated with anxiety in both rats and humans and increased peripheral BDNF may be marking these phenomena. PMID:23168995

The hydroxylated form of docosahexaenoic acid (DHA-H) modifies the brain lipid composition in a model of Alzheimer's disease, improving behavioral motor function and survival.

PubMed

Mohaibes, Raheem J; Fiol-deRoque, María A; Torres, Manuel; Ordinas, Margarita; López, David J; Castro, José A; Escribá, Pablo V; Busquets, Xavier

2017-09-01

We have compared the effect of the commonly used ω-3 fatty acid, docosahexaenoic acid ethyl ester (DHA-EE), and of its 2-hydroxylated DHA form (DHA-H), on brain lipid composition, behavior and lifespan in a new human transgenic Drosophila melanogaster model of Alzheimer's disease (AD). The transgenic flies expressed human Aβ42 and tau, and the overexpression of these human transgenes in the CNS of these flies produced progressive defects in motor function (antigeotaxic behavior) while reducing the animal's lifespan. Here, we demonstrate that both DHA-EE and DHA-H increase the longer chain fatty acids (≥18C) species in the heads of the flies, although only DHA-H produced an unknown chromatographic peak that corresponded to a non-hydroxylated lipid. In addition, only treatment with DHA-H prevented the abnormal climbing behavior and enhanced the lifespan of these transgenic flies. These benefits of DHA-H were confirmed in the well characterized transgenic PS1/APP mouse model of familial AD (5xFAD mice), mice that develop defects in spatial learning and in memory, as well as behavioral deficits. Hence, it appears that the modulation of brain lipid composition by DHA-H could have remedial effects on AD associated neurodegeneration. This article is part of a Special Issue entitled: Membrane Lipid Therapy: Drugs Targeting Biomembranes edited by Pablo V. Escribá. Copyright © 2017. Published by Elsevier B.V.

Beyond the Paleolithic prescription: incorporating diversity and flexibility in the study of human diet evolution.

PubMed

Turner, Bethany L; Thompson, Amanda L

2013-08-01

Evolutionary paradigms of human health and nutrition center on the evolutionary discordance or "mismatch" model in which human bodies, reflecting adaptations established in the Paleolithic era, are ill-suited to modern industrialized diets, resulting in rapidly increasing rates of chronic metabolic disease. Though this model remains useful, its utility in explaining the evolution of human dietary tendencies is limited. The assumption that human diets are mismatched to the evolved biology of humans implies that the human diet is instinctual or genetically determined and rooted in the Paleolithic era. This review looks at current research indicating that human eating habits are learned primarily through behavioral, social, and physiological mechanisms that start in utero and extend throughout the life course. Adaptations that appear to be strongly genetic likely reflect Neolithic, rather than Paleolithic, adaptations and are significantly influenced by human niche-constructing behavior. Several examples are used to conclude that incorporating a broader understanding of both the evolved mechanisms by which humans learn and imprint eating habits and the reciprocal effects of those habits on physiology would provide useful tools for structuring more lasting nutrition interventions. © 2013 International Life Sciences Institute.

Theoretical Bounds for the Influence of Tissue-Level Ductility on the Apparent-Level Strength of Human Trabecular Bone

PubMed Central

Nawathe, Shashank; Juillard, Frédéric; Keaveny, Tony M.

2015-01-01

The role of tissue-level post-yield behavior on the apparent-level strength of trabecular bone is a potentially important aspect of bone quality. To gain insight into this issue, we compared the apparent-level strength of trabecular bone for the hypothetical cases of fully brittle versus fully ductile failure behavior of the trabecular tissue. Twenty human cadaver trabecular bone specimens (5 mm cube; BV/TV = 6–36%) were scanned with micro-CT to create 3D finite element models (22-micron element size). For each model, apparent-level strength was computed assuming either fully brittle (fracture with no tissue ductility) or fully ductile (yield with no tissue fracture) tissue-level behaviors. We found that the apparent-level ultimate strength for the brittle behavior was only about half the value of the apparent-level 0.2%-offset yield strength for the ductile behavior, and the ratio of these brittle to ductile strengths was almost constant (mean ± SD = 0.56 ± 0.02; n=20; R2 = 0.99 between the two measures). As a result of this small variation, although the ratio of brittle to ductile strengths was positively correlated with the bone volume fraction (R2=0.44, p=0.01) and structure model index (SMI, R2=0.58, p<0.01), these effects were small. Mechanistically, the fully ductile behavior resulted in a much higher apparent-level strength because in this case about 16-fold more tissue was required to fail than for the fully brittle behavior; also, there was more tensile- than compressive-mode of failure at the tissue level for the fully brittle behavior. We conclude that, in theory, the apparent-level strength behavior of human trabecular bone can vary appreciably depending on whether the tissue fails in a fully ductile versus fully brittle manner, and this effect is largely constant despite appreciable variations in bone volume fraction and microarchitecture. PMID:23497799

Modeling and analysis of visual digital impact model for a Chinese human thorax.

PubMed

Zhu, Jin; Wang, Kai-Ming; Li, Shu; Liu, Hai-Yan; Jing, Xiao; Li, Xiao-Fang; Liu, Yi-He

2017-01-01

To establish a three-dimensional finite element model of the human chest for engineering research on individual protection. Computed tomography (CT) scanning data were used for three-dimensional reconstruction with the medical image reconstruction software Mimics. The finite element method (FEM) preprocessing software ANSYS ICEM CFD was used for cell mesh generation, and the relevant material behavior parameters of all of the model's parts were specified. The finite element model was constructed with the FEM software, and the model availability was verified based on previous cadaver experimental data. A finite element model approximating the anatomical structure of the human chest was established, and the model's simulation results conformed to the results of the cadaver experiment overall. Segment data of the human body and specialized software can be utilized for FEM model reconstruction to satisfy the need for numerical analysis of shocks to the human chest in engineering research on body mechanics.

Modeling bursts and heavy tails in human dynamics

NASA Astrophysics Data System (ADS)

Vázquez, Alexei; Oliveira, João Gama; Dezsö, Zoltán; Goh, Kwang-Il; Kondor, Imre; Barabási, Albert-László

2006-03-01

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. Here we provide direct evidence that for five human activity patterns, such as email and letter based communications, web browsing, library visits and stock trading, the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. We show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experiencing very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. We discuss two queuing models that capture human activity. The first model assumes that there are no limitations on the number of tasks an individual can hadle at any time, predicting that the waiting time of the individual tasks follow a heavy tailed distribution P(τw)˜τw-α with α=3/2 . The second model imposes limitations on the queue length, resulting in a heavy tailed waiting time distribution characterized by α=1 . We provide empirical evidence supporting the relevance of these two models to human activity patterns, showing that while emails, web browsing and library visitation display α=1 , the surface mail based communication belongs to the α=3/2 universality class. Finally, we discuss possible extension of the proposed queuing models and outline some future challenges in exploring the statistical mechanics of human dynamics.

Modeling bursts and heavy tails in human dynamics.

PubMed

Vázquez, Alexei; Oliveira, João Gama; Dezsö, Zoltán; Goh, Kwang-Il; Kondor, Imre; Barabási, Albert-László

2006-03-01

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. Here we provide direct evidence that for five human activity patterns, such as email and letter based communications, web browsing, library visits and stock trading, the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. We show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experiencing very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. We discuss two queuing models that capture human activity. The first model assumes that there are no limitations on the number of tasks an individual can handle at any time, predicting that the waiting time of the individual tasks follow a heavy tailed distribution P(tau(w)) approximately tau(w)(-alpha) with alpha=3/2. The second model imposes limitations on the queue length, resulting in a heavy tailed waiting time distribution characterized by alpha=1. We provide empirical evidence supporting the relevance of these two models to human activity patterns, showing that while emails, web browsing and library visitation display alpha=1, the surface mail based communication belongs to the alpha=3/2 universality class. Finally, we discuss possible extension of the proposed queuing models and outline some future challenges in exploring the statistical mechanics of human dynamics.

Extinction Dynamics and Control in Adaptive Networks

NASA Astrophysics Data System (ADS)

Schwartz, Ira; Shaw, Leah; Hindes, Jason

Disease control is of paramount importance in public health. Moreover, models of disease spread are an important component in implementing effective vaccination and treatment campaigns. However, human behavior in response to an outbreak has only recently been included in epidemic models on networks. Here we develop the mathematical machinery to describe the dynamics of extinction in finite populations that include human adaptive behavior. The formalism enables us to compute the optimal, fluctuation-induced path to extinction, and predict the average extinction time in adaptive networks as a function of the adaptation rate. We find that both observables have several unique scalings depending on the relative speed of infection and adaptivity. Finally, we discuss how the theory can be used to design optimal control programs in general networks, by coupling the effective force of noise with treatment and human behavior. Research supported by U.S. Naval Research Laboratory funding (Grant No. N0001414WX00023) and the Office of Naval Research (Grant No. N0001414WX20610).

Operant conditioning of a multiple degree-of-freedom brain-machine interface in a primate model of amputation.

PubMed

Balasubramanian, Karthikeyan; Southerland, Joshua; Vaidya, Mukta; Qian, Kai; Eleryan, Ahmed; Fagg, Andrew H; Sluzky, Marc; Oweiss, Karim; Hatsopoulos, Nicholas

2013-01-01

Operant conditioning with biofeedback has been shown to be an effective method to modify neural activity to generate goal-directed actions in a brain-machine interface. It is particularly useful when neural activity cannot be mathematically mapped to motor actions of the actual body such as in the case of amputation. Here, we implement an operant conditioning approach with visual feedback in which an amputated monkey is trained to control a multiple degree-of-freedom robot to perform a reach-to-grasp behavior. A key innovation is that each controlled dimension represents a behaviorally relevant synergy among a set of joint degrees-of-freedom. We present a number of behavioral metrics by which to assess improvements in BMI control with exposure to the system. The use of non-human primates with chronic amputation is arguably the most clinically-relevant model of human amputation that could have direct implications for developing a neural prosthesis to treat humans with missing upper limbs.

Brain-derived neurotrophic factor as a model system for examining gene by environment interactions across development.

PubMed

Casey, B J; Glatt, C E; Tottenham, N; Soliman, F; Bath, K; Amso, D; Altemus, M; Pattwell, S; Jones, R; Levita, L; McEwen, B; Magariños, A M; Gunnar, M; Thomas, K M; Mezey, J; Clark, A G; Hempstead, B L; Lee, F S

2009-11-24

There has been a dramatic rise in gene x environment studies of human behavior over the past decade that have moved the field beyond simple nature versus nurture debates. These studies offer promise in accounting for more variability in behavioral and biological phenotypes than studies that focus on genetic or experiential factors alone. They also provide clues into mechanisms of modifying genetic risk or resilience in neurodevelopmental disorders. Yet, it is rare that these studies consider how these interactions change over the course of development. In this paper, we describe research that focuses on the impact of a polymorphism in a brain-derived neurotrophic factor (BDNF) gene, known to be involved in learning and development. Specifically we present findings that assess the effects of genotypic and environmental loadings on neuroanatomic and behavioral phenotypes across development. The findings illustrate the use of a genetic mouse model that mimics the human polymorphism, to constrain the interpretation of gene-environment interactions across development in humans.

When does it pay to invest in a patch? The evolution of intentional niche construction.

PubMed

Mohlenhoff, Kathryn A; Codding, Brian F

2017-09-01

Humans modify their environments in ways that significantly transform the earth's ecosystems. Recent research suggests that such niche-constructing behaviors are not passive human responses to environmental variation, but instead should be seen as active and intentional management of the environment. Although such research is useful in highlighting the interactive dynamics between humans and their natural world, the niche-construction framework, as currently applied, fails to explain why people would decide to modify their environments in the first place. To help resolve this problem, we use a model of technological intensification to analyze the cost-benefit trade-offs associated with niche construction as a form of patch investment. We use this model to assess the costs and benefits of three paradigmatic cases of intentional niche construction in Western North America: the application of fire in acorn groves, the manufacture of fishing weirs, and the adoption of maize agriculture. Intensification models predict that investing in patch modification (niche construction) only provides a net benefit when the amount of resources needed crosses a critical threshold that makes the initial investment worthwhile. From this, it follows that low-cost investments, such as burning in oak groves, should be quite common, while more costly investments, such as maize agriculture, should be less common and depend on the alternatives available in the local environment. We examine how patterns of mobility, risk management, territoriality, and private property also co-evolve with the costs and benefits of niche construction. This approach illustrates that explaining niche-constructing behavior requires understanding the economic trade-offs involved in patch investment. Integrating concepts from niche construction and technological intensification models within a behavioral ecological framework provides insights into the coevolution and active feedback between adaptive behaviors and environmental change across human history. © 2017 Wiley Periodicals, Inc.

The Effect of Prenatal Hypoxia on Brain Development: Short- and Long-Term Consequences Demonstrated in Rodent Models

ERIC Educational Resources Information Center

Golan, Hava; Huleihel, Mahmoud

2006-01-01

Hypoxia (H) and hypoxia-ischemia (HI) are major causes of foetal brain damage with long-lasting behavioral implications. The effect of hypoxia has been widely studied in human and a variety of animal models. In the present review, we summarize the latest studies testing the behavioral outcomes following prenatal hypoxia/hypoxia-ischemia in rodent…

Effects of a Health Behavior Change Model-Based HIV/STI Prevention Intervention on Condom Use among Heterosexual Couples: A Randomized Trial

ERIC Educational Resources Information Center

Harvey, S. Marie; Kraft, Joan Marie; West, Stephen G.; Taylor, Aaron B.; Pappas-DeLuca, Katina A.; Beckman, Linda J.

2009-01-01

This study examines an intervention for heterosexual couples to prevent human immunodeficiency virus/sexually transmitted infections. It also evaluates the effect of the intervention, which is based on current models of health behavior change, on intermediate outcomes (individual and relationship factors) and consistency of condom use. Eligible…

Overlap of food addiction and substance use disorders definitions: analysis of animal and human studies.

PubMed

Hone-Blanchet, Antoine; Fecteau, Shirley

2014-10-01

Food has both homeostatic and hedonic components, which makes it a potent natural reward. Food related reward could therefore promote an escalation of intake and trigger symptoms associated to withdrawal, suggesting a behavioral parallel with substance abuse. Animal and human theoretical models of food reward and addiction have emerged, raising further interrogations on the validity of a bond between Substance Use Disorders, as clinically categorized in the DSM 5, and food reward. These models propose that highly palatable food items, rich in sugar and/or fat, are overly stimulating to the brain's reward pathways. Moreover, studies have also investigated the possibility of causal link between food reward and the contemporary obesity epidemic, with obesity being potentiated and maintained due to this overwhelming food reward. Although natural rewards are a hot topic in the definition and categorization of Substance Use Disorders, proofs of concept and definite evidence are still inconclusive. This review focuses on available results from experimental studies in animal and human models exploring the concept of food addiction, in an effort to determine if it depicts a specific phenotype and if there is truly a neurobiological similarity between food addiction and Substance Use Disorders. It describes results from sugar, fat and sweet-fat bingeing in rodent models, and behavioral and neurobiological assessments in different human populations. Although pieces of behavioral and neurobiological evidence supporting a food addiction phenotype in animals and humans are interesting, it seems premature to conclude on its validity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Toward Self-Referential Autonomous Learning of Object and Situation Models.

PubMed

Damerow, Florian; Knoblauch, Andreas; Körner, Ursula; Eggert, Julian; Körner, Edgar

2016-01-01

Most current approaches to scene understanding lack the capability to adapt object and situation models to behavioral needs not anticipated by the human system designer. Here, we give a detailed description of a system architecture for self-referential autonomous learning which enables the refinement of object and situation models during operation in order to optimize behavior. This includes structural learning of hierarchical models for situations and behaviors that is triggered by a mismatch between expected and actual action outcome. Besides proposing architectural concepts, we also describe a first implementation of our system within a simulated traffic scenario to demonstrate the feasibility of our approach.

Systems view on spatial planning and perception based on invariants in agent-environment dynamics

PubMed Central

Mettler, Bérénice; Kong, Zhaodan; Li, Bin; Andersh, Jonathan

2015-01-01

Modeling agile and versatile spatial behavior remains a challenging task, due to the intricate coupling of planning, control, and perceptual processes. Previous results have shown that humans plan and organize their guidance behavior by exploiting patterns in the interactions between agent or organism and the environment. These patterns, described under the concept of Interaction Patterns (IPs), capture invariants arising from equivalences and symmetries in the interaction with the environment, as well as effects arising from intrinsic properties of human control and guidance processes, such as perceptual guidance mechanisms. The paper takes a systems' perspective, considering the IP as a unit of organization, and builds on its properties to present a hierarchical model that delineates the planning, control, and perceptual processes and their integration. The model's planning process is further elaborated by showing that the IP can be abstracted, using spatial time-to-go functions. The perceptual processes are elaborated from the hierarchical model. The paper provides experimental support for the model's ability to predict the spatial organization of behavior and the perceptual processes. PMID:25628524

Perspectives on zebrafish models of hallucinogenic drugs and related psychotropic compounds.

PubMed

Neelkantan, Nikhil; Mikhaylova, Alina; Stewart, Adam Michael; Arnold, Raymond; Gjeloshi, Visar; Kondaveeti, Divya; Poudel, Manoj K; Kalueff, Allan V

2013-08-21

Among different classes of psychotropic drugs, hallucinogenic agents exert one of the most prominent effects on human and animal behaviors, markedly altering sensory, motor, affective, and cognitive responses. The growing clinical and preclinical interest in psychedelic, dissociative, and deliriant hallucinogens necessitates novel translational, sensitive, and high-throughput in vivo models and screens. Primate and rodent models have been traditionally used to study cellular mechanisms and neural circuits of hallucinogenic drugs' action. The utility of zebrafish ( Danio rerio ) in neuroscience research is rapidly growing due to their high physiological and genetic homology to humans, ease of genetic manipulation, robust behaviors, and cost effectiveness. Possessing a fully characterized genome, both adult and larval zebrafish are currently widely used for in vivo screening of various psychotropic compounds, including hallucinogens and related drugs. Recognizing the growing importance of hallucinogens in biological psychiatry, here we discuss hallucinogenic-induced phenotypes in zebrafish and evaluate their potential as efficient preclinical models of drug-induced states in humans.

Perspectives on Zebrafish Models of Hallucinogenic Drugs and Related Psychotropic Compounds

PubMed Central

2013-01-01

Among different classes of psychotropic drugs, hallucinogenic agents exert one of the most prominent effects on human and animal behaviors, markedly altering sensory, motor, affective, and cognitive responses. The growing clinical and preclinical interest in psychedelic, dissociative, and deliriant hallucinogens necessitates novel translational, sensitive, and high-throughput in vivo models and screens. Primate and rodent models have been traditionally used to study cellular mechanisms and neural circuits of hallucinogenic drugs’ action. The utility of zebrafish (Danio rerio) in neuroscience research is rapidly growing due to their high physiological and genetic homology to humans, ease of genetic manipulation, robust behaviors, and cost effectiveness. Possessing a fully characterized genome, both adult and larval zebrafish are currently widely used for in vivo screening of various psychotropic compounds, including hallucinogens and related drugs. Recognizing the growing importance of hallucinogens in biological psychiatry, here we discuss hallucinogenic-induced phenotypes in zebrafish and evaluate their potential as efficient preclinical models of drug-induced states in humans. PMID:23883191

Commentary on: Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research

PubMed Central

De Timary, Philippe; Philippot, Pierre

2015-01-01

Background This paper is a commentary to the article entitled: “Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research”, by Billieux, Schimmenti, Khazaal, Maurage and Heeren (2015). Methods and Aims In this manuscript, we commented on two aspects developed by the authors. Billieux et al. (2015) propose that the recent development of propositions of behavioral addiction is driven by an unwise application of an addiction model to excessive behaviors and rests on a confirmatory research strategy that does not question the psychological processes underlying the development of the conduct. They also show that applying a process driven strategy leads to a more appropriate description of the reality of the behavior and conduct, in particular by describing a variety of motivations for the excessive behavior, which is central to understanding the nature of the conduct. We believe that this new approach, which is fruitful to the emerging domain of behavioral addictions, could also apply to the domain of addictions in general. The latter is characterized by the application of a generic biological model, largely influenced by animal models, focusing on neurophysiological determinants of addiction. This approach may have decreased the attention paid to dimensions of addictions that are more specifically human. We will firstly briefly argue on the limitation of this neurophysiological addiction model for the field of excessive behavioral conducts. Secondly, we will argue for an approach centered on the differentiation of motivations and on the adaptive dimension of the behavior when it first developed and on the evocation of a transition where the conduct became independent of its original function. Conclusions The emerging domain of behavioral addictions, where no animal model has been developed so far, may bring a new reflection that may apply to the domain of addictions in general, with a specific attention to human questions. PMID:26551903

Simulating motivated cognition

NASA Technical Reports Server (NTRS)

Gevarter, William B.

1991-01-01

A research effort to develop a sophisticated computer model of human behavior is described. A computer framework of motivated cognition was developed. Motivated cognition focuses on the motivations or affects that provide the context and drive in human cognition and decision making. A conceptual architecture of the human decision-making approach from the perspective of information processing in the human brain is developed in diagrammatic form. A preliminary version of such a diagram is presented. This architecture is then used as a vehicle for successfully constructing a computer program simulation Dweck and Leggett's findings that relate how an individual's implicit theories orient them toward particular goals, with resultant cognitions, affects, and behavior.

A computational model of the human hand 93-ERI-053

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hollerbach, K.; Axelrod, T.

1996-03-01

The objectives of the Computational Hand Modeling project were to prove the feasibility of the Laboratory`s NIKE3D finite element code to orthopaedic problems. Because of the great complexity of anatomical structures and the nonlinearity of their behavior, we have focused on a subset of joints of the hand and lower extremity and have developed algorithms to model their behavior. The algorithms developed here solve fundamental problems in computational biomechanics and can be expanded to describe any other joints of the human body. This kind of computational modeling has never successfully been attempted before, due in part to a lack ofmore » biomaterials data and a lack of computational resources. With the computational resources available at the National Laboratories and the collaborative relationships we have established with experimental and other modeling laboratories, we have been in a position to pursue our innovative approach to biomechanical and orthopedic modeling.« less

Speech Communication Behavior; Perspectives and Principles.

ERIC Educational Resources Information Center

Barker, Larry L., Ed.; Kibler, Robert J., Ed.

Readings are included on seven topics: 1) theories and models of communication processes, 2) acquisition and performance of communication behaviors, 3) human information processing and diffusion, 4) persuasion and attitude change, 5) psychophysiological approaches to studying communication, 6) interpersonal communication within transracial…

Self-organization via active exploration in robotic applications. Phase 2: Hybrid hardware prototype

NASA Technical Reports Server (NTRS)

Oegmen, Haluk

1993-01-01

In many environments human-like intelligent behavior is required from robots to assist and/or replace human operators. The purpose of these robots is to reduce human time and effort in various tasks. Thus the robot should be robust and as autonomous as possible in order to eliminate or to keep to a strict minimum its maintenance and external control. Such requirements lead to the following properties: fault tolerance, self organization, and intelligence. A good insight into implementing these properties in a robot can be gained by considering human behavior. In the first phase of this project, a neural network architecture was developed that captures some fundamental aspects of human categorization, habit, novelty, and reinforcement behavior. The model, called FRONTAL, is a 'cognitive unit' regulating the exploratory behavior of the robot. In the second phase of the project, FRONTAL was interfaced with an off-the-shelf robotic arm and a real-time vision system. The components of this robotic system, a review of FRONTAL, and simulation studies are presented in this report.

Explaining reported puma-related behaviors and behavioral intentions among northern Arizona residents

USGS Publications Warehouse

Mattson, David J.; Ruther, Elizabeth J.

2012-01-01

Management of pumas in the American West is typified by conflict among stakeholders plausibly rooted in life experiences and worldviews. We used a mail questionnaire to assess demographics, nature-views, puma-related life experiences and behaviors, and support for puma-related policies among residents of northern Arizona. Data from the questionnaire (n = 693 respondents) were used to model behaviors and support for policies. Compared to models based on nature-views and life experiences, those based on demographics had virtually no support from the data. The Utilitarian/Dominionistic nature-view had the strongest effect of any variable in six of seven models, and was associated with firearms and opposition to policies that would limit killing pumas. The Humanistic/Moralistic nature-view was positively associated with non-lethal behaviors and policies in five models. Gender had the strongest effect of any demographic variable. Compared to demographics alone, our results suggest that worldviews provide a more meaningful explanation of reported human behaviors and behavioral intentions regarding pumas.

Mathematical Analysis for Non-reciprocal-interaction-based Model of Collective Behavior

NASA Astrophysics Data System (ADS)

Kano, Takeshi; Osuka, Koichi; Kawakatsu, Toshihiro; Ishiguro, Akio

2017-12-01

In many natural and social systems, collective behaviors emerge as a consequence of non-reciprocal interaction between their constituents. As a first step towards understanding the core principle that underlies these phenomena, we previously proposed a minimal model of collective behavior based on non-reciprocal interactions by drawing inspiration from friendship formation in human society, and demonstrated via simulations that various non-trivial patterns emerge by changing parameters. In this study, a mathematical analysis of the proposed model wherein the system size is small is performed. Through the analysis, the mechanism of the transition between several patterns is elucidated.

Introduction of the human AVPR1A gene substantially alters brain receptor expression patterns and enhances aspects of social behavior in transgenic mice.

PubMed

Charles, Rhonda; Sakurai, Takeshi; Takahashi, Nagahide; Elder, Gregory A; Gama Sosa, Miguel A; Young, Larry J; Buxbaum, Joseph D

2014-08-01

Central arginine vasopressin receptor 1A (AVPR1A) modulates a wide range of behaviors, including stress management and territorial aggression, as well as social bonding and recognition. Inter- and intra-species variations in the expression pattern of AVPR1A in the brain and downstream differential behavioral phenotypes have been attributed to differences in the non-coding regions of the AVPR1A gene, including polymorphic elements within upstream regulatory areas. Gene association studies have suggested a link between AVPR1A polymorphisms and autism, and AVPR1A has emerged as a potential pharmacological target for treatment of social cognitive impairments and mood and anxiety disorders. To further investigate the genetic mechanism giving rise to species differences in AVPR1A expression patterns and associated social behaviors, and to create a preclinical mouse model useful for screening drugs targeting AVPR1A, we engineered and extensively characterized bacterial artificial chromosome (BAC) transgenic mice harboring the entire human AVPR1A locus with the surrounding regulatory elements. Compared with wild-type animals, the humanized mice displayed a more widely distributed ligand-AVPR1A binding pattern, which overlapped with that of primates. Furthermore, humanized AVPR1A mice displayed increased reciprocal social interactions compared with wild-type animals, but no differences in social approach and preference for social novelty were observed. Aspects of learning and memory, specifically novel object recognition and spatial relocation recognition, were unaffected. The biological alterations in humanized AVPR1A mice resulted in the rescue of the prepulse inhibition impairments that were observed in knockout mice, indicating conserved functionality. Although further behavioral paradigms and additional cohorts need to be examined in humanized AVPR1A mice, the results demonstrate that species-specific variations in the genomic content of regulatory regions surrounding the AVPR1A locus are responsible for differential receptor protein expression patterns across species and that they are likely to contribute to species-specific behavioral variation. The humanized AVPR1A mouse is a potential preclinical model for further understanding the regulation of receptor gene expression and the impact of variation in receptor expression on behaviors, and should be useful for screening drugs targeting human AVPR1A, taking advantage of the expression of human AVPR1A in human-relevant brain regions. © 2014. Published by The Company of Biologists Ltd.

A model of interval timing by neural integration.

PubMed

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

Cognitive Aspects of Power in a Two-Level Game

NASA Astrophysics Data System (ADS)

Juvina, Ion; Lebiere, Christian; Martin, Jolie; Gonzalez, Cleotilde

The Intergroup Prisoner's Dilemma with Intragroup Power Dynamics (IPD^2) is a new game paradigm for studying human behavior in conflict situations. IPD^2 adds the concept of intragroup power to an intergroup version of the standard Iterated Prisoner's Dilemma game. We conducted an exploratory laboratory study in which individual human participants played the game against computer strategies of various complexities. We also developed a cognitive model of human decision making in this game. The model was run in place of the human participant under the same conditions as in the laboratory study. Results from the human study and the model simulations are presented and discussed, emphasizing the value of including intragroup power in game theoretic models of conflict.

Integrating an agent-based model into a large-scale hydrological model for evaluating drought management in California

NASA Astrophysics Data System (ADS)

Sheffield, J.; He, X.; Wada, Y.; Burek, P.; Kahil, M.; Wood, E. F.; Oppenheimer, M.

2017-12-01

California has endured record-breaking drought since winter 2011 and will likely experience more severe and persistent drought in the coming decades under changing climate. At the same time, human water management practices can also affect drought frequency and intensity, which underscores the importance of human behaviour in effective drought adaptation and mitigation. Currently, although a few large-scale hydrological and water resources models (e.g., PCR-GLOBWB) consider human water use and management practices (e.g., irrigation, reservoir operation, groundwater pumping), none of them includes the dynamic feedback between local human behaviors/decisions and the natural hydrological system. It is, therefore, vital to integrate social and behavioral dimensions into current hydrological modeling frameworks. This study applies the agent-based modeling (ABM) approach and couples it with a large-scale hydrological model (i.e., Community Water Model, CWatM) in order to have a balanced representation of social, environmental and economic factors and a more realistic representation of the bi-directional interactions and feedbacks in coupled human and natural systems. In this study, we focus on drought management in California and considers two types of agents, which are (groups of) farmers and state management authorities, and assumed that their corresponding objectives are to maximize the net crop profit and to maintain sufficient water supply, respectively. Farmers' behaviors are linked with local agricultural practices such as cropping patterns and deficit irrigation. More precisely, farmers' decisions are incorporated into CWatM across different time scales in terms of daily irrigation amount, seasonal/annual decisions on crop types and irrigated area as well as the long-term investment of irrigation infrastructure. This simulation-based optimization framework is further applied by performing different sets of scenarios to investigate and evaluate the effectiveness of different water management strategies and how policy interventions will facilitate drought adaptation in California.

Following rules in the intermontane west: 19th-century mormon settlement

PubMed Central

Norton, William

2001-01-01

The academic discipline of human geography is concerned with human activities, especially as these relate to physical landscapes and contribute to the modification of those landscapes. Although little attention has been paid to objectivist philosophies to inform human geography, behavior analysis might offer a useful explanatory model. As an example, a behavior analysis of selected aspects of 19th-century Mormon movement and settlement in the intermontane West is conducted. Mormons are a society of believers who practice cooperative effort and support for other members, and the Mormon church is governed by priesthood authority with members being called to perform tasks. This analysis employs the concepts of metacontingency, rule-governed behavior, and delayed reinforcement to analyze how Mormons settled the intermontane West. PMID:22478355

Serotonin depletion induces pessimistic-like behavior in a cognitive bias paradigm in pigs.

PubMed

Stracke, Jenny; Otten, Winfried; Tuchscherer, Armin; Puppe, Birger; Düpjan, Sandra

2017-05-15

Cognitive and affective processes are highly interrelated. This has implications for neuropsychiatric disorders such as major depressive disorder in humans but also for the welfare of non-human animals. The brain serotonergic system might play a key role in mediating the relationship between cognitive functions and affective regulation. The aim of our study was to examine the influence of serotonin depletion on the affective state and cognitive processing in pigs, an important farm animal species but also a potential model species for biomedical research in humans. For this purpose, we modified a serotonin depletion model using para-chlorophenylalanine (pCPA) to decrease serotonin levels in brain areas involved in cognitive and affective processing (part 1). The consequences of serotonin depletion were then measured in two behavioral tests (part 2): the spatial judgement task (SJT), providing information about the effects of the affective state on cognitive processing, and the open field/novel object (OFNO) test, which measures behavioral reactions to novelty that are assumed to reflect affective state. In part 1, 40 pigs were treated with either pCPA or saline for six consecutive days. Serotonin levels were assessed in seven different brain regions 4, 5, 6, 11 and 13days after the first injection. Serotonin was significantly depleted in all analyzed brain regions up to 13days after the first application. In part 2, the pCPA model was applied to 48 animals in behavioral testing. Behavioral tests, the OFNO test and the SJT, were conducted both before and after pCPA/saline injections. While results from the OFNO tests were inconclusive, an effect of treatment as well as an effect of the phase (before and after treatment) was observed in the SJT. Animals treated with pCPA showed more pessimistic-like behavior, suggesting a more negative affective state due to serotonin depletion. Thus, our results confirm that the serotonergic system is a key player in cognitive-emotional processing. Hence, the serotonin depletion model and the spatial judgement task can increase our understanding of the basic mechanisms underlying both human neuropsychiatric disorders and animal welfare. Copyright © 2017 Elsevier Inc. All rights reserved.

A Comparison of Three Approaches to Model Human Behavior

NASA Astrophysics Data System (ADS)

Palmius, Joel; Persson-Slumpi, Thomas

2010-11-01

One way of studying social processes is through the use of simulations. The use of simulations for this purpose has been established as its own field, social simulations, and has been used for studying a variety of phenomena. A simulation of a social setting can serve as an aid for thinking about that social setting, and for experimenting with different parameters and studying the outcomes caused by them. When using the simulation as an aid for thinking and experimenting, the chosen simulation approach will implicitly steer the simulationist towards thinking in a certain fashion in order to fit the model. To study the implications of model choice on the understanding of a setting where human anticipation comes into play, a simulation scenario of a coffee room was constructed using three different simulation approaches: Cellular Automata, Systems Dynamics and Agent-based modeling. The practical implementations of the models were done in three different simulation packages: Stella for Systems Dynamic, CaFun for Cellular automata and SesAM for Agent-based modeling. The models were evaluated both using Randers' criteria for model evaluation, and through introspection where the authors reflected upon how their understanding of the scenario was steered through the model choice. Further the software used for implementing the simulation models was evaluated, and practical considerations for the choice of software package are listed. It is concluded that the models have very different strengths. The Agent-based modeling approach offers the most intuitive support for thinking about and modeling a social setting where the behavior of the individual is in focus. The Systems Dynamics model would be preferable in situations where populations and large groups would be studied as wholes, but where individual behavior is of less concern. The Cellular Automata models would be preferable where processes need to be studied from the basis of a small set of very simple rules. It is further concluded that in most social simulation settings the Agent-based modeling approach would be the probable choice. This since the other models does not offer much in the way of supporting the modeling of the anticipatory behavior of humans acting in an organization.

Understanding the dynamics of sustainable social-ecological systems: human behavior, institutions, and regulatory feedback networks.

PubMed

Anderies, John M

2015-02-01

I present a general mathematical modeling framework that can provide a foundation for the study of sustainability in social- ecological systems (SESs). Using basic principles from feedback control and a sequence of specific models from bioeconomics and economic growth, I outline several mathematical and empirical challenges associated with the study of sustainability of SESs. These challenges are categorized into three classes: (1) the social choice of performance measures, (2) uncertainty, and (3) collective action. Finally, I present some opportunities for combining stylized dynamical systems models with empirical data on human behavior and biophysical systems to address practical challenges for the design of effective governance regimes (policy feedbacks) for highly uncertain natural resource systems.

Effect of cholesterol and triglycerides levels on the rheological behavior of human blood

NASA Astrophysics Data System (ADS)

Moreno, Leonardo; Calderas, Fausto; Sanchez-Olivares, Guadalupe; Medina-Torres, Luis; Sanchez-Solis, Antonio; Manero, Octavio

2015-02-01

Important public health problems worldwide such as obesity, diabetes, hyperlipidemia and coronary diseases are quite common. These problems arise from numerous factors, such as hyper-caloric diets, sedentary habits and other epigenetic factors. With respect to Mexico, the population reference values of total cholesterol in plasma are around 200 mg/dL. However, a large proportion has higher levels than this reference value. In this work, we analyze the rheological properties of human blood obtained from 20 donors, as a function of cholesterol and triglyceride levels, upon a protocol previously approved by the health authorities. Samples with high and low cholesterol and triglyceride levels were selected and analyzed by simple-continuous and linear-oscillatory shear flow. Rheometric properties were measured and related to the structure and composition of human blood. In addition, rheometric data were modeled by using several constitutive equations: Bautista-Manero-Puig (BMP) and the multimodal Maxwell equations to predict the flow behavior of human blood. Finally, a comparison was made among various models, namely, the BMP, Carreau and Quemada equations for simple shear rate flow. An important relationship was found between cholesterol, triglycerides and the structure of human blood. Results show that blood with high cholesterol levels (400 mg/dL) has flow properties fully different (higher viscosity and a more pseudo-plastic behavior) than blood with lower levels of cholesterol (tendency to Newtonian behavior or viscosity plateau at low shear rates).

Simulating Activities: Relating Motives, Deliberation and Attentive Coordination

NASA Technical Reports Server (NTRS)

Clancey, William J.; Clancy, Daniel (Technical Monitor)

2002-01-01

Activities are located behaviors, taking time, conceived as socially meaningful, and usually involving interaction with tools and the environment. In modeling human cognition as a form of problem solving (goal-directed search and operator sequencing), cognitive science researchers have not adequately studied "off-task" activities (e.g., waiting), non-intellectual motives (e.g., hunger), sustaining a goal state (e.g., playful interaction), and coupled perceptual-motor dynamics (e.g., following someone). These aspects of human behavior have been considered in bits and pieces in past research, identified as scripts, human factors, behavior settings, ensemble, flow experience, and situated action. More broadly, activity theory provides a comprehensive framework relating motives, goals, and operations. This paper ties these ideas together, using examples from work life in a Canadian High Arctic research station. The emphasis is on simulating human behavior as it naturally occurs, such that "working" is understood as an aspect of living. The result is a synthesis of previously unrelated analytic perspectives and a broader appreciation of the nature of human cognition. Simulating activities in this comprehensive way is useful for understanding work practice, promoting learning, and designing better tools, including human-robot systems.

Recent Advances in the Genetics of Vocal Learning

PubMed Central

Condro, Michael C.; White, Stephanie A.

2015-01-01

Language is a complex communicative behavior unique to humans, and its genetic basis is poorly understood. Genes associated with human speech and language disorders provide some insights, originating with the FOXP2 transcription factor, a mutation in which is the source of an inherited form of developmental verbal dyspraxia. Subsequently, targets of FOXP2 regulation have been associated with speech and language disorders, along with other genes. Here, we review these recent findings that implicate genetic factors in human speech. Due to the exclusivity of language to humans, no single animal model is sufficient to study the complete behavioral effects of these genes. Fortunately, some animals possess subcomponents of language. One such subcomponent is vocal learning, which though rare in the animal kingdom, is shared with songbirds. We therefore discuss how songbird studies have contributed to the current understanding of genetic factors that impact human speech, and support the continued use of this animal model for such studies in the future. PMID:26052371

An integrated approach to rotorcraft human factors research

NASA Technical Reports Server (NTRS)

Hart, Sandra G.; Hartzell, E. James; Voorhees, James W.; Bucher, Nancy M.; Shively, R. Jay

1988-01-01

As the potential of civil and military helicopters has increased, more complex and demanding missions in increasingly hostile environments have been required. Users, designers, and manufacturers have an urgent need for information about human behavior and function to create systems that take advantage of human capabilities, without overloading them. Because there is a large gap between what is known about human behavior and the information needed to predict pilot workload and performance in the complex missions projected for pilots of advanced helicopters, Army and NASA scientists are actively engaged in Human Factors Research at Ames. The research ranges from laboratory experiments to computational modeling, simulation evaluation, and inflight testing. Information obtained in highly controlled but simpler environments generates predictions which can be tested in more realistic situations. These results are used, in turn, to refine theoretical models, provide the focus for subsequent research, and ensure operational relevance, while maintaining predictive advantages. The advantages and disadvantages of each type of research are described along with examples of experimental results.

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

PubMed Central

Van Nimmen, Katrien; Lombaert, Geert; De Roeck, Guido; Van den Broeck, Peter

2016-01-01

For slender and lightweight structures, vibration serviceability is a matter of growing concern, often constituting the critical design requirement. With designs governed by the dynamic performance under human-induced loads, a strong demand exists for the verification and refinement of currently available load models. The present contribution uses a 3D inertial motion tracking technique for the characterization of the in-field pedestrian behavior. The technique is first tested in laboratory experiments with simultaneous registration of the corresponding ground reaction forces. The experiments include walking persons as well as rhythmical human activities such as jumping and bobbing. It is shown that the registered motion allows for the identification of the time variant pacing rate of the activity. Together with the weight of the person and the application of generalized force models available in literature, the identified time-variant pacing rate allows to characterize the human-induced loads. In addition, time synchronization among the wireless motion trackers allows identifying the synchronization rate among the participants. Subsequently, the technique is used on a real footbridge where both the motion of the persons and the induced structural vibrations are registered. It is shown how the characterized in-field pedestrian behavior can be applied to simulate the induced structural response. It is demonstrated that the in situ identified pacing rate and synchronization rate constitute an essential input for the simulation and verification of the human-induced loads. The main potential applications of the proposed methodology are the estimation of human-structure interaction phenomena and the development of suitable models for the correlation among pedestrians in real traffic conditions. PMID:27167309

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors

NASA Astrophysics Data System (ADS)

Cenek, Martin; Dahl, Spencer K.

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors.

PubMed

Cenek, Martin; Dahl, Spencer K

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

GABAergic modulation of human social interaction in a prisoner's dilemma model by acute administration of alprazolam.

PubMed

Lane, Scott D; Gowin, Joshua L

2009-10-01

Recent work in neuroeconomics has used game theory paradigms to examine neural systems that subserve human social interaction and decision making. Attempts to modify social interaction through pharmacological manipulation have been less common. Here we show dose-dependent modification of human social behavior in a prisoner's dilemma model after acute administration of the γ-aminobutyric acid (GABA)-A modulating benzodiazepine alprazolam. Nine healthy adults received doses of placebo, 0.5, 1.0, and 2.0 mg alprazolam in a counterbalanced within-subject design, while completing multiple test blocks per day on an iterated prisoner's dilemma game. During test blocks in which peak subjective effects of alprazolam were reported, cooperative choices were significantly decreased as a function of dose. Consistent with previous reports showing that high acute doses of GABA-modulating drugs are associated with violence and other antisocial behavior, our data suggest that at sufficiently high doses, alprazolam can decrease cooperation. These behavioral changes may be facilitated by changes in inhibitory control facilitated by GABA. Game theory paradigms may prove useful in behavioral pharmacology studies seeking to measure social interaction, and may help inform the emerging field of neuroeconomics.

GABAergic modulation of human social interaction in a prisoner’s dilemma model via acute administration of alprazolam

PubMed Central

Lane, Scott D.; Gowin, Joshua L.

2010-01-01

Recent work in neuroeconomics has utilized game theory paradigms to examine neural systems that subserve human social interaction and decision making. Attempts to modify social interaction through pharmacological manipulation have been less common. Here we show dose-dependent modification of human social behavior in a prisoner’s dilemma (PD) model following acute administration of the GABA-A modulating benzodiazepine alprazolam. Nine healthy adults received doses of placebo, 0.5, 1.0, and 2.0 mg alprazolam in a counterbalanced within-subject design, while completing multiple test blocks per day on an iterated PD game. During test blocks in which peak subjective effects of alprazolam were reported, cooperative choices were significantly decreased as a function of dose. Consistent with previous reports showing that high acute doses of GABA-modulating drugs are associated with violence and other antisocial behavior, our data suggest that at sufficiently high doses, alprazolam can decrease cooperation. These behavioral changes may be facilitated by changes in inhibitory control facilitated by GABA. Game theory paradigms may prove useful in behavioral pharmacology studies seeking to measure social interaction, and may help inform the emerging field of neuroeconomics. PMID:19667972

Evaluation of an intact, an ACL-deficient, and a reconstructed human knee joint finite element model.

PubMed

Vairis, Achilles; Stefanoudakis, George; Petousis, Markos; Vidakis, Nectarios; Tsainis, Andreas-Marios; Kandyla, Betina

2016-02-01

The human knee joint has a three-dimensional geometry with multiple body articulations that produce complex mechanical responses under loads that occur in everyday life and sports activities. Understanding the complex mechanical interactions of these load-bearing structures is of use when the treatment of relevant diseases is evaluated and assisting devices are designed. The anterior cruciate ligament (ACL) in the knee is one of four main ligaments that connects the femur to the tibia and is often torn during sudden twisting motions, resulting in knee instability. The objective of this work is to study the mechanical behavior of the human knee joint and evaluate the differences in its response for three different states, i.e., intact, ACL-deficient, and surgically treated (reconstructed) knee. The finite element models corresponding to these states were developed. For the reconstructed model, a novel repair device was developed and patented by the author in previous work. Static load cases were applied, as have already been presented in a previous work, in order to compare the calculated results produced by the two models the ACL-deficient and the surgically reconstructed knee joint, under the exact same loading conditions. Displacements were calculated in different directions for the load cases studied and were found to be very close to those from previous modeling work and were in good agreement with experimental data presented in literature. The developed finite element model for both the intact and the ACL-deficient human knee joint is a reliable tool to study the kinematics of the human knee, as results of this study show. In addition, the reconstructed human knee joint model had kinematic behavior similar to the intact knee joint, showing that such reconstruction devices can restore human knee stability to an adequate extent.

Viscoelastic modeling and quantitative experimental characterization of normal and osteoarthritic human articular cartilage using indentation.

PubMed

Richard, F; Villars, M; Thibaud, S

2013-08-01

The viscoelastic behavior of articular cartilage changes with progression of osteoarthritis. The objective of this study is to quantify this progression and to propose a viscoelastic model of articular cartilage taking into account the degree of osteoarthritis that which be easily used in predictive numerical simulations of the hip joint behavior. To quantify the effects of osteoarthritis (OA) on the viscoelastic behavior of human articular cartilage, samples were obtained from the hip arthroplasty due to femoral neck fracture (normal cartilage) or advanced coxarthrosis (OA cartilage). Experimental data were obtained from instrumented indentation tests on unfrozen femoral cartilage collected and studied in the day following the prosthetic hip surgery pose. By using an inverse method coupled with a numerical modeling (FEM) of all experimental data of the indentation tests, the viscoelastic properties of the two states were quantified. Mean values of viscoelastic parameters were significantly lower for OA cartilage than normal (instantaneous and relaxed tension moduli, viscosity coefficient). Based on the results and in the thermodynamic framework, a constitutive viscoelastic model taking into account the degree of osteoarthritis as an internal variable of damage is proposed. The isotropic phenomenological viscoelastic model including degradation provides an accurate prediction of the mechanical response of the normal human cartilage and OA cartilage with advanced coxarthrosis but should be further validated for intermediate degrees of osteoarthritis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Developmental consequences of behavioral inhibition: a model in rhesus monkeys (Macaca mulatta).

PubMed

Chun, Katie; Capitanio, John P

2016-11-01

In children, behavioral inhibition is characterized by a disposition to withdraw in the presence of strangers and novel situations. Later in life, behavioral inhibition can result in an increased risk for anxiety and depression and a decrease in social behavior. We selected rhesus monkeys that, during infancy, showed evidence of behavioral inhibition in response to separation, and contrasted them with non-inhibited peers. To understand the development of behavioral inhibition at juvenile age, we collected behavioral data in response to relocation; in response to a human intruder challenge; and in naturalistic outdoor field corrals. At 4 years of age (young adulthood), we again collected behavioral data in the outdoor field corrals to understand the adult social consequences of behavioral inhibition. We also included sex, dominance rank, and number of available kin in our analyses. Finally, to understand the consistency in behavior in behaviorally inhibited animals, we conducted exploratory analyses contrasting behaviorally inhibited animals that showed high vs. low durations of non-social behaviors as adults. At juvenile age, behaviorally inhibited animals continued to show behavioral differences in the novel testing room and during the human intruder challenge, generally showing evidence of greater anxiety and emotionality compared to non-inhibited controls. In their outdoor corrals, behaviorally inhibited juveniles spent more time alone and less time in proximity and grooming with mother and other adult females. In young adulthood, we found that behavioral inhibition was not related to time spent alone. We did find that duration of time alone in adulthood was related to time alone exhibited as juveniles; sex, dominance rank, or the number of kin were not influential in adult non-social duration, either as main effects or as moderators. Finally, exploratory analyses revealed that behaviorally inhibited females that were more sociable (less time spent alone) as adults had spent more time grooming as juveniles, suggesting that high-quality social interaction at a young age might mitigate the social consequences of behavioral inhibition. Overall, we believe that the many similarities with the human data that we found suggest that this monkey model of naturally occurring behavioral inhibition can be valuable for understanding social development. © 2015 John Wiley & Sons Ltd.

Estimation of Time-Varying Pilot Model Parameters

NASA Technical Reports Server (NTRS)

Zaal, Peter M. T.; Sweet, Barbara T.

2011-01-01

Human control behavior is rarely completely stationary over time due to fatigue or loss of attention. In addition, there are many control tasks for which human operators need to adapt their control strategy to vehicle dynamics that vary in time. In previous studies on the identification of time-varying pilot control behavior wavelets were used to estimate the time-varying frequency response functions. However, the estimation of time-varying pilot model parameters was not considered. Estimating these parameters can be a valuable tool for the quantification of different aspects of human time-varying manual control. This paper presents two methods for the estimation of time-varying pilot model parameters, a two-step method using wavelets and a windowed maximum likelihood estimation method. The methods are evaluated using simulations of a closed-loop control task with time-varying pilot equalization and vehicle dynamics. Simulations are performed with and without remnant. Both methods give accurate results when no pilot remnant is present. The wavelet transform is very sensitive to measurement noise, resulting in inaccurate parameter estimates when considerable pilot remnant is present. Maximum likelihood estimation is less sensitive to pilot remnant, but cannot detect fast changes in pilot control behavior.

Adaptive neuroplastic responses in early and late hemispherectomized monkeys.

PubMed

Burke, Mark W; Kupers, Ron; Ptito, Maurice

2012-01-01

Behavioural recovery in children who undergo medically required hemispherectomy showcase the remarkable ability of the cerebral cortex to adapt and reorganize following insult early in life. Case study data suggest that lesions sustained early in childhood lead to better recovery compared to those that occur later in life. In these children, it is possible that neural reorganization had begun prior to surgery but was masked by the dysfunctional hemisphere. The degree of neural reorganization has been difficult to study systematically in human infants. Here we present a 20-year culmination of data on our nonhuman primate model (Chlorocebus sabeus) of early-life hemispherectomy in which behavioral recovery is interpreted in light of plastic processes that lead to the anatomical reorganization of the early-damaged brain. The model presented here suggests that significant functional recovery occurs after the removal of one hemisphere in monkeys with no preexisting neurological dysfunctions. Human and primate studies suggest a critical role for subcortical and brainstem structures as well as corticospinal tracts in the neuroanatomical reorganization which result in the remarkable behavioral recovery following hemispherectomy. The non-human primate model presented here offers a unique opportunity for studying the behavioral and functional neuroanatomical reorganization that underlies developmental plasticity.

Experimental characterization of post rigor mortis human muscle subjected to small tensile strains and application of a simple hyper-viscoelastic model.

PubMed

Gras, Laure-Lise; Laporte, Sébastien; Viot, Philippe; Mitton, David

2014-10-01

In models developed for impact biomechanics, muscles are usually represented with one-dimensional elements having active and passive properties. The passive properties of muscles are most often obtained from experiments performed on animal muscles, because limited data on human muscle are available. The aim of this study is thus to characterize the passive response of a human muscle in tension. Tensile tests at different strain rates (0.0045, 0.045, and 0.45 s⁻¹) were performed on 10 extensor carpi ulnaris muscles. A model composed of a nonlinear element defined with an exponential law in parallel with one or two Maxwell elements and considering basic geometrical features was proposed. The experimental results were used to identify the parameters of the model. The results for the first- and second-order model were similar. For the first-order model, the mean parameters of the exponential law are as follows: Young's modulus E (6.8 MPa) and curvature parameter α (31.6). The Maxwell element mean values are as follows: viscosity parameter η (1.2 MPa s) and relaxation time τ (0.25 s). Our results provide new data on a human muscle tested in vitro and a simple model with basic geometrical features that represent its behavior in tension under three different strain rates. This approach could be used to assess the behavior of other human muscles. © IMechE 2014.

High risk sexual behaviors for HIV among the in-school youth in Swaziland: a structural equation modeling approach.

PubMed

Sacolo, Hlengiwe Nokuthula; Chung, Min-Huey; Chu, Hsin; Liao, Yuan-Mei; Chen, Chiung-Hua; Ou, Keng-Liang; Chang, Lu-I; Chou, Kuei-Ru

2013-01-01

Global efforts in response to the increased prevalence of the human immunodeficiency virus (HIV) are mainly aimed at reducing high risk sexual behaviors among young people. However, knowledge regarding intentions of young people to engage in protective sexual behaviors is still lacking in many countries around the world, especially in Sub-Saharan Africa where prevalence of human immunodeficiency virus is the highest. The objective of this study was to test the theory of planned behavior (TPB) for predicting factors associated with protective sexual behaviors, including sexual abstinence and condom use, among in-school youths aged between 15 and 19 years in Swaziland. This cross-sectional survey was conducted using a anonymous questionnaire. A two-stage stratified and cluster random sampling method was used. Approximately one hundred pupils from each of four schools agreed to participate in the study, providing a total sample size of 403 pupils of which 369 were ultimately included for data analysis. The response rate was 98%. Structural equation modeling was used to analyse hypothesized paths. The TPB model used in this study was effective in predicting protective sexual behavior among Swazi in-school youths, as shown by model fit indices. All hypothesized constructs significantly predicted intentions for abstinence and condom use, except perceived abstinence controls. Subjective norms were the strongest predictors of intention for premarital sexual abstinence; however, perceived controls for condom use were the strongest predictors of intention for condom use. Our findings support application of the model in predicting determinants of condom use and abstinence intentions among Swazi in-school youths.

Potential of zebrafish as a model for exploring the role of the amygdala in emotional memory and motivational behavior.

PubMed

Perathoner, Simon; Cordero-Maldonado, Maria Lorena; Crawford, Alexander D

2016-06-01

Emotion is a key aspect of behavior, enabling humans and animals to assign either positive or negative values to sensory inputs and thereby to make appropriate decisions. Classical experiments in mammalian models, mainly in primates and rodents, have shown that the amygdala is essential for appetitive and aversive associative processing and that dysfunction of this brain region leads to various psychiatric conditions, including depression, generalized anxiety disorder, panic disorder, phobias, autism, and posttraumatic stress disorder. In the past 2 decades, the zebrafish (Danio rerio; Cyprinidae) has emerged as a versatile, reliable vertebrate model organism for the in vivo study of development, gene function, and numerous aspects of human pathologies. Small size, high fecundity, rapid external development, transparency, genetic tractability, and high genetic and physiologic homology with humans are among the factors that have contributed to the success with this small fish in different biomedical research areas. Recent findings indicate that, despite the anatomical differences in the brain structure of teleosts and tetrapods, fish possess a structure homologous to the mammalian amygdala, a hypothesis that is supported by the expression of molecular markers, analyses of neuronal projections in different brain areas, and behavioral studies. This Review summarizes this evidence and highlights a number of relevant bioassays in zebrafish to study emotional memory and motivational behavior. © 2016 Wiley Periodicals, Inc.

Modeling the human as a controller in a multitask environment

NASA Technical Reports Server (NTRS)

Govindaraj, T.; Rouse, W. B.

1978-01-01

Modeling the human as a controller of slowly responding systems with preview is considered. Along with control tasks, discrete noncontrol tasks occur at irregular intervals. In multitask situations such as these, it has been observed that humans tend to apply piecewise constant controls. It is believed that the magnitude of controls and the durations for which they remain constant are dependent directly on the system bandwidth, preview distance, complexity of the trajectory to be followed, and nature of the noncontrol tasks. A simple heuristic model of human control behavior in this situation is presented. The results of a simulation study, whose purpose was determination of the sensitivity of the model to its parameters, are discussed.

Goal Translation: How To Create a Results-Focused Organizational Culture.

ERIC Educational Resources Information Center

Mourier, Pierre

2000-01-01

Presents a model for changing human and organizational behavior. Highlights include behavioral dynamics; expectations; alignment; organizational structure; organizational culture; individual skills and training; leadership; management systems; developing corporate-level goals; communicating goals to the organization; and developing employee goals.…

Does the Macaque Monkey Provide a Good Model for Studying Human Executive Control? A Comparative Behavioral Study of Task Switching

PubMed Central

Caselli, Luana; Chelazzi, Leonardo

2011-01-01

The ability to swiftly and smoothly switch from one task set to another is central to intelligent behavior, because it allows an organism to flexibly adapt to ever changing environmental conditions and internal needs. For this reason, researchers interested in executive control processes have often relied on task-switching paradigms as powerful tools to uncover the underlying cognitive and brain architecture. In order to gather fundamental information at the single-cell level, it would be greatly helpful to demonstrate that non-human primates, especially the macaque monkey, share with us similar behavioral manifestations of task-switching and therefore, in all likelihood, similar underlying brain mechanisms. Unfortunately, prior attempts have provided negative results (e.g., Stoet & Snyder, 2003b), in that it was reported that macaques do not show the typical signature of task-switching operations at the behavioral level, represented by switch costs. If confirmed, this would indicate that the macaque cannot be used as a model approach to explore human executive control mechanisms by means of task-switching paradigms. We have therefore decided to re-explore this issue, by conducting a comparative experiment on a group of human participants and two macaque monkeys, whereby we measured and compared performance costs linked to task switching and resistance to interference across the two species. Contrary to what previously reported, we found that both species display robust task switching costs, thus supporting the claim that macaque monkeys provide an exquisitely suitable model to study the brain mechanisms responsible for maintaining and switching task sets. PMID:21720549

Testing the role of reward and punishment sensitivity in avoidance behavior: a computational modeling approach

PubMed Central

Sheynin, Jony; Moustafa, Ahmed A.; Beck, Kevin D.; Servatius, Richard J.; Myers, Catherine E.

2015-01-01

Exaggerated avoidance behavior is a predominant symptom in all anxiety disorders and its degree often parallels the development and persistence of these conditions. Both human and non-human animal studies suggest that individual differences as well as various contextual cues may impact avoidance behavior. Specifically, we have recently shown that female sex and inhibited temperament, two anxiety vulnerability factors, are associated with greater duration and rate of the avoidance behavior, as demonstrated on a computer-based task closely related to common rodent avoidance paradigms. We have also demonstrated that avoidance is attenuated by the administration of explicit visual signals during “non-threat” periods (i.e., safety signals). Here, we use a reinforcement-learning network model to investigate the underlying mechanisms of these empirical findings, with a special focus on distinct reward and punishment sensitivities. Model simulations suggest that sex and inhibited temperament are associated with specific aspects of these sensitivities. Specifically, differences in relative sensitivity to reward and punishment might underlie the longer avoidance duration demonstrated by females, whereas higher sensitivity to punishment might underlie the higher avoidance rate demonstrated by inhibited individuals. Simulations also suggest that safety signals attenuate avoidance behavior by strengthening the competing approach response. Lastly, several predictions generated by the model suggest that extinction-based cognitive-behavioral therapies might benefit from the use of safety signals, especially if given to individuals with high reward sensitivity and during longer safe periods. Overall, this study is the first to suggest cognitive mechanisms underlying the greater avoidance behavior observed in healthy individuals with different anxiety vulnerabilities. PMID:25639540

Micromechanical modeling of rate-dependent behavior of Connective tissues.

PubMed

Fallah, A; Ahmadian, M T; Firozbakhsh, K; Aghdam, M M

2017-03-07

In this paper, a constitutive and micromechanical model for prediction of rate-dependent behavior of connective tissues (CTs) is presented. Connective tissues are considered as nonlinear viscoelastic material. The rate-dependent behavior of CTs is incorporated into model using the well-known quasi-linear viscoelasticity (QLV) theory. A planar wavy representative volume element (RVE) is considered based on the tissue microstructure histological evidences. The presented model parameters are identified based on the available experiments in the literature. The presented constitutive model introduced to ABAQUS by means of UMAT subroutine. Results show that, monotonic uniaxial test predictions of the presented model at different strain rates for rat tail tendon (RTT) and human patellar tendon (HPT) are in good agreement with experimental data. Results of incremental stress-relaxation test are also presented to investigate both instantaneous and viscoelastic behavior of connective tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Animal Models of Post-Traumatic Stress Disorder and Recent Neurobiological Insights

PubMed Central

Whitaker, Annie M.; Gilpin, Nicholas W.; Edwards, Scott

2014-01-01

Post-traumatic stress disorder (PTSD) is a complex psychiatric disorder characterized by the intrusive re-experiencing of past trauma, avoidant behavior, enhanced fear, and hyperarousal following a traumatic event in vulnerable populations. Preclinical animal models do not replicate the human condition in its entirety, but seek to mimic symptoms or endophenotypes associated with PTSD. Although many models of traumatic stress exist, few adequately capture the complex nature of the disorder and the observed individual variability in susceptibility of humans to develop PTSD. In addition, various types of stressors may produce different molecular neuroadaptations that likely contribute to the various behavioral disruptions produced by each model, although certain consistent neurobiological themes related to PTSD have emerged. For example, animal models report traumatic stress- and trauma reminder-induced alterations in neuronal activity in the amygdala and prefrontal cortex, in agreement with the human PTSD literature. Models have also provided a conceptual framework for the often observed combination of PTSD and co-morbid conditions such as alcohol use disorder (AUD). Future studies will continue to refine preclinical PTSD models in hopes of capitalizing on their potential to deliver new and more efficacious treatments for PTSD and associated psychiatric disorders. PMID:25083568

Social Dynamics Modeling and Inference

DTIC Science & Technology

2018-03-29

AFRL-AFOSR-JP-TR-2018-0027 Social Dynamics Modeling and Inference Kwang-Cheng Chen NATIONAL TAIWAN UNIVERSITY Final Report 03/29/2018 DISTRIBUTION A...DATES COVERED (From - To)      14 May 2014 to 13 May 2017 4.  TITLE AND SUBTITLE Social Dynamics Modeling and Inference 5a.  CONTRACT NUMBER 5b.  GRANT...behavior in human society, to set up the foundation of future possible inference and even control of social collective behavior. Two primary

Money Walks: Implicit Mobility Behavior and Financial Well-Being.

PubMed

Singh, Vivek Kumar; Bozkaya, Burcin; Pentland, Alex

2015-01-01

Traditional financial decision systems (e.g. credit) had to rely on explicit individual traits like age, gender, job type, and marital status, while being oblivious to spatio-temporal mobility or the habits of the individual involved. Emerging trends in geo-aware and mobile payment systems, and the resulting "big data," present an opportunity to study human consumption patterns across space and time. Taking inspiration from animal behavior studies that have reported significant interconnections between animal spatio-temporal "foraging" behavior and their life outcomes, we analyzed a corpus of hundreds of thousands of human economic transactions and found that financial outcomes for individuals are intricately linked with their spatio-temporal traits like exploration, engagement, and elasticity. Such features yield models that are 30% to 49% better at predicting future financial difficulties than the comparable demographic models.

Money Walks: Implicit Mobility Behavior and Financial Well-Being

PubMed Central

Singh, Vivek Kumar; Bozkaya, Burcin; Pentland, Alex

2015-01-01

Traditional financial decision systems (e.g. credit) had to rely on explicit individual traits like age, gender, job type, and marital status, while being oblivious to spatio-temporal mobility or the habits of the individual involved. Emerging trends in geo-aware and mobile payment systems, and the resulting “big data,” present an opportunity to study human consumption patterns across space and time. Taking inspiration from animal behavior studies that have reported significant interconnections between animal spatio-temporal “foraging” behavior and their life outcomes, we analyzed a corpus of hundreds of thousands of human economic transactions and found that financial outcomes for individuals are intricately linked with their spatio-temporal traits like exploration, engagement, and elasticity. Such features yield models that are 30% to 49% better at predicting future financial difficulties than the comparable demographic models. PMID:26317339

Acquisition and improvement of human motor skills: Learning through observation and practice

NASA Technical Reports Server (NTRS)

Iba, Wayne

1991-01-01

Skilled movement is an integral part of the human existence. A better understanding of motor skills and their development is a prerequisite to the construction of truly flexible intelligent agents. We present MAEANDER, a computational model of human motor behavior, that uniformly addresses both the acquisition of skills through observation and the improvement of skills through practice. MAEANDER consists of a sensory-effector interface, a memory of movements, and a set of performance and learning mechanisms that let it recognize and generate motor skills. The system initially acquires such skills by observing movements performed by another agent and constructing a concept hierarchy. Given a stored motor skill in memory, MAEANDER will cause an effector to behave appropriately. All learning involves changing the hierarchical memory of skill concepts to more closely correspond to either observed experience or to desired behaviors. We evaluated MAEANDER empirically with respect to how well it acquires and improves both artificial movement types and handwritten script letters from the alphabet. We also evaluate MAEANDER as a psychological model by comparing its behavior to robust phenomena in humans and by considering the richness of the predictions it makes.

The refined biomimetic NeuroDigm GEL™ model of neuropathic pain in a mature rat

PubMed Central

Hannaman, Mary R.; Fitts, Douglas A.; Doss, Rose M.; Weinstein, David E.; Bryant, Joseph L.

2017-01-01

Background: Many humans suffering with chronic neuropathic pain have no objective evidence of an etiological lesion or disease. Frequently their persistent pain occurs after the healing of a soft tissue injury. Based on clinical observations over time, our hypothesis was that after an injury in mammals the process of tissue repair could cause chronic neural pain. Our objectives were to create the delayed onset of neuropathic pain in rats with minimal nerve trauma using a physiologic hydrogel, and characterize the rats’ responses to known analgesics and a targeted biologic. Methods: In mature male Sprague Dawley rats (age 9.5 months) a percutaneous implant of tissue-derived hydrogel was placed in the musculofascial tunnel of the distal tibial nerve. Subcutaneous morphine (3 mg/kg), celecoxib (10 mg/kg), gabapentin (25 mg/kg) and duloxetine (10 mg/kg) were each screened in the model three times each over 5 months after pain behaviors developed. Sham and control groups were used in all screenings. A pilot study followed in which recombinant human erythropoietin (200 units) was injected by the GEL™ neural procedure site. Results: The GEL group gradually developed mechanical hypersensitivity lasting months. Morphine, initially effective, had less analgesia over time. Celecoxib produced no analgesia, while gabapentin and duloxetine at low doses demonstrated profound analgesia at all times tested. The injected erythropoietin markedly decreased bilateral pain behavior that had been present for over 4 months, p ≤ 0.001. Histology of the GEL group tibial nerve revealed a site of focal neural remodeling, with neural regeneration, as found in nerve biopsies of patients with neuropathic pain. Conclusion: The refined NeuroDigm GEL™ model induces a neural response resulting in robust neuropathic pain behavior. The analgesic responses in this model reflect known responses of humans with neuropathic pain. The targeted recombinant human erythropoietin at the ectopic neural lesion appears to alleviate the persistent pain behavior in the GEL™ model rodents. PMID:28620451

Gait Analysis Methods for Rodent Models of Osteoarthritis

PubMed Central

Jacobs, Brittany Y.; Kloefkorn, Heidi E.; Allen, Kyle D.

2014-01-01

Patients with osteoarthritis (OA) primarily seek treatment due to pain and disability, yet the primary endpoints for rodent OA models tend to be histological measures of joint destruction. The discrepancy between clinical and preclinical evaluations is problematic, given that radiographic evidence of OA in humans does not always correlate to the severity of patient-reported symptoms. Recent advances in behavioral analyses have provided new methods to evaluate disease sequelae in rodents. Of particular relevance to rodent OA models are methods to assess rodent gait. While obvious differences exist between quadrupedal and bipedal gait sequences, the gait abnormalities seen in humans and in rodent OA models reflect similar compensatory behaviors that protect an injured limb from loading. The purpose of this review is to describe these compensations and current methods used to assess rodent gait characteristics, while detailing important considerations for the selection of gait analysis methods in rodent OA models. PMID:25160712

A Car-Steering Model Based on an Adaptive Neuro-Fuzzy Controller

NASA Astrophysics Data System (ADS)

Amor, Mohamed Anis Ben; Oda, Takeshi; Watanabe, Shigeyoshi

This paper is concerned with the development of a car-steering model for traffic simulation. Our focus in this paper is to propose a model of the steering behavior of a human driver for different driving scenarios. These scenarios are modeled in a unified framework using the idea of target position. The proposed approach deals with the driver’s approximation and decision-making mechanisms in tracking a target position by means of fuzzy set theory. The main novelty in this paper lies in the development of a learning algorithm that has the intention to imitate the driver’s self-learning from his driving experience and to mimic his maneuvers on the steering wheel, using linear networks as local approximators in the corresponding fuzzy areas. Results obtained from the simulation of an obstacle avoidance scenario show the capability of the model to carry out a human-like behavior with emphasis on learned skills.

Technical advance: live-imaging analysis of human dendritic cell migrating behavior under the influence of immune-stimulating reagents in an organotypic model of lung.

PubMed

Nguyen Hoang, Anh Thu; Chen, Puran; Björnfot, Sofia; Högstrand, Kari; Lock, John G; Grandien, Alf; Coles, Mark; Svensson, Mattias

2014-09-01

This manuscript describes technical advances allowing manipulation and quantitative analyses of human DC migratory behavior in lung epithelial tissue. DCs are hematopoietic cells essential for the maintenance of tissue homeostasis and the induction of tissue-specific immune responses. Important functions include cytokine production and migration in response to infection for the induction of proper immune responses. To design appropriate strategies to exploit human DC functional properties in lung tissue for the purpose of clinical evaluation, e.g., candidate vaccination and immunotherapy strategies, we have developed a live-imaging assay based on our previously described organotypic model of the human lung. This assay allows provocations and subsequent quantitative investigations of DC functional properties under conditions mimicking morphological and functional features of the in vivo parental tissue. We present protocols to set up and prepare tissue models for 4D (x, y, z, time) fluorescence-imaging analysis that allow spatial and temporal studies of human DCs in live epithelial tissue, followed by flow cytometry analysis of DCs retrieved from digested tissue models. This model system can be useful for elucidating incompletely defined pathways controlling DC functional responses to infection and inflammation in lung epithelial tissue, as well as the efficacy of locally administered candidate interventions. © 2014 Society for Leukocyte Biology.

DYT1 dystonia increases risk taking in humans.

PubMed

Arkadir, David; Radulescu, Angela; Raymond, Deborah; Lubarr, Naomi; Bressman, Susan B; Mazzoni, Pietro; Niv, Yael

2016-06-01

It has been difficult to link synaptic modification to overt behavioral changes. Rodent models of DYT1 dystonia, a motor disorder caused by a single gene mutation, demonstrate increased long-term potentiation and decreased long-term depression in corticostriatal synapses. Computationally, such asymmetric learning predicts risk taking in probabilistic tasks. Here we demonstrate abnormal risk taking in DYT1 dystonia patients, which is correlated with disease severity, thereby supporting striatal plasticity in shaping choice behavior in humans.

A reverse-translational study of dysfunctional exploration in psychiatric disorders: from mice to men.

PubMed

Perry, William; Minassian, Arpi; Paulus, Martin P; Young, Jared W; Kincaid, Meegin J; Ferguson, Eliza J; Henry, Brook L; Zhuang, Xiaoxi; Masten, Virginia L; Sharp, Richard F; Geyer, Mark A

2009-10-01

Bipolar mania and schizophrenia are recognized as separate disorders but share many commonalities, which raises the question of whether they are the same disorder on different ends of a continuum. The lack of distinct endophenotypes of bipolar mania and schizophrenia has complicated the development of animal models that are specific to these disorders. Exploration is fundamental to survival and is dysregulated in these 2 disorders. Although exploratory behavior in rodents has been widely studied, surprisingly little work has examined this critical function in humans. To quantify the exploratory behavior of individuals with bipolar mania and schizophrenia and to identify distinctive phenotypes of these illnesses. Static group comparison by the use of a novel human open field paradigm, the human Behavioral Pattern Monitor (BPM). Psychiatric hospital. Fifteen patients with bipolar mania and 16 patients with schizophrenia were compared with 26 healthy volunteers in the human BPM. The effects of amphetamine sulfate, the selective dopamine transporter inhibitor GBR12909, and the genetic knockdown of the dopamine transporter were compared with controls in the mouse BPM. The amount of motor activity, spatial patterns of activity, and exploration of novel stimuli were quantified in both the human and mouse BPMs. Patients with bipolar mania demonstrated a unique exploratory pattern, characterized by high motor activity and increased object exploration. Patients with schizophrenia did not show the expected habituation of motor activity. Selective genetic or pharmacologic inhibition of the dopamine transporter matched the mania phenotype better than the effects of amphetamine, which has been the criterion standard for animal models of mania. These findings validate the human open field paradigm and identify defining characteristics of bipolar mania that are distinct from those of schizophrenia. This cross-species study of exploration calls into question an accepted animal model of mania and should help to develop more accurate human and animal models, which are essential to the identification of the neurobiological underpinnings of neuropsychiatric disorders.

A reverse translational study of dysfunctional exploration in psychiatric disorders: from mice to men

PubMed Central

Perry, William; Minassian, Arpi; Paulus, Martin P.; Young, Jared W.; Kincaid, Meegin J.; Ferguson, Eliza J.; Henry, Brook L.; Zhuang, Xiaoxi; Masten, Virginia L.; Sharp, Richard F.; Geyer, Mark A.

2009-01-01

Context Bipolar mania and schizophrenia are recognized as separate disorders but share many commonalities, raising the question of whether they are in fact the same disorder on different ends of a continuum. The lack of distinct endophenotypes of bipolar mania and schizophrenia has complicated the development of animal models that are specific to these disorders. Exploration is fundamental to survival and is dysregulated in these two disorders. Although exploratory behavior in rodents has been widely studied, surprisingly little work has examined this critical function in humans. Objective We used a novel human open field paradigm, the human Behavioral Pattern Monitor (BPM), to quantify exploratory behavior of individuals with bipolar mania and schizophrenia and to identify distinctive phenotypes of these illnesses. Design Static group comparison. Setting Psychiatric hospital. Participants 15 bipolar mania and 16 schizophrenia subjects were compared to 26 healthy volunteers in the human BPM. The effects of amphetamine, the selective dopamine transporter (DAT) inhibitor GBR12909, and genetic knockdown of the DAT were compared to controls in the mouse BPM. Measures The amount of motor activity, spatial patterns of activity, and exploration of novel stimuli were quantified in both the human and mouse BPMs. Results Bipolar manic subjects demonstrated a unique exploratory pattern, characterized by high motor activity and increased object exploration. Schizophrenia subjects did not show the expected habituation of motor activity. Selective genetic or pharmacological inhibition of the DAT matched the mania phenotype better than the “gold standard” model of mania (amphetamine). Conclusion These findings validate the human open field paradigm and identify defining characteristics of bipolar mania that are distinct from schizophrenia. This cross-species study of exploration calls into question an accepted animal model of mania and should help to develop more accurate human and animal models, which are essential to identify neurobiological underpinnings of neuropsychiatric disorders. PMID:19805697

The Modeling of Human Intelligence in the Computer as Demonstrated in the Game of DIPLOMAT.

ERIC Educational Resources Information Center

Collins, James Edward; Paulsen, Thomas Dean

An attempt was made to develop human-like behavior in the computer. A theory of the human learning process was described. A computer game was presented which simulated the human capabilities of reasoning and learning. The program was required to make intelligent decisions based on past experiences and critical analysis of the present situation.…

Attentional Switching in Humans and Flies: Rivalry in Large and Miniature Brains

PubMed Central

Miller, Steven Mark; Ngo, Trung Thanh; van Swinderen, Bruno

2012-01-01

Human perception, and consequently behavior, is driven by attention dynamics. In the special case of rivalry, where attention alternates between competing percepts, such dynamics can be measured and their determinants investigated. A recent study in the fruit fly, Drosophila melanogaster, now shows that the origins of attentional rivalry may be quite ancient. Furthermore, individual variation exists in the rate of attentional rivalry in both humans and flies, and in humans this is under substantial genetic influence. In the pathophysiological realm, slowing of rivalry rate is associated with the heritable psychiatric condition, bipolar disorder. Fly rivalry may therefore prove a powerful model to examine genetic and molecular influences on rivalry rate, and may even shed light on human cognitive and behavioral dysfunction. PMID:22279432

Wetware, Hardware, or Software Incapacitation: Observational Methods to Determine When Autonomy Should Assume Control

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.

2014-01-01

Control-theoretic modeling of human operator's dynamic behavior in manual control tasks has a long, rich history. There has been significant work on techniques used to identify the pilot model of a given structure. This research attempts to go beyond pilot identification based on experimental data to develop a predictor of pilot behavior. Two methods for pre-dicting pilot stick input during changing aircraft dynamics and deducing changes in pilot behavior are presented This approach may also have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot. With this ability to detect changes in piloting behavior, the possibility now exists to mediate human adverse behaviors, hardware failures, and software anomalies with autono-my that may ameliorate these undesirable effects. However, appropriate timing of when au-tonomy should assume control is dependent on criticality of actions to safety, sensitivity of methods to accurately detect these adverse changes, and effects of changes in levels of auto-mation of the system as a whole.

SlgA, encoded by the homolog of the human schizophrenia-associated gene PRODH, acts in clock neurons to regulate Drosophila aggression.

PubMed

Zwarts, Liesbeth; Vulsteke, Veerle; Buhl, Edgar; Hodge, James J L; Callaerts, Patrick

2017-06-01

Mutations in the proline dehydrogenase gene PRODH are linked to behavioral alterations in schizophrenia and as part of DiGeorge and velo-cardio-facial syndromes, but the role of PRODH in their etiology remains unclear. Here, we establish a Drosophila model to study the role of PRODH in behavioral disorders. We determine the distribution of the Drosophila PRODH homolog slgA in the brain and show that knockdown and overexpression of human PRODH and slgA in the lateral neurons ventral (LNv) lead to altered aggressive behavior. SlgA acts in an isoform-specific manner and is regulated by casein kinase II (CkII). Our data suggest that these effects are, at least partially, due to effects on mitochondrial function. We thus show that precise regulation of proline metabolism is essential to drive normal behavior and we identify Drosophila aggression as a model behavior relevant for the study of the mechanisms that are impaired in neuropsychiatric disorders. © 2017. Published by The Company of Biologists Ltd.

Is there an association between hypercholesterolemia and depression? Behavioral evidence from the LDLr(-/-) mouse experimental model.

PubMed

Engel, Daiane Fátima; de Oliveira, Jade; Lopes, Jadna Bogado; Santos, Danúbia Bonfanti; Moreira, Eduardo Luiz Gasnhar; Farina, Marcelo; Rodrigues, Ana Lúcia S; de Souza Brocardo, Patricia; de Bem, Andreza Fabro

2016-09-15

Although epidemiological studies have reported an association between hypercholesterolemia and mood disorders, there is a lack of data regarding depressive-like behavior in animal models of hypercholesterolemia. To address these questions, we assessed depressive-like behavior and hippocampal and cortical monoaminergic metabolism in three-month-old, low-density lipoprotein receptor knockout (LDLr(-/-)) and C57BL/6 wild-type mice. The LDLr(-/-) mice exhibited depressive-like behavior in the sucrose preference test, splash test, and tail suspension test. Increased monoamine oxidase (MAO) A and B activity was evidenced in the hippocampus of LDLr(-/-) mice. Furthermore, to address whether or not cholesterol modulates MAO activity, we exposed SH-SY5Y human neuroblastoma cells to human isolated low-density lipoprotein (LDL). Notably, LDL increased the activity of MAO-A and stimulated the reactive species generation in vitro. These findings indicate that depressive-like behavior in hypercholesterolemic mice is accompanied by alterations in the monoaminergic metabolism, providing new evidence about the association between hypercholesterolemia and depression. Copyright © 2016. Published by Elsevier B.V.

Rhetorical Consequences of the Computer Society: Expert Systems and Human Communication.

ERIC Educational Resources Information Center

Skopec, Eric Wm.

Expert systems are computer programs that solve selected problems by modelling domain-specific behaviors of human experts. These computer programs typically consist of an input/output system that feeds data into the computer and retrieves advice, an inference system using the reasoning and heuristic processes of human experts, and a knowledge…

Controlling for selection effects in the relationship between child behavior problems and exposure to intimate partner violence.

PubMed

Emery, Clifton R

2011-05-01

This article used the Project on Human Development in Chicago Neighborhoods (PHDCN) data to examine the relationship between exposure to intimate partner violence (IPV) and child behavior problems (externalizing and internalizing), truancy, grade repetition, smoking, drinking, and use of marijuana. Longitudinal data analysis was conducted on 1,816 primary caregivers and their children. Fixed-effects regression models were employed to address concerns with selection bias. IPV was associated with significantly greater internalizing behavior, externalizing behavior, and truancy. Findings from age interaction models suggested that the relationship between IPV and child behavior problems may attenuate as the age of the child at time of exposure increases.

From an animal model to human patients: An example of a translational study on obsessive compulsive disorder (OCD).

PubMed

Eilam, David

2017-05-01

The application of similar analyses enables a direct projection from translational research in animals to human studies. Following is an example of how the methodology of a specific animal model of obsessive-compulsive disorder (OCD) was applied to study human patients. Specifically, the quinpirole rat model for OCD was based on analyzing the trajectories of travel among different locales, and scoring the set of acts performed at each locale. Applying this analytic approach in human patients unveiled various aspects of OCD, such as the repetition and addition of acts, incompleteness, and the link between behavior and specific locations. It is also illustrated how the same analytical approach could be applicable to studying other mental disorders. Finally, it is suggested that the development of OCD could be explained by the four-phase sequence of Repetition, Addition, Condensation, and Elimination, as outlined in the study of ontogeny and phylogeny and applied to normal development of behavior. In OCD, this sequence is curtailed, resulting in the abundant repetition and addition of acts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Implications of genetic research on the role of the serotonin in depression: emphasis on the serotonin type 1A receptor and the serotonin transporter.

PubMed

Neumeister, Alexander; Young, Theresa; Stastny, Juergen

2004-08-01

Serotonin systems appear to play a key role in the pathophysiology of major depressive disorder. Consequently, ongoing research determines whether serotonin related genes account for the very robust differential behavioral and neural mechanisms that discriminate patients with depression from healthy controls. Serotonin type 1(A) receptors and the serotonin transporters are reduced in depression, and recent genetic research in animals and humans has implicated both in depression. Preclinical studies have utilized a variety of animal models that have been used to explain pathophysiological mechanisms in humans, although it is not clear at all whether these models constitute relevant models for depression in humans. However, data from preclinical studies can generate hypotheses that are tested in humans by combining genetic data with behavioral and physiological challenge paradigms and neuroimaging. These studies will enhance our understanding about combined influences from multiple interacting genes, as well as from environmental factors on brain circuits and their function, and about how these mechanisms may contribute to the pathophysiology of neuropsychiatric disorders.

Human factors phase IV : risk analysis tool for new train control technology.

DOT National Transportation Integrated Search

2005-01-31

This report covers the theoretical development of the safety state model for railroad operations. Using data from a train control technology experiment, experimental application of the model is demonstrated. A stochastic model of system behavior is d...

Human factors phase IV : risk analysis tool for new train control technology

DOT National Transportation Integrated Search

2005-01-01

This report covers the theoretical development of the safety state model for railroad operations. Using data from a train control technology experiment, experimental application of the model is demonstrated. A stochastic model of system behavior is d...

Modeling choice and reaction time during arbitrary visuomotor learning through the coordination of adaptive working memory and reinforcement learning

PubMed Central

Viejo, Guillaume; Khamassi, Mehdi; Brovelli, Andrea; Girard, Benoît

2015-01-01

Current learning theory provides a comprehensive description of how humans and other animals learn, and places behavioral flexibility and automaticity at heart of adaptive behaviors. However, the computations supporting the interactions between goal-directed and habitual decision-making systems are still poorly understood. Previous functional magnetic resonance imaging (fMRI) results suggest that the brain hosts complementary computations that may differentially support goal-directed and habitual processes in the form of a dynamical interplay rather than a serial recruitment of strategies. To better elucidate the computations underlying flexible behavior, we develop a dual-system computational model that can predict both performance (i.e., participants' choices) and modulations in reaction times during learning of a stimulus–response association task. The habitual system is modeled with a simple Q-Learning algorithm (QL). For the goal-directed system, we propose a new Bayesian Working Memory (BWM) model that searches for information in the history of previous trials in order to minimize Shannon entropy. We propose a model for QL and BWM coordination such that the expensive memory manipulation is under control of, among others, the level of convergence of the habitual learning. We test the ability of QL or BWM alone to explain human behavior, and compare them with the performance of model combinations, to highlight the need for such combinations to explain behavior. Two of the tested combination models are derived from the literature, and the latter being our new proposal. In conclusion, all subjects were better explained by model combinations, and the majority of them are explained by our new coordination proposal. PMID:26379518

Control Theory and Statistical Generalizations.

ERIC Educational Resources Information Center

Powers, William T.

1990-01-01

Contrasts modeling methods in control theory to the methods of statistical generalizations in empirical studies of human or animal behavior. Presents a computer simulation that predicts behavior based on variables (effort and rewards) determined by the invariable (desired reward). Argues that control theory methods better reflect relationships to…

PFIESTERIA PISCICIDA-INDUCED COGNITIVE EFFECTS: VISUAL SIGNAL DETECTION PERFORMANCE AND REVERSAL.

EPA Science Inventory

Humans exposed to Pfiesteria piscicida report cognitive impairment. In a rat model, we showed that exposure to Pfiesteria impaired learning a new task, but not performance of previously-learned behavior. In this study, we characterized the behavioral effects of Pfiesteria in rats...

Investigating the effects of roadway design on driver behavior : applications for Minnesota highway design

DOT National Transportation Integrated Search

1999-02-01

This report details a project to study the relationship between highway design and human behavior as influenced by roadside environments. The project was developed in two phases. In the visualization phase, computer simulation was used to model an ac...

Metaphors to Drive By: Exploring New Ways to Guide Human-Robot Interaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

David J. Bruemmer; David I. Gertman; Curtis W. Nielsen

2007-08-01

Autonomous behaviors created by the research and development community are not being extensively utilized within energy, defense, security, or industrial contexts. This paper provides evidence that the interaction methods used alongside these behaviors may not provide a mental model that can be easily adopted or used by operators. Although autonomy has the potential to reduce overall workload, the use of robot behaviors often increased the complexity of the underlying interaction metaphor. This paper reports our development of new metaphors that support increased robot complexity without passing the complexity of the interaction onto the operator. Furthermore, we illustrate how recognition ofmore » problems in human-robot interactions can drive the creation of new metaphors for design and how human factors lessons in usability, human performance, and our social contract with technology have the potential for enormous payoff in terms of establishing effective, user-friendly robot systems when appropriate metaphors are used.« less

Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models

PubMed Central

Soto-Icaza, Patricia; Aboitiz, Francisco; Billeke, Pablo

2015-01-01

Social skills refer to a wide group of abilities that allow us to interact and communicate with others. Children learn how to solve social situations by predicting and understanding other's behaviors. The way in which humans learn to interact successfully with others encompasses a complex interaction between neural, behavioral, and environmental elements. These have a role in the accomplishment of positive developmental outcomes, including peer acceptance, academic achievement, and mental health. All these social abilities depend on widespread brain networks that are recently being studied by neuroscience. In this paper, we will first review the studies on this topic, aiming to clarify the behavioral and neural mechanisms related to the acquisition of social skills during infancy and their appearance in time. Second, we will briefly describe how developmental diseases like Autism Spectrum Disorders (ASD) can inform about the neurobiological mechanisms of social skills. We finally sketch a general framework for the elaboration of cognitive models in order to facilitate the comprehension of human social development. PMID:26483621

Predicting human papillomavirus vaccine uptake in young adult women: Comparing the Health Belief Model and Theory of Planned Behavior

PubMed Central

Gerend, Mary A.; Shepherd, Janet E.

2012-01-01

Background Although theories of health behavior have guided thousands of studies, relatively few studies have compared these theories against one another. Purpose The purpose of the current study was to compare two classic theories of health behavior—the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB)—in their prediction of human papillomavirus (HPV) vaccination. Methods After watching a gain-framed, loss-framed, or control video, women (N=739) ages 18–26 completed a survey assessing HBM and TPB constructs. HPV vaccine uptake was assessed ten months later. Results Although the message framing intervention had no effect on vaccine uptake, support was observed for both the TPB and HBM. Nevertheless, the TPB consistently outperformed the HBM. Key predictors of uptake included subjective norms, self-efficacy, and vaccine cost. Conclusions Despite the observed advantage of the TPB, findings revealed considerable overlap between the two theories and highlighted the importance of proximal versus distal predictors of health behavior. PMID:22547155

Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models.

PubMed

Soto-Icaza, Patricia; Aboitiz, Francisco; Billeke, Pablo

2015-01-01

Social skills refer to a wide group of abilities that allow us to interact and communicate with others. Children learn how to solve social situations by predicting and understanding other's behaviors. The way in which humans learn to interact successfully with others encompasses a complex interaction between neural, behavioral, and environmental elements. These have a role in the accomplishment of positive developmental outcomes, including peer acceptance, academic achievement, and mental health. All these social abilities depend on widespread brain networks that are recently being studied by neuroscience. In this paper, we will first review the studies on this topic, aiming to clarify the behavioral and neural mechanisms related to the acquisition of social skills during infancy and their appearance in time. Second, we will briefly describe how developmental diseases like Autism Spectrum Disorders (ASD) can inform about the neurobiological mechanisms of social skills. We finally sketch a general framework for the elaboration of cognitive models in order to facilitate the comprehension of human social development.

SIGNAL DETECTION BEHAVIOR IN HUMANS AND RATS: A COMPARISON WITH MATCHED TASKS.

EPA Science Inventory

Animal models of human cognitive processes are essential for studying the neurobiological mechanisms of these processes and for developing therapies for intoxication and neurodegenerative diseases. A discrete-trial signal detection task was developed for assessing sustained atten...

Maladaptive “Gambling” by Pigeons

PubMed Central

Zentall, Thomas R.

2012-01-01

When humans buy a lottery ticket or gamble at a casino they are engaging in an activity that on average leads to a loss of money. Although animals are purported to engage in optimal foraging behavior, similar sub-optimal behavior can be found in pigeons, They show a preference for an alternative that is associated with a low probability of reinforcement (e.g., one that is followed by a red hue on 20% of the trials and then reinforcement or by a green hue on 80% of the trials and then the absence of reinforcement) over an alternative that is associated with a higher probability of reinforcement (e.g., blue or yellow each of which is followed by reinforcement 50% of the time). This effect appears to result from the strong conditioned reinforcement associated with the stimulus that is always followed by reinforcement. Surprisingly, although it is experienced four times as much, the stimulus that is never followed by reinforcement does not appear to result in significant conditioned inhibition (perhaps due to the absence of observing behavior). Similarly, human gamblers tend to overvalue wins and undervalue losses. Thus, this animal model may provide a useful analog to human gambling behavior, one that is free from the influence of human culture, language, social reinforcement, and other experiential biases that may influence human gambling behavior. PMID:21215301

Interaction studies reveal specific recognition of an anti-inflammatory polyphosphorhydrazone dendrimer by human monocytes

NASA Astrophysics Data System (ADS)

Ledall, Jérémy; Fruchon, Séverine; Garzoni, Matteo; Pavan, Giovanni M.; Caminade, Anne-Marie; Turrin, Cédric-Olivier; Blanzat, Muriel; Poupot, Rémy

2015-10-01

Dendrimers are nano-materials with perfectly defined structure and size, and multivalency properties that confer substantial advantages for biomedical applications. Previous work has shown that phosphorus-based polyphosphorhydrazone (PPH) dendrimers capped with azabisphosphonate (ABP) end groups have immuno-modulatory and anti-inflammatory properties leading to efficient therapeutic control of inflammatory diseases in animal models. These properties are mainly prompted through activation of monocytes. Here, we disclose new insights into the molecular mechanisms underlying the anti-inflammatory activation of human monocytes by ABP-capped PPH dendrimers. Following an interdisciplinary approach, we have characterized the physicochemical and biological behavior of the lead ABP dendrimer with model and cell membranes, and compared this experimental set of data to predictive computational modelling studies. The behavior of the ABP dendrimer was compared to the one of an isosteric analog dendrimer capped with twelve azabiscarboxylate (ABC) end groups instead of twelve ABP end groups. The ABC dendrimer displayed no biological activity on human monocytes, therefore it was considered as a negative control. In detail, we show that the ABP dendrimer can bind both non-specifically and specifically to the membrane of human monocytes. The specific binding leads to the internalization of the ABP dendrimer by human monocytes. On the contrary, the ABC dendrimer only interacts non-specifically with human monocytes and is not internalized. These data indicate that the bioactive ABP dendrimer is recognized by specific receptor(s) at the surface of human monocytes.Dendrimers are nano-materials with perfectly defined structure and size, and multivalency properties that confer substantial advantages for biomedical applications. Previous work has shown that phosphorus-based polyphosphorhydrazone (PPH) dendrimers capped with azabisphosphonate (ABP) end groups have immuno-modulatory and anti-inflammatory properties leading to efficient therapeutic control of inflammatory diseases in animal models. These properties are mainly prompted through activation of monocytes. Here, we disclose new insights into the molecular mechanisms underlying the anti-inflammatory activation of human monocytes by ABP-capped PPH dendrimers. Following an interdisciplinary approach, we have characterized the physicochemical and biological behavior of the lead ABP dendrimer with model and cell membranes, and compared this experimental set of data to predictive computational modelling studies. The behavior of the ABP dendrimer was compared to the one of an isosteric analog dendrimer capped with twelve azabiscarboxylate (ABC) end groups instead of twelve ABP end groups. The ABC dendrimer displayed no biological activity on human monocytes, therefore it was considered as a negative control. In detail, we show that the ABP dendrimer can bind both non-specifically and specifically to the membrane of human monocytes. The specific binding leads to the internalization of the ABP dendrimer by human monocytes. On the contrary, the ABC dendrimer only interacts non-specifically with human monocytes and is not internalized. These data indicate that the bioactive ABP dendrimer is recognized by specific receptor(s) at the surface of human monocytes. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr03884g

Lumped parametric model of the human ear for sound transmission.

PubMed

Feng, Bin; Gan, Rong Z

2004-09-01

A lumped parametric model of the human auditoria peripherals consisting of six masses suspended with six springs and ten dashpots was proposed. This model will provide the quantitative basis for the construction of a physical model of the human middle ear. The lumped model parameters were first identified using published anatomical data, and then determined through a parameter optimization process. The transfer function of the middle ear obtained from human temporal bone experiments with laser Doppler interferometers was used for creating the target function during the optimization process. It was found that, among 14 spring and dashpot parameters, there were five parameters which had pronounced effects on the dynamic behaviors of the model. The detailed discussion on the sensitivity of those parameters was provided with appropriate applications for sound transmission in the ear. We expect that the methods for characterizing the lumped model of the human ear and the model parameters will be useful for theoretical modeling of the ear function and construction of the ear physical model.

Assistance dogs provide a useful behavioral model to enrich communicative skills of assistance robots.

PubMed

Gácsi, Márta; Szakadát, Sára; Miklósi, Adám

2013-01-01

These studies are part of a project aiming to reveal relevant aspects of human-dog interactions, which could serve as a model to design successful human-robot interactions. Presently there are no successfully commercialized assistance robots, however, assistance dogs work efficiently as partners for persons with disabilities. In Study 1, we analyzed the cooperation of 32 assistance dog-owner dyads performing a carrying task. We revealed typical behavior sequences and also differences depending on the dyads' experiences and on whether the owner was a wheelchair user. In Study 2, we investigated dogs' responses to unforeseen difficulties during a retrieving task in two contexts. Dogs displayed specific communicative and displacement behaviors, and a strong commitment to execute the insoluble task. Questionnaire data from Study 3 confirmed that these behaviors could successfully attenuate owners' disappointment. Although owners anticipated the technical competence of future assistance robots to be moderate/high, they could not imagine robots as emotional companions, which negatively affected their acceptance ratings of future robotic assistants. We propose that assistance dogs' cooperative behaviors and problem solving strategies should inspire the development of the relevant functions and social behaviors of assistance robots with limited manual and verbal skills.

Naturally-Occurring Canine Invasive Urothelial Carcinoma: A Model for Emerging Therapies

PubMed Central

Sommer, Breann C.; Dhawan, Deepika; Ratliff, Timothy L.; Knapp, Deborah W.

2018-01-01

The development of targeted therapies and the resurgence of immunotherapy offer enormous potential to dramatically improve the outlook for patients with invasive urothelial carcinoma (InvUC). Optimization of these therapies, however, is crucial as only a minority of patients achieve dramatic remission, and toxicities are common. With the complexities of the therapies, and the growing list of possible drug combinations to test, highly relevant animal models are needed to assess and select the most promising approaches to carry forward into human trials. The animal model(s) should possess key features that dictate success or failure of cancer drugs in humans including tumor heterogeneity, genetic-epigenetic crosstalk, immune cell responsiveness, invasive and metastatic behavior, and molecular subtypes (e.g., luminal, basal). While it may not be possible to create these collective features in experimental models, these features are present in naturally-occurring InvUC in pet dogs. Naturally occurring canine InvUC closely mimics muscle-invasive bladder cancer in humans in regards to cellular and molecular features, molecular subtypes, biological behavior (sites and frequency of metastasis), and response to therapy. Clinical treatment trials in pet dogs with InvUC are considered a win-win scenario; the individual dog benefits from effective treatment, the results are expected to help other dogs, and the findings are expected to translate to better treatment outcomes in humans. This review will provide an overview of canine InvUC, the similarities to the human condition, and the potential for dogs with InvUC to serve as a model to predict the outcomes of targeted therapy and immunotherapy in humans. PMID:29732386

Naturally-Occurring Canine Invasive Urothelial Carcinoma: A Model for Emerging Therapies.

PubMed

Sommer, Breann C; Dhawan, Deepika; Ratliff, Timothy L; Knapp, Deborah W

2018-04-26

The development of targeted therapies and the resurgence of immunotherapy offer enormous potential to dramatically improve the outlook for patients with invasive urothelial carcinoma (InvUC). Optimization of these therapies, however, is crucial as only a minority of patients achieve dramatic remission, and toxicities are common. With the complexities of the therapies, and the growing list of possible drug combinations to test, highly relevant animal models are needed to assess and select the most promising approaches to carry forward into human trials. The animal model(s) should possess key features that dictate success or failure of cancer drugs in humans including tumor heterogeneity, genetic-epigenetic crosstalk, immune cell responsiveness, invasive and metastatic behavior, and molecular subtypes (e.g., luminal, basal). While it may not be possible to create these collective features in experimental models, these features are present in naturally-occurring InvUC in pet dogs. Naturally occurring canine InvUC closely mimics muscle-invasive bladder cancer in humans in regards to cellular and molecular features, molecular subtypes, biological behavior (sites and frequency of metastasis), and response to therapy. Clinical treatment trials in pet dogs with InvUC are considered a win-win scenario; the individual dog benefits from effective treatment, the results are expected to help other dogs, and the findings are expected to translate to better treatment outcomes in humans. This review will provide an overview of canine InvUC, the similarities to the human condition, and the potential for dogs with InvUC to serve as a model to predict the outcomes of targeted therapy and immunotherapy in humans.

Simulating closed- and open-loop voluntary movement: a nonlinear control-systems approach.

PubMed

Davidson, Paul R; Jones, Richard D; Andreae, John H; Sirisena, Harsha R

2002-11-01

In many recent human motor control models, including feedback-error learning and adaptive model theory (AMT), feedback control is used to correct errors while an inverse model is simultaneously tuned to provide accurate feedforward control. This popular and appealing hypothesis, based on a combination of psychophysical observations and engineering considerations, predicts that once the tuning of the inverse model is complete the role of feedback control is limited to the correction of disturbances. This hypothesis was tested by looking at the open-loop behavior of the human motor system during adaptation. An experiment was carried out involving 20 normal adult subjects who learned a novel visuomotor relationship on a pursuit tracking task with a steering wheel for input. During learning, the response cursor was periodically blanked, removing all feedback about the external system (i.e., about the relationship between hand motion and response cursor motion). Open-loop behavior was not consistent with a progressive transfer from closed- to open-loop control. Our recently developed computational model of the brain--a novel nonlinear implementation of AMT--was able to reproduce the observed closed- and open-loop results. In contrast, other control-systems models exhibited only minimal feedback control following adaptation, leading to incorrect open-loop behavior. This is because our model continues to use feedback to control slow movements after adaptation is complete. This behavior enhances the internal stability of the inverse model. In summary, our computational model is currently the only motor control model able to accurately simulate the closed- and open-loop characteristics of the experimental response trajectories.

"Sexy stimulants": the interaction between psychomotor stimulants and sexual behavior in the female brain.

PubMed

Guarraci, Fay A; Bolton, Jessica L

2014-06-01

Research indicates gender differences in sensitivity to psychomotor stimulants. Preclinical work investigating the interaction between drugs of abuse and sex-specific behaviors, such as sexual behavior, is critical to our understanding of such gender differences in humans. A number of behavioral paradigms can be used to model aspects of human sexual behavior in animal subjects. Although traditional assessment of the reflexive, lordosis posture of the female rat has been used to map the neuroanatomical and neurochemical systems that contribute to uniquely female copulatory behavior, the additional behavioral paradigms discussed in the current review have helped us expand our description of the appetitive and consummatory patterns of sexual behavior in the female rat. Measuring appetitive behavior is particularly important for assessing sexual motivation, the equivalent of "desire" in humans. By investigating the effects of commonly abused drugs on female sexual motivation, we are beginning to elucidate the role of dopaminergic neurotransmission, a neural system also known to be critical to the neurobiology of drug addiction, in female sexual motivation. A better understanding of the nexus of sex and drugs in the female brain will help advance our understanding of motivation in general and explain how psychomotor stimulants affect males and females differently. Copyright © 2013 Elsevier Inc. All rights reserved.

A Data-Driven Approach to Reverse Engineering Customer Engagement Models: Towards Functional Constructs

PubMed Central

de Vries, Natalie Jane; Carlson, Jamie; Moscato, Pablo

2014-01-01

Online consumer behavior in general and online customer engagement with brands in particular, has become a major focus of research activity fuelled by the exponential increase of interactive functions of the internet and social media platforms and applications. Current research in this area is mostly hypothesis-driven and much debate about the concept of Customer Engagement and its related constructs remains existent in the literature. In this paper, we aim to propose a novel methodology for reverse engineering a consumer behavior model for online customer engagement, based on a computational and data-driven perspective. This methodology could be generalized and prove useful for future research in the fields of consumer behaviors using questionnaire data or studies investigating other types of human behaviors. The method we propose contains five main stages; symbolic regression analysis, graph building, community detection, evaluation of results and finally, investigation of directed cycles and common feedback loops. The ‘communities’ of questionnaire items that emerge from our community detection method form possible ‘functional constructs’ inferred from data rather than assumed from literature and theory. Our results show consistent partitioning of questionnaire items into such ‘functional constructs’ suggesting the method proposed here could be adopted as a new data-driven way of human behavior modeling. PMID:25036766

A data-driven approach to reverse engineering customer engagement models: towards functional constructs.

PubMed

de Vries, Natalie Jane; Carlson, Jamie; Moscato, Pablo

2014-01-01

Online consumer behavior in general and online customer engagement with brands in particular, has become a major focus of research activity fuelled by the exponential increase of interactive functions of the internet and social media platforms and applications. Current research in this area is mostly hypothesis-driven and much debate about the concept of Customer Engagement and its related constructs remains existent in the literature. In this paper, we aim to propose a novel methodology for reverse engineering a consumer behavior model for online customer engagement, based on a computational and data-driven perspective. This methodology could be generalized and prove useful for future research in the fields of consumer behaviors using questionnaire data or studies investigating other types of human behaviors. The method we propose contains five main stages; symbolic regression analysis, graph building, community detection, evaluation of results and finally, investigation of directed cycles and common feedback loops. The 'communities' of questionnaire items that emerge from our community detection method form possible 'functional constructs' inferred from data rather than assumed from literature and theory. Our results show consistent partitioning of questionnaire items into such 'functional constructs' suggesting the method proposed here could be adopted as a new data-driven way of human behavior modeling.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

PubMed Central

Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

2015-01-01

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

Humanizing Aggregated Data: Developing Personas to Prioritize User Needs for Earthquake Early Warning

NASA Astrophysics Data System (ADS)

Burkett, E. R.; Jayanty, N. K.; Sellnow, D. D.; Given, D. D.; DeGroot, R. M.

2016-12-01

Methods that use storytelling to gather and synthesize data from people can be advantageous in understanding user needs and designing successful communication products. Using a multidisciplinary approach, we research and prioritize user needs for the ShakeAlert Earthquake Early Warning system (http://pubs.usgs.gov/fs/2014/3083/), drawing on best practices from social and behavioral science, risk communication, and human-centered design. We apply quantitative and qualitative human data collection methods including user surveys, interviews, journey maps, personas, and scenarios. Human-centered design methods leverage storytelling (a) in the acquisition of qualitative behavioral data (e.g. with journey mapping), (b) through goal-driven behaviors and needs that are synthesized into a persona as a composite model of the data, and (c) within context scenarios (the story plot or projected circumstances) in which the persona is placed in context to inform the design of relevant and usable products or services. ShakeAlert, operated by the USGS and partners, has transitioned into a production prototype phase in which users are permitted to begin testing pilot implementations to take protective actions in response to an earthquake alert. While a subset of responses will be automated (e.g., opening fire house doors), other applications of the technology will alert individuals by broadcast, public address, or mobile device notifications and require self-protective behavioral decisions (e.g., "Drop, Cover, and Hold On"). To better understand ShakeAlert user decisions and needs, we use human-centered design methods to synthesize aggregated behavioral data into "personas," which model the common behavioral patterns that can be used to guide plans for the ShakeAlert interface, messaging, and training. We present user data, methods, and resulting personas that will inform decisions moving forward to shape ShakeAlert messaging and training that will be most usable by alert recipients.

Computational Neuroscience.

ERIC Educational Resources Information Center

Sejnowski, Terrence J.; And Others

1988-01-01

Describes the use of brain models to connect the microscopic level accessible by molecular and cellular techniques with the systems level accessible by the study of behavior. Discusses classes of brain models, and specific examples of such models. Evaluates the strengths and weaknesses of using brain modelling to understand human brain function.…

Brain and Social Networks: Fundamental Building Blocks of Human Experience.

PubMed

Falk, Emily B; Bassett, Danielle S

2017-09-01

How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Human Social Culture Behavior Modeling Program Newsletter. Volume 1. Issue 1, Spring 2009

DTIC Science & Technology

2009-03-30

the social psychol- ogy of consumer behavior . A key theory in this space is the Theory of Reasoned Action (TRA), which hypothesizes the re...useful in predicting a range of consumer behavior , including the effectiveness of anti-smoking cam- paigns and weight loss programs—each of which...Priester, J.R. (2002). The social psychology of consumer behavior . Buckingham, UK: Open University Press. Ajzen, I. & Fishbein, M. (1980

Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

PubMed

Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

2016-01-01

To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

Genetic imaging of the association of oxytocin receptor gene (OXTR) polymorphisms with positive maternal parenting

PubMed Central

Michalska, Kalina J.; Decety, Jean; Liu, Chunyu; Chen, Qi; Martz, Meghan E.; Jacob, Suma; Hipwell, Alison E.; Lee, Steve S.; Chronis-Tuscano, Andrea; Waldman, Irwin D.; Lahey, Benjamin B.

2013-01-01

Background: Well-validated models of maternal behavior in small-brain mammals posit a central role of oxytocin in parenting, by reducing stress and enhancing the reward value of social interactions with offspring. In contrast, human studies are only beginning to gain insights into how oxytocin modulates maternal behavior and affiliation. Methods: To explore associations between oxytocin receptor genes and maternal parenting behavior in humans, we conducted a genetic imaging study of women selected to exhibit a wide range of observed parenting when their children were 4–6 years old. Results: In response to child stimuli during functional magnetic resonance imaging (fMRI), hemodynamic responses in brain regions that mediate affect, reward, and social behavior were significantly correlated with observed positive parenting. Furthermore, single nucleotide polymorphisms (SNPs) (rs53576 and rs1042778) in the gene encoding the oxytocin receptor were significantly associated with both positive parenting and hemodynamic responses to child stimuli in orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and hippocampus. Conclusions: These findings contribute to the emerging literature on the role of oxytocin in human social behavior and support the feasibility of tracing biological pathways from genes to neural regions to positive maternal parenting behaviors in humans using genetic imaging methods. PMID:24550797

A Comparison of the Different Animal Models of Fetal Alcohol Spectrum Disorders and Their Use in Studying Complex Behaviors

PubMed Central

Patten, Anna R.; Fontaine, Christine J.; Christie, Brian R.

2014-01-01

Prenatal ethanol exposure (PNEE) has been linked to widespread impairments in brain structure and function. There are a number of animal models that are used to study the structural and functional deficits caused by PNEE, including, but not limited to invertebrates, fish, rodents, and non-human primates. Animal models enable a researcher to control important variables such as the route of ethanol administration, as well as the timing, frequency and amount of ethanol exposure. Each animal model and system of exposure has its place, depending on the research question being undertaken. In this review, we will examine the different routes of ethanol administration and the various animal models of fetal alcohol spectrum disorders (FASD) that are commonly used in research, emphasizing their strengths and limitations. We will also present an up-to-date summary on the effects of prenatal/neonatal ethanol exposure on behavior across the lifespan, focusing on learning and memory, olfaction, social, executive, and motor functions. Special emphasis will be placed where the various animal models best represent deficits observed in the human condition and offer a viable test bed to examine potential therapeutics for human beings with FASD. PMID:25232537