Sample records for modeling individual differences
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Modelling individual difference in visual categorization.
Shen, Jianhong; Palmeri, Thomas J
Recent years has seen growing interest in understanding, characterizing, and explaining individual differences in visual cognition. We focus here on individual differences in visual categorization. Categorization is the fundamental visual ability to group different objects together as the same kind of thing. Research on visual categorization and category learning has been significantly informed by computational modeling, so our review will focus both on how formal models of visual categorization have captured individual differences and how individual difference have informed the development of formal models. We first examine the potential sources of individual differences in leading models of visual categorization, providing a brief review of a range of different models. We then describe several examples of how computational models have captured individual differences in visual categorization. This review also provides a bit of an historical perspective, starting with models that predicted no individual differences, to those that captured group differences, to those that predict true individual differences, and to more recent hierarchical approaches that can simultaneously capture both group and individual differences in visual categorization. Via this selective review, we see how considerations of individual differences can lead to important theoretical insights into how people visually categorize objects in the world around them. We also consider new directions for work examining individual differences in visual categorization.
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Modelling individual difference in visual categorization
Shen, Jianhong; Palmeri, Thomas J.
2016-01-01
Recent years has seen growing interest in understanding, characterizing, and explaining individual differences in visual cognition. We focus here on individual differences in visual categorization. Categorization is the fundamental visual ability to group different objects together as the same kind of thing. Research on visual categorization and category learning has been significantly informed by computational modeling, so our review will focus both on how formal models of visual categorization have captured individual differences and how individual difference have informed the development of formal models. We first examine the potential sources of individual differences in leading models of visual categorization, providing a brief review of a range of different models. We then describe several examples of how computational models have captured individual differences in visual categorization. This review also provides a bit of an historical perspective, starting with models that predicted no individual differences, to those that captured group differences, to those that predict true individual differences, and to more recent hierarchical approaches that can simultaneously capture both group and individual differences in visual categorization. Via this selective review, we see how considerations of individual differences can lead to important theoretical insights into how people visually categorize objects in the world around them. We also consider new directions for work examining individual differences in visual categorization. PMID:28154496
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Ignoring Individual Differences in Times of Assessment in Growth Curve Modeling
ERIC Educational Resources Information Center
Coulombe, Patrick; Selig, James P.; Delaney, Harold D.
2016-01-01
Researchers often collect longitudinal data to model change over time in a phenomenon of interest. Inevitably, there will be some variation across individuals in specific time intervals between assessments. In this simulation study of growth curve modeling, we investigate how ignoring individual differences in time points when modeling change over…
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Modeling individual differences in working memory performance: a source activation account
Daily, Larry Z.; Lovett, Marsha C.; Reder, Lynne M.
2008-01-01
Working memory resources are needed for processing and maintenance of information during cognitive tasks. Many models have been developed to capture the effects of limited working memory resources on performance. However, most of these models do not account for the finding that different individuals show different sensitivities to working memory demands, and none of the models predicts individual subjects' patterns of performance. We propose a computational model that accounts for differences in working memory capacity in terms of a quantity called source activation, which is used to maintain goal-relevant information in an available state. We apply this model to capture the working memory effects of individual subjects at a fine level of detail across two experiments. This, we argue, strengthens the interpretation of source activation as working memory capacity. PMID:19079561
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Reasoning in Reference Games: Individual- vs. Population-Level Probabilistic Modeling
Franke, Michael; Degen, Judith
2016-01-01
Recent advances in probabilistic pragmatics have achieved considerable success in modeling speakers’ and listeners’ pragmatic reasoning as probabilistic inference. However, these models are usually applied to population-level data, and so implicitly suggest a homogeneous population without individual differences. Here we investigate potential individual differences in Theory-of-Mind related depth of pragmatic reasoning in so-called reference games that require drawing ad hoc Quantity implicatures of varying complexity. We show by Bayesian model comparison that a model that assumes a heterogenous population is a better predictor of our data, especially for comprehension. We discuss the implications for the treatment of individual differences in probabilistic models of language use. PMID:27149675
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Limit sets for natural extensions of Schelling’s segregation model
NASA Astrophysics Data System (ADS)
Singh, Abhinav; Vainchtein, Dmitri; Weiss, Howard
2011-07-01
Thomas Schelling developed an influential demographic model that illustrated how, even with relatively mild assumptions on each individual's nearest neighbor preferences, an integrated city would likely unravel to a segregated city, even if all individuals prefer integration. Individuals in Schelling's model cities are divided into two groups of equal number and each individual is "happy" or "unhappy" when the number of similar neighbors cross a simple threshold. In this manuscript we consider natural extensions of Schelling's original model to allow the two groups have different sizes and to allow different notions of happiness of an individual. We observe that differences in aggregation patterns of majority and minority groups are highly sensitive to the happiness threshold; for low threshold, the differences are small, and when the threshold is raised, striking new patterns emerge. We also observe that when individuals strongly prefer to live in integrated neighborhoods, the final states exhibit a new tessellated-like structure.
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Moving beyond qualitative evaluations of Bayesian models of cognition.
Hemmer, Pernille; Tauber, Sean; Steyvers, Mark
2015-06-01
Bayesian models of cognition provide a powerful way to understand the behavior and goals of individuals from a computational point of view. Much of the focus in the Bayesian cognitive modeling approach has been on qualitative model evaluations, where predictions from the models are compared to data that is often averaged over individuals. In many cognitive tasks, however, there are pervasive individual differences. We introduce an approach to directly infer individual differences related to subjective mental representations within the framework of Bayesian models of cognition. In this approach, Bayesian data analysis methods are used to estimate cognitive parameters and motivate the inference process within a Bayesian cognitive model. We illustrate this integrative Bayesian approach on a model of memory. We apply the model to behavioral data from a memory experiment involving the recall of heights of people. A cross-validation analysis shows that the Bayesian memory model with inferred subjective priors predicts withheld data better than a Bayesian model where the priors are based on environmental statistics. In addition, the model with inferred priors at the individual subject level led to the best overall generalization performance, suggesting that individual differences are important to consider in Bayesian models of cognition.
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Three-Mode Models and Individual Differences in Semantic Differential Data.
ERIC Educational Resources Information Center
Murakami, Takashi; Kroonenberg, Pieter M.
2003-01-01
Demonstrated how individual differences in semantic differential data can be modeled and assessed using three-mode models by studying the characterization of Chopin's "Preludes" by 38 Japanese college students. (SLD)
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ERIC Educational Resources Information Center
Armstrong, Patrick Ian; Rounds, James
2010-01-01
Career assessment methods often include measures of individual differences constructs, such as interests, personality, abilities, and values. Although many researchers have recently called for the development of integrated models, career counseling professionals have long faced the challenge of integrating this information into their practice. The…
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Vadeby, Anna; Forsman, Åsa
2017-06-01
This study investigated the effect of applying two aggregated models (the Power model and the Exponential model) to individual vehicle speeds instead of mean speeds. This is of particular interest when the measure introduced affects different parts of the speed distribution differently. The aim was to examine how the estimated overall risk was affected when assuming the models are valid on an individual vehicle level. Speed data from two applications of speed measurements were used in the study: an evaluation of movable speed cameras and a national evaluation of new speed limits in Sweden. The results showed that when applied on individual vehicle speed level compared with aggregated level, there was essentially no difference between these for the Power model in the case of injury accidents. However, for fatalities the difference was greater, especially for roads with new cameras where those driving fastest reduced their speed the most. For the case with new speed limits, the individual approach estimated a somewhat smaller effect, reflecting that changes in the 15th percentile (P15) were somewhat larger than changes in P85 in this case. For the Exponential model there was also a clear, although small, difference between applying the model to mean speed changes and individual vehicle speed changes when speed cameras were used. This applied both for injury accidents and fatalities. There were also larger effects for the Exponential model than for the Power model, especially for injury accidents. In conclusion, applying the Power or Exponential model to individual vehicle speeds is an alternative that provides reasonable results in relation to the original Power and Exponential models, but more research is needed to clarify the shape of the individual risk curve. It is not surprising that the impact on severe traffic crashes was larger in situations where those driving fastest reduced their speed the most. Further investigations on use of the Power and/or the Exponential model at individual vehicle level would require more data on the individual level from a range of international studies. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno
2016-01-01
Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision. PMID:27303323
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Scherer, Ronny; Nilsen, Trude; Jansen, Malte
2016-01-01
Students' perceptions of instructional quality are among the most important criteria for evaluating teaching effectiveness. The present study evaluates different latent variable modeling approaches (confirmatory factor analysis, exploratory structural equation modeling, and bifactor modeling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance, and the relations to selected educational outcomes (achievement, self-concept, and motivation in mathematics). On the basis of the Programme for International Student Assessment (PISA) 2012 large-scale data sets of Australia, Canada, and the USA (N = 26,746 students), we find support for the distinction between three factors of individual students' perceptions and full measurement invariance across countries for all modeling approaches. In this regard, bifactor exploratory structural equation modeling outperformed alternative approaches with respect to model fit. Our findings reveal significant relations to the educational outcomes. This study synthesizes different modeling approaches of individual students' perceptions of instructional quality and provides insights into the nature of these perceptions from an individual differences perspective. Implications for the measurement and modeling of individually perceived instructional quality are discussed.
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Individual differences in posttraumatic distress: problems with the DSM-IV model.
Bowman, M L
1999-02-01
To evaluate the evidence concerning the role of threatening life events in accounting for clinically significant posttraumatic stress responses. Research was examined to review the epidemiology, evidence of dose-response relations, and individual difference factors in accounting for variations in conditions, including posttraumatic stress disorder, after exposure to threatening events. The evidence is significantly discrepant from the clinical Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) model. Greater distress arises from individual differences than from event characteristics. Important individual differences that interact with threat exposures include trait negative affectivity (neuroticism); beliefs about emotions, the self, the world, and the sources and consequences of danger; and prevent acts, disorders, and intelligence. Reasons for the discrepancies between the evidence and the current model of posttraumatic distress are proposed. In accounting for responses to threatening life events, the relatively minor contribution of event qualities compared with individual differences has significant treatment implications. Treatment approaches assuming that toxic event exposure creates a posttraumatic disorder fail to consider individual differences that could improve treatment efficacy.
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Cho, Sun-Joo; Athay, Michele; Preacher, Kristopher J
2013-05-01
Even though many educational and psychological tests are known to be multidimensional, little research has been done to address how to measure individual differences in change within an item response theory framework. In this paper, we suggest a generalized explanatory longitudinal item response model to measure individual differences in change. New longitudinal models for multidimensional tests and existing models for unidimensional tests are presented within this framework and implemented with software developed for generalized linear models. In addition to the measurement of change, the longitudinal models we present can also be used to explain individual differences in change scores for person groups (e.g., learning disabled students versus non-learning disabled students) and to model differences in item difficulties across item groups (e.g., number operation, measurement, and representation item groups in a mathematics test). An empirical example illustrates the use of the various models for measuring individual differences in change when there are person groups and multiple skill domains which lead to multidimensionality at a time point. © 2012 The British Psychological Society.
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Scherer, Ronny; Nilsen, Trude; Jansen, Malte
2016-01-01
Students' perceptions of instructional quality are among the most important criteria for evaluating teaching effectiveness. The present study evaluates different latent variable modeling approaches (confirmatory factor analysis, exploratory structural equation modeling, and bifactor modeling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance, and the relations to selected educational outcomes (achievement, self-concept, and motivation in mathematics). On the basis of the Programme for International Student Assessment (PISA) 2012 large-scale data sets of Australia, Canada, and the USA (N = 26,746 students), we find support for the distinction between three factors of individual students' perceptions and full measurement invariance across countries for all modeling approaches. In this regard, bifactor exploratory structural equation modeling outperformed alternative approaches with respect to model fit. Our findings reveal significant relations to the educational outcomes. This study synthesizes different modeling approaches of individual students' perceptions of instructional quality and provides insights into the nature of these perceptions from an individual differences perspective. Implications for the measurement and modeling of individually perceived instructional quality are discussed. PMID:26903917
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NASA Astrophysics Data System (ADS)
Clark, Martyn; Essery, Richard
2017-04-01
When faced with the complex and interdisciplinary challenge of building process-based land models, different modelers make different decisions at different points in the model development process. These modeling decisions are generally based on several considerations, including fidelity (e.g., what approaches faithfully simulate observed processes), complexity (e.g., which processes should be represented explicitly), practicality (e.g., what is the computational cost of the model simulations; are there sufficient resources to implement the desired modeling concepts), and data availability (e.g., is there sufficient data to force and evaluate models). Consequently the research community, comprising modelers of diverse background, experience, and modeling philosophy, has amassed a wide range of models, which differ in almost every aspect of their conceptualization and implementation. Model comparison studies have been undertaken to explore model differences, but have not been able to meaningfully attribute inter-model differences in predictive ability to individual model components because there are often too many structural and implementation differences among the different models considered. As a consequence, model comparison studies to date have provided limited insight into the causes of differences in model behavior, and model development has often relied on the inspiration and experience of individual modelers rather than on a systematic analysis of model shortcomings. This presentation will summarize the use of "multiple-hypothesis" modeling frameworks to understand differences in process-based snow models. Multiple-hypothesis frameworks define a master modeling template, and include a a wide variety of process parameterizations and spatial configurations that are used in existing models. Such frameworks provide the capability to decompose complex models into the individual decisions that are made as part of model development, and evaluate each decision in isolation. It is hence possible to attribute differences in system-scale model predictions to individual modeling decisions, providing scope to mimic the behavior of existing models, understand why models differ, characterize model uncertainty, and identify productive pathways to model improvement. Results will be presented applying multiple hypothesis frameworks to snow model comparison projects, including PILPS, SnowMIP, and the upcoming ESM-SnowMIP project.
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Costalago Meruelo, Alicia; Simpson, David M; Veres, Sandor M; Newland, Philip L
2016-03-01
Mathematical modelling is used routinely to understand the coding properties and dynamics of responses of neurons and neural networks. Here we analyse the effectiveness of Artificial Neural Networks (ANNs) as a modelling tool for motor neuron responses. We used ANNs to model the synaptic responses of an identified motor neuron, the fast extensor motor neuron, of the desert locust in response to displacement of a sensory organ, the femoral chordotonal organ, which monitors movements of the tibia relative to the femur of the leg. The aim of the study was threefold: first to determine the potential value of ANNs as tools to model and investigate neural networks, second to understand the generalisation properties of ANNs across individuals and to different input signals and third, to understand individual differences in responses of an identified neuron. A metaheuristic algorithm was developed to design the ANN architectures. The performance of the models generated by the ANNs was compared with those generated through previous mathematical models of the same neuron. The results suggest that ANNs are significantly better than LNL and Wiener models in predicting specific neural responses to Gaussian White Noise, but not significantly different when tested with sinusoidal inputs. They are also able to predict responses of the same neuron in different individuals irrespective of which animal was used to develop the model, although notable differences between some individuals were evident. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
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ERIC Educational Resources Information Center
Schmiedek, Florian; Oberauer, Klaus; Wilhelm, Oliver; Suss, Heinz-Martin; Wittmann, Werner W.
2007-01-01
The authors bring together approaches from cognitive and individual differences psychology to model characteristics of reaction time distributions beyond measures of central tendency. Ex-Gaussian distributions and a diffusion model approach are used to describe individuals' reaction time data. The authors identified common latent factors for each…
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Cognitive models of risky choice: parameter stability and predictive accuracy of prospect theory.
Glöckner, Andreas; Pachur, Thorsten
2012-04-01
In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are individual differences as measured by model parameters stable enough to improve the ability to predict behavior as compared to modeling without adjustable parameters? We examined this issue in cumulative prospect theory (CPT), arguably the most widely used framework to model decisions under risk. Specifically, we examined (a) the temporal stability of CPT's parameters; and (b) how well different implementations of CPT, varying in the number of adjustable parameters, predict individual choice relative to models with no adjustable parameters (such as CPT with fixed parameters, expected value theory, and various heuristics). We presented participants with risky choice problems and fitted CPT to each individual's choices in two separate sessions (which were 1 week apart). All parameters were correlated across time, in particular when using a simple implementation of CPT. CPT allowing for individual variability in parameter values predicted individual choice better than CPT with fixed parameters, expected value theory, and the heuristics. CPT's parameters thus seem to pick up stable individual differences that need to be considered when predicting risky choice. Copyright © 2011 Elsevier B.V. All rights reserved.
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The Onion Model: Myth or Reality in the Field of Individual Differences Psychology?
ERIC Educational Resources Information Center
Cools, Eva; Bellens, Kim
2012-01-01
To bring order in concepts related to individual learner differences, Curry (1983) designed the three-layered onion model. As this model provides an interesting way to distinguish related concepts--such as cognitive styles and approaches to studying--on the basis of their stability in learning situations, ample studies build further on this model.…
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ERIC Educational Resources Information Center
Gibbons, Pamela
1995-01-01
Describes a study that investigated individual differences in the construction of mental models of recursion in LOGO programming. The learning process was investigated from the perspective of Norman's mental models theory and employed diSessa's ontology regarding distributed, functional, and surrogate mental models, and the Luria model of brain…
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ERIC Educational Resources Information Center
van der Maas, Han L. J.; Molenaar, Dylan; Maris, Gunter; Kievit, Rogier A.; Borsboom, Denny
2011-01-01
This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line…
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Tinker, M. Tim; Guimarães, Paulo R.; Novak, Mark; Marquitti, Flavia Maria Darcie; Bodkin, James L.; Staedler, Michelle; Bentall, Gena B.; Estes, James A.
2012-01-01
Studies of consumer-resource interactions suggest that individual diet specialisation is empirically widespread and theoretically important to the organisation and dynamics of populations and communities. We used weighted networks to analyze the resource use by sea otters, testing three alternative models for how individual diet specialisation may arise. As expected, individual specialisation was absent when otter density was low, but increased at high-otter density. A high-density emergence of nested resource-use networks was consistent with the model assuming individuals share preference ranks. However, a density-dependent emergence of a non-nested modular network for ‘core’ resources was more consistent with the ‘competitive refuge’ model. Individuals from different diet modules showed predictable variation in rank-order prey preferences and handling times of core resources, further supporting the competitive refuge model. Our findings support a hierarchical organisation of diet specialisation and suggest individual use of core and marginal resources may be driven by different selective pressures.
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Individual differences in emotion word processing: A diffusion model analysis.
Mueller, Christina J; Kuchinke, Lars
2016-06-01
The exploratory study investigated individual differences in implicit processing of emotional words in a lexical decision task. A processing advantage for positive words was observed, and differences between happy and fear-related words in response times were predicted by individual differences in specific variables of emotion processing: Whereas more pronounced goal-directed behavior was related to a specific slowdown in processing of fear-related words, the rate of spontaneous eye blinks (indexing brain dopamine levels) was associated with a processing advantage of happy words. Estimating diffusion model parameters revealed that the drift rate (rate of information accumulation) captures unique variance of processing differences between happy and fear-related words, with highest drift rates observed for happy words. Overall emotion recognition ability predicted individual differences in drift rates between happy and fear-related words. The findings emphasize that a significant amount of variance in emotion processing is explained by individual differences in behavioral data.
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Zimprich, Daniel; Kurtz, Tanja
2013-01-01
The goal of the present study was to examine whether individual differences in basic cognitive abilities, processing speed, and working memory, are reliable predictors of individual differences in forgetting rates in old age. The sample for the present study comprised 364 participants aged between 65 and 80 years from the Zurich Longitudinal Study on Cognitive Aging. The impact of basic cognitive abilities on forgetting was analyzed by modeling working memory and processing speed as predictors of the amount of forgetting of 27 words, which had been learned across five trials. Forgetting was measured over a 30-minute interval by using parceling and a latent change model, in which the latent difference between recall performance after five learning trials and a delayed recall was modeled. Results implied reliable individual differences in forgetting. These individual differences in forgetting were strongly related to processing speed and working memory. Moreover, an age-related effect, which was significantly stronger for forgetting than for learning, emerged even after controlling effects of processing speed and working memory.
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Simple model of epidemics with pathogen mutation.
Girvan, Michelle; Callaway, Duncan S; Newman, M E J; Strogatz, Steven H
2002-03-01
We study how the interplay between the memory immune response and pathogen mutation affects epidemic dynamics in two related models. The first explicitly models pathogen mutation and individual memory immune responses, with contacted individuals becoming infected only if they are exposed to strains that are significantly different from other strains in their memory repertoire. The second model is a reduction of the first to a system of difference equations. In this case, individuals spend a fixed amount of time in a generalized immune class. In both models, we observe four fundamentally different types of behavior, depending on parameters: (1) pathogen extinction due to lack of contact between individuals; (2) endemic infection; (3) periodic epidemic outbreaks; and (4) one or more outbreaks followed by extinction of the epidemic due to extremely low minima in the oscillations. We analyze both models to determine the location of each transition. Our main result is that pathogens in highly connected populations must mutate rapidly in order to remain viable.
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A new simple local muscle recovery model and its theoretical and experimental validation.
Ma, Liang; Zhang, Wei; Wu, Su; Zhang, Zhanwu
2015-01-01
This study was conducted to provide theoretical and experimental validation of a local muscle recovery model. Muscle recovery has been modeled in different empirical and theoretical approaches to determine work-rest allowance for musculoskeletal disorder (MSD) prevention. However, time-related parameters and individual attributes have not been sufficiently considered in conventional approaches. A new muscle recovery model was proposed by integrating time-related task parameters and individual attributes. Theoretically, this muscle recovery model was compared to other theoretical models mathematically. Experimentally, a total of 20 subjects participated in the experimental validation. Hand grip force recovery and shoulder joint strength recovery were measured after a fatiguing operation. The recovery profile was fitted by using the recovery model, and individual recovery rates were calculated as well after fitting. Good fitting values (r(2) > .8) were found for all the subjects. Significant differences in recovery rates were found among different muscle groups (p < .05). The theoretical muscle recovery model was primarily validated by characterization of the recovery process after fatiguing operation. The determined recovery rate may be useful to represent individual recovery attribute.
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López, Leonardo; Burguerner, Germán; Giovanini, Leonardo
2014-04-12
The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease.
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Kano, Fumihiro; Shepherd, Stephen V; Hirata, Satoshi; Call, Josep
2018-01-01
When viewing social scenes, humans and nonhuman primates focus on particular features, such as the models' eyes, mouth, and action targets. Previous studies reported that such viewing patterns vary significantly across individuals in humans, and also across closely-related primate species. However, the nature of these individual and species differences remains unclear, particularly among nonhuman primates. In large samples of human and nonhuman primates, we examined species differences and the effects of experience on patterns of gaze toward social movies. Experiment 1 examined the species differences across rhesus macaques, nonhuman apes (bonobos, chimpanzees, and orangutans), and humans while they viewed movies of various animals' species-typical behaviors. We found that each species had distinct viewing patterns of the models' faces, eyes, mouths, and action targets. Experiment 2 tested the effect of individuals' experience on chimpanzee and human viewing patterns. We presented movies depicting natural behaviors of chimpanzees to three groups of chimpanzees (individuals from a zoo, a sanctuary, and a research institute) differing in their early social and physical experiences. We also presented the same movies to human adults and children differing in their expertise with chimpanzees (experts vs. novices) or movie-viewing generally (adults vs. preschoolers). Individuals varied within each species in their patterns of gaze toward models' faces, eyes, mouths, and action targets depending on their unique individual experiences. We thus found that the viewing patterns for social stimuli are both individual- and species-specific in these closely-related primates. Such individual/species-specificities are likely related to both individual experience and species-typical temperament, suggesting that primate individuals acquire their unique attentional biases through both ontogeny and evolution. Such unique attentional biases may help them learn efficiently about their particular social environments.
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Sansone, Carol; Thoman, Dustin B
2006-12-01
Typically, models of self-regulation include motivation in terms of goals. Motivation is proposed to differ among individuals as a consequence of the goals they hold as well as how much they value those goals and expect to attain them. We suggest that goal-defined motivation is only one source of motivation critical for sustained engagement. A second source is the motivation that arises from the degree of interest experienced in the process of goal pursuit. Our model integrates both sources of motivation within the goal-striving process and suggests that individuals may actively monitor and regulate them. Conceptualizing motivation in terms of a self-regulatory process provides an organizing framework for understanding how individuals might differ in whether they experience interest while working toward goals, whether they persist without interest, and whether and how they try to create interest. We first present the self-regulation of motivation model and then review research illustrating how the consideration of individual differences at different points in the process allows a better understanding of variability in people's choices, efforts, and persistence over time.
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ERIC Educational Resources Information Center
Rast, Philippe; Hofer, Scott M.; Sparks, Catharine
2012-01-01
A mixed effects location scale model was used to model and explain individual differences in within-person variability of negative and positive affect across 7 days (N=178) within a measurement burst design. The data come from undergraduate university students and are pooled from a study that was repeated at two consecutive years. Individual…
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Artificial neural network cardiopulmonary modeling and diagnosis
Kangas, L.J.; Keller, P.E.
1997-10-28
The present invention is a method of diagnosing a cardiopulmonary condition in an individual by comparing data from a progressive multi-stage test for the individual to a non-linear multi-variate model, preferably a recurrent artificial neural network having sensor fusion. The present invention relies on a cardiovascular model developed from physiological measurements of an individual. Any differences between the modeled parameters and the parameters of an individual at a given time are used for diagnosis. 12 figs.
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Artificial neural network cardiopulmonary modeling and diagnosis
Kangas, Lars J.; Keller, Paul E.
1997-01-01
The present invention is a method of diagnosing a cardiopulmonary condition in an individual by comparing data from a progressive multi-stage test for the individual to a non-linear multi-variate model, preferably a recurrent artificial neural network having sensor fusion. The present invention relies on a cardiovascular model developed from physiological measurements of an individual. Any differences between the modeled parameters and the parameters of an individual at a given time are used for diagnosis.
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A Mixture Approach to Vagueness and Ambiguity
Verheyen, Steven; Storms, Gert
2013-01-01
When asked to indicate which items from a set of candidates belong to a particular natural language category inter-individual differences occur: Individuals disagree which items should be considered category members. The premise of this paper is that these inter-individual differences in semantic categorization reflect both ambiguity and vagueness. Categorization differences are said to be due to ambiguity when individuals employ different criteria for categorization. For instance, individuals may disagree whether hiking or darts is the better example of sports because they emphasize respectively whether an activity is strenuous and whether rules apply. Categorization differences are said to be due to vagueness when individuals employ different cut-offs for separating members from non-members. For instance, the decision to include hiking in the sports category or not, may hinge on how strenuous different individuals require sports to be. This claim is supported by the application of a mixture model to categorization data for eight natural language categories. The mixture model can identify latent groups of categorizers who regard different items likely category members (i.e., ambiguity) with categorizers within each of the groups differing in their propensity to provide membership responses (i.e., vagueness). The identified subgroups are shown to emphasize different sets of category attributes when making their categorization decisions. PMID:23667627
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USDA-ARS?s Scientific Manuscript database
The Individual Differences Model posits that individual differences in physiological and psychological factors explain eating behaviors in response to stress. The purpose was to determine the effects of individual differences in adiposity, dietary restraint and stress reactivity on children's energy...
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Individual differences in attention influence perceptual decision making.
Nunez, Michael D; Srinivasan, Ramesh; Vandekerckhove, Joachim
2015-01-01
Sequential sampling decision-making models have been successful in accounting for reaction time (RT) and accuracy data in two-alternative forced choice tasks. These models have been used to describe the behavior of populations of participants, and explanatory structures have been proposed to account for between individual variability in model parameters. In this study we show that individual differences in behavior from a novel perceptual decision making task can be attributed to (1) differences in evidence accumulation rates, (2) differences in variability of evidence accumulation within trials, and (3) differences in non-decision times across individuals. Using electroencephalography (EEG), we demonstrate that these differences in cognitive variables, in turn, can be explained by attentional differences as measured by phase-locking of steady-state visual evoked potential (SSVEP) responses to the signal and noise components of the visual stimulus. Parameters of a cognitive model (a diffusion model) were obtained from accuracy and RT distributions and related to phase-locking indices (PLIs) of SSVEPs with a single step in a hierarchical Bayesian framework. Participants who were able to suppress the SSVEP response to visual noise in high frequency bands were able to accumulate correct evidence faster and had shorter non-decision times (preprocessing or motor response times), leading to more accurate responses and faster response times. We show that the combination of cognitive modeling and neural data in a hierarchical Bayesian framework relates physiological processes to the cognitive processes of participants, and that a model with a new (out-of-sample) participant's neural data can predict that participant's behavior more accurately than models without physiological data.
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Jager, Tjalling
2013-02-05
The individuals of a species are not equal. These differences frustrate experimental biologists and ecotoxicologists who wish to study the response of a species (in general) to a treatment. In the analysis of data, differences between model predictions and observations on individual animals are usually treated as random measurement error around the true response. These deviations, however, are mainly caused by real differences between the individuals (e.g., differences in physiology and in initial conditions). Understanding these intraspecies differences, and accounting for them in the data analysis, will improve our understanding of the response to the treatment we are investigating and allow for a more powerful, less biased, statistical analysis. Here, I explore a basic scheme for statistical inference to estimate parameters governing stress that allows individuals to differ in their basic physiology. This scheme is illustrated using a simple toxicokinetic-toxicodynamic model and a data set for growth of the springtail Folsomia candida exposed to cadmium in food. This article should be seen as proof of concept; a first step in bringing more realism into the statistical inference for process-based models in ecotoxicology.
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Individual differences in transcranial electrical stimulation current density
Russell, Michael J; Goodman, Theodore; Pierson, Ronald; Shepherd, Shane; Wang, Qiang; Groshong, Bennett; Wiley, David F
2013-01-01
Transcranial electrical stimulation (TCES) is effective in treating many conditions, but it has not been possible to accurately forecast current density within the complex anatomy of a given subject's head. We sought to predict and verify TCES current densities and determine the variability of these current distributions in patient-specific models based on magnetic resonance imaging (MRI) data. Two experiments were performed. The first experiment estimated conductivity from MRIs and compared the current density results against actual measurements from the scalp surface of 3 subjects. In the second experiment, virtual electrodes were placed on the scalps of 18 subjects to model simulated current densities with 2 mA of virtually applied stimulation. This procedure was repeated for 4 electrode locations. Current densities were then calculated for 75 brain regions. Comparison of modeled and measured external current in experiment 1 yielded a correlation of r = .93. In experiment 2, modeled individual differences were greatest near the electrodes (ten-fold differences were common), but simulated current was found in all regions of the brain. Sites that were distant from the electrodes (e.g. hypothalamus) typically showed two-fold individual differences. MRI-based modeling can effectively predict current densities in individual brains. Significant variation occurs between subjects with the same applied electrode configuration. Individualized MRI-based modeling should be considered in place of the 10-20 system when accurate TCES is needed. PMID:24285948
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2014-01-01
Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease. PMID:24725804
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Uher, Jana
2015-12-01
As science seeks to make generalisations, a science of individual peculiarities encounters intricate challenges. This article explores these challenges by applying the Transdisciplinary Philosophy-of-Science Paradigm for Research on Individuals (TPS-Paradigm) and by exploring taxonomic "personality" research as an example. Analyses of researchers' interpretations of the taxonomic "personality" models, constructs and data that have been generated in the field reveal widespread erroneous assumptions about the abilities of previous methodologies to appropriately represent individual-specificity in the targeted phenomena. These assumptions, rooted in everyday thinking, fail to consider that individual-specificity and others' minds cannot be directly perceived, that abstract descriptions cannot serve as causal explanations, that between-individual structures cannot be isomorphic to within-individual structures, and that knowledge of compositional structures cannot explain the process structures of their functioning and development. These erroneous assumptions and serious methodological deficiencies in widely used standardised questionnaires have effectively prevented psychologists from establishing taxonomies that can comprehensively model individual-specificity in most of the kinds of phenomena explored as "personality", especially in experiencing and behaviour and in individuals' functioning and development. Contrary to previous assumptions, it is not universal models but rather different kinds of taxonomic models that are required for each of the different kinds of phenomena, variations and structures that are commonly conceived of as "personality". Consequently, to comprehensively explore individual-specificity, researchers have to apply a portfolio of complementary methodologies and develop different kinds of taxonomies, most of which have yet to be developed. Closing, the article derives some meta-desiderata for future research on individuals' "personality".
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ERIC Educational Resources Information Center
Savine, Adam C.; McDaniel, Mark A.; Shelton, Jill Talley; Scullin, Michael K.
2012-01-01
Prospective memory--remembering to retrieve and execute future goals--is essential to daily life. Prospective remembering is often achieved through effortful monitoring; however, potential individual differences in monitoring patterns have not been characterized. We propose 3 candidate models to characterize the individual differences present in…
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An emotional contagion model for heterogeneous social media with multiple behaviors
NASA Astrophysics Data System (ADS)
Xiong, Xi; Li, Yuanyuan; Qiao, Shaojie; Han, Nan; Wu, Yue; Peng, Jing; Li, Binyong
2018-01-01
The emotion varies and propagates with the spatial and temporal information of individuals through social media, which uncovers several interaction mechanisms and features the community structure in order to facilitate individuals' communication and emotional contagion in social networks. Aiming to show the detailed process and characteristics of emotional contagion within social media, we propose an emotional independent cascade model in which individual emotion can affect the subsequent emotion of his/her friends. The transmissibility is introduced to measure the capability of propagating emotion with respect to an individual in social networks. By analyzing the patterns of emotional contagion on Twitter data, we find that the value of transmissibility differs on different layers and on different community structures. Extensive experiments were conducted and the results reveal that, the polar emotion of hub users can lead to the disappearance of opposite emotion, and the transmissibility makes no sense. The final emotional distribution depends on the initial emotional distribution and the transmissibilities. Individuals from a small community are more likely to change their mood by the influence of community leaders. In addition, we compared the proposed model with two other models, the emotion-based spreader-ignorant-stifler model and the standard independent cascade model. The results demonstrate that the proposed model can reflect the real-world situation of emotional contagion for heterogeneous social media while the computational complexities of all these three models are similar.
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Predicting individual fusional range from optometric data
NASA Astrophysics Data System (ADS)
Endrikhovski, Serguei; Jin, Elaine; Miller, Michael E.; Ford, Robert W.
2005-03-01
A model was developed to predict the range of disparities that can be fused by an individual user from optometric measurements. This model uses parameters, such as dissociated phoria and fusional reserves, to calculate an individual user"s fusional range (i.e., the disparities that can be fused on stereoscopic displays) when the user views a stereoscopic stimulus from various distances. This model is validated by comparing its output with data from a study in which the individual fusional range of a group of users was quantified while they viewed a stereoscopic display from distances of 0.5, 1.0, and 2.0 meters. Overall, the model provides good data predictions for the majority of the subjects and can be generalized for other viewing conditions. The model may, therefore, be used within a customized stereoscopic system, which would render stereoscopic information in a way that accounts for the individual differences in fusional range. Because the comfort of an individual user also depends on the user"s ability to fuse stereo images, such a system may, consequently, improve the comfort level and viewing experience for people with different stereoscopic fusional capabilities.
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Leveraging social networks for understanding the evolution of epidemics
2011-01-01
Background To understand how infectious agents disseminate throughout a population it is essential to capture the social model in a realistic manner. This paper presents a novel approach to modeling the propagation of the influenza virus throughout a realistic interconnection network based on actual individual interactions which we extract from online social networks. The advantage is that these networks can be extracted from existing sources which faithfully record interactions between people in their natural environment. We additionally allow modeling the characteristics of each individual as well as customizing his daily interaction patterns by making them time-dependent. Our purpose is to understand how the infection spreads depending on the structure of the contact network and the individuals who introduce the infection in the population. This would help public health authorities to respond more efficiently to epidemics. Results We implement a scalable, fully distributed simulator and validate the epidemic model by comparing the simulation results against the data in the 2004-2005 New York State Department of Health Report (NYSDOH), with similar temporal distribution results for the number of infected individuals. We analyze the impact of different types of connection models on the virus propagation. Lastly, we analyze and compare the effects of adopting several different vaccination policies, some of them based on individual characteristics -such as age- while others targeting the super-connectors in the social model. Conclusions This paper presents an approach to modeling the propagation of the influenza virus via a realistic social model based on actual individual interactions extracted from online social networks. We implemented a scalable, fully distributed simulator and we analyzed both the dissemination of the infection and the effect of different vaccination policies on the progress of the epidemics. The epidemic values predicted by our simulator match real data from NYSDOH. Our results show that our simulator can be a useful tool in understanding the differences in the evolution of an epidemic within populations with different characteristics and can provide guidance with regard to which, and how many, individuals should be vaccinated to slow down the virus propagation and reduce the number of infections. PMID:22784620
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MONTEIRO, J.F.G.; ESCUDERO, D.J.; WEINREB, C.; FLANIGAN, T.; GALEA, S.; FRIEDMAN, S.R.; MARSHALL, B.D.L.
2017-01-01
SUMMARY We investigated how different models of HIV transmission, and assumptions regarding the distribution of unprotected sex and syringe-sharing events (‘risk acts’), affect quantitative understanding of HIV transmission process in people who inject drugs (PWID). The individual-based model simulated HIV transmission in a dynamic sexual and injecting network representing New York City. We constructed four HIV transmission models: model 1, constant probabilities; model 2, random number of sexual and parenteral acts; model 3, viral load individual assigned; and model 4, two groups of partnerships (low and high risk). Overall, models with less heterogeneity were more sensitive to changes in numbers risk acts, producing HIV incidence up to four times higher than that empirically observed. Although all models overestimated HIV incidence, micro-simulations with greater heterogeneity in the HIV transmission modelling process produced more robust results and better reproduced empirical epidemic dynamics. PMID:26753627
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Towards a Pedagogy for Clinical Education: Beyond Individual Learning Differences
ERIC Educational Resources Information Center
Kinchin, Ian M.; Baysan, Aylin; Cabot, Lyndon Bruce
2008-01-01
The development of teaching in higher education towards a more learner-orientated model has been supported by the literature on individual learning differences and on learning styles in particular. This has contributed to the evolution of university pedagogy away from a medieval transmission model than runs counter to contemporary understanding of…
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A critical aspect of air pollution exposure assessment is the estimation of the time spent by individuals in various microenvironments (ME). Accounting for the time spent in different ME with different pollutant concentrations can reduce exposure misclassifications, while failure...
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Anterior EEG Asymmetry and the Modifier Model of Autism
ERIC Educational Resources Information Center
Burnette, Courtney P.; Henderson, Heather A.; Inge, Anne Pradella; Zahka, Nicole E.; Schwartz, Caley B.; Mundy, Peter C.
2011-01-01
Individual differences in the expression of autism complicate research on the nature and treatment of this disorder. In the Modifier Model of Autism (Mundy et al. 2007), we proposed that individual differences in autism may result not only from syndrome specific causal processes, but also from variability in generic, non-syndrome specific…
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Gergs, André; Preuss, Thomas G.; Palmqvist, Annemette
2014-01-01
Population size is often regulated by negative feedback between population density and individual fitness. At high population densities, animals run into double trouble: they might concurrently suffer from overexploitation of resources and also from negative interference among individuals regardless of resource availability, referred to as crowding. Animals are able to adapt to resource shortages by exhibiting a repertoire of life history and physiological plasticities. In addition to resource-related plasticity, crowding might lead to reduced fitness, with consequences for individual life history. We explored how different mechanisms behind resource-related plasticity and crowding-related fitness act independently or together, using the water flea Daphnia magna as a case study. For testing hypotheses related to mechanisms of plasticity and crowding stress across different biological levels, we used an individual-based population model that is based on dynamic energy budget theory. Each of the hypotheses, represented by a sub-model, is based on specific assumptions on how the uptake and allocation of energy are altered under conditions of resource shortage or crowding. For cross-level testing of different hypotheses, we explored how well the sub-models fit individual level data and also how well they predict population dynamics under different conditions of resource availability. Only operating resource-related and crowding-related hypotheses together enabled accurate model predictions of D. magna population dynamics and size structure. Whereas this study showed that various mechanisms might play a role in the negative feedback between population density and individual life history, it also indicated that different density levels might instigate the onset of the different mechanisms. This study provides an example of how the integration of dynamic energy budget theory and individual-based modelling can facilitate the exploration of mechanisms behind the regulation of population size. Such understanding is important for assessment, management and the conservation of populations and thereby biodiversity in ecosystems. PMID:24626228
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What Controls the Acute Viral Infection Following Yellow Fever Vaccination?
Moore, James; Ahmed, Hasan; Jia, Jonathan; Akondy, Rama; Ahmed, Rafi; Antia, Rustom
2018-01-01
Does target cell depletion, innate immunity, or adaptive immunity play the dominant role in controlling primary acute viral infections? Why do some individuals have higher peak virus titers than others? Answering these questions is a basic problem in immunology and can be particularly difficult in humans due to limited data, heterogeneity in responses in different individuals, and limited ability for experimental manipulation. We address these questions for infections following vaccination with the live attenuated yellow fever virus (YFV-17D) by analyzing viral load data from 80 volunteers. Using a mixed effects modeling approach, we find that target cell depletion models do not fit the data as well as innate or adaptive immunity models. Examination of the fits of the innate and adaptive immunity models to the data allows us to select a minimal model that gives improved fits by widely used model selection criteria (AICc and BIC) and explains why it is hard to distinguish between the innate and adaptive immunity models. We then ask why some individuals have over 1000-fold higher virus titers than others and find that most of the variation arises from differences in the initial/maximum growth rate of the virus in different individuals.
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Seeking psychological help: a comparison of individual and group treatment.
Shechtman, Zipora; Vogel, David; Maman, Neta
2010-01-01
The study examined public and self-stigma and their association with attitudes and intentions to seek psychological help in regard to both individual and group treatment as well as to various subgroups, including gender, ethnicity, educational orientation, level of religion, and age. Undergraduate students (N=307) in three universities in Israel participated in the study. Results partly confirmed the model for both individual and group therapy: Self-stigma was related to attitudes and intentions to seek help. However, public stigma was not related to self-stigma. Importantly, some differences were also found among the various subgroups, and the model, which takes into account the different subgroups, looks somewhat different for individual and group therapy.
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Individualized Cognitive Modeling for Close-Loop Task Mitigation
NASA Technical Reports Server (NTRS)
Zhang, Guangfan; Xu, Roger; Wang, Wei; Li, Jiang; Schnell, Tom; Keller, Mike
2010-01-01
An accurate real-time operator functional state assessment makes it possible to perform task management, minimize risks, and improve mission performance. In this paper, we discuss the development of an individualized operator functional state assessment model that identifies states likely leading to operational errors. To address large individual variations, we use two different approaches to build a model for each individual using its data as well as data from subjects with similar responses. If a subject's response is similar to that of the individual of interest in a specific functional state, all the training data from this subject will be used to build the individual model. The individualization methods have been successfully verified and validated with a driving test data set provided by University of Iowa. With the individualized models, the mean squared error can be significantly decreased (by around 20%).
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Mismatch or cumulative stress: toward an integrated hypothesis of programming effects.
Nederhof, Esther; Schmidt, Mathias V
2012-07-16
This paper integrates the cumulative stress hypothesis with the mismatch hypothesis, taking into account individual differences in sensitivity to programming. According to the cumulative stress hypothesis, individuals are more likely to suffer from disease as adversity accumulates. According to the mismatch hypothesis, individuals are more likely to suffer from disease if a mismatch occurs between the early programming environment and the later adult environment. These seemingly contradicting hypotheses are integrated into a new model proposing that the cumulative stress hypothesis applies to individuals who were not or only to a small extent programmed by their early environment, while the mismatch hypothesis applies to individuals who experienced strong programming effects. Evidence for the main effects of adversity as well as evidence for the interaction between adversity in early and later life is presented from human observational studies and animal models. Next, convincing evidence for individual differences in sensitivity to programming is presented. We extensively discuss how our integrated model can be tested empirically in animal models and human studies, inviting researchers to test this model. Furthermore, this integrated model should tempt clinicians and other intervenors to interpret symptoms as possible adaptations from an evolutionary biology perspective. Copyright © 2011 Elsevier Inc. All rights reserved.
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Damian, Rodica Ioana; Su, Rong; Shanahan, Michael; Trautwein, Ulrich; Roberts, Brent W
2015-09-01
This study investigated the interplay of family background and individual differences, such as personality traits and intelligence (measured in a large U.S. representative sample of high school students; N = 81,000) in predicting educational attainment, annual income, and occupational prestige 11 years later. Specifically, we tested whether individual differences followed 1 of 3 patterns in relation to parental socioeconomic status (SES) when predicting attained status: (a) the independent effects hypothesis (i.e., individual differences predict attainments independent of parental SES level), (b) the resource substitution hypothesis (i.e., individual differences are stronger predictors of attainments at lower levels of parental SES), and (c) the Matthew effect hypothesis (i.e., "the rich get richer"; individual differences are stronger predictors of attainments at higher levels of parental SES). We found that personality traits and intelligence in adolescence predicted later attained status above and beyond parental SES. A standard deviation increase in individual differences translated to up to 8 additional months of education, $4,233 annually, and more prestigious occupations. Furthermore, although we did find some evidence for both the resource substitution and the Matthew effect hypotheses, the most robust pattern across all models supported the independent effects hypothesis. Intelligence was the exception, the interaction models being more robust. Finally, we found that although personality traits may help compensate for background disadvantage to a small extent, they do not usually lead to a "full catch-up" effect, unlike intelligence. This was the first longitudinal study of status attainment to test interactive models of individual differences and background factors. (c) 2015 APA, all rights reserved).
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Damian, Rodica Ioana; Su, Rong; Shanahan, Michael; Trautwein, Ulrich; Roberts, Brent W.
2014-01-01
This paper investigates the interplay of family background and individual differences, such as personality traits and intelligence (measured in a large US representative sample of high school students; N = 81,000) in predicting educational attainment, annual income, and occupational prestige eleven years later. Specifically, we tested whether individual differences followed one of three patterns in relation to parental SES when predicting attained status: (a) the independent effects hypothesis (i.e., individual differences predict attainments independent of parental SES level), (b) the resource substitution hypothesis (i.e., individual differences are stronger predictors of attainments at lower levels of parental SES), and (c) the Matthew effect hypothesis (i.e., “the rich get richer,” individual differences are stronger predictors of attainments at higher levels of parental SES). We found that personality traits and intelligence in adolescence predicted later attained status above and beyond parental SES. A standard deviation increase in individual differences translated to up to 8 additional months of education, $4,233 annually, and more prestigious occupations. Furthermore, although we did find some evidence for both the resource substitution and the Matthew effect hypotheses, the most robust pattern across all models supported the independent effects hypothesis. Intelligence was the exception, where interaction models were more robust. Finally, we found that although personality traits may help compensate for background disadvantage to a small extent, they do not usually lead to a “full catch up” effect, unlike intelligence. This was the first longitudinal study of status attainment to test interactive models of individual differences and background factors. PMID:25402679
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Application of random effects to the study of resource selection by animals
Gillies, C.S.; Hebblewhite, M.; Nielsen, S.E.; Krawchuk, M.A.; Aldridge, Cameron L.; Frair, J.L.; Saher, D.J.; Stevens, C.E.; Jerde, C.L.
2006-01-01
1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence.2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability.3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed.4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects.5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection.6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.
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Application of random effects to the study of resource selection by animals.
Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L
2006-07-01
1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.
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Li, Linling; Huang, Gan; Lin, Qianqian; Liu, Jia; Zhang, Shengli; Zhang, Zhiguo
2018-01-01
The level of pain perception is correlated with the magnitude of pain-evoked brain responses, such as laser-evoked potentials (LEP), across trials. The positive LEP-pain relationship lays the foundation for pain prediction based on single-trial LEP, but cross-individual pain prediction does not have a good performance because the LEP-pain relationship exhibits substantial cross-individual difference. In this study, we aim to explain the cross-individual difference in the LEP-pain relationship using inter-stimulus EEG (isEEG) features. The isEEG features (root mean square as magnitude and mean square successive difference as temporal variability) were estimated from isEEG data (at full band and five frequency bands) recorded between painful stimuli. A linear model was fitted to investigate the relationship between pain ratings and LEP response for fast-pain trials on a trial-by-trial basis. Then the correlation between isEEG features and the parameters of LEP-pain model (slope and intercept) was evaluated. We found that the magnitude and temporal variability of isEEG could modulate the parameters of an individual's linear LEP-pain model for fast-pain trials. Based on this, we further developed a new individualized fast-pain prediction scheme, which only used training individuals with similar isEEG features as the test individual to train the fast-pain prediction model, and obtained improved accuracy in cross-individual fast-pain prediction. The findings could help elucidate the neural mechanism of cross-individual difference in pain experience and the proposed fast-pain prediction scheme could be potentially used as a practical and feasible pain prediction method in clinical practice. PMID:29904336
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Anderson, John R; Bothell, Daniel; Fincham, Jon M; Anderson, Abraham R; Poole, Ben; Qin, Yulin
2011-12-01
Part- and whole-task conditions were created by manipulating the presence of certain components of the Space Fortress video game. A cognitive model was created for two-part games that could be combined into a model that performed the whole game. The model generated predictions both for behavioral patterns and activation patterns in various brain regions. The activation predictions concerned both tonic activation that was constant in these regions during performance of the game and phasic activation that occurred when there was resource competition. The model's predictions were confirmed about how tonic and phasic activation in different regions would vary with condition. These results support the Decomposition Hypothesis that the execution of a complex task can be decomposed into a set of information-processing components and that these components combine unchanged in different task conditions. In addition, individual differences in learning gains were predicted by individual differences in phasic activation in those regions that displayed highest tonic activity. This individual difference pattern suggests that the rate of learning of a complex skill is determined by capacity limits.
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Helping as a Function of Empathic Responses and Sociopathy.
ERIC Educational Resources Information Center
Marks, Edward L.; And Others
1982-01-01
Investigated helping as a function of empathic anxiety (anxiety in response to modeled distress) and individual differences in sociopathic tendencies. Results indicated modeled distress produces increases in anxiety which are positively associated with helping and sociopathic individuals are less likely to help than are nonsociopathic individuals.…
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Paul A. Murphy; David L. Graney
1988-01-01
Models were developed for individual-tree basal area growth, survival, and total heights for different species of upland hardwoods in the Boston Mountains of north Arkansas. Data used were from 87 permanent plots located in an array of different sites and stand ages; the plots were thinned to different stocking levels and included unthinned controls. To test these...
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Boldness by habituation and social interactions: a model.
Oosten, Johanneke E; Magnhagen, Carin; Hemelrijk, Charlotte K
2010-04-01
Most studies of animal personality attribute personality to genetic traits. But a recent study by Magnhagen and Staffan (Behav Ecol Sociobiol 57:295-303, 2005) on young perch in small groups showed that boldness, a central personality trait, is also shaped by social interactions and by previous experience. The authors measured boldness by recording the duration that an individual spent near a predator and the speed with which it fed there. They found that duration near the predator increased over time and was higher the higher the average boldness of other group members. In addition, the feeding rate of shy individuals was reduced if other members of the same group were bold. The authors supposed that these behavioral dynamics were caused by genetic differences, social interactions, and habituation to the predator. However, they did not quantify exactly how this could happen. In the present study, we therefore use an agent-based model to investigate whether these three factors may explain the empirical findings. We choose an agent-based model because this type of model is especially suited to study the relation between behavior at an individual level and behavioral dynamics at a group level. In our model, individuals were either hiding in vegetation or feeding near a predator, whereby their behavior was affected by habituation and by two social mechanisms: social facilitation to approach the predator and competition over food. We show that even if we start the model with identical individuals, these three mechanisms were sufficient to reproduce the behavioral dynamics of the empirical study, including the consistent differences among individuals. Moreover, if we start the model with individuals that already differ in boldness, the behavioral dynamics produced remained the same. Our results indicate the importance of previous experience and social interactions when studying animal personality empirically.
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ERIC Educational Resources Information Center
Aktas, Idris; Bilgin, Ibrahim
2015-01-01
Background: Many researchers agree that students, especially primary students, have learning difficulties on the "Particulate Nature of Matter" unit. One reason for this difficulty is not considering individual differences for teaching science. In 4MAT model learning, environment is arranged according to individual differences. Purpose:…
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Modeling individual tree survial
Quang V. Cao
2016-01-01
Information provided by growth and yield models is the basis for forest managers to make decisions on how to manage their forests. Among different types of growth models, whole-stand models offer predictions at stand level, whereas individual-tree models give detailed information at tree level. The well-known logistic regression is commonly used to predict tree...
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Origins of Individual Differences in Theory of Mind: From Nature to Nurture?
ERIC Educational Resources Information Center
Hughes, Claire; Jaffee, Sara R.; Happ, Francesca; Taylor, Alan; Caspi, Avshalom; Moffitt, Terrie E.
2005-01-01
In this study of the origins of individual differences in theory of mind (ToM), the Environmental Risk (E-Risk) Longitudinal Twin Study sample of 1,116 sixty-month-old twin pairs completed a comprehensive battery of ToM tasks. Individual differences in ToM were striking and strongly associated with verbal ability. Behavioral genetic models of the…
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Growth Control and Disease Mechanisms in Computational Embryogeny
NASA Technical Reports Server (NTRS)
Shapiro, Andrew A.; Yogev, Or; Antonsson, Erik K.
2008-01-01
This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum 3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads.
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A Linear Variable-[theta] Model for Measuring Individual Differences in Response Precision
ERIC Educational Resources Information Center
Ferrando, Pere J.
2011-01-01
Models for measuring individual response precision have been proposed for binary and graded responses. However, more continuous formats are quite common in personality measurement and are usually analyzed with the linear factor analysis model. This study extends the general Gaussian person-fluctuation model to the continuous-response case and…
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Predicting human chronically paralyzed muscle force: a comparison of three mathematical models.
Frey Law, Laura A; Shields, Richard K
2006-03-01
Chronic spinal cord injury (SCI) induces detrimental musculoskeletal adaptations that adversely affect health status, ranging from muscle paralysis and skin ulcerations to osteoporosis. SCI rehabilitative efforts may increasingly focus on preserving the integrity of paralyzed extremities to maximize health quality using electrical stimulation for isometric training and/or functional activities. Subject-specific mathematical muscle models could prove valuable for predicting the forces necessary to achieve therapeutic loading conditions in individuals with paralyzed limbs. Although numerous muscle models are available, three modeling approaches were chosen that can accommodate a variety of stimulation input patterns. To our knowledge, no direct comparisons between models using paralyzed muscle have been reported. The three models include 1) a simple second-order linear model with three parameters and 2) two six-parameter nonlinear models (a second-order nonlinear model and a Hill-derived nonlinear model). Soleus muscle forces from four individuals with complete, chronic SCI were used to optimize each model's parameters (using an increasing and decreasing frequency ramp) and to assess the models' predictive accuracies for constant and variable (doublet) stimulation trains at 5, 10, and 20 Hz in each individual. Despite the large differences in modeling approaches, the mean predicted force errors differed only moderately (8-15% error; P=0.0042), suggesting physiological force can be adequately represented by multiple mathematical constructs. The two nonlinear models predicted specific force characteristics better than the linear model in nearly all stimulation conditions, with minimal differences between the two nonlinear models. Either nonlinear mathematical model can provide reasonable force estimates; individual application needs may dictate the preferred modeling strategy.
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Howe, Laura D; Tilling, Kate; Matijasevich, Alicia; Petherick, Emily S; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S; Barros, Aluísio Jd; Martin, Richard M; Kramer, Michael S; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A
2016-10-01
Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models. © The Author(s) 2013.
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Tilling, Kate; Matijasevich, Alicia; Petherick, Emily S; Santos, Ana Cristina; Fairley, Lesley; Wright, John; Santos, Iná S.; Barros, Aluísio JD; Martin, Richard M; Kramer, Michael S; Bogdanovich, Natalia; Matush, Lidia; Barros, Henrique; Lawlor, Debbie A
2013-01-01
Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models. PMID:24108269
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Wolf, Tabea; Zimprich, Daniel
2016-10-01
The reminiscence bump phenomenon has frequently been reported for the recall of autobiographical memories. The present study complements previous research by examining individual differences in the distribution of word-cued autobiographical memories. More importantly, we introduce predictor variables that might account for individual differences in the mean (location) and the standard deviation (scale) of individual memory distributions. All variables were derived from different theoretical accounts for the reminiscence bump phenomenon. We used a mixed location-scale logitnormal model, to analyse the 4602 autobiographical memories reported by 118 older participants. Results show reliable individual differences in the location and the scale. After controlling for age and gender, individual proportions of first-time experiences and individual proportions of positive memories, as well as the ratings on Openness to new Experiences and Self-Concept Clarity accounted for 29% of individual differences in location and 42% of individual differences in scale of autobiographical memory distributions. Results dovetail with a life-story account for the reminiscence bump which integrates central components of previous accounts.
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Frasca, Mattia; Sharkey, Kieran J
2016-06-21
Understanding the dynamics of spread of infectious diseases between individuals is essential for forecasting the evolution of an epidemic outbreak or for defining intervention policies. The problem is addressed by many approaches including stochastic and deterministic models formulated at diverse scales (individuals, populations) and different levels of detail. Here we consider discrete-time SIR (susceptible-infectious-removed) dynamics propagated on contact networks. We derive a novel set of 'discrete-time moment equations' for the probability of the system states at the level of individual nodes and pairs of nodes. These equations form a set which we close by introducing appropriate approximations of the joint probabilities appearing in them. For the example case of SIR processes, we formulate two types of model, one assuming statistical independence at the level of individuals and one at the level of pairs. From the pair-based model we then derive a model at the level of the population which captures the behavior of epidemics on homogeneous random networks. With respect to their continuous-time counterparts, the models include a larger number of possible transitions from one state to another and joint probabilities with a larger number of individuals. The approach is validated through numerical simulation over different network topologies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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The interplay between cooperativity and diversity in model threshold ensembles
Cervera, Javier; Manzanares, José A.; Mafe, Salvador
2014-01-01
The interplay between cooperativity and diversity is crucial for biological ensembles because single molecule experiments show a significant degree of heterogeneity and also for artificial nanostructures because of the high individual variability characteristic of nanoscale units. We study the cross-effects between cooperativity and diversity in model threshold ensembles composed of individually different units that show a cooperative behaviour. The units are modelled as statistical distributions of parameters (the individual threshold potentials here) characterized by central and width distribution values. The simulations show that the interplay between cooperativity and diversity results in ensemble-averaged responses of interest for the understanding of electrical transduction in cell membranes, the experimental characterization of heterogeneous groups of biomolecules and the development of biologically inspired engineering designs with individually different building blocks. PMID:25142516
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Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric
2012-08-01
Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.
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Natural Disasters and Human Behavior: Explanation, Research and Models.
ERIC Educational Resources Information Center
Glenn, Christopher
1979-01-01
A survey of published research determined that individual and group reactions to natural disasters differ greatly and depend partially on the predisaster personality. Four models are examined to explain individual and group reactions to natural disasters. A conglomerate model and a possible structure to future disaster research are offered.…
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Jongerling, Joran; Laurenceau, Jean-Philippe; Hamaker, Ellen L
2015-01-01
In this article we consider a multilevel first-order autoregressive [AR(1)] model with random intercepts, random autoregression, and random innovation variance (i.e., the level 1 residual variance). Including random innovation variance is an important extension of the multilevel AR(1) model for two reasons. First, between-person differences in innovation variance are important from a substantive point of view, in that they capture differences in sensitivity and/or exposure to unmeasured internal and external factors that influence the process. Second, using simulation methods we show that modeling the innovation variance as fixed across individuals, when it should be modeled as a random effect, leads to biased parameter estimates. Additionally, we use simulation methods to compare maximum likelihood estimation to Bayesian estimation of the multilevel AR(1) model and investigate the trade-off between the number of individuals and the number of time points. We provide an empirical illustration by applying the extended multilevel AR(1) model to daily positive affect ratings from 89 married women over the course of 42 consecutive days.
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Phuong, H N; Martin, O; de Boer, I J M; Ingvartsen, K L; Schmidely, Ph; Friggens, N C
2015-01-01
This study explored the ability of an existing lifetime nutrient partitioning model for simulating individual variability in genetic potentials of dairy cows. Generally, the model assumes a universal trajectory of dynamic partitioning of priority between life functions and genetic scaling parameters are then incorporated to simulate individual difference in performance. Data of 102 cows including 180 lactations of 3 breeds: Danish Red, Danish Holstein, and Jersey, which were completely independent from those used previously for model development, were used. Individual cow performance records through sequential lactations were used to derive genetic scaling parameters for each animal by calibrating the model to achieve best fit, cow by cow. The model was able to fit individual curves of body weight, and milk fat, milk protein, and milk lactose concentrations with a high degree of accuracy. Daily milk yield and dry matter intake were satisfactorily predicted in early and mid lactation, but underpredictions were found in late lactation. Breeds and parities did not significantly affect the prediction accuracy. The means of genetic scaling parameters between Danish Red and Danish Holstein were similar but significantly different from those of Jersey. The extent of correlations between the genetic scaling parameters was consistent with that reported in the literature. In conclusion, this model is of value as a tool to derive estimates of genetic potentials of milk yield, milk composition, body reserve usage, and growth for different genotypes of cow. Moreover, it can be used to separate genetic variability in performance between individual cows from environmental noise. The model enables simulation of the effects of a genetic selection strategy on lifetime efficiency of individual cows, which has a main advantage of including the rearing costs, and thus, can be used to explore the impact of future selection on animal performance and efficiency. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Individual heterogeneity in reproductive rates and cost of reproduction in a long-lived vertebrate
Chambert, Thierry; Rotella, Jay J; Higgs, Megan D; Garrott, Robert A
2013-01-01
Individual variation in reproductive success is a key feature of evolution, but also has important implications for predicting population responses to variable environments. Although such individual variation in reproductive outcomes has been reported in numerous studies, most analyses to date have not considered whether these realized differences were due to latent individual heterogeneity in reproduction or merely random chance causing different outcomes among like individuals. Furthermore, latent heterogeneity in fitness components might be expressed differently in contrasted environmental conditions, an issue that has only rarely been investigated. Here, we assessed (i) the potential existence of latent individual heterogeneity and (ii) the nature of its expression (fixed vs. variable) in a population of female Weddell seals (Leptonychotes weddellii), using a hierarchical modeling approach on a 30-year mark–recapture data set consisting of 954 individual encounter histories. We found strong support for the existence of latent individual heterogeneity in the population, with “robust” individuals expected to produce twice as many pups as “frail” individuals. Moreover, the expression of individual heterogeneity appeared consistent, with only mild evidence that it might be amplified when environmental conditions are severe. Finally, the explicit modeling of individual heterogeneity allowed us to detect a substantial cost of reproduction that was not evidenced when the heterogeneity was ignored. PMID:23919151
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The potential of composite cognitive scores for tracking progression in Huntington's disease.
Jones, Rebecca; Stout, Julie C; Labuschagne, Izelle; Say, Miranda; Justo, Damian; Coleman, Allison; Dumas, Eve M; Hart, Ellen; Owen, Gail; Durr, Alexandra; Leavitt, Blair R; Roos, Raymund; O'Regan, Alison; Langbehn, Doug; Tabrizi, Sarah J; Frost, Chris
2014-01-01
Composite scores derived from joint statistical modelling of individual risk factors are widely used to identify individuals who are at increased risk of developing disease or of faster disease progression. We investigated the ability of composite measures developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls. Using longitudinal data from TRACK-HD, the optimal combinations of quantitative cognitive measures to differentiate premanifest and early stage HD individuals respectively from controls was determined using logistic regression. Composite scores were calculated from the parameters of each statistical model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change over 24 months between premanifest and early stage HD groups respectively and controls. ES for the composites were compared with ES for individual cognitive outcomes and other measures used in HD research. The 0.632 bootstrap was used to eliminate biases which result from developing and testing models in the same sample. In early HD, the composite score from the HD change prediction model produced an ES for difference in rate of 24-month change relative to controls of 1.14 (95% CI: 0.90 to 1.39), larger than the ES for any individual cognitive outcome and UHDRS Total Motor Score and Total Functional Capacity. In addition, this composite gave a statistically significant difference in rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI: 0.04 to 0.44), even though none of the individual cognitive outcomes produced statistically significant ES over this period. Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.
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Lonsdorf, Tina B; Merz, Christian J
2017-09-01
Why do only some individuals develop pathological anxiety following adverse events? Fear acquisition, extinction and return of fear paradigms serve as experimental learning models for the development, treatment and relapse of anxiety. Individual differences in experimental performance were however mostly regarded as 'noise' by researchers interested in basic associative learning principles. Our work for the first time presents a comprehensive literature overview and methodological discussion on inter-individual differences in fear acquisition, extinction and return of fear. We tell a story from noise that steadily develops into a meaningful tune and converges to a model of mechanisms contributing to individual risk/resilience with respect to fear and anxiety-related behavior. Furthermore, in light of the present 'replicability crisis' we identify methodological pitfalls and provide suggestions for study design and analyses tailored to individual difference research in fear conditioning. Ultimately, synergistic transdisciplinary and collaborative efforts hold promise to not only improve our mechanistic understanding but can also be expected to contribute to the development of specifically tailored ('individualized') intervention and targeted prevention programs in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Zhang, Shiyu; Baams, Laura; van de Bongardt, Daphne; Dubas, Judith Semon
2018-05-01
Utilizing four waves of data from 1126 secondary school Dutch adolescents (Mage = 13.95 at the first wave; 53% boys), the current study examined the interplay between parent-adolescent and friend-adolescent relationship quality (satisfaction and conflict) in relation to adolescents' depressive mood. Using multilevel analyses, the interacting effects of parent/friend relationship quality on depressive mood were tested at both the intra- and inter-individual level. Analyses at the intra-individual level investigated whether individual depressive mood fluctuated along with changes in their social relationships regardless of one's general level of depressive mood; and analyses at the inter-individual level examined whether the average differences in depressive mood between adolescents were associated with different qualities of social relationships. We interpreted the patterns of interactions between parent and friend relationships using four theoretical models: the reinforcement, toxic friends, compensation, and additive model. The results demonstrate the covariation of parent- and friend- relationship quality with adolescents' depressive mood, and highlight that parent and peer effects are not independent from each other-affirming the compensation and additive models at the intra-individual and the reinforcement and additive models at the inter-individual level. The findings highlight the robustness of the protective effects of parent and peer support and the deleterious effects of conflictual relationships for adolescent mental health. The results have implications for both the theoretical and practical design of (preventive) interventions aimed at decreasing adolescents' depressive mood.
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ERIC Educational Resources Information Center
Steacy, Laura M.; Kearns, Devin M.; Gilbert, Jennifer K.; Compton, Donald L.; Cho, Eunsoo; Lindstrom, Esther R.; Collins, Alyson A.
2017-01-01
Models of irregular word reading that take into account both child- and word-level predictors have not been evaluated in typically developing children and children with reading difficulty (RD). The purpose of the present study was to model individual differences in irregular word reading ability among 5th grade children (N = 170), oversampled for…
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Sadeghi, Neda; Prastawa, Marcel; Fletcher, P Thomas; Gilmore, John H; Lin, Weili; Gerig, Guido
2012-01-01
A population growth model that represents the growth trajectories of individual subjects is critical to study and understand neurodevelopment. This paper presents a framework for jointly estimating and modeling individual and population growth trajectories, and determining significant regional differences in growth pattern characteristics applied to longitudinal neuroimaging data. We use non-linear mixed effect modeling where temporal change is modeled by the Gompertz function. The Gompertz function uses intuitive parameters related to delay, rate of change, and expected asymptotic value; all descriptive measures which can answer clinical questions related to growth. Our proposed framework combines nonlinear modeling of individual trajectories, population analysis, and testing for regional differences. We apply this framework to the study of early maturation in white matter regions as measured with diffusion tensor imaging (DTI). Regional differences between anatomical regions of interest that are known to mature differently are analyzed and quantified. Experiments with image data from a large ongoing clinical study show that our framework provides descriptive, quantitative information on growth trajectories that can be directly interpreted by clinicians. To our knowledge, this is the first longitudinal analysis of growth functions to explain the trajectory of early brain maturation as it is represented in DTI.
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Modelling nutrition across organizational levels: from individuals to superorganisms.
Lihoreau, Mathieu; Buhl, Jerome; Charleston, Michael A; Sword, Gregory A; Raubenheimer, David; Simpson, Stephen J
2014-10-01
The Geometric Framework for nutrition has been increasingly used to describe how individual animals regulate their intake of multiple nutrients to maintain target physiological states maximizing growth and reproduction. However, only a few studies have considered the potential influences of the social context in which these nutritional decisions are made. Social insects, for instance, have evolved extreme levels of nutritional interdependence in which food collection, processing, storage and disposal are performed by different individuals with different nutritional needs. These social interactions considerably complicate nutrition and raise the question of how nutrient regulation is achieved at multiple organizational levels, by individuals and groups. Here, we explore the connections between individual- and collective-level nutrition by developing a modelling framework integrating concepts of nutritional geometry into individual-based models. Using this approach, we investigate how simple nutritional interactions between individuals can mediate a range of emergent collective-level phenomena in social arthropods (insects and spiders) and provide examples of novel and empirically testable predictions. We discuss how our approach could be expanded to a wider range of species and social systems. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Lockwood, Penelope; Marshall, Tara C; Sadler, Pamela
2005-03-01
In two studies, cross-cultural differences in reactions to positive and negative role models were examined. The authors predicted that individuals from collectivistic cultures, who have a stronger prevention orientation, would be most motivated by negative role models, who highlight a strategy of avoiding failure; individuals from individualistic cultures, who have a stronger promotion focus, would be most motivated by positive role models, who highlight a strategy of pursuing success. In Study 1, the authors examined participants' reported preferences for positive and negative role models. Asian Canadian participants reported finding negative models more motivating than did European Canadians; self-construals and regulatory focus mediated cultural differences in reactions to role models. In Study 2, the authors examined the impact of role models on the academic motivation of Asian Canadian and European Canadian participants. Asian Canadians were motivated only by a negative model, and European Canadians were motivated only by a positive model.
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Predicting the size of individual and group differences on speeded cognitive tasks.
Chen, Jing; Hale, Sandra; Myerson, Joel
2007-06-01
An a priori test of the difference engine model (Myerson, Hale, Zheng, Jenkins, & Widaman, 2003) was conducted using a large, diverse sample of individuals who performed three speeded verbal tasks and three speeded visuospatial tasks. Results demonstrated that, as predicted by the model, the group standard deviation (SD) on any task was proportional to the amount of processing required by that task. Both individual performances as well as those of fast and slow subgroups could be accurately predicted by the model using no free parameters, just an individual or subgroup's mean z-score and the values of theoretical constructs estimated from fits to the group SDs. Taken together, these results are consistent with post hoc analyses reported by Myerson et al. and provide even stronger supporting evidence. In particular, the ability to make quantitative predictions without using any free parameters provides the clearest demonstration to date of the power of an analytic approach on the basis of the difference engine.
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How Programming Can Make a Difference for Gifted Students--A Multi-Methods Model.
ERIC Educational Resources Information Center
Hall, Eleanor G.
A multimethod model of educating gifted and talented students was based on graduate students' study of 14 eminent self actualized individuals. Common environmental elements of these individuals were found in parent background, birth order, relationship with family, education, task commitment, personality traits, and interests. The model was…
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The financial impact of employment decisions for individuals with HIV.
Cho, Elizabeth; Chan, Kee
2013-01-01
Individuals living with HIV face challenging employment decisions that have personal, financial, and health impacts. The decision to stay or to leave the work force is much more complicated for an individual with HIV because the financial choices related to potential health benefits are not clearly understood. To assist in the decision-making process for an individual with HIV, we propose to develop a decision model that compares the potential costs and benefits of staying in or leaving the work force. A hypothetical cohort of HIV-infected individuals was simulated in our decision model. Characteristics of these individuals over a one-year period were extracted from the medical literature and publicly available national surveys. Men and women between the ages of 18 and 59 were included in our simulated cohort. A decision tree model was created to estimate the financial impact of an individual's decision on employment. The outcomes were presented as the cost-savings associated with the following employment statuses over a one-year period: 1) staying full-time, 2) switching from full-to part-time, 3) transitioning from full-time to unemployment, and 4) staying unemployed. CD4 T cell counts and employment statuses were stratified by earned income. Employment probabilities were calculated from national databases on employment trends in the United States. Sensitivity analyses were conducted to test the robustness of the effects of the variables on the outcomes. Overall, the decision outcome that resulted in the least financial loss for individuals with HIV was to remain at work. For an individual with CD4 T cell count > 350, the cost difference between staying employed full-time and switching from full-time to part-time status was a maximum of $2,970. For an individual with a CD4 T cell count between 200 and 350, the cost difference was as low as $126 and as great as $2,492. For an individual with a CD4 T cell count < 200, the minimum cost difference was $375 and the maximum cost difference was $2,253. Based on our simulated model, we recommend an individual with CD4 T cell count > 350 to stay employed full-time because it resulted in the least financial loss. On the other hand, for an individual with a CD4 T cell < 350, the financial cost loss was much more variable. Our model provides an objective decision-making guide for individuals with HIV to weigh the costs and benefits of employment decisions.
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Individual differences in learning predict the return of fear.
Gershman, Samuel J; Hartley, Catherine A
2015-09-01
Using a laboratory analogue of learned fear (Pavlovian fear conditioning), we show that there is substantial heterogeneity across individuals in spontaneous recovery of fear following extinction training. We propose that this heterogeneity might stem from qualitative individual differences in the nature of extinction learning. Whereas some individuals tend to form a new memory during extinction, leaving their fear memory intact, others update the original threat association with new safety information, effectively unlearning the fear memory. We formalize this account in a computational model of fear learning and show that individuals who, according to the model, are more likely to form new extinction memories tend to show greater spontaneous recovery compared to individuals who appear to only update a single memory. This qualitative variation in fear and extinction learning may have important implications for understanding vulnerability and resilience to fear-related psychiatric disorders.
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Behavioral and neuronal determinants of negative reciprocity in the ultimatum game
Hildebrandt, Andrea; Wilhelm, Oliver; Sommer, Werner
2016-01-01
The rejection of unfair offers in the ultimatum game (UG) indicates negative reciprocity. The model of strong reciprocity claims that negative reciprocity reflects prosociality because the rejecting individual is sacrificing resources in order to punish unfair behavior. However, a recent study found that the rejection rate of unfair offers is linked to assertiveness (status defense model). To pursue the question what drives negative reciprocity, the present study investigated individual differences in the rejection of unfair offers along with their behavioral and neuronal determinants. We measured fairness preferences and event-related potentials (ERP) in 200 healthy participants playing a computerized version of the UG with pictures of unfair and fair proposers. Structural equation modeling (SEM) on the behavioral data corroborated both the strong reciprocity and the status defense models of human cooperation: Not only more prosocial but also more assertive individuals were more likely to show negative reciprocity by rejecting unfair offers. Experimental ERP results confirmed the feedback negativity (FN) as a neural signature of fairness processing. Multilevel SEM of brain–behavior relationships revealed that negative reciprocity was significantly associated with individual differences in FN amplitudes in response to proposers. Our results confirm stable individual differences in fairness processing at the behavioral and neuronal level. PMID:27261490
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The interplay between cooperativity and diversity in model threshold ensembles.
Cervera, Javier; Manzanares, José A; Mafe, Salvador
2014-10-06
The interplay between cooperativity and diversity is crucial for biological ensembles because single molecule experiments show a significant degree of heterogeneity and also for artificial nanostructures because of the high individual variability characteristic of nanoscale units. We study the cross-effects between cooperativity and diversity in model threshold ensembles composed of individually different units that show a cooperative behaviour. The units are modelled as statistical distributions of parameters (the individual threshold potentials here) characterized by central and width distribution values. The simulations show that the interplay between cooperativity and diversity results in ensemble-averaged responses of interest for the understanding of electrical transduction in cell membranes, the experimental characterization of heterogeneous groups of biomolecules and the development of biologically inspired engineering designs with individually different building blocks. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
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Validation of simplified centre of mass models during gait in individuals with chronic stroke.
Huntley, Andrew H; Schinkel-Ivy, Alison; Aqui, Anthony; Mansfield, Avril
2017-10-01
The feasibility of using a multiple segment (full-body) kinematic model in clinical gait assessment is difficult when considering obstacles such as time and cost constraints. While simplified gait models have been explored in healthy individuals, no such work to date has been conducted in a stroke population. The aim of this study was to quantify the errors of simplified kinematic models for chronic stroke gait assessment. Sixteen individuals with chronic stroke (>6months), outfitted with full body kinematic markers, performed a series of gait trials. Three centre of mass models were computed: (i) 13-segment whole-body model, (ii) 3 segment head-trunk-pelvis model, and (iii) 1 segment pelvis model. Root mean squared error differences were compared between models, along with correlations to measures of stroke severity. Error differences revealed that, while both models were similar in the mediolateral direction, the head-trunk-pelvis model had less error in the anteroposterior direction and the pelvis model had less error in the vertical direction. There was some evidence that the head-trunk-pelvis model error is influenced in the mediolateral direction for individuals with more severe strokes, as a few significant correlations were observed between the head-trunk-pelvis model and measures of stroke severity. These findings demonstrate the utility and robustness of the pelvis model for clinical gait assessment in individuals with chronic stroke. Low error in the mediolateral and vertical directions is especially important when considering potential stability analyses during gait for this population, as lateral stability has been previously linked to fall risk. Copyright © 2017 Elsevier Ltd. All rights reserved.
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LATENT SPACE MODELS FOR MULTIVIEW NETWORK DATA
Salter-Townshend, Michael; McCormick, Tyler H.
2018-01-01
Social relationships consist of interactions along multiple dimensions. In social networks, this means that individuals form multiple types of relationships with the same person (e.g., an individual will not trust all of his/her acquaintances). Statistical models for these data require understanding two related types of dependence structure: (i) structure within each relationship type, or network view, and (ii) the association between views. In this paper, we propose a statistical framework that parsimoniously represents dependence between relationship types while also maintaining enough flexibility to allow individuals to serve different roles in different relationship types. Our approach builds on work on latent space models for networks [see, e.g., J. Amer. Statist. Assoc. 97 (2002) 1090–1098]. These models represent the propensity for two individuals to form edges as conditionally independent given the distance between the individuals in an unobserved social space. Our work departs from previous work in this area by representing dependence structure between network views through a multivariate Bernoulli likelihood, providing a representation of between-view association. This approach infers correlations between views not explained by the latent space model. Using our method, we explore 6 multiview network structures across 75 villages in rural southern Karnataka, India [Banerjee et al. (2013)]. PMID:29721127
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LATENT SPACE MODELS FOR MULTIVIEW NETWORK DATA.
Salter-Townshend, Michael; McCormick, Tyler H
2017-09-01
Social relationships consist of interactions along multiple dimensions. In social networks, this means that individuals form multiple types of relationships with the same person (e.g., an individual will not trust all of his/her acquaintances). Statistical models for these data require understanding two related types of dependence structure: (i) structure within each relationship type, or network view, and (ii) the association between views. In this paper, we propose a statistical framework that parsimoniously represents dependence between relationship types while also maintaining enough flexibility to allow individuals to serve different roles in different relationship types. Our approach builds on work on latent space models for networks [see, e.g., J. Amer. Statist. Assoc. 97 (2002) 1090-1098]. These models represent the propensity for two individuals to form edges as conditionally independent given the distance between the individuals in an unobserved social space. Our work departs from previous work in this area by representing dependence structure between network views through a multivariate Bernoulli likelihood, providing a representation of between-view association. This approach infers correlations between views not explained by the latent space model. Using our method, we explore 6 multiview network structures across 75 villages in rural southern Karnataka, India [Banerjee et al. (2013)].
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Philosophically Precocious Individuals and Their Developmental Strategies.
ERIC Educational Resources Information Center
Bai, Wenyu
This study interviewed five philosophically precocious individuals (PPIs), four Chinese and one American, to examine their development. Theoretical frameworks used to evaluate data were the Transcendence Evolution Model and the taxonomy of developmental strategies. The Transcendence Evolution Model posits that children's different developmental…
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Animal personality and state-behaviour feedbacks: a review and guide for empiricists.
Sih, Andrew; Mathot, Kimberley J; Moirón, María; Montiglio, Pierre-Olivier; Wolf, Max; Dingemanse, Niels J
2015-01-01
An exciting area in behavioural ecology focuses on understanding why animals exhibit consistent among-individual differences in behaviour (animal personalities). Animal personality has been proposed to emerge as an adaptation to individual differences in state variables, leading to the question of why individuals differ consistently in state. Recent theory emphasizes the role that positive feedbacks between state and behaviour can play in producing consistent among-individual covariance between state and behaviour, hence state-dependent personality. We review the role of feedbacks in recent models of adaptive personalities, and provide guidelines for empirical testing of model assumptions and predictions. We discuss the importance of the mediating effects of ecology on these feedbacks, and provide a roadmap for including state-behaviour feedbacks in behavioural ecology research. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Capasso, Roberto; Zurlo, Maria Clelia; Smith, Andrew P
2018-02-01
This study integrates different aspects of ethnicity and work-related stress dimensions (based on the Demands-Resources-Individual-Effects model, DRIVE [Mark, G. M., and A. P. Smith. 2008. "Stress Models: A Review and Suggested New Direction." In Occupational Health Psychology, edited by J. Houdmont and S. Leka, 111-144. Nottingham: Nottingham University Press]) and aims to test a multi-dimensional model that combines individual differences, ethnicity dimensions, work characteristics, and perceived job satisfaction/stress as independent variables in the prediction of subjectives reports of health by workers differing in ethnicity. A questionnaire consisting of the following sections was submitted to 900 workers in Southern Italy: for individual and cultural characteristics, coping strategies, personality behaviours, and acculturation strategies; for work characteristics, perceived job demands and job resources/rewards; for appraisals, perceived job stress/satisfaction and racial discrimination; for subjective reports of health, psychological disorders and general health. To test the reliability and construct validity of the extracted factors referred to all dimensions involved in the proposed model and logistic regression analyses to evaluate the main effects of the independent variables on the health outcomes were conducted. Principal component analysis (PCA) yielded seven factors for individual and cultural characteristics (emotional/relational coping, objective coping, Type A behaviour, negative affectivity, social inhibition, affirmation/maintenance culture, and search identity/adoption of the host culture); three factors for work characteristics (work demands, intrinsic/extrinsic rewards, and work resources); three factors for appraisals (perceived job satisfaction, perceived job stress, perceived racial discrimination) and three factors for subjective reports of health (interpersonal disorders, anxious-depressive disorders, and general health). Logistic regression analyses showed main effects of specific individual and cultural differences, work characteristics and perceived job satisfaction/stress on the risk of suffering health problems. The suggested model provides a strong framework that illustrates how psychosocial and individual variables can influence occupational health in multi-cultural workplaces.
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Are Some Negotiators Better Than Others? Individual Differences in Bargaining Outcomes
Elfenbein, Hillary Anger; Curhan, Jared R.; Eisenkraft, Noah; Shirako, Aiwa; Baccaro, Lucio
2008-01-01
The authors address the long-standing mystery of stable individual differences in negotiation performance, on which intuition and conventional wisdom have clashed with inconsistent empirical findings. The present study used the Social Relations Model to examine individual differences directly via consistency in performance across multiple negotiations and to disentangle the roles of both parties within these inherently dyadic interactions. Individual differences explained a substantial 46% of objective performance and 19% of subjective performance in a mixed-motive bargaining exercise. Previous work may have understated the influence of individual differences because conventional research designs require specific traits to be identified and measured. Exploratory analyses of a battery of traits revealed few reliable associations with consistent individual differences in objective performance—except for positive beliefs about negotiation, positive affect, and concern for one's outcome, each of which predicted better performance. Findings suggest that the field has large untapped potential to explain substantial individual differences. Limitations, areas for future research, and practical implications are discussed. PMID:21720453
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Christopher, Micaela E.; Hulslander, Jacqueline; Byrne, Brian; Samuelsson, Stefan; Keenan, Janice M.; Pennington, Bruce; DeFries, John C.; Wadsworth, Sally J.; Willcutt, Erik; Olson, Richard K.
2013-01-01
This first cross-country twin study of individual differences in reading growth from post-kindergarten to post-2nd grade analyzed data from 487 twin pairs from the United States, 267 pairs from Australia, and 280 pairs from Scandinavia. Data from two reading measures were fit to biometric latent growth models. Individual differences for the reading measures at post-kindergarten in the U.S. and Australia were due primarily to genetic influences, and to both genetic and shared environmental influences in Scandinavia. In contrast, individual differences in growth generally had large genetic influences in all countries. These results suggest that genetic influences are largely responsible for individual differences in early reading development. In addition, the timing of the start of formal literacy instruction may affect the etiology of individual differences in early reading development, but have only limited influence on the etiology of individual differences in growth. PMID:23665180
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Patel, Ronak; Page, Shyanne; Al-Ahmad, Abraham Jacob
2017-07-01
The blood-brain barrier (BBB) constitutes an important component of the neurovascular unit formed by specialized brain microvascular endothelial cells (BMECs) surrounded by astrocytes, pericytes, and neurons. Recently, isogenic in vitro models of the BBB based on human pluripotent stem cells have been documented, yet the impact of inter-individual variability on the yield and phenotype of such models remains to be documented. In this study, we investigated the impact of inter-individual variability on the yield and phenotype of isogenic models of the BBB, using patient-derived induced pluripotent stem cells (iPSCs). Astrocytes, BMECs, and neurons were differentiated from four asymptomatic patient-derived iPSCs (two males, two females). We differentiated such cells using existing differentiation protocols and quantified expression of cell lineage markers, as well as BBB phenotype, barrier induction, and formation of neurite processes. iPSC-derived BMECs showed barrier properties better than hCMEC/D3 monolayers; however, we noted differences in the expression and activity among iPSC lines. In addition, we noted differences in the differentiation efficiency of these cells into neural stem cells and progenitor cells (as noted by differences in expression of cell lineage markers). Such differences were reflected later in the terminal differentiation, as seen as ability to induce barrier function and to form neurite processes. Although we demonstrated our ability to obtain an isogenic model of the BBB with different patients' iPSCs, we also noted subtle differences in the expression of cell lineage markers and cell maturation processes, suggesting the presence of inter-individual polymorphisms. © 2017 International Society for Neurochemistry.
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Of goals and habits: age-related and individual differences in goal-directed decision-making.
Eppinger, Ben; Walter, Maik; Heekeren, Hauke R; Li, Shu-Chen
2013-01-01
In this study we investigated age-related and individual differences in habitual (model-free) and goal-directed (model-based) decision-making. Specifically, we were interested in three questions. First, does age affect the balance between model-based and model-free decision mechanisms? Second, are these age-related changes due to age differences in working memory (WM) capacity? Third, can model-based behavior be affected by manipulating the distinctiveness of the reward value of choice options? To answer these questions we used a two-stage Markov decision task in in combination with computational modeling to dissociate model-based and model-free decision mechanisms. To affect model-based behavior in this task we manipulated the distinctiveness of reward probabilities of choice options. The results show age-related deficits in model-based decision-making, which are particularly pronounced if unexpected reward indicates the need for a shift in decision strategy. In this situation younger adults explore the task structure, whereas older adults show perseverative behavior. Consistent with previous findings, these results indicate that older adults have deficits in the representation and updating of expected reward value. We also observed substantial individual differences in model-based behavior. In younger adults high WM capacity is associated with greater model-based behavior and this effect is further elevated when reward probabilities are more distinct. However, in older adults we found no effect of WM capacity. Moreover, age differences in model-based behavior remained statistically significant, even after controlling for WM capacity. Thus, factors other than decline in WM, such as deficits in the in the integration of expected reward value into strategic decisions may contribute to the observed impairments in model-based behavior in older adults.
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Of goals and habits: age-related and individual differences in goal-directed decision-making
Eppinger, Ben; Walter, Maik; Heekeren, Hauke R.; Li, Shu-Chen
2013-01-01
In this study we investigated age-related and individual differences in habitual (model-free) and goal-directed (model-based) decision-making. Specifically, we were interested in three questions. First, does age affect the balance between model-based and model-free decision mechanisms? Second, are these age-related changes due to age differences in working memory (WM) capacity? Third, can model-based behavior be affected by manipulating the distinctiveness of the reward value of choice options? To answer these questions we used a two-stage Markov decision task in in combination with computational modeling to dissociate model-based and model-free decision mechanisms. To affect model-based behavior in this task we manipulated the distinctiveness of reward probabilities of choice options. The results show age-related deficits in model-based decision-making, which are particularly pronounced if unexpected reward indicates the need for a shift in decision strategy. In this situation younger adults explore the task structure, whereas older adults show perseverative behavior. Consistent with previous findings, these results indicate that older adults have deficits in the representation and updating of expected reward value. We also observed substantial individual differences in model-based behavior. In younger adults high WM capacity is associated with greater model-based behavior and this effect is further elevated when reward probabilities are more distinct. However, in older adults we found no effect of WM capacity. Moreover, age differences in model-based behavior remained statistically significant, even after controlling for WM capacity. Thus, factors other than decline in WM, such as deficits in the in the integration of expected reward value into strategic decisions may contribute to the observed impairments in model-based behavior in older adults. PMID:24399925
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Real-time individualization of the unified model of performance.
Liu, Jianbo; Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Balkin, Thomas J; Reifman, Jaques
2017-12-01
Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available. We assessed the algorithm's performance by simulating real-time model individualization for 18 subjects subjected to 64 h of total sleep deprivation (TSD) and 7 days of chronic sleep restriction (CSR) with 3 h of time in bed per night, using psychomotor vigilance task (PVT) data collected every 2 h during wakefulness. This UMP individualization process produced parameter estimates that progressively approached the solution produced by a post-hoc fitting of model parameters using all data. The minimum number of PVT measurements needed to individualize the model parameters depended upon the type of sleep-loss challenge, with ~30 required for TSD and ~70 for CSR. However, model individualization depended upon the overall duration of data collection, yielding increasingly accurate model parameters with greater number of days. Interestingly, reducing the PVT sampling frequency by a factor of two did not notably hamper model individualization. The proposed algorithm facilitates real-time learning of an individual's trait-like responses to sleep loss and enables the development of individualized performance prediction models for use in a mobile computing platform. © 2017 European Sleep Research Society.
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Investigating Individual Differences in Toddler Search with Mixture Models
ERIC Educational Resources Information Center
Berthier, Neil E.; Boucher, Kelsea; Weisner, Nina
2015-01-01
Children's performance on cognitive tasks is often described in categorical terms in that a child is described as either passing or failing a test, or knowing or not knowing some concept. We used binomial mixture models to determine whether individual children could be classified as passing or failing two search tasks, the DeLoache model room…
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Simulating natural selection in landscape genetics
E. L. Landguth; S. A. Cushman; N. Johnson
2012-01-01
Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially- explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal...
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Fringe Benefits Available to Supported Employment Participants.
ERIC Educational Resources Information Center
West, Michael; And Others
1990-01-01
Examined fringe benefits available to individuals in supported employment. Found that 64 percent of supported employees received fringe benefits. Found significant differences in availability of particular benefits across employment models. Medical-health insurance coverage was available more frequently to persons in individual placement models.…
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Constraints on decision making: implications from genetics, personality, and addiction.
Baker, Travis E; Stockwell, Tim; Holroyd, Clay B
2013-09-01
An influential neurocomputational theory of the biological mechanisms of decision making, the "basal ganglia go/no-go model," holds that individual variability in decision making is determined by differences in the makeup of a striatal system for approach and avoidance learning. The model has been tested empirically with the probabilistic selection task (PST), which determines whether individuals learn better from positive or negative feedback. In accordance with the model, in the present study we examined whether an individual's ability to learn from positive and negative reinforcement can be predicted by genetic factors related to the midbrain dopamine system. We also asked whether psychiatric and personality factors related to substance dependence and dopamine affect PST performance. Although we found characteristics that predicted individual differences in approach versus avoidance learning, these observations were qualified by additional findings that appear inconsistent with the predictions of the go/no-go model. These results highlight a need for future research to validate the PST as a measure of basal ganglia reward learning.
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Perspective Taking, Cultural Stress, and the Individual: From the Inside Out
2014-05-01
how Soldier individual differences, cultural stress, and perspective taking affect decision making through the Relevant Information for Social ...Cultural Depiction. This report will show that inclusion of individual difference variables is essential to social -cultural model development, which will...are capable of inducing a stress response. Common external stressors fall within four general categories: personal, social /familial, work, and the
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Sex Differences and Neurodevelopmental Variables: A Vector Model
ERIC Educational Resources Information Center
Languis, Marlin; Naour, Paul
For the individual, gender difference falls along the feminine-masculine continuum with strong neurodevelopmental influences at various points throughout the lifespan. Neurodevelopmental influences are conceptualized in a vector model of sex difference. Vector attributes, direction and magnitude, are influenced initially by differences in levels…
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NASA Astrophysics Data System (ADS)
Ito, Shin-Ichi; Mitsukura, Yasue; Nakamura Miyamura, Hiroko; Saito, Takafumi; Fukumi, Minoru
EEG is characterized by the unique and individual characteristics. Little research has been done to take into account the individual characteristics when analyzing EEG signals. Often the EEG has frequency components which can describe most of the significant characteristics. Then there is the difference of importance between the analyzed frequency components of the EEG. We think that the importance difference shows the individual characteristics. In this paper, we propose a new EEG extraction method of characteristic vector by a latency structure model in individual characteristics (LSMIC). The LSMIC is the latency structure model, which has personal error as the individual characteristics, based on normal distribution. The real-coded genetic algorithms (RGA) are used for specifying the personal error that is unknown parameter. Moreover we propose an objective estimation method that plots the EEG characteristic vector on a visualization space. Finally, the performance of the proposed method is evaluated using a realistic simulation and applied to a real EEG data. The result of our experiment shows the effectiveness of the proposed method.
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Building the bridge between animal movement and population dynamics.
Morales, Juan M; Moorcroft, Paul R; Matthiopoulos, Jason; Frair, Jacqueline L; Kie, John G; Powell, Roger A; Merrill, Evelyn H; Haydon, Daniel T
2010-07-27
While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through 'spatially informed' movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission-fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction.
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Anderson, John R.; Bothell, Daniel; Fincham, Jon M.; Anderson, Abraham R.; Poole, Ben; Qin, Yulin
2013-01-01
Part- and whole-task conditions were created by manipulating the presence of certain components of the Space Fortress video game. A cognitive model was created for two-part games that could be combined into a model that performed the whole game. The model generated predictions both for behavioral patterns and activation patterns in various brain regions. The activation predictions concerned both tonic activation that was constant in these regions during performance of the game and phasic activation that occurred when there was resource competition. The model’s predictions were confirmed about how tonic and phasic activation in different regions would vary with condition. These results support the Decomposition Hypothesis that the execution of a complex task can be decomposed into a set of information-processing components and that these components combine unchanged in different task conditions. In addition, individual differences in learning gains were predicted by individual differences in phasic activation in those regions that displayed highest tonic activity. This individual difference pattern suggests that the rate of learning of a complex skill is determined by capacity limits. PMID:21557648
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Is job a viable unit of analysis? A multilevel analysis of demand-control-support models.
Morrison, David; Payne, Roy L; Wall, Toby D
2003-07-01
The literature has ignored the fact that the demand-control (DC) and demand-control-support (DCS) models of stress are about jobs and not individuals' perceptions of their jobs. Using multilevel modeling, the authors report results of individual- and job-level analyses from a study of over 6,700 people in 81 different jobs. Support for additive versions of the models came when individuals were the unit of analysis. DC and DCS models are only helpful for understanding the effects of individual perceptions of jobs and their relationship to psychological states. When job perceptions are aggregated and their relationship to the collective experience of jobholders is assessed, the models prove of little value. Role set may be a better unit of analysis.
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Quinn, Francis; Johnston, Marie; Johnston, Derek W
2013-01-01
Previous research has supported an integrated biomedical and behavioural model explaining activity limitations. However, further tests of this model are required at the within-person level, because while it proposes that the constructs are related within individuals, it has primarily been tested between individuals in large group studies. We aimed to test the integrated model at the within-person level. Six correlational N-of-1 studies in participants with arthritis, chronic pain and walking limitations were carried out. Daily measures of theoretical constructs were collected using a hand-held computer (PDA), the activity was assessed by self-report and accelerometer and the data were analysed using time-series analysis. The biomedical model was not supported as pain impairment did not predict activity, so the integrated model was supported partially. Impairment predicted intention to move around, while perceived behavioural control (PBC) and intention predicted activity. PBC did not predict activity limitation in the expected direction. The integrated model of disability was partially supported within individuals, especially the behavioural elements. However, results suggest that different elements of the model may drive activity (limitations) for different individuals. The integrated model provides a useful framework for understanding disability and suggests interventions, and the utility of N-of-1 methodology for testing theory is illustrated.
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Individual Differences in Achievement Goals among Young Children.
ERIC Educational Resources Information Center
Smiley, Patricia A.; Dweck, Carol S.
1994-01-01
Tested on preschoolers a goal-confidence model for older children that predicts achievement behavior during failure. Found that individual differences in achievement goals emerge very early. Children appeared to have developed a mechanism for selecting learning opportunities prior to formal school experience. (AA)
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Women’s Sexuality: Behaviors, Responses, and Individual Differences
Andersen, Barbara L.; Cyranowski, Jill M.
2009-01-01
Classic and contemporary approaches to the assessment of female sexuality are discussed. General approaches, assessment strategies, and models of female sexuality are organized within the conceptual domains of sexual behaviors, sexual responses (desire, excitement, orgasm, and resolution), and individual differences, including general and sex-specific personality models. Where applicable, important trends and relationships are highlighted in the literature with both existing reports and previously unpublished data. The present conceptual overview highlights areas in sexual assessment and model building that are in need of further research and theoretical clarification. PMID:8543712
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Promiscuity and the evolution of sexual transmitted diseases
NASA Astrophysics Data System (ADS)
Gonçalves, Sebastián; Kuperman, Marcelo; Ferreira da Costa Gomes, Marcelo
2003-09-01
We study the relation between different social behaviors and the onset of epidemics in a model for the dynamics of sexual transmitted diseases. The model considers the society as a system of individual sexuated agents that can be organized in couples and interact with each other. The different social behaviors are incorporated assigning what we call a promiscuity value to each individual agent. The individual promiscuity is taken from a distribution and represents the daily probability of going out to look for a sexual partner, abandoning its eventual mate. In terms of this parameter we find a threshold for the epidemic which is much lower than the classical SIR model prediction, i.e., R0 (basic reproductive number)=1. Different forms for the distribution of the population promiscuity are considered showing that the threshold is weakly sensitive to them. We study the homosexual and the heterosexual case as well.
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Bayesian analysis of Jolly-Seber type models
Matechou, Eleni; Nicholls, Geoff K.; Morgan, Byron J. T.; Collazo, Jaime A.; Lyons, James E.
2016-01-01
We propose the use of finite mixtures of continuous distributions in modelling the process by which new individuals, that arrive in groups, become part of a wildlife population. We demonstrate this approach using a data set of migrating semipalmated sandpipers (Calidris pussila) for which we extend existing stopover models to allow for individuals to have different behaviour in terms of their stopover duration at the site. We demonstrate the use of reversible jump MCMC methods to derive posterior distributions for the model parameters and the models, simultaneously. The algorithm moves between models with different numbers of arrival groups as well as between models with different numbers of behavioural groups. The approach is shown to provide new ecological insights about the stopover behaviour of semipalmated sandpipers but is generally applicable to any population in which animals arrive in groups and potentially exhibit heterogeneity in terms of one or more other processes.
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Geiser, Christian; Griffin, Daniel; Shiffman, Saul
2016-01-01
Sometimes, researchers are interested in whether an intervention, experimental manipulation, or other treatment causes changes in intra-individual state variability. The authors show how multigroup-multiphase latent state-trait (MG-MP-LST) models can be used to examine treatment effects with regard to both mean differences and differences in state variability. The approach is illustrated based on a randomized controlled trial in which N = 338 smokers were randomly assigned to nicotine replacement therapy (NRT) vs. placebo prior to quitting smoking. We found that post quitting, smokers in both the NRT and placebo group had significantly reduced intra-individual affect state variability with respect to the affect items calm and content relative to the pre-quitting phase. This reduction in state variability did not differ between the NRT and placebo groups, indicating that quitting smoking may lead to a stabilization of individuals' affect states regardless of whether or not individuals receive NRT.
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Geiser, Christian; Griffin, Daniel; Shiffman, Saul
2016-01-01
Sometimes, researchers are interested in whether an intervention, experimental manipulation, or other treatment causes changes in intra-individual state variability. The authors show how multigroup-multiphase latent state-trait (MG-MP-LST) models can be used to examine treatment effects with regard to both mean differences and differences in state variability. The approach is illustrated based on a randomized controlled trial in which N = 338 smokers were randomly assigned to nicotine replacement therapy (NRT) vs. placebo prior to quitting smoking. We found that post quitting, smokers in both the NRT and placebo group had significantly reduced intra-individual affect state variability with respect to the affect items calm and content relative to the pre-quitting phase. This reduction in state variability did not differ between the NRT and placebo groups, indicating that quitting smoking may lead to a stabilization of individuals' affect states regardless of whether or not individuals receive NRT. PMID:27499744
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Evolution of trust and trustworthiness: social awareness favours personality differences
McNamara, John M.; Stephens, Philip A.; Dall, Sasha R.X.; Houston, Alasdair I.
2008-01-01
Interest in the evolution and maintenance of personality is burgeoning. Individuals of diverse animal species differ in their aggressiveness, fearfulness, sociability and activity. Strong trade-offs, mutation–selection balance, spatio-temporal fluctuations in selection, frequency dependence and good-genes mate choice are invoked to explain heritable personality variation, yet for continuous behavioural traits, it remains unclear which selective force is likely to maintain distinct polymorphisms. Using a model of trust and cooperation, we show how allowing individuals to monitor each other's cooperative tendencies, at a cost, can select for heritable polymorphisms in trustworthiness. This variation, in turn, favours costly ‘social awareness’ in some individuals. Feedback of this sort can explain the individual differences in trust and trustworthiness so often documented by economists in experimental public goods games across a range of cultures. Our work adds to growing evidence that evolutionary game theorists can no longer afford to ignore the importance of real world inter-individual variation in their models. PMID:18957369
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Wang, Yunsheng; Weinacker, Holger; Koch, Barbara
2008-01-01
A procedure for both vertical canopy structure analysis and 3D single tree modelling based on Lidar point cloud is presented in this paper. The whole area of research is segmented into small study cells by a raster net. For each cell, a normalized point cloud whose point heights represent the absolute heights of the ground objects is generated from the original Lidar raw point cloud. The main tree canopy layers and the height ranges of the layers are detected according to a statistical analysis of the height distribution probability of the normalized raw points. For the 3D modelling of individual trees, individual trees are detected and delineated not only from the top canopy layer but also from the sub canopy layer. The normalized points are resampled into a local voxel space. A series of horizontal 2D projection images at the different height levels are then generated respect to the voxel space. Tree crown regions are detected from the projection images. Individual trees are then extracted by means of a pre-order forest traversal process through all the tree crown regions at the different height levels. Finally, 3D tree crown models of the extracted individual trees are reconstructed. With further analyses on the 3D models of individual tree crowns, important parameters such as crown height range, crown volume and crown contours at the different height levels can be derived. PMID:27879916
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Van Dongen, Hans P A; Caldwell, John A; Caldwell, J Lynn
2006-05-01
Laboratory research has revealed considerable systematic variability in the degree to which individuals' alertness and performance are affected by sleep deprivation. However, little is known about whether or not different populations exhibit similar levels of individual variability. In the present study, we examined individual variability in performance impairment due to sleep loss in a highly select population of militaryjet pilots. Ten active-duty F-117 pilots were deprived of sleep for 38 h and studied repeatedly in a high-fidelity flight simulator. Data were analyzed with a mixed-model ANOVA to quantify individual variability. Statistically significant, systematic individual differences in the effects of sleep deprivation were observed, even when baseline differences were accounted for. The findings suggest that highly select populations may exhibit individual differences in vulnerability to performance impairment from sleep loss just as the general population does. Thus, the scientific and operational communities' reliance on group data as opposed to individual data may entail substantial misestimation of the impact of job-related stressors on safety and performance.
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Effect of NGA West-2 Predictive Ground Motion Equations on Loss
NASA Astrophysics Data System (ADS)
Jemberie, A. L.
2014-12-01
Individual Predictive Ground Motion Equations (PGMEs) of the NGA West-2 project have been analyzed for possible differences in loss for certain locations in California. Differences between the individual hazard curves are pronounced in the loss results. The differences are more than a factor of 2 for longer return periods between the Gross losses from the individual PGMEs. Similar differences are also found between the Average Annual Losses from the individual PGMEs. This indicates the difficulty in choosing any one of the PGMEs except using the weighted average of them. Comparisons between losses from the 2008 and 2014 models are also reported.
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White, Corey N.; Congdon, Eliza; Mumford, Jeanette A.; Karlsgodt, Katherine H.; Sabb, Fred W.; Freimer, Nelson B.; London, Edythe D.; Cannon, Tyrone D.; Bilder, Robert M.; Poldrack, Russell A.
2014-01-01
The Stop-signal task (SST), in which participants must inhibit prepotent responses, has been used to identify neural systems that vary with individual differences in inhibitory control. To explore how these differences relate to other aspects of decision-making, a drift diffusion model of simple decisions was fitted to SST data from Go trials to extract measures of caution, motor execution time, and stimulus processing speed for each of 123 participants. These values were used to probe fMRI data to explore individual differences in neural activation. Faster processing of the Go stimulus correlated with greater activation in the right frontal pole for both Go and Stop trials. On Stop trials stimulus processing speed also correlated with regions implicated in inhibitory control, including the right inferior frontal gyrus, medial frontal gyrus, and basal ganglia. Individual differences in motor execution time correlated with activation of the right parietal cortex. These findings suggest a robust relationship between the speed of stimulus processing and inhibitory processing at the neural level. This model-based approach provides novel insight into the interrelationships among decision components involved in inhibitory control, and raises interesting questions about strategic adjustments in performance and inhibitory deficits associated with psychopathology. PMID:24405185
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Kwok, Oi-Man; Underhill, Andrea T.; Berry, Jack W.; Luo, Wen; Elliott, Timothy R.; Yoon, Myeongsun
2008-01-01
The use and quality of longitudinal research designs has increased over the past two decades, and new approaches for analyzing longitudinal data, including multi-level modeling (MLM) and latent growth modeling (LGM), have been developed. The purpose of this paper is to demonstrate the use of MLM and its advantages in analyzing longitudinal data. Data from a sample of individuals with intra-articular fractures of the lower extremity from the University of Alabama at Birmingham’s Injury Control Research Center is analyzed using both SAS PROC MIXED and SPSS MIXED. We start our presentation with a discussion of data preparation for MLM analyses. We then provide example analyses of different growth models, including a simple linear growth model and a model with a time-invariant covariate, with interpretation for all the parameters in the models. More complicated growth models with different between- and within-individual covariance structures and nonlinear models are discussed. Finally, information related to MLM analysis such as online resources is provided at the end of the paper. PMID:19649151
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Emotion perception and empathy: An individual differences test of relations.
Olderbak, Sally; Wilhelm, Oliver
2017-10-01
Numerous theories posit a positive relation between perceiving emotion expressed in the face of a stranger (emotion perception) and feeling or cognitively understanding the emotion of that person (affective and cognitive empathy, respectively). However, when relating individual differences in emotion perception with individual differences in affective or cognitive empathy, effect sizes are contradictory, but often not significantly different from zero. Based on 4 studies (study ns range from 97 to 486 persons; n total = 958) that differ from one another on many design and sample characteristics, applying advanced modeling techniques to control for measurement error, we estimate relations between affective empathy, cognitive empathy, and emotion perception. Relations are tested separately for each of the 6 basic emotions (an emotion-specific model) as well as across all emotions (an emotion-general model). Reflecting the literature, effect sizes and statistical significance with an emotion-general model vary across the individual studies (rs range from -.001 to .24 for emotion perception with affective empathy and -.01 to .39 for emotion perception with cognitive empathy), with a meta-analysis of these results indicating emotion perception is weakly related with affective (r = .13, p = .003) and cognitive empathy (r = .13, p = .05). Relations are not strengthened in an emotion-specific model. We argue that the weak effect sizes and inconsistency across studies reflects a neglected distinction of measurement approach-specifically, empathy is assessed as typical behavior and emotion perception is assessed as maximal effort-and conclude with considerations regarding the measurement of each construct. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Christopher, Micaela E.; Hulslander, Jacqueline; Byrne, Brian; Samuelsson, Stefan; Keenan, Janice M.; Pennington, Bruce; DeFries, John C.; Wadsworth, Sally J.; Willcutt, Erik; Olson, Richard K.
2012-01-01
We explored the etiology of individual differences in reading development from post-kindergarten to post-4th grade by analyzing data from 487 twin pairs tested in Colorado. Data from three reading measures and one spelling measure were fit to biometric latent growth curve models, allowing us to extend previous behavioral genetic studies of the etiology of early reading development at specific time points. We found primarily genetic influences on individual differences at post-1st grade for all measures. Genetic influences on variance in growth rates were also found, with evidence of small, nonsignificant, shared environmental influences for two measures. We discuss our results, including their implications for educational policy. PMID:24489459
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Vincenzi, Simone; Mangel, Marc; Crivelli, Alain J; Munch, Stephan; Skaug, Hans J
2014-09-01
The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation in growth. We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth using a von Bertalanffy growth model with random effects. To illustrate the power and generality of the method, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually tagged fish have been sampled for more than 15 years. We use year-of-birth cohort, population density during the first year of life, and individual random effects as potential predictors of the von Bertalanffy growth function's parameters k (rate of growth) and L∞ (asymptotic size). Our results showed that size ranks were largely maintained throughout marble trout lifetime in both populations. According to the Akaike Information Criterion (AIC), the best models showed different growth patterns for year-of-birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. For both populations, models including density during the first year of life showed that growth tended to decrease with increasing population density early in life. Model validation showed that predictions of individual growth trajectories using the random-effects model were more accurate than predictions based on mean size-at-age of fish.
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A capability model of individual differences in frontal EEG asymmetry.
Coan, James A; Allen, John J B; McKnight, Patrick E
2006-05-01
Researchers interested in measuring individual differences in affective style via asymmetries in frontal brain activity have depended almost exclusively upon the resting state for EEG recording. This reflects an implicit conceptualization of affective style as a response predisposition that is manifest in frontal EEG asymmetry, with the goal to describe individuals in terms of their general approach or withdrawal tendencies. Alternatively, the response capability conceptualization seeks to identify individual capabilities for approach versus withdrawal responses during emotionally salient events. The capability approach confers a variety of advantages to the study of affective style and personality, and suggests new possibilities for the approach/withdrawal motivational model of frontal EEG asymmetry and emotion. Logical as well as empirical arguments supportive of this conclusion are presented.
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Comparing estimates of genetic variance across different relationship models.
Legarra, Andres
2016-02-01
Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.
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Sumer, H C; Knight, P A
2001-08-01
This study explored whether different models of work-family relationship were possible for individuals with different attachment styles. A mail survey was conducted using employees (N = 481) at a midwestern university in the United States. Results suggested that (a) individuals with a preoccupied attachment pattern were more likely to experience negative spillover from the family/home to the work domain than those with a secure or dismissing style, (b) securely attached individuals experienced positive spillover in both work and family domains more than those in the other groups, and (c) preoccupied individuals were much less likely to use a segmentation strategy than the other 3 attachment groups. However, when the conventional job satisfaction life satisfaction relationship was examined, the data provided unique support for the spillover model. Implications of the findings for both attachment and work family relationship literatures are discussed.
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Accounting for Individual Differences in Bradley-Terry Models by Means of Recursive Partitioning
ERIC Educational Resources Information Center
Strobl, Carolin; Wickelmaier, Florian; Zeileis, Achim
2011-01-01
The preference scaling of a group of subjects may not be homogeneous, but different groups of subjects with certain characteristics may show different preference scalings, each of which can be derived from paired comparisons by means of the Bradley-Terry model. Usually, either different models are fit in predefined subsets of the sample or the…
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The Separate Spheres Model of Gendered Inequality.
Miller, Andrea L; Borgida, Eugene
2016-01-01
Research on role congruity theory and descriptive and prescriptive stereotypes has established that when men and women violate gender stereotypes by crossing spheres, with women pursuing career success and men contributing to domestic labor, they face backlash and economic penalties. Less is known, however, about the types of individuals who are most likely to engage in these forms of discrimination and the types of situations in which this is most likely to occur. We propose that psychological research will benefit from supplementing existing research approaches with an individual differences model of support for separate spheres for men and women. This model allows psychologists to examine individual differences in support for separate spheres as they interact with situational and contextual forces. The separate spheres ideology (SSI) has existed as a cultural idea for many years but has not been operationalized or modeled in social psychology. The Separate Spheres Model presents the SSI as a new psychological construct characterized by individual differences and a motivated system-justifying function, operationalizes the ideology with a new scale measure, and models the ideology as a predictor of some important gendered outcomes in society. As a first step toward developing the Separate Spheres Model, we develop a new measure of individuals' endorsement of the SSI and demonstrate its reliability, convergent validity, and incremental predictive validity. We provide support for the novel hypotheses that the SSI predicts attitudes regarding workplace flexibility accommodations, income distribution within families between male and female partners, distribution of labor between work and family spheres, and discriminatory workplace behaviors. Finally, we provide experimental support for the hypothesis that the SSI is a motivated, system-justifying ideology.
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Behavioral and neuronal determinants of negative reciprocity in the ultimatum game.
Kaltwasser, Laura; Hildebrandt, Andrea; Wilhelm, Oliver; Sommer, Werner
2016-10-01
The rejection of unfair offers in the ultimatum game (UG) indicates negative reciprocity. The model of strong reciprocity claims that negative reciprocity reflects prosociality because the rejecting individual is sacrificing resources in order to punish unfair behavior. However, a recent study found that the rejection rate of unfair offers is linked to assertiveness (status defense model). To pursue the question what drives negative reciprocity, the present study investigated individual differences in the rejection of unfair offers along with their behavioral and neuronal determinants. We measured fairness preferences and event-related potentials (ERP) in 200 healthy participants playing a computerized version of the UG with pictures of unfair and fair proposers. Structural equation modeling (SEM) on the behavioral data corroborated both the strong reciprocity and the status defense models of human cooperation: Not only more prosocial but also more assertive individuals were more likely to show negative reciprocity by rejecting unfair offers. Experimental ERP results confirmed the feedback negativity (FN) as a neural signature of fairness processing. Multilevel SEM of brain-behavior relationships revealed that negative reciprocity was significantly associated with individual differences in FN amplitudes in response to proposers. Our results confirm stable individual differences in fairness processing at the behavioral and neuronal level. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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Facial Recognition in a Group-Living Cichlid Fish.
Kohda, Masanori; Jordan, Lyndon Alexander; Hotta, Takashi; Kosaka, Naoya; Karino, Kenji; Tanaka, Hirokazu; Taniyama, Masami; Takeyama, Tomohiro
2015-01-01
The theoretical underpinnings of the mechanisms of sociality, e.g. territoriality, hierarchy, and reciprocity, are based on assumptions of individual recognition. While behavioural evidence suggests individual recognition is widespread, the cues that animals use to recognise individuals are established in only a handful of systems. Here, we use digital models to demonstrate that facial features are the visual cue used for individual recognition in the social fish Neolamprologus pulcher. Focal fish were exposed to digital images showing four different combinations of familiar and unfamiliar face and body colorations. Focal fish attended to digital models with unfamiliar faces longer and from a further distance to the model than to models with familiar faces. These results strongly suggest that fish can distinguish individuals accurately using facial colour patterns. Our observations also suggest that fish are able to rapidly (≤ 0.5 sec) discriminate between familiar and unfamiliar individuals, a speed of recognition comparable to primates including humans.
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Analysing the Costs of Integrated Care: A Case on Model Selection for Chronic Care Purposes
Sánchez-Pérez, Inma; Ibern, Pere; Coderch, Jordi; Inoriza, José María
2016-01-01
Background: The objective of this study is to investigate whether the algorithm proposed by Manning and Mullahy, a consolidated health economics procedure, can also be used to estimate individual costs for different groups of healthcare services in the context of integrated care. Methods: A cross-sectional study focused on the population of the Baix Empordà (Catalonia-Spain) for the year 2012 (N = 92,498 individuals). A set of individual cost models as a function of sex, age and morbidity burden were adjusted and individual healthcare costs were calculated using a retrospective full-costing system. The individual morbidity burden was inferred using the Clinical Risk Groups (CRG) patient classification system. Results: Depending on the characteristics of the data, and according to the algorithm criteria, the choice of model was a linear model on the log of costs or a generalized linear model with a log link. We checked for goodness of fit, accuracy, linear structure and heteroscedasticity for the models obtained. Conclusion: The proposed algorithm identified a set of suitable cost models for the distinct groups of services integrated care entails. The individual morbidity burden was found to be indispensable when allocating appropriate resources to targeted individuals. PMID:28316542
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Correlates of Individual, and Age-Related, Differences in Short-Term Learning
ERIC Educational Resources Information Center
Zhang, Zhiyong; Davis, Hasker P.; Salthouse, Timothy A.; Tucker-Drob, Elliot M.
2007-01-01
Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individual differences in both initial level of performance and subsequent learning were found in both tasks, age differences were found only in mean initial level, and not in mean learning. In neither task…
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Online Instructors as Thinking Advisors: A Model for Online Learner Adaptation
ERIC Educational Resources Information Center
Benedetti, Christopher
2015-01-01
This article examines the characteristics and challenges of online instruction and presents a model for improving learner adaptation in an online classroom. Instruction in an online classroom presents many challenges, including learner individualization. Individual differences in learning styles and preferences are often not considered in the…
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Individual Differences in a Positional Learning Task across the Adult Lifespan
ERIC Educational Resources Information Center
Rast, Philippe; Zimprich, Daniel
2010-01-01
This study aimed at modeling individual and average non-linear trajectories of positional learning using a structured latent growth curve approach. The model is based on an exponential function which encompasses three parameters: Initial performance, learning rate, and asymptotic performance. These learning parameters were compared in a positional…
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Individualized Prediction of Reading Comprehension Ability Using Gray Matter Volume.
Cui, Zaixu; Su, Mengmeng; Li, Liangjie; Shu, Hua; Gong, Gaolang
2018-05-01
Reading comprehension is a crucial reading skill for learning and putatively contains 2 key components: reading decoding and linguistic comprehension. Current understanding of the neural mechanism underlying these reading comprehension components is lacking, and whether and how neuroanatomical features can be used to predict these 2 skills remain largely unexplored. In the present study, we analyzed a large sample from the Human Connectome Project (HCP) dataset and successfully built multivariate predictive models for these 2 skills using whole-brain gray matter volume features. The results showed that these models effectively captured individual differences in these 2 skills and were able to significantly predict these components of reading comprehension for unseen individuals. The strict cross-validation using the HCP cohort and another independent cohort of children demonstrated the model generalizability. The identified gray matter regions contributing to the skill prediction consisted of a wide range of regions covering the putative reading, cerebellum, and subcortical systems. Interestingly, there were gender differences in the predictive models, with the female-specific model overestimating the males' abilities. Moreover, the identified contributing gray matter regions for the female-specific and male-specific models exhibited considerable differences, supporting a gender-dependent neuroanatomical substrate for reading comprehension.
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Using multilevel models to quantify heterogeneity in resource selection
Wagner, Tyler; Diefenbach, Duane R.; Christensen, Sonja; Norton, Andrew S.
2011-01-01
Models of resource selection are being used increasingly to predict or model the effects of management actions rather than simply quantifying habitat selection. Multilevel, or hierarchical, models are an increasingly popular method to analyze animal resource selection because they impose a relatively weak stochastic constraint to model heterogeneity in habitat use and also account for unequal sample sizes among individuals. However, few studies have used multilevel models to model coefficients as a function of predictors that may influence habitat use at different scales or quantify differences in resource selection among groups. We used an example with white-tailed deer (Odocoileus virginianus) to illustrate how to model resource use as a function of distance to road that varies among deer by road density at the home range scale. We found that deer avoidance of roads decreased as road density increased. Also, we used multilevel models with sika deer (Cervus nippon) and white-tailed deer to examine whether resource selection differed between species. We failed to detect differences in resource use between these two species and showed how information-theoretic and graphical measures can be used to assess how resource use may have differed. Multilevel models can improve our understanding of how resource selection varies among individuals and provides an objective, quantifiable approach to assess differences or changes in resource selection.
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Gabsi, Faten; Schäffer, Andreas; Preuss, Thomas G
2014-07-01
Population responses to chemical stress exposure are influenced by nonchemical, environmental processes such as species interactions. A realistic quantification of chemical toxicity to populations calls for the use of methodologies that integrate these multiple stress effects. The authors used an individual-based model for Daphnia magna as a virtual laboratory to determine the influence of ecological interactions on population sensitivity to chemicals with different modes of action on individuals. In the model, hypothetical chemical toxicity targeted different vital individual-level processes: reproduction, survival, feeding rate, or somatic growth rate. As for species interactions, predatory and competition effects on daphnid populations were implemented following a worst-case approach. The population abundance was simulated at different food levels and exposure scenarios, assuming exposure to chemical stress solely or in combination with either competition or predation. The chemical always targeted one vital endpoint. Equal toxicity-inhibition levels differently affected the population abundance with and without species interactions. In addition, population responses to chemicals were highly sensitive to the environmental stressor (predator or competitor) and to the food level. Results show that population resilience cannot be attributed to chemical stress only. Accounting for the relevant ecological interactions would reduce uncertainties when extrapolating effects of chemicals from individuals to the population level. Validated population models should be used for a more realistic risk assessment of chemicals. © 2014 SETAC.
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Solving the puzzle of collective action through inter-individual differences
von Rueden, Chris; Gavrilets, Sergey; Glowacki, Luke
2015-01-01
Models of collective action infrequently account for differences across individuals beyond a limited set of strategies, ignoring variation in endowment (e.g. physical condition, wealth, knowledge, personality, support), individual costs of effort, or expected gains from cooperation. However, behavioural research indicates these inter-individual differences can have significant effects on the dynamics of collective action. The papers contributed to this theme issue evaluate how individual differences affect the propensity to cooperate, and how they can catalyse others’ likelihood of cooperation (e.g. via leadership). Many of the papers emphasize the relationship between individual decisions and socio-ecological context, particularly the effect of group size. All together, the papers in this theme issue provide a more complete picture of collective action, by embracing the reality of inter-individual variation and its multiple roles in the success or failure of collective action. PMID:26503677
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SUMMA and Model Mimicry: Understanding Differences Among Land Models
NASA Astrophysics Data System (ADS)
Nijssen, B.; Nearing, G. S.; Ou, G.; Clark, M. P.
2016-12-01
Model inter-comparison and model ensemble experiments suffer from an inability to explain the mechanisms behind differences in model outcomes. We can clearly demonstrate that the models are different, but we cannot necessarily identify the reasons why, because most models exhibit myriad differences in process representations, model parameterizations, model parameters and numerical solution methods. This inability to identify the reasons for differences in model performance hampers our understanding and limits model improvement, because we cannot easily identify the most promising paths forward. We have developed the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to allow for controlled experimentation with model construction, numerical techniques, and parameter values and therefore isolate differences in model outcomes to specific choices during the model development process. In developing SUMMA, we recognized that hydrologic models can be thought of as individual instantiations of a master modeling template that is based on a common set of conservation equations for energy and water. Given this perspective, SUMMA provides a unified approach to hydrologic modeling that integrates different modeling methods into a consistent structure with the ability to instantiate alternative hydrologic models at runtime. Here we employ SUMMA to revisit a previous multi-model experiment and demonstrate its use for understanding differences in model performance. Specifically, we implement SUMMA to mimic the spread of behaviors exhibited by the land models that participated in the Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) and draw conclusions about the relative performance of specific model parameterizations for water and energy fluxes through the soil-vegetation continuum. SUMMA's ability to mimic the spread of model ensembles and the behavior of individual models can be an important tool in focusing model development and improvement efforts.
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Attachment change processes in the early years of marriage.
Davila, J; Karney, B R; Bradbury, T N
1999-05-01
The authors examined 4 models of attachment change: a contextual model, a social-cognitive model, an individual-difference model, and a diathesis-stress model. Models were examined in a sample of newlyweds over the first 2 years of marriage, using growth curve analyses. Reciprocal processes, whereby attachment representations and interpersonal life circumstances affect one another over time, also were studied. On average, newlyweds became more secure over time. However, there was significant within-subject variability on attachment change that was predicted by intra- and interpersonal factors. Attachment representations changed in response to contextual, social-cognitive, and individual-difference factors. Reciprocal processes between attachment representations and marital variables emerged, suggesting that these factors influence one another in an ongoing way.
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Insight with hands and things.
Vallée-Tourangeau, Frédéric; Steffensen, Sune Vork; Vallée-Tourangeau, Gaëlle; Sirota, Miroslav
2016-10-01
Two experiments examined whether different task ecologies influenced insight problem solving. The 17 animals problem was employed, a pure insight problem. Its initial formulation encourages the application of a direct arithmetic solution, but its solution requires the spatial arrangement of sets involving some degree of overlap. Participants were randomly allocated to either a tablet condition where they could use a stylus and an electronic tablet to sketch a solution or a model building condition where participants were given material with which to build enclosures and figurines. In both experiments, participants were much more likely to develop a working solution in the model building condition. The difference in performance elicited by different task ecologies was unrelated to individual differences in working memory, actively open-minded thinking, or need for cognition (Experiment 1), although individual differences in creativity were correlated with problem solving success in Experiment 2. The discussion focuses on the implications of these findings for the prevailing metatheoretical commitment to methodological individualism that places the individual as the ontological locus of cognition. Copyright © 2016 Elsevier B.V. All rights reserved.
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Host mating system and the prevalence of a disease in a plant population
Koslow, Jennifer M.; DeAngelis, Donald L.
2006-01-01
A modified susceptible–infected–recovered (SIR) host–pathogen model is used to determine the influence of plant mating system on the outcome of a host–pathogen interaction. Unlike previous models describing how interactions between mating system and pathogen infection affect individual fitness, this model considers the potential consequences of varying mating systems on the prevalence of resistance alleles and disease within the population. If a single allele for disease resistance is sufficient to confer complete resistance in an individual and if both homozygote and heterozygote resistant individuals have the same mean birth and death rates, then, for any parameter set, the selfing rate does not affect the proportions of resistant, susceptible or infected individuals at equilibrium. If homozygote and heterozygote individual birth rates differ, however, the mating system can make a difference in these proportions. In that case, depending on other parameters, increased selfing can either increase or decrease the rate of infection in the population. Results from this model also predict higher frequencies of resistance alleles in predominantly selfing compared to predominantly outcrossing populations for most model conditions. In populations that have higher selfing rates, the resistance alleles are concentrated in homozygotes, whereas in more outcrossing populations, there are more resistant heterozygotes.
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Tack, Ignace L M M; Logist, Filip; Noriega Fernández, Estefanía; Van Impe, Jan F M
2015-02-01
Traditional kinetic models in predictive microbiology reliably predict macroscopic dynamics of planktonically-growing cell cultures in homogeneous liquid food systems. However, most food products have a semi-solid structure, where microorganisms grow locally in colonies. Individual colony cells exhibit strongly different and non-normally distributed behavior due to local nutrient competition. As a result, traditional models considering average population behavior in a homogeneous system do not describe colony dynamics in full detail. To incorporate local resource competition and individual cell differences, an individual-based modeling approach has been applied to Escherichia coli K-12 MG1655 colonies, considering the microbial cell as modeling unit. The first contribution of this individual-based model is to describe single colony growth under nutrient-deprived conditions. More specifically, the linear and stationary phase in the evolution of the colony radius, the evolution from a disk-like to branching morphology, and the emergence of a starvation zone in the colony center are simulated and compared to available experimental data. These phenomena occur earlier at more severe nutrient depletion conditions, i.e., at lower nutrient diffusivity and initial nutrient concentration in the medium. Furthermore, intercolony interactions have been simulated. Higher inoculum densities lead to stronger intercolony interactions, such as colony merging and smaller colony sizes, due to nutrient competition. This individual-based model contributes to the elucidation of characteristic experimentally observed colony behavior from mechanistic information about cellular physiology and interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Leyk, Stefan; Binder, Claudia R; Nuckols, John R
2009-03-30
Pesticide poisoning is a global health issue with the largest impacts in the developing countries where residential and small-scale agricultural areas are often integrated and pesticides sprayed manually. To reduce health risks from pesticide exposure approaches for personalized exposure assessment (PEA) are needed. We present a conceptual framework to develop a spatial individual-based model (IBM) prototype for assessing potential exposure of farm-workers conducting small-scale agricultural production, which accounts for a considerable portion of global food crop production. Our approach accounts for dynamics in the contaminant distributions in the environment, as well as patterns of movement and activities performed on an individual level under different safety scenarios. We demonstrate a first prototype using data from a study area in a rural part of Colombia, South America. Different safety scenarios of PEA were run by including weighting schemes for activities performed under different safety conditions. We examined the sensitivity of individual exposure estimates to varying patterns of pesticide application and varying individual patterns of movement. This resulted in a considerable variation in estimates of magnitude, frequency and duration of exposure over the model runs for each individual as well as between individuals. These findings indicate the influence of patterns of pesticide application, individual spatial patterns of movement as well as safety conditions on personalized exposure in the agricultural production landscape that is the focus of our research. This approach represents a conceptual framework for developing individual based models to carry out PEA in small-scale agricultural settings in the developing world based on individual patterns of movement, safety conditions, and dynamic contaminant distributions. The results of our analysis indicate our prototype model is sufficiently sensitive to differentiate and quantify the influence of individual patterns of movement and decision-based pesticide management activities on potential exposure. This approach represents a framework for further understanding the contribution of agricultural pesticide use to exposure in the small-scale agricultural production landscape of many developing countries, and could be useful to evaluate public health intervention strategies to reduce risks to farm-workers and their families. Further research is needed to fully develop an operational version of the model.
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Interactive vs. Non-Interactive Ensembles for Weather Prediction and Climate Projection
NASA Astrophysics Data System (ADS)
Duane, Gregory
2013-04-01
If the members of an ensemble of different models are allowed to interact with one another in run time, predictive skill can be improved as compared to that of any individual model or any average of indvidual model outputs. Inter-model connections in such an interactive ensemble can be trained, using historical data, so that the resulting ``supermodel" synchronizes with reality when used in weather-prediction mode, where the individual models perform data assimilation from each other (with trainable inter-model "observation error") as well as from real observations. In climate-projection mode, parameters of the individual models are changed, as might occur from an increase in GHG levels, and one obtains relevant statistical properties of the new supermodel attractor. In simple cases, it has been shown that training of the inter-model connections with the old parameter values gives a supermodel that is still predictive when the parameter values are changed. Here we inquire as to the circumstances under which supermodel performance can be expected to exceed that of the customary weighted average of model outputs. We consider a supermodel formed from quasigeostrophic channel models with different forcing coefficients, and introduce an effective training scheme for the inter-model connections. We show that the blocked-zonal index cycle is reproduced better by the supermodel than by any non-interactive ensemble in the extreme case where the forcing coefficients of the different models are very large or very small. With realistic differences in forcing coefficients, as would be representative of actual differences among IPCC-class models, the usual linearity assumption is justified and a weighted average of model outputs is adequate. It is therefore hypothesized that supermodeling is likely to be useful in situations where there are qualitative model differences, as arising from sub-gridscale parameterizations, that affect overall model behavior. Otherwise the usual ex post facto averaging will probably suffice. Previous results from an ENSO-prediction supermodel [Kirtman et al.] are re-examined in light of the hypothesis about the importance of qualitative inter-model differences.
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Strategic sophistication of individuals and teams. Experimental evidence
Sutter, Matthias; Czermak, Simon; Feri, Francesco
2013-01-01
Many important decisions require strategic sophistication. We examine experimentally whether teams act more strategically than individuals. We let individuals and teams make choices in simple games, and also elicit first- and second-order beliefs. We find that teams play the Nash equilibrium strategy significantly more often, and their choices are more often a best response to stated first order beliefs. Distributional preferences make equilibrium play less likely. Using a mixture model, the estimated probability to play strategically is 62% for teams, but only 40% for individuals. A model of noisy introspection reveals that teams differ from individuals in higher order beliefs. PMID:24926100
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Howe, P D; Bryant, S R; Shreeve, T G
2007-10-01
We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.
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Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn
2013-01-01
Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059
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van Ments, Laila; Roelofsma, Peter; Treur, Jan
2018-01-01
Religion is a central aspect of many individuals' lives around the world, and its influence on human behaviour has been extensively studied from many different perspectives. The current study integrates a number of these perspectives into one adaptive temporal-causal network model describing the mental states involved, their mutual relations, and the adaptation of some of these relations over time due to learning. By first developing a conceptual representation of a network model based on the literature, and then formalizing this model into a numerical representation, simulations can be done for almost any kind of religion and person, showing different behaviours for persons with different religious backgrounds and characters. The focus was mainly on the influence of religion on human empathy and dis-empathy, a topic very relevant today. The developed model could be valuable for many uses, involving support for a better understanding, and even prediction, of the behaviour of religious individuals. It is illustrated for a number of different scenarios based on different characteristics of the persons and of the religion.
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Individual Differences in Online Spoken Word Recognition: Implications for SLI
ERIC Educational Resources Information Center
McMurray, Bob; Samelson, Vicki M.; Lee, Sung Hee; Tomblin, J. Bruce
2010-01-01
Thirty years of research has uncovered the broad principles that characterize spoken word processing across listeners. However, there have been few systematic investigations of individual differences. Such an investigation could help refine models of word recognition by indicating which processing parameters are likely to vary, and could also have…
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The Stability of Social Desirability: A Latent Change Analysis.
Haberecht, Katja; Schnuerer, Inga; Gaertner, Beate; John, Ulrich; Freyer-Adam, Jennis
2015-08-01
Social desirability has been shown to be stable in samples with higher school education. However, little is known about the stability of social desirability in more heterogeneous samples differing in school education. This study aimed to investigate the stability of social desirability and which factors predict interindividual differences in intraindividual change. As part of a randomized controlled trial, 1,243 job seekers with unhealthy alcohol use were systematically recruited at three job agencies. A total of 1,094 individuals (87.8%) participated in at least one of two follow-ups (6 and 15 months after baseline) and constitute this study's sample. The Social Desirability Scale-17 was applied. Two latent change models were conducted: Model 1 tested for interindividual differences in intraindividual change of social desirability between both follow-ups; Model 2 included possible predictors (age, sex, education, current employment status) of interindividual differences in intraindividual change. Model 1 revealed a significant decrease of social desirability over time. Model 2 revealed school education to be the only significant predictor of change. These findings indicate that stability of social desirability may depend on school education. It may not be as stable in individuals with higher school education as in individuals with lower education. © 2014 Wiley Periodicals, Inc.
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Waubert de Puiseau, Berenike; Greving, Sven; Aßfalg, André; Musch, Jochen
2017-09-01
Aggregating information across multiple testimonies may improve crime reconstructions. However, different aggregation methods are available, and research on which method is best suited for aggregating multiple observations is lacking. Furthermore, little is known about how variance in the accuracy of individual testimonies impacts the performance of competing aggregation procedures. We investigated the superiority of aggregation-based crime reconstructions involving multiple individual testimonies and whether this superiority varied as a function of the number of witnesses and the degree of heterogeneity in witnesses' ability to accurately report their observations. Moreover, we examined whether heterogeneity in competence levels differentially affected the relative accuracy of two aggregation procedures: a simple majority rule, which ignores individual differences, and the more complex general Condorcet model (Romney et al., Am Anthropol 88(2):313-338, 1986; Batchelder and Romney, Psychometrika 53(1):71-92, 1988), which takes into account differences in competence between individuals. 121 participants viewed a simulated crime and subsequently answered 128 true/false questions about the crime. We experimentally generated groups of witnesses with homogeneous or heterogeneous competences. Both the majority rule and the general Condorcet model provided more accurate reconstructions of the observed crime than individual testimonies. The superiority of aggregated crime reconstructions involving multiple individual testimonies increased with an increasing number of witnesses. Crime reconstructions were most accurate when competences were heterogeneous and aggregation was based on the general Condorcet model. We argue that a formal aggregation should be considered more often when eyewitness testimonies have to be assessed and that the general Condorcet model provides a good framework for such aggregations.
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Individual differences in long-range time representation.
Agostino, Camila S; Caetano, Marcelo S; Balci, Fuat; Claessens, Peter M E; Zana, Yossi
2017-04-01
On the basis of experimental data, long-range time representation has been proposed to follow a highly compressed power function, which has been hypothesized to explain the time inconsistency found in financial discount rate preferences. The aim of this study was to evaluate how well linear and power function models explain empirical data from individual participants tested in different procedural settings. The line paradigm was used in five different procedural variations with 35 adult participants. Data aggregated over the participants showed that fitted linear functions explained more than 98% of the variance in all procedures. A linear regression fit also outperformed a power model fit for the aggregated data. An individual-participant-based analysis showed better fits of a linear model to the data of 14 participants; better fits of a power function with an exponent β > 1 to the data of 12 participants; and better fits of a power function with β < 1 to the data of the remaining nine participants. Of the 35 volunteers, the null hypothesis β = 1 was rejected for 20. The dispersion of the individual β values was approximated well by a normal distribution. These results suggest that, on average, humans perceive long-range time intervals not in a highly compressed, biased manner, but rather in a linear pattern. However, individuals differ considerably in their subjective time scales. This contribution sheds new light on the average and individual psychophysical functions of long-range time representation, and suggests that any attribution of deviation from exponential discount rates in intertemporal choice to the compressed nature of subjective time must entail the characterization of subjective time on an individual-participant basis.
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Chacón-Labella, Julia; de la Cruz, Marcelino; Pescador, David S; Escudero, Adrián
2016-04-01
Evaluating community assembly through the use of functional traits is a promising tool for testing predictions arising from Niche and Coexistence theories. Although interactions among neighboring species and their inter-specific differences are known drivers of coexistence with a strong spatial signal, assessing the role of individual species on the functional structure of the community at different spatial scales remains a challenge. Here, we ask whether individual species exert a measurable effect on the spatial organization of different functional traits in local assemblages. We first propose and compute two functions that describe different aspects of functional trait organization around individual species at multiple scales: individual weighted mean area relationship and individual functional diversity area relationship. Secondly, we develop a conceptual model on the relationship and simultaneous variation of these two metrics, providing five alternative scenarios in response to the ability of some target species to modify its neighbor environment and the possible assembly mechanisms involved. Our results show that some species influence the spatial structure of specific functional traits, but their effects were always restricted to the finest spatial scales. In the basis of our conceptual model, the observed patterns point to two main mechanisms driving the functional structure of the community at the fine scale, "biotic" filtering meditated by individual species and resource partitioning driven by indirect facilitation rather than by competitive mechanisms.
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Adaptive collective foraging in groups with conflicting nutritional needs
Senior, Alistair M.; Lihoreau, Mathieu; Charleston, Michael A.; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J.
2016-01-01
Collective foraging, based on positive feedback and quorum responses, is believed to improve the foraging efficiency of animals. Nutritional models suggest that social information transfer increases the ability of foragers with closely aligned nutritional needs to find nutrients and maintain a balanced diet. However, whether or not collective foraging is adaptive in a heterogeneous group composed of individuals with differing nutritional needs is virtually unexplored. Here we develop an evolutionary agent-based model using concepts of nutritional ecology to address this knowledge gap. Our aim was to evaluate how collective foraging, mediated by social retention on foods, can improve nutrient balancing in individuals with different requirements. The model suggests that in groups where inter-individual nutritional needs are unimodally distributed, high levels of collective foraging yield optimal individual fitness by reducing search times that result from moving between nutritionally imbalanced foods. However, where nutritional needs are highly bimodal (e.g. where the requirements of males and females differ) collective foraging is selected against, leading to group fission. In this case, additional mechanisms such as assortative interactions can coevolve to allow collective foraging by subgroups of individuals with aligned requirements. Our findings indicate that collective foraging is an efficient strategy for nutrient regulation in animals inhabiting complex nutritional environments and exhibiting a range of social forms. PMID:27152206
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Galaiduk, Ronen; Radford, Ben T; Harvey, Euan S
2018-06-21
Many fishes undergo ontogenetic habitat shifts to meet their energy and resource needs as they grow. Habitat resource partitioning and patterns of habitat connectivity between conspecific fishes at different life-history stages is a significant knowledge gap. Species distribution models were used to examine patterns in the relative abundance, individual biomass estimates and environmental niche associations of different life stages of three iconic West Australian fishes. Continuous predictive maps describing the spatial distribution of abundance and individual biomass of the study species were created as well predictive hotspot maps that identify possible areas for aggregation of individuals of similar life stages of multiple species (i.e. spawning grounds, fisheries refugia or nursery areas). The models and maps indicate that processes driving the abundance patterns could be different from the body size associated demographic processes throughout an individual's life cycle. Incorporating life-history in the spatially explicit management plans can ensure that critical habitat of the vulnerable stages (e.g. juvenile fish, spawning stock) is included within proposed protected areas and can enhance connectivity between various functional areas (e.g. nursery areas and adult populations) which, in turn, can improve the abundance of targeted species as well as other fish species relying on healthy ecosystem functioning.
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Modelling personality, plasticity and predictability in shelter dogs
2017-01-01
Behavioural assessments of shelter dogs (Canis lupus familiaris) typically comprise standardized test batteries conducted at one time point, but test batteries have shown inconsistent predictive validity. Longitudinal behavioural assessments offer an alternative. We modelled longitudinal observational data on shelter dog behaviour using the framework of behavioural reaction norms, partitioning variance into personality (i.e. inter-individual differences in behaviour), plasticity (i.e. inter-individual differences in average behaviour) and predictability (i.e. individual differences in residual intra-individual variation). We analysed data on interactions of 3263 dogs (n = 19 281) with unfamiliar people during their first month after arrival at the shelter. Accounting for personality, plasticity (linear and quadratic trends) and predictability improved the predictive accuracy of the analyses compared to models quantifying personality and/or plasticity only. While dogs were, on average, highly sociable with unfamiliar people and sociability increased over days since arrival, group averages were unrepresentative of all dogs and predictions made at the individual level entailed considerable uncertainty. Effects of demographic variables (e.g. age) on personality, plasticity and predictability were observed. Behavioural repeatability was higher one week after arrival compared to arrival day. Our results highlight the value of longitudinal assessments on shelter dogs and identify measures that could improve the predictive validity of behavioural assessments in shelters. PMID:28989764
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Perceived Risk of Burglary and Fear of Crime: Individual- and Country-Level Mixed Modeling.
Chon, Don Soo; Wilson, Mary
2016-02-01
Given the scarcity of prior studies, the current research introduced country-level variables, along with individual-level ones, to test how they are related to an individual's perceived risk of burglary (PRB) and fear of crime (FC), separately, by using mixed-level logistic regression analyses. The analyses of 104,218 individuals, residing in 50 countries, showed that country-level poverty was positively associated with FC only. However, individual-level variables, such as prior property crime victimization and female gender, had consistently positive relationships with both PRB and FC. However, age group and socioeconomic status were inconsistent between those two models, suggesting that PRB and FC are two different concepts. Finally, no significant difference in the pattern of PRB and FC was found between a highly developed group of countries and a less developed one. © The Author(s) 2014.
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Accounting for individual differences in human associative learning
Byrom, Nicola C.
2013-01-01
Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning. PMID:24027551
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Accounting for individual differences in human associative learning.
Byrom, Nicola C
2013-09-04
Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning.
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Interaction times change evolutionary outcomes: Two-player matrix games.
Křivan, Vlastimil; Cressman, Ross
2017-03-07
Two most influential models of evolutionary game theory are the Hawk-Dove and Prisoner's dilemma models. The Hawk-Dove model explains evolution of aggressiveness, predicting individuals should be aggressive when the cost of fighting is lower than its benefit. As the cost of aggressiveness increases and outweighs benefits, aggressiveness in the population should decrease. Similarly, the Prisoner's dilemma models evolution of cooperation. It predicts that individuals should never cooperate despite cooperation leading to a higher collective fitness than defection. The question is then what are the conditions under which cooperation evolves? These classic matrix games, which are based on pair-wise interactions between two opponents with player payoffs given in matrix form, do not consider the effect that conflict duration has on payoffs. However, interactions between different strategies often take different amounts of time. In this article, we develop a new approach to an old idea that opportunity costs lost while engaged in an interaction affect individual fitness. When applied to the Hawk-Dove and Prisoner's dilemma, our theory that incorporates general interaction times leads to qualitatively different predictions. In particular, not all individuals will behave as Hawks when fighting cost is lower than benefit, and cooperation will evolve in the Prisoner's dilemma. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Validation of individual and aggregate global flood hazard models for two major floods in Africa.
NASA Astrophysics Data System (ADS)
Trigg, M.; Bernhofen, M.; Whyman, C.
2017-12-01
A recent intercomparison of global flood hazard models undertaken by the Global Flood Partnership shows that there is an urgent requirement to undertake more validation of the models against flood observations. As part of the intercomparison, the aggregated model dataset resulting from the project was provided as open access data. We compare the individual and aggregated flood extent output from the six global models and test these against two major floods in the African Continent within the last decade, namely severe flooding on the Niger River in Nigeria in 2012, and on the Zambezi River in Mozambique in 2007. We test if aggregating different number and combination of models increases model fit to the observations compared with the individual model outputs. We present results that illustrate some of the challenges of comparing imperfect models with imperfect observations and also that of defining the probability of a real event in order to test standard model output probabilities. Finally, we propose a collective set of open access validation flood events, with associated observational data and descriptions that provide a standard set of tests across different climates and hydraulic conditions.
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Spatiotemporal Patterns of Urban Human Mobility
NASA Astrophysics Data System (ADS)
Hasan, Samiul; Schneider, Christian M.; Ukkusuri, Satish V.; González, Marta C.
2013-04-01
The modeling of human mobility is adopting new directions due to the increasing availability of big data sources from human activity. These sources enclose digital information about daily visited locations of a large number of individuals. Examples of these data include: mobile phone calls, credit card transactions, bank notes dispersal, check-ins in internet applications, among several others. In this study, we consider the data obtained from smart subway fare card transactions to characterize and model urban mobility patterns. We present a simple mobility model for predicting peoples' visited locations using the popularity of places in the city as an interaction parameter between different individuals. This ingredient is sufficient to reproduce several characteristics of the observed travel behavior such as: the number of trips between different locations in the city, the exploration of new places and the frequency of individual visits of a particular location. Moreover, we indicate the limitations of the proposed model and discuss open questions in the current state of the art statistical models of human mobility.
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The dimensionality of between-person differences in white matter microstructure in old age.
Lövdén, Martin; Laukka, Erika Jonsson; Rieckmann, Anna; Kalpouzos, Grégoria; Li, Tie-Qiang; Jonsson, Tomas; Wahlund, Lars-Olof; Fratiglioni, Laura; Bäckman, Lars
2013-06-01
Between-person differences in white matter microstructure may partly generalize across the brain and partly play out differently for distinct tracts. We used diffusion-tensor imaging and structural equation modeling to investigate this issue in a sample of 260 adults aged 60-87 years. Mean fractional anisotropy and mean diffusivity of seven white matter tracts in each hemisphere were quantified. Results showed good fit of a model positing that individual differences in white matter microstructure are structured according to tracts. A general factor, although accounting for variance in the measures, did not adequately represent the individual differences. This indicates the presence of a substantial amount of tract-specific individual differences in white matter microstructure. In addition, individual differences are to a varying degree shared between tracts, indicating that general factors also affect white matter microstructure. Age-related differences in white matter microstructure were present for all tracts. Correlations among tract factors did not generally increase as a function of age, suggesting that aging is not a process with homogenous effects on white matter microstructure across the brain. These findings highlight the need for future research to examine whether relations between white matter microstructure and diverse outcomes are specific or general. Copyright © 2011 Wiley Periodicals, Inc.
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Human Exposure Assessment for Air Pollution.
Han, Bin; Hu, Li-Wen; Bai, Zhipeng
2017-01-01
Assessment of human exposure to air pollution is a fundamental part of the more general process of health risk assessment. The measurement methods for exposure assessment now include personal exposure monitoring, indoor-outdoor sampling, mobile monitoring, and exposure assessment modeling (such as proximity models, interpolation model, air dispersion models, and land-use regression (LUR) models). Among these methods, personal exposure measurement is considered to be the most accurate method of pollutant exposure assessment until now, since it can better quantify observed differences and better reflect exposure among smaller groups of people at ground level. And since the great differences of geographical environment, source distribution, pollution characteristics, economic conditions, and living habits, there is a wide range of differences between indoor, outdoor, and individual air pollution exposure in different regions of China. In general, the indoor particles in most Chinese families comprise infiltrated outdoor particles, particles generated indoors, and a few secondary organic aerosol particles, and in most cases, outdoor particle pollution concentrations are a major contributor to indoor concentrations in China. Furthermore, since the time, energy, and expense are limited, it is difficult to measure the concentration of pollutants for each individual. In recent years, obtaining the concentration of air pollutants by using a variety of exposure assessment models is becoming a main method which could solve the problem of the increasing number of individuals in epidemiology studies.
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Hood, Donald C; Anderson, Susan C; Wall, Michael; Raza, Ali S; Kardon, Randy H
2009-09-01
Retinal nerve fiber (RNFL) thickness and visual field loss data from patients with glaucoma were analyzed in the context of a model, to better understand individual variation in structure versus function. Optical coherence tomography (OCT) RNFL thickness and standard automated perimetry (SAP) visual field loss were measured in the arcuate regions of one eye of 140 patients with glaucoma and 82 normal control subjects. An estimate of within-individual (measurement) error was obtained by repeat measures made on different days within a short period in 34 patients and 22 control subjects. A linear model, previously shown to describe the general characteristics of the structure-function data, was extended to predict the variability in the data. For normal control subjects, between-individual error (individual differences) accounted for 87% and 71% of the total variance in OCT and SAP measures, respectively. SAP within-individual error increased and then decreased with increased SAP loss, whereas OCT error remained constant. The linear model with variability (LMV) described much of the variability in the data. However, 12.5% of the patients' points fell outside the 95% boundary. An examination of these points revealed factors that can contribute to the overall variability in the data. These factors include epiretinal membranes, edema, individual variation in field-to-disc mapping, and the location of blood vessels and degree to which they are included by the RNFL algorithm. The model and the partitioning of within- versus between-individual variability helped elucidate the factors contributing to the considerable variability in the structure-versus-function data.
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Vincenzi, Simone; Mangel, Marc; Crivelli, Alain J.; Munch, Stephan; Skaug, Hans J.
2014-01-01
The differences in demographic and life-history processes between organisms living in the same population have important consequences for ecological and evolutionary dynamics. Modern statistical and computational methods allow the investigation of individual and shared (among homogeneous groups) determinants of the observed variation in growth. We use an Empirical Bayes approach to estimate individual and shared variation in somatic growth using a von Bertalanffy growth model with random effects. To illustrate the power and generality of the method, we consider two populations of marble trout Salmo marmoratus living in Slovenian streams, where individually tagged fish have been sampled for more than 15 years. We use year-of-birth cohort, population density during the first year of life, and individual random effects as potential predictors of the von Bertalanffy growth function's parameters k (rate of growth) and (asymptotic size). Our results showed that size ranks were largely maintained throughout marble trout lifetime in both populations. According to the Akaike Information Criterion (AIC), the best models showed different growth patterns for year-of-birth cohorts as well as the existence of substantial individual variation in growth trajectories after accounting for the cohort effect. For both populations, models including density during the first year of life showed that growth tended to decrease with increasing population density early in life. Model validation showed that predictions of individual growth trajectories using the random-effects model were more accurate than predictions based on mean size-at-age of fish. PMID:25211603
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mizer: an R package for multispecies, trait-based and community size spectrum ecological modelling.
Scott, Finlay; Blanchard, Julia L; Andersen, Ken H
2014-10-01
Size spectrum ecological models are representations of a community of individuals which grow and change trophic level. A key emergent feature of these models is the size spectrum; the total abundance of all individuals that scales negatively with size. The models we focus on are designed to capture fish community dynamics useful for assessing the community impacts of fishing.We present mizer , an R package for implementing dynamic size spectrum ecological models of an entire aquatic community subject to fishing. Multiple fishing gears can be defined and fishing mortality can change through time making it possible to simulate a range of exploitation strategies and management options. mizer implements three versions of the size spectrum modelling framework: the community model, where individuals are only characterized by their size; the trait-based model, where individuals are further characterized by their asymptotic size; and the multispecies model where additional trait differences are resolved.A range of plot, community indicator and summary methods are available to inspect the results of the simulations.
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The High Five: Associations of the Five Positive Factors with the Big Five and Well-being.
Cosentino, Alejandro C; Castro Solano, Alejandro
2017-01-01
The study of individual differences in positive characteristics has mainly focused on moral traits. The objectives of this research were to study individual differences in positive characteristics from the point of view of the layperson, including non-moral individual characteristics, and to generate a replicable model of positive factors. Three studies based on a lexical approach were conducted. The first study generated a corpus of words which resulted in a refined list of socially shared positive characteristics. The second study produced a five-factor model of positive characteristics: erudition, peace, cheerfulness, honesty, and tenacity. The third study confirmed the model with a different sample. The five-positive-factor model not only showed positive associations with emotional, psychological and social well-being, but it also accounted for the variance beyond that accounted for by the Big Five factors in predicting these well-being dimensions. In addition, the presence of convergent and divergent validity of the five positive factors is shown with relation to the Values-in-Action (VIA) classification of character strengths proposed by Peterson and Seligman (2004).
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The High Five: Associations of the Five Positive Factors with the Big Five and Well-being
Cosentino, Alejandro C.; Castro Solano, Alejandro
2017-01-01
The study of individual differences in positive characteristics has mainly focused on moral traits. The objectives of this research were to study individual differences in positive characteristics from the point of view of the layperson, including non-moral individual characteristics, and to generate a replicable model of positive factors. Three studies based on a lexical approach were conducted. The first study generated a corpus of words which resulted in a refined list of socially shared positive characteristics. The second study produced a five-factor model of positive characteristics: erudition, peace, cheerfulness, honesty, and tenacity. The third study confirmed the model with a different sample. The five-positive-factor model not only showed positive associations with emotional, psychological and social well-being, but it also accounted for the variance beyond that accounted for by the Big Five factors in predicting these well-being dimensions. In addition, the presence of convergent and divergent validity of the five positive factors is shown with relation to the Values-in-Action (VIA) classification of character strengths proposed by Peterson and Seligman (2004). PMID:28790947
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A Privacy Preservation Model for Health-Related Social Networking Sites.
Li, Jingquan
2015-07-08
The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS.
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A Privacy Preservation Model for Health-Related Social Networking Sites
2015-01-01
The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS. PMID:26155953
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A Modular Mind? A Test Using Individual Data from Seven Primate Species
Amici, Federica; Barney, Bradley; Johnson, Valen E.; Call, Josep; Aureli, Filippo
2012-01-01
It has long been debated whether the mind consists of specialized and independently evolving modules, or whether and to what extent a general factor accounts for the variance in performance across different cognitive domains. In this study, we used a hierarchical Bayesian model to re-analyse individual level data collected on seven primate species (chimpanzees, bonobos, orangutans, gorillas, spider monkeys, brown capuchin monkeys and long-tailed macaques) across 17 tasks within four domains (inhibition, memory, transposition and support). Our modelling approach evidenced the existence of both a domain-specific factor and a species factor, each accounting for the same amount (17%) of the observed variance. In contrast, inter-individual differences played a minimal role. These results support the hypothesis that the mind of primates is (at least partially) modular, with domain-specific cognitive skills undergoing different evolutionary pressures in different species in response to specific ecological and social demands. PMID:23284816
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Engelhardt, Paul E; Nigg, Joel T; Ferreira, Fernanda
2013-10-01
There has been little research on the fluency of language production and individual difference variables, such as intelligence and executive function. In this study, we report data from 106 participants who completed a battery of standardized cognitive tasks and a sentence production task. For the sentence production task, participants were presented with two objects and a verb and their task was to formulate a sentence. Four types of disfluency were examined: filled pauses (e.g. uh, um), unfilled pauses, repetitions, and repairs. Repetitions occur when the speaker suspends articulation and then repeats the previous word/phrase, and repairs occur when the speaker suspends articulation and then starts over with a different word/phrase. Hierarchical structural equation modeling revealed a significant relationship between repair disfluencies and inhibition. Conclusions focus on the role of individual differences in cognitive ability and their role in models and theories of language production. © 2013.
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Engelhardt, Paul E.; Nigg, Joel T.; Ferreira, Fernanda
2013-01-01
There has been little research on the fluency of language production and individual differences variables, such as intelligence and executive function. In this study, we report data from 106 participants who completed a battery of standardized cognitive tasks and a sentence production task. For the sentence production task, participants were presented with two objects and a verb and their task was to formulate a sentence. Four types of disfluency were examined: filled pauses (e.g. uh, um), unfilled pauses, repetitions, and repairs. Repetitions occur when the speaker suspends articulation and then repeats the previous word/phrase, and repairs occur when the speaker suspends articulation and then starts over with a different word/phrase. Hierarchical structural equation modeling revealed a significant relationship between repair disfluencies and inhibition. Conclusions focus on the role of individual differences in cognitive ability and their role in models and theories of language production. PMID:24018099
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Aguado, Jaume; Baez, Sandra; Huepe, David; Lopez, Vladimir; Ortega, Rodrigo; Sigman, Mariano; Mikulan, Ezequiel; Lischinsky, Alicia; Torrente, Fernando; Cetkovich, Marcelo; Torralva, Teresa; Bekinschtein, Tristan; Manes, Facundo
2014-01-01
It is commonly assumed that early emotional signals provide relevant information for social cognition tasks. The goal of this study was to test the association between (a) cortical markers of face emotional processing and (b) social-cognitive measures, and also to build a model which can predict this association (a and b) in healthy volunteers as well as in different groups of psychiatric patients. Thus, we investigated the early cortical processing of emotional stimuli (N170, using a face and word valence task) and their relationship with the social-cognitive profiles (SCPs, indexed by measures of theory of mind, fluid intelligence, speed processing and executive functions). Group comparisons and individual differences were assessed among schizophrenia (SCZ) patients and their relatives, individuals with attention deficit hyperactivity disorder (ADHD), individuals with euthymic bipolar disorder (BD) and healthy participants (educational level, handedness, age and gender matched). Our results provide evidence of emotional N170 impairments in the affected groups (SCZ and relatives, ADHD and BD) as well as subtle group differences. Importantly, cortical processing of emotional stimuli predicted the SCP, as evidenced by a structural equation model analysis. This is the first study to report an association model of brain markers of emotional processing and SCP. PMID:23685775
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Leadership, personality and social feedback
Ang, Tzo Zen; Sweetman, Gemma; Johnstone, Rufus A; Manica, Andrea
2009-01-01
In a recent paper, we showed that leadership arises from individual behavioral differences in pairs of foraging stickleback (Gasterosteus aculeatus). Foraging data from randomly combined pairs of fish were analyzed using Markov Chain models to infer the individual movement rules underlying joint behavior. While both fish responded to partner movement, bolder individuals were the least responsive and showed greater individual initiative. Shy partners were more faithful followers and were also found to bring about greater leadership tendencies in their bold partners. The ability of such followers to inspire bolder fish suggests that leadership may be dependent on individual temperament differences, reinforced by social feedback. PMID:19721883
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An analysis of intergroup rivalry using Ising model and reinforcement learning
NASA Astrophysics Data System (ADS)
Zhao, Feng-Fei; Qin, Zheng; Shao, Zhuo
2014-01-01
Modeling of intergroup rivalry can help us better understand economic competitions, political elections and other similar activities. The result of intergroup rivalry depends on the co-evolution of individual behavior within one group and the impact from the rival group. In this paper, we model the rivalry behavior using Ising model. Different from other simulation studies using Ising model, the evolution rules of each individual in our model are not static, but have the ability to learn from historical experience using reinforcement learning technique, which makes the simulation more close to real human behavior. We studied the phase transition in intergroup rivalry and focused on the impact of the degree of social freedom, the personality of group members and the social experience of individuals. The results of computer simulation show that a society with a low degree of social freedom and highly educated, experienced individuals is more likely to be one-sided in intergroup rivalry.
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NASA Technical Reports Server (NTRS)
Davis, Donald D.; Bryant, Janet L.; Tedrow, Lara; Liu, Ying; Selgrade, Katherine A.; Downey, Heather J.
2005-01-01
This report describes results of a study conducted for NASA-Langley Research Center. This study is part of a program of research conducted for NASA-LARC that has focused on identifying the influence of national culture on the performance of flight crews. We first reviewed the literature devoted to models of teamwork and team performance, crew resource management, error management, and cross-cultural psychology. Davis (1999) reported the results of this review and presented a model that depicted how national culture could influence teamwork and performance in flight crews. The second study in this research program examined accident investigations of foreign airlines in the United States conducted by the National Transportation Safety Board (NTSB). The ability of cross-cultural values to explain national differences in flight outcomes was examined. Cultural values were found to covary in a predicted way with national differences, but the absence of necessary data in the NTSB reports and limitations in the research method that was used prevented a clear understanding of the causal impact of cultural values. Moreover, individual differences such as personality traits were not examined in this study. Davis and Kuang (2001) report results of this second study. The research summarized in the current report extends this previous research by directly assessing cultural and individual differences among students from the United States and China who were trained to fly in a flight simulator using desktop computer workstations. The research design used in this study allowed delineation of the impact of national origin, cultural values, personality traits, cognitive style, shared mental model, and task workload on teamwork, error management and flight outcomes. We briefly review the literature that documents the importance of teamwork and error management and its impact on flight crew performance. We next examine teamwork and crew resource management training designed to improve teamwork. This is followed by discussion of the potential influence of national culture on teamwork and crew resource management. We then examine the influence of other individual and team differences, such as personality traits, cognitive style, shared mental model, and task workload. We provide a heuristic model that depicts the influence of national culture and individual differences on teamwork, error management and flight outcomes. The results demonstrate the usefulness of the model for future research.
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Kelman, Herbert C
2006-01-01
This chapter begins with a summary of a model, developed half a century ago, that distinguishes three qualitatively different processes of social influence: compliance, identification, and internalization. The model, originally geared to and experimentally tested in the context of persuasive communication, was subsequently applied to influence in the context of long-term relationships, including psychotherapy, international exchanges, and the socialization of national/ethnic identity. It has been extended to analysis of the relationship of individuals to social systems. Individuals' rule, role, and value orientations to a system--conceptually linked to compliance, identification, and internalization--predict different reactions to their own violations of societal standards, different patterns of personal involvement in the political system, and differences in attitude toward authorities and readiness to obey. In a further extension of the model, three approaches to peacemaking in international or intergroup conflicts are identified--conflict settlement, conflict resolution, and reconciliation--which, respectively, focus on the accommodation of interests, relationships, and identities, and are conducive to changes at the level of compliance, identification, and internalization.
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Personalized glucose forecasting for type 2 diabetes using data assimilation
Albers, David J.; Gluckman, Bruce; Ginsberg, Henry; Hripcsak, George; Mamykina, Lena
2017-01-01
Type 2 diabetes leads to premature death and reduced quality of life for 8% of Americans. Nutrition management is critical to maintaining glycemic control, yet it is difficult to achieve due to the high individual differences in glycemic response to nutrition. Anticipating glycemic impact of different meals can be challenging not only for individuals with diabetes, but also for expert diabetes educators. Personalized computational models that can accurately forecast an impact of a given meal on an individual’s blood glucose levels can serve as the engine for a new generation of decision support tools for individuals with diabetes. However, to be useful in practice, these computational engines need to generate accurate forecasts based on limited datasets consistent with typical self-monitoring practices of individuals with type 2 diabetes. This paper uses three forecasting machines: (i) data assimilation, a technique borrowed from atmospheric physics and engineering that uses Bayesian modeling to infuse data with human knowledge represented in a mechanistic model, to generate real-time, personalized, adaptable glucose forecasts; (ii) model averaging of data assimilation output; and (iii) dynamical Gaussian process model regression. The proposed data assimilation machine, the primary focus of the paper, uses a modified dual unscented Kalman filter to estimate states and parameters, personalizing the mechanistic models. Model selection is used to make a personalized model selection for the individual and their measurement characteristics. The data assimilation forecasts are empirically evaluated against actual postprandial glucose measurements captured by individuals with type 2 diabetes, and against predictions generated by experienced diabetes educators after reviewing a set of historical nutritional records and glucose measurements for the same individual. The evaluation suggests that the data assimilation forecasts compare well with specific glucose measurements and match or exceed in accuracy expert forecasts. We conclude by examining ways to present predictions as forecast-derived range quantities and evaluate the comparative advantages of these ranges. PMID:28448498
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Schad, Daniel J.; Jünger, Elisabeth; Sebold, Miriam; Garbusow, Maria; Bernhardt, Nadine; Javadi, Amir-Homayoun; Zimmermann, Ulrich S.; Smolka, Michael N.; Heinz, Andreas; Rapp, Michael A.; Huys, Quentin J. M.
2014-01-01
Theories of decision-making and its neural substrates have long assumed the existence of two distinct and competing valuation systems, variously described as goal-directed vs. habitual, or, more recently and based on statistical arguments, as model-free vs. model-based reinforcement-learning. Though both have been shown to control choices, the cognitive abilities associated with these systems are under ongoing investigation. Here we examine the link to cognitive abilities, and find that individual differences in processing speed covary with a shift from model-free to model-based choice control in the presence of above-average working memory function. This suggests shared cognitive and neural processes; provides a bridge between literatures on intelligence and valuation; and may guide the development of process models of different valuation components. Furthermore, it provides a rationale for individual differences in the tendency to deploy valuation systems, which may be important for understanding the manifold neuropsychiatric diseases associated with malfunctions of valuation. PMID:25566131
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Validation of an individualised model of human thermoregulation for predicting responses to cold air
NASA Astrophysics Data System (ADS)
van Marken Lichtenbelt, Wouter D.; Frijns, Arjan J. H.; van Ooijen, Marieke J.; Fiala, Dusan; Kester, Arnold M.; van Steenhoven, Anton A.
2007-01-01
Most computer models of human thermoregulation are population based. Here, we individualised the Fiala model [Fiala et al. (2001) Int J Biometeorol 45:143 159] with respect to anthropometrics, body fat, and metabolic rate. The predictions of the adapted multisegmental thermoregulatory model were compared with measured skin temperatures of individuals. Data from two experiments, in which reclining subjects were suddenly exposed to mild to moderate cold environmental conditions, were used to study the effect on dynamic skin temperature responses. Body fat was measured by the three-compartment method combining underwater weighing and deuterium dilution. Metabolic rate was determined by indirect calorimetry. In experiment 1, the bias (mean difference) between predicted and measured mean skin temperature decreased from 1.8°C to -0.15°C during cold exposure. The standard deviation of the mean difference remained of the same magnitude (from 0.7°C to 0.9°C). In experiment 2 the bias of the skin temperature changed from 2.0±1.09°C using the standard model to 1.3±0.93°C using individual characteristics in the model. The inclusion of individual characteristics thus improved the predictions for an individual and led to a significantly smaller systematic error. However, a large part of the discrepancies in individual response to cold remained unexplained. Possible further improvements to the model accomplished by inclusion of more subject characteristics (i.e. body fat distribution, body shape) and model refinements on the level of (skin) blood perfusion, and control functions, are discussed.
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Cognitive Control and Individual Differences in Economic Ultimatum Decision-Making
De Neys, Wim; Novitskiy, Nikolay; Geeraerts, Leen; Ramautar, Jennifer; Wagemans, Johan
2011-01-01
Much publicity has been given to the fact that people's economic decisions often deviate from the rational predictions of standard economic models. In the classic ultimatum game, for example, most people turn down financial gains by rejecting unequal monetary splits. The present study points to neglected individual differences in this debate. After participants played the ultimatum game we tested for individual differences in cognitive control capacity of the most and least economic responders. The key finding was that people who were higher in cognitive control, as measured by behavioral (Go/No-Go performance) and neural (No-Go N2 amplitude) markers, did tend to behave more in line with the standard models and showed increased acceptance of unequal splits. Hence, the cognitively highest scoring decision-makers were more likely to maximize their monetary payoffs and adhere to the standard economic predictions. Findings question popular claims with respect to the rejection of standard economic models and the irrationality of human economic decision-making. PMID:22096522
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Zurlo, Maria Clelia; Vallone, Federica; Smith, Andrew P.
2018-01-01
The Demand Resources and Individual Effects Model (DRIVE Model) is a transactional model that integrates Demands- Control-Support and Effort-Reward Imbalance models emphasising the role of individual (Coping Strategies; Overcommitment) and job characteristics (Job Demands, Social Support, Decision Latitude, Skill Discretion, Effort, Rewards) in the work-related stress process. The present study aimed to test the DRIVE Model in a sample of 450 Italian nurses and to compare findings with those of a study conducted in a sample of UK nurses. A questionnaire composed of Ways of Coping Checklist-Revised (WCCL-R); Job Content Questionnaire (JCQ); ERI Test; Hospital Anxiety and Depression Scale (HADS) was used. Data supported the application of the DRIVE Model to the Italian context, showing significant associations of the individual characteristics of Problem-focused, Seek Advice and Wishful Thinking coping strategies and the job characteristics of Job Demands, Skill Discretion, Decision Latitude, and Effort with perceived levels of Anxiety and Depression. Effort represented the best predictor for psychological health conditions among Italian nurses, and Social Support significantly moderated the effects of Job Demands on perceived levels of Anxiety. The comparison study showed significant differences in the risk profiles of Italian and UK nurses. Findings were discussed in order to define focused interventions to promote nurses’ wellbeing.
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Risk preferences impose a hidden distortion on measures of choice impulsivity
Konova, Anna B.; Louie, Kenway; Glimcher, Paul W.
2018-01-01
Measuring temporal discounting through the use of intertemporal choice tasks is now the gold standard method for quantifying human choice impulsivity (impatience) in neuroscience, psychology, behavioral economics, public health and computational psychiatry. A recent area of growing interest is individual differences in discounting levels, as these may predispose to (or protect from) mental health disorders, addictive behaviors, and other diseases. At the same time, more and more studies have been dedicated to the quantification of individual attitudes towards risk, which have been measured in many clinical and non-clinical populations using closely related techniques. Economists have pointed to interactions between measurements of time preferences and risk preferences that may distort estimations of the discount rate. However, although becoming standard practice in economics, discount rates and risk preferences are rarely measured simultaneously in the same subjects in other fields, and the magnitude of the imposed distortion is unknown in the assessment of individual differences. Here, we show that standard models of temporal discounting —such as a hyperbolic discounting model widely present in the literature which fails to account for risk attitudes in the estimation of discount rates— result in a large and systematic pattern of bias in estimated discounting parameters. This can lead to the spurious attribution of differences in impulsivity between individuals when in fact differences in risk attitudes account for observed behavioral differences. We advance a model which, when applied to standard choice tasks typically used in psychology and neuroscience, provides both a better fit to the data and successfully de-correlates risk and impulsivity parameters. This results in measures that are more accurate and thus of greater utility to the many fields interested in individual differences in impulsivity. PMID:29373590
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Risk preferences impose a hidden distortion on measures of choice impulsivity.
Lopez-Guzman, Silvia; Konova, Anna B; Louie, Kenway; Glimcher, Paul W
2018-01-01
Measuring temporal discounting through the use of intertemporal choice tasks is now the gold standard method for quantifying human choice impulsivity (impatience) in neuroscience, psychology, behavioral economics, public health and computational psychiatry. A recent area of growing interest is individual differences in discounting levels, as these may predispose to (or protect from) mental health disorders, addictive behaviors, and other diseases. At the same time, more and more studies have been dedicated to the quantification of individual attitudes towards risk, which have been measured in many clinical and non-clinical populations using closely related techniques. Economists have pointed to interactions between measurements of time preferences and risk preferences that may distort estimations of the discount rate. However, although becoming standard practice in economics, discount rates and risk preferences are rarely measured simultaneously in the same subjects in other fields, and the magnitude of the imposed distortion is unknown in the assessment of individual differences. Here, we show that standard models of temporal discounting -such as a hyperbolic discounting model widely present in the literature which fails to account for risk attitudes in the estimation of discount rates- result in a large and systematic pattern of bias in estimated discounting parameters. This can lead to the spurious attribution of differences in impulsivity between individuals when in fact differences in risk attitudes account for observed behavioral differences. We advance a model which, when applied to standard choice tasks typically used in psychology and neuroscience, provides both a better fit to the data and successfully de-correlates risk and impulsivity parameters. This results in measures that are more accurate and thus of greater utility to the many fields interested in individual differences in impulsivity.
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Lange, Julia; Weil, Frederik; Riegler, Christoph; Groeber, Florian; Rebhan, Silke; Kurdyn, Szymon; Alb, Miriam; Kneitz, Hermann; Gelbrich, Götz; Walles, Heike; Mielke, Stephan
2016-10-01
Human artificial skin models are increasingly employed as non-animal test platforms for research and medical purposes. However, the overall histopathological quality of such models may vary significantly. Therefore, the effects of manufacturing protocols and donor sources on the quality of skin models built-up from fibroblasts and keratinocytes derived from juvenile foreskins is studied. Histo-morphological parameters such as epidermal thickness, number of epidermal cell layers, dermal thickness, dermo-epidermal adhesion and absence of cellular nuclei in the corneal layer are obtained and scored accordingly. In total, 144 full-thickness skin models derived from 16 different donors, built-up in triplicates using three different culture conditions were successfully generated. In univariate analysis both media and donor age affected the quality of skin models significantly. Both parameters remained statistically significant in multivariate analyses. Performing general linear model analyses we could show that individual medium-donor-interactions influence the quality. These observations suggest that the optimal choice of media may differ from donor to donor and coincides with findings where significant inter-individual variations of growth rates in keratinocytes and fibroblasts have been described. Thus, the consideration of individual medium-donor-interactions may improve the overall quality of human organ models thereby forming a reproducible test platform for sophisticated clinical research. Copyright © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Curve Appeal: Exploring Individual Differences in Preference for Curved Versus Angular Objects
Cotter, Katherine N.; Bertamini, Marco; Palumbo, Letizia; Vartanian, Oshin
2017-01-01
A preference for smooth curvature, as opposed to angularity, is a well-established finding for lines, two-dimensional shapes, and complex objects, but little is known about individual differences. We used two-dimensional black-and-white shapes—randomly generated irregular polygons, and arrays of circles and hexagons—and measured many individual differences, including artistic expertise, personality, and cognitive style. As expected, people preferred curved over angular stimuli, and people’s degree of curvature preference correlated across the two sets of shapes. Multilevel models showed varying patterns of interaction between shape and individual differences. For the irregular polygons, people higher in artistic expertise or openness to experience showed a greater preference for curvature. This pattern was not evident for the arrays of circles and hexagons. We discuss the results in relation to the nature of the stimuli, and we conclude that individual differences do play a role in moderating the preference for smooth curvature. PMID:28491269
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Design-Comparable Effect Sizes in Multiple Baseline Designs: A General Modeling Framework
ERIC Educational Resources Information Center
Pustejovsky, James E.; Hedges, Larry V.; Shadish, William R.
2014-01-01
In single-case research, the multiple baseline design is a widely used approach for evaluating the effects of interventions on individuals. Multiple baseline designs involve repeated measurement of outcomes over time and the controlled introduction of a treatment at different times for different individuals. This article outlines a general…
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Individual Differences in Visual Word Recognition: Insights from the English Lexicon Project
ERIC Educational Resources Information Center
Yap, Melvin J.; Balota, David A.; Sibley, Daragh E.; Ratcliff, Roger
2012-01-01
Empirical work and models of visual word recognition have traditionally focused on group-level performance. Despite the emphasis on the prototypical reader, there is clear evidence that variation in reading skill modulates word recognition performance. In the present study, we examined differences among individuals who contributed to the English…
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Drichoutis, Andreas C.; Lusk, Jayson L.
2014-01-01
Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample. PMID:25029467
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Drichoutis, Andreas C; Lusk, Jayson L
2014-01-01
Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample.
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The earnings and employment losses before entering the disability system.
Cervini-Pla, Maria; Vall Castelló, Judit
2018-02-17
Although a number of papers in the literature have shown the employment and wage differences between individuals receiving disability benefits and non-disabled individuals, not much is known about the potential employment and wage losses that disabled individuals suffer before being officially accepted into the disability insurance system (DI). Therefore, in this paper we compare individuals that enter into the DI system due to a progressive deterioration in the health status (ordinary illness) to similar non-disabled individuals. Our aim is to identify the differences in employment and wages between these two groups before disabled individuals are officially accepted into the DI system. We combine matching models and difference-in-difference and we find that the wage (employment) growth patterns of both groups of workers become significantly different three (five) years before entering the DI system. More specifically, our estimates suggest that 1 year before entering the system, there is a difference of 79 Euros/month in the wages of the two groups (8.3% of average wage) as well as a 7.8% point difference in employment probabilities.
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Falco, Adriana M.; Bevins, Rick A.
2015-01-01
Not everyone who tries tobacco or other nicotine-containing products becomes a long-term user. Certain traits or factors that are differentially present in these individuals must be able to help health care providers and researchers determine who is more likely to become chronic users of nicotine-containing products. Some of these factors, particularly sensation-seeking/novelty, impulsivity, and anxiety, lend themselves to the creation of animal models of reactivity to nicotine. These models of reactivity to nicotine can improve the translational aspects of preclinical animal research on nicotine-induced behaviors and treatments in order to help reduce negative outcomes in human populations. The goal of this review is to evaluate the current status of animal models of individual differences that serve to predict the later behavioral effects of nicotine. The limited utility and inconsistency of existing novelty models is considered, as well as the promise of impulsivity and anxiety models in preclinical animal populations. Finally, other models that could be employed to extend the benefit of the current research are examined. PMID:26410616
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The Derivation of Sink Functions of Wheat Organs using the GREENLAB Model
Kang, Mengzhen; Evers, Jochem B.; Vos, Jan; de Reffye, Philippe
2008-01-01
Background and Aims In traditional crop growth models assimilate production and partitioning are described with empirical equations. In the GREENLAB functional–structural model, however, allocation of carbon to different kinds of organs depends on the number and relative sink strengths of growing organs present in the crop architecture. The aim of this study is to generate sink functions of wheat (Triticum aestivum) organs by calibrating the GREENLAB model using a dedicated data set, consisting of time series on the mass of individual organs (the ‘target data’). Methods An experiment was conducted on spring wheat (Triticum aestivum, ‘Minaret’), in a growth chamber from, 2004 to, 2005. Four harvests were made of six plants each to determine the size and mass of individual organs, including the root system, leaf blades, sheaths, internodes and ears of the main stem and different tillers. Leaf status (appearance, expansion, maturity and death) of these 24 plants was recorded. With the structures and mass of organs of four individual sample plants, the GREENLAB model was calibrated using a non-linear least-square-root fitting method, the aim of which was to minimize the difference in mass of the organs between measured data and model output, and to provide the parameter values of the model (the sink strengths of organs of each type, age and tiller order, and two empirical parameters linked to biomass production). Key Results and Conclusions The masses of all measured organs from one plant from each harvest were fitted simultaneously. With estimated parameters for sink and source functions, the model predicted the mass and size of individual organs at each position of the wheat structure in a mechanistic way. In addition, there was close agreement between experimentally observed and simulated values of leaf area index. PMID:18045794
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Sensitivity Analysis of Mixed Models for Incomplete Longitudinal Data
ERIC Educational Resources Information Center
Xu, Shu; Blozis, Shelley A.
2011-01-01
Mixed models are used for the analysis of data measured over time to study population-level change and individual differences in change characteristics. Linear and nonlinear functions may be used to describe a longitudinal response, individuals need not be observed at the same time points, and missing data, assumed to be missing at random (MAR),…
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Modeling Fear of Crime in Dallas Neighborhoods: A Test of Social Capital Theory
ERIC Educational Resources Information Center
Ferguson, Kristin M.; Mindel, Charles H.
2007-01-01
This study tested a model of the effects of different predictors on individuals' levels of fear of crime in Dallas neighborhoods. Given its dual focus on individual perceptions and community-level interactions, social capital theory was selected as the most appropriate framework to explore fear of crime within the neighborhood milieu. A structural…
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Collective opinion formation model under Bayesian updating and confirmation bias
NASA Astrophysics Data System (ADS)
Nishi, Ryosuke; Masuda, Naoki
2013-06-01
We propose a collective opinion formation model with a so-called confirmation bias. The confirmation bias is a psychological effect with which, in the context of opinion formation, an individual in favor of an opinion is prone to misperceive new incoming information as supporting the current belief of the individual. Our model modifies a Bayesian decision-making model for single individuals [M. Rabin and J. L. Schrag, Q. J. Econ.0033-553310.1162/003355399555945 114, 37 (1999)] for the case of a well-mixed population of interacting individuals in the absence of the external input. We numerically simulate the model to show that all the agents eventually agree on one of the two opinions only when the confirmation bias is weak. Otherwise, the stochastic population dynamics ends up creating a disagreement configuration (also called polarization), particularly for large system sizes. A strong confirmation bias allows various final disagreement configurations with different fractions of the individuals in favor of the opposite opinions.
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Murray, A; Montgomery, J E; Chang, H; Rogers, W H; Inui, T; Safran, D G
2001-07-01
To examine the differences in physician satisfaction associated with open- versus closed-model practice settings and to evaluate changes in physician satisfaction between 1986 and 1997. Open-model practices refer to those in which physicians accept patients from multiple health plans and insurers (i.e., do not have an exclusive arrangement with any single health plan). Closed-model practices refer to those wherein physicians have an exclusive relationship with a single health plan (i.e., staff- or group-model HMO). Two cross-sectional surveys of physicians; one conducted in 1986 (Medical Outcomes Study) and one conducted in 1997 (Study of Primary Care Performance in Massachusetts). Primary care practices in Massachusetts. General internists and family practitioners in Massachusetts. Seven measures of physician satisfaction, including satisfaction with quality of care, the potential to achieve professional goals, time spent with individual patients, total earnings from practice, degree of personal autonomy, leisure time, and incentives for high quality. Physicians in open- versus closed-model practices differed significantly in several aspects of their professional satisfaction. In 1997, open-model physicians were less satisfied than closed-model physicians with their total earnings, leisure time, and incentives for high quality. Open-model physicians reported significantly more difficulty with authorization procedures and reported more denials for care. Overall, physicians in 1997 were less satisfied in every aspect of their professional life than 1986 physicians. Differences were significant in three areas: time spent with individual patients, autonomy, and leisure time (P < or =.05). Among open-model physicians, satisfaction with autonomy and time with individual patients were significantly lower in 1997 than 1986 (P < or =.01). Among closed-model physicians, satisfaction with total earnings and with potential to achieve professional goals were significantly lower in 1997 than in 1986 (P < or =.01). This study finds that the state of physician satisfaction in Massachusetts is extremely low, with the majority of physicians dissatisfied with the amount of time they have with individual patients, their leisure time, and their incentives for high quality. Satisfaction with most areas of practice declined significantly between 1986 and 1997. Open-model physicians were less satisfied than closed-model physicians in most aspects of practices.
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De Gieter, Sara; Hofmans, Joeri; Pepermans, Roland
2011-12-01
Nurse turnover is an important contributing factor to the worldwide nursing shortage. Many studies have examined the antecedents of nurse turnover to gain a better understanding of the problem and help hospitals reduce their turnover rates. However, an important shortcoming of this research stream is its exclusive focus on explaining turnover behavior of the "average nurse", thereby disregarding individual differences between nurses and groups of nurses. To examine individual differences in the relationships between two crucial turnover antecedents - job satisfaction and organizational commitment - and nurse turnover intention. A sample of 287 nurses working for a variety of Belgian hospitals participated in the study. A survey method was used to collect quantitative data, which were analyzed through standard multiple linear regression, mixture regression models and t-tests. In the total sample of hospital nurses, both job satisfaction and organizational commitment significantly predicted nurse turnover intention. However, subsequent individual differences analyses revealed the existence of two subgroups of nurses. In the satisfaction focused group, only job satisfaction was found to predict nurse turnover intention, whereas in the satisfaction and commitment focused group both job satisfaction and organizational commitment were related to turnover intention. Furthermore, nurses in the latter group displayed stronger turnover intention, were significantly younger and had less job tenure and organizational tenure than nurses in the satisfaction focused group. The debate on the antecedents of nurse turnover still continues, as the existing models fail to fully grasp nurse turnover. The present study identifies individual differences in nurse turnover antecedents among groups of nurses as a possible reason for the absence of one comprehensive turnover model that holds for the general nursing population. Further studies are needed in order to capture the total impact of the underlying individual differences in nurse turnover antecedents. 2011 Elsevier Ltd. All rights reserved.
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Individual differences in perceiving and recognizing faces-One element of social cognition.
Wilhelm, Oliver; Herzmann, Grit; Kunina, Olga; Danthiir, Vanessa; Schacht, Annekathrin; Sommer, Werner
2010-09-01
Recognizing faces swiftly and accurately is of paramount importance to humans as a social species. Individual differences in the ability to perform these tasks may therefore reflect important aspects of social or emotional intelligence. Although functional models of face cognition based on group and single case studies postulate multiple component processes, little is known about the ability structure underlying individual differences in face cognition. In 2 large individual differences experiments (N = 151 and N = 209), a broad variety of face-cognition tasks were tested and the component abilities of face cognition-face perception, face memory, and the speed of face cognition-were identified and then replicated. Experiment 2 also showed that the 3 face-cognition abilities are clearly distinct from immediate and delayed memory, mental speed, general cognitive ability, and object cognition. These results converge with functional and neuroanatomical models of face cognition by demonstrating the difference between face perception and face memory. The results also underline the importance of distinguishing between speed and accuracy of face cognition. Together our results provide a first step toward establishing face-processing abilities as an independent ability reflecting elements of social intelligence. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
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Integration of individual and social information for decision-making in groups of different sizes.
Park, Seongmin A; Goïame, Sidney; O'Connor, David A; Dreher, Jean-Claude
2017-06-01
When making judgments in a group, individuals often revise their initial beliefs about the best judgment to make given what others believe. Despite the ubiquity of this phenomenon, we know little about how the brain updates beliefs when integrating personal judgments (individual information) with those of others (social information). Here, we investigated the neurocomputational mechanisms of how we adapt our judgments to those made by groups of different sizes, in the context of jury decisions for a criminal. By testing different theoretical models, we showed that a social Bayesian inference model captured changes in judgments better than 2 other models. Our results showed that participants updated their beliefs by appropriately weighting individual and social sources of information according to their respective credibility. When investigating 2 fundamental computations of Bayesian inference, belief updates and credibility estimates of social information, we found that the dorsal anterior cingulate cortex (dACC) computed the level of belief updates, while the bilateral frontopolar cortex (FPC) was more engaged in individuals who assigned a greater credibility to the judgments of a larger group. Moreover, increased functional connectivity between these 2 brain regions reflected a greater influence of group size on the relative credibility of social information. These results provide a mechanistic understanding of the computational roles of the FPC-dACC network in steering judgment adaptation to a group's opinion. Taken together, these findings provide a computational account of how the human brain integrates individual and social information for decision-making in groups.
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Diversity-induced resonance in a model for opinion formation
NASA Astrophysics Data System (ADS)
Tessone, C. J.; Toral, R.
2009-10-01
We study an opinion formation model that takes into account that individuals have diverse preferences when adopting an opinion regarding a particular issue. We show that the system exhibits “diversity-induced resonance” [C.J. Tessone et al. Phys. Rev. Lett. 97, 194101 (2006)], by which an external influence (for example advertising, or fashion trends) is better followed by populations having the right degree of diversity in their preferences, rather than others where the individuals are identical or have too different preferences. We support our findings by numerical simulations of the model in different network topologies and a mean-field type analytical theory.
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An IRT Model with a Parameter-Driven Process for Change
ERIC Educational Resources Information Center
Rijmen, Frank; De Boeck, Paul; van der Maas, Han L. J.
2005-01-01
An IRT model with a parameter-driven process for change is proposed. Quantitative differences between persons are taken into account by a continuous latent variable, as in common IRT models. In addition, qualitative inter-individual differences and auto-dependencies are accounted for by assuming within-subject variability with respect to the…
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Lei, Chon Lok; Wang, Ken; Clerx, Michael; Johnstone, Ross H; Hortigon-Vinagre, Maria P; Zamora, Victor; Allan, Andrew; Smith, Godfrey L; Gavaghan, David J; Mirams, Gary R; Polonchuk, Liudmila
2017-01-01
Human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) have applications in disease modeling, cell therapy, drug screening and personalized medicine. Computational models can be used to interpret experimental findings in iPSC-CMs, provide mechanistic insights, and translate these findings to adult cardiomyocyte (CM) electrophysiology. However, different cell lines display different expression of ion channels, pumps and receptors, and show differences in electrophysiology. In this exploratory study, we use a mathematical model based on iPSC-CMs from Cellular Dynamic International (CDI, iCell), and compare its predictions to novel experimental recordings made with the Axiogenesis Cor.4U line. We show that tailoring this model to the specific cell line, even using limited data and a relatively simple approach, leads to improved predictions of baseline behavior and response to drugs. This demonstrates the need and the feasibility to tailor models to individual cell lines, although a more refined approach will be needed to characterize individual currents, address differences in ion current kinetics, and further improve these results.
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Simple models for studying complex spatiotemporal patterns of animal behavior
NASA Astrophysics Data System (ADS)
Tyutyunov, Yuri V.; Titova, Lyudmila I.
2017-06-01
Minimal mathematical models able to explain complex patterns of animal behavior are essential parts of simulation systems describing large-scale spatiotemporal dynamics of trophic communities, particularly those with wide-ranging species, such as occur in pelagic environments. We present results obtained with three different modelling approaches: (i) an individual-based model of animal spatial behavior; (ii) a continuous taxis-diffusion-reaction system of partial-difference equations; (iii) a 'hybrid' approach combining the individual-based algorithm of organism movements with explicit description of decay and diffusion of the movement stimuli. Though the models are based on extremely simple rules, they all allow description of spatial movements of animals in a predator-prey system within a closed habitat, reproducing some typical patterns of the pursuit-evasion behavior observed in natural populations. In all three models, at each spatial position the animal movements are determined by local conditions only, so the pattern of collective behavior emerges due to self-organization. The movement velocities of animals are proportional to the density gradients of specific cues emitted by individuals of the antagonistic species (pheromones, exometabolites or mechanical waves of the media, e.g., sound). These cues play a role of taxis stimuli: prey attract predators, while predators repel prey. Depending on the nature and the properties of the movement stimulus we propose using either a simplified individual-based model, a continuous taxis pursuit-evasion system, or a little more detailed 'hybrid' approach that combines simulation of the individual movements with the continuous model describing diffusion and decay of the stimuli in an explicit way. These can be used to improve movement models for many species, including large marine predators.
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Individual Differences in the Extent and Development of Aggressive Cognitive-Associative Networks.
ERIC Educational Resources Information Center
Bushman, Brad J.
1996-01-01
Extends L. Berkowitz's neoassociationist aggression model by considering the role of personality variables. Experiment one tested the hypothesis that high-trait-aggressive individuals have more developed aggressive cognitive-associative networks than low-trait-aggressive individuals. In experiment two, participants rated the stimulus words used in…
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Numerical evaluation of the skull for human neuromodulation with transcranial focused ultrasound
NASA Astrophysics Data System (ADS)
Mueller, Jerel K.; Ai, Leo; Bansal, Priya; Legon, Wynn
2017-12-01
Objective. Transcranial focused ultrasound is an emerging field for human non-invasive neuromodulation, but its dosing in humans is difficult to know due to the skull. The objective of the present study was to establish modeling methods based on medical images to assess skull differences between individuals on the wave propagation of ultrasound. Approach. Computational models of transcranial focused ultrasound were constructed using CT and MR scans to solve for intracranial pressure. We explored the effect of including the skull base in models, different transducer placements on the head, and differences between 250 kHz or 500 kHz acoustic frequency for both female and male models. We further tested these features using linear, nonlinear, and elastic simulations. To better understand inter-subject skull thickness and composition effects we evaluated the intracranial pressure maps between twelve individuals at two different skull sites. Main results. Nonlinear acoustic simulations resulted in virtually identical intracranial pressure maps with linear acoustic simulations. Elastic simulations showed a difference in max pressures and full width half maximum volumes of 15% at most. Ultrasound at an acoustic frequency of 250 kHz resulted in the creation of more prominent intracranial standing waves compared to 500 kHz. Finally, across twelve model human skulls, a significant linear relationship to characterize intracranial pressure maps was not found. Significance. Despite its appeal, an inherent problem with the use of a noninvasive transcranial ultrasound method is the difficulty of knowing intracranial effects because of the skull. Here we develop detailed computational models derived from medical images of individuals to simulate the propagation of neuromodulatory ultrasound across the skull and solve for intracranial pressure maps. These methods allow for a much better understanding of the intracranial effects of ultrasound for an individual in order to ensure proper targeting and more tightly control dosing.
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Dynamics of Change and Change in Dynamics
Boker, Steven M.; Staples, Angela D.; Hu, Yueqin
2017-01-01
A framework is presented for building and testing models of dynamic regulation by categorizing sources of differences between theories of dynamics. A distinction is made between the dynamics of change, i.e., how a system self–regulates on a short time scale, and change in dynamics, i.e., how those dynamics may themselves change over a longer time scale. In order to clarify the categories, models are first built to estimate individual differences in equilibrium value and equilibrium change. Next, models are presented in which there are individual differences in parameters of dynamics such as frequency of fluctuations, damping of fluctuations, and amplitude of fluctuations. Finally, models for within–person change in dynamics over time are proposed. Simulations demonstrating feasibility of these models are presented and OpenMx scripts for fitting these models have been made available in a downloadable archive along with scripts to simulate data so that a researcher may test a selected models’ feasibility within a chosen experimental design. PMID:29046764
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Jenkins-Smith, H.C.
1994-12-01
This report analyzes data from surveys on the effects that images associated with nuclear power and waste (i.e., nuclear images) have on people`s preference to vacation in Nevada. The analysis was stimulated by a model of imagery and stigma which assumes that information about a potentially hazardous facility generates signals that elicit negative images about the place in which it is located. Individuals give these images negative values (valences) that lessen their desire to vacation, relocate, or retire in that place. The model has been used to argue that the proposed Yucca Mountain high-level nuclear waste repository could elicit imagesmore » of nuclear waste that would stigmatize Nevada and thus impose substantial economic losses there. This report proposes a revised model that assumes that the acquisition and valuation of images depend on individuals` ideological and cultural predispositions and that the ways in which new images will affect their preferences and behavior partly depend on these predispositions. The report tests these hypotheses: (1) individuals with distinct cultural and ideological predispositions have different propensities for acquiring nuclear images, (2) these people attach different valences to these images, (3) the variations in these valences are important, and (4) the valences of the different categories of images within an individual`s image sets for a place correlate very well. The analysis largely confirms these hypotheses, indicating that the stigma model should be revised to (1) consider the relevant ideological and cultural predispositions of the people who will potentially acquire and attach value to the image, (2) specify the kinds of images that previously attracted people to the host state, and (3) consider interactions between the old and potential new images of the place. 37 refs., 18 figs., 17 tabs.« less
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Wood, Julie; Oravecz, Zita; Vogel, Nina; Benson, Lizbeth; Chow, Sy-Miin; Cole, Pamela; Conroy, David E; Pincus, Aaron L; Ram, Nilam
2017-12-15
Life-span theories of aging suggest improvements and decrements in individuals' ability to regulate affect. Dynamic process models, with intensive longitudinal data, provide new opportunities to articulate specific theories about individual differences in intraindividual dynamics. This paper illustrates a method for operationalizing affect dynamics using a multilevel stochastic differential equation (SDE) model, and examines how those dynamics differ with age and trait-level tendencies to deploy emotion regulation strategies (reappraisal and suppression). Univariate multilevel SDE models, estimated in a Bayesian framework, were fit to 21 days of ecological momentary assessments of affect valence and arousal (average 6.93/day, SD = 1.89) obtained from 150 adults (age 18-89 years)-specifically capturing temporal dynamics of individuals' core affect in terms of attractor point, reactivity to biopsychosocial (BPS) inputs, and attractor strength. Older age was associated with higher arousal attractor point and less BPS-related reactivity. Greater use of reappraisal was associated with lower valence attractor point. Intraindividual variability in regulation strategy use was associated with greater BPS-related reactivity and attractor strength, but in different ways for valence and arousal. The results highlight the utility of SDE models for studying affect dynamics and informing theoretical predictions about how intraindividual dynamics change over the life course. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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John, Majnu; Lencz, Todd; Malhotra, Anil K; Correll, Christoph U; Zhang, Jian-Ping
2018-06-01
Meta-analysis of genetic association studies is being increasingly used to assess phenotypic differences between genotype groups. When the underlying genetic model is assumed to be dominant or recessive, assessing the phenotype differences based on summary statistics, reported for individual studies in a meta-analysis, is a valid strategy. However, when the genetic model is additive, a similar strategy based on summary statistics will lead to biased results. This fact about the additive model is one of the things that we establish in this paper, using simulations. The main goal of this paper is to present an alternate strategy for the additive model based on simulating data for the individual studies. We show that the alternate strategy is far superior to the strategy based on summary statistics.
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Mixed conditional logistic regression for habitat selection studies.
Duchesne, Thierry; Fortin, Daniel; Courbin, Nicolas
2010-05-01
1. Resource selection functions (RSFs) are becoming a dominant tool in habitat selection studies. RSF coefficients can be estimated with unconditional (standard) and conditional logistic regressions. While the advantage of mixed-effects models is recognized for standard logistic regression, mixed conditional logistic regression remains largely overlooked in ecological studies. 2. We demonstrate the significance of mixed conditional logistic regression for habitat selection studies. First, we use spatially explicit models to illustrate how mixed-effects RSFs can be useful in the presence of inter-individual heterogeneity in selection and when the assumption of independence from irrelevant alternatives (IIA) is violated. The IIA hypothesis states that the strength of preference for habitat type A over habitat type B does not depend on the other habitat types also available. Secondly, we demonstrate the significance of mixed-effects models to evaluate habitat selection of free-ranging bison Bison bison. 3. When movement rules were homogeneous among individuals and the IIA assumption was respected, fixed-effects RSFs adequately described habitat selection by simulated animals. In situations violating the inter-individual homogeneity and IIA assumptions, however, RSFs were best estimated with mixed-effects regressions, and fixed-effects models could even provide faulty conclusions. 4. Mixed-effects models indicate that bison did not select farmlands, but exhibited strong inter-individual variations in their response to farmlands. Less than half of the bison preferred farmlands over forests. Conversely, the fixed-effect model simply suggested an overall selection for farmlands. 5. Conditional logistic regression is recognized as a powerful approach to evaluate habitat selection when resource availability changes. This regression is increasingly used in ecological studies, but almost exclusively in the context of fixed-effects models. Fitness maximization can imply differences in trade-offs among individuals, which can yield inter-individual differences in selection and lead to departure from IIA. These situations are best modelled with mixed-effects models. Mixed-effects conditional logistic regression should become a valuable tool for ecological research.
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Robison, Matthew K; Gath, Katherine I; Unsworth, Nash
2017-04-01
Cognitive psychology and cognitive neuroscience have recently developed a keen interest in the phenomenon of mind-wandering. People mind-wander frequently, and mind-wandering is associated with decreased cognitive performance. But why do people mind-wander so much? Previous investigations have focused on cognitive abilities like working memory capacity and attention control. But an individual's tendency to worry, feel anxious, and entertain personal concerns also influences mind-wandering. The Control Failure × Concerns model of mind-wandering. Psychological Bulletin, 136, 188-197] argues that individual differences in the propensity to mind-wander are jointly determined by cognitive abilities and by the presence of personally salient concerns that intrude on task focus. In order to test this model, we investigated individual differences in mind-wandering, executive attention, and personality with a focus on neuroticism. The results showed that neurotic individuals tended to report more mind-wandering during cognitive tasks, lower working memory capacity, and poorer attention control. Thus the trait of neuroticism adds an additional source of variance in the tendency to mind-wander, which offers support for the Control Failure × Concerns model. The results help bridge the fields of clinical psychology, cognitive psychology, affective neuroscience, and cognitive neuroscience as a means of developing a more complete understanding of the complex relationship between cognition, personality, and emotion.
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Determinants of conflict detection: a model of risk judgments in air traffic control.
Stankovic, Stéphanie; Raufaste, Eric; Averty, Philippe
2008-02-01
A model of conflict judgments in air traffic control (ATC) is proposed. Three horizontal distances determine risk judgments about conflict between two aircraft: (a) Dt(o) is the distance between the crossing of the aircraft trajectories and the first aircraft to reach that point; (b) Dt(h) is the distance between the two aircraft when they are horizontally closest; and (c) Dt(v) is the horizontal distance between the two aircraft when their growing vertical distance reaches 1000 feet. Two experiments tested whether the variables in the model reflect what controllers do. In Experiment 1, 125 certified controllers provided risk judgments about situations in which the model variables were manipulated. Experiment 2 investigated the relationship between the model and expertise by comparing a population of certified controllers with a population of ATC students. Across both experiments, the model accounted for 44% to 50% of the variance in risk judgments by certified controllers (N=161) but only 20% in judgments by ATC students (N=88). There were major individual differences in the predictive power of the model as well as in the contributions of the three variables. In Experiment 2, the model described experts better than novices. The model provided a satisfying account of the data, albeit with substantial individual differences. It is argued that an individual-differences approach is required when investigating the strategies involved in conflict judgment in ATC. These findings should have implications for developing user-friendly interfaces with conflict detection devices and for devising ATC training programs.
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Nogueira, Waldo; Schurzig, Daniel; Büchner, Andreas; Penninger, Richard T.; Würfel, Waldemar
2016-01-01
Cochlear Implants (CIs) are medical implantable devices that can restore the sense of hearing in people with profound hearing loss. Clinical trials assessing speech intelligibility in CI users have found large intersubject variability. One possibility to explain the variability is the individual differences in the interface created between electrodes of the CI and the auditory nerve. In order to understand the variability, models of the voltage distribution of the electrically stimulated cochlea may be useful. With this purpose in mind, we developed a parametric model that can be adapted to each CI user based on landmarks from individual cone beam computed tomography (CBCT) scans of the cochlea before and after implantation. The conductivity values of each cochlea compartment as well as the weighting factors of different grounding modes have also been parameterized. Simulations were performed modeling the cochlea and electrode positions of 12 CI users. Three models were compared with different levels of detail: a homogeneous model (HM), a non-patient-specific model (NPSM), and a patient-specific model (PSM). The model simulations were compared with voltage distribution measurements obtained from the backward telemetry of the 12 CI users. Results show that the PSM produces the lowest error when predicting individual voltage distributions. Given a patient-specific geometry and electrode positions, we show an example on how to optimize the parameters of the model and how to couple it to an auditory nerve model. The model here presented may help to understand speech performance variability and support the development of new sound coding strategies for CIs. PMID:27933290
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Using eye tracking to test for individual differences in attention to attractive faces
Valuch, Christian; Pflüger, Lena S.; Wallner, Bernard; Laeng, Bruno; Ansorge, Ulrich
2015-01-01
We assessed individual differences in visual attention toward faces in relation to their attractiveness via saccadic reaction times. Motivated by the aim to understand individual differences in attention to faces, we tested three hypotheses: (a) Attractive faces hold or capture attention more effectively than less attractive faces; (b) men show a stronger bias toward attractive opposite-sex faces than women; and (c) blue-eyed men show a stronger bias toward blue-eyed than brown-eyed feminine faces. The latter test was included because prior research suggested a high effect size. Our data supported hypotheses (a) and (b) but not (c). By conducting separate tests for disengagement of attention and attention capture, we found that individual differences exist at distinct stages of attentional processing but these differences are of varying robustness and importance. In our conclusion, we also advocate the use of linear mixed effects models as the most appropriate statistical approach for studying inter-individual differences in visual attention with naturalistic stimuli. PMID:25698993
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Individual differences in human brain development.
Brown, Timothy T
2017-01-01
This article discusses recent scientific advances in the study of individual differences in human brain development. Focusing on structural neuroimaging measures of brain morphology and tissue properties, two kinds of variability are related and explored: differences across individuals of the same age and differences across age as a result of development. A recent multidimensional modeling study is explained, which was able to use brain measures to predict an individual's chronological age within about one year on average, in children, adolescents, and young adults between 3 and 20 years old. These findings reveal great regularity in the sequence of the aggregate brain state across different ages and phases of development, despite the pronounced individual differences people show on any single brain measure at any given age. Future research is suggested, incorporating additional measures of brain activity and function. WIREs Cogn Sci 2017, 8:e1389. doi: 10.1002/wcs.1389 For further resources related to this article, please visit the WIREs website. © 2016 The Authors. WIREs Cognitive Science published by Wiley Periodicals, Inc.
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Using eye tracking to test for individual differences in attention to attractive faces.
Valuch, Christian; Pflüger, Lena S; Wallner, Bernard; Laeng, Bruno; Ansorge, Ulrich
2015-01-01
We assessed individual differences in visual attention toward faces in relation to their attractiveness via saccadic reaction times. Motivated by the aim to understand individual differences in attention to faces, we tested three hypotheses: (a) Attractive faces hold or capture attention more effectively than less attractive faces; (b) men show a stronger bias toward attractive opposite-sex faces than women; and (c) blue-eyed men show a stronger bias toward blue-eyed than brown-eyed feminine faces. The latter test was included because prior research suggested a high effect size. Our data supported hypotheses (a) and (b) but not (c). By conducting separate tests for disengagement of attention and attention capture, we found that individual differences exist at distinct stages of attentional processing but these differences are of varying robustness and importance. In our conclusion, we also advocate the use of linear mixed effects models as the most appropriate statistical approach for studying inter-individual differences in visual attention with naturalistic stimuli.
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Jonsen, Ian
2016-02-08
State-space models provide a powerful way to scale up inference of movement behaviours from individuals to populations when the inference is made across multiple individuals. Here, I show how a joint estimation approach that assumes individuals share identical movement parameters can lead to improved inference of behavioural states associated with different movement processes. I use simulated movement paths with known behavioural states to compare estimation error between nonhierarchical and joint estimation formulations of an otherwise identical state-space model. Behavioural state estimation error was strongly affected by the degree of similarity between movement patterns characterising the behavioural states, with less error when movements were strongly dissimilar between states. The joint estimation model improved behavioural state estimation relative to the nonhierarchical model for simulated data with heavy-tailed Argos location errors. When applied to Argos telemetry datasets from 10 Weddell seals, the nonhierarchical model estimated highly uncertain behavioural state switching probabilities for most individuals whereas the joint estimation model yielded substantially less uncertainty. The joint estimation model better resolved the behavioural state sequences across all seals. Hierarchical or joint estimation models should be the preferred choice for estimating behavioural states from animal movement data, especially when location data are error-prone.
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The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness.
Guo, Quantong; Lei, Yanjun; Xia, Chengyi; Guo, Lu; Jiang, Xin; Zheng, Zhiming
2016-01-01
Exploring the interplay between information spreading and epidemic spreading is a topic that has been receiving increasing attention. As an efficient means of depicting the spreading of information, which manifests as a cascade phenomenon, awareness cascading is utilized to investigate this coupled transmission. Because in reality, different individuals facing the same epidemic will exhibit distinct behaviors according to their own experiences and attributes, it is important for us to consider the heterogeneity of individuals. Consequently, we propose a heterogeneous spreading model. To describe the heterogeneity, two of the most important but radically different methods for this purpose, the degree and k-core measures, are studied in this paper through three models based on different assumptions. Adopting a Markov chain approach, we succeed in predicting the epidemic threshold trend. Furthermore, we find that when the k-core measure is used to classify individuals, the spreading process is robust to these models, meaning that regardless of the model used, the spreading process is nearly identical at the macroscopic level. In addition, the k-core measure leads to a much larger final epidemic size than the degree measure. These results are cross-checked through numerous simulations, not only of a synthetic network but also of a real multiplex network. The presented findings provide a better understanding of k-core individuals and reveal the importance of considering network structure when investigating various dynamic processes.
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The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness
2016-01-01
Exploring the interplay between information spreading and epidemic spreading is a topic that has been receiving increasing attention. As an efficient means of depicting the spreading of information, which manifests as a cascade phenomenon, awareness cascading is utilized to investigate this coupled transmission. Because in reality, different individuals facing the same epidemic will exhibit distinct behaviors according to their own experiences and attributes, it is important for us to consider the heterogeneity of individuals. Consequently, we propose a heterogeneous spreading model. To describe the heterogeneity, two of the most important but radically different methods for this purpose, the degree and k-core measures, are studied in this paper through three models based on different assumptions. Adopting a Markov chain approach, we succeed in predicting the epidemic threshold trend. Furthermore, we find that when the k-core measure is used to classify individuals, the spreading process is robust to these models, meaning that regardless of the model used, the spreading process is nearly identical at the macroscopic level. In addition, the k-core measure leads to a much larger final epidemic size than the degree measure. These results are cross-checked through numerous simulations, not only of a synthetic network but also of a real multiplex network. The presented findings provide a better understanding of k-core individuals and reveal the importance of considering network structure when investigating various dynamic processes. PMID:27517715
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ERIC Educational Resources Information Center
Crossley, Scott A.; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S.
2016-01-01
This study investigates a novel approach to automatically assessing essay quality that combines natural language processing approaches that assess text features with approaches that assess individual differences in writers such as demographic information, standardized test scores, and survey results. The results demonstrate that combining text…
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ERIC Educational Resources Information Center
Andringa, Sible; Olsthoorn, Nomi; van Beuningen, Catherine; Schoonen, Rob; Hulstijn, Jan
2012-01-01
The goal of this study was to explain individual differences in both native and non-native listening comprehension; 121 native and 113 non-native speakers of Dutch were tested on various linguistic and nonlinguistic cognitive skills thought to underlie listening comprehension. Structural equation modeling was used to identify the predictors of…
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NASA Astrophysics Data System (ADS)
Hinckley, Sarah; Parada, Carolina; Horne, John K.; Mazur, Michael; Woillez, Mathieu
2016-10-01
Biophysical individual-based models (IBMs) have been used to study aspects of early life history of marine fishes such as recruitment, connectivity of spawning and nursery areas, and marine reserve design. However, there is no consistent approach to validating the spatial outputs of these models. In this study, we hope to rectify this gap. We document additions to an existing individual-based biophysical model for Alaska walleye pollock (Gadus chalcogrammus), some simulations made with this model and methods that were used to describe and compare spatial output of the model versus field data derived from ichthyoplankton surveys in the Gulf of Alaska. We used visual methods (e.g. distributional centroids with directional ellipses), several indices (such as a Normalized Difference Index (NDI), and an Overlap Coefficient (OC), and several statistical methods: the Syrjala method, the Getis-Ord Gi* statistic, and a geostatistical method for comparing spatial indices. We assess the utility of these different methods in analyzing spatial output and comparing model output to data, and give recommendations for their appropriate use. Visual methods are useful for initial comparisons of model and data distributions. Metrics such as the NDI and OC give useful measures of co-location and overlap, but care must be taken in discretizing the fields into bins. The Getis-Ord Gi* statistic is useful to determine the patchiness of the fields. The Syrjala method is an easily implemented statistical measure of the difference between the fields, but does not give information on the details of the distributions. Finally, the geostatistical comparison of spatial indices gives good information of details of the distributions and whether they differ significantly between the model and the data. We conclude that each technique gives quite different information about the model-data distribution comparison, and that some are easy to apply and some more complex. We also give recommendations for a multistep process to validate spatial output from IBMs.
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den Ruijter, H M; Peters, S A E; Groenewegen, K A; Anderson, T J; Britton, A R; Dekker, J M; Engström, G; Eijkemans, M J; Evans, G W; de Graaf, J; Grobbee, D E; Hedblad, B; Hofman, A; Holewijn, S; Ikeda, A; Kavousi, M; Kitagawa, K; Kitamura, A; Koffijberg, H; Ikram, M A; Lonn, E M; Lorenz, M W; Mathiesen, E B; Nijpels, G; Okazaki, S; O'Leary, D H; Polak, J F; Price, J F; Robertson, C; Rembold, C M; Rosvall, M; Rundek, T; Salonen, J T; Sitzer, M; Stehouwer, C D A; Witteman, J C; Moons, K G; Bots, M L
2013-07-01
The aim of this work was to investigate whether measurement of the mean common carotid intima-media thickness (CIMT) improves cardiovascular risk prediction in individuals with diabetes. We performed a subanalysis among 4,220 individuals with diabetes in a large ongoing individual participant data meta-analysis involving 56,194 subjects from 17 population-based cohorts worldwide. We first refitted the risk factors of the Framingham heart risk score on the individuals without previous cardiovascular disease (baseline model) and then expanded this model with the mean common CIMT (CIMT model). The absolute 10 year risk for developing a myocardial infarction or stroke was estimated from both models. In individuals with diabetes we compared discrimination and calibration of the two models. Reclassification of individuals with diabetes was based on allocation to another cardiovascular risk category when mean common CIMT was added. During a median follow-up of 8.7 years, 684 first-time cardiovascular events occurred among the population with diabetes. The C statistic was 0.67 for the Framingham model and 0.68 for the CIMT model. The absolute 10 year risk for developing a myocardial infarction or stroke was 16% in both models. There was no net reclassification improvement with the addition of mean common CIMT (1.7%; 95% CI -1.8, 3.8). There were no differences in the results between men and women. There is no improvement in risk prediction in individuals with diabetes when measurement of the mean common CIMT is added to the Framingham risk score. Therefore, this measurement is not recommended for improving individual cardiovascular risk stratification in individuals with diabetes.
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Sociodemographic Factors Associated With Changes in Successful Aging in Spain: A Follow-Up Study.
Domènech-Abella, Joan; Perales, Jaime; Lara, Elvira; Moneta, Maria Victoria; Izquierdo, Ana; Rico-Uribe, Laura Alejandra; Mundó, Jordi; Haro, Josep Maria
2017-06-01
Successful aging (SA) refers to maintaining well-being in old age. Several definitions or models of SA exist (biomedical, psychosocial, and mixed). We examined the longitudinal association between various SA models and sociodemographic factors, and analyzed the patterns of change within these models. This was a nationally representative follow-up in Spain including 3,625 individuals aged ≥50 years. Some 1,970 individuals were interviewed after 3 years. Linear regression models were used to analyze the survey data. Age, sex, and occupation predicted SA in the biomedical model, while marital status, educational level, and urbanicity predicted SA in the psychosocial model. The remaining models included different sets of these predictors as significant. In the psychosocial model, individuals tended to improve over time but this was not the case in the biomedical model. The biomedical and psychosocial components of SA need to be addressed specifically to achieve the best aging trajectories.
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Street, Nichola; Forsythe, Alexandra M; Reilly, Ronan; Taylor, Richard; Helmy, Mai S
2016-01-01
Fractal patterns offer one way to represent the rough complexity of the natural world. Whilst they dominate many of our visual experiences in nature, little large-scale perceptual research has been done to explore how we respond aesthetically to these patterns. Previous research (Taylor et al., 2011) suggests that the fractal patterns with mid-range fractal dimensions (FDs) have universal aesthetic appeal. Perceptual and aesthetic responses to visual complexity have been more varied with findings suggesting both linear (Forsythe et al., 2011) and curvilinear (Berlyne, 1970) relationships. Individual differences have been found to account for many of the differences we see in aesthetic responses but some, such as culture, have received little attention within the fractal and complexity research fields. This two-study article aims to test preference responses to FD and visual complexity, using a large cohort (N = 443) of participants from around the world to allow universality claims to be tested. It explores the extent to which age, culture and gender can predict our preferences for fractally complex patterns. Following exploratory analysis that found strong correlations between FD and visual complexity, a series of linear mixed-effect models were implemented to explore if each of the individual variables could predict preference. The first tested a linear complexity model (likelihood of selecting the more complex image from the pair of images) and the second a mid-range FD model (likelihood of selecting an image within mid-range). Results show that individual differences can reliably predict preferences for complexity across culture, gender and age. However, in fitting with current findings the mid-range models show greater consistency in preference not mediated by gender, age or culture. This article supports the established theory that the mid-range fractal patterns appear to be a universal construct underlying preference but also highlights the fragility of universal claims by demonstrating individual differences in preference for the interrelated concept of visual complexity. This highlights a current stalemate in the field of empirical aesthetics.
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The emergence of coordination in public good games
NASA Astrophysics Data System (ADS)
Hichri, W.; Kirman, A.
2007-01-01
In physical models it is well understood that the aggregate behaviour of a system is not in one to one correspondence with the behaviour of the average individual element of that system. Yet, in many economic models the behaviour of aggregates is thought of as corresponding to that of an individual. A typical example is that of public goods experiments. A systematic feature of such experiments is that, with repetition, people contribute less to public goods. A typical explanation is that people “learn to play Nash” or something approaching it. To justify such an explanation, an individual learning model is tested on average or aggregate data. In this paper we will examine this idea by analysing average and individual behaviour in a series of public goods experiments. We analyse data from a series of games of contributions to public goods and as is usual, we test a learning model on the average data. We then look at individual data, examine the changes that this produces and see if some general model such as the EWA (Expected Weighted Attraction) with varying parameters can account for individual behaviour. We find that once we disaggregate data such models have poor explanatory power. Groups do not learn as supposed, their behaviour differs markedly from one group to another, and the behaviour of the individuals who make up the groups also varies within groups. The decline in aggregate contributions cannot be explained by resorting to a uniform model of individual behaviour. However, the Nash equilibrium of such a game is a total payment for all the individuals and there is some convergence of the group in this respect. Yet the individual contributions do not converge. How the individuals “self-organsise” to coordinate, even in this limited way remains to be explained.
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Individual differences in personality change across the adult life span.
Schwaba, Ted; Bleidorn, Wiebke
2018-06-01
A precise and comprehensive description of personality continuity and change across the life span is the bedrock upon which theories of personality development are built. Little research has quantified the degree to which individuals deviate from mean-level developmental trends. In this study, we addressed this gap by examining individual differences in personality trait change across the life span. Data came from a nationally representative sample of 9,636 Dutch participants who provided Big Five self-reports at five assessment waves across 7 years. We divided our sample into 14 age groups (ages 16-84 at initial measurement) and estimated latent growth curve models to describe individual differences in personality change across the study period for each trait and age group. Across the adult life span, individual differences in personality change were small but significant until old age. For Openness, Conscientiousness, Extraversion, and Agreeableness, individual differences in change were most pronounced in emerging adulthood and decreased throughout midlife and old age. For Emotional Stability, individual differences in change were relatively consistent across the life span. These results inform theories of life span development and provide future directions for research on the causes and conditions of personality change. © 2017 Wiley Periodicals, Inc.
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Individual differences in social information gathering revealed through Bayesian hierarchical models
Pearson, John M.; Watson, Karli K.; Klein, Jeffrey T.; Ebitz, R. Becket; Platt, Michael L.
2013-01-01
As studies of the neural circuits underlying choice expand to include more complicated behaviors, analysis of behaviors elicited in laboratory paradigms has grown increasingly difficult. Social behaviors present a particular challenge, since inter- and intra-individual variation are expected to play key roles. However, due to limitations on data collection, studies must often choose between pooling data across all subjects or using individual subjects' data in isolation. Hierarchical models mediate between these two extremes by modeling individual subjects as drawn from a population distribution, allowing the population at large to serve as prior information about individuals' behavior. Here, we apply this method to data collected across multiple experimental sessions from a set of rhesus macaques performing a social information valuation task. We show that, while the values of social images vary markedly between individuals and between experimental sessions for the same individual, individuals also differentially value particular categories of social images. Furthermore, we demonstrate covariance between values for image categories within individuals and find evidence suggesting that magnitudes of stimulus values tend to diminish over time. PMID:24062635
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The Separate Spheres Model of Gendered Inequality
Miller, Andrea L.; Borgida, Eugene
2016-01-01
Research on role congruity theory and descriptive and prescriptive stereotypes has established that when men and women violate gender stereotypes by crossing spheres, with women pursuing career success and men contributing to domestic labor, they face backlash and economic penalties. Less is known, however, about the types of individuals who are most likely to engage in these forms of discrimination and the types of situations in which this is most likely to occur. We propose that psychological research will benefit from supplementing existing research approaches with an individual differences model of support for separate spheres for men and women. This model allows psychologists to examine individual differences in support for separate spheres as they interact with situational and contextual forces. The separate spheres ideology (SSI) has existed as a cultural idea for many years but has not been operationalized or modeled in social psychology. The Separate Spheres Model presents the SSI as a new psychological construct characterized by individual differences and a motivated system-justifying function, operationalizes the ideology with a new scale measure, and models the ideology as a predictor of some important gendered outcomes in society. As a first step toward developing the Separate Spheres Model, we develop a new measure of individuals’ endorsement of the SSI and demonstrate its reliability, convergent validity, and incremental predictive validity. We provide support for the novel hypotheses that the SSI predicts attitudes regarding workplace flexibility accommodations, income distribution within families between male and female partners, distribution of labor between work and family spheres, and discriminatory workplace behaviors. Finally, we provide experimental support for the hypothesis that the SSI is a motivated, system-justifying ideology. PMID:26800454
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Knowledge transmission model with differing initial transmission and retransmission process
NASA Astrophysics Data System (ADS)
Wang, Haiying; Wang, Jun; Small, Michael
2018-10-01
Knowledge transmission is a cyclic dynamic diffusion process. The rate of acceptance of knowledge differs upon whether or not the recipient has previously held the knowledge. In this paper, the knowledge transmission process is divided into an initial and a retransmission procedure, each with its own transmission and self-learning parameters. Based on epidemic spreading model, we propose a naive-evangelical-agnostic (VEA) knowledge transmission model and derive mean-field equations to describe the dynamics of knowledge transmission in homogeneous networks. Theoretical analysis identifies a criterion for the persistence of knowledge, i.e., the reproduction number R0 depends on the minor effective parameters between the initial and retransmission process. Moreover, the final size of evangelical individuals is only related to retransmission process parameters. Numerical simulations validate the theoretical analysis. Furthermore, the simulations indicate that increasing the initial transmission parameters, including first transmission and self-learning rates of naive individuals, can accelerate the velocity of knowledge transmission efficiently but have no effect on the final size of evangelical individuals. In contrast, the retransmission parameters, including retransmission and self-learning rates of agnostic individuals, have a significant effect on the rate of knowledge transmission, i.e., the larger parameters the greater final density of evangelical individuals.
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Individual differences in behavioural plasticities.
Stamps, Judy A
2016-05-01
Interest in individual differences in animal behavioural plasticities has surged in recent years, but research in this area has been hampered by semantic confusion as different investigators use the same terms (e.g. plasticity, flexibility, responsiveness) to refer to different phenomena. The first goal of this review is to suggest a framework for categorizing the many different types of behavioural plasticities, describe examples of each, and indicate why using reversibility as a criterion for categorizing behavioural plasticities is problematic. This framework is then used to address a number of timely questions about individual differences in behavioural plasticities. One set of questions concerns the experimental designs that can be used to study individual differences in various types of behavioural plasticities. Although within-individual designs are the default option for empirical studies of many types of behavioural plasticities, in some situations (e.g. when experience at an early age affects the behaviour expressed at subsequent ages), 'replicate individual' designs can provide useful insights into individual differences in behavioural plasticities. To date, researchers using within-individual and replicate individual designs have documented individual differences in all of the major categories of behavioural plasticities described herein. Another important question is whether and how different types of behavioural plasticities are related to one another. Currently there is empirical evidence that many behavioural plasticities [e.g. contextual plasticity, learning rates, IIV (intra-individual variability), endogenous plasticities, ontogenetic plasticities) can themselves vary as a function of experiences earlier in life, that is, many types of behavioural plasticity are themselves developmentally plastic. These findings support the assumption that differences among individuals in prior experiences may contribute to individual differences in behavioural plasticities observed at a given age. Several authors have predicted correlations across individuals between different types of behavioural plasticities, i.e. that some individuals will be generally more plastic than others. However, empirical support for most of these predictions, including indirect evidence from studies of relationships between personality traits and plasticities, is currently sparse and equivocal. The final section of this review suggests how an appreciation of the similarities and differences between different types of behavioural plasticities may help theoreticians formulate testable models to explain the evolution of individual differences in behavioural plasticities and the evolutionary and ecological consequences of individual differences in behavioural plasticities. © 2015 Cambridge Philosophical Society.
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A Bayesian hierarchical diffusion model decomposition of performance in Approach–Avoidance Tasks
Krypotos, Angelos-Miltiadis; Beckers, Tom; Kindt, Merel; Wagenmakers, Eric-Jan
2015-01-01
Common methods for analysing response time (RT) tasks, frequently used across different disciplines of psychology, suffer from a number of limitations such as the failure to directly measure the underlying latent processes of interest and the inability to take into account the uncertainty associated with each individual's point estimate of performance. Here, we discuss a Bayesian hierarchical diffusion model and apply it to RT data. This model allows researchers to decompose performance into meaningful psychological processes and to account optimally for individual differences and commonalities, even with relatively sparse data. We highlight the advantages of the Bayesian hierarchical diffusion model decomposition by applying it to performance on Approach–Avoidance Tasks, widely used in the emotion and psychopathology literature. Model fits for two experimental data-sets demonstrate that the model performs well. The Bayesian hierarchical diffusion model overcomes important limitations of current analysis procedures and provides deeper insight in latent psychological processes of interest. PMID:25491372
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Integrating public risk perception into formal natural hazard risk assessment
NASA Astrophysics Data System (ADS)
Plattner, Th.; Plapp, T.; Hebel, B.
2006-06-01
An urgent need to take perception into account for risk assessment has been pointed out by relevant literature, its impact in terms of risk-related behaviour by individuals is obvious. This study represents an effort to overcome the broadly discussed question of whether risk perception is quantifiable or not by proposing a still simple but applicable methodology. A novel approach is elaborated to obtain a more accurate and comprehensive quantification of risk in comparison to present formal risk evaluation practice. A consideration of relevant factors enables a explicit quantification of individual risk perception and evaluation. The model approach integrates the effective individual risk reff and a weighted mean of relevant perception affecting factors PAF. The relevant PAF cover voluntariness of risk-taking, individual reducibility of risk, knowledge and experience, endangerment, subjective damage rating and subjective recurrence frequency perception. The approach assigns an individual weight to each PAF to represent its impact magnitude. The quantification of these weights is target-group-dependent (e.g. experts, laypersons) and may be effected by psychometric methods. The novel approach is subject to a plausibility check using data from an expert-workshop. A first model application is conducted by means of data of an empirical risk perception study in Western Germany to deduce PAF and weight quantification as well as to confirm and evaluate model applicbility and flexibility. Main fields of application will be a quantification of risk perception by individual persons in a formal and technical way e.g. for the purpose of risk communication issues in illustrating differing perspectives of experts and non-experts. For decision making processes this model will have to be applied with caution, since it is by definition not designed to quantify risk acceptance or risk evaluation. The approach may well explain how risk perception differs, but not why it differs. The formal model generates only "snap shots" and considers neither the socio-cultural nor the historical context of risk perception, since it is a highly individualistic and non-contextual approach.
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Automated MRI segmentation for individualized modeling of current flow in the human head.
Huang, Yu; Dmochowski, Jacek P; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C
2013-12-01
High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials.
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Ibáñez, Agustín; Aguado, Jaume; Baez, Sandra; Huepe, David; Lopez, Vladimir; Ortega, Rodrigo; Sigman, Mariano; Mikulan, Ezequiel; Lischinsky, Alicia; Torrente, Fernando; Cetkovich, Marcelo; Torralva, Teresa; Bekinschtein, Tristan; Manes, Facundo
2014-07-01
It is commonly assumed that early emotional signals provide relevant information for social cognition tasks. The goal of this study was to test the association between (a) cortical markers of face emotional processing and (b) social-cognitive measures, and also to build a model which can predict this association (a and b) in healthy volunteers as well as in different groups of psychiatric patients. Thus, we investigated the early cortical processing of emotional stimuli (N170, using a face and word valence task) and their relationship with the social-cognitive profiles (SCPs, indexed by measures of theory of mind, fluid intelligence, speed processing and executive functions). Group comparisons and individual differences were assessed among schizophrenia (SCZ) patients and their relatives, individuals with attention deficit hyperactivity disorder (ADHD), individuals with euthymic bipolar disorder (BD) and healthy participants (educational level, handedness, age and gender matched). Our results provide evidence of emotional N170 impairments in the affected groups (SCZ and relatives, ADHD and BD) as well as subtle group differences. Importantly, cortical processing of emotional stimuli predicted the SCP, as evidenced by a structural equation model analysis. This is the first study to report an association model of brain markers of emotional processing and SCP. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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Comparing Binaural Pre-processing Strategies III
Warzybok, Anna; Ernst, Stephan M. A.
2015-01-01
A comprehensive evaluation of eight signal pre-processing strategies, including directional microphones, coherence filters, single-channel noise reduction, binaural beamformers, and their combinations, was undertaken with normal-hearing (NH) and hearing-impaired (HI) listeners. Speech reception thresholds (SRTs) were measured in three noise scenarios (multitalker babble, cafeteria noise, and single competing talker). Predictions of three common instrumental measures were compared with the general perceptual benefit caused by the algorithms. The individual SRTs measured without pre-processing and individual benefits were objectively estimated using the binaural speech intelligibility model. Ten listeners with NH and 12 HI listeners participated. The participants varied in age and pure-tone threshold levels. Although HI listeners required a better signal-to-noise ratio to obtain 50% intelligibility than listeners with NH, no differences in SRT benefit from the different algorithms were found between the two groups. With the exception of single-channel noise reduction, all algorithms showed an improvement in SRT of between 2.1 dB (in cafeteria noise) and 4.8 dB (in single competing talker condition). Model predictions with binaural speech intelligibility model explained 83% of the measured variance of the individual SRTs in the no pre-processing condition. Regarding the benefit from the algorithms, the instrumental measures were not able to predict the perceptual data in all tested noise conditions. The comparable benefit observed for both groups suggests a possible application of noise reduction schemes for listeners with different hearing status. Although the model can predict the individual SRTs without pre-processing, further development is necessary to predict the benefits obtained from the algorithms at an individual level. PMID:26721922
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Stukken, Loes; Van Rensbergen, Bram; Vanpaemel, Wolf; Storms, Gert
2016-10-01
Several studies have reported differences in categorization strategies among participants: some learn a category by making abstraction across the category members while others use a memorization strategy. Despite the prevalence of these differences, little attention has been paid to investigating what influences some to use an abstraction strategy and others a memorization strategy. The current study had two goals: in a first experiment we investigated whether these differences were stable across time, using the parallel form method often used in psychometric research, and in a second experiment we investigated whether the individual differences in categorization strategy were related to working memory capacity. We used a modelling strategy, in which we not only focused on full abstraction and memorization strategies, but also on intermediate strategies in which some category members are abstracted and others are not. The first study revealed that the individual abstraction strategy of individual participants in two different experiments, performed at different times, correlate significantly, and second study showed that these individual differences were related to the working memory capacity of the participants. Copyright © 2016 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Wong-Ala, J.; Neuheimer, A. B.; Hixon, M.; Powell, B.
2016-02-01
Connectivity estimates, which measure the exchange of individuals among populations, are necessary to create effective reserves for marine life. Connectivity can be influenced by a combination of biology (e.g. spawning time) and physics (e.g. currents). In the past a dispersal model was created in an effort to explain connectivity for the highly sought after reef fish Lau`ipala (Yellow Tang, Zebrasoma flavescens) around Hawai`i Island using physics alone, but this was shown to be insufficient. Here we created an individual based model (IBM) to describe Lau`ipala life history and behavior forced with ocean currents and temperature (via coupling to a physical model) to examine biophysical interactions. The IBM allows for tracking of individual fish from spawning to settlement, and individual variability in modeled processes. We first examined the influence of different reproductive (e.g. batch vs. constant spawners), developmental (e.g. pelagic larval duration), and behavioral (e.g. active vs. passive buoyancy control) traits on modeled connectivity estimates for larval reef fish around Hawai`i Island and compared results to genetic observations of parent-offspring pair distribution. Our model is trait-based which allows individuals to vary in life history strategies enabling mechanistic links between predictions and underlying traits and straightforward applications to other species and sites.
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ERIC Educational Resources Information Center
Biesanz, Jeremy C.
2010-01-01
The social accuracy model of interpersonal perception (SAM) is a componential model that estimates perceiver and target effects of different components of accuracy across traits simultaneously. For instance, Jane may be generally accurate in her perceptions of others and thus high in "perceptive accuracy"--the extent to which a particular…
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Stocco, Andrea; Yamasaki, Brianna L; Prat, Chantel S
2018-04-01
This article describes the data analyzed in the paper "Individual differences in the Simon effect are underpinned by differences in the competitive dynamics in the basal ganglia: An experimental verification and a computational model" (Stocco et al., 2017) [1]. The data includes behavioral results from participants performing three cognitive tasks (Probabilistic Stimulus Selection (Frank et al., 2004) [2], Simon task (Craft and Simon, 1970) [3], and Automated Operation Span (Unsworth et al., 2005) [4]), as well as simulationed traces generated by a computational neurocognitive model that accounts for individual variations in human performance across the tasks. The experimental data encompasses individual data files (in both preprocessed and native output format) as well as group-level summary files. The simulation data includes the entire model code, the results of a full-grid search of the model's parameter space, and the code used to partition the model space and parallelize the simulations. Finally, the repository includes the R scripts used to carry out the statistical analyses reported in the original paper.
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Zijlstra, Agnes; Zijlstra, Wiebren
2013-09-01
Inverted pendulum (IP) models of human walking allow for wearable motion-sensor based estimations of spatio-temporal gait parameters during unconstrained walking in daily-life conditions. At present it is unclear to what extent different IP based estimations yield different results, and reliability and validity have not been investigated in older persons without a specific medical condition. The aim of this study was to compare reliability and validity of four different IP based estimations of mean step length in independent-living older persons. Participants were assessed twice and walked at different speeds while wearing a tri-axial accelerometer at the lower back. For all step-length estimators, test-retest intra-class correlations approached or were above 0.90. Intra-class correlations with reference step length were above 0.92 with a mean error of 0.0 cm when (1) multiplying the estimated center-of-mass displacement during a step by an individual correction factor in a simple IP model, or (2) adding an individual constant for bipedal stance displacement to the estimated displacement during single stance in a 2-phase IP model. When applying generic corrections or constants in all subjects (i.e. multiplication by 1.25, or adding 75% of foot length), correlations were above 0.75 with a mean error of respectively 2.0 and 1.2 cm. Although the results indicate that an individual adjustment of the IP models provides better estimations of mean step length, the ease of a generic adjustment can be favored when merely evaluating intra-individual differences. Further studies should determine the validity of these IP based estimations for assessing gait in daily life. Copyright © 2013 Elsevier B.V. All rights reserved.
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Ensemble predictive model for more accurate soil organic carbon spectroscopic estimation
NASA Astrophysics Data System (ADS)
Vašát, Radim; Kodešová, Radka; Borůvka, Luboš
2017-07-01
A myriad of signal pre-processing strategies and multivariate calibration techniques has been explored in attempt to improve the spectroscopic prediction of soil organic carbon (SOC) over the last few decades. Therefore, to come up with a novel, more powerful, and accurate predictive approach to beat the rank becomes a challenging task. However, there may be a way, so that combine several individual predictions into a single final one (according to ensemble learning theory). As this approach performs best when combining in nature different predictive algorithms that are calibrated with structurally different predictor variables, we tested predictors of two different kinds: 1) reflectance values (or transforms) at each wavelength and 2) absorption feature parameters. Consequently we applied four different calibration techniques, two per each type of predictors: a) partial least squares regression and support vector machines for type 1, and b) multiple linear regression and random forest for type 2. The weights to be assigned to individual predictions within the ensemble model (constructed as a weighted average) were determined by an automated procedure that ensured the best solution among all possible was selected. The approach was tested at soil samples taken from surface horizon of four sites differing in the prevailing soil units. By employing the ensemble predictive model the prediction accuracy of SOC improved at all four sites. The coefficient of determination in cross-validation (R2cv) increased from 0.849, 0.611, 0.811 and 0.644 (the best individual predictions) to 0.864, 0.650, 0.824 and 0.698 for Site 1, 2, 3 and 4, respectively. Generally, the ensemble model affected the final prediction so that the maximal deviations of predicted vs. observed values of the individual predictions were reduced, and thus the correlation cloud became thinner as desired.
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Neural Spike-Train Analyses of the Speech-Based Envelope Power Spectrum Model
Rallapalli, Varsha H.
2016-01-01
Diagnosing and treating hearing impairment is challenging because people with similar degrees of sensorineural hearing loss (SNHL) often have different speech-recognition abilities. The speech-based envelope power spectrum model (sEPSM) has demonstrated that the signal-to-noise ratio (SNRENV) from a modulation filter bank provides a robust speech-intelligibility measure across a wider range of degraded conditions than many long-standing models. In the sEPSM, noise (N) is assumed to: (a) reduce S + N envelope power by filling in dips within clean speech (S) and (b) introduce an envelope noise floor from intrinsic fluctuations in the noise itself. While the promise of SNRENV has been demonstrated for normal-hearing listeners, it has not been thoroughly extended to hearing-impaired listeners because of limited physiological knowledge of how SNHL affects speech-in-noise envelope coding relative to noise alone. Here, envelope coding to speech-in-noise stimuli was quantified from auditory-nerve model spike trains using shuffled correlograms, which were analyzed in the modulation-frequency domain to compute modulation-band estimates of neural SNRENV. Preliminary spike-train analyses show strong similarities to the sEPSM, demonstrating feasibility of neural SNRENV computations. Results suggest that individual differences can occur based on differential degrees of outer- and inner-hair-cell dysfunction in listeners currently diagnosed into the single audiological SNHL category. The predicted acoustic-SNR dependence in individual differences suggests that the SNR-dependent rate of susceptibility could be an important metric in diagnosing individual differences. Future measurements of the neural SNRENV in animal studies with various forms of SNHL will provide valuable insight for understanding individual differences in speech-in-noise intelligibility.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Weisbrod, A.V.; Shea, D.; Moore, M.J.
1995-12-31
The goals of this project were: (1) to determine the level of organochlorine exposure to pilot whales; (2) to identify tissue and individual bioaccumulation patterns, and (3) to develop a predictive model to approximate contaminant bioaccumulation into blubber. Samples from eighteen pilot whales beached in 1990--91 on Cape Cod, MA were analyzed by GC/ECD and GC/MS for polychlorinated biphenyls (PCB) and polycyclic aromatic hydrocarbons (PAHs). Individual congeners and total PCBs were identified and found to be high (ppm range) in several individuals. Blubber and liver differences in metabolizable PCB congeners correlate with differences in CYP 1A abundance and activity inmore » mature vs. immature animals. ANOVA and cluster analyses were performed to identify specific bioaccumulation patterns. Pod or exposure conditions appear to be the most important factor in bioaccumulation in these whales. Maturity level, gender, and metabolizability also seem to influence bioaccumulation in various tissues. These patterns were applied in the development of a steady state mass balance model, which focuses on exposure differences rather than metabolic and gender influences. Using a range of environmental contaminant concentrations for seawater, plankton, squid and fish, the model`s low range of output values best approximated blubber residues.« less
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Interactive vs. Non-Interactive Multi-Model Ensembles
NASA Astrophysics Data System (ADS)
Duane, G. S.
2013-12-01
If the members of an ensemble of different models are allowed to interact with one another in run time, predictive skill can be improved as compared to that of any individual model or any average of indvidual model outputs. Inter-model connections in such an interactive ensemble can be trained, using historical data, so that the resulting ``supermodel' synchronizes with reality when used in weather-prediction mode, where the individual models perform data assimilation from each other (with trainable inter-model 'observation error') as well as from real observations. In climate-projection mode, parameters of the individual models are changed, as might occur from an increase in GHG levels, and one obtains relevant statistical properties of the new supermodel attractor. In simple cases, it has been shown that training of the inter-model connections with the old parameter values gives a supermodel that is still predictive when the parameter values are changed. Here we inquire as to the circumstances under which supermodel performance can be expected to exceed that of the customary weighted average of model outputs. We consider a supermodel formed from quasigeostrophic (QG) channel models with different forcing coefficients, and introduce an effective training scheme for the inter-model connections. We show that the blocked-zonal index cycle is reproduced better by the supermodel than by any non-interactive ensemble in the extreme case where the forcing coefficients of the different models are very large or very small. With realistic differences in forcing coefficients, as would be representative of actual differences among IPCC-class models, the usual linearity assumption is justified and a weighted average of model outputs is adequate. It is therefore hypothesized that supermodeling is likely to be useful in situations where there are qualitative model differences, as arising from sub-gridscale parameterizations, that affect overall model behavior. Otherwise the usual ex post facto averaging will probably suffice. The advantage of supermodeling is seen in statistics such as anticorrelation between blocking activity in the Atlantic and Pacific sectors, in the case of the QG channel model, rather than in overall blocking frequency. Likewise in climate models, the advantage of supermodeling is typically manifest in higher-order statistics rather than in quantities such as mean temperature.
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Séguin, Monique; Di Mambro, Mélanie; Desgranges, Annie
2012-01-01
If certain risk factors are known to increase suicidal behaviors, the question is to determine the differential weight of these various risk factors, on which individuals, in which context and in what period of their lives? We have put to test a model that explains different life trajectories leading to suicide. This research allows to surpass a correlation model of identification of risk factors and to target four distinct sub-groups of individuals for whom the developmental history seems quite different. It is clear that suicide is a complex, multidimensional and multilevel issue. Being at the crossroads of many scientific disciplines, psychology may help integrate and connect knowledge with other disciplines in order to clarify the contexts that affect suicidal individuals differently. This knowledge may help in identifying specific prevention interventions that could modify this chain of events leading ultimately to suicide.
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Routes to short-term memory indexing: lessons from deaf native users of American Sign Language.
Hirshorn, Elizabeth A; Fernandez, Nina M; Bavelier, Daphne
2012-01-01
Models of working memory (WM) have been instrumental in understanding foundational cognitive processes and sources of individual differences. However, current models cannot conclusively explain the consistent group differences between deaf signers and hearing speakers on a number of short-term memory (STM) tasks. Here we take the perspective that these results are not due to a temporal order-processing deficit in deaf individuals, but rather reflect different biases in how different types of memory cues are used to do a given task. We further argue that the main driving force behind the shifts in relative biasing is a consequence of language modality (sign vs. speech) and the processing they afford, and not deafness, per se.
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Routes to short term memory indexing: Lessons from deaf native users of American Sign Language
Hirshorn, Elizabeth A.; Fernandez, Nina M.; Bavelier, Daphne
2012-01-01
Models of working memory (WM) have been instrumental in understanding foundational cognitive processes and sources of individual differences. However, current models cannot conclusively explain the consistent group differences between deaf signers and hearing speakers on a number of short-term memory (STM) tasks. Here we take the perspective that these results are not due to a temporal order-processing deficit in deaf individuals, but rather reflect different biases in how different types of memory cues are used to do a given task. We further argue that the main driving force behind the shifts in relative biasing is a consequence of language modality (sign vs. speech) and the processing they afford, and not deafness, per se. PMID:22871205
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Pathological Narcissism and Interpersonal Behavior in Daily Life
Roche, Michael J.; Pincus, Aaron L.; Conroy, David E.; Hyde, Amanda L.; Ram, Nilam
2014-01-01
The Cognitive-Affective Processing System (CAPS) has been proposed as a useful meta-framework for integrating contextual differences in situations with individual differences in personality pathology. In this article, we evaluated the potential of combining the CAPS meta-framework and contemporary interpersonal theory to investigate how individual differences in pathological narcissism influenced interpersonal functioning in daily life. University students (N = 184) completed event-contingent reports about interpersonal interactions across a 7-day diary study. Using multilevel regression models, we found that combinations of narcissistic expression (grandiosity, vulnerability) were associated with different interpersonal behavior patterns reflective of interpersonal dysfunction. These results are among the first to empirically demonstrate the usefulness of the CAPS model to conceptualize personality pathology through the patterning of if-then interpersonal processes. PMID:23205698
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Automatic RBG-depth-pressure anthropometric analysis and individualised sleep solution prescription.
Esquirol Caussa, Jordi; Palmero Cantariño, Cristina; Bayo Tallón, Vanessa; Cos Morera, Miquel Àngel; Escalera, Sergio; Sánchez, David; Sánchez Padilla, Maider; Serrano Domínguez, Noelia; Relats Vilageliu, Mireia
2017-08-01
Sleep surfaces must adapt to individual somatotypic features to maintain a comfortable, convenient and healthy sleep, preventing diseases and injuries. Individually determining the most adequate rest surface can often be a complex and subjective question. To design and validate an automatic multimodal somatotype determination model to automatically recommend an individually designed mattress-topper-pillow combination. Design and validation of an automated prescription model for an individualised sleep system is performed through a single-image 2 D-3 D analysis and body pressure distribution, to objectively determine optimal individual sleep surfaces combining five different mattress densities, three different toppers and three cervical pillows. A final study (n = 151) and re-analysis (n = 117) defined and validated the model, showing high correlations between calculated and real data (>85% in height and body circumferences, 89.9% in weight, 80.4% in body mass index and more than 70% in morphotype categorisation). Somatotype determination model can accurately prescribe an individualised sleep solution. This can be useful for healthy people and for health centres that need to adapt sleep surfaces to people with special needs. Next steps will increase model's accuracy and analise, if this prescribed individualised sleep solution can improve sleep quantity and quality; additionally, future studies will adapt the model to mattresses with technological improvements, tailor-made production and will define interfaces for people with special needs.
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Electrophysiological models of neural processing.
Nelson, Mark E
2011-01-01
The brain is an amazing information processing system that allows organisms to adaptively monitor and control complex dynamic interactions with their environment across multiple spatial and temporal scales. Mathematical modeling and computer simulation techniques have become essential tools in understanding diverse aspects of neural processing ranging from sub-millisecond temporal coding in the sound localization circuity of barn owls to long-term memory storage and retrieval in humans that can span decades. The processing capabilities of individual neurons lie at the core of these models, with the emphasis shifting upward and downward across different levels of biological organization depending on the nature of the questions being addressed. This review provides an introduction to the techniques for constructing biophysically based models of individual neurons and local networks. Topics include Hodgkin-Huxley-type models of macroscopic membrane currents, Markov models of individual ion-channel currents, compartmental models of neuronal morphology, and network models involving synaptic interactions among multiple neurons.
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State-dependent cognition and its relevance to cultural evolution.
Nettle, Daniel
2018-02-05
Individuals cope with their worlds by using information. In humans in particular, an important potential source of information is cultural tradition. Evolutionary models have examined when it is advantageous to use cultural information, and psychological studies have examined the cognitive biases and priorities that may transform cultural traditions over time. However, these studies have not generally incorporated the idea that individuals vary in state. I argue that variation in state is likely to influence the relative payoffs of using cultural information versus gathering personal information; and also that people in different states will have different cognitive biases and priorities, leading them to transform cultural information in different ways. I explore hunger as one example of state variable likely to have consequences for cultural evolution. Variation in state has the potential to explain why cultural traditions and dynamics are so variable between individuals and populations. It offers evolutionarily-grounded links between the ecology in which individuals live, individual-level cognitive processes, and patterns of culture. However, incorporating heterogeneity of state also makes the modelling of cultural evolution more complex, particularly if the distribution of states is itself influenced by the distribution of cultural beliefs and practices. Copyright © 2018 Elsevier B.V. All rights reserved.
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Neighborhood differences in social capital: a compositional artifact or a contextual construct?
Subramanian, S V; Lochner, Kimberly A; Kawachi, Ichiro
2003-03-01
Assessment of social capital at the neighborhood level is often based on aggregating individual perceptions of trust and reciprocity. Individual perceptions, meanwhile, are influenced through a range of individual attributes. This paper examines the socioeconomic and demographic attributes that systematically correlate with individual perception of social capital and determines the extent to which such attributes account for neighborhood differences in social capital. Using improved multilevel modeling procedures, we ascertain the extent to which differences in social capital perception can be ascribed to true neighborhood-level variations. The analysis is based on the 1994-95 Community Survey of the Project on Human Development in Chicago Neighborhoods (PHDCN). The response measure is based on survey respondent's perceptions of whether people in their neighborhood can be trusted. The results suggest that even after accounting for individual demographic (age, sex, race, marital status) and socioeconomic characteristics (income, education), significant neighborhood differences remain in individual perceptions of trust, substantiating the notion of social capital as a true contextual construct.
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Yamamoto, Dorothy J.; Nelson, Anna M.; Mandt, Bruce H.; Larson, Gaynor A.; Rorabaugh, Jacki M.; Ng, Christopher M.C.; Barcomb, Kelsey M.; Richards, Toni L.; Allen, Richard M.; Zahniser, Nancy R.
2013-01-01
Individual differences are a hallmark of drug addiction. Here, we describe a rat model based on differential initial responsiveness to low dose cocaine. Despite similar brain cocaine levels, individual outbred Sprague-Dawley rats exhibit markedly different magnitudes of acute cocaine-induced locomotor activity and, thereby, can be classified as low or high cocaine responders (LCRs or HCRs). LCRs and HCRs differ in drug-induced, but not novelty-associated, hyperactivity. LCRs have higher basal numbers of striatal dopamine transporters (DATs) than HCRs and exhibit marginal cocaine inhibition of in vivo DAT activity and cocaine-induced increases in extracellular DA. Importantly, lower initial cocaine response predicts greater locomotor sensitization, conditioned place preference and greater motivation to self-administer cocaine following low dose acquisition. Further, outbred Long-Evans rats classified as LCRs, versus HCRs, are more sensitive to cocaine’s discriminative stimulus effects. Overall, results to date with the LCR/HCR model underscore the contribution of striatal DATs to individual differences in initial cocaine responsiveness and the value of assessing the influence of initial drug response on subsequent expression of addiction-like behaviors. PMID:23850581
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Consistent Individual Differences Drive Collective Behavior and Group Functioning of Schooling Fish.
Jolles, Jolle W; Boogert, Neeltje J; Sridhar, Vivek H; Couzin, Iain D; Manica, Andrea
2017-09-25
The ubiquity of consistent inter-individual differences in behavior ("animal personalities") [1, 2] suggests that they might play a fundamental role in driving the movements and functioning of animal groups [3, 4], including their collective decision-making, foraging performance, and predator avoidance. Despite increasing evidence that highlights their importance [5-16], we still lack a unified mechanistic framework to explain and to predict how consistent inter-individual differences may drive collective behavior. Here we investigate how the structure, leadership, movement dynamics, and foraging performance of groups can emerge from inter-individual differences by high-resolution tracking of known behavioral types in free-swimming stickleback (Gasterosteus aculeatus) shoals. We show that individual's propensity to stay near others, measured by a classic "sociability" assay, was negatively linked to swim speed across a range of contexts, and predicted spatial positioning and leadership within groups as well as differences in structure and movement dynamics between groups. In turn, this trait, together with individual's exploratory tendency, measured by a classic "boldness" assay, explained individual and group foraging performance. These effects of consistent individual differences on group-level states emerged naturally from a generic model of self-organizing groups composed of individuals differing in speed and goal-orientedness. Our study provides experimental and theoretical evidence for a simple mechanism to explain the emergence of collective behavior from consistent individual differences, including variation in the structure, leadership, movement dynamics, and functional capabilities of groups, across social and ecological scales. In addition, we demonstrate individual performance is conditional on group composition, indicating how social selection may drive behavioral differentiation between individuals. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.
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Dollé, Laurent; Chavarriaga, Ricardo
2018-01-01
We present a computational model of spatial navigation comprising different learning mechanisms in mammals, i.e., associative, cognitive mapping and parallel systems. This model is able to reproduce a large number of experimental results in different variants of the Morris water maze task, including standard associative phenomena (spatial generalization gradient and blocking), as well as navigation based on cognitive mapping. Furthermore, we show that competitive and cooperative patterns between different navigation strategies in the model allow to explain previous apparently contradictory results supporting either associative or cognitive mechanisms for spatial learning. The key computational mechanism to reconcile experimental results showing different influences of distal and proximal cues on the behavior, different learning times, and different abilities of individuals to alternatively perform spatial and response strategies, relies in the dynamic coordination of navigation strategies, whose performance is evaluated online with a common currency through a modular approach. We provide a set of concrete experimental predictions to further test the computational model. Overall, this computational work sheds new light on inter-individual differences in navigation learning, and provides a formal and mechanistic approach to test various theories of spatial cognition in mammals. PMID:29630600
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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…
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Evolution of Cooperation in Adaptive Social Networks
NASA Astrophysics Data System (ADS)
Segbroeck, Sven Van; Santos, Francisco C.; Traulsen, Arne; Lenaerts, Tom; Pacheco, Jorge M.
Humans are organized in societies, a phenomenon that would never have been possible without the evolution of cooperative behavior. Several mechanisms that foster this evolution have been unraveled over the years, with population structure as a prominent promoter of cooperation. Modern networks of exchange and cooperation are, however, becoming increasingly volatile, and less and less based on long-term stable structure. Here, we address how this change of paradigm aspects the evolution of cooperation. We discuss analytical and numerical models in which individuals can break social ties and create new ones. Interactions are modeled as two-player dilemmas of cooperation. Once a link between two individuals has formed, the productivity of this link is evaluated. Links can be broken off at different rates. This individual capacity of forming new links or severing inconvenient ones can effectively change the nature of the game. We address random formation of new links and local linking rules as well as different individual capacities to maintain social interactions. We conclude by discussing how adaptive social networks can become an important step towards more realistic models of cultural dynamics.
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How Team-Level and Individual-Level Conflict Influences Team Commitment: A Multilevel Investigation.
Lee, Sanghyun; Kwon, Seungwoo; Shin, Shung J; Kim, MinSoo; Park, In-Jo
2017-01-01
We investigate how two different types of conflict (task conflict and relationship conflict) at two different levels (individual-level and team-level) influence individual team commitment. The analysis was conducted using data we collected from 193 employees in 31 branch offices of a Korean commercial bank. The relationships at multiple levels were tested using hierarchical linear modeling (HLM). The results showed that individual-level relationship conflict was negatively related to team commitment while individual-level task conflict was not. In addition, both team-level task and relationship conflict were negatively associated with team commitment. Finally, only team-level relationship conflict significantly moderated the relationship between individual-level relationship conflict and team commitment. We further derive theoretical implications of these findings.
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How Team-Level and Individual-Level Conflict Influences Team Commitment: A Multilevel Investigation
Lee, Sanghyun; Kwon, Seungwoo; Shin, Shung J.; Kim, MinSoo; Park, In-Jo
2018-01-01
We investigate how two different types of conflict (task conflict and relationship conflict) at two different levels (individual-level and team-level) influence individual team commitment. The analysis was conducted using data we collected from 193 employees in 31 branch offices of a Korean commercial bank. The relationships at multiple levels were tested using hierarchical linear modeling (HLM). The results showed that individual-level relationship conflict was negatively related to team commitment while individual-level task conflict was not. In addition, both team-level task and relationship conflict were negatively associated with team commitment. Finally, only team-level relationship conflict significantly moderated the relationship between individual-level relationship conflict and team commitment. We further derive theoretical implications of these findings. PMID:29387033
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Foster, Gary; Navarro-Ruan, Tamara; McEneny-King, Alanna; Edginton, Andrea N; Thabane, Lehana
2016-01-01
Background Individual pharmacokinetic assessment is a critical component of tailored prophylaxis for hemophilia patients. Population pharmacokinetics allows using individual sparse data, thus simplifying individual pharmacokinetic studies. Implementing population pharmacokinetics capacity for the hemophilia community is beyond individual reach and requires a system effort. Objective The Web-Accessible Population Pharmacokinetic Service—Hemophilia (WAPPS-Hemo) project aims to assemble a database of patient pharmacokinetic data for all existing factor concentrates, develop and validate population pharmacokinetics models, and integrate these models within a Web-based calculator for individualized pharmacokinetic estimation in patients at participating treatment centers. Methods Individual pharmacokinetic studies on factor VIII and IX concentrates will be sourced from pharmaceutical companies and independent investigators. All factor concentrate manufacturers, hemophilia treatment centers (HTCs), and independent investigators (identified via a systematic review of the literature) having on file pharmacokinetic data and willing to contribute full or sparse pharmacokinetic data will be eligible for participation. Multicompartmental modeling will be performed using a mixed-model approach for derivation and Bayesian forecasting for estimation of individual sparse data. NONMEM (ICON Development Solutions) will be used as modeling software. Results The WAPPS-Hemo research network has been launched and is currently joined by 30 HTCs from across the world. We have gathered dense individual pharmacokinetic data on 878 subjects, including several replicates, on 21 different molecules from 17 different sources. We have collected sparse individual pharmacokinetic data on 289 subjects from the participating centers through the testing phase of the WAPPS-Hemo Web interface. We have developed prototypal population pharmacokinetics models for 11 molecules. The WAPPS-Hemo website (available at www.wapps-hemo.org, version 2.4), with core functionalities allowing hemophilia treaters to obtain individual pharmacokinetic estimates on sparse data points after 1 or more infusions of a factor concentrate, was launched for use within the research network in July 2015. Conclusions The WAPPS-Hemo project and research network aims to make it easier to perform individual pharmacokinetic assessments on a reduced number of plasma samples by adoption of a population pharmacokinetics approach. The project will also gather data to substantially enhance the current knowledge about factor concentrate pharmacokinetics and sources of its variability in target populations. Trial Registration ClinicalTrials.gov NCT02061072; https://clinicaltrials.gov/ct2/show/NCT02061072 (Archived by WebCite at http://www.webcitation.org/6mRK9bKP6) PMID:27977390
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Avenanti, Alessio; Minio-Paluello, Ilaria; Bufalari, Ilaria; Aglioti, Salvatore M
2009-01-01
The study of inter-individual differences at behavioural and neural levels represents a new avenue for neuroscience. The response to socio-emotional stimuli varies greatly across individuals. For example, identification with the feelings of a movie character may be total for some people or virtually absent for others. Inter-individual differences may reflect both the on-line effect (state) of the observed stimuli and more stable personal characteristics (trait). Here we show that somatomotor mirror responses when viewing others' pain are modulated by both state- and trait-differences in empathy. We recorded motor-evoked potentials (MEPs) induced by Transcranial Magnetic Stimulation (TMS) in healthy individuals observing needles penetrating a model's hand. We found a reduction of corticospinal excitability that was specific for the muscle that subjects observed being penetrated. This inhibition correlated with sensory qualities of the pain ascribed to the model. Moreover, it was greater in subjects with high trait-cognitive empathy and lower in subjects with high trait-personal distress and in those with high aversion for the observed movies. Results indicate that somatomotor responses to others' pain are influenced by specific onlookers' personality traits and self-oriented emotional reactions. Our findings suggest that multiple distinct mechanisms shape mirror mapping of others' pain.
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A Spatial Agent-Based Model for the Simulation of Adults’ Daily Walking Within a City
Yang, Yong; Roux, Ana V. Diez; Auchincloss, Amy H.; Rodriguez, Daniel A.; Brown, Daniel G.
2012-01-01
Environmental effects on walking behavior have received attention in recent years because of the potential for policy interventions to increase population levels of walking. Most epidemiologic studies describe associations of walking behavior with environmental features. These analyses ignore the dynamic processes that shape walking behaviors. A spatial agent-based model (ABM) was developed to simulate peoples’ walking behaviors within a city. Each individual was assigned properties such as age, SES, walking ability, attitude toward walking and a home location. Individuals perform different activities on a regular basis such as traveling for work, for shopping, and for recreation. Whether an individual walks and the amount she or he walks is a function distance to different activities and her or his walking ability and attitude toward walking. An individual’s attitude toward walking evolves over time as a function of past experiences, walking of others along the walking route, limits on distances walked per day, and attitudes toward walking of the other individuals within her/his social network. The model was calibrated and used to examine the contributions of land use and safety to socioeconomic differences in walking. With further refinement and validation, ABMs may help to better understand the determinants of walking and identify the most promising interventions to increase walking. PMID:21335269
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ERIC Educational Resources Information Center
Ghosh, Rajashi; Chaudhuri, Sanghamitra
2009-01-01
This article proposes a conceptual model to explore the effects of intergenerational transition in individualism/collectivism orientations on the outlook towards different human resource development (HRD) and management practices. It contributes to the existing cross-cultural research in HRD by defining three prominent generations in India and by…
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Integration of individual and social information for decision-making in groups of different sizes
Goïame, Sidney; O'Connor, David A.; Dreher, Jean-Claude
2017-01-01
When making judgments in a group, individuals often revise their initial beliefs about the best judgment to make given what others believe. Despite the ubiquity of this phenomenon, we know little about how the brain updates beliefs when integrating personal judgments (individual information) with those of others (social information). Here, we investigated the neurocomputational mechanisms of how we adapt our judgments to those made by groups of different sizes, in the context of jury decisions for a criminal. By testing different theoretical models, we showed that a social Bayesian inference model captured changes in judgments better than 2 other models. Our results showed that participants updated their beliefs by appropriately weighting individual and social sources of information according to their respective credibility. When investigating 2 fundamental computations of Bayesian inference, belief updates and credibility estimates of social information, we found that the dorsal anterior cingulate cortex (dACC) computed the level of belief updates, while the bilateral frontopolar cortex (FPC) was more engaged in individuals who assigned a greater credibility to the judgments of a larger group. Moreover, increased functional connectivity between these 2 brain regions reflected a greater influence of group size on the relative credibility of social information. These results provide a mechanistic understanding of the computational roles of the FPC-dACC network in steering judgment adaptation to a group’s opinion. Taken together, these findings provide a computational account of how the human brain integrates individual and social information for decision-making in groups. PMID:28658252
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Self-organization and natural selection in the evolution of complex despotic societies.
Hemelrijk, C K
2002-06-01
Differences between related species are usually explained as separate adaptations produced by individual selection. I discuss in this paper how related species, which differ in many respects, may evolve by a combination of individual selection, self-organization, and group-selection, requiring an evolutionary adaptation of only a single trait. In line with the supposed evolution of despotic species of macaques, we take as a starting point an ancestral species that is egalitarian and mildly aggressive. We suppose it to live in an environment with abundant food and we put the case that, if food becomes scarce and more clumped, natural selection at the level of the individual will favor individuals with a more intense aggression (implying, for instance, biting and fierce fighting). Using an individual-centered model, called DomWorld, I show what happens when the intensity of aggression increases. In DomWorld, group life is represented by artificial individuals that live in a homogeneous world. Individuals are extremely simple: all they do is flock together and, upon meeting one another, they may perform dominance interactions in which the effects of winning and losing are self-reinforcing. When the intensity of aggression in the model is increased, a complex feedback between the hierarchy and spatial structure results; via self-organization, this feedback causes the egalitarian society to change into a despotic one. The many differences between the two types of artificial society closely correspond to those between despotic and egalitarian macaques in the real world. Given that, in the model, the organization changes as a side effect of the change of one single trait proper to an egalitarian society, in the real world a despotic society may also have arisen as a side effect of the mutation of a single trait of an egalitarian species. If groups with different intensities of aggression evolve in this way, they will also have different gradients of hierarchy. When food is scarce, groups with the steepest hierarchy may have the best chance to survive, because at least a small number of individuals in such a group may succeed in producing offspring, whereas in egalitarian societies every individual is at risk of being insufficiently fed to reproduce. Therefore, intrademic group selection (selection within an interbreeding group) may have contributed to the evolution of despotic societies.
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SYSTEMS BIOLOGY MODEL DEVELOPMENT AND APPLICATION
System biology models holistically describe, in a quantitative fashion, the relationships between different levels of a biologic system. Relationships between individual components of a system are delineated. System biology models describe how the components of the system inter...
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Holm, Kristen E.; Borson, Soo; Sandhaus, Robert A.; Ford, Dee W.; Strange, Charlie; Bowler, Russell P.; Make, Barry J.; Wamboldt, Frederick S.
2013-01-01
Smokers who have severe alpha-1 antitrypsin deficiency (AATD) are at risk for developing COPD earlier in life than smokers without AATD, and are likely to experience challenges adjusting to their illness because they are in a highly productive life stage when they are diagnosed with COPD. This study examined whether individuals with AATD-associated COPD differ from individuals with non-AATD COPD with regard to depression, anxiety, dyspnea, and health-related quality of life (HRQL). Cross-sectional data were collected via self-report questionnaires completed by 480 individuals with non-AATD COPD and 578 individuals with AATD-associated COPD under protocols with IRB approval. Multiple linear regression models were used to test whether individuals with non-AATD COPD differed from individuals with AATD-associated COPD with regard to depression, anxiety, dyspnea, and HRQL. All models adjusted for demographic and health characteristics. Individuals with AATD-associated COPD did not report more symptoms of depression or anxiety; however, they did report more dyspnea (B = 0.31, 95% CI = 0.16 to 0.47, p < 0.001) and impairment in HRQL (B = 4.75, 95% CI = 2.10 to 7.41, p < 0.001) than other individuals with COPD. Individuals with AATD-associated COPD were more likely to be a member of a couple (rather than single) and had a higher level of education when compared to individuals with non-AATD COPD. Resources available to persons with AATD-associated COPD, such as being in a serious relationship and having higher education, may offset the effect of age when considering symptoms of depression and anxiety in patients with COPD. PMID:23547634
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Holm, Kristen E; Borson, Soo; Sandhaus, Robert A; Ford, Dee W; Strange, Charlie; Bowler, Russell P; Make, Barry J; Wamboldt, Frederick S
2013-04-01
Smokers who have severe alpha-1 antitrypsin deficiency (AATD) are at risk for developing COPD earlier in life than smokers without AATD, and are likely to experience challenges adjusting to their illness because they are in a highly productive life stage when they are diagnosed with COPD. This study examined whether individuals with AATD-associated COPD differ from individuals with non-AATD COPD with regard to depression, anxiety, dyspnea, and health-related quality of life (HRQL). Cross-sectional data were collected via self-report questionnaires completed by 480 individuals with non-AATD COPD and 578 individuals with AATD-associated COPD under protocols with IRB approval. Multiple linear regression models were used to test whether individuals with non-AATD COPD differed from individuals with AATD-associated COPD with regard to depression, anxiety, dyspnea, and HRQL. All models adjusted for demographic and health characteristics. Individuals with AATD-associated COPD did not report more symptoms of depression or anxiety; however, they did report more dyspnea (B = 0.31, 95% CI = 0.16 to 0.47, p < 0.001) and impairment in HRQL (B = 4.75, 95% CI = 2.10 to 7.41, p < 0.001) than other individuals with COPD. Individuals with AATD-associated COPD were more likely to be a member of a couple (rather than single) and had a higher level of education when compared to individuals with non-AATD COPD. Resources available to persons with AATD-associated COPD, such as being in a serious relationship and having higher education, may offset the effect of age when considering symptoms of depression and anxiety in patients with COPD.
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Movement ecology: size-specific behavioral response of an invasive snail to food availability.
Snider, Sunny B; Gilliam, James F
2008-07-01
Immigration, emigration, migration, and redistribution describe processes that involve movement of individuals. These movements are an essential part of contemporary ecological models, and understanding how movement is affected by biotic and abiotic factors is important for effectively modeling ecological processes that depend on movement. We asked how phenotypic heterogeneity (body size) and environmental heterogeneity (food resource level) affect the movement behavior of an aquatic snail (Tarebia granifera), and whether including these phenotypic and environmental effects improves advection-diffusion models of movement. We postulated various elaborations of the basic advection diffusion model as a priori working hypotheses. To test our hypotheses we measured individual snail movements in experimental streams at high- and low-food resource treatments. Using these experimental movement data, we examined the dependency of model selection on resource level and body size using Akaike's Information Criterion (AIC). At low resources, large individuals moved faster than small individuals, producing a platykurtic movement distribution; including size dependency in the model improved model performance. In stark contrast, at high resources, individuals moved upstream together as a wave, and body size differences largely disappeared. The model selection exercise indicated that population heterogeneity is best described by the advection component of movement for this species, because the top-ranked model included size dependency in advection, but not diffusion. Also, all probable models included resource dependency. Thus population and environmental heterogeneities both influence individual movement behaviors and the population-level distribution kernels, and their interaction may drive variation in movement behaviors in terms of both advection rates and diffusion rates. A behaviorally informed modeling framework will integrate the sentient response of individuals in terms of movement and enhance our ability to accurately model ecological processes that depend on animal movement.
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Bret C. Harvey; Jason L. White; Rodney J. Nakamoto; Steven F. Railsback
2014-01-01
Resource managers commonly face the need to evaluate the ecological consequences of specific water diversions of small streams. We addressed this need by conducting 4 years of biophysical monitoring of stream reaches above and below a diversion and applying two individual-based models of salmonid fish that simulated different levels of behavioral complexity. The...
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Brandt, C.C.; Weinstein, D.A.; Shugart, H.H.
1980-10-01
The Quechua Indians of the Peruvian Andes are an example of a human population which has developed special cultural adaptations to deal with hypocaloric stress imposed by a harsh environment. A highly detailed human ecosystem model, NUNOA, which simulates the yearly energy balance of individuals, families, and extended families in a hypothetical farming and herding Quechua community of the high Andes was developed. Unlike most population models which use sets of differential equations in which individuals are aggregated into groups, this model considers the response of each individual to a stochastic environment. The model calculates the yearly energy demand formore » each family based on caloric requirements of its members. For each family, the model simulates the cultivation of seven different crops and the impact of precipitation, temperature, and disease on yield. Herding, slaughter, and market sales of three different animal species are also simulated. Any energy production in excess of the family's energy demand is placed into extended family storage for possible redistribution. A family failing to meet their annual energy demand may slaughter additional herd animals, temporarily migrate from the community, or borrow food from the extended family storage. The energy balance is used in determining births, deaths, marriages, and resource sharing in the Indian community. In addition, the model maintains a record of each individual's ancestry as well as seven genetic traits for use in tracing lineage and gene flow. The model user has the opportunity to investigate the effect of changes in marriage patterns, resource sharing patterns, or subsistence activities on the ability of the human population to survive in the harsh Andean environment. In addition, the user may investigate the impact of external technology on the Indian culture.« less
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Chimpanzees demonstrate individual differences in social information use.
Watson, Stuart K; Vale, Gillian L; Hopper, Lydia M; Dean, Lewis G; Kendal, Rachel L; Price, Elizabeth E; Wood, Lara A; Davis, Sarah J; Schapiro, Steven J; Lambeth, Susan P; Whiten, Andrew
2018-06-19
Studies of transmission biases in social learning have greatly informed our understanding of how behaviour patterns may diffuse through animal populations, yet within-species inter-individual variation in social information use has received little attention and remains poorly understood. We have addressed this question by examining individual performances across multiple experiments with the same population of primates. We compiled a dataset spanning 16 social learning studies (26 experimental conditions) carried out at the same study site over a 12-year period, incorporating a total of 167 chimpanzees. We applied a binary scoring system to code each participant's performance in each study according to whether they demonstrated evidence of using social information from conspecifics to solve the experimental task or not (Social Information Score-'SIS'). Bayesian binomial mixed effects models were then used to estimate the extent to which individual differences influenced SIS, together with any effects of sex, rearing history, age, prior involvement in research and task type on SIS. An estimate of repeatability found that approximately half of the variance in SIS was accounted for by individual identity, indicating that individual differences play a critical role in the social learning behaviour of chimpanzees. According to the model that best fit the data, females were, depending on their rearing history, 15-24% more likely to use social information to solve experimental tasks than males. However, there was no strong evidence of an effect of age or research experience, and pedigree records indicated that SIS was not a strongly heritable trait. Our study offers a novel, transferable method for the study of individual differences in social learning.
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Individual-based modeling of ecological and evolutionary processes
DeAngelis, Donald L.; Mooij, Wolf M.
2005-01-01
Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.
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Hertzog, Christopher; Dixon, Roger A; Hultsch, David F; MacDonald, Stuart W S
2003-12-01
The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations.
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Bansal, Ravi; Liu, Jun; Gerber, Andrew J.; Goh, Suzanne; Posner, Jonathan; Colibazzi, Tiziano; Algermissen, Molly; Chiang, I-Chin; Russell, James A.; Peterson, Bradley S.
2015-01-01
The Affective Circumplex Model holds that emotions can be described as linear combinations of two underlying, independent neurophysiological systems (arousal, valence). Given research suggesting individuals with autism spectrum disorders (ASD) have difficulty processing emotions, we used the circumplex model to compare how individuals with ASD and typically-developing (TD) individuals respond to facial emotions. Participants (51 ASD, 80 TD) rated facial expressions along arousal and valence dimensions; we fitted closed, smooth, 2-dimensional curves to their ratings to examine overall circumplex contours. We modeled individual and group influences on parameters describing curve contours to identify differences in dimensional effects across groups. Significant main effects of diagnosis indicated the ASD-group’ s ratings were constricted for the entire circumplex, suggesting range constriction across all emotions. Findings did not change when covarying for overall intelligence. PMID:24234677
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Modeling individualized coefficient alpha to measure quality of test score data.
Liu, Molei; Hu, Ming; Zhou, Xiao-Hua
2018-05-23
Individualized coefficient alpha is defined. It is item and subject specific and is used to measure the quality of test score data with heterogenicity among the subjects and items. A regression model is developed based on 3 sets of generalized estimating equations. The first set of generalized estimating equation models the expectation of the responses, the second set models the response's variance, and the third set is proposed to estimate the individualized coefficient alpha, defined and used to measure individualized internal consistency of the responses. We also use different techniques to extend our method to handle missing data. Asymptotic property of the estimators is discussed, based on which inference on the coefficient alpha is derived. Performance of our method is evaluated through simulation study and real data analysis. The real data application is from a health literacy study in Hunan province of China. Copyright © 2018 John Wiley & Sons, Ltd.
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Bellenguez, Céline; Strange, Amy; Freeman, Colin; Donnelly, Peter; Spencer, Chris C A
2012-01-01
High-throughput genotyping arrays provide an efficient way to survey single nucleotide polymorphisms (SNPs) across the genome in large numbers of individuals. Downstream analysis of the data, for example in genome-wide association studies (GWAS), often involves statistical models of genotype frequencies across individuals. The complexities of the sample collection process and the potential for errors in the experimental assay can lead to biases and artefacts in an individual's inferred genotypes. Rather than attempting to model these complications, it has become a standard practice to remove individuals whose genome-wide data differ from the sample at large. Here we describe a simple, but robust, statistical algorithm to identify samples with atypical summaries of genome-wide variation. Its use as a semi-automated quality control tool is demonstrated using several summary statistics, selected to identify different potential problems, and it is applied to two different genotyping platforms and sample collections. The algorithm is written in R and is freely available at www.well.ox.ac.uk/chris-spencer chris.spencer@well.ox.ac.uk Supplementary data are available at Bioinformatics online.
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Individual Differences in Visual Word Recognition: Insights from the English Lexicon Project
Yap, Melvin J.; Balota, David A.; Sibley, Daragh E.; Ratcliff, Roger
2011-01-01
Empirical work and models of visual word recognition have traditionally focused on group-level performance. Despite the emphasis on the prototypical reader, there is clear evidence that variation in reading skill modulates word recognition performance. In the present study, we examined differences between individuals who contributed to the English Lexicon Project (http://elexicon.wustl.edu), an online behavioral database containing nearly four million word recognition (speeded pronunciation and lexical decision) trials from over 1,200 participants. We observed considerable within- and between-session reliability across distinct sets of items, in terms of overall mean response time (RT), RT distributional characteristics, diffusion model parameters (Ratcliff, Gomez, & McKoon, 2004), and sensitivity to underlying lexical dimensions. This indicates reliably detectable individual differences in word recognition performance. In addition, higher vocabulary knowledge was associated with faster, more accurate word recognition performance, attenuated sensitivity to stimuli characteristics, and more efficient accumulation of information. Finally, in contrast to suggestions in the literature, we did not find evidence that individuals were trading-off in their utilization of lexical and nonlexical information. PMID:21728459
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Affecting Factors of Secondhand Smoke Exposure in Korea: Focused on Different Exposure Locations.
Sun, Li Yuan; Cheong, Hae Kwan; Lee, Eun Whan; Kang, Kyeong Jin; Park, Jae Hyun
2016-09-01
Exposure to secondhand smoke (SHS) not only can cause serious illness, but is also an economic and social burden. Contextual and individual factors of non-smoker exposure to SHS depend on location. However, studies focusing on this subject are lacking. In this study, we described and compared the factors related to SHS exposure according to location in Korea. Regarding individual factors related to SHS exposure, a common individual variable model and location-specific variable model was used to evaluate SHS exposure at home/work/public locations based on sex. In common individual variables, such as age, and smoking status showed different relationships with SHS exposure in different locations. Among home-related variables, housing type and family with a single father and unmarried children showed the strongest positive relationships with SHS exposure in both males and females. In the workplace, service and sales workers, blue-collar workers, and manual laborers showed the strongest positive association with SHS exposure in males and females. For multilevel analysis in public places, only SHS exposure in females was positively related with cancer screening rate. Exposure to SHS in public places showed a positive relationship with drinking rate and single-parent family in males and females. The problem of SHS embodies social policies and interactions between individuals and social contextual factors. Policy makers should consider the contextual factors of specific locations and regional and individual context, along with differences between males and females, to develop effective strategies for reducing SHS exposure.
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Lamb, S E; Pepper, J; Lall, R; Jørstad-Stein, E C; Clark, M D; Hill, L; Fereday-Smith, J
2009-09-14
The aim was to compare effectiveness of group versus individual sessions of physiotherapy in terms of symptoms, quality of life, and costs, and to investigate the effect of patient preference on uptake and outcome of treatment. A pragmatic, multi-centre randomised controlled trial in five British National Health Service physiotherapy departments. 174 women with stress and/or urge incontinence were randomised to receive treatment from a physiotherapist delivered in a group or individual setting over three weekly sessions. Outcome were measured as Symptom Severity Index; Incontinence-related Quality of Life questionnaire; National Health Service costs, and out of pocket expenses. The majority of women expressed no preference (55%) or preference for individual treatment (36%). Treatment attendance was good, with similar attendance with both service delivery models. Overall, there were no statistically significant differences in symptom severity or quality of life outcomes between the models. Over 85% of women reported a subjective benefit of treatment, with a slightly higher rating in the individual compared with the group setting. When all health care costs were considered, average cost per patient was lower for group sessions (Mean cost difference 52.91 pounds 95%, confidence interval ( 25.82 pounds- 80.00 pounds)). Indications are that whilst some women may have an initial preference for individual treatment, there are no substantial differences in the symptom, quality of life outcomes or non-attendance. Because of the significant difference in mean cost, group treatment is recommended. ISRCTN 16772662.
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Epidemics spread in heterogeneous populations
NASA Astrophysics Data System (ADS)
Capała, Karol; Dybiec, Bartłomiej
2017-05-01
Individuals building populations are subject to variability. This variability affects progress of epidemic outbreaks, because individuals tend to be more or less resistant. Individuals also differ with respect to their recovery rate. Here, properties of the SIR model in inhomogeneous populations are studied. It is shown that a small change in model's parameters, e.g. recovery or infection rate, can substantially change properties of final states which is especially well-visible in distributions of the epidemic size. In addition to the epidemic size and radii distributions, the paper explores first passage time properties of epidemic outbreaks.
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ERIC Educational Resources Information Center
Kearns, Devin M.; Steacy, Laura M.; Compton, Donald L.; Gilbert, Jennifer K.; Goodwin, Amanda P.; Cho, Eunsoo; Lindstrom, Esther R.; Collins, Alyson A.
2016-01-01
Comprehensive models of derived polymorphemic word recognition skill in developing readers, with an emphasis on children with reading difficulty (RD), have not been developed. The purpose of the present study was to model individual differences in polymorphemic word recognition ability at the item level among 5th-grade children (N = 173)…
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A Cross-Cultural Analysis of the Effectiveness of the Learning Organization Model in School Contexts
ERIC Educational Resources Information Center
Alavi, Seyyed Babak; McCormick, John
2004-01-01
It has been argued that some management theories and models may not be universal and are based on some cultural assumptions. It is argued in this paper that the effectiveness of applying the Learning Organization (LO) model in school contexts across different countries may be associated with cultural differences such as individualism,…
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Evers, Ellen; de Vries, Han; Spruijt, Berry M.; Sterck, Elisabeth H. M.
2011-01-01
In group-living animals, such as primates, the average spatial group structure often reflects the dominance hierarchy, with central dominants and peripheral subordinates. This central-peripheral group structure can arise by self-organization as a result of subordinates fleeing from dominants after losing a fight. However, in real primates, subordinates often avoid interactions with potentially aggressive group members, thereby preventing aggression and subsequent fleeing. Using agent-based modeling, we investigated which spatial and encounter structures emerge when subordinates also avoid known potential aggressors at a distance as compared with the model which only included fleeing after losing a fight (fleeing model). A central-peripheral group structure emerged in most conditions. When avoidance was employed at small or intermediate distances, centrality of dominants emerged similar to the fleeing model, but in a more pronounced way. This result was also found when fleeing after a fight was made independent of dominance rank, i.e. occurred randomly. Employing avoidance at larger distances yielded more spread out groups. This provides a possible explanation of larger group spread in more aggressive species. With avoidance at very large distances, spatially and socially distinct subgroups emerged. We also investigated how encounters were distributed amongst group members. In the fleeing model all individuals encountered all group members equally often, whereas in the avoidance model encounters occurred mostly among similar-ranking individuals. Finally, we also identified a very general and simple mechanism causing a central-peripheral group structure: when individuals merely differed in velocity, faster individuals automatically ended up at the periphery. In summary, a central-peripheral group pattern can easily emerge from individual variation in different movement properties in general, such as fleeing, avoidance or velocity. Moreover, avoidance behavior also affects the encounter structure and can lead to subgroup formation. PMID:22125595
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Affect intensity and individual differences in informational style.
Larsen, R J; Billings, D W; Cutler, S E
1996-03-01
Although individuals differ widely in the typical intensity of their affective experience, the mechanisms that create or maintain these differences are unclear. Larsen, Diener, and Cropanzano (1987) examined the hypothesis that individual differences in affect intensity (AI) are related to how people interpret emotional stimuli. They found that high AI individuals engaged in more personalizing and generalizing cognitions while construing emotional stimuli than low AI individuals. The present study extends these findings by examining cognitive activity during a different task-the generation of information to communicate about life events. Participants provided free-response descriptions of 16 life events. These descriptions were content coded for five informational style variables. It was found that the descriptive information generated by high AI participants contained significantly more references to emotional arousal, more focus on feelings, and more generalization compared to participants low in AI. These results are consistent with the notion that specific cognitive activity may lead to, or at least be associated with, dispositional affect intensity. In addition, the informational style variables identified in this study were stable over time and consistent across situations. Although men and women differ in AI, this difference becomes insignificant after controlling for informational style variation. Overall results are discussed in terms of a model of various psychological mechanisms that may potentially create or maintain individual differences in affect intensity.
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Conceptual Models and the Future of Special Education
ERIC Educational Resources Information Center
Kauffman, James M.
2007-01-01
A medical model has advantages over a legal model in thinking about special education, especially in responding supportively to difference, meeting individual needs, and practicing prevention. The legal conceptual model now dominates thinking about special education, but a medical model promises a brighter future for special education and for…
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Evolutionary dynamics of group formation.
Javarone, Marco Alberto; Marinazzo, Daniele
2017-01-01
Group formation is a quite ubiquitous phenomenon across different animal species, whose individuals cluster together forming communities of diverse size. Previous investigations suggest that, in general, this phenomenon might have similar underlying reasons across the interested species, despite genetic and behavioral differences. For instance improving the individual safety (e.g. from predators), and increasing the probability to get food resources. Remarkably, the group size might strongly vary from species to species, e.g. shoals of fishes and herds of lions, and sometimes even within the same species, e.g. tribes and families in human societies. Here we build on previous theories stating that the dynamics of group formation may have evolutionary roots, and we explore this fascinating hypothesis from a purely theoretical perspective, with a model using the framework of Evolutionary Game Theory. In our model we hypothesize that homogeneity constitutes a fundamental ingredient in these dynamics. Accordingly, we study a population that tries to form homogeneous groups, i.e. composed of similar agents. The formation of a group can be interpreted as a strategy. Notably, agents can form a group (receiving a 'group payoff'), or can act individually (receiving an 'individual payoff'). The phase diagram of the modeled population shows a sharp transition between the 'group phase' and the 'individual phase', characterized by a critical 'individual payoff'. Our results then support the hypothesis that the phenomenon of group formation has evolutionary roots.
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Yoneoka, Daisuke; Henmi, Masayuki
2017-06-01
Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the sets of covariates differ across models, interpretation of coefficients will differ, thereby making it difficult to synthesize them. Moreover, previous synthesis methods for regression models, such as multivariate meta-analysis, often have problems because covariance matrix of coefficients (i.e. within-study correlations) or individual patient data are not necessarily available. This study, therefore, proposes a brief explanation regarding a method to synthesize linear regression models under different covariate sets by using a generalized least squares method involving bias correction terms. Especially, we also propose an approach to recover (at most) threecorrelations of covariates, which is required for the calculation of the bias term without individual patient data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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Lauck, Sandra B; Sawatzky, Richard; Johnson, Joy L; Humphries, Karin; Bennett, Matthew T; Chakrabarti, Santabhanu; Kerr, Charles R; Tung, Stanley; Yeung-Lai-Wah, John A; Ratner, Pamela A
2015-03-01
Social health is a dimension of quality of life, and refers to people's involvement in, and satisfaction with social roles, responsibilities, and activities. The implantable cardioverter-defibrillator is associated with changes in overall quality of life, but little is known about sex differences in individual trajectories of change in social health. We prospectively measured changes in 3 subscales of the SF-36v2 generic health questionnaire (role physical, role emotional, and social functioning), 2 Patient-Reported Outcomes Measurement Information System short forms (satisfaction with participation in social roles and satisfaction with participation in discretionary social activities), and the Florida Patient Acceptance Survey before and at 1, 2, and 6 months after implantation. Individual growth models of temporal change were estimated. The scores of the 6 indicators improved with time. The unconditional model demonstrated significant (fixed effects: P<0.05; covariance parameters: P<0.10) residual variability in the individual trajectories. In the conditional model, men and women differed significantly in their rates of change in the scores of 3 of the 6 measures. Although men's mean scores exceeded women's mean scores on all indicators at baseline (range of relative mean difference: 11.0% to 17.8%), the rate of women's change resulted in a reversal in relative standing at 6 months after implantation, with the mean scores of women exceeding the men's by 4.5% to 5.6%. Men and women differed in their trajectories of change in social health, both in terms of their starting points (ie, baseline scores) and their rates of change. © 2015 American Heart Association, Inc.
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Rands, Sean A.
2011-01-01
Although social behaviour can bring many benefits to an individual, there are also costs that may be incurred whenever the members of a social group interact. The formation of dominance hierarchies could offer a means of reducing some of the costs of social interaction, but individuals within the hierarchy may end up paying differing costs dependent upon their position within the hierarchy. These differing interaction costs may therefore influence the behaviour of the group, as subordinate individuals may experience very different benefits and costs to dominants when the group is conducting a given behaviour. Here, a state-dependent dynamic game is described which considers a pair of social foragers where there is a set dominance relationship within the pair. The model considers the case where the subordinate member of the pair pays an interference cost when it and the dominant individual conduct specific pairs of behaviours together. The model demonstrates that if the subordinate individual pays these energetic costs when it interacts with the dominant individual, this has effects upon the behaviour of both subordinate and the dominant individuals. Including interaction costs increases the amount of foraging behaviour both individuals conduct, with the behaviour of the pair being driven by the subordinate individual. The subordinate will tend to be the lighter individual for longer periods of time when interaction costs are imposed. This supports earlier suggestions that lighter individuals should act as the decision-maker within the pair, giving leadership-like behaviours that are based upon energetic state. Pre-existing properties of individuals such as their dominance will be less important for determining which individual makes the decisions for the pair. This suggests that, even with strict behavioural hierarchies, identifying which individual is the dominant one is not sufficient for identifying which one is the leader. PMID:22028645
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Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.
Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit
2018-02-13
Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Taksler, Glen B; Perzynski, Adam T; Kattan, Michael W
2017-04-01
Recommendations for colorectal cancer screening encourage patients to choose among various screening methods based on individual preferences for benefits, risks, screening frequency, and discomfort. We devised a model to illustrate how individuals with varying tolerance for screening complications risk might decide on their preferred screening strategy. We developed a discrete-time Markov mathematical model that allowed hypothetical individuals to maximize expected lifetime utility by selecting screening method, start age, stop age, and frequency. Individuals could choose from stool-based testing every 1 to 3 years, flexible sigmoidoscopy every 1 to 20 years with annual stool-based testing, colonoscopy every 1 to 20 years, or no screening. We compared the life expectancy gained from the chosen strategy with the life expectancy available from a benchmark strategy of decennial colonoscopy. For an individual at average risk of colorectal cancer who was risk neutral with respect to screening complications (and therefore was willing to undergo screening if it would actuarially increase life expectancy), the model predicted that he or she would choose colonoscopy every 10 years, from age 53 to 73 years, consistent with national guidelines. For a similar individual who was moderately averse to screening complications risk (and therefore required a greater increase in life expectancy to accept potential risks of colonoscopy), the model predicted that he or she would prefer flexible sigmoidoscopy every 12 years with annual stool-based testing, with 93% of the life expectancy benefit of decennial colonoscopy. For an individual with higher risk aversion, the model predicted that he or she would prefer 2 lifetime flexible sigmoidoscopies, 20 years apart, with 70% of the life expectancy benefit of decennial colonoscopy. Mathematical models may formalize how individuals with different risk attitudes choose between various guideline-recommended colorectal cancer screening strategies.
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Wu, Yazhou; Zhang, Ling; Yuan, Xiaoyan; Wu, Yamin; Yi, Dong
2011-04-01
The objective of this study is to investigate the risk factors of stroke in a community in Chongqing by setting quantitative criteria for determining the risk factors of stroke. Thus, high-risk individuals can be identified and laid a foundation for predicting individual risk of stroke. 1,034 cases with 1:2 matched controls (2,068) were chosen from five communities in Chongqing including Shapingba, Xiaolongkan, Tianxingqiao, Yubei Road and Ciqikou. Participants were interviewed with a uniform questionnaire. The risk factors of stroke and the odds ratios of risk factors were analyzed with a logistic regression model, and risk exposure factors of different levels were converted into risk scores using statistical models. For men, ten risk factors including hypertension (5.728), family history of stroke (4.599), and coronary heart disease (5.404), among others, were entered into the main effect model. For women, 11 risk factors included hypertension (5.270), family history of stroke (4.866), hyperlipidemia (4.346), among others. The related risk scores were added to obtain a combined risk score to predict the individual's risk of stoke in the future. An individual health risk appraisal model of stroke, which was applicable to individuals of different gender, age, health behavior, disease and family history, was established. In conclusion, personal diseases including hypertension, diabetes mellitus, etc., were very important to the prevalence of stoke. The prevalence of stroke can be effectively reduced by changing unhealthy lifestyles and curing the positive individual disease. The study lays a foundation for health education to persuade people to change their unhealthy lifestyles or behaviors, and could be used in community health services.
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Life expectancy inequalities in the elderly by socioeconomic status: evidence from Italy.
Lallo, Carlo; Raitano, Michele
2018-04-12
Life expectancy considerably increased in most developed countries during the twentieth century. However, the increase in longevity is neither uniform nor random across individuals belonging to various socioeconomic groups. From an economic policy perspective, the difference in mortality by socioeconomic conditions challenges the fairness of the social security systems. We focus on the case of Italy and aim at measuring differences in longevity at older ages by individuals belonging to different socioeconomic groups, also in order to assess the effective fairness of the Italian public pension system, which is based on a notional defined contribution (NDC) benefit computation formula, whose rules do not take into account individual heterogeneity in expected longevity. We use a longitudinal dataset that matches survey data on individual features recorded in the Italian module of the EU-SILC, with information on the whole working life and until death collected in the administrative archives managed by the Italian National Social Security Institute. In more detail, we follow until 2009 a sample of 11,281 individuals aged at least 60 in 2005. We use survival analysis and measure the influence of a number of events experienced in the labor market and individual characteristics on mortality. Furthermore, through Kaplan-Meier simulations of hypothetical social groups, adjusted by a Brass relational model, we estimate and compare differences in life expectancy of individuals belonging to different socioeconomic groups. Our findings confirm that socioeconomic status strongly predicts life expectancy even in old age. All estimated models show that the prevalent type of working activity before retirement is significantly associated with the risk of death, even when controlling for dozens of variables as proxies of individual demographic and socioeconomic characteristics. The risk of death for self-employed individuals is 26% lower than that of employees, and life expectancy at 60 differs by five years between individuals with opposite socioeconomic statuses. Our study is the first that links results based on a micro survival analysis on subgroups of the elderly population with results related to the entire Italian population. The extreme differences in mortality risks by socioeconomic status found in our study confirm the existence of large health inequalities and strongly question the fairness of the Italian public pension system.
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From Predictive Models to Instructional Policies
ERIC Educational Resources Information Center
Rollinson, Joseph; Brunskill, Emma
2015-01-01
At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…
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James, Andrew I. W.; Böhnke, Jan R.; Young, Andrew W.; Lewis, Gary J.
2015-01-01
Understanding the underpinnings of behavioural disturbances following brain injury is of considerable importance, but little at present is known about the relationships between different types of behavioural disturbances. Here, we take a novel approach to this issue by using confirmatory factor analysis to elucidate the architecture of verbal aggression, physical aggression and inappropriate sexual behaviour using systematic records made across an eight-week observation period for a large sample (n = 301) of individuals with a range of brain injuries. This approach offers a powerful test of the architecture of these behavioural disturbances by testing the fit between observed behaviours and different theoretical models. We chose models that reflected alternative theoretical perspectives based on generalized disinhibition (Model 1), a difference between aggression and inappropriate sexual behaviour (Model 2), or on the idea that verbal aggression, physical aggression and inappropriate sexual behaviour reflect broadly distinct but correlated clinical phenomena (Model 3). Model 3 provided the best fit to the data indicating that these behaviours can be viewed as distinct, but with substantial overlap. These data are important both for developing models concerning the architecture of behaviour as well as for clinical management in individuals with brain injury. PMID:26136449
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Information spreading dynamics in hypernetworks
NASA Astrophysics Data System (ADS)
Suo, Qi; Guo, Jin-Li; Shen, Ai-Zhong
2018-04-01
Contact pattern and spreading strategy fundamentally influence the spread of information. Current mathematical methods largely assume that contacts between individuals are fixed by networks. In fact, individuals are affected by all his/her neighbors in different social relationships. Here, we develop a mathematical approach to depict the information spreading process in hypernetworks. Each individual is viewed as a node, and each social relationship containing the individual is viewed as a hyperedge. Based on SIS epidemic model, we construct two spreading models. One model is based on global transmission, corresponding to RP strategy. The other is based on local transmission, corresponding to CP strategy. These models can degenerate into complex network models with a special parameter. Thus hypernetwork models extend the traditional models and are more realistic. Further, we discuss the impact of parameters including structure parameters of hypernetwork, spreading rate, recovering rate as well as information seed on the models. Propagation time and density of informed nodes can reveal the overall trend of information dissemination. Comparing these two models, we find out that there is no spreading threshold in RP, while there exists a spreading threshold in CP. The RP strategy induces a broader and faster information spreading process under the same parameters.
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A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Shengzhi; Ming, Bo; Huang, Qiang
It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four orecastingmore » models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.« less
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Evans, Nathan J; Steyvers, Mark; Brown, Scott D
2018-06-05
Understanding individual differences in cognitive performance is an important part of understanding how variations in underlying cognitive processes can result in variations in task performance. However, the exploration of individual differences in the components of the decision process-such as cognitive processing speed, response caution, and motor execution speed-in previous research has been limited. Here, we assess the heritability of the components of the decision process, with heritability having been a common aspect of individual differences research within other areas of cognition. Importantly, a limitation of previous work on cognitive heritability is the underlying assumption that variability in response times solely reflects variability in the speed of cognitive processing. This assumption has been problematic in other domains, due to the confounding effects of caution and motor execution speed on observed response times. We extend a cognitive model of decision-making to account for relatedness structure in a twin study paradigm. This approach can separately quantify different contributions to the heritability of response time. Using data from the Human Connectome Project, we find strong evidence for the heritability of response caution, and more ambiguous evidence for the heritability of cognitive processing speed and motor execution speed. Our study suggests that the assumption made in previous studies-that the heritability of cognitive ability is based on cognitive processing speed-may be incorrect. More generally, our methodology provides a useful avenue for future research in complex data that aims to analyze cognitive traits across different sources of related data, whether the relation is between people, tasks, experimental phases, or methods of measurement. © 2018 Cognitive Science Society, Inc.
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Plant interactions alter the predictions of metabolic scaling theory.
Lin, Yue; Berger, Uta; Grimm, Volker; Huth, Franka; Weiner, Jacob
2013-01-01
Metabolic scaling theory (MST) is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of -4/3 between mean individual biomass and density during density-dependent mortality (self-thinning). Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms' internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric), and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than -4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.
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Mattson-Prince, J
1997-05-01
Two groups of individuals with high level tetraplegia (C1-4) were compared with respect to the model of personal care assistance used. The study was undertaken to determine whether a finite population with severe disability had differences in health status, costs and perceived quality of life, relative to whether they used agencies for their care, or hired, trained and reimbursed care givers independently. A survey, which included demographics as well as portions of RAND-36, LSI-A, PIP, PASI and CHART was used. Telephone interviews were held with 29 individuals who received their care through an agency and 42 who managed care independently. Chi square, 't'-tests, and multiple regression analysis were used to control for potentially confounding group differences. The self-managed group demonstrated significantly better health outcomes, with fewer re-hospitalizations for preventable complications. They experienced better life satisfaction and significantly lower costs. Although those who used an independent model of care-giving received significantly more hours of paid assistance, the average annual cost of care was significantly lower for each individual. In addition to reducing the financial burden on the individual and society, self-managed care seemed to diminish the emotional burden borne by these individuals.
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Combined group and individual model for postbariatric surgery follow-up care.
Lorentz, Paul A; Swain, James M; Gall, Margaret M; Collazo-Clavell, Maria L
2012-01-01
The prevalence of bariatric surgery in the United States has increased significantly during the past decade, increasing the number of patients requiring postbariatric surgery follow-up care. Our objective was to develop and implement an efficient, financially viable, postbariatric surgery practice model that would be acceptable to patients. The setting was the Mayo Clinic (Rochester, MN). By monitoring the attendance rates and using patient surveys, we tested patient acceptance of a new, shared medical appointment practice model in the care of postbariatric surgery patients. Efficiency was assessed by comparing differences in time per patient and total provider time required between the former and new care models. Individual-only patient/provider visits were replaced by combined group and individual visits (CGV). Our CGV model was well-attended and accepted. The patient attendance rate was >90% at all postoperative follow-up points. Furthermore, 83%, 85.2%, and 75.7% of the 3-, 6-, and 12-month postbariatric surgery patients, respectively, responded that they would not prefer to have only individual visits with their healthcare providers. The CGV model also resulted in greater time efficiency and cost reduction. On average, 5 patients were seen within 4.9 provider hours compared with 10.4 provider hours with the individual-only patient/provider visit model. Furthermore, the average billable charge for the CGV model's group medical nutrition therapy was 50-64% less than the equivalent individual medical nutrition therapy used in the individual-only patient/provider visit model. Shared medical appointments have a valuable role in the care of the postbariatric surgery population, offering a time- and cost-effective model for healthcare provision that is well-accepted by patients. Copyright © 2012 American Society for Metabolic and Bariatric Surgery. Published by Elsevier Inc. All rights reserved.
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Murray, Alison; Montgomery, Jana E; Chang, Hong; Rogers, William H; Inui, Thomas; Safran, Dana Gelb
2001-01-01
OBJECTIVE To examine the differences in physician satisfaction associated with open- versus closed-model practice settings and to evaluate changes in physician satisfaction between 1986 and 1997. Open-model practices refer to those in which physicians accept patients from multiple health plans and insurers (i.e., do not have an exclusive arrangement with any single health plan). Closed-model practices refer to those wherein physicians have an exclusive relationship with a single health plan (i.e., staff- or group-model HMO). DESIGN Two cross-sectional surveys of physicians; one conducted in 1986 (Medical Outcomes Study) and one conducted in 1997 (Study of Primary Care Performance in Massachusetts). SETTING Primary care practices in Massachusetts. PARTICIPANTS General internists and family practitioners in Massachusetts. MEASUREMENTS Seven measures of physician satisfaction, including satisfaction with quality of care, the potential to achieve professional goals, time spent with individual patients, total earnings from practice, degree of personal autonomy, leisure time, and incentives for high quality. RESULTS Physicians in open- versus closed-model practices differed significantly in several aspects of their professional satisfaction. In 1997, open-model physicians were less satisfied than closed-model physicians with their total earnings, leisure time, and incentives for high quality. Open-model physicians reported significantly more difficulty with authorization procedures and reported more denials for care. Overall, physicians in 1997 were less satisfied in every aspect of their professional life than 1986 physicians. Differences were significant in three areas: time spent with individual patients, autonomy, and leisure time (P ≤ .05). Among open-model physicians, satisfaction with autonomy and time with individual patients were significantly lower in 1997 than 1986 (P ≤ .01). Among closed-model physicians, satisfaction with total earnings and with potential to achieve professional goals were significantly lower in 1997 than in 1986 (P ≤ .01). CONCLUSIONS This study finds that the state of physician satisfaction in Massachusetts is extremely low, with the majority of physicians dissatisfied with the amount of time they have with individual patients, their leisure time, and their incentives for high quality. Satisfaction with most areas of practice declined significantly between 1986 and 1997. Open-model physicians were less satisfied than closed-model physicians in most aspects of practices.
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Wright, Aidan G. C.; Beltz, Adriene M.; Gates, Kathleen M.; Molenaar, Peter C. M.; Simms, Leonard J.
2015-01-01
Psychiatric diagnostic covariation suggests that the underlying structure of psychopathology is not one of circumscribed disorders. Quantitative modeling of individual differences in diagnostic patterns has uncovered several broad domains of mental disorder liability, of which the Internalizing and Externalizing spectra have garnered the greatest support. These dimensions have generally been estimated from lifetime or past-year comorbidity patters, which are distal from the covariation of symptoms and maladaptive behavior that ebb and flow in daily life. In this study, structural models are applied to daily diary data (Median = 94 days) of maladaptive behaviors collected from a sample (N = 101) of individuals diagnosed with personality disorders (PDs). Using multilevel and unified structural equation modeling, between-person, within-person, and person-specific structures were estimated from 16 behaviors that are encompassed by the Internalizing and Externalizing spectra. At the between-person level (i.e., individual differences in average endorsement across days) we found support for a two-factor Internalizing–Externalizing model, which exhibits significant associations with corresponding diagnostic spectra. At the within-person level (i.e., dynamic covariation among daily behavior pooled across individuals) we found support for a more differentiated, four-factor, Negative Affect-Detachment-Hostility-Disinhibition structure. Finally, we demonstrate that the person-specific structures of associations between these four domains are highly idiosyncratic. PMID:26732546
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Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease.
Lin, Qi; Rosenberg, Monica D; Yoo, Kwangsun; Hsu, Tiffany W; O'Connell, Thomas P; Chun, Marvin M
2018-01-01
Resting-state functional connectivity (rs-FC) is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11) scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV) significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.
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Silventoinen, Karri; Jelenkovic, Aline; Latvala, Antti; Sund, Reijo; Yokoyama, Yoshie; Ullemar, Vilhelmina; Almqvist, Catarina; Derom, Catherine A; Vlietinck, Robert F; Loos, Ruth J F; Kandler, Christian; Honda, Chika; Inui, Fujio; Iwatani, Yoshinori; Watanabe, Mikio; Rebato, Esther; Stazi, Maria A; Fagnani, Corrado; Brescianini, Sonia; Hur, Yoon-Mi; Jeong, Hoe-Uk; Cutler, Tessa L; Hopper, John L; Busjahn, Andreas; Saudino, Kimberly J; Ji, Fuling; Ning, Feng; Pang, Zengchang; Rose, Richard J; Koskenvuo, Markku; Heikkilä, Kauko; Cozen, Wendy; Hwang, Amie E; Mack, Thomas M; Siribaddana, Sisira H; Hotopf, Matthew; Sumathipala, Athula; Rijsdijk, Fruhling; Sung, Joohon; Kim, Jina; Lee, Jooyeon; Lee, Sooji; Nelson, Tracy L; Whitfield, Keith E; Tan, Qihua; Zhang, Dongfeng; Llewellyn, Clare H; Fisher, Abigail; Burt, S Alexandra; Klump, Kelly L; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Medland, Sarah E; Martin, Nicholas G; Montgomery, Grant W; Magnusson, Patrik K E; Pedersen, Nancy L; Dahl Aslan, Anna K; Corley, Robin P; Huibregtse, Brooke M; Öncel, Sevgi Y; Aliev, Fazil; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Willemsen, Gonneke; Bartels, Meike; van Beijsterveldt, Catharina E M; Silberg, Judy L; Eaves, Lindon J; Maes, Hermine H; Harris, Jennifer R; Brandt, Ingunn; Nilsen, Thomas S; Rasmussen, Finn; Tynelius, Per; Baker, Laura A; Tuvblad, Catherine; Ordoñana, Juan R; Sánchez-Romera, Juan F; Colodro-Conde, Lucia; Gatz, Margaret; Butler, David A; Lichtenstein, Paul; Goldberg, Jack H; Harden, K Paige; Tucker-Drob, Elliot M; Duncan, Glen E; Buchwald, Dedra; Tarnoki, Adam D; Tarnoki, David L; Franz, Carol E; Kremen, William S; Lyons, Michael J; Maia, José A; Freitas, Duarte L; Turkheimer, Eric; Sørensen, Thorkild I A; Boomsma, Dorret I; Kaprio, Jaakko
2017-10-01
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990-1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
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A mathematical model of medial consonant identification by cochlear implant users.
Svirsky, Mario A; Sagi, Elad; Meyer, Ted A; Kaiser, Adam R; Teoh, Su Wooi
2011-04-01
The multidimensional phoneme identification model is applied to consonant confusion matrices obtained from 28 postlingually deafened cochlear implant users. This model predicts consonant matrices based on these subjects' ability to discriminate a set of postulated spectral, temporal, and amplitude speech cues as presented to them by their device. The model produced confusion matrices that matched many aspects of individual subjects' consonant matrices, including information transfer for the voicing, manner, and place features, despite individual differences in age at implantation, implant experience, device and stimulation strategy used, as well as overall consonant identification level. The model was able to match the general pattern of errors between consonants, but not the full complexity of all consonant errors made by each individual. The present study represents an important first step in developing a model that can be used to test specific hypotheses about the mechanisms cochlear implant users employ to understand speech.
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A mathematical model of medial consonant identification by cochlear implant users
Svirsky, Mario A.; Sagi, Elad; Meyer, Ted A.; Kaiser, Adam R.; Teoh, Su Wooi
2011-01-01
The multidimensional phoneme identification model is applied to consonant confusion matrices obtained from 28 postlingually deafened cochlear implant users. This model predicts consonant matrices based on these subjects’ ability to discriminate a set of postulated spectral, temporal, and amplitude speech cues as presented to them by their device. The model produced confusion matrices that matched many aspects of individual subjects’ consonant matrices, including information transfer for the voicing, manner, and place features, despite individual differences in age at implantation, implant experience, device and stimulation strategy used, as well as overall consonant identification level. The model was able to match the general pattern of errors between consonants, but not the full complexity of all consonant errors made by each individual. The present study represents an important first step in developing a model that can be used to test specific hypotheses about the mechanisms cochlear implant users employ to understand speech. PMID:21476674
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Lau-Walker, Margaret
2006-02-01
This paper analyses the two prominent psychological theories of patient response--illness representation and self-efficacy--and explore the possibilities of the development of a conceptual individualized care model that would make use of both theories. Analysis of the literature established common themes that were used as the basis to form a conceptual framework intended to assist in the joint application of these theories to therapeutic settings. Both theories emphasize personal experience, pre-construction of self, individual response to illness and treatment, and that the patients' beliefs are more influential in their recovery than the severity of the illness. Where the theories are most divergent is their application to therapeutic interventions, which reflects the different sources of influence that each theory emphasizes. Based on their similarities and differences it is possible to integrate the two theories into a conceptual care model. The Interactive Care Model combines both theories of patient response and provides an explicit framework for further research into the design of effective therapeutic interventions in rehabilitation care.
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Breen, Michael S.; Long, Thomas C.; Schultz, Bradley D.; Crooks, James; Breen, Miyuki; Langstaff, John E.; Isaacs, Kristin K.; Tan, Yu-Mei; Williams, Ronald W.; Cao, Ye; Geller, Andrew M.; Devlin, Robert B.; Batterman, Stuart A.; Buckley, Timothy J.
2014-01-01
A critical aspect of air pollution exposure assessment is the estimation of the time spent by individuals in various microenvironments (ME). Accounting for the time spent in different ME with different pollutant concentrations can reduce exposure misclassifications, while failure to do so can add uncertainty and bias to risk estimates. In this study, a classification model, called MicroTrac, was developed to estimate time of day and duration spent in eight ME (indoors and outdoors at home, work, school; inside vehicles; other locations) from global positioning system (GPS) data and geocoded building boundaries. Based on a panel study, MicroTrac estimates were compared with 24-h diary data from nine participants, with corresponding GPS data and building boundaries of home, school, and work. MicroTrac correctly classified the ME for 99.5% of the daily time spent by the participants. The capability of MicroTrac could help to reduce the time–location uncertainty in air pollution exposure models and exposure metrics for individuals in health studies. PMID:24619294
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Assimilation and Individual Differences in Emotion: The Dynamics of Anger and Approach Motivation.
Lechuga, Julia; Fernandez, Norma P
2011-03-01
Individuals who cross cultural boundaries face many challenges when trying to adapt to a receiving culture. Adaptation challenges such as learning to maneuver across societal domains may become increasingly complex if structural level factors such as discrimination are present. Researchers have conceptualized acculturation as a relatively autonomous decision indicating that four acculturation strategies exist: assimilation, separation, integration, and marginalization. Moreover, researchers have also long debated the link between acculturation strategy, adaptation hassles and negative health outcomes. However, models seeking to explain how individual difference and structural level variables may influence each other and subsequently influence acculturation and adaptation are needed. The purpose of this study is to lay the foundation for the conceptualization of such a model. We propose that temperamental predispositions to negative emotionality, anger, and impulsivity may highlight discrimination which in turn may lead to increases in acculturative stress and negative markers of psychosocial well-being. We used SEM to test our hypothesized model. Results supported a modified model. Implications for the measurement of adaptation and interventions are discussed.
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Assimilation and Individual Differences in Emotion: The Dynamics of Anger and Approach Motivation
Lechuga, Julia; Fernandez, Norma P.
2011-01-01
Individuals who cross cultural boundaries face many challenges when trying to adapt to a receiving culture. Adaptation challenges such as learning to maneuver across societal domains may become increasingly complex if structural level factors such as discrimination are present. Researchers have conceptualized acculturation as a relatively autonomous decision indicating that four acculturation strategies exist: assimilation, separation, integration, and marginalization. Moreover, researchers have also long debated the link between acculturation strategy, adaptation hassles and negative health outcomes. However, models seeking to explain how individual difference and structural level variables may influence each other and subsequently influence acculturation and adaptation are needed. The purpose of this study is to lay the foundation for the conceptualization of such a model. We propose that temperamental predispositions to negative emotionality, anger, and impulsivity may highlight discrimination which in turn may lead to increases in acculturative stress and negative markers of psychosocial well-being. We used SEM to test our hypothesized model. Results supported a modified model. Implications for the measurement of adaptation and interventions are discussed. PMID:21625350
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A Multicultural Feminist Model of Mentoring
ERIC Educational Resources Information Center
Benishek, Lois A.; Bieschke, Kathleen J.; Park, Jeeseon; Slattery, Suzanne M.
2004-01-01
This article identifies ways professionals perpetuate misperceptions about mentoring when engaging in traditional methods of mentoring. Fassinger's feminist model of mentoring is expanded by incorporating multicultural elements into the model. The authors' definition of "multiculturalism" is inclusive of individuals from different races,…
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Measuring individual differences in responses to date-rape vignettes using latent variable models.
Tuliao, Antover P; Hoffman, Lesa; McChargue, Dennis E
2017-01-01
Vignette methodology can be a flexible and powerful way to examine individual differences in response to dangerous real-life scenarios. However, most studies underutilize the usefulness of such methodology by analyzing only one outcome, which limits the ability to track event-related changes (e.g., vacillation in risk perception). The current study was designed to illustrate the dynamic influence of risk perception on exit point from a date-rape vignette. Our primary goal was to provide an illustrative example of how to use latent variable models for vignette methodology, including latent growth curve modeling with piecewise slopes, as well as latent variable measurement models. Through the combination of a step-by-step exposition in this text and corresponding model syntax available electronically, we detail an alternative statistical "blueprint" to enhance future violence research efforts using vignette methodology. Aggr. Behav. 43:60-73, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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Implementation science: a role for parallel dual processing models of reasoning?
Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J
2006-01-01
Background A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Discussion Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. Summary It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice. PMID:16725023
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Implementation science: a role for parallel dual processing models of reasoning?
Sladek, Ruth M; Phillips, Paddy A; Bond, Malcolm J
2006-05-25
A better theoretical base for understanding professional behaviour change is needed to support evidence-based changes in medical practice. Traditionally strategies to encourage changes in clinical practices have been guided empirically, without explicit consideration of underlying theoretical rationales for such strategies. This paper considers a theoretical framework for reasoning from within psychology for identifying individual differences in cognitive processing between doctors that could moderate the decision to incorporate new evidence into their clinical decision-making. Parallel dual processing models of reasoning posit two cognitive modes of information processing that are in constant operation as humans reason. One mode has been described as experiential, fast and heuristic; the other as rational, conscious and rule based. Within such models, the uptake of new research evidence can be represented by the latter mode; it is reflective, explicit and intentional. On the other hand, well practiced clinical judgments can be positioned in the experiential mode, being automatic, reflexive and swift. Research suggests that individual differences between people in both cognitive capacity (e.g., intelligence) and cognitive processing (e.g., thinking styles) influence how both reasoning modes interact. This being so, it is proposed that these same differences between doctors may moderate the uptake of new research evidence. Such dispositional characteristics have largely been ignored in research investigating effective strategies in implementing research evidence. Whilst medical decision-making occurs in a complex social environment with multiple influences and decision makers, it remains true that an individual doctor's judgment still retains a key position in terms of diagnostic and treatment decisions for individual patients. This paper argues therefore, that individual differences between doctors in terms of reasoning are important considerations in any discussion relating to changing clinical practice. It is imperative that change strategies in healthcare consider relevant theoretical frameworks from other disciplines such as psychology. Generic dual processing models of reasoning are proposed as potentially useful in identifying factors within doctors that may moderate their individual uptake of evidence into clinical decision-making. Such factors can then inform strategies to change practice.
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Watts, Amber; Walters, Ryan W; Hoffman, Lesa; Templin, Jonathan
2016-01-01
Physical activity shows promise for protection against cognitive decline in older adults with and without Alzheimer's disease (AD). To better understand barriers to adoption of physical activity in this population, a clear understanding of daily and weekly activity patterns is needed. Most accelerometry studies report average physical activity over an entire wear period without considering the potential importance of the variability of physical activity. This study evaluated individual differences in the amount and intra-individual variability of physical activity and determined whether these differences could be predicted by AD status, day of wear, age, gender, education, and cardiorespiratory capacity. Physical activity was measured via accelerometry (Actigraph GT3X+) over one week in 86 older adults with and without AD (n = 33 and n = 53, respectively). Mixed-effects location-scale models were estimated to evaluate and predict individual differences in the amount and intra-individual variability of physical activity. Results indicated that compared to controls, participants with AD averaged 21% less activity, but averaged non-significantly greater intra-individual variability. Women and men averaged similar amounts of physical activity, but women were significantly less variable. The amount of physical activity differed significantly across days of wear. Increased cardiorespiratory capacity was associated with greater average amounts of physical activity. Investigation of individual differences in the amount and intra-individual variability of physical activity provided insight into differences by AD status, days of monitor wear, gender, and cardiovascular capacity. All individuals regardless of AD status were equally consistent in their physical activity, which may have been due to a highly sedentary sample and/or the early disease stage of those participants with AD. These results highlight the value of considering individual differences in both the amount and intra-individual variability of physical activity.
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van der Maas, Han L J; Molenaar, Dylan; Maris, Gunter; Kievit, Rogier A; Borsboom, Denny
2011-04-01
This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line of reasoning, we discuss the appropriateness of IRT for measuring abilities and bipolar traits, such as pro versus contra attitudes. Surprisingly, if a diffusion model underlies the response processes, IRT models are appropriate for bipolar traits but not for ability tests. A reconsideration of the concept of ability that is appropriate for such situations leads to a new item response model for accuracy and speed based on the idea that ability has a natural zero point. The model implies fundamentally new ways to think about guessing, response speed, and person fit in IRT. We discuss the relation between this model and existing models as well as implications for psychology and psychometrics. 2011 APA, all rights reserved
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Driving-forces model on individual behavior in scenarios considering moving threat agents
NASA Astrophysics Data System (ADS)
Li, Shuying; Zhuang, Jun; Shen, Shifei; Wang, Jia
2017-09-01
The individual behavior model is a contributory factor to improve the accuracy of agent-based simulation in different scenarios. However, few studies have considered moving threat agents, which often occur in terrorist attacks caused by attackers with close-range weapons (e.g., sword, stick). At the same time, many existing behavior models lack validation from cases or experiments. This paper builds a new individual behavior model based on seven behavioral hypotheses. The driving-forces model is an extension of the classical social force model considering scenarios including moving threat agents. An experiment was conducted to validate the key components of the model. Then the model is compared with an advanced Elliptical Specification II social force model, by calculating the fitting errors between the simulated and experimental trajectories, and being applied to simulate a specific circumstance. Our results show that the driving-forces model reduced the fitting error by an average of 33.9% and the standard deviation by an average of 44.5%, which indicates the accuracy and stability of the model in the studied situation. The new driving-forces model could be used to simulate individual behavior when analyzing the risk of specific scenarios using agent-based simulation methods, such as risk analysis of close-range terrorist attacks in public places.
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Movement behavior explains genetic differentiation in American black bears
Samuel A Cushman; Jesse S. Lewis
2010-01-01
Individual-based landscape genetic analyses provide empirically based models of gene flow. It would be valuable to verify the predictions of these models using independent data of a different type. Analyses using different data sources that produce consistent results provide strong support for the generality of the findings. Mating and dispersal movements are the...
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The Role of IT Literacy in Defining Digital Divide Policy Needs
ERIC Educational Resources Information Center
Ferro, Enrico; Helbig, Natalie C.; Gil-Garcia, J. Ramon
2011-01-01
This article expands our current understanding of the digital divide by examining differences in individuals' IT skills acquisition. In the last two decades scholars have gradually refined the conceptualization of the digital divide, moving from a dichotomous model mainly based on access, to a multidimensional model accounting for differences in…
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Brito-Rocha, E; Schilling, A C; Dos Anjos, L; Piotto, D; Dalmolin, A C; Mielke, M S
2016-01-01
Individual leaf area (LA) is a key variable in studies of tree ecophysiology because it directly influences light interception, photosynthesis and evapotranspiration of adult trees and seedlings. We analyzed the leaf dimensions (length - L and width - W) of seedlings and adults of seven Neotropical rainforest tree species (Brosimum rubescens, Manilkara maxima, Pouteria caimito, Pouteria torta, Psidium cattleyanum, Symphonia globulifera and Tabebuia stenocalyx) with the objective to test the feasibility of single regression models to estimate LA of both adults and seedlings. In southern Bahia, Brazil, a first set of data was collected between March and October 2012. From the seven species analyzed, only two (P. cattleyanum and T. stenocalyx) had very similar relationships between LW and LA in both ontogenetic stages. For these two species, a second set of data was collected in August 2014, in order to validate the single models encompassing adult and seedlings. Our results show the possibility of development of models for predicting individual leaf area encompassing different ontogenetic stages for tropical tree species. The development of these models was more dependent on the species than the differences in leaf size between seedlings and adults.
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Patterns of threshold evolution in polyphenic insects under different developmental models.
Tomkins, Joseph L; Moczek, Armin P
2009-02-01
Two hypotheses address the evolution of polyphenic traits in insects. Under the developmental reprogramming model, individuals exceeding a threshold follow a different developmental pathway from individuals below the threshold. This decoupling is thought to free selection to independently hone alternative morphologies, increasing phenotypic plasticity and morphological diversity. Under the alternative model, extreme positive allometry explains the existence of alternative phenotypes and divergent phenotypes are developmentally coupled by a continuous reaction norm, such that selection on either morph acts on both. We test the hypothesis that continuous reaction norm polyphenisms, evolve through changes in the allometric parameters of even the smallest males with minimal trait expression, whereas threshold polyphenisms evolve independent of the allometric parameters of individuals below the threshold. We compare two polyphenic species; the dung beetle Onthophagus taurus, whose allometry has been modeled both as a threshold polyphenism and a continuous reaction norm and the earwig Forficula auricularia, whose allometry is best modeled with a discontinuous threshold. We find that across populations of both species, variation in forceps or horn allometry in minor males are correlated to the population's threshold. These findings suggest that regardless of developmental mode, alternative morphs do not evolve independently of one another.
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Galic, Nika; Sullivan, Lauren L; Grimm, Volker; Forbes, Valery E
2018-04-01
Ecosystems are exposed to multiple stressors which can compromise functioning and service delivery. These stressors often co-occur and interact in different ways which are not yet fully understood. Here, we applied a population model representing a freshwater amphipod feeding on leaf litter in forested streams. We simulated impacts of hypothetical stressors, individually and in pairwise combinations that target the individuals' feeding, maintenance, growth and reproduction. Impacts were quantified by examining responses at three levels of biological organisation: individual-level body sizes and cumulative reproduction, population-level abundance and biomass and ecosystem-level leaf litter decomposition. Interactive effects of multiple stressors at the individual level were mostly antagonistic, that is, less negative than expected. Most population- and ecosystem-level responses to multiple stressors were stronger than expected from an additive model, that is, synergistic. Our results suggest that across levels of biological organisation responses to multiple stressors are rarely only additive. We suggest methods for efficiently quantifying impacts of multiple stressors at different levels of biological organisation. © 2018 John Wiley & Sons Ltd/CNRS.
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Consistent individual differences in human social learning strategies.
Molleman, Lucas; van den Berg, Pieter; Weissing, Franz J
2014-04-04
Social learning has allowed humans to build up extensive cultural repertoires, enabling them to adapt to a wide variety of environmental and social conditions. However, it is unclear which social learning strategies people use, especially in social contexts where their payoffs depend on the behaviour of others. Here we show experimentally that individuals differ in their social learning strategies and that they tend to employ the same learning strategy irrespective of the interaction context. Payoff-based learners focus on their peers' success, while decision-based learners disregard payoffs and exclusively focus on their peers' past behaviour. These individual differences may be of considerable importance for cultural evolution. By means of a simple model, we demonstrate that groups harbouring individuals with different learning strategies may be faster in adopting technological innovations and can be more efficient through successful role differentiation. Our study highlights the importance of individual variation for human interactions and sheds new light on the dynamics of cultural evolution.
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This Gun for Hire: The Fascination of Movie Assassins
ERIC Educational Resources Information Center
Beck, Bernard
2005-01-01
The main characters in a movie can serve individuals in many different ways, but the usual way is to appear good. In whatever form, stories of individuals are a useful part of popular culture when they offer models of how individuals might save themselves or be saved. However, there are other ways. Villains, monsters, and enemies can be at the…
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Fluid Intelligence as a Predictor of Learning: A Longitudinal Multilevel Approach Applied to Math
ERIC Educational Resources Information Center
Primi, Ricardo; Ferrao, Maria Eugenia; Almeida, Leandro S.
2010-01-01
The association between fluid intelligence and inter-individual differences was investigated using multilevel growth curve modeling applied to data measuring intra-individual improvement on math achievement tests. A sample of 166 students (88 boys and 78 girls), ranging in age from 11 to 14 (M = 12.3, SD = 0.64), was tested. These individuals took…
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Fusar-Poli, Paolo; Werbeloff, Nomi; Rutigliano, Grazia; Oliver, Dominic; Davies, Cathy; Stahl, Daniel; McGuire, Philip; Osborn, David
2018-06-12
The benefits of indicated primary prevention among individuals at Clinical High Risk for Psychosis (CHR-P) are limited by the difficulty in detecting these individuals. To overcome this problem, a transdiagnostic, clinically based, individualized risk calculator has recently been developed and subjected to a first external validation in 2 different catchment areas of the South London and Maudsley (SLaM) NHS Trust. Second external validation of real world, real-time electronic clinical register-based cohort study. All individuals who received a first ICD-10 index diagnosis of nonorganic and nonpsychotic mental disorder within the Camden and Islington (C&I) NHS Trust between 2009 and 2016 were included. The model previously validated included age, gender, ethnicity, age by gender, and ICD-10 index diagnosis to predict the development of any ICD-10 nonorganic psychosis. The model's performance was measured using Harrell's C-index. This study included a total of 13702 patients with an average age of 40 (range 16-99), 52% were female, and most were of white ethnicity (64%). There were no CHR-P or child/adolescent services in the C&I Trust. The C&I and SLaM Trust samples also differed significantly in terms of age, gender, ethnicity, and distribution of index diagnosis. Despite these significant differences, the original model retained an acceptable predictive performance (Harrell's C of 0.73), which is comparable to that of CHR-P tools currently recommended for clinical use. This risk calculator may pragmatically support an improved transdiagnostic detection of at-risk individuals and psychosis prediction even in NHS Trusts in the United Kingdom where CHR-P services are not provided.
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Barnett, Michael D; Öz, Haluk C M; Marsden, Arthur D
2018-05-01
Previous research has linked conservative political ideology with homophobia. Political ideology has also been linked to differences in moral decision-making, with research suggesting that conservatives and liberals may use different values in their moral decision-making processes. Moral foundations theory is a model of moral decision-making that proposes that individuals emphasize different domains in moral decision-making. Conservatives tend to emphasize binding foundations, while liberals tend to emphasize individualizing foundations. Utilizing large, ethnically diverse college samples, the purpose of these two cross-sectional studies (Study 1 N = 492; Study 2 N = 861) was to explore whether moral foundations mediate the relationship between political ideology and homophobia. These studies explored economic and social political ideology separately and utilized a two-factor model of moral foundations theory (individualizing and binding foundations). Results of both studies found that conservative economic and social political ideology was positively associated with homophobia. Study 1 found that both conservative economic and social political ideology had an indirect effect on homophobia through binding foundations. Study 2 found that both economic and social political ideology had an indirect effect on homophobia through both binding and individualizing foundations. Overall, the results were consistent with the notion that moral foundations may explain the relationship between political ideology and homophobia.
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Assortative social learning and its implications for human (and animal?) societies.
Katsnelson, Edith; Lotem, Arnon; Feldman, Marcus W
2014-07-01
Choosing from whom to learn is an important element of social learning. It affects learner success and the profile of behaviors in the population. Because individuals often differ in their traits and capabilities, their benefits from different behaviors may also vary. Homophily, or assortment, the tendency of individuals to interact with other individuals with similar traits, is known to affect the spread of behaviors in humans. We introduce models to study the evolution of assortative social learning (ASL), where assorting on a trait acts as an individual-specific mechanism for filtering relevant models from which to learn when that trait varies. We show that when the trait is polymorphic, ASL may maintain a stable behavioral polymorphism within a population (independently of coexistence with individual learning in a population). We explore the evolution of ASL when assortment is based on a nonheritable or partially heritable trait, and when ASL competes with different non-ASL strategies: oblique (learning from the parental generation) and vertical (learning from the parent). We suggest that the tendency to assort may be advantageous in the context of social learning, and that ASL might be an important concept for the evolutionary theory of social learning. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.
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Goldenberg, Amit; Halperin, Eran; van Zomeren, Martijn; Gross, James J
2016-05-01
Scholars interested in emotion regulation have documented the different goals and strategies individuals have for regulating their emotions. However, little attention has been paid to the regulation of group-based emotions, which are based on individuals' self-categorization as a group member and occur in response to situations perceived as relevant for that group. We propose a model for examining group-based emotion regulation that integrates intergroup emotions theory and the process model of emotion regulation. This synergy expands intergroup emotion theory by facilitating further investigation of different goals (i.e., hedonic or instrumental) and strategies (e.g., situation selection and modification strategies) used to regulate group-based emotions. It also expands emotion regulation research by emphasizing the role of self-categorization (e.g., as an individual or a group member) in the emotional process. Finally, we discuss the promise of this theoretical synergy and suggest several directions for future research on group-based emotion regulation. © 2015 by the Society for Personality and Social Psychology, Inc.
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[A Cellular Automata Model for a Community Comprising Two Plant Species of Different Growth Forms].
Frolov, P V; Zubkova, E V; Komarov, A S
2015-01-01
A cellular automata computer model for the interactions between two plant species of different growth forms--the lime hairgrass Deschampsia caespitosa (L.) P. Beauv., a sod cereal, and the moneywort Lysimachia nummularia L., a ground creeping perennial herb--is considered. Computer experiments on the self-maintenance of the populations of each species against the background of a gradual increase in the share of randomly eliminated individuals, coexistence of the populations of two species, and the effect of the phytogenous field have been conducted. As has been shown, all the studied factors determine the number of individuals and self-sustainability of the simulated populations by the degree of their impact. The limits of action have been determined for individual factors; within these limits, the specific features in plant reproduction and dispersal provide sustainable coexistence of the simulated populations. It has been demonstrated that the constructed model allows for studying the long-term developmental dynamics of the plants belonging to the selected growth forms.
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Lobréaux, Stéphane; Melodelima, Christelle
2015-02-01
We tested the use of Generalized Linear Mixed Models to detect associations between genetic loci and environmental variables, taking into account the population structure of sampled individuals. We used a simulation approach to generate datasets under demographically and selectively explicit models. These datasets were used to analyze and optimize GLMM capacity to detect the association between markers and selective coefficients as environmental data in terms of false and true positive rates. Different sampling strategies were tested, maximizing the number of populations sampled, sites sampled per population, or individuals sampled per site, and the effect of different selective intensities on the efficiency of the method was determined. Finally, we apply these models to an Arabidopsis thaliana SNP dataset from different accessions, looking for loci associated with spring minimal temperature. We identified 25 regions that exhibit unusual correlations with the climatic variable and contain genes with functions related to temperature stress. Copyright © 2014 Elsevier Inc. All rights reserved.
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Simple Model of Mating Preference and Extinction Risk
NASA Astrophysics Data System (ADS)
PȨKALSKI, Andrzej
We present a simple model of a population of individuals characterized by their genetic structure in the form of a double string of bits and the phenotype following from it. The population is living in an unchanging habitat preferring a certain type of phenotype (optimum). Individuals are unisex, however a pair is necessary for breeding. An individual rejects a mate if the latter's phenotype contains too many bad, i.e. different from the optimum, genes in the same places as the individual's. We show that such strategy, analogous to disassortative mating based on the major histocompatibility complex, avoiding inbreeding and incest, could be beneficial for the population and could reduce considerably the extinction risk, especially in small populations.
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Gavriel-Fried, Belle; Rabayov, Tal
2017-01-01
Aims: People with gambling as well as substance use problems who are exposed to public stigmatization may internalize and apply it to themselves through a mechanism known as self-stigma. This study implemented the Progressive Model for Self-Stigma which consists four sequential interrelated stages: awareness, agreement, application and harm on three groups of individuals with gambling, alcohol and other substance use problems. It explored whether the two guiding assumptions of this model (each stage is precondition for the following stage which are trickle-down in nature, and correlations between proximal stages should be larger than correlations between more distant stages) would differentiate people with gambling problems from those with alcohol and other substance use problems in terms of their patterns of self-stigma and in terms of the stages in the model. Method: 37 individuals with gambling problems, 60 with alcohol problems and 51 with drug problems who applied for treatment in rehabilitation centers in Israel in 2015–2016 were recruited. They completed the Self-stigma of Mental Illness Scale-Short Form which was adapted by changing the term “mental health” to gambling, alcohol or drugs, and the DSM-5-diagnostic criteria for gambling, alcohol or drug disorder. Results: The assumptions of the model were broadly confirmed: a repeated measures ANCOVA revealed that in all three groups there was a difference between first two stages (aware and agree) and the latter stages (apply and harm). In addition, the gambling group differed from the drug use and alcohol groups on the awareness stage: individuals with gambling problems were less likely to be aware of stigma than people with substance use or alcohol problems. Conclusion: The internalization of stigma among individuals with gambling problems tends to work in a similar way as for those with alcohol or drug problems. The differences between the gambling group and the alcohol and other substance groups at the aware stage may suggest that public stigma with regard to any given addictive disorder may be a function of the type of addiction (substance versus behavioral). PMID:28649212
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Organizational Adaptative Behavior: The Complex Perspective of Individuals-Tasks Interaction
NASA Astrophysics Data System (ADS)
Wu, Jiang; Sun, Duoyong; Hu, Bin; Zhang, Yu
Organizations with different organizational structures have different organizational behaviors when responding environmental changes. In this paper, we use a computational model to examine organizational adaptation on four dimensions: Agility, Robustness, Resilience, and Survivability. We analyze the dynamics of organizational adaptation by a simulation study from a complex perspective of the interaction between tasks and individuals in a sales enterprise. The simulation studies in different scenarios show that more flexible communication between employees and less hierarchy level with the suitable centralization can improve organizational adaptation.
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Individual Differences in Childhood Sleep Problems Predict Later Cognitive Executive Control
Friedman, Naomi P.; Corley, Robin P.; Hewitt, John K.; Wright, Kenneth P.
2009-01-01
Study Objective: To determine whether individual differences in developmental patterns of general sleep problems are associated with 3 executive function abilities—inhibiting, updating working memory, and task shifting—in late adolescence. Participants: 916 twins (465 female, 451 male) and parents from the Colorado Longitudinal Twin Study. Measurements and Results: Parents reported their children's sleep problems at ages 4 years, 5 y, 7 y, and 9–16 y based on a 7-item scale from the Child-Behavior Checklist; a subset of children (n = 568) completed laboratory assessments of executive functions at age 17. Latent variable growth curve analyses were used to model individual differences in longitudinal trajectories of childhood sleep problems. Sleep problems declined over time, with ~70% of children having ≥ 1 problem at age 4 and ~33% of children at age 16. However, significant individual differences in both the initial levels of problems (intercept) and changes across time (slope) were observed. When executive function latent variables were added to the model, the intercept did not significantly correlate with the later executive function latent variables; however, the slope variable significantly (P < 0.05) negatively correlated with inhibiting (r = −0.27) and updating (r = −0.21), but not shifting (r = −0.10) abilities. Further analyses suggested that the slope variable predicted the variance common to the 3 executive functions (r = −0.29). Conclusions: Early levels of sleep problems do not seem to have appreciable implications for later executive functioning. However, individuals whose sleep problems decrease more across time show better general executive control in late adolescence. Citation: Friedman NP; Corley RP; Hewitt JK; Wright KP. Individual differences in childhood sleep problems predict later cognitive executive control. SLEEP 2009;32(3):323-333. PMID:19294952
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Verma, Sanjeev; Singh, SP; Utreja, Ashok
2014-01-01
Aim: The aim of this study was to evaluate angulation and inclination of teeth from the study models of individuals with normal occlusion and evaluation of actual expression of torque expressed by three different bracket systems. Materials and Methods: In this study, the inclination and angulation were measured on 30 study models of North Indian individuals. A self-developed instrument (torque angle gauge) was used for the measurement. Fifteen study models were duplicated for the evaluation of torque expression in the bracket of three different manufacturers with different shape and size of bases. Results: The results give the mean, minimum and maximum, standard deviation of the normative data individually for each tooth. A significant correlation was noted in the angulation of maxillary canine and first premolar, and between premolars; and between mandibular central incisor with lateral incisor and canine, and between premolars. Conclusions: There was a highly significant correlation of teeth angulation and inclination in the maxillary and mandibular arch. Though the error in expression of torque was not significant, but it showed a large range, indicating the need to vary the position of brackets in different bracket systems for achieving optimum torque. PMID:25143932
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Muscle function may depend on model selection in forward simulation of normal walking
Xiao, Ming; Higginson, Jill S.
2008-01-01
The purpose of this study was to quantify how the predicted muscle function would change in a muscle-driven forward simulation of normal walking when changing the number of degrees of freedom in the model. Muscle function was described by individual muscle contributions to the vertical acceleration of the center of mass (COM). We built a two-dimensional (2D) sagittal plane model and a three-dimensional (3D) model in OpenSim and used both models to reproduce the same normal walking data. Perturbation analysis was applied to deduce muscle function in each model. Muscle excitations and contributions to COM support were compared between the 2D and 3D models. We found that the 2D model was able to reproduce similar joint kinematics and kinetics patterns as the 3D model. Individual muscle excitations were different for most of the hip muscles but ankle and knee muscles were able to attain similar excitations. Total induced vertical COM acceleration by muscles and gravity was the same for both models. However, individual muscle contributions to COM support varied, especially for hip muscles. Although there is currently no standard way to validate muscle function predictions, a 3D model seems to be more appropriate for estimating individual hip muscle function. PMID:18804767
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Spontaneous emergence of milling (vortex state) in a Vicsek-like model
NASA Astrophysics Data System (ADS)
Costanzo, A.; Hemelrijk, C. K.
2018-04-01
Collective motion is of interest to laymen and scientists in different fields. In groups of animals, many patterns of collective motion arise such as polarized schools and mills (i.e. circular motion). Collective motion can be generated in computational models of different degrees of complexity. In these models, moving individuals coordinate with others nearby. In the more complex models, individuals attract each other, aligning their headings, and avoiding collisions. Simpler models may include only one or two of these types of interactions. The collective pattern that interests us here is milling, which is observed in many animal species. It has been reproduced in the more complex models, but not in simpler models that are based only on alignment, such as the well-known Vicsek model. Our aim is to provide insight in the minimal conditions required for milling by making minimal modifications to the Vicsek model. Our results show that milling occurs when both the field of view and the maximal angular velocity are decreased. Remarkably, apart from milling, our minimal model also exhibits many of the other patterns of collective motion observed in animal groups.
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The Process Communication Model: Understanding Ourselves and Others.
ERIC Educational Resources Information Center
Gilbert, Michael
1996-01-01
The Process Communication Model is based on personality types (reactors, persisters, workaholics, dreamers, rebels, and promoters) denoting different sets of behaviors, perceptions, and motivators that influence individual learning and teaching styles. The model is comprehensive and process-oriented, covering interaction styles, communication…
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Manuel, D G; Ho, T H; Harper, S; Anderson, G M; Lynch, J; Rosella, L C
2014-07-01
Most individual preventive therapies potentially narrow or widen health disparities depending on the difference in community effectiveness across socioeconomic position (SEP). The equity tipping point (defined as the point at which health disparities become larger) can be calculated by varying components of community effectiveness such as baseline risk of disease, intervention coverage and/or intervention efficacy across SEP. We used a simple modelling approach to estimate the community effectiveness of diabetes prevention across SEP in Canada under different scenarios of intervention coverage. Five-year baseline diabetes risk differed between the lowest and highest income groups by 1.76%. Assuming complete coverage across all income groups, the difference was reduced to 0.90% (144 000 cases prevented) with lifestyle interventions and 1.24% (88 100 cases prevented) with pharmacotherapy. The equity tipping point was estimated to be a coverage difference of 30% for preventive interventions (100% and 70% coverage among the highest and lowest income earners, respectively). Disparities in diabetes risk could be measurably reduced if existing interventions were equally adopted across SEP. However, disparities in coverage could lead to increased inequity in risk. Simple modelling approaches can be used to examine the community effectiveness of individual preventive interventions and their potential to reduce (or increase) disparities. The equity tipping point can be used as a critical threshold for disparities analyses.
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Non-consensus Opinion Models on Complex Networks
NASA Astrophysics Data System (ADS)
Li, Qian; Braunstein, Lidia A.; Wang, Huijuan; Shao, Jia; Stanley, H. Eugene; Havlin, Shlomo
2013-04-01
Social dynamic opinion models have been widely studied to understand how interactions among individuals cause opinions to evolve. Most opinion models that utilize spin interaction models usually produce a consensus steady state in which only one opinion exists. Because in reality different opinions usually coexist, we focus on non-consensus opinion models in which above a certain threshold two opinions coexist in a stable relationship. We revisit and extend the non-consensus opinion (NCO) model introduced by Shao et al. (Phys. Rev. Lett. 103:01870, 2009). The NCO model in random networks displays a second order phase transition that belongs to regular mean field percolation and is characterized by the appearance (above a certain threshold) of a large spanning cluster of the minority opinion. We generalize the NCO model by adding a weight factor W to each individual's original opinion when determining their future opinion (NCO W model). We find that as W increases the minority opinion holders tend to form stable clusters with a smaller initial minority fraction than in the NCO model. We also revisit another non-consensus opinion model based on the NCO model, the inflexible contrarian opinion (ICO) model (Li et al. in Phys. Rev. E 84:066101, 2011), which introduces inflexible contrarians to model the competition between two opinions in a steady state. Inflexible contrarians are individuals that never change their original opinion but may influence the opinions of others. To place the inflexible contrarians in the ICO model we use two different strategies, random placement and one in which high-degree nodes are targeted. The inflexible contrarians effectively decrease the size of the largest rival-opinion cluster in both strategies, but the effect is more pronounced under the targeted method. All of the above models have previously been explored in terms of a single network, but human communities are usually interconnected, not isolated. Because opinions propagate not only within single networks but also between networks, and because the rules of opinion formation within a network may differ from those between networks, we study here the opinion dynamics in coupled networks. Each network represents a social group or community and the interdependent links joining individuals from different networks may be social ties that are unusually strong, e.g., married couples. We apply the non-consensus opinion (NCO) rule on each individual network and the global majority rule on interdependent pairs such that two interdependent agents with different opinions will, due to the influence of mass media, follow the majority opinion of the entire population. The opinion interactions within each network and the interdependent links across networks interlace periodically until a steady state is reached. We find that the interdependent links effectively force the system from a second order phase transition, which is characteristic of the NCO model on a single network, to a hybrid phase transition, i.e., a mix of second-order and abrupt jump-like transitions that ultimately becomes, as we increase the percentage of interdependent agents, a pure abrupt transition. We conclude that for the NCO model on coupled networks, interactions through interdependent links could push the non-consensus opinion model to a consensus opinion model, which mimics the reality that increased mass communication causes people to hold opinions that are increasingly similar. We also find that the effect of interdependent links is more pronounced in interdependent scale free networks than in interdependent Erdős Rényi networks.
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Street, Nichola; Forsythe, Alexandra M.; Reilly, Ronan; Taylor, Richard; Helmy, Mai S.
2016-01-01
Fractal patterns offer one way to represent the rough complexity of the natural world. Whilst they dominate many of our visual experiences in nature, little large-scale perceptual research has been done to explore how we respond aesthetically to these patterns. Previous research (Taylor et al., 2011) suggests that the fractal patterns with mid-range fractal dimensions (FDs) have universal aesthetic appeal. Perceptual and aesthetic responses to visual complexity have been more varied with findings suggesting both linear (Forsythe et al., 2011) and curvilinear (Berlyne, 1970) relationships. Individual differences have been found to account for many of the differences we see in aesthetic responses but some, such as culture, have received little attention within the fractal and complexity research fields. This two-study article aims to test preference responses to FD and visual complexity, using a large cohort (N = 443) of participants from around the world to allow universality claims to be tested. It explores the extent to which age, culture and gender can predict our preferences for fractally complex patterns. Following exploratory analysis that found strong correlations between FD and visual complexity, a series of linear mixed-effect models were implemented to explore if each of the individual variables could predict preference. The first tested a linear complexity model (likelihood of selecting the more complex image from the pair of images) and the second a mid-range FD model (likelihood of selecting an image within mid-range). Results show that individual differences can reliably predict preferences for complexity across culture, gender and age. However, in fitting with current findings the mid-range models show greater consistency in preference not mediated by gender, age or culture. This article supports the established theory that the mid-range fractal patterns appear to be a universal construct underlying preference but also highlights the fragility of universal claims by demonstrating individual differences in preference for the interrelated concept of visual complexity. This highlights a current stalemate in the field of empirical aesthetics. PMID:27252634
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Hambrick, David Z; Meinz, Elizabeth J; Oswald, Frederick L
2007-03-01
What accounts for individual differences in the sort of knowledge that people may draw on in everyday cognitive tasks, such as deciding whom to vote for in a presidential election, how to invest money in the stock market, or what team to bet on in a friendly wager? In a large sample of undergraduate students, we investigated correlates of individual differences in recently acquired knowledge of current events in domains such as politics, business, and sports. Structural equation modeling revealed two predictive pathways: one involving cognitive ability factors and the other involving two major nonability factors (personality and interests). The results of this study add to what is known about the sources of individual differences in knowledge and are interpreted in the context of theoretical conceptions of adult intelligence that emphasize the centrality and importance of knowledge (e.g., Ackerman, 1996; Cattell, 1971).
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Individual variation behind the evolution of cooperation.
Barta, Zoltán
2016-02-05
Life on Earth has two remarkable properties. The first is variation: even apart from the vast number of extant species, there are considerable differences between individuals within a single species. The second property is cooperation. It is surprising that until recently the interactions between these two properties have rarely been addressed from an evolutionary point of view. Here, I concentrate on how inter-individual differences influence the evolution of cooperation. First, I deal with cases where individuality is maintained by random processes like mutation or phenotypic noise. Second, I examine when differences in state cause differences in behaviour. Finally, I investigate the effects of individual role specialization. Variation can be important in several ways. Increased random variation can change the expectation about cooperativeness of future partners, altering behaviour in a current relationship. Differences in state may serve as a book-keeping mechanism that is necessary for the evolution of reciprocity. If the cost of cooperation can depend on state then strategic regulation of state makes it possible to coerce partners to cooperate. If conditions force individuals to specialize, cooperation becomes more valuable. My review of theoretical models suggests that variation plays an important role in the evolution of cooperation. © 2016 The Author(s).
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Individual covariation in life-history traits: seeing the trees despite the forest
Cam, E.; Link, W.A.; Cooch, E.G.; Monnat, J.-Y.; Danchin, E.
2002-01-01
We investigated the influence of age on survival and breeding rates in a long-lived species Rissa tridactyla using models with individual random effects permitting variation and covariation in fitness components among individuals. Differences in survival or breeding probabilities among individuals are substantial, and there was positive covariation between survival and breeding probability; birds that were more likely to survive were also more likely to breed, given that they survived. The pattern of age-related variation in these rates detected at the individual level differed from that observed at the population level. Our results provided confirmation of what has been suggested by other investigators: within-cohort phenotypic selection can mask senescence. Although this phenomenon has been extensively studied in humans and captive animals, conclusive evidence of the discrepancy between population-level and individual-level patterns of age-related variation in life-history traits is extremely rare in wild animal populations. Evolutionary studies of the influence of age on life-history traits should use approaches differentiating population level from the genuine influence of age: only the latter is relevant to theories of life-history evolution. The development of models permitting access to individual variation in fitness is a promising advance for the study of senescence and evolutionary processes.
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Inferring social status and rich club effects in enterprise communication networks.
Dong, Yuxiao; Tang, Jie; Chawla, Nitesh V; Lou, Tiancheng; Yang, Yang; Wang, Bai
2015-01-01
Social status, defined as the relative rank or position that an individual holds in a social hierarchy, is known to be among the most important motivating forces in social behaviors. In this paper, we consider the notion of status from the perspective of a position or title held by a person in an enterprise. We study the intersection of social status and social networks in an enterprise. We study whether enterprise communication logs can help reveal how social interactions and individual status manifest themselves in social networks. To that end, we use two enterprise datasets with three communication channels--voice call, short message, and email--to demonstrate the social-behavioral differences among individuals with different status. We have several interesting findings and based on these findings we also develop a model to predict social status. On the individual level, high-status individuals are more likely to be spanned as structural holes by linking to people in parts of the enterprise networks that are otherwise not well connected to one another. On the community level, the principle of homophily, social balance and clique theory generally indicate a "rich club" maintained by high-status individuals, in the sense that this community is much more connected, balanced and dense. Our model can predict social status of individuals with 93% accuracy.
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The cost of different types of lameness in dairy cows calculated by dynamic programming.
Cha, E; Hertl, J A; Bar, D; Gröhn, Y T
2010-10-01
Traditionally, studies which placed a monetary value on the effect of lameness have calculated the costs at the herd level and rarely have they been specific to different types of lameness. These costs which have been calculated from former studies are not particularly useful for farmers in making economically optimal decisions depending on individual cow characteristics. The objective of this study was to calculate the cost of different types of lameness at the individual cow level and thereby identify the optimal management decision for each of three representative lameness diagnoses. This model would provide a more informed decision making process in lameness management for maximal economic profitability. We made modifications to an existing dynamic optimization and simulation model, studying the effects of various factors (incidence of lameness, milk loss, pregnancy rate and treatment cost) on the cost of different types of lameness. The average cost per case (US$) of sole ulcer, digital dermatitis and foot rot were 216.07, 132.96 and 120.70, respectively. It was recommended that 97.3% of foot rot cases, 95.5% of digital dermatitis cases and 92.3% of sole ulcer cases be treated. The main contributor to the total cost per case of sole ulcer was milk loss (38%), treatment cost for digital dermatitis (42%) and the effect of decreased fertility for foot rot (50%). This model affords versatility as it allows for parameters such as production costs, economic values and disease frequencies to be altered. Therefore, cost estimates are the direct outcome of the farm specific parameters entered into the model. Thus, this model can provide farmers economically optimal guidelines specific to their individual cows suffering from different types of lameness. Copyright © 2010 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Scutt Phillips, Joe; Sen Gupta, Alex; Senina, Inna; van Sebille, Erik; Lange, Michael; Lehodey, Patrick; Hampton, John; Nicol, Simon
2018-05-01
The distribution of marine species is often modeled using Eulerian approaches, in which changes to population density or abundance are calculated at fixed locations in space. Conversely, Lagrangian, or individual-based, models simulate the movement of individual particles moving in continuous space, with broader-scale patterns such as distribution being an emergent property of many, potentially adaptive, individuals. These models offer advantages in examining dynamics across spatiotemporal scales and making comparisons with observations from individual-scale data. Here, we introduce and describe such a model, the Individual-based Kinesis, Advection and Movement of Ocean ANimAls model (Ikamoana), which we use to replicate the movement processes of an existing Eulerian model for marine predators (the Spatial Ecosystem and Population Dynamics Model, SEAPODYM). Ikamoana simulates the movement of either individual or groups of animals by physical ocean currents, habitat-dependent stochastic movements (kinesis), and taxis movements representing active searching behaviours. Applying our model to Pacific skipjack tuna (Katsuwonus pelamis), we show that it accurately replicates the evolution of density distribution simulated by SEAPODYM with low time-mean error and a spatial correlation of density that exceeds 0.96 at all times. We demonstrate how the Lagrangian approach permits easy tracking of individuals' trajectories for examining connectivity between different regions, and show how the model can provide independent estimates of transfer rates between commonly used assessment regions. In particular, we find that retention rates in most assessment regions are considerably smaller (up to a factor of 2) than those estimated by this population of skipjack's primary assessment model. Moreover, these rates are sensitive to ocean state (e.g. El Nino vs La Nina) and so assuming fixed transfer rates between regions may lead to spurious stock estimates. A novel feature of the Lagrangian approach is that individual schools can be tracked through time, and we demonstrate that movement between two assessment regions at broad temporal scales includes extended transits through other regions at finer-scales. Finally, we discuss the utility of this modeling framework for the management of marine reserves, designing effective monitoring programmes, and exploring hypotheses regarding the behaviour of hard-to-observe oceanic animals.
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2013-01-01
Background As health systems evolve, it is essential to evaluate their impact on the delivery of health services to socially disadvantaged populations. We evaluated the delivery of primary health services for different socio-economic groups and assessed the performance of different organizational models in terms of equality of health care delivery in Ontario, Canada. Methods Cross sectional study of 5,361 patients receiving care from primary care practices using Capitation, Salaried or Fee-For-Service remuneration models. We assessed self-reported health status of patients, visit duration, number of visits per year, quality of health service delivery, and quality of health promotion. We used multi-level regressions to study service delivery across socio-economic groups and within each delivery model. Identified disparities were further analysed using a t-test to determine the impact of service delivery model on equity. Results Low income individuals were more likely to be women, unemployed, recent immigrants, and in poorer health. These individuals were overrepresented in the Salaried model, reported more visits/year across all models, and tended to report longer visits in the Salaried model. Measures of primary care services generally did not differ significantly between low and higher income/education individuals; when they did, the difference favoured better service delivery for at-risk groups. At-risk patients in the Salaried model were somewhat more likely to report health promotion activities than patients from Capitation and Fee-For-Service models. At-risk patients from Capitation models reported a smaller increase in the number of additional clinic visits/year than Fee-For-Service and Salaried models. At-risk patients reported better first contact accessibility than their non-at-risk counterparts in the Fee-For-Service model only. Conclusions Primary care service measures did not differ significantly across socio-economic status or primary care delivery models. In Ontario, capitation-based remuneration is age and sex adjusted only. Patients of low socio-economic status had fewer additional visits compared to those with high socio-economic status under the Capitation model. This raises the concern that Capitation may not support the provision of additional care for more vulnerable groups. Regions undertaking primary care model reforms need to consider the potential impact of the changes on the more vulnerable populations. PMID:24341530
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Dahrouge, Simone; Hogg, William; Ward, Natalie; Tuna, Meltem; Devlin, Rose Anne; Kristjansson, Elizabeth; Tugwell, Peter; Pottie, Kevin
2013-12-17
As health systems evolve, it is essential to evaluate their impact on the delivery of health services to socially disadvantaged populations. We evaluated the delivery of primary health services for different socio-economic groups and assessed the performance of different organizational models in terms of equality of health care delivery in Ontario, Canada. Cross sectional study of 5,361 patients receiving care from primary care practices using Capitation, Salaried or Fee-For-Service remuneration models. We assessed self-reported health status of patients, visit duration, number of visits per year, quality of health service delivery, and quality of health promotion. We used multi-level regressions to study service delivery across socio-economic groups and within each delivery model. Identified disparities were further analysed using a t-test to determine the impact of service delivery model on equity. Low income individuals were more likely to be women, unemployed, recent immigrants, and in poorer health. These individuals were overrepresented in the Salaried model, reported more visits/year across all models, and tended to report longer visits in the Salaried model. Measures of primary care services generally did not differ significantly between low and higher income/education individuals; when they did, the difference favoured better service delivery for at-risk groups. At-risk patients in the Salaried model were somewhat more likely to report health promotion activities than patients from Capitation and Fee-For-Service models. At-risk patients from Capitation models reported a smaller increase in the number of additional clinic visits/year than Fee-For-Service and Salaried models. At-risk patients reported better first contact accessibility than their non-at-risk counterparts in the Fee-For-Service model only. Primary care service measures did not differ significantly across socio-economic status or primary care delivery models. In Ontario, capitation-based remuneration is age and sex adjusted only. Patients of low socio-economic status had fewer additional visits compared to those with high socio-economic status under the Capitation model. This raises the concern that Capitation may not support the provision of additional care for more vulnerable groups. Regions undertaking primary care model reforms need to consider the potential impact of the changes on the more vulnerable populations.
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Active Brownian Particles. From Individual to Collective Stochastic Dynamics
NASA Astrophysics Data System (ADS)
Romanczuk, P.; Bär, M.; Ebeling, W.; Lindner, B.; Schimansky-Geier, L.
2012-03-01
We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.
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A white-box model of S-shaped and double S-shaped single-species population growth
Kalmykov, Lev V.
2015-01-01
Complex systems may be mechanistically modelled by white-box modeling with using logical deterministic individual-based cellular automata. Mathematical models of complex systems are of three types: black-box (phenomenological), white-box (mechanistic, based on the first principles) and grey-box (mixtures of phenomenological and mechanistic models). Most basic ecological models are of black-box type, including Malthusian, Verhulst, Lotka–Volterra models. In black-box models, the individual-based (mechanistic) mechanisms of population dynamics remain hidden. Here we mechanistically model the S-shaped and double S-shaped population growth of vegetatively propagated rhizomatous lawn grasses. Using purely logical deterministic individual-based cellular automata we create a white-box model. From a general physical standpoint, the vegetative propagation of plants is an analogue of excitation propagation in excitable media. Using the Monte Carlo method, we investigate a role of different initial positioning of an individual in the habitat. We have investigated mechanisms of the single-species population growth limited by habitat size, intraspecific competition, regeneration time and fecundity of individuals in two types of boundary conditions and at two types of fecundity. Besides that, we have compared the S-shaped and J-shaped population growth. We consider this white-box modeling approach as a method of artificial intelligence which works as automatic hyper-logical inference from the first principles of the studied subject. This approach is perspective for direct mechanistic insights into nature of any complex systems. PMID:26038717
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Isaacs, Anton N; Sutton, Keith; Dalziel, Kim; Maybery, Darryl
2017-02-01
Owing to difficulties faced by individuals with severe and persistent mental illness (SPMI) in accessing multiple services, the Australian Government trialed a care coordinated service model called the Partners in Recovery (PIR) initiative. A total of 45 stakeholders in Gippsland were asked what difference the initiative had made. The PIR initiative benefited not only clients and carers but also service providers. It addressed an unmet need in service delivery for individuals with SPMI. The PIR initiative has filled a gap in delivery of care for individuals with SPMI in Gippsland.
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Gonsalkorale, Karen; Sherman, Jeffrey W; Allen, Thomas J; Klauer, Karl Christoph; Amodio, David M
2011-11-01
Individuals who are primarily internally motivated to respond without prejudice show less bias on implicit measures than individuals who are externally motivated or unmotivated to respond without prejudice. However, it is not clear why these individuals exhibit less implicit bias than others. We used the Quad model to examine motivation-based individual differences in three processes that have been proposed to account for this effect: activation of associations, overcoming associations, and response monitoring. Participants completed an implicit measure of stereotyping (Study 1) or racial attitudes (Study 2). Modeling of the data revealed that individuals who were internally (but not externally) motivated to respond without prejudice showed enhanced detection and reduced activation of biased associations, suggesting that these processes may be key to achieving unbiased responding.
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Katahira, Kentaro; Fujimura, Tomomi; Matsuda, Yoshi-Taka; Okanoya, Kazuo; Okada, Masato
2014-12-01
Although the emotional outcome of a choice generally affects subsequent decisions, humans can inhibit the influence of emotion. Heart rate variability (HRV) has emerged as an objective measure of individual differences in the capacity for inhibitory control. In the present study, we investigated how individual differences in HRV at rest are associated with the emotional effects of the outcome of a choice on subsequent decision making using a decision-making task in which emotional pictures appeared as decision outcomes. We used a reinforcement learning model to characterize the observed behaviors according to several parameters, namely, the learning rate and the motivational value of positive and negative pictures. Consequently, we found that individuals with a lower resting HRV exhibited a greater negative motivational value in response to negative pictures, suggesting that these individuals tend to avoid negative pictures compared with individuals with a higher resting HRV. Copyright © 2014 Elsevier B.V. All rights reserved.
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Lamb, SE; Pepper, J; Lall, R; Jørstad-Stein, EC; Clark, MD; Hill, L; Fereday-Smith, J
2009-01-01
Background The aim was to compare effectiveness of group versus individual sessions of physiotherapy in terms of symptoms, quality of life, and costs, and to investigate the effect of patient preference on uptake and outcome of treatment. Methods A pragmatic, multi-centre randomised controlled trial in five British National Health Service physiotherapy departments. 174 women with stress and/or urge incontinence were randomised to receive treatment from a physiotherapist delivered in a group or individual setting over three weekly sessions. Outcome were measured as Symptom Severity Index; Incontinence-related Quality of Life questionnaire; National Health Service costs, and out of pocket expenses. Results The majority of women expressed no preference (55%) or preference for individual treatment (36%). Treatment attendance was good, with similar attendance with both service delivery models. Overall, there were no statistically significant differences in symptom severity or quality of life outcomes between the models. Over 85% of women reported a subjective benefit of treatment, with a slightly higher rating in the individual compared with the group setting. When all health care costs were considered, average cost per patient was lower for group sessions (Mean cost difference £52.91 95%, confidence interval (£25.82 - £80.00)). Conclusion Indications are that whilst some women may have an initial preference for individual treatment, there are no substantial differences in the symptom, quality of life outcomes or non-attendance. Because of the significant difference in mean cost, group treatment is recommended. Trial Registration Trial Registration number: ISRCTN 16772662 PMID:19751517
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Group level effects of social versus individual learning.
Jost, Jürgen; Li, Wei
2013-06-01
We study the effects of learning by imitating others within the framework of an iterated game in which the members of two complementary populations interact via random pairing at each round. This allows us to compare both the fitness of different strategies within a population and the performance of populations in which members have access to different types of strategies. Previous studies reveal some emergent dynamics at the population level, when players learn individually. We here investigate a different mechanism in which players can choose between two different learning strategies, individual or social. Imitating behavior can spread within a mixed population, with the frequency of imitators varying over generation time. When compared to a pure population with solely individual learners, a mixed population with both individual and social learners can do better, independently of the precise learning scheme employed. We can then search for the best imitating strategy. Imitating the neighbor with the highest payoff turns out to be consistently superior. This is in agreement with findings in experimental and model studies that have been carried out in different settings.
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Boer, H M T; Butler, S T; Stötzel, C; Te Pas, M F W; Veerkamp, R F; Woelders, H
2017-11-01
A recently developed mechanistic mathematical model of the bovine estrous cycle was parameterized to fit empirical data sets collected during one estrous cycle of 31 individual cows, with the main objective to further validate the model. The a priori criteria for validation were (1) the resulting model can simulate the measured data correctly (i.e. goodness of fit), and (2) this is achieved without needing extreme, probably non-physiological parameter values. We used a least squares optimization procedure to identify parameter configurations for the mathematical model to fit the empirical in vivo measurements of follicle and corpus luteum sizes, and the plasma concentrations of progesterone, estradiol, FSH and LH for each cow. The model was capable of accommodating normal variation in estrous cycle characteristics of individual cows. With the parameter sets estimated for the individual cows, the model behavior changed for 21 cows, with improved fit of the simulated output curves for 18 of these 21 cows. Moreover, the number of follicular waves was predicted correctly for 18 of the 25 two-wave and three-wave cows, without extreme parameter value changes. Estimation of specific parameters confirmed results of previous model simulations indicating that parameters involved in luteolytic signaling are very important for regulation of general estrous cycle characteristics, and are likely responsible for differences in estrous cycle characteristics between cows.
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Evaluation models of some morphological characteristics for talent scouting in sport.
Rogulj, Nenad; Papić, Vladan; Cavala, Marijana
2009-03-01
In this paper, for the purpose of expert system evaluation within the scientific project "Talent scouting in sport", two methodological approaches for recognizing an athlete's morphological compatibility for various sports has been presented, evaluated and compared. First approach is based on the fuzzy logic and expert opinion about compatibility of proposed hypothetical morphological models for 14 different sports which are part of the expert system. Second approach is based on determining the differences between morphological characteristics of a tested individual and top athlete's morphological characteristics for particular sport. Logical and mathematical bases of both methodological approaches have been explained in detail. High prognostic efficiency in recognition of individual's sport has been determined. Some improvements in further development of both methods have been proposed. Results of the research so far suggest that this or similar approaches can be successfully used for detection of individual's morphological compatibility for different sports. Also, it is expected to be useful in the selection of young talents for particular sport.
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Bimler, David; Kirkland, John; Pichler, Shaun
2004-02-01
The structure of color perception can be examined by collecting judgments about color dissimilarities. In the procedure used here, stimuli are presented three at a time on a computer monitor and the spontaneous grouping of most-similar stimuli into gestalts provides the dissimilarity comparisons. Analysis with multidimensional scaling allows such judgments to be pooled from a number of observers without obscuring the variations among them. The anomalous perceptions of color-deficient observers produce comparisons that are represented well by a geometric model of compressed individual color spaces, with different forms of deficiency distinguished by different directions of compression. The geometrical model is also capable of accommodating the normal spectrum of variation, so that there is greater variation in compression parameters between tests on normal subjects than in those between repeated tests on individual subjects. The method is sufficiently sensitive and the variations sufficiently large that they are not obscured by the use of a range of monitors, even under somewhat loosely controlled conditions.
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Iorio, Alfonso; Keepanasseril, Arun; Foster, Gary; Navarro-Ruan, Tamara; McEneny-King, Alanna; Edginton, Andrea N; Thabane, Lehana
2016-12-15
Individual pharmacokinetic assessment is a critical component of tailored prophylaxis for hemophilia patients. Population pharmacokinetics allows using individual sparse data, thus simplifying individual pharmacokinetic studies. Implementing population pharmacokinetics capacity for the hemophilia community is beyond individual reach and requires a system effort. The Web-Accessible Population Pharmacokinetic Service-Hemophilia (WAPPS-Hemo) project aims to assemble a database of patient pharmacokinetic data for all existing factor concentrates, develop and validate population pharmacokinetics models, and integrate these models within a Web-based calculator for individualized pharmacokinetic estimation in patients at participating treatment centers. Individual pharmacokinetic studies on factor VIII and IX concentrates will be sourced from pharmaceutical companies and independent investigators. All factor concentrate manufacturers, hemophilia treatment centers (HTCs), and independent investigators (identified via a systematic review of the literature) having on file pharmacokinetic data and willing to contribute full or sparse pharmacokinetic data will be eligible for participation. Multicompartmental modeling will be performed using a mixed-model approach for derivation and Bayesian forecasting for estimation of individual sparse data. NONMEM (ICON Development Solutions) will be used as modeling software. The WAPPS-Hemo research network has been launched and is currently joined by 30 HTCs from across the world. We have gathered dense individual pharmacokinetic data on 878 subjects, including several replicates, on 21 different molecules from 17 different sources. We have collected sparse individual pharmacokinetic data on 289 subjects from the participating centers through the testing phase of the WAPPS-Hemo Web interface. We have developed prototypal population pharmacokinetics models for 11 molecules. The WAPPS-Hemo website (available at www.wapps-hemo.org, version 2.4), with core functionalities allowing hemophilia treaters to obtain individual pharmacokinetic estimates on sparse data points after 1 or more infusions of a factor concentrate, was launched for use within the research network in July 2015. The WAPPS-Hemo project and research network aims to make it easier to perform individual pharmacokinetic assessments on a reduced number of plasma samples by adoption of a population pharmacokinetics approach. The project will also gather data to substantially enhance the current knowledge about factor concentrate pharmacokinetics and sources of its variability in target populations. ClinicalTrials.gov NCT02061072; https://clinicaltrials.gov/ct2/show/NCT02061072 (Archived by WebCite at http://www.webcitation.org/6mRK9bKP6). ©Alfonso Iorio, Arun Keepanasseril, Gary Foster, Tamara Navarro-Ruan, Alanna McEneny-King, Andrea N Edginton, Lehana Thabane. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 15.12.2016.
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Ferris, Abbie E; Smith, Jeremy D; Heise, Gary D; Hinrichs, Richard N; Martin, Philip E
2017-03-21
Lower extremity joint moment magnitudes during swing are dependent on the inertial properties of the prosthesis and residual limb of individuals with transtibial amputation (TTA). Often, intact limb inertial properties (INTACT) are used for prosthetic limb values in an inverse dynamics model even though these values overestimate the amputated limb's inertial properties. The purpose of this study was to use subject-specific (SPECIFIC) measures of prosthesis inertial properties to generate a general model (GENERAL) for estimating TTA prosthesis inertial properties. Subject-specific mass, center of mass, and moment of inertia were determined for the shank and foot segments of the prosthesis (n=11) using an oscillation technique and reaction board. The GENERAL model was derived from the means of the SPECIFIC model. Mass and segment lengths are required GENERAL model inputs. Comparisons of segment inertial properties and joint moments during walking were made using three inertial models (unique sample; n=9): (1) SPECIFIC, (2) GENERAL, and (3) INTACT. Prosthetic shank inertial properties were significantly smaller with the SPECIFIC and GENERAL model than the INTACT model, but the SPECIFIC and GENERAL model did not statistically differ. Peak knee and hip joint moments during swing were significantly smaller for the SPECIFIC and GENERAL model compared with the INTACT model and were not significantly different between SPECIFIC and GENERAL models. When subject-specific measures are unavailable, using the GENERAL model produces a better estimate of prosthetic side inertial properties resulting in more accurate joint moment measurements for individuals with TTA than the INTACT model. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Suzuki, Etsuji; Yamamoto, Eiji; Takao, Soshi; Kawachi, Ichiro; Subramanian, S. V.
2012-01-01
Background Multilevel analyses are ideally suited to assess the effects of ecological (higher level) and individual (lower level) exposure variables simultaneously. In applying such analyses to measures of ecologies in epidemiological studies, individual variables are usually aggregated into the higher level unit. Typically, the aggregated measure includes responses of every individual belonging to that group (i.e. it constitutes a self-included measure). More recently, researchers have developed an aggregate measure which excludes the response of the individual to whom the aggregate measure is linked (i.e. a self-excluded measure). In this study, we clarify the substantive and technical properties of these two measures when they are used as exposures in multilevel models. Methods Although the differences between the two aggregated measures are mathematically subtle, distinguishing between them is important in terms of the specific scientific questions to be addressed. We then show how these measures can be used in two distinct types of multilevel models—self-included model and self-excluded model—and interpret the parameters in each model by imposing hypothetical interventions. The concept is tested on empirical data of workplace social capital and employees' systolic blood pressure. Results Researchers assume group-level interventions when using a self-included model, and individual-level interventions when using a self-excluded model. Analytical re-parameterizations of these two models highlight their differences in parameter interpretation. Cluster-mean centered self-included models enable researchers to decompose the collective effect into its within- and between-group components. The benefit of cluster-mean centering procedure is further discussed in terms of hypothetical interventions. Conclusions When investigating the potential roles of aggregated variables, researchers should carefully explore which type of model—self-included or self-excluded—is suitable for a given situation, particularly when group sizes are relatively small. PMID:23251609
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Automated MRI Segmentation for Individualized Modeling of Current Flow in the Human Head
Huang, Yu; Dmochowski, Jacek P.; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C.
2013-01-01
Objective High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography (HD-EEG) require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images (MRI) requires labor-intensive manual segmentation, even when leveraging available automated segmentation tools. Also, accurate placement of many high-density electrodes on individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. Approach A fully automated segmentation technique based on Statical Parametric Mapping 8 (SPM8), including an improved tissue probability map (TPM) and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on 4 healthy subjects and 7 stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. Main results The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view (FOV) extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Significance Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials. PMID:24099977
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Automated MRI segmentation for individualized modeling of current flow in the human head
NASA Astrophysics Data System (ADS)
Huang, Yu; Dmochowski, Jacek P.; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C.
2013-12-01
Objective. High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. Approach. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets.Main results. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly.Significance. Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials.
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NASA Astrophysics Data System (ADS)
Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst
2017-11-01
Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.
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Henderson, Nicole L; Dressler, William W
2017-12-01
This study examines the knowledge individuals use to make judgments about persons with substance use disorder. First, we show that there is a cultural model of addiction causality that is both shared and contested. Second, we examine how individuals' understanding of that model is associated with stigma attribution. Research was conducted among undergraduate students at the University of Alabama. College students in the 18-25 age range are especially at risk for developing substance use disorder, and they are, perhaps more than any other population group, intensely targeted by drug education. The elicited cultural model includes different types of causes distributed across five distinct themes: Biological, Self-Medication, Familial, Social, and Hedonistic. Though there was cultural consensus among respondents overall, residual agreement analysis showed that the cultural model of addiction causality is a multicentric domain. Two centers of the model, the moral and the medical, were discovered. Differing adherence to these centers is associated with the level of stigma attributed towards individuals with substance use disorder. The results suggest that current approaches to substance use education could contribute to stigma attribution, which may or may not be inadvertent. The significance of these results for both theory and the treatment of addiction are discussed.
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Quality of asthma care under different primary care models in Canada: a population-based study.
To, Teresa; Guan, Jun; Zhu, Jingqin; Lougheed, M Diane; Kaplan, Alan; Tamari, Itamar; Stanbrook, Matthew B; Simatovic, Jacqueline; Feldman, Laura; Gershon, Andrea S
2015-02-14
Previous research has shown variations in quality of care and patient outcomes under different primary care models. The objective of this study was to use previously validated, evidence-based performance indicators to measure quality of asthma care over time and to compare quality of care between different primary care models. Data were obtained for years 2006 to 2010 from the Ontario Asthma Surveillance Information System, which uses health administrative databases to track individuals with asthma living in the province of Ontario, Canada. Individuals with asthma (n=1,813,922) were divided into groups based on the practice model of their primary care provider (i.e., fee-for-service, blended fee-for-service, blended capitation). Quality of asthma care was measured using six validated, evidence-based asthma care performance indicators. All of the asthma performance indicators improved over time within each of the primary care models. Compared to the traditional fee-for-service model, the blended fee-for-service and blended capitation models had higher use of spirometry for asthma diagnosis and monitoring, higher rates of inhaled corticosteroid prescription, and lower outpatient claims. Emergency department visits were lowest in the blended fee-for-service group. Quality of asthma care improved over time within each of the primary care models. However, the amount by which they improved differed between the models. The newer primary care models (i.e., blended fee-for-service, blended capitation) appear to provide better quality of asthma care compared to the traditional fee-for-service model.
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NASA Astrophysics Data System (ADS)
Lauter, Judith
2002-05-01
As Research Director of CID, Ira emphasized the importance of combining information from biology with rigorous studies of behavior, such as psychophysics, to better understand how the brain and body accomplish the goals of everyday life. In line with this philosophy, my doctoral dissertation sought to explain brain functional asymmetries (studied with dichotic listening) in terms of the physical dimensions of a library of test sounds designed to represent a speech-music continuum. Results highlighted individual differences plus similarities in terms of patterns of relative ear advantages, suggesting an organizational basis for brain asymmetries depending on physical dimensions of stimulus and gesture with analogs in auditory, visual, somatosensory, and motor systems. My subsequent work has employed a number of noninvasive methods (OAEs, EPs, qEEG, PET, MRI) to explore the neurobiological bases of individual differences in general and functional asymmetries in particular. This research has led to (1) the AXS test battery for assessing the neurobiology of human sensory-motor function; (2) the handshaking model of brain function, describing dynamic relations along all three body/brain axes; (3) the four-domain EPIC model of functional asymmetries; and (4) the trimodal brain, a new model of individual differences based on psychoimmunoneuroendocrinology.
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Aschenbrenner, Andrew J.; Balota, David A.; Gordon, Brian A.; Ratcliff, Roger; Morris, John C.
2015-01-01
Objective A family history of Alzheimer disease (AD) increases the risk of developing AD and can influence the accumulation of well-established AD biomarkers. There is some evidence that family history can influence episodic memory performance even in cognitively normal individuals. We attempted to replicate the effect of family history on episodic memory and used a specific computational model of binary decision making (the diffusion model) to understand precisely how family history influences cognition. Finally, we assessed the sensitivity of model parameters to family history controlling for standard neuropsychological test performance. Method Across two experiments, cognitively healthy participants from the Adult Children Study completed an episodic recognition test consisting of high and low frequency words. The diffusion model was applied to decompose accuracy and reaction time into latent parameters which were analyzed as a function of family history. Results In both experiments, individuals with a family history of AD exhibited lower recognition accuracy and this occurred in the absence of an apolipoprotein E (APOE) ε4 allele. The diffusion model revealed this difference was due to changes in the quality of information accumulation (the drift rate) and not differences in response caution or other model parameters. This difference remained after controlling for several standard neuropsychological tests. Conclusions These results confirm that the presence of a family history of AD confers a subtle cognitive deficit in episodic memory as reflected by decreased drift rate that cannot be attributed to APOE. This measure may serve as a novel cognitive marker of preclinical AD. PMID:26192539
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Trap configuration and spacing influences parameter estimates in spatial capture-recapture models
Sun, Catherine C.; Fuller, Angela K.; Royle, J. Andrew
2014-01-01
An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.
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Singh, Minerva; Evans, Damian; Coomes, David A.; Friess, Daniel A.; Suy Tan, Boun; Samean Nin, Chan
2016-01-01
This research examines the role of canopy cover in influencing above ground biomass (AGB) dynamics of an open canopied forest and evaluates the efficacy of individual-based and plot-scale height metrics in predicting AGB variation in the tropical forests of Angkor Thom, Cambodia. The AGB was modeled by including canopy cover from aerial imagery alongside with the two different canopy vertical height metrics derived from LiDAR; the plot average of maximum tree height (Max_CH) of individual trees, and the top of the canopy height (TCH). Two different statistical approaches, log-log ordinary least squares (OLS) and support vector regression (SVR), were used to model AGB variation in the study area. Ten different AGB models were developed using different combinations of airborne predictor variables. It was discovered that the inclusion of canopy cover estimates considerably improved the performance of AGB models for our study area. The most robust model was log-log OLS model comprising of canopy cover only (r = 0.87; RMSE = 42.8 Mg/ha). Other models that approximated field AGB closely included both Max_CH and canopy cover (r = 0.86, RMSE = 44.2 Mg/ha for SVR; and, r = 0.84, RMSE = 47.7 Mg/ha for log-log OLS). Hence, canopy cover should be included when modeling the AGB of open-canopied tropical forests. PMID:27176218
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Singh, Minerva; Evans, Damian; Coomes, David A; Friess, Daniel A; Suy Tan, Boun; Samean Nin, Chan
2016-01-01
This research examines the role of canopy cover in influencing above ground biomass (AGB) dynamics of an open canopied forest and evaluates the efficacy of individual-based and plot-scale height metrics in predicting AGB variation in the tropical forests of Angkor Thom, Cambodia. The AGB was modeled by including canopy cover from aerial imagery alongside with the two different canopy vertical height metrics derived from LiDAR; the plot average of maximum tree height (Max_CH) of individual trees, and the top of the canopy height (TCH). Two different statistical approaches, log-log ordinary least squares (OLS) and support vector regression (SVR), were used to model AGB variation in the study area. Ten different AGB models were developed using different combinations of airborne predictor variables. It was discovered that the inclusion of canopy cover estimates considerably improved the performance of AGB models for our study area. The most robust model was log-log OLS model comprising of canopy cover only (r = 0.87; RMSE = 42.8 Mg/ha). Other models that approximated field AGB closely included both Max_CH and canopy cover (r = 0.86, RMSE = 44.2 Mg/ha for SVR; and, r = 0.84, RMSE = 47.7 Mg/ha for log-log OLS). Hence, canopy cover should be included when modeling the AGB of open-canopied tropical forests.
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Questions of time and affect: a person's affectivity profile, time perspective, and well-being.
Garcia, Danilo; Sailer, Uta; Nima, Ali Al; Archer, Trevor
2016-01-01
Background. A "balanced" time perspective has been suggested to have a positive influence on well-being: a sentimental and positive view of the past (high Past Positive), a less pessimistic attitude toward the past (low Past Negative), the desire of experiencing pleasure with slight concern for future consequences (high Present Hedonistic), a less fatalistic and hopeless view of the future (low Present Fatalistic), and the ability to find reward in achieving specific long-term goals (high Future). We used the affective profiles model (i.e., combinations of individuals' experience of high/low positive/negative affectivity) to investigate differences between individuals in time perspective dimensions and to investigate if the influence of time perspective dimensions on well-being was moderated by the individual's type of profile. Method. Participants (N = 720) answered to the Positive Affect Negative Affect Schedule, the Zimbardo Time Perspective Inventory and two measures of well-being: the Temporal Satisfaction with Life Scale and Ryff's Scales of Psychological Well-Being-short version. A Multivariate Analysis of Variance (MANOVA) was conducted to identify differences in time perspective dimensions and well-being among individuals with distinct affective profiles. Four structural equation models (SEM) were used to investigate which time perspective dimensions predicted well-being for individuals in each profile. Results. Comparisons between individuals at the extreme of the affective profiles model suggested that individuals with a self-fulfilling profile (high positive/low negative affect) were characterized by a "balanced" time perspective and higher well-being compared to individuals with a self-destructive profile (low positive/high negative affect). However, a different pattern emerged when individuals who differed in one affect dimension but matched in the other were compared to each other. For instance, decreases in the past negative time perspective dimension lead to high positive affect when negative affect is high (i.e., self-destructive vs. high affective) but to low negative affect when positive affect was high (i.e., high affective vs. self-fulfilling). The moderation analyses showed, for example, that for individuals with a self-destructive profile, psychological well-being was significantly predicted by the past negative, present fatalistic and future time perspectives. Among individuals with a high affective or a self-fulfilling profile, psychological well-being was significantly predicted by the present fatalistic dimension. Conclusions. The interactions found here go beyond the postulation of a "balanced" time perspective being the only way to promote well-being. Instead, we present a more person-centered approach to achieve higher levels of emotional, cognitive, and psychological well-being.
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Which risk models perform best in selecting ever-smokers for lung cancer screening?
A new analysis by scientists at NCI evaluates nine different individualized lung cancer risk prediction models based on their selections of ever-smokers for computed tomography (CT) lung cancer screening.
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NASA Astrophysics Data System (ADS)
Schunk, R. W.; Scherliess, L.; Eccles, V.; Gardner, L. C.; Sojka, J. J.; Zhu, L.; Pi, X.; Mannucci, A. J.; Komjathy, A.; Wang, C.; Rosen, G.
2016-12-01
As part of the NASA-NSF Space Weather Modeling Collaboration, we created a Multimodel Ensemble Prediction System (MEPS) for the Ionosphere-Thermosphere-Electrodynamics system that is based on Data Assimilation (DA) models. MEPS is composed of seven physics-based data assimilation models that cover the globe. Ensemble modeling can be conducted for the mid-low latitude ionosphere using the four GAIM data assimilation models, including the Gauss Markov (GM), Full Physics (FP), Band Limited (BL) and 4DVAR DA models. These models can assimilate Total Electron Content (TEC) from a constellation of satellites, bottom-side electron density profiles from digisondes, in situ plasma densities, occultation data and ultraviolet emissions. The four GAIM models were run for the March 16-17, 2013, geomagnetic storm period with the same data, but we also systematically added new data types and re-ran the GAIM models to see how the different data types affected the GAIM results, with the emphasis on elucidating differences in the underlying ionospheric dynamics and thermospheric coupling. Also, for each scenario the outputs from the four GAIM models were used to produce an ensemble mean for TEC, NmF2, and hmF2. A simple average of the models was used in the ensemble averaging to see if there was an improvement of the ensemble average over the individual models. For the scenarios considered, the ensemble average yielded better specifications than the individual GAIM models. The model differences and averages, and the consequent differences in ionosphere-thermosphere coupling and dynamics will be discussed.
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Competency-Based Accounting Instruction
ERIC Educational Resources Information Center
Graham, John E.
1977-01-01
Shows how the proposed model (an individualized competency based learning system) can be used effectively to produce a course in accounting principles which adapts to different entering competencies and to different rates and styles of learning. (TA)
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NASA Astrophysics Data System (ADS)
Giner-Sanz, J. J.; Ortega, E. M.; Pérez-Herranz, V.
2018-03-01
The internal resistance of a PEM fuel cell depends on the operation conditions and on the current delivered by the cell. This work's goal is to obtain a semiempirical model able to reproduce the effect of the operation current on the internal resistance of an individual cell of a commercial PEM fuel cell stack; and to perform a statistical analysis in order to study the effect of the operation temperature and the inlet humidities on the parameters of the model. First, the internal resistance of the individual fuel cell operating in different operation conditions was experimentally measured for different DC currents, using the high frequency intercept of the impedance spectra. Then, a semiempirical model based on Springer and co-workers' model was proposed. This model is able to successfully reproduce the experimental trends. Subsequently, the curves of resistance versus DC current obtained for different operation conditions were fitted to the semiempirical model, and an analysis of variance (ANOVA) was performed in order to determine which factors have a statistically significant effect on each model parameter. Finally, a response surface method was applied in order to obtain a regression model.
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Individual and Institutional Components of the Medical School Educational Environment.
Gruppen, Larry D; Stansfield, R Brent
2016-11-01
To examine, using a systems framework, the relative influence of individual-level and institution-level factors on student perceptions of the medical school educational environment. A series of hierarchical linear models were fit to a large, 18-school longitudinal dataset of student perceptions of the educational environment, various demographics, and student empathy, tolerance of ambiguity, coping, and patient-provider orientation. Separate models were evaluated for individual-level factors alone, institution-level factors alone, and the combination of individual- and institution-level factors. The individual-level model accounted for 56.7% of the variance in student perceptions of the educational environment. However, few specific variables at the individual level had noteworthy direct effects on these perceptions. Similarly, the institution-level model accounted for 10.3% of the variance in student perceptions, but the specific characteristics of the institution explained little of this impact. The combined individual- and institution-level model attributed 45.5% of the variance in student perceptions to individual-level factors and 10.8% to institution-level factors. Again, specific variables explained little of this impact. These findings indicate that the impact of individual-level factors on perceptions of the educational environment is about four times greater than institution-level factors. This contrast reflects the fact that the educational environment is defined through a learner, not institutional lens. Nonetheless, institutions vary in learner perceptions of their environments, and these differences may provide some support for institutional initiatives to improve the educational environment. More broadly, these results evidence the complexity of the educational environment, both in defining it and in understanding its dynamics.
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ERIC Educational Resources Information Center
Choi, Kilchan; Seltzer, Michael
2005-01-01
In studies of change in education and numerous other fields, interest often centers on how differences in the status of individuals at the start of a time period of substantive interest relate to differences in subsequent change. This report presents a fully Bayesian approach to estimating three-level hierarchical models in which latent variable…
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Modeling the Direct and Indirect Determinants of Different Types of Individual Job Performance
2008-06-01
cognitions , and self-regulation). A different model was found to describe the process depending on whether the performance dimension was an element of...performing the behaviors they indicated they intended to perform, and assembled a battery of existing instruments to measure cognitive ability, personality...model came from the task performance dimension. For this dimension, knowledge, skill, cognitive choice aspects of motivation, and self-regulation
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Examining variation in working memory capacity and retrieval in cued recall.
Unsworth, Nash
2009-05-01
Two experiments examined the notion that individual differences in working memory capacity (WMC) are partially due to differences in search set size in cued recall. High and low WMC individuals performed variants of a cued recall task with either unrelated cue words (Experiment 1) or specific cue phrases (Experiment 2). Across both experiments low WMC individuals recalled fewer items, made more errors, and had longer correct recall latencies than high WMC individuals. Cross-experimental analyses suggested that providing participants with more specific cues decreased the size of the search set, leading to better recall overall. However, these effects were equivalent for high and low WMC. It is argued that these results are consistent with a search model framework in which low WMC individuals search through a larger set of items than high WMC individuals.
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Laparoscopic Common Bile Duct Exploration Four-Task Training Model: Construct Validity
Otaño, Natalia; Rodríguez, Omaira; Sánchez, Renata; Benítez, Gustavo; Schweitzer, Michael
2012-01-01
Background: Training models in laparoscopic surgery allow the surgical team to practice procedures in a safe environment. We have proposed the use of a 4-task, low-cost inert model to practice critical steps of laparoscopic common bile duct exploration. Methods: The performance of 3 groups with different levels of expertise in laparoscopic surgery, novices (A), intermediates (B), and experts (C), was evaluated using a low-cost inert model in the following tasks: (1) intraoperative cholangiography catheter insertion, (2) transcystic exploration, (3) T-tube placement, and (4) choledochoscope management. Kruskal-Wallis and Mann-Whitney tests were used to identify differences among the groups. Results: A total of 14 individuals were evaluated: 5 novices (A), 5 intermediates (B), and 4 experts (C). The results involving intraoperative cholangiography catheter insertion were similar among the 3 groups. As for the other tasks, the expert had better results than the other 2, in which no significant differences occurred. The proposed model is able to discriminate among individuals with different levels of expertise, indicating that the abilities that the model evaluates are relevant in the surgeon's performance in CBD exploration. Conclusions: Construct validity for tasks 2 and 3 was demonstrated. However, task 1 was no capable of distinguishing between groups, and task 4 was not statistically validated. PMID:22906323
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Individualized estimation of human core body temperature using noninvasive measurements.
Laxminarayan, Srinivas; Rakesh, Vineet; Oyama, Tatsuya; Kazman, Josh B; Yanovich, Ran; Ketko, Itay; Epstein, Yoram; Morrison, Shawnda; Reifman, Jaques
2018-06-01
A rising core body temperature (T c ) during strenuous physical activity is a leading indicator of heat-injury risk. Hence, a system that can estimate T c in real time and provide early warning of an impending temperature rise may enable proactive interventions to reduce the risk of heat injuries. However, real-time field assessment of T c requires impractical invasive technologies. To address this problem, we developed a mathematical model that describes the relationships between T c and noninvasive measurements of an individual's physical activity, heart rate, and skin temperature, and two environmental variables (ambient temperature and relative humidity). A Kalman filter adapts the model parameters to each individual and provides real-time personalized T c estimates. Using data from three distinct studies, comprising 166 subjects who performed treadmill and cycle ergometer tasks under different experimental conditions, we assessed model performance via the root mean squared error (RMSE). The individualized model yielded an overall average RMSE of 0.33 (SD = 0.18)°C, allowing us to reach the same conclusions in each study as those obtained using the T c measurements. Furthermore, for 22 unique subjects whose T c exceeded 38.5°C, a potential lower T c limit of clinical relevance, the average RMSE decreased to 0.25 (SD = 0.20)°C. Importantly, these results remained robust in the presence of simulated real-world operational conditions, yielding no more than 16% worse RMSEs when measurements were missing (40%) or laden with added noise. Hence, the individualized model provides a practical means to develop an early warning system for reducing heat-injury risk. NEW & NOTEWORTHY A model that uses an individual's noninvasive measurements and environmental variables can continually "learn" the individual's heat-stress response by automatically adapting the model parameters on the fly to provide real-time individualized core body temperature estimates. This individualized model can replace impractical invasive sensors, serving as a practical and effective surrogate for core temperature monitoring.
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Tran, Steven; Nowicki, Magda; Muraleetharan, Arrujyan; Chatterjee, Diptendu; Gerlai, Robert
2016-02-04
Variation among individuals may arise for several reasons, and may have diverse underlying mechanisms. Individual differences have been studied in a variety of species, but recently a new model organism has emerged in this field that offers both sophistication in phenotypical characterization and powerful mechanistic analysis. Recently, zebrafish, one of the favorites of geneticists, have been shown to exhibit consistent individual differences in baseline locomotor activity. In the current study, we further explore this finding and examine whether individual differences in locomotor activity correlate with anxiety-like behavioral measures and with levels of dopamine, serotonin and the metabolites of these neurotransmitters. In addition, we examine whether individual differences in locomotor activity are also associated with reactivity to the locomotor stimulant effects of and neurochemical responses to acute ethanol exposure (30min long, 1% v/v ethanol bath application). Principal component analyses revealed a strong association among anxiety-like responses, locomotor activity, serotonin and dopamine levels. Furthermore, ethanol exposure was found to abolish the locomotion-dependent anxiety-like behavioral and serotonergic responses suggesting that this drug also engages a common underlying pathway. Overall, our results provide support for an important role of the serotonergic system in mediating individual differences in anxiety-like responses and locomotor activity in zebrafish and for a minor modulatory role of the dopaminergic system. Copyright © 2015 Elsevier Inc. All rights reserved.
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Risk Factors for Addiction and Their Association with Model-Based Behavioral Control.
Reiter, Andrea M F; Deserno, Lorenz; Wilbertz, Tilmann; Heinze, Hans-Jochen; Schlagenhauf, Florian
2016-01-01
Addiction shows familial aggregation and previous endophenotype research suggests that healthy relatives of addicted individuals share altered behavioral and cognitive characteristics with individuals suffering from addiction. In this study we asked whether impairments in behavioral control proposed for addiction, namely a shift from goal-directed, model-based toward habitual, model-free control, extends toward an unaffected sample (n = 20) of adult children of alcohol-dependent fathers as compared to a sample without any personal or family history of alcohol addiction (n = 17). Using a sequential decision-making task designed to investigate model-free and model-based control combined with a computational modeling analysis, we did not find any evidence for altered behavioral control in individuals with a positive family history of alcohol addiction. Independent of family history of alcohol dependence, we however observed that the interaction of two different risk factors of addiction, namely impulsivity and cognitive capacities, predicts the balance of model-free and model-based behavioral control. Post-hoc tests showed a positive association of model-based behavior with cognitive capacity in the lower, but not in the higher impulsive group of the original sample. In an independent sample of particularly high- vs. low-impulsive individuals, we confirmed the interaction effect of cognitive capacities and high vs. low impulsivity on model-based control. In the confirmation sample, a positive association of omega with cognitive capacity was observed in highly impulsive individuals, but not in low impulsive individuals. Due to the moderate sample size of the study, further investigation of the association of risk factors for addiction with model-based behavior in larger sample sizes is warranted.
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The temporal dynamics of cortisol and affective states in depressed and non-depressed individuals.
Booij, Sanne H; Bos, Elisabeth H; de Jonge, Peter; Oldehinkel, Albertine J
2016-07-01
Cortisol levels have been related to mood disorders at the group level, but not much is known about how cortisol relates to affective states within individuals over time. We examined the temporal dynamics of cortisol and affective states in depressed and non-depressed individuals in daily life. Specifically, we addressed the direction and timing of the effects, as well as individual differences. Thirty depressed and non-depressed participants (aged 20-50 years) filled out questionnaires regarding their affect and sampled saliva three times a day for 30 days in their natural environment. They were pair-matched on age, gender, smoking behavior and body mass index. The multivariate time series (T=90) of every participant were analyzed using vector autoregressive (VAR) modeling to assess lagged effects of cortisol on affect, and vice versa. Contemporaneous effects were assessed using the residuals of the VAR models. Impulse response function analysis was used to examine the timing of effects. For 29 out of 30 participants, a VAR model could be constructed. A significant relationship between cortisol and positive or negative affect was found for the majority of the participants, but the direction, sign, and timing of the relationship varied among individuals. This approach proves to be a valuable addition to traditional group designs, because our results showed that daily life fluctuations in cortisol can influence affective states, and vice versa, but not in all individuals and in varying ways. Future studies may examine whether these individual differences relate to susceptibility for or progression of mood disorders. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Biagianti, Bruno; Fisher, Melissa; Neilands, Torsten B.; Loewy, Rachel; Vinogradov, Sophia
2016-01-01
BACKGROUND Individuals with schizophrenia who engage in targeted cognitive training (TCT) of the auditory system show generalized cognitive improvements. The high degree of variability in cognitive gains maybe due to individual differences in the level of engagement of the underlying neural system target. METHODS 131 individuals with schizophrenia underwent 40 hours of TCT. We identified target engagement of auditory system processing efficiency by modeling subject-specific trajectories of auditory processing speed (APS) over time. Lowess analysis, mixed models repeated measures analysis, and latent growth curve modeling were used to examine whether APS trajectories were moderated by age and illness duration, and mediated improvements in cognitive outcome measures. RESULTS We observed signifcant improvements in APS from baseline to 20 hours of training (initial change), followed by a flat APS trajectory (plateau) at subsequent time-points. Participants showed inter-individual variability in the steepness of the initial APS change and in the APS plateau achieved and sustained between 20–40 hours. We found that participants who achieved the fastest APS plateau, showed the greatest transfer effects to untrained cognitive domains. CONCLUSIONS There is a significant association between an individual's ability to generate and sustain auditory processing efficiency and their degree of cognitive improvement after TCT, independent of baseline neurocognition. APS plateau may therefore represent a behavioral measure of target engagement mediating treatment response. Future studies should examine the optimal plateau of auditory processing efficiency required to induce significant cognitive improvements, in the context of inter-individual differences in neural plasticity and sensory system efficiency that characterize schizophrenia. PMID:27617637
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Galle, J; Hoffmann, M; Aust, G
2009-01-01
Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.
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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
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Louppe, Vivien; Courant, Julien; Herrel, Anthony
2017-01-15
Theoretical models predict that spatial sorting at the range edge of expanding populations should favor individuals with increased mobility relative to individuals at the center of the range. Despite the fact that empirical evidence for the evolution of locomotor performance at the range edge is rare, data on cane toads support this model. However, whether this can be generalized to other species remains largely unknown. Here, we provide data on locomotor stamina and limb morphology in individuals from two sites: one from the center and one from the periphery of an expanding population of the clawed frog Xenopus laevis in France where it was introduced about 30 years ago. Additionally, we provide data on the morphology of frogs from two additional sites to test whether the observed differences can be generalized across the range of this species in France. Given the known sexual size dimorphism in this species, we also test for differences between the sexes in locomotor performance and morphology. Our results show significant sexual dimorphism in stamina and morphology, with males having longer legs and greater stamina than females. Moreover, in accordance with the predictions from theoretical models, individuals from the range edge had a greater stamina. This difference in locomotor performance is likely to be driven by the significantly longer limb segments observed in animals in both sites sampled in different areas along the range edge. Our data have implications for conservation because spatial sorting on the range edge may lead to an accelerated increase in the spread of this invasive species in France. © 2017. Published by The Company of Biologists Ltd.
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Toward a Science of Cooperation.
ERIC Educational Resources Information Center
Newbern, Dianna; And Others
Scripted cooperative learning and individual learning of descriptive information were compared in a 2-x-2 factorial design with 104 undergraduates. Influenced by models of individual learning and cognition, differences were assessed in (1) information acquisition and retrieval, (2) the quality and quantity of recalled information, and (3) the…
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Van Lange, Paul A M; Rinderu, Maria I; Bushman, Brad J
2017-01-01
Worldwide there are substantial differences within and between countries in aggression and violence. Although there are various exceptions, a general rule is that aggression and violence increase as one moves closer to the equator, which suggests the important role of climate differences. While this pattern is robust, theoretical explanations for these large differences in aggression and violence within countries and around the world are lacking. Most extant explanations focus on the influence of average temperature as a factor that triggers aggression (The General Aggression Model), or the notion that warm temperature allows for more social interaction situations (Routine Activity Theory) in which aggression is likely to unfold. We propose a new model, CLimate, Aggression, and Self-control in Humans (CLASH), that helps us to understand differences within and between countries in aggression and violence in terms of differences in climate. Lower temperatures, and especially larger degrees of seasonal variation in climate, call for individuals and groups to adopt a slower life history strategy, a greater focus on the future (vs. present), and a stronger focus on self-control. The CLASH model further outlines that slow life strategy, future orientation, and strong self-control are important determinants of inhibiting aggression and violence. We also discuss how CLASH differs from other recently developed models that emphasize climate differences for understanding conflict. We conclude by discussing the theoretical and societal importance of climate in shaping individual and societal differences in aggression and violence.
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Ensminger, Amanda L; Fernández-Juricic, Esteban
2014-01-01
Between-individual variation has been documented in a wide variety of taxa, especially for behavioral characteristics; however, intra-population variation in sensory systems has not received similar attention in wild animals. We measured a key trait of the visual system, the density of retinal cone photoreceptors, in a wild population of house sparrows (Passer domesticus). We tested whether individuals differed from each other in cone densities given within-individual variation across the retina and across eyes. We further tested whether the existing variation could lead to individual differences in two aspects of perception: visual resolution and chromatic contrast. We found consistent between-individual variation in the densities of all five types of avian cones, involved in chromatic and achromatic vision. Using perceptual modeling, we found that this degree of variation translated into significant between-individual differences in visual resolution and the chromatic contrast of a plumage signal that has been associated with mate choice and agonistic interactions. However, there was no evidence for a relationship between individual visual resolution and chromatic contrast. The implication is that some birds may have the sensory potential to perform "better" in certain visual tasks, but not necessarily in both resolution and contrast simultaneously. Overall, our findings (a) highlight the need to consider multiple individuals when characterizing sensory traits of a species, and (b) provide some mechanistic basis for between-individual variation in different behaviors (i.e., animal personalities) and for testing the predictions of several widely accepted hypotheses (e.g., honest signaling).
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Ensminger, Amanda L.; Fernández-Juricic, Esteban
2014-01-01
Between-individual variation has been documented in a wide variety of taxa, especially for behavioral characteristics; however, intra-population variation in sensory systems has not received similar attention in wild animals. We measured a key trait of the visual system, the density of retinal cone photoreceptors, in a wild population of house sparrows (Passer domesticus). We tested whether individuals differed from each other in cone densities given within-individual variation across the retina and across eyes. We further tested whether the existing variation could lead to individual differences in two aspects of perception: visual resolution and chromatic contrast. We found consistent between-individual variation in the densities of all five types of avian cones, involved in chromatic and achromatic vision. Using perceptual modeling, we found that this degree of variation translated into significant between-individual differences in visual resolution and the chromatic contrast of a plumage signal that has been associated with mate choice and agonistic interactions. However, there was no evidence for a relationship between individual visual resolution and chromatic contrast. The implication is that some birds may have the sensory potential to perform “better” in certain visual tasks, but not necessarily in both resolution and contrast simultaneously. Overall, our findings (a) highlight the need to consider multiple individuals when characterizing sensory traits of a species, and (b) provide some mechanistic basis for between-individual variation in different behaviors (i.e., animal personalities) and for testing the predictions of several widely accepted hypotheses (e.g., honest signaling). PMID:25372039
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Calibration of a stochastic health evolution model using NHIS data
NASA Astrophysics Data System (ADS)
Gupta, Aparna; Li, Zhisheng
2011-10-01
This paper presents and calibrates an individual's stochastic health evolution model. In this health evolution model, the uncertainty of health incidents is described by a stochastic process with a finite number of possible outcomes. We construct a comprehensive health status index (HSI) to describe an individual's health status, as well as a health risk factor system (RFS) to classify individuals into different risk groups. Based on the maximum likelihood estimation (MLE) method and the method of nonlinear least squares fitting, model calibration is formulated in terms of two mixed-integer nonlinear optimization problems. Using the National Health Interview Survey (NHIS) data, the model is calibrated for specific risk groups. Longitudinal data from the Health and Retirement Study (HRS) is used to validate the calibrated model, which displays good validation properties. The end goal of this paper is to provide a model and methodology, whose output can serve as a crucial component of decision support for strategic planning of health related financing and risk management.
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An integrated model of communication influence on beliefs
Eveland, William P.; Cooper, Kathryn E.
2013-01-01
How do people develop and maintain their beliefs about science? Decades of social science research exist to help us answer this question. The Integrated Model of Communication Influence on Beliefs presented here combines multiple theories that have considered aspects of this process into a comprehensive model to explain how individuals arrive at their scientific beliefs. In this article, we (i) summarize what is known about how science is presented in various news and entertainment media forms; (ii) describe how individuals differ in their choices to be exposed to various forms and sources of communication; (iii) discuss the implications of how individuals mentally process information on the effects of communication; (iv) consider how communication effects can be altered depending on background characteristics and motivations of individuals; and (v) emphasize that the process of belief formation is not unidirectional but rather, feeds back on itself over time. We conclude by applying the Integrated Model of Communication Influence on Beliefs to the complex issue of beliefs about climate change. PMID:23940328
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An integrated model of communication influence on beliefs.
Eveland, William P; Cooper, Kathryn E
2013-08-20
How do people develop and maintain their beliefs about science? Decades of social science research exist to help us answer this question. The Integrated Model of Communication Influence on Beliefs presented here combines multiple theories that have considered aspects of this process into a comprehensive model to explain how individuals arrive at their scientific beliefs. In this article, we (i) summarize what is known about how science is presented in various news and entertainment media forms; (ii) describe how individuals differ in their choices to be exposed to various forms and sources of communication; (iii) discuss the implications of how individuals mentally process information on the effects of communication; (iv) consider how communication effects can be altered depending on background characteristics and motivations of individuals; and (v) emphasize that the process of belief formation is not unidirectional but rather, feeds back on itself over time. We conclude by applying the Integrated Model of Communication Influence on Beliefs to the complex issue of beliefs about climate change.
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Integrating Biodiversity into Biosphere-Atmosphere Interactions Using Individual-Based Models (IBM)
NASA Astrophysics Data System (ADS)
Wang, B.; Shugart, H. H., Jr.; Lerdau, M.
2017-12-01
A key component regulating complex, nonlinear, and dynamic biosphere-atmosphere interactions is the inherent diversity of biological systems. The model frameworks currently widely used, i.e., Plant Functional Type models) do not even begin to capture the metabolic and taxonomic diversity found in many terrestrial systems. We propose that a transition from PFT-based to individual-based modeling approaches (hereafter referred to as IBM) is essential for integrating biodiversity into research on biosphere-atmosphere interactions. The proposal emerges from our studying the interactions of forests with atmospheric processes in the context of climate change using an individual-based forest volatile organic compounds model, UVAFME-VOC. This individual-based model can explicitly simulate VOC emissions based on an explicit modelling of forest dynamics by computing the growth, death, and regeneration of each individual tree of different species and their competition for light, moisture, and nutrient, from which system-level VOC emissions are simulated by explicitly computing and summing up each individual's emissions. We found that elevated O3 significantly altered the forest dynamics by favoring species that are O3-resistant, which, meanwhile, are producers of isoprene. Such compositional changes, on the one hand, resulted in unsuppressed forest productivity and carbon stock because of the compensation by O3-resistant species. On the other hand, with more isoprene produced arising from increased producers, a possible positive feedback loop between tropospheric O3 and forest thereby emerged. We also found that climate warming will not always stimulate isoprene emissions because warming simultaneously reduces isoprene emissions by causing a decline in the abundance of isoprene-emitting species. These results suggest that species diversity is of great significance and that individual-based modelling strategies should be applied in studying biosphere-atmosphere interactions.
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Parallel interactive retrieval of item and associative information from event memory.
Cox, Gregory E; Criss, Amy H
2017-09-01
Memory contains information about individual events (items) and combinations of events (associations). Despite the fundamental importance of this distinction, it remains unclear exactly how these two kinds of information are stored and whether different processes are used to retrieve them. We use both model-independent qualitative properties of response dynamics and quantitative modeling of individuals to address these issues. Item and associative information are not independent and they are retrieved concurrently via interacting processes. During retrieval, matching item and associative information mutually facilitate one another to yield an amplified holistic signal. Modeling of individuals suggests that this kind of facilitation between item and associative retrieval is a ubiquitous feature of human memory. Copyright © 2017 Elsevier Inc. All rights reserved.
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A network model of behavioural performance in a rule learning task.
Hasselmo, Michael E; Stern, Chantal E
2018-04-19
Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'. © 2018 The Author(s).
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Fisher waves and front roughening in a two-species invasion model with preemptive competition.
O'Malley, L; Kozma, B; Korniss, G; Rácz, Z; Caraco, T
2006-10-01
We study front propagation when an invading species competes with a resident; we assume nearest-neighbor preemptive competition for resources in an individual-based, two-dimensional lattice model. The asymptotic front velocity exhibits an effective power-law dependence on the difference between the two species' clonal propagation rates (key ecological parameters). The mean-field approximation behaves similarly, but the power law's exponent slightly differs from the individual-based model's result. We also study roughening of the front, using the framework of nonequilibrium interface growth. Our analysis indicates that initially flat, linear invading fronts exhibit Kardar-Parisi-Zhang (KPZ) roughening in one transverse dimension. Further, this finding implies, and is also confirmed by simulations, that the temporal correction to the asymptotic front velocity is of O(t(-2/3)).
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Hedeker, D; Flay, B R; Petraitis, J
1996-02-01
Methods are proposed and described for estimating the degree to which relations among variables vary at the individual level. As an example of the methods, M. Fishbein and I. Ajzen's (1975; I. Ajzen & M. Fishbein, 1980) theory of reasoned action is examined, which posits first that an individual's behavioral intentions are a function of 2 components: the individual's attitudes toward the behavior and the subjective norms as perceived by the individual. A second component of their theory is that individuals may weight these 2 components differently in assessing their behavioral intentions. This article illustrates the use of empirical Bayes methods based on a random-effects regression model to estimate these individual influences, estimating an individual's weighting of both of these components (attitudes toward the behavior and subjective norms) in relation to their behavioral intentions. This method can be used when an individual's behavioral intentions, subjective norms, and attitudes toward the behavior are all repeatedly measured. In this case, the empirical Bayes estimates are derived as a function of the data from the individual, strengthened by the overall sample data.
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Resende, R T; Resende, M D V; Silva, F F; Azevedo, C F; Takahashi, E K; Silva-Junior, O B; Grattapaglia, D
2017-10-01
We report a genomic selection (GS) study of growth and wood quality traits in an outbred F 2 hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.
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[Estimating survival of thrushes: modeling capture-recapture probabilities].
Burskiî, O V
2011-01-01
The stochastic modeling technique serves as a way to correctly separate "return rate" of marked animals into survival rate (phi) and capture probability (p). The method can readily be used with the program MARK freely distributed through Internet (Cooch, White, 2009). Input data for the program consist of "capture histories" of marked animals--strings of units and zeros indicating presence or absence of the individual among captures (or sightings) along the set of consequent recapture occasions (e.g., years). Probability of any history is a product of binomial probabilities phi, p or their complements (1 - phi) and (1 - p) for each year of observation over the individual. Assigning certain values to parameters phi and p, one can predict the composition of all individual histories in the sample and assess the likelihood of the prediction. The survival parameters for different occasions and cohorts of individuals can be set either equal or different, as well as recapture parameters can be set in different ways. There is a possibility to constraint the parameters, according to the hypothesis being tested, in the form of a specific model. Within the specified constraints, the program searches for parameter values that describe the observed composition of histories with the maximum likelihood. It computes the parameter estimates along with confidence limits and the overall model likelihood. There is a set of tools for testing the model goodness-of-fit under assumption of equality of survival rates among individuals and independence of their fates. Other tools offer a proper selection among a possible variety of models, providing the best parity between details and precision in describing reality. The method was applied to 20-yr recapture and resighting data series on 4 thrush species (genera Turdus, Zoothera) breeding in the Yenisei River floodplain within the middle taiga subzone. The capture probabilities were quite independent of observational efforts fluctuations while differing significantly between the species and sexes. The estimates of adult survival rate, obtained for the Siberian migratory populations, were lower than those for sedentary populations from both the tropics and intermediate latitudes with marine climate (data by Ricklefs, 1997). Two factors, the average temperature influencing birds during their annual movements, and climatic seasonality (temperature difference between summer and winter) in the breeding area, fit the latitudinal pattern of survival most closely (R2 = 0.90). Final survival of migrants reflects an adaptive life history compromise for use of superabundant resources in breeding area at the cost of avoidance of severe winter conditions.
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Maydeu-Olivares, Alberto
2016-01-01
Nesselroade and Molenaar advocate the use of an idiographic filter approach. This is a fixed-effects approach, which may limit the number of individuals that can be simultaneously modeled, and it is not clear how to model the presence of subpopulations. Most important, Nesselroade and Molenaar's proposal appears to be best suited for modeling long time series on a few variables for a few individuals. Long time series are not common in psychological applications. Can it be applied to the usual longitudinal data we face? These are characterized by short time series (four to five points in time), hundreds of individuals, and dozens of variables. If so, what do we gain? Applied settings most often involve between-individual decisions. I conjecture that their approach will not outperform common, simpler, methods. However, when intraindividual decisions are involved, their approach may have an edge.
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Dessalew, Nigus; Bharatam, Prasad V
2007-07-01
Selective glycogen synthase kinase 3 (GSK3) inhibition over cyclin dependent kinases such as cyclin dependent kinase 2 (CDK2) and cyclin dependent kinase 4 (CDK4) is an important requirement for improved therapeutic profile of GSK3 inhibitors. The concepts of selectivity and additivity fields have been employed in developing selective CoMFA models for these related kinases. Initially, sets of three individual CoMFA models were developed, using 36 compounds of bisarylmaleimide series to correlate with the GSK3, CDK2 and CDK4 inhibitory potencies. These models showed a satisfactory statistical significance: CoMFA-GSK3 (r(2)(con), r(2)(cv): 0.931, 0.519), CoMFA-CDK2 (0.937, 0.563), and CoMFA-CDK4 (0.892, 0.725). Three different selective CoMFA models were then developed using differences in pIC(50) values. These three models showed a superior statistical significance: (i) CoMFA-Selective1 (r(2)(con), r(2)(cv): 0.969, 0.768), (ii) CoMFA-Selective 2 (0.974, 0.835) and (iii) CoMFA-Selective3 (0.963, 0.776). The selective models were found to outperform the individual models in terms of the quality of correlation and were found to be more informative in pinpointing the structural basis for the observed quantitative differences of kinase inhibition. An in-depth comparative investigation was carried out between the individual and selective models to gain an insight into the selectivity criterion. To further validate this approach, a set of new compounds were designed which show selectivity and were docked into the active site of GSK3, using FlexX based incremental construction algorithm.
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Cheung, Felix; Lucas, Richard E.
2015-01-01
Previous research shows that the correlation between income and life satisfaction is small to medium in size. We hypothesized that income may mean different things to people at different ages, and therefore, that the association between income and life satisfaction may vary at different points in the life course. We tested this hypothesis in three nationally representative panel studies. Multilevel modeling techniques were used to test whether age moderated both the within- and between-person associations. Consistent with past research, we found that individuals who earned more on average and individuals who earned more over time reported higher levels of life satisfaction. Importantly, these effects were strongest for midlife individuals (those in their 30s–50s) compared to individuals who were younger or older. PMID:25621741
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Using sensors to measure activity in people with stroke.
Fulk, George D; Sazonov, Edward
2011-01-01
The purpose of this study was to determine the ability of a novel shoe-based sensor that uses accelerometers, pressure sensors, and pattern recognition with a support vector machine (SVM) to accurately identify sitting, standing, and walking postures in people with stroke. Subjects with stroke wore the shoe-based sensor while randomly assuming 3 main postures: sitting, standing, and walking. A SVM classifier was used to train and validate the data to develop individual and group models, which were tested for accuracy, recall, and precision. Eight subjects participated. Both individual and group models were able to accurately identify the different postures (99.1% to 100% individual models and 76.9% to 100% group models). Recall and precision were also high for both individual (0.99 to 1.00) and group (0.82 to 0.99) models. The unique combination of accelerometer and pressure sensors built into the shoe was able to accurately identify postures. This shoe sensor could be used to provide accurate information on community performance of activities in people with stroke as well as provide behavioral enhancing feedback as part of a telerehabilitation intervention.
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Culture, morality and individual differences: comparability and incomparability across species.
Saucier, Gerard
2018-04-19
Major routes to identifying individual differences (in diverse species) include studies of behaviour patterns as represented in language and neurophysiology. But results from these approaches appear not to converge on some major dimensions. Identifying dimensions of human variation least applicable to non-human species may help to partition human-specific individual differences of recent evolutionary origin from those shared across species. Human culture includes learned, enforced social-norm systems that are symbolically reinforced and referenced in displays signalling adherence. At a key juncture in human evolution bullying aggression and deception-based cheating apparently became censured in the language of a moral community, enabling mutual observation coordinated in gossip, associated with external sanctions. That still-conserved cultural paradigm moralistically regulates selfish advantage-taking, with shared semantics and explicit rules. Ethics and moral codes remain critical and universal components of human culture and have a stronger imprint in language than most aspects of the currently popular Big-Five taxonomy, a model that sets out five major lines of individual-differences variation in human personality. In other species (e.g. chimpanzees), human observers might see apparent individual differences in morality-relevant traits, but not because the animals have human-analogue sanctioning systems. Removing the moral dimension of personality and other human-specific manifestations (e.g. religion) may aid in identifying those other bases of individual differences more ubiquitous across species.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'. © 2018 The Author(s).
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Therapeutic Enactment: Integrating Individual and Group Counseling Models for Change
ERIC Educational Resources Information Center
Westwood, Marvin J.; Keats, Patrice A.; Wilensky, Patricia
2003-01-01
The purpose of this article is to introduce the reader to a group-based therapy model known as therapeutic enactment. A description of this multimodal change model is provided by outlining the relevant background information, key concepts related to specific change processes, and the differences in this model compared to earlier psychodrama…
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The Cattell-Horn-Carroll Model of Cognition for Clinical Assessment
ERIC Educational Resources Information Center
Jewsbury, Paul A.; Bowden, Stephen C.; Duff, Kevin
2017-01-01
The Cattell-Horn-Carroll (CHC) model is a comprehensive model of the major dimensions of individual differences that underlie performance on cognitive tests. Studies evaluating the generality of the CHC model across test batteries, age, gender, and culture were reviewed and found to be overwhelmingly supportive. However, less research is available…
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Goodreau, Steven M; Golden, Matthew R
2007-01-01
Objectives HIV disproportionately affects men who have sex with men (MSM). MSM and heterosexual networks are distinguished by biologically determined sexual role segregation among heterosexual individuals but not MSM, and anal/vaginal transmissibility differences. To identify how much these biological and demographic differences could explain persistent disparities in HIV/sexually transmitted disease prevalence in the United States, even were MSM and heterosexual individuals to report identical numbers of unprotected sexual partnerships per year. Methods A compartmental model parameterized using two population‐based surveys. Role composition was varied between MSM and heterosexual subjects (insertive‐only and receptive‐only versus versatile individuals) and infectivity values. Results The absence of sexual role segregation in MSM and the differential anal/vaginal transmission probabilities led to considerable disparities in equilibrium prevalence. The US heterosexual population would only experience an epidemic comparable to MSM if the mean partner number of heterosexual individuals was increased several fold over that observed in population‐based studies of either group. In order for MSM to eliminate the HIV epidemic, they would need to develop rates of unprotected sex lower than those currently exhibited by heterosexual individuals in the United States. In this model, for US heterosexual individuals to have a self‐sustaining epidemic, they would need to adopt levels of unprotected sex higher than those currently exhibited by US MSM. Conclusions The persistence of disparities in HIV between heterosexual individuals and MSM in the United States cannot be explained solely by differences in risky sexual behavior between these two populations. PMID:17855487
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ERIC Educational Resources Information Center
Greene, Jeffrey A.; Azevedo, Roger A.; Torney-Purta, Judith
2008-01-01
We propose an integration of aspects of several developmental and systems of beliefs models of personal epistemology. Qualitatively different positions, including realism, dogmatism, skepticism, and rationalism, are characterized according to individuals' beliefs across three dimensions in a model of epistemic and ontological cognition. This model…
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Peer group socialization of homophobic attitudes and behavior during adolescence.
Poteat, V Paul
2007-01-01
A social developmental framework was applied to test for the socialization of homophobic attitudes and behavior within adolescent peer groups (Grades 7-11; aged 12-17 years). Substantial similarity within and differences across groups were documented. Multilevel models identified a group socializing contextual effect, predicting homophobic attitudes and behavior of individuals within the group 8 months later, even after controlling for the predictive effect of individuals' own previously reported attitudes and behavior. Several group characteristics moderated the extent to which individuals' previously reported attitudes predicted later attitudes. Findings indicate the need to integrate the concurrent assessment of individual and social factors to inform the construction of more comprehensive models of how prejudiced attitudes and behaviors develop and are perpetuated.
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Graves, Tabitha A.; Royle, J. Andrew; Kendall, Katherine C.; Beier, Paul; Stetz, Jeffrey B.; Macleod, Amy C.
2012-01-01
Using multiple detection methods can increase the number, kind, and distribution of individuals sampled, which may increase accuracy and precision and reduce cost of population abundance estimates. However, when variables influencing abundance are of interest, if individuals detected via different methods are influenced by the landscape differently, separate analysis of multiple detection methods may be more appropriate. We evaluated the effects of combining two detection methods on the identification of variables important to local abundance using detections of grizzly bears with hair traps (systematic) and bear rubs (opportunistic). We used hierarchical abundance models (N-mixture models) with separate model components for each detection method. If both methods sample the same population, the use of either data set alone should (1) lead to the selection of the same variables as important and (2) provide similar estimates of relative local abundance. We hypothesized that the inclusion of 2 detection methods versus either method alone should (3) yield more support for variables identified in single method analyses (i.e. fewer variables and models with greater weight), and (4) improve precision of covariate estimates for variables selected in both separate and combined analyses because sample size is larger. As expected, joint analysis of both methods increased precision as well as certainty in variable and model selection. However, the single-method analyses identified different variables and the resulting predicted abundances had different spatial distributions. We recommend comparing single-method and jointly modeled results to identify the presence of individual heterogeneity between detection methods in N-mixture models, along with consideration of detection probabilities, correlations among variables, and tolerance to risk of failing to identify variables important to a subset of the population. The benefits of increased precision should be weighed against those risks. The analysis framework presented here will be useful for other species exhibiting heterogeneity by detection method.
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Rössler, Wulf; Hengartner, Michael P; Ajdacic-Gross, Vladeta; Haker, Helene; Angst, Jules
2014-03-01
The study objective was to examine childhood adversity in association with intra-individual changes and inter-individual differences in subclinical psychosis in a representative community cohort over a 30-year period of observation. We analyzed two psychosis syndromes derived from the SCL-90-R - schizotypal signs and schizophrenia nuclear symptoms - in 335 participants. Participants were repeatedly assessed between 1978 (around age 20) and 2008 (around age 50). We focused specifically on inter-individual differences and intra-individual changes over time by applying structural equation modeling, generalized linear models, and generalized estimating equations. Several weak inter-individual differences revealed that increased schizotypal signs are related to various childhood adversities, such as being repeatedly involved in fights and parents having severe conflicts among themselves. We also found a significant positive association between schizotypal signs and the total number of adversities a subject experienced. This pointed toward a modest dose-response relationship. The intra-individual change in schizotypal signs over time was rather weak, although some adjustment did occur. In contrast, inter-individual schizophrenia nuclear symptoms were mainly unrelated to childhood adversity. However, some striking intra-individual changes in distress were noted over time, especially those linked with severe punishment and the total adversity score. In conclusion, we have confirmed previous positive findings about the association between childhood adversity and subsequent subclinical psychosis symptoms: An increase in adversity is weakly related to an increase of the psychosis symptom load. However, depending on the kind of adversity experienced the psychosis symptom load decreases gradually in adult life. Copyright © 2014 Elsevier B.V. All rights reserved.
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Bleakley, B H; Welter, S M; McCauley-Cole, K; Shuster, S M; Moore, A J
2013-04-01
Models for the evolution of cannibalism highlight the importance of asymmetries between individuals in initiating cannibalistic attacks. Studies may include measures of body size but typically group individuals into size/age classes or compare populations. Such broad comparisons may obscure the details of interactions that ultimately determine how socially contingent characteristics evolve. We propose that understanding cannibalism is facilitated by using an interacting phenotypes perspective that includes the influences of the phenotype of a social partner on the behaviour of a focal individual and focuses on variation in individual pairwise interactions. We investigated how relative body size, a composite trait between a focal individual and its social partner, and the sex of the partners influenced precannibalistic aggression in the endangered Socorro isopod, Thermosphaeroma thermophilum. We also investigated whether differences in mating interest among males and females influenced cannibalism in mixed sex pairs. We studied these questions in three populations that differ markedly in range of body size and opportunities for interactions among individuals. We found that relative body size influences the probability of and latency to attack. We observed differences in the likelihood of and latency to attack based on both an individual's sex and the sex of its partner but found no evidence of sexual conflict. The instigation of precannibalistic aggression in these isopods is therefore a property of both an individual and its social partner. Our results suggest that interacting phenotype models would be improved by incorporating a new conditional ψ, which describes the strength of a social partner's influence on focal behaviour. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.
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Effects of distribution of infection rate on epidemic models
NASA Astrophysics Data System (ADS)
Lachiany, Menachem; Louzoun, Yoram
2016-08-01
A goal of many epidemic models is to compute the outcome of the epidemics from the observed infected early dynamics. However, often, the total number of infected individuals at the end of the epidemics is much lower than predicted from the early dynamics. This discrepancy is argued to result from human intervention or nonlinear dynamics not incorporated in standard models. We show that when variability in infection rates is included in standard susciptible-infected-susceptible (SIS ) and susceptible-infected-recovered (SIR ) models the total number of infected individuals in the late dynamics can be orders lower than predicted from the early dynamics. This discrepancy holds for SIS and SIR models, where the assumption that all individuals have the same sensitivity is eliminated. In contrast with network models, fixed partnerships are not assumed. We derive a moment closure scheme capturing the distribution of sensitivities. We find that the shape of the sensitivity distribution does not affect R0 or the number of infected individuals in the early phases of the epidemics. However, a wide distribution of sensitivities reduces the total number of removed individuals in the SIR model and the steady-state infected fraction in the SIS model. The difference between the early and late dynamics implies that in order to extrapolate the expected effect of the epidemics from the initial phase of the epidemics, the rate of change in the average infectivity should be computed. These results are supported by a comparison of the theoretical model to the Ebola epidemics and by numerical simulation.
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Computational Dysfunctions in Anxiety: Failure to Differentiate Signal From Noise.
Huang, He; Thompson, Wesley; Paulus, Martin P
2017-09-15
Differentiating whether an action leads to an outcome by chance or by an underlying statistical regularity that signals environmental change profoundly affects adaptive behavior. Previous studies have shown that anxious individuals may not appropriately differentiate between these situations. This investigation aims to precisely quantify the process deficit in anxious individuals and determine the degree to which these process dysfunctions are specific to anxiety. One hundred twenty-two subjects recruited as part of an ongoing large clinical population study completed a change point detection task. Reinforcement learning models were used to explicate observed behavioral differences in low anxiety (Overall Anxiety Severity and Impairment Scale score ≤ 8) and high anxiety (Overall Anxiety Severity and Impairment Scale score ≥ 9) groups. High anxiety individuals used a suboptimal decision strategy characterized by a higher lose-shift rate. Computational models and simulations revealed that this difference was related to a higher base learning rate. These findings are better explained in a context-dependent reinforcement learning model. Anxious subjects' exaggerated response to uncertainty leads to a suboptimal decision strategy that makes it difficult for these individuals to determine whether an action is associated with an outcome by chance or by some statistical regularity. These findings have important implications for developing new behavioral intervention strategies using learning models. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
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Ability and Motivation: Assessing Individual Factors that Contribute to University Retention
ERIC Educational Resources Information Center
Alarcon, Gene M.; Edwards, Jean M.
2013-01-01
The current study explored individual differences in ability and motivation factors of retention in first-year college students. We used discrete-time survival mixture analysis to model university retention. Parents' education, gender, American College Test (ACT) scores, conscientiousness, and trait affectivity were explored as predictors of…
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Children's Early Approaches to Learning and Academic Trajectories through Fifth Grade
ERIC Educational Resources Information Center
Li-Grining, Christine P.; Votruba-Drzal, Elizabeth; Maldonado-Carreno, Carolina; Haas, Kelly
2010-01-01
Children's early approaches to learning (ATL) enhance their adaptation to the demands they experience with the start of formal schooling. The current study uses individual growth modeling to investigate whether children's early ATL, which includes persistence, emotion regulation, and attentiveness, explain individual differences in their academic…
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Eggert, G M; Zimmer, J G; Hall, W J; Friedman, B
1991-10-01
This randomized controlled study compared two types of case management for skilled nursing level patients living at home: the centralized individual model and the neighborhood team model. The team model differed from the individual model in that team case managers performed client assessments, care planning, some direct services, and reassessments; they also had much smaller caseloads and were assigned a specific catchment area. While patients in both groups incurred very high estimated health services costs, the average annual cost during 1983-85 for team cases was 13.6 percent less than that of individual model cases. While the team cases were 18.3 percent less expensive among "old" patients (patients who entered the study from the existing ACCESS caseload), they were only 2.7 percent less costly among "new" cases. The lower costs were due to reductions in hospital days and home care. Team cases averaged 26 percent fewer hospital days per year and 17 percent fewer home health aide hours. Nursing home use was 48 percent higher for the team group than for the individual model group. Mortality was almost exactly the same for both groups during the first year (about 30 percent), but was lower for team patients during the second year (11 percent as compared to 16 percent). Probable mechanisms for the observed results are discussed.
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Bivalves: From individual to population modelling
NASA Astrophysics Data System (ADS)
Saraiva, S.; van der Meer, J.; Kooijman, S. A. L. M.; Ruardij, P.
2014-11-01
An individual based population model for bivalves was designed, built and tested in a 0D approach, to simulate the population dynamics of a mussel bed located in an intertidal area. The processes at the individual level were simulated following the dynamic energy budget theory, whereas initial egg mortality, background mortality, food competition, and predation (including cannibalism) were additional population processes. Model properties were studied through the analysis of theoretical scenarios and by simulation of different mortality parameter combinations in a realistic setup, imposing environmental measurements. Realistic criteria were applied to narrow down the possible combination of parameter values. Field observations obtained in the long-term and multi-station monitoring program were compared with the model scenarios. The realistically selected modeling scenarios were able to reproduce reasonably the timing of some peaks in the individual abundances in the mussel bed and its size distribution but the number of individuals was not well predicted. The results suggest that the mortality in the early life stages (egg and larvae) plays an important role in population dynamics, either by initial egg mortality, larvae dispersion, settlement failure or shrimp predation. Future steps include the coupling of the population model with a hydrodynamic and biogeochemical model to improve the simulation of egg/larvae dispersion, settlement probability, food transport and also to simulate the feedback of the organisms' activity on the water column properties, which will result in an improvement of the food quantity and quality characterization.
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Chuderski, Adam; Andrelczyk, Krzysztof
2015-02-01
Several existing computational models of working memory (WM) have predicted a positive relationship (later confirmed empirically) between WM capacity and the individual ratio of theta to gamma oscillatory band lengths. These models assume that each gamma cycle represents one WM object (e.g., a binding of its features), whereas the theta cycle integrates such objects into the maintained list. As WM capacity strongly predicts reasoning, it might be expected that this ratio also predicts performance in reasoning tasks. However, no computational model has yet explained how the differences in the theta-to-gamma ratio found among adult individuals might contribute to their scores on a reasoning test. Here, we propose a novel model of how WM capacity constraints figural analogical reasoning, aimed at explaining inter-individual differences in reasoning scores in terms of the characteristics of oscillatory patterns in the brain. In the model, the gamma cycle encodes the bindings between objects/features and the roles they play in the relations processed. Asynchrony between consecutive gamma cycles results from lateral inhibition between oscillating bindings. Computer simulations showed that achieving the highest WM capacity required reaching the optimal level of inhibition. When too strong, this inhibition eliminated some bindings from WM, whereas, when inhibition was too weak, the bindings became unstable and fell apart or became improperly grouped. The model aptly replicated several empirical effects and the distribution of individual scores, as well as the patterns of correlations found in the 100-people sample attempting the same reasoning task. Most importantly, the model's reasoning performance strongly depended on its theta-to-gamma ratio in same way as the performance of human participants depended on their WM capacity. The data suggest that proper regulation of oscillations in the theta and gamma bands may be crucial for both high WM capacity and effective complex cognition. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
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Opinion formation on social media: An empirical approach
NASA Astrophysics Data System (ADS)
Xiong, Fei; Liu, Yun
2014-03-01
Opinion exchange models aim to describe the process of public opinion formation, seeking to uncover the intrinsic mechanism in social systems; however, the model results are seldom empirically justified using large-scale actual data. Online social media provide an abundance of data on opinion interaction, but the question of whether opinion models are suitable for characterizing opinion formation on social media still requires exploration. We collect a large amount of user interaction information from an actual social network, i.e., Twitter, and analyze the dynamic sentiments of users about different topics to investigate realistic opinion evolution. We find two nontrivial results from these data. First, public opinion often evolves to an ordered state in which one opinion predominates, but not to complete consensus. Second, agents are reluctant to change their opinions, and the distribution of the number of individual opinion changes follows a power law. Then, we suggest a model in which agents take external actions to express their internal opinions according to their activity. Conversely, individual actions can influence the activity and opinions of neighbors. The probability that an agent changes its opinion depends nonlinearly on the fraction of opponents who have taken an action. Simulation results show user action patterns and the evolution of public opinion in the model coincide with the empirical data. For different nonlinear parameters, the system may approach different regimes. A large decay in individual activity slows down the dynamics, but causes more ordering in the system.
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Paap, Kenneth R; Sawi, Oliver
2016-12-01
Studies testing for individual or group differences in executive functioning can be compromised by unknown test-retest reliability. Test-retest reliabilities across an interval of about one week were obtained from performance in the antisaccade, flanker, Simon, and color-shape switching tasks. There is a general trade-off between the greater reliability of single mean RT measures, and the greater process purity of measures based on contrasts between mean RTs in two conditions. The individual differences in RT model recently developed by Miller and Ulrich was used to evaluate the trade-off. Test-retest reliability was statistically significant for 11 of the 12 measures, but was of moderate size, at best, for the difference scores. The test-retest reliabilities for the Simon and flanker interference scores were lower than those for switching costs. Standard practice evaluates the reliability of executive-functioning measures using split-half methods based on data obtained in a single day. Our test-retest measures of reliability are lower, especially for difference scores. These reliability measures must also take into account possible day effects that classical test theory assumes do not occur. Measures based on single mean RTs tend to have acceptable levels of reliability and convergent validity, but are "impure" measures of specific executive functions. The individual differences in RT model shows that the impurity problem is worse than typically assumed. However, the "purer" measures based on difference scores have low convergent validity that is partly caused by deficiencies in test-retest reliability. Copyright © 2016 Elsevier B.V. All rights reserved.
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Animal models of post-traumatic stress disorder: face validity
Goswami, Sonal; Rodríguez-Sierra, Olga; Cascardi, Michele; Paré, Denis
2013-01-01
Post-traumatic stress disorder (PTSD) is a debilitating condition that develops in a proportion of individuals following a traumatic event. Despite recent advances, ethical limitations associated with human research impede progress in understanding PTSD. Fortunately, much effort has focused on developing animal models to help study the pathophysiology of PTSD. Here, we provide an overview of animal PTSD models where a variety of stressors (physical, psychosocial, or psychogenic) are used to examine the long-term effects of severe trauma. We emphasize models involving predator threat because they reproduce human individual differences in susceptibility to, and in the long-term consequences of, psychological trauma. PMID:23754973
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ERIC Educational Resources Information Center
Choi, Kilchan; Seltzer, Michael
2010-01-01
In studies of change in education and numerous other fields, interest often centers on how differences in the status of individuals at the start of a period of substantive interest relate to differences in subsequent change. In this article, the authors present a fully Bayesian approach to estimating three-level Hierarchical Models in which latent…
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Voinson, Marina; Billiard, Sylvain; Alvergne, Alexandra
2015-01-01
Background Theoretical studies predict that it is not possible to eradicate a disease under voluntary vaccination because of the emergence of non-vaccinating “free-riders” when vaccination coverage increases. A central tenet of this approach is that human behaviour follows an economic model of rational choice. Yet, empirical studies reveal that vaccination decisions do not necessarily maximize individual self-interest. Here we investigate the dynamics of vaccination coverage using an approach that dispenses with payoff maximization and assumes that risk perception results from the interaction between epidemiology and cognitive biases. Methods We consider a behaviour-incidence model in which individuals perceive actual epidemiological risks as a function of their opinion of vaccination. As a result of confirmation bias, sceptical individuals (negative opinion) overestimate infection cost while pro-vaccines individuals (positive opinion) overestimate vaccination cost. We considered a feedback between individuals and their environment as individuals could change their opinion, and thus the way they perceive risks, as a function of both the epidemiology and the most common opinion in the population. Results For all parameter values investigated, the infection is never eradicated under voluntary vaccination. For moderately contagious diseases, oscillations in vaccination coverage emerge because individuals process epidemiological information differently depending on their opinion. Conformism does not generate oscillations but slows down the cultural response to epidemiological change. Conclusion Failure to eradicate vaccine preventable disease emerges from the model because of cognitive biases that maintain heterogeneity in how people perceive risks. Thus, assumptions of economic rationality and payoff maximization are not mandatory for predicting commonly observed dynamics of vaccination coverage. This model shows that alternative notions of rationality, such as that of ecological rationality whereby individuals use simple cognitive heuristics, offer promising new avenues for modelling vaccination behaviour. PMID:26599688
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Voinson, Marina; Billiard, Sylvain; Alvergne, Alexandra
2015-01-01
Theoretical studies predict that it is not possible to eradicate a disease under voluntary vaccination because of the emergence of non-vaccinating "free-riders" when vaccination coverage increases. A central tenet of this approach is that human behaviour follows an economic model of rational choice. Yet, empirical studies reveal that vaccination decisions do not necessarily maximize individual self-interest. Here we investigate the dynamics of vaccination coverage using an approach that dispenses with payoff maximization and assumes that risk perception results from the interaction between epidemiology and cognitive biases. We consider a behaviour-incidence model in which individuals perceive actual epidemiological risks as a function of their opinion of vaccination. As a result of confirmation bias, sceptical individuals (negative opinion) overestimate infection cost while pro-vaccines individuals (positive opinion) overestimate vaccination cost. We considered a feedback between individuals and their environment as individuals could change their opinion, and thus the way they perceive risks, as a function of both the epidemiology and the most common opinion in the population. For all parameter values investigated, the infection is never eradicated under voluntary vaccination. For moderately contagious diseases, oscillations in vaccination coverage emerge because individuals process epidemiological information differently depending on their opinion. Conformism does not generate oscillations but slows down the cultural response to epidemiological change. Failure to eradicate vaccine preventable disease emerges from the model because of cognitive biases that maintain heterogeneity in how people perceive risks. Thus, assumptions of economic rationality and payoff maximization are not mandatory for predicting commonly observed dynamics of vaccination coverage. This model shows that alternative notions of rationality, such as that of ecological rationality whereby individuals use simple cognitive heuristics, offer promising new avenues for modelling vaccination behaviour.
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A rational eating model of binges, diets and obesity.
Dragone, Davide
2009-07-01
This paper addresses the rapid diffusion of obesity and the existence of different individual patterns of food consumption between non-dieters and chronic dieters. I propose a rational eating model where a forward-looking agent optimizes the intertemporal satisfaction from eating, taking into account the cost of changing consumption habits and the negative health consequences of having a non-optimal body weight. Consistent with the evidence, I show that the intertemporal maximization problem leads to a condition of overweightness, and that heterogeneity in the individual relevance of habits in consumption can determine the observed differences in the individual intertemporal patterns of food consumption and body weight. Sufficient conditions for determining when the convergence to the steady state implies oscillations or is monotonic are given. In the former case, the agent optimally alternates diets and binges until the steady state is reached, in the latter a regular intertemporal pattern of food consumption is optimal.
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The socialization of dominance: peer group contextual effects on homophobic and dominance attitudes.
Poteat, V Paul; Espelage, Dorothy L; Green, Harold D
2007-06-01
Using the framework of social dominance theory, the current investigation tested for the contextual effects of adolescent peer groups on individuals' homophobic and social dominance attitudes. Results from multilevel models indicated that significant differences existed across peer groups on homophobic attitudes. In addition, these differences were accounted for on the basis of the hierarchy-enhancing or -attenuating climate of the group. A group socialization effect on individuals' social dominance attitudes over time was also observed. Furthermore, the social climate of the peer group moderated the stability of individuals' social dominance attitudes. Findings support the need to examine more proximal and informal group affiliations and earlier developmental periods in efforts to build more comprehensive theoretical models explaining when and how prejudiced and dominance attitudes are formed and the way in which they are perpetuated. (c) 2007 APA, all rights reserved.
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Mental models at work: cognitive causes and consequences of conflict in organizations.
Halevy, Nir; Cohen, Taya R; Chou, Eileen Y; Katz, James J; Panter, A T
2014-01-01
This research investigated the reciprocal relationship between mental models of conflict and various forms of dysfunctional social relations in organizations, including experiences of task and relationship conflicts, interpersonal hostility, workplace ostracism, and abusive supervision. We conceptualize individual differences in conflict construals as reflecting variation in people's belief structures about conflict and explore how different elements in people's associative networks-in particular, their beliefs about their best and worst strategy in conflict-relate to their personality, shape their experiences of workplace conflict, and influence others' behavioral intentions toward them. Five studies using a variety of methods (including cross-sectional surveys, a 12-week longitudinal diary study, and an experiment) show that the best strategy beliefs relate in theoretically meaningful ways to individuals' personality, shape social interactions and relationships significantly more than the worst strategy beliefs, and are updated over time as a result of individuals' ongoing experiences of conflict.
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NASA Astrophysics Data System (ADS)
Ma, Jing; Zhu, He
2018-06-01
In this study, we propose a novel rumor spreading model in consideration of the individuals' subjective judgment and diverse characteristics. To reflect the diversity of the individuals' characteristics, we introduce two probability distribution functions, which could be chosen arbitrarily or given by empirical data, to characterize individuals' mastering degree of knowledge with respect to the domain of a specific rumor and individuals' rationality degree. Different from existing models, no two persons in our model are identical, and each individual can judge the authenticity of the information, e.g., rumors, with his distinctive characteristics. In addition, by means of the mean-field method, we establish the expression of the dynamics of the rumor propagation in the complex heterogeneous networks and derive the rumor spreading threshold. Through the theoretical analysis, we find that the threshold is independent of the forms of the two introduced functions. Furthermore, we prove the stability of the rumor-free equilibrium set E0. That is if and only if R0 < 1, the rumor-free equilibrium set E0 is globally asymptotically stable. Finally, we conduct a series of numerical simulations to verify the theoretical results and comprehensively illustrate the evolution of the model. The simulation results show that because of the diversity of individuals' characteristics, it becomes more difficult for the rumor to disseminate in the networks and the higher the mean of knowledge and the mean of rationality are, the more time it will take for the model to evolve to the steady state.
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Variable threshold algorithm for division of labor analyzed as a dynamical system.
Castillo-Cagigal, Manuel; Matallanas, Eduardo; Navarro, Iñaki; Caamaño-Martín, Estefanía; Monasterio-Huelin, Félix; Gutiérrez, Álvaro
2014-12-01
Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.
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Real beards and real networks: a spin-glass model for interacting individuals
NASA Astrophysics Data System (ADS)
O'Neale, Dion
''I want to be different, just like all the other different people'' sang the band King Missile. Whether they are the Beatniks of the 1950s, the punks of the 1970s, or the hipsters of today, non-conformists often tend to look the same, seemingly at odds with their goal of non-conformity. The spin-glass model, originally developed to describe the interaction of magnetic spins, and since applied to situations as diverse as the electrical activity of networks of neurons, to trades on a financial market, has recently been used in social science to study populations of interacting individuals comprised of a mix of both conformists and anti-conformists - or hipsters. Including delay effects for the interactions between individuals has been shown to give a system with non-trivial dynamics with a phase transition from stable behaviour to periodic switching between two states (let's call them bushy bearded and clean shaven). Analytic solutions to such a model are possible, but only for particular assumptions about the interaction and delay matrices. In this work we will show what happens when the interactions in the model are based on real-world networks with ''small-world'' effects and clustering.
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NASA Astrophysics Data System (ADS)
D, Meena; Francis, Fredy; T, Sarath K.; E, Dipin; Srinivas, T.; K, Jayasree V.
2014-10-01
Wavelength Division Multiplexing (WDM) techniques overfibrelinks helps to exploit the high bandwidth capacity of single mode fibres. A typical WDM link consisting of laser source, multiplexer/demultiplexer, amplifier and detectoris considered for obtaining the open loop gain model of the link. The methodology used here is to obtain individual component models using mathematical and different curve fitting techniques. These individual models are then combined to obtain the WDM link model. The objective is to deduce a single variable model for the WDM link in terms of input current to system. Thus it provides a black box solution for a link. The Root Mean Square Error (RMSE) associated with each of the approximated models is given for comparison. This will help the designer to select the suitable WDM link model during a complex link design.
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Can Horton hear the whos? The importance of scale in mosquito-borne disease.
Lord, C C; Alto, B W; Anderson, S L; Connelly, C R; Day, J F; Richards, S L; Smartt, C T; Tabachnick, W J
2014-03-01
The epidemiology of vector-borne pathogens is determined by mechanisms and interactions at different scales of biological organization, from individual-level cellular processes to community interactions between species and with the environment. Most research, however, focuses on one scale or level with little integration between scales or levels within scales. Understanding the interactions between levels and how they influence our perception of vector-borne pathogens is critical. Here two examples of biological scales (pathogen transmission and mosquito mortality) are presented to illustrate some of the issues of scale and to explore how processes on different levels may interact to influence mosquito-borne pathogen transmission cycles. Individual variation in survival, vector competence, and other traits affect population abundance, transmission potential, and community structure. Community structure affects interactions between individuals such as competition and predation, and thus influences the individual-level dynamics and transmission potential. Modeling is a valuable tool to assess interactions between scales and how processes at different levels can affect transmission dynamics. We expand an existing model to illustrate the types of studies needed, showing that individual-level variation in viral dose acquired or needed for infection can influence the number of infectious vectors. It is critical that interactions within and among biological scales and levels of biological organization are understood for greater understanding of pathogen transmission with the ultimate goal of improving control of vector-borne pathogens.
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Accounting for immunoprecipitation efficiencies in the statistical analysis of ChIP-seq data.
Bao, Yanchun; Vinciotti, Veronica; Wit, Ernst; 't Hoen, Peter A C
2013-05-30
ImmunoPrecipitation (IP) efficiencies may vary largely between different antibodies and between repeated experiments with the same antibody. These differences have a large impact on the quality of ChIP-seq data: a more efficient experiment will necessarily lead to a higher signal to background ratio, and therefore to an apparent larger number of enriched regions, compared to a less efficient experiment. In this paper, we show how IP efficiencies can be explicitly accounted for in the joint statistical modelling of ChIP-seq data. We fit a latent mixture model to eight experiments on two proteins, from two laboratories where different antibodies are used for the two proteins. We use the model parameters to estimate the efficiencies of individual experiments, and find that these are clearly different for the different laboratories, and amongst technical replicates from the same lab. When we account for ChIP efficiency, we find more regions bound in the more efficient experiments than in the less efficient ones, at the same false discovery rate. A priori knowledge of the same number of binding sites across experiments can also be included in the model for a more robust detection of differentially bound regions among two different proteins. We propose a statistical model for the detection of enriched and differentially bound regions from multiple ChIP-seq data sets. The framework that we present accounts explicitly for IP efficiencies in ChIP-seq data, and allows to model jointly, rather than individually, replicates and experiments from different proteins, leading to more robust biological conclusions.
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Individual Colorimetric Observer Model
Asano, Yuta; Fairchild, Mark D.; Blondé, Laurent
2016-01-01
This study proposes a vision model for individual colorimetric observers. The proposed model can be beneficial in many color-critical applications such as color grading and soft proofing to assess ranges of color matches instead of a single average match. We extended the CIE 2006 physiological observer by adding eight additional physiological parameters to model individual color-normal observers. These eight parameters control lens pigment density, macular pigment density, optical densities of L-, M-, and S-cone photopigments, and λmax shifts of L-, M-, and S-cone photopigments. By identifying the variability of each physiological parameter, the model can simulate color matching functions among color-normal populations using Monte Carlo simulation. The variabilities of the eight parameters were identified through two steps. In the first step, extensive reviews of past studies were performed for each of the eight physiological parameters. In the second step, the obtained variabilities were scaled to fit a color matching dataset. The model was validated using three different datasets: traditional color matching, applied color matching, and Rayleigh matches. PMID:26862905
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Stargardt disease: towards developing a model to predict phenotype.
Heathfield, Laura; Lacerda, Miguel; Nossek, Christel; Roberts, Lisa; Ramesar, Rajkumar S
2013-10-01
Stargardt disease is an ABCA4-associated retinopathy, which generally follows an autosomal recessive inheritance pattern and is a frequent cause of macular degeneration in childhood. ABCA4 displays significant allelic heterogeneity whereby different mutations can cause retinal diseases with varying severity and age of onset. A genotype-phenotype model has been proposed linking ABCA4 mutations, purported ABCA4 functional protein activity and severity of disease, as measured by degree of visual loss and the age of onset. It has, however, been difficult to verify this model statistically in observational studies, as the number of individuals sharing any particular mutation combination is typically low. Seven founder mutations have been identified in a large number of Caucasian Afrikaner patients in South Africa, making it possible to test the genotype-phenotype model. A generalised linear model was developed to predict and assess the relative pathogenic contribution of the seven mutations to the age of onset of Stargardt disease. It is shown that the pathogenicity of an individual mutation can differ significantly depending on the genetic context in which it occurs. The results reported here may be used to identify suitable candidates for inclusion in clinical trials, as well as guide the genetic counselling of affected individuals and families.
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Stargardt Disease: towards developing a model to predict phenotype
Heathfield, Laura; Lacerda, Miguel; Nossek, Christel; Roberts, Lisa; Ramesar, Rajkumar S
2013-01-01
Stargardt disease is an ABCA4-associated retinopathy, which generally follows an autosomal recessive inheritance pattern and is a frequent cause of macular degeneration in childhood. ABCA4 displays significant allelic heterogeneity whereby different mutations can cause retinal diseases with varying severity and age of onset. A genotype–phenotype model has been proposed linking ABCA4 mutations, purported ABCA4 functional protein activity and severity of disease, as measured by degree of visual loss and the age of onset. It has, however, been difficult to verify this model statistically in observational studies, as the number of individuals sharing any particular mutation combination is typically low. Seven founder mutations have been identified in a large number of Caucasian Afrikaner patients in South Africa, making it possible to test the genotype–phenotype model. A generalised linear model was developed to predict and assess the relative pathogenic contribution of the seven mutations to the age of onset of Stargardt disease. It is shown that the pathogenicity of an individual mutation can differ significantly depending on the genetic context in which it occurs. The results reported here may be used to identify suitable candidates for inclusion in clinical trials, as well as guide the genetic counselling of affected individuals and families. PMID:23695285
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Perception without self-matching in conditional tag based cooperation.
McAvity, David M; Bristow, Tristen; Bunker, Eric; Dreyer, Alex
2013-09-21
We consider a model for the evolution of cooperation in a population where individuals may have one of a number of different heritable and distinguishable markers or tags. Individuals interact with each of their neighbors on a square lattice by either cooperating by donating some benefit at a cost to themselves or defecting by doing nothing. The decision to cooperate or defect is contingent on each individual's perception of its interacting partner's tag. Unlike in other tag-based models individuals do not compare their own tag to that of their interaction partner. That is, there is no self-matching. When perception is perfect the cooperation rate is substantially higher than in the usual spatial prisoner's dilemma game when the cost of cooperation is high. The enhancement in cooperation is positively correlated with the number of different tags. The more diverse a population is the more cooperative it becomes. When individuals start with an inability to perceive tags the population evolves to a state where individuals gain at least partial perception. With some reproduction mechanisms perfect perception evolves, but with others the ability to perceive tags is imperfect. We find that perception of tags evolves to lower levels when the cost of cooperation is higher. Copyright © 2013 Elsevier Ltd. All rights reserved.
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ERIC Educational Resources Information Center
Marceau, Kristine; Ram, Nilam; Houts, Renate M.; Grimm, Kevin J.; Susman, Elizabeth J.
2011-01-01
Pubertal development is a nonlinear process progressing from prepubescent beginnings through biological, physical, and psychological changes to full sexual maturity. To tether theoretical concepts of puberty with sophisticated longitudinal, analytical models capable of articulating pubertal development more accurately, we used nonlinear…
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de Vlaming, Rianne; Haveman-Nies, Annemien; Van't Veer, Pieter; de Groot, Lisette Cpgm
2010-09-13
The aim of this paper is to provide the rationale for an evaluation design for a complex intervention program targeting loneliness among non-institutionalized elderly people in a Dutch community. Complex public health interventions characteristically use the combined approach of intervening on the individual and on the environmental level. It is assumed that the components of a complex intervention interact with and reinforce each other. Furthermore, implementation is highly context-specific and its impact is influenced by external factors. Although the entire community is exposed to the intervention components, each individual is exposed to different components with a different intensity. A logic model of change is used to develop the evaluation design. The model describes what outcomes may logically be expected at different points in time at the individual level. In order to address the complexity of a real-life setting, the evaluation design of the loneliness intervention comprises two types of evaluation studies. The first uses a quasi-experimental pre-test post-test design to evaluate the effectiveness of the overall intervention. A control community comparable to the intervention community was selected, with baseline measurements in 2008 and follow-up measurements scheduled for 2010. This study focuses on changes in the prevalence of loneliness and in the determinants of loneliness within individuals in the general elderly population. Complementarily, the second study is designed to evaluate the individual intervention components and focuses on delivery, reach, acceptance, and short-term outcomes. Different means of project records and surveys among participants are used to collect these data. Combining these two evaluation strategies has the potential to assess the effectiveness of the overall complex intervention and the contribution of the individual intervention components thereto.
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2010-01-01
Background The aim of this paper is to provide the rationale for an evaluation design for a complex intervention program targeting loneliness among non-institutionalized elderly people in a Dutch community. Complex public health interventions characteristically use the combined approach of intervening on the individual and on the environmental level. It is assumed that the components of a complex intervention interact with and reinforce each other. Furthermore, implementation is highly context-specific and its impact is influenced by external factors. Although the entire community is exposed to the intervention components, each individual is exposed to different components with a different intensity. Methods/Design A logic model of change is used to develop the evaluation design. The model describes what outcomes may logically be expected at different points in time at the individual level. In order to address the complexity of a real-life setting, the evaluation design of the loneliness intervention comprises two types of evaluation studies. The first uses a quasi-experimental pre-test post-test design to evaluate the effectiveness of the overall intervention. A control community comparable to the intervention community was selected, with baseline measurements in 2008 and follow-up measurements scheduled for 2010. This study focuses on changes in the prevalence of loneliness and in the determinants of loneliness within individuals in the general elderly population. Complementarily, the second study is designed to evaluate the individual intervention components and focuses on delivery, reach, acceptance, and short-term outcomes. Different means of project records and surveys among participants are used to collect these data. Discussion Combining these two evaluation strategies has the potential to assess the effectiveness of the overall complex intervention and the contribution of the individual intervention components thereto. PMID:20836840
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Fine tuning and MOND in a metamaterial "multiverse".
Smolyaninov, Igor I; Smolyaninova, Vera N
2017-08-14
We consider the recently suggested model of a multiverse based on a ferrofluid. When the ferrofluid is subjected to a modest external magnetic field, the nanoparticles inside the ferrofluid form small hyperbolic metamaterial domains, which from the electromagnetic standpoint behave as individual "Minkowski universes" exhibiting different "laws of physics", such as different strength of effective gravity, different versions of modified Newtonian dynamics (MOND) and different radiation lifetimes. When the ferrofluid "multiverse" is populated with atomic or molecular species, and these species are excited using an external laser source, the radiation lifetimes of atoms and molecules in these "universes" depend strongly on the individual physical properties of each "universe" via the Purcell effect. Some "universes" are better fine-tuned than others to sustain the excited states of these species. Thus, the ferrofluid-based metamaterial "multiverse" may be used to study models of MOND and to illustrate the fine-tuning mechanism in cosmology.
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Composite collective decision-making
Czaczkes, Tomer J.; Czaczkes, Benjamin; Iglhaut, Carolin; Heinze, Jürgen
2015-01-01
Individual animals are adept at making decisions and have cognitive abilities, such as memory, which allow them to hone their decisions. Social animals can also share information. This allows social animals to make adaptive group-level decisions. Both individual and collective decision-making systems also have drawbacks and limitations, and while both are well studied, the interaction between them is still poorly understood. Here, we study how individual and collective decision-making interact during ant foraging. We first gathered empirical data on memory-based foraging persistence in the ant Lasius niger. We used these data to create an agent-based model where ants may use social information (trail pheromones), private information (memories) or both to make foraging decisions. The combined use of social and private information by individuals results in greater efficiency at the group level than when either information source was used alone. The modelled ants couple consensus decision-making, allowing them to quickly exploit high-quality food sources, and combined decision-making, allowing different individuals to specialize in exploiting different resource patches. Such a composite collective decision-making system reaps the benefits of both its constituent parts. Exploiting such insights into composite collective decision-making may lead to improved decision-making algorithms. PMID:26019155
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Does it all go together when it goes? The Nineteenth Bartlett Memorial Lecture.
Rabbitt, P
1993-08-01
As groups of people age, the differences in the cognitive abilities of the most and least able become more extreme. This increase in between-individual variance is accompanied by an increase in within-individual variance: the difference between individuals' levels of performance on their best and least well retained skills. The implications of increasing between-individual variance are discussed in terms of the range of different factors that may affect cognitive ageing. Increases in within-individual variance are discussed in terms of differences between "fluid" and "crystallized" abilities. The usefulness of this distinction and its functional implications are questioned. The hypothesis that age-related declines in "fluid" abilities are best modelled in terms of declines in a single factor is evaluated. Evidence is presented of disparate rates of decline, even of "fluid" cognitive abilities, such as performance on IQ tests, ability on information-processing tasks, and efficiency on memory tasks. Data from large-scale cross-sectional studies suggests that cognitive skills do not "all go together when they go," but that there may rather, be characteristic patterns, or syndromes, of cognitive ageing.
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Dynamical origins of the community structure of an online multi-layer society
NASA Astrophysics Data System (ADS)
Klimek, Peter; Diakonova, Marina; Eguíluz, Víctor M.; San Miguel, Maxi; Thurner, Stefan
2016-08-01
Social structures emerge as a result of individuals managing a variety of different social relationships. Societies can be represented as highly structured dynamic multiplex networks. Here we study the dynamical origins of the specific community structures of a large-scale social multiplex network of a human society that interacts in a virtual world of a massive multiplayer online game. There we find substantial differences in the community structures of different social actions, represented by the various layers in the multiplex network. Community sizes distributions are either fat-tailed or appear to be centered around a size of 50 individuals. To understand these observations we propose a voter model that is built around the principle of triadic closure. It explicitly models the co-evolution of node- and link-dynamics across different layers of the multiplex network. Depending on link and node fluctuation probabilities, the model exhibits an anomalous shattered fragmentation transition, where one layer fragments from one large component into many small components. The observed community size distributions are in good agreement with the predicted fragmentation in the model. This suggests that several detailed features of the fragmentation in societies can be traced back to the triadic closure processes.
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Data Relationships: Towards a Conceptual Model of Scientific Data Catalogs
NASA Astrophysics Data System (ADS)
Hourcle, J. A.
2008-12-01
As the amount of data, types of processing and storage formats increase, the total number of record permutations increase dramatically. The result is an overwhelming number of records that make identifying the best data object to answer a user's needs more difficult. The issue is further complicated as each archive's data catalog may be designed around different concepts - - anything from individual files to be served, series of similarly generated and processed data, or something entirely different. Catalogs may not only be flat tables, but may be structured as multiple tables with each table being a different data series, or a normalized structure of the individual data files. Merging federated search results from archives with different catalog designs can create situations where the data object of interest is difficult to find due to an overwhelming number of seemingly similar or entirely unwanted records. We present a reference model for discussing data catalogs and the complex relationships between similar data objects. We show how the model can be used to improve scientist's ability to quickly identify the best data object for their purposes and discuss technical issues required to use this model in a federated system.
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Barron, Daniel S; Fox, Peter T; Pardoe, Heath; Lancaster, Jack; Price, Larry R; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas
2015-01-01
Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.
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Li, He; Wu, Jing; Gao, Yiwen; Shi, Yao
2016-04-01
Wearable technology has shown the potential of improving healthcare efficiency and reducing healthcare cost. Different from pioneering studies on healthcare wearable devices from technical perspective, this paper explores the predictors of individuals' adoption of healthcare wearable devices. Considering the importance of individuals' privacy perceptions in healthcare wearable devices adoption, this study proposes a model based on the privacy calculus theory to investigate how individuals adopt healthcare wearable devices. The proposed conceptual model was empirically tested by using data collected from a survey. The sample covers 333 actual users of healthcare wearable devices. Structural equation modeling (SEM) method was employed to estimate the significance of the path coefficients. This study reveals several main findings: (1) individuals' decisions to adopt healthcare wearable devices are determined by their risk-benefit analyses (refer to privacy calculus). In short, if an individual's perceived benefit is higher than perceived privacy risk, s/he is more likely to adopt the device. Otherwise, the device would not be adopted; (2) individuals' perceived privacy risk is formed by health information sensitivity, personal innovativeness, legislative protection, and perceived prestige; and (3) individuals' perceived benefit is determined by perceived informativeness and functional congruence. The theoretical and practical implications, limitations, and future research directions are then discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models
Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori
2016-01-01
A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner’s faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals. PMID:27191162
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Facial Recognition in a Discus Fish (Cichlidae): Experimental Approach Using Digital Models.
Satoh, Shun; Tanaka, Hirokazu; Kohda, Masanori
2016-01-01
A number of mammals and birds are known to be capable of visually discriminating between familiar and unfamiliar individuals, depending on facial patterns in some species. Many fish also visually recognize other conspecifics individually, and previous studies report that facial color patterns can be an initial signal for individual recognition. For example, a cichlid fish and a damselfish will use individual-specific color patterns that develop only in the facial area. However, it remains to be determined whether the facial area is an especially favorable site for visual signals in fish, and if so why? The monogamous discus fish, Symphysopdon aequifasciatus (Cichlidae), is capable of visually distinguishing its pair-partner from other conspecifics. Discus fish have individual-specific coloration patterns on entire body including the facial area, frontal head, trunk and vertical fins. If the facial area is an inherently important site for the visual cues, this species will use facial patterns for individual recognition, but otherwise they will use patterns on other body parts as well. We used modified digital models to examine whether discus fish use only facial coloration for individual recognition. Digital models of four different combinations of familiar and unfamiliar fish faces and bodies were displayed in frontal and lateral views. Focal fish frequently performed partner-specific displays towards partner-face models, and did aggressive displays towards models of non-partner's faces. We conclude that to identify individuals this fish does not depend on frontal color patterns but does on lateral facial color patterns, although they have unique color patterns on the other parts of body. We discuss the significance of facial coloration for individual recognition in fish compared with birds and mammals.
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Attentional focus affects how events are segmented and updated in narrative reading.
Bailey, Heather R; Kurby, Christopher A; Sargent, Jesse Q; Zacks, Jeffrey M
2017-08-01
Readers generate situation models representing described events, but the nature of these representations may differ depending on the reading goals. We assessed whether instructions to pay attention to different situational dimensions affect how individuals structure their situation models (Exp. 1) and how they update these models when situations change (Exp. 2). In Experiment 1, participants read and segmented narrative texts into events. Some readers were oriented to pay specific attention to characters or space. Sentences containing character or spatial-location changes were perceived as event boundaries-particularly if the reader was oriented to characters or space, respectively. In Experiment 2, participants read narratives and responded to recognition probes throughout the texts. Readers who were oriented to the spatial dimension were more likely to update their situation models at spatial changes; all readers tracked the character dimension. The results from both experiments indicated that attention to individual situational dimensions influences how readers segment and update their situation models. More broadly, the results provide evidence for a global situation model updating mechanism that serves to set up new models at important narrative changes.
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Inferring Social Status and Rich Club Effects in Enterprise Communication Networks
Dong, Yuxiao; Tang, Jie; Chawla, Nitesh V.; Lou, Tiancheng; Yang, Yang; Wang, Bai
2015-01-01
Social status, defined as the relative rank or position that an individual holds in a social hierarchy, is known to be among the most important motivating forces in social behaviors. In this paper, we consider the notion of status from the perspective of a position or title held by a person in an enterprise. We study the intersection of social status and social networks in an enterprise. We study whether enterprise communication logs can help reveal how social interactions and individual status manifest themselves in social networks. To that end, we use two enterprise datasets with three communication channels — voice call, short message, and email — to demonstrate the social-behavioral differences among individuals with different status. We have several interesting findings and based on these findings we also develop a model to predict social status. On the individual level, high-status individuals are more likely to be spanned as structural holes by linking to people in parts of the enterprise networks that are otherwise not well connected to one another. On the community level, the principle of homophily, social balance and clique theory generally indicate a “rich club” maintained by high-status individuals, in the sense that this community is much more connected, balanced and dense. Our model can predict social status of individuals with 93% accuracy. PMID:25822343
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Uniting statistical and individual-based approaches for animal movement modelling.
Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel
2014-01-01
The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.
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Uniting Statistical and Individual-Based Approaches for Animal Movement Modelling
Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel
2014-01-01
The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems. PMID:24979047
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Quinn, Cristina L.
2012-01-01
Background: Body burdens of persistent bioaccumulative contaminants estimated from the cross-sectional biomonitoring of human populations are often plotted against age. Such relationships have previously been assumed to reflect the role of age in bioaccumulation. Objectives: We used a mechanistic modeling approach to reproduce concentration-versus-age relationships and investigate factors that influence them. Method: CoZMoMAN is an environmental fate and human food chain bioaccumulation model that estimates time trends in human body burdens in response to time-variant environmental emissions. Trends of polychlorinated biphenyl (PCB) congener 153 concentrations versus age for population cross sections were estimated using simulated longitudinal data for individual women born at different times. The model was also used to probe the influence of partitioning and degradation properties, length of emissions, and model assumptions regarding lipid content and liver metabolism on concentration–age trends of bioaccumulative and persistent contaminants. Results: Body burden–age relationships for population cross sections and individuals over time are not equivalent. The time lapse between the peak in emissions and sample collection for biomonitoring is the most influential factor controlling the shape of concentration–age trends for chemicals with human metabolic half-lives longer than 1 year. Differences in observed concentration–age trends for PCBs and polybrominated diphenyl ethers are consistent with differences in emission time trends and human metabolic half-lives. Conclusions: Bioaccumulation does not monotonically increase with age. Our model suggests that the main predictors of cross-sectional body burden trends with age are the amount of time elapsed after peak emissions and the human metabolic and environmental degradation rates. PMID:22472302
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Hershey, Douglas A; Henkens, Kene; Van Dalen, Hendrik P
2010-01-01
Current theoretical models support the existence of interactions between the individual and socio-environmental forces when it comes to the formation and enactment of life plans (Friedman & Scholnick, 1997; Shanahan & Elder, 2002). In this investigation, we examine the social, economic, and psychological forces that impact financial planning for retirement. The collective force of these three broad sets of influences was examined from developmental and cross-cultural perspectives, among respondents from two countries with very different retirement financing systems. Participants were 419 American and 556 Dutch working adults, 25-64 years of age. Path analysis models were created to examine differences in planning associated with age and national origin. Compared to younger individuals, older respondents in both countries were more involved in nearly all aspects of the financial planning process. Differences across cultures were also observed in the social support mechanisms that underlie planning and the impact economic forces have on perceptions of saving adequacy. The discussion focuses on the value of developing interdisciplinary theoretical models of planning, and how such models can inform the development of savings-oriented intervention and public policy initiatives.
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Individual Differences in Human Reliability Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jeffrey C. Joe; Ronald L. Boring
2014-06-01
While human reliability analysis (HRA) methods include uncertainty in quantification, the nominal model of human error in HRA typically assumes that operator performance does not vary significantly when they are given the same initiating event, indicators, procedures, and training, and that any differences in operator performance are simply aleatory (i.e., random). While this assumption generally holds true when performing routine actions, variability in operator response has been observed in multiple studies, especially in complex situations that go beyond training and procedures. As such, complexity can lead to differences in operator performance (e.g., operator understanding and decision-making). Furthermore, psychological research hasmore » shown that there are a number of known antecedents (i.e., attributable causes) that consistently contribute to observable and systematically measurable (i.e., not random) differences in behavior. This paper reviews examples of individual differences taken from operational experience and the psychological literature. The impact of these differences in human behavior and their implications for HRA are then discussed. We propose that individual differences should not be treated as aleatory, but rather as epistemic. Ultimately, by understanding the sources of individual differences, it is possible to remove some epistemic uncertainty from analyses.« less
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Microscopic models for the study of taxpayer audit effects
NASA Astrophysics Data System (ADS)
Bertotti, Maria Letizia; Modanese, Giovanni
2016-03-01
A microscopic dynamic model is here constructed and analyzed, describing the evolution of the income distribution in the presence of taxation and redistribution in a society in which also tax evasion and auditing processes occur. The focus is on effects of enforcement regimes, characterized by different choices of the audited taxpayer fraction and of the penalties imposed to noncompliant individuals. A complex systems perspective is adopted: society is considered as a system composed by a large number of heterogeneous individuals. These are divided into income classes and may as well have different tax evasion behaviors. The variation in time of the number of individuals in each class is described by a system of nonlinear differential equations of the kinetic discretized Boltzmann type involving transition probabilities. A priori, one could think that audits and fines should have a positive effect on the reduction of economic inequality and correspondingly of the Gini index G. According to our model, however, such effect is rather small. In contrast, the effect on the increase of the tax revenue may be significant.
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Latent trait cortisol (LTC) during pregnancy: Composition, continuity, change, and concomitants.
Giesbrecht, Gerald F; Bryce, Crystal I; Letourneau, Nicole; Granger, Douglas A
2015-12-01
Individual differences in the activity of the hypothalamic pituitary adrenal (HPA) axis are often operationalized using summary measures of cortisol that are taken to represent stable individual differences. Here we extend our understanding of a novel latent variable approach to latent trait cortisol (LTC) as a measure of trait-like HPA axis function during pregnancy. Pregnant women (n=380) prospectively collected 8 diurnal saliva samples (4 samples/day, 2 days) within each trimester. Saliva was assayed for cortisol. Confirmatory factor analyses were used to fit LTC models to early morning and daytime cortisol. For individual trimester data, only the daytime LTC models had adequate fit. These daytime LTC models were strongly correlated between trimesters and stable over pregnancy. Daytime LTC was unrelated to the cortisol awakening response and the daytime slope but strongly correlated with the area under the curve from ground. The findings support the validity of LTC as a measure of cortisol during pregnancy and suggest that it is not affected by pregnancy-related changes in HPA axis function. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Adediran, S A; Ratkowsky, D A; Donaghy, D J; Malau-Aduli, A E O
2012-09-01
Fourteen lactation models were fitted to average and individual cow lactation data from pasture-based dairy systems in the Australian states of Victoria and Tasmania. The models included a new "log-quadratic" model, and a major objective was to evaluate and compare the performance of this model with the other models. Nine empirical and 5 mechanistic models were first fitted to average test-day milk yield of Holstein-Friesian dairy cows using the nonlinear procedure in SAS. Two additional semiparametric models were fitted using a linear model in ASReml. To investigate the influence of days to first test-day and the number of test-days, 5 of the best-fitting models were then fitted to individual cow lactation data. Model goodness of fit was evaluated using criteria such as the residual mean square, the distribution of residuals, the correlation between actual and predicted values, and the Wald-Wolfowitz runs test. Goodness of fit was similar in all but one of the models in terms of fitting average lactation but they differed in their ability to predict individual lactations. In particular, the widely used incomplete gamma model most displayed this failing. The new log-quadratic model was robust in fitting average and individual lactations, and was less affected by sampled data and more parsimonious in having only 3 parameters, each of which lends itself to biological interpretation. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Mathematical modelling methodologies in predictive food microbiology: a SWOT analysis.
Ferrer, Jordi; Prats, Clara; López, Daniel; Vives-Rego, Josep
2009-08-31
Predictive microbiology is the area of food microbiology that attempts to forecast the quantitative evolution of microbial populations over time. This is achieved to a great extent through models that include the mechanisms governing population dynamics. Traditionally, the models used in predictive microbiology are whole-system continuous models that describe population dynamics by means of equations applied to extensive or averaged variables of the whole system. Many existing models can be classified by specific criteria. We can distinguish between survival and growth models by seeing whether they tackle mortality or cell duplication. We can distinguish between empirical (phenomenological) models, which mathematically describe specific behaviour, and theoretical (mechanistic) models with a biological basis, which search for the underlying mechanisms driving already observed phenomena. We can also distinguish between primary, secondary and tertiary models, by examining their treatment of the effects of external factors and constraints on the microbial community. Recently, the use of spatially explicit Individual-based Models (IbMs) has spread through predictive microbiology, due to the current technological capacity of performing measurements on single individual cells and thanks to the consolidation of computational modelling. Spatially explicit IbMs are bottom-up approaches to microbial communities that build bridges between the description of micro-organisms at the cell level and macroscopic observations at the population level. They provide greater insight into the mesoscale phenomena that link unicellular and population levels. Every model is built in response to a particular question and with different aims. Even so, in this research we conducted a SWOT (Strength, Weaknesses, Opportunities and Threats) analysis of the different approaches (population continuous modelling and Individual-based Modelling), which we hope will be helpful for current and future researchers.
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Tanaka, Yoshihisa; Nakamura, Shinichiro; Kuriyama, Shinichi; Ito, Hiromu; Furu, Moritoshi; Komistek, Richard D; Matsuda, Shuichi
2016-11-01
It is unknown whether a computer simulation with simple models can estimate individual in vivo knee kinematics, although some complex models have predicted the knee kinematics. The purposes of this study are first, to validate the accuracy of the computer simulation with our developed model during a squatting activity in a weight-bearing deep knee bend and then, to analyze the contact area and the contact stress of the tri-condylar implants for individual patients. We compared the anteroposterior (AP) contact positions of medial and lateral condyles calculated by the computer simulation program with the positions measured from the fluoroscopic analysis for three implanted knees. Then the contact area and the stress including the third condyle were calculated individually using finite element (FE) analysis. The motion patterns were similar in the simulation program and the fluoroscopic surveillance. Our developed model could nearly estimate the individual in vivo knee kinematics. The mean and maximum differences of the AP contact positions were 1.0mm and 2.5mm, respectively. At 120° of knee flexion, the contact area at the third condyle was wider than the both condyles. The mean maximum contact stress at the third condyle was lower than the both condyles at 90° and 120° of knee flexion. Individual bone models are required to estimate in vivo knee kinematics in our simple model. The tri-condylar implant seems to be safe for deep flexion activities due to the wide contact area and low contact stress. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Prioritizing Conservation of Ungulate Calving Resources in Multiple-Use Landscapes
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
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Vodosek, Markus
2009-04-01
Relational models theory (Fiske, 1991 ) proposes that all thinking about social relationships is based on four elementary mental models: communal sharing, authority ranking, equality matching, and market pricing. Triandis and his colleagues (e.g., Triandis, Kurowski, & Gelfand, 1994 ) have suggested a relationship between the constructs of horizontal and vertical individualism and collectivism and Fiske's relational models. However, no previous research has examined this proposed relationship empirically. The objective of the current study was to test the association between the two frameworks in order to further our understanding of why members of culturally diverse groups may prefer different relational models in interactions with other group members. Findings from this study support a relationship between Triandis' constructs and Fiske's four relational models and uphold Fiske's ( 1991 ) claim that the use of the relational models is culturally dependent. As hypothesized, horizontal collectivism was associated with a preference for equality matching and communal sharing, vertical individualism was related to a preference for authority ranking, and vertical collectivism was related to a preference for authority ranking and communal sharing. However, contrary to expectations, horizontal individualism was not related to a preference for equality matching and market pricing, and vertical individualism was not associated with market pricing. By showing that there is a relationship between Triandis' and Fiske's frameworks, this study closes a gap in relational models theory, namely how culture relates to people's preferences for relational models. Thus, the findings from this study will enable future researchers to explain and predict what relational models are likely to be used in a certain cultural context.
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Samson, F; Zeffiro, T A; Doyon, J; Benali, H; Mottron, L
2015-09-01
A continuum of phenotypes makes up the autism spectrum (AS). In particular, individuals show large differences in language acquisition, ranging from precocious speech to severe speech onset delay. However, the neurological origin of this heterogeneity remains unknown. Here, we sought to determine whether AS individuals differing in speech acquisition show different cortical responses to auditory stimulation and morphometric brain differences. Whole-brain activity following exposure to non-social sounds was investigated. Individuals in the AS were classified according to the presence or absence of Speech Onset Delay (AS-SOD and AS-NoSOD, respectively) and were compared with IQ-matched typically developing individuals (TYP). AS-NoSOD participants displayed greater task-related activity than TYP in the inferior frontal gyrus and peri-auditory middle and superior temporal gyri, which are associated with language processing. Conversely, the AS-SOD group only showed enhanced activity in the vicinity of the auditory cortex. We detected no differences in brain structure between groups. This is the first study to demonstrate the existence of differences in functional brain activity between AS individuals divided according to their pattern of speech development. These findings support the Trigger-threshold-target model and indicate that the occurrence of speech onset delay in AS individuals depends on the location of cortical functional reallocation, which favors perception in AS-SOD and language in AS-NoSOD. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Inter-individual variation in nutrient balancing in the honeybee (Apis mellifera).
Reade, Abbie J; Naug, Dhruba
2016-12-01
The Geometric Framework approach in nutritional ecology postulates that animals attempt to balance the consumption of different nutrients rather than simply maximizing energetic gain. The intake target with respect to each nutrient maximizes fitness in a specific dimension and any difference between individuals in intake target therefore represents alternative behavioral and fitness maximization strategies. Nutritional interactions are a central component of all social groups and any inter-individual variation in intake target should therefore have a significant influence on social dynamics. Using the honeybee colony as an experimental model, we quantified differences in the carbohydrate intake target of individual foragers using a capillary feeder (CAFE) assay. Our results show that the bees did not simply maximize their net energetic gain, but combined sugar and water in their diet in a way that brought them to an intake target equivalent to a 33% sucrose solution. Although the mean intake target with respect to the nutrients sucrose and water was the same under different food choice regimens, there was significant inter-individual variation in intake target and the manner in which individuals reached this target, a variation which suggests different levels of tolerance to nutrient imbalance. We discuss our results in the context of how colony performance may be influenced by the different nutrient balancing strategies of individual members and how such nutritional constraints could have contributed to the evolution of sociality. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Martin, Jordan S; Suarez, Scott A
2017-08-01
Interest in quantifying consistent among-individual variation in primate behavior, also known as personality, has grown rapidly in recent decades. Although behavioral coding is the most frequently utilized method for assessing primate personality, limitations in current statistical practice prevent researchers' from utilizing the full potential of their coding datasets. These limitations include the use of extensive data aggregation, not modeling biologically relevant sources of individual variance during repeatability estimation, not partitioning between-individual (co)variance prior to modeling personality structure, the misuse of principal component analysis, and an over-reliance upon exploratory statistical techniques to compare personality models across populations, species, and data collection methods. In this paper, we propose a statistical framework for primate personality research designed to address these limitations. Our framework synthesizes recently developed mixed-effects modeling approaches for quantifying behavioral variation with an information-theoretic model selection paradigm for confirmatory personality research. After detailing a multi-step analytic procedure for personality assessment and model comparison, we employ this framework to evaluate seven models of personality structure in zoo-housed bonobos (Pan paniscus). We find that differences between sexes, ages, zoos, time of observation, and social group composition contributed to significant behavioral variance. Independently of these factors, however, personality nonetheless accounted for a moderate to high proportion of variance in average behavior across observational periods. A personality structure derived from past rating research receives the strongest support relative to our model set. This model suggests that personality variation across the measured behavioral traits is best described by two correlated but distinct dimensions reflecting individual differences in affiliation and sociability (Agreeableness) as well as activity level, social play, and neophilia toward non-threatening stimuli (Openness). These results underscore the utility of our framework for quantifying personality in primates and facilitating greater integration between the behavioral ecological and comparative psychological approaches to personality research. © 2017 Wiley Periodicals, Inc.
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Dovgopoly, Alexander; Mercado, Eduardo
2013-06-01
Individuals with autism spectrum disorder (ASD) show atypical patterns of learning and generalization. We explored the possible impacts of autism-related neural abnormalities on perceptual category learning using a neural network model of visual cortical processing. When applied to experiments in which children or adults were trained to classify complex two-dimensional images, the model can account for atypical patterns of perceptual generalization. This is only possible, however, when individual differences in learning are taken into account. In particular, analyses performed with a self-organizing map suggested that individuals with high-functioning ASD show two distinct generalization patterns: one that is comparable to typical patterns, and a second in which there is almost no generalization. The model leads to novel predictions about how individuals will generalize when trained with simplified input sets and can explain why some researchers have failed to detect learning or generalization deficits in prior studies of category learning by individuals with autism. On the basis of these simulations, we propose that deficits in basic neural plasticity mechanisms may be sufficient to account for the atypical patterns of perceptual category learning and generalization associated with autism, but they do not account for why only a subset of individuals with autism would show such deficits. If variations in performance across subgroups reflect heterogeneous neural abnormalities, then future behavioral and neuroimaging studies of individuals with ASD will need to account for such disparities.
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Country of origin and bariatric surgery in Sweden during 2001–2010
Memarian, Ensieh; Sundquist, Kristina; Calling, Susanna; Sundquist, Jan; Li, Xinjun
2016-01-01
Background The prevalence of obesity, as well as use of bariatric surgery, has increased worldwide. The aim of the present study was to investigate the potential differences in the use of bariatric surgery among Swedes and immigrants in Sweden and whether the hypothesized differences remain after adjustment for socioeconomic factors. Methods A closed cohort of all individuals aged 20–64 years was followed during 2001–2010. Further analyses were performed in 2 periods separately (2001–2005 and 2006–2010). Age-standardized cumulative incidence rates (CR) of bariatric surgery were compared between Swedes and immigrants considering individual variables. Cox proportional hazards models were used in univariate and multivariate models for males and females. Results A total of 12,791 Swedes and 2060 immigrants underwent bariatric surgery. The lowest rates of bariatric surgery were found in immigrant men. The largest difference in CR between Swedes and immigrants was observed among low-income individuals (3.4 and 2.3 per 1000 individuals, respectively). Adjusted hazard ratios (HRs) were lower for all immigrants compared with Swedes in the second period. The highest HRs were observed among immigrants from Chile and Lebanon and the lowest among immigrants from Bosnia. Except for Nordic countries, immigrants from all other European countries had a lower HR compared with Swedes. Conclusions Men in general and some immigrant groups had a lower HR of bariatric surgery. Moreover, the difference between Swedes and immigrants was more pronounced in individuals with low socioeconomic status (income). It is unclear if underlying barriers to receive bariatric surgery are due to patients’ preferences/lack of knowledge or healthcare structures. Future studies are needed to examine potential causes behind these differences. PMID:25979207
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Country of origin and bariatric surgery in Sweden during 2001-2010.
Memarian, Ensieh; Sundquist, Kristina; Calling, Susanna; Sundquist, Jan; Li, Xinjun
2015-01-01
The prevalence of obesity, as well as use of bariatric surgery, has increased worldwide. The aim of the present study was to investigate the potential differences in the use of bariatric surgery among Swedes and immigrants in Sweden and whether the hypothesized differences remain after adjustment for socioeconomic factors. A closed cohort of all individuals aged 20-64 years was followed during 2001-2010. Further analyses were performed in 2 periods separately (2001-2005 and 2006-2010). Age-standardized cumulative incidence rates (CR) of bariatric surgery were compared between Swedes and immigrants considering individual variables. Cox proportional hazards models were used in univariate and multivariate models for males and females. A total of 12,791 Swedes and 2060 immigrants underwent bariatric surgery. The lowest rates of bariatric surgery were found in immigrant men. The largest difference in CR between Swedes and immigrants was observed among low-income individuals (3.4 and 2.3 per 1000 individuals, respectively). Adjusted hazard ratios (HRs) were lower for all immigrants compared with Swedes in the second period. The highest HRs were observed among immigrants from Chile and Lebanon and the lowest among immigrants from Bosnia. Except for Nordic countries, immigrants from all other European countries had a lower HR compared with Swedes. Men in general and some immigrant groups had a lower HR of bariatric surgery. Moreover, the difference between Swedes and immigrants was more pronounced in individuals with low socioeconomic status (income). It is unclear if underlying barriers to receive bariatric surgery are due to patients' preferences/lack of knowledge or healthcare structures. Future studies are needed to examine potential causes behind these differences. Copyright © 2015 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.
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Collective decision making and social interaction rules in mixed-species flocks of songbirds
Farine, Damien R.; Aplin, Lucy M.; Garroway, Colin J.; Mann, Richard P.; Sheldon, Ben C.
2014-01-01
Associations in mixed-species foraging groups are common in animals, yet have rarely been explored in the context of collective behaviour. Despite many investigations into the social and ecological conditions under which individuals should form groups, we still know little about the specific behavioural rules that individuals adopt in these contexts, or whether these can be generalized to heterospecifics. Here, we studied collective behaviour in flocks in a community of five species of woodland passerine birds. We adopted an automated data collection protocol, involving visits by RFID-tagged birds to feeding stations equipped with antennae, over two winters, recording 91 576 feeding events by 1904 individuals. We demonstrated highly synchronized feeding behaviour within patches, with birds moving towards areas of the patch with the largest proportion of the flock. Using a model of collective decision making, we then explored the underlying decision rule birds may be using when foraging in mixed-species flocks. The model tested whether birds used a different decision rule for conspecifics and heterospecifics, and whether the rules used by individuals of different species varied. We found that species differed in their response to the distribution of conspecifics and heterospecifics across foraging patches. However, simulating decisions using the different rules, which reproduced our data well, suggested that the outcome of using different decision rules by each species resulted in qualitatively similar overall patterns of movement. It is possible that the decision rules each species uses may be adjusted to variation in mean species abundance in order for individuals to maintain the same overall flock-level response. This is likely to be important for maintaining coordinated behaviour across species, and to result in quick and adaptive flock responses to food resources that are patchily distributed in space and time. PMID:25214653
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How the distance between regional and human mobility behavior affect the epidemic spreading
NASA Astrophysics Data System (ADS)
Wu, Minna; Han, She; Sun, Mei; Han, Dun
2018-02-01
The distance between different regions has a lot of impact on the individuals' mobility behavior. Meanwhile, the individuals' mobility could greatly affect the epidemic propagation way. By researching the individuals' mobility behavior, we establish the coupled dynamic model for individual mobility and transmission of infectious disease. The basic reproduction number is theoretically obtained according to the next-generation matrix method. Through this study, we may get that the stability state of the epidemic system will be prolonged under a higher commuting level. The infection density is almost the same in different regions over a sufficiently long time. The results show that, due to the individual movement, the origin of virus can only speed up or delay the outbreak of infectious diseases, however, it have little impact on the final infection size.
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Penas Steinhardt, Alberto; López, Ariel Pablo; González, Claudio Daniel; Vilariño, Jorge; Frechtel, Gustavo Daniel; Cerrone, Gloria Edith
2017-01-01
The Metabolic Syndrome (MetS) is a cluster of cardiometabolic risk factors, usually accompanied by the presence of insulin resistance (IR) and a systemic subclinical inflammation state. Metabolically healthy obese (MHO) individuals seem to be protected against cardiometabolic complications. The aim of this work was to characterize phenotypically the low-grade inflammation and the IR in MHO individuals in comparison to obese individuals with MetS and control non obese. We studied two different populations: 940 individuals from the general population of Buenos Aires and 518 individuals from the general population of Venado Tuerto; grouped in three groups: metabolically healthy non-obese individuals (MHNO), MHO and obese individuals with MetS (MSO). Inflammation was measured by the levels of hs-CRP (high-sensitivity C reactive protein), and we found that MHO presented an increase in inflammation when compared with MHNO (Buenos Aires: p<0.001; Venado Tuerto: p<0.001), but they did not differ from MSO. To evaluate IR we analyzed the HOMA (Homoeostatic Model Assessment) values, and we found differences between MHO and MSO (Buenos Aires: p<0.001; Venado Tuerto: p<0.001), but not between MHNO and MHO. In conclusion, MHO group would be defined as a subgroup of obese individuals with an intermediate phenotype between MHNO and MSO individuals considering HOMA, hs-CRP and central obesity. PMID:29284058
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Active Aging in Very Old Age and the Relevance of Psychological Aspects.
Paúl, Constança; Teixeira, Laetitia; Ribeiro, Oscar
2017-01-01
Active aging encompasses a socially and individually designed mix of different domains that range from personal and familial, to social and professional. In being a key policy concept often focused on the young-old individuals, efforts in studying its dimensions in advanced ages have seldom been made. Nevertheless, there is a recognized need to promote adequate responses to the growing number of individuals reaching advanced ages and to recognize their specific dependability on health-related aspects, services attendance, social interactions, or on psychological characteristics for what it means to "age actively." This study provides a secondary analysis of data and follows the preceding work on the operationalization of the World Health Organization's (WHO) active aging model by means of an assessment protocol to measure which variables, within the model's determinants, contribute the most for an active aging process (1). Authors used the achieved model (composed by six factors: health, psychological component, cognitive performance, social relationships, biological component, and personality) and performed multi-group analysis of structural invariance to examine hypothetical differences between age groups (<75 years vs. ≥75 years) and to contrast obtained findings with the originally achieved model for the total sample (1,322 individuals aged 55 +). The structural covariances for the two age groups were statistically different. The comparison of components between age groups revealed a major relevance of the psychological component for the older age group. These findings reinforce the importance of psychological functioning in active aging in oldest old, and the need for further research on specific psychological features underlying the subjective meaning of active aging in more advanced ages.
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Connor, Phillip; Koenig, Matthias
2015-01-01
It is well-documented that Muslims experience economic disadvantages in Western European labor markets. However, few studies comprehensively test individual-level explanations for the Muslim employment gap. Using data from the European Social Survey, this research note briefly examines the role of individual-level differences between Muslims and non-Muslims in mediating employment differences. Results reveal that human capital, migration background, religiosity, cultural values, and perceptions of discrimination jointly account for about 40% of the employment variance between Muslims and non-Muslims. Model specifications for first- and second-generation Muslim immigrants reveal a similar pattern, with migration background and perceived discrimination being of key relevance in mediating employment difference. While individual-level effects are indeed relevant, unexplained variance suggests that symbolic boundaries against Islam may still translate into tangible ethno-religious penalties. Copyright © 2014 Elsevier Inc. All rights reserved.
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Computational Modeling of Morphological Effects in Bangla Visual Word Recognition.
Dasgupta, Tirthankar; Sinha, Manjira; Basu, Anupam
2015-10-01
In this paper we aim to model the organization and processing of Bangla polymorphemic words in the mental lexicon. Our objective is to determine whether the mental lexicon accesses a polymorphemic word as a whole or decomposes the word into its constituent morphemes and then recognize them accordingly. To address this issue, we adopted two different strategies. First, we conduct a masked priming experiment over native speakers. Analysis of reaction time (RT) and error rates indicates that in general, morphologically derived words are accessed via decomposition process. Next, based on the collected RT data we have developed a computational model that can explain the processing phenomena of the access and representation of Bangla derivationally suffixed words. In order to do so, we first explored the individual roles of different linguistic features of a Bangla morphologically complex word and observed that processing of Bangla morphologically complex words depends upon several factors like, the base and surface word frequency, suffix type/token ratio, suffix family size and suffix productivity. Accordingly, we have proposed different feature models. Finally, we combine these feature models together and came up with a new model that takes the advantage of the individual feature models and successfully explain the processing phenomena of most of the Bangla morphologically derived words. Our proposed model shows an accuracy of around 80% which outperforms the other related frequency models.
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The role of scripts in personal consistency and individual differences.
Demorest, Amy; Popovska, Ana; Dabova, Milena
2012-02-01
This article examines the role of scripts in personal consistency and individual differences. Scripts are personally distinctive rules for understanding emotionally significant experiences. In 2 studies, scripts were identified from autobiographical memories of college students (Ns = 47 and 50) using standard categories of events and emotions to derive event-emotion compounds (e.g., Affiliation-Joy). In Study 1, scripts predicted responses to a reaction-time task 1 month later, such that participants responded more quickly to the event from their script when asked to indicate what emotion would be evoked by a series of events. In Study 2, individual differences in 5 common scripts were found to be systematically related to individual differences in traits of the Five-Factor Model. Distinct patterns of correlation revealed the importance of studying events and emotions in compound units, that is, in script form (e.g., Agreeableness was correlated with the script Affiliation-Joy but not with the scripts Fun-Joy or Affiliation-Love). © 2012 The Authors. Journal of Personality © 2012, Wiley Periodicals, Inc.
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Naber, Marnix; Vedder, Anneke; Brown, Stephen B R E; Nieuwenhuis, Sander
2016-01-01
The Stroop task is a popular neuropsychological test that measures executive control. Strong Stroop interference is commonly interpreted in neuropsychology as a diagnostic marker of impairment in executive control, possibly reflecting executive dysfunction. However, popular models of the Stroop task indicate that several other aspects of color and word processing may also account for individual differences in the Stroop task, independent of executive control. Here we use new approaches to investigate the degree to which individual differences in Stroop interference correlate with the relative processing speed of word and color stimuli, and the lateral inhibition between visual stimuli. We conducted an electrophysiological and behavioral experiment to measure (1) how quickly an individual's brain processes words and colors presented in isolation (P3 latency), and (2) the strength of an individual's lateral inhibition between visual representations with a visual illusion. Both measures explained at least 40% of the variance in Stroop interference across individuals. As these measures were obtained in contexts not requiring any executive control, we conclude that the Stroop effect also measures an individual's pre-set way of processing visual features such as words and colors. This study highlights the important contributions of stimulus processing speed and lateral inhibition to individual differences in Stroop interference, and challenges the general view that the Stroop task primarily assesses executive control.
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Link prediction measures considering different neighbors’ effects and application in social networks
NASA Astrophysics Data System (ADS)
Luo, Peng; Wu, Chong; Li, Yongli
Link prediction measures have been attracted particular attention in the field of mathematical physics. In this paper, we consider the different effects of neighbors in link prediction and focus on four different situations: only consider the individual’s own effects; consider the effects of individual, neighbors and neighbors’ neighbors; consider the effects of individual, neighbors, neighbors’ neighbors, neighbors’ neighbors’ neighbors and neighbors’ neighbors’ neighbors’ neighbors; consider the whole network participants’ effects. Then, according to the four situations, we present our link prediction models which also take the effects of social characteristics into consideration. An artificial network is adopted to illustrate the parameter estimation based on logistic regression. Furthermore, we compare our methods with the some other link prediction methods (LPMs) to examine the validity of our proposed model in online social networks. The results show the superior of our proposed link prediction methods compared with others. In the application part, our models are applied to study the social network evolution and used to recommend friends and cooperators in social networks.
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How cognitive heuristics can explain social interactions in spatial movement.
Seitz, Michael J; Bode, Nikolai W F; Köster, Gerta
2016-08-01
The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as 'stop if another step would lead to a collision' or 'follow the person in front'. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour. © 2016 The Author(s).
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How cognitive heuristics can explain social interactions in spatial movement
Köster, Gerta
2016-01-01
The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as ‘stop if another step would lead to a collision’ or ‘follow the person in front’. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour. PMID:27581483