1,382 research outputs found

    A Bayesian Assessment of Real-World Behavior During Multitasking

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    Multitasking is common in everyday life, but its effect on activities of daily living is not well understood. Critical appraisal of performance for both healthy individuals and patients is required. Motor activities during meal preparation were monitored in healthy individuals with a wearable sensor network during single and multitask conditions. Motor performance was quantified by the median frequencies (f m) of hand trajectories and wrist accelerations. The probability that multitasking occurred based on the obtained motor information was estimated using a NaĂŻve Bayes Model, with a specific focus on the single and triple loading conditions. The Bayesian probability estimator showed task distinction for the wrist accelerometer data at the high and low value ranges. The likelihood of encountering a certain motor performance during well-established everyday activities, such as preparing a simple meal, changed when additional (cognitive) tasks were performed. Within a healthy population, the probability of lower acceleration frequency patterns increases when people are asked to multitask. Cognitive decline due to aging or disease might yield even greater differences

    Validation of the Virtual Reality Everyday Assessment Lab (VR-EAL):An immersive virtual reality neuropsychological battery with enhanced ecological validity

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    International audienceObjective: The assessment of cognitive functions such as prospective memory, episodic memory, attention, and executive functions benefits from an ecologically valid approach to better understand how performance outcomes generalize to everyday life. Immersive virtual reality (VR) is considered capable of simulating real-life situations to enhance ecological validity. The present study attempted to validate the Virtual Reality Everyday Assessment Lab (VR-EAL), an immersive VR neuropsychological battery, against an extensive paper-andpencil neuropsychological battery. Methods: Forty-one participants (21 females) were recruited: 18 gamers and 23 non-gamers who attended both an immersive VR and a paper-and-pencil testing session. Bayesian Pearson correlation analyses were conducted to assess construct and convergent validity of the VR-EAL. Bayesian t-tests were performed to compare VR and paper-and-pencil testing in terms of administration time, similarity to real life tasks (i.e., ecological validity), and pleasantness. Results: VR-EAL scores were significantly correlated with their equivalent scores on the paper-and-pencil tests. The participants' reports indicated that the VR-EAL tasks were significantly more ecologically valid and pleasant than the paper-and-pencil neuropsychological battery. The VR-EAL battery also had a shorter administration time. Conclusion: The VR-EAL appears as an effective neuropsychological tool for the assessment of everyday cognitive functions, which has enhanced ecological validity, a highly pleasant testing experience, and does not induce cybersickness

    Cognitive workload measurement and modeling under divided attention

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    Motorists often engage in secondary tasks unrelated to driving that increase cognitive workload, resulting in fatal crashes and injuries. An International Standards Organization method for measuring a driver's cognitive workload, the detection response task (DRT), correlates well with driving outcomes, but investigation of its putative theoretical basis in terms of finite attention capacity remains limited. We address this knowledge gap using evidence-accumulation modeling of simple and choice versions of the DRT in a driving scenario. Our experiments demonstrate how dual-task load affects the parameters of evidence-accumulation models. We found that the cognitive workload induced by a secondary task (counting backward by 3s) reduced the rate of evidence accumulation, consistent with rates being sensitive to limited-capacity attention. We also found a compensatory increase in the amount of evidence required for a response and a small speeding in the time for nondecision processes. The International Standards Organization version of the DRT was found to be most sensitive to cognitive workload. A Wald-distributed evidence-accumulation model augmented with a parameter measuring response omissions provided a parsimonious measure of the underlying causes of cognitive workload in this task. This work demonstrates that evidence-accumulation modeling can accurately represent data produced by cognitive workload measurements, reproduce the data through simulation, and provide supporting evidence for the cognitive processes underlying cognitive workload. Our results provide converging evidence that the DRT method is sensitive to dynamic fluctuations in limited-capacity attention

    Prediction Techniques in Internet of Things (IoT) Environment: A Comparative Study

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    Socialization and Personalization in Internet of Things (IOT) environment are the current trends in computing research. Most of the research work stresses the importance of predicting the service & providing socialized and personalized services. This paper presents a survey report on different techniques used for predicting user intention in wide variety of IOT based applications like smart mobile, smart television, web mining, weather forecasting, health-care/medical, robotics, road-traffic, educational data mining, natural calamities, retail banking, e-commerce, wireless networks & social networking. As per the survey made the prediction techniques are used for: predicting the application that can be accessed by the mobile user, predicting the next page to be accessed by web user, predicting the users favorite TV program, predicting user navigational patterns and usage needs on websites & also to extract the users browsing behavior, predicting future climate conditions, predicting whether a patient is suffering from a disease, predicting user intention to make implicit and human-like interactions possible by accepting implicit commands, predicting the amount of traffic occurring at a particular location, predicting student performance in schools & colleges, predicting & estimating the frequency of natural calamities occurrences like floods, earthquakes over a long period of time & also to take precautionary measures, predicting & detecting false user trying to make transaction in the name of genuine user, predicting the actions performed by the user to improve the business, predicting & detecting the intruder acting in the network, predicting the mood transition information of the user by using context history, etc. This paper also discusses different techniques like Decision Tree algorithm, Artificial Intelligence and Data Mining based Machine learning techniques, Content and Collaborative based Recommender algorithms used for prediction

    Permanently online and permanently connected : development and validation of the Online Vigilance Scale

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    Smartphones and other mobile devices have fundamentally changed patterns of Internet use in everyday life by making online access constantly available. The present paper offers a theoretical explication and empirical assessment of the concept of online vigilance, referring to users’ permanent cognitive orientation towards online content and communication as well as their disposition to exploit these options constantly. Based on four studies, a validated and reliable self-report measure of online vigilance was developed. In combination, the results suggest that the Online Vigilance Scale (OVS) shows a stable factor structure in various contexts and user populations and provides future work in communication, psychology, and other social sciences with a new measure of the individual cognitive orientation towards ubiquitous online communication

    Cognitive control in media multitaskers:Two replication studies and a meta-Analysis

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    Ophir, Nass, and Wagner (2009, Proceedings of the National Academy of Sciences of the United States of America, 106(37), 15583–15587) found that people with high scores on the media-use questionnaire—a questionnaire that measures the proportion of media-usage time during which one uses more than one medium at the same time—show impaired performance on various tests of distractor filtering. Subsequent studies, however, did not all show this association between media multitasking and distractibility, thus casting doubt on the reliability of the initial findings. Here, we report the results of two replication studies and a meta-analysis that included the results from all published studies into the relationship between distractor filtering and media multitasking. Our replication studies included a total of 14 tests that had an average replication power of 0.81. Of these 14 tests, only five yielded a statistically significant effect in the direction of increased distractibility for people with higher scores on the media-use questionnaire, and only two of these effects held in a more conservative Bayesian analysis. Supplementing these outcomes, our meta-analysis on a total of 39 effect sizes yielded a weak but significant association between media multitasking and distractibility that turned nonsignificant after correction for small-study effects. Taken together, these findings lead us to question the existence of an association between media multitasking and distractibility in laboratory tasks of information processing

    Immersive virtual reality methods in cognitive neuroscience and neuropsychology: the Virtual Reality Everyday Assessment Lab (VR-EAL).an immersive neuropsychological test battery of everyday cognitive functions

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    In cognitive neuroscience and neuropsychology, the collection of cognitive and behavioural data is predominantly achieved by implementing paper-and-pencil and computerized (i.e., 2D and 3D applications) assessments. However, these psychometric tools in clinics and/or laboratories display several limitations and discrepancies between the observed performance in the laboratory/clinic and the actual performance of individuals in everyday life. The functional and predictive association between an individual's performance on a set of neuropsychological tests and the individual's performance in various everyday life settings is called ecological validity. Ecological validity is considered an important issue that cannot be resolved by the currently available assessment tools. Virtual reality head-mounted displays (HMD) appear to be effective research tools, which may address the problem of ecological validity in neuropsychological testing. However, their widespread implementation is hindered by virtual reality induced symptoms and effects (VRISE) and the lack of skills in virtual reality software development. In this PhD, a technological systematic literature review of the reasons for adverse symptomatology was conducted and suggestions and technological knowledge for the implementation of virtual reality HMD systems in cognitive neuroscience provided. The review indicated features pertinent to display, sound, motion tracking, navigation, ergonomic interactions, user experience, and computer hardware that should be considered by researchers. Subsequently, a meta-analysis of 44 neuroscientific or neuropsychological studies involving virtual reality HMD systems was performed. The meta-analysis of the virtual reality studies demonstrated that new generation HMDs induce significantly less VRISE and marginally fewer dropouts. Importantly, the commercial versions of the new generation HMDs with ergonomic interactions had zero incidents of adverse symptomatology and dropouts. HMDs equivalent to or greater than the commercial versions of contemporary HMDs accompanied with ergonomic interactions are suitable for implementation in cognitive neuroscience. Another aim of this PhD was to devise a brief tool to appraise and report both the quality of software features and VRISE intensity quantitatively; such a tool does not currently exist. The Virtual Reality Neuroscience Questionnaire (VRNQ; Kourtesis et al., 2019) was developed to assess the quality of virtual reality software in terms of user experience, game mechanics, in-game assistance, and VRISE. Forty participants aged between 28 and 43 years were recruited (18 gamers and 22 non-gamers) for the study. They participated in 3 different virtual reality sessions until they felt weary or discomfort and subsequently filled in the VRNQ. The results demonstrated that VRNQ is a valid tool for assessing virtual reality software as it has good convergent, discriminant, and construct validity. The maximum duration of virtual reality sessions should be between 55 and 70 min when the virtual reality software meets or exceeds the parsimonious cut-offs of the VRNQ, and the users are familiarized with the virtual reality system. Also, gaming experience does not affect how long virtual reality sessions should last. Furthermore, while the quality of virtual reality software substantially modulates the maximum duration of virtual reality sessions, age and education do not. Finally, deeper immersion, better quality of graphics and sound, and more helpful in-game instructions and prompts were found to reduce VRISE intensity. The VRNQ facilitates the brief assessment and reporting of the quality of virtual reality software features and/or the intensity of VRISE, while its minimum and parsimonious cut-offs may appraise the suitability of virtual reality software for implementation in research and clinical settings. However, the development of virtual reality software is predominantly dependent on third parties (e.g., freelancers or companies) with programming and software development skills. A solution that will promote the adoption of immersive virtual reality as a research and clinical tool might be the in-house development of virtual reality research/clinical software by computer science literate cognitive scientists or research software engineers. In Chapter 4, guidelines are offered for the development of virtual reality software in cognitive neuroscience and neuropsychology, by describing and discussing the stages of the development of Virtual Reality Everyday Assessment Lab (VR-EAL), the first neuropsychological battery in immersive virtual reality. Techniques for evaluating cognitive functions within a realistic storyline are discussed. The utility of various assets in Unity, software development kits, and other software are described so that cognitive scientists can overcome challenges pertinent to VRISE and the quality of the virtual reality software. In addition, VR-EAL is evaluated in accordance with the necessary criteria for virtual reality software for research purposes. The virtual reality neuroscience questionnaire (VRNQ) was implemented to appraise the quality of the three versions of VR-EAL in terms of user experience, game mechanics, in-game assistance, and VRISE. Twenty-five participants aged between 20 and 45 years with 12–16 years of full-time education evaluated various versions of VR-EAL. The final version of VR-EAL achieved high scores in every sub-score of the VRNQ and exceeded its parsimonious cut-offs. It also appeared to have better in-game assistance and game mechanics, while its improved graphics substantially increased the quality of the user experience and almost eradicated VRISE. The results substantially support the feasibility of the development of effective virtual reality research and clinical software without the presence of VRISE during a 60-min virtual reality session. In Chapter 5, validation of VR-EAL as an assessment of prospective memory, episodic memory, attention, and executive functions using an ecologically valid approach is examined. Performance on the VR-EAL, an immersive virtual reality neuropsychological battery, is examined against an extensive paper-and-pencil neuropsychological battery. Forty-one participants (21 females) were recruited: 18 gamers and 23 non-gamers who attended both an immersive virtual reality and a paper-and-pencil testing session. Bayesian Pearson correlation analyses were conducted to assess construct and convergent validity of the VR-EAL. Bayesian t-tests were performed to compare virtual reality and paper-and-pencil testing in terms of administration time, similarity to real life tasks (i.e., ecological validity), and pleasantness. VR-EAL scores were significantly correlated with their equivalent scores on the paper-and-pencil tests. The participants’ reports indicated that the VR-EAL tasks were considered significantly more ecologically valid and pleasant than the paper-and-pencil neuropsychological battery. The VR-EAL battery also had a shorter administration time. The VR-EAL appears to be an effective neuropsychological tool for the assessment of everyday cognitive functions, and has enhanced ecological validity, a highly pleasant testing experience, and does not induce cybersickness. In the final part of this thesis, the preparatory attentional and memory (PAM) and the multiprocess theories of prospective memory are examined by attempting to identify the cognitive functions which may predict the individual’s performance on ecologically valid prospective memory tasks in the same group of participants described in Chapter 5. Bayesian t-tests were conducted to explore the differences among different prospective memory tasks (e.g., event-based and time-based) and prospective memory tasks with varying delays between encoding and the recall of the intended action (e.g., short-delay versus long-delay). Bayesian linear regression analyses were performed to examine the predictors of VR-EAL scores. The results revealed that the type of prospective memory task does not play a significant role in everyday prospective memory functioning, but instead the length of delay between encoding and retrieving the prospective memory intention plays a central role. Support for the PAM and MP frameworks was found in non-focal and focal event-based tasks respectively. However, the findings, inferring a dynamic interplay between automatic and intentional monitoring and retrieval processes, agree with the inclusive approach of the multiprocess framework. Also, the role of executive functions appears crucial in everyday PM. Finally, everyday PM is predominantly facilitated by episodic memory, visuospatial attention, auditory attention, and executive functions. In conclusion, this PhD thesis attempted to show how immersive virtual reality research methods may be implemented efficiently without the confounding effect of cybersickness symptomatology in order to enhance the ecological validity of neuropsychological testing and contribute to our understanding of everyday cognitive ability

    Video gaming in a hyperconnected world : a cross-sectional study of heavy gaming, problematic gaming symptoms, and online socializing in adolescents

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    Aims: Examining online social interactions along with patterns of video gaming behaviors and game addiction symptoms has the potential to enrich our understanding of disorders related to excessive video game play. Methods: We performed latent class analysis in a sample of 9733 adolescents based on heavy use of games, social networking and instant messaging, and game addiction symptoms. We used latent class regression to determine associations between classes, psychosocial well-being and friendship quality. Results: We identified two types of heavy gaming classes that differed in probability of online social interaction. Classes with more online social interaction reported fewer problematic gaming symptoms than those with less online social interaction. Most adolescents estimated to be in heavy gaming classes had more depressive symptoms than normative classes. Male non-social gamers had more social anxiety. Female social gamers had less social anxiety and loneliness, but lower self-esteem. Friendship quality attenuated depression in some male social gamers, but strengthened associations with loneliness in some male non-social gamers. Conclusions: In adolescents, symptoms of video game addiction depend not only on video game play but also on concurrent levels of online communication, and those who are very socially active online report fewer symptoms of game addiction
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