Relations between the attentional blink and aspects of psychometric intelligence: A fixed-links modeling approach

The attentional blink phenomenon (AB) represents impaired identification of the second of two targets presented in rapid succession within a stream of stimuli. Despite the well-known association between attentional processes and psychometric intelligence (PI), evidence for a relationship between AB and PI is highly inconsistent. Theory and empirical findings suggest AB to be multifaceted. Hence, relations between AB and PI may be blurred when AB is measured as a single process. Furthermore, different aspects of PI might be differentially related to AB. The present study explored the relationship between processes underlying AB and general PI as well as specific aspects of PI (Reasoning, Speed, Memory, and Creativity) in 201 female students. Fixed-links modeling revealed three processes underlying AB: (1) a U-shaped process positively related to Speed and negatively related to Memory but unrelated to Reasoning, Creativity, and general PI, (2) an increasing process positively related to Reasoning, Speed, Memory, and general PI but not to Creativity, and (3) a decreasing process positively related to general PI and Memory but not to other aspects of PI. Our findings demonstrate that dissociating processes underlying AB and considering specific aspects of PI is required to understand the relationship between AB and PI.

The assessment of visual short-term memory in considering the underlying processes and their relation to psychometric intelligence

By means of fixed-links modeling the present study assessed processes involved in visual short-term memory functioning and investigates how these processes are related to intelligence. Using a color change detection task, short-term memory demands increased across three experimental conditions as a function of number of presented stimuli. We measured amount of information retained in visual short-term memory by hit rate as well as speed of visual short-term memory scanning by reaction time. For both measures, fixed-links modeling revealed a constant process reflecting processes irrespective of task manipulation as well as two increasing processes reflecting the increasing short-term memory demands. For visual short-term memory scanning, a negative association between intelligence and the constant process was found but no relationship between intelligence and the increasing processes. Thus, basic processing speed, rather than speed influenced by visual short-term memory demands, differentiates between high- and low-intelligent individuals. Intelligence was positively related to the experimental processes of shortterm memory retention but not to the constant process. In sum, significant associations with intelligence were only obtained when the specific processes of short-term memory were decomposed emphasizing the importance of a thorough assessment of cognitive processes when investigating their relation to intelligence.

Sensory discrimination, working memory and intelligence in 9-year-old and 11-year-old children

More than a century ago, Galton and Spearman suggested that there was a functional relationship between sensory discrimination ability and intelligence. Studies have since been able to confirm a close relationship between general discrimination ability (GDA) and IQ. The aim of the present study was to assess whether this strong relationship between GDA and IQ could be due to working memory (WM) demands of GDA tasks. A sample of 140 children (seventy 9-year-olds and seventy 11-year-olds) was studied. Results showed that there was a significant overlap between WM, GDA and fluid intelligence. Furthermore, results also revealed that WM could not explain the relationship between GDA and fluid intelligence as such, but that it acted as a bottleneck of information processing, limiting the influence of GDA on the prediction of fluid intelligence. Specifically, GDA's influence on the prediction of intelligence was only visible when WM capacity was above a certain level.

Net CO 2 surface emissions at Bern, Switzerland inferred from ambient observations of CO 2 , δ(O 2 /N 2 ), and 222 Rn using a customized radon tracer inversion

The 222Radon tracer method is a powerful tool to estimate local and regional surface emissions of, e.g., greenhouse gases. In this paper we demonstrate that in practice, the method as it is commonly used, produces inaccurate results in case of nonhomogeneously spread emission sources, and we propose a different approach to account for this. We have applied the new methodology to ambient observations of CO2 and 222Radon to estimate CO2 surface emissions for the city of Bern, Switzerland. Furthermore, by utilizing combined measurements of CO2 and δ(O2/N2) we obtain valuable information about the spatial and temporal variability of the main emission sources. Mean net CO2 emissions based on 2 years of observations are estimated at (11.2 ± 2.9) kt km−2 a−1. Oxidative ratios indicate a significant influence from the regional biosphere in summer/spring and fossil fuel combustion processes in winter/autumn. Our data indicate that the emissions from fossil fuels are, to a large degree, related to the combustion of natural gas which is used for heating purposes.

Sonic intelligence as a virtual therapeutic environment

This paper reports on the results of a research project, on comparing one virtual collaborative environment with a first-person visual immersion (first-perspective interaction) and a second one where the user interacts through a sound-kinetic virtual representation of himself (avatar), as a stress-coping environment in real-life situations. Recent developments in coping research are proposing a shift from a trait-oriented approach of coping to a more situation-specific treatment. We defined as real-life situation a target-oriented situation that demands a complex coping skills inventory of high self-efficacy and internal or external "locus of control" strategies. The participants were 90 normal adults with healthy or impaired coping skills, 25-40 years of age, randomly spread across two groups. There was the same number of participants across groups and gender balance within groups. All two groups went through two phases. In Phase I, Solo, one participant was assessed using a three-stage assessment inspired by the transactional stress theory of Lazarus and the stress inoculation theory of Meichenbaum. In Phase I, each participant was given a coping skills measurement within the time course of various hypothetical stressful encounters performed in two different conditions and a control group. In Condition A, the participant was given a virtual stress assessment scenario relative to a first-person perspective (VRFP). In Condition B, the participant was given a virtual stress assessment scenario relative to a behaviorally realistic motion controlled avatar with sonic feedback (VRSA). In Condition C, the No Treatment Condition (NTC), the participant received just an interview. In Phase II, all three groups were mixed and exercised the same tasks but with two participants in pairs. The results showed that the VRSA group performed notably better in terms of cognitive appraisals, emotions and attributions than the other two groups in Phase I (VRSA, 92%; VRFP, 85%; NTC, 34%). In Phase II, the difference again favored the VRSA group against the other two. These results indicate that a virtual collaborative environment seems to be a consistent coping environment, tapping two classes of stress: (a) aversive or ambiguous situations, and (b) loss or failure situations in relation to the stress inoculation theory. In terms of coping behaviors, a distinction is made between self-directed and environment-directed strategies. A great advantage of the virtual collaborative environment with the behaviorally enhanced sound-kinetic avatar is the consideration of team coping intentions in different stages. Even if the aim is to tap transactional processes in real-life situations, it might be better to conduct research using a sound-kinetic avatar based collaborative environment than a virtual first-person perspective scenario alone. The VE consisted of two dual-processor PC systems, a video splitter, a digital camera and two stereoscopic CRT displays. The system was programmed in C++ and VRScape Immersive Cluster from VRCO, which created an artificial environment that encodes the user's motion from a video camera, targeted at the face of the users and physiological sensors attached to the body.

Performance on auditory and visual temporal informationprocessing is related to psychometric intelligence

The present study investigated the relationship between psychometric intelligence and temporal resolution power (TRP) as simultaneously assessed by auditory and visual psychophysical timing tasks. In addition, three different theoretical models of the functional relationship between TRP and psychometric intelligence as assessed by means of the Adaptive Matrices Test (AMT) were developed. To test the validity of these models, structural equation modeling was applied. Empirical data supported a hierarchical model that assumed auditory and visual modality-specific temporal processing at a first level and amodal temporal processing at a second level. This second-order latent variable was substantially correlated with psychometric intelligence. Therefore, the relationship between psychometric intelligence and psychophysical timing performance can be explained best by a hierarchical model of temporal information processing.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases

This chapter presents fuzzy cognitive maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. The corresponding Web KnowARR framework incorporates findings from fuzzy logic. To this end, a first emphasis is particularly on the Web KnowARR framework along with a stakeholder management use case to illustrate the framework’s usefulness as a second focal point. This management form is to help projects to acceptance and assertiveness where claims for company decisions are actively involved in the management process. Stakeholder maps visually (re-) present these claims. On one hand, they resort to non-public content and on the other they resort to content that is available to the public (mostly on the Web). The Semantic Web offers opportunities not only to present public content descriptively but also to show relationships. The proposed framework can serve as the basis for the public content of stakeholder maps.

Individual differences in working memory capacity explain the relationship between general discrimination ability and psychometric intelligence

The close association between psychometric intelligence and general discrimination ability (GDA), conceptualized as latent variable derived from performance on different sensory discrimination tasks, is empirically well-established but theoretically widely unclear. The present study contrasted two alternative explanations for this association. The first explanation is based on what Spearman (1904) referred to as a central function underlying this relationship in the sense of the g factor of intelligence and becoming most evident in GDA. In this case, correlations between different aspects of cognitive abilities, such as working memory (WM) capacity, and psychometric intelligence should be mediated by GDA if their correlation is caused by g. Alternatively, the second explanation for the relationship between psychometric intelligence and GDA proceeds from fMRI studies which emphasize the role of WM functioning for sensory discrimination. Given the well-known relationship between WM and psychometric intelligence, the relationship between GDA and psychometric intelligence might be attributed to WM. The present study investigated these two alternative explanations at the level of latent variables. In 197 young adults, a model in which WM mediated the relationship between GDA and psychometric intelligence described the data better than a model in which GDA mediated the relationship between WM and psychometric intelligence. Moreover, GDA failed to explain portions of variance of psychometric intelligence above and beyond WM. These findings clearly support the view that the association between psychometric intelligence and GDA must be understood in terms of WM functioning.