Childhood Trauma and PTSD symptoms increase the risk of cognitive impairment in a sample of former indetured child laborers in old Age.

A growing body of evidence suggests a link between early childhood trauma, post-traumatic stress disorder (PTSD) and higher risk for dementia in old age. The aim of the present study was to investigate the association between childhood trauma exposure, PTSD and neurocognitive function in a unique cohort of former indentured Swiss child laborers in their late adulthood. To the best of our knowledge this is the first study ever conducted on former indentured child laborers and the first to investigate the relationship between childhood versus adulthood trauma and cognitive function. According to PTSD symptoms and whether they experienced childhood trauma (CT) or adulthood trauma (AT), participants (n = 96) were categorized as belonging to one of four groups: CT/PTSD+, CT/PTSD-, AT/PTSD+, AT/PTSD-. Information on cognitive function was assessed using the Structured Interview for Diagnosis of Dementia of Alzheimer Type, Multi-infarct Dementia and Dementia of other Etiology according to ICD-10 and DSM-III-R, the Mini-Mental State Examination, and a vocabulary test. Depressive symptoms were investigated as a potential mediator for neurocognitive functioning. Individuals screening positively for PTSD symptoms performed worse on all cognitive tasks compared to healthy individuals, independent of whether they reported childhood or adulthood adversity. When controlling for depressive symptoms, the relationship between PTSD symptoms and poor cognitive function became stronger. Overall, results tentatively indicate that PTSD is accompanied by cognitive deficits which appear to be independent of earlier childhood adversity. Our findings suggest that cognitive deficits in old age may be partly a consequence of PTSD or at least be aggravated by it. However, several study limitations need to considered. Consideration of cognitive deficits when treating PTSD patients and victims of lifespan trauma (even without a diagnosis of a psychiatric condition) is crucial. Furthermore, early intervention may prevent long-term deficits in memory function and development of dementia in adulthood.

Applying the Fuzzy Analytical Hierarchy Process in Cognitive Cities

This paper introduces a mobile application (app) as the first part of an interactive framework. The framework enhances the inter-action between cities and their citizens, introducing the Fuzzy Analytical Hierarchy Process (FAHP) as a potential information acquisition method to improve existing citizen management en-deavors for cognitive cities. Citizen management is enhanced by advanced visualization using Fuzzy Cognitive Maps (FCM). The presented app takes fuzziness into account in the constant inter-action and continuous development of communication between cities or between certain of their entities (e.g., the tax authority) and their citizens. A transportation use case is implemented for didactical reasons.

A Conceptual Model to Combine Creativity Techniques with Fuzzy Cognitive Maps for Enhanced Knowledge Management

This chapter introduces a conceptual model to combine creativity techniques with fuzzy cognitive maps (FCMs) and aims to support knowledge management methods by improving expert knowledge acquisition and aggregation. The aim of the conceptual model is to represent acquired knowledge in a manner that is as computer-understandable as possible with the intention of developing automated reasoning in the future as part of intelligent information systems. The formal represented knowledge thus may provide businesses with intelligent information integration. To this end, we introduce and evaluate various creativity techniques with a list of attributes to define the most suitable to combine with FCMs. This proposed combination enables enhanced knowledge management through the acquisition and representation of expert knowledge with FCMs. Our evaluation indicates that the creativity technique known as mind mapping is the most suitable technique in our set. Finally, a scenario from stakeholder management demonstrates the combination of mind mapping with FCMs as an integrated system.

Early adolescent cognitive gains are marked by increased sleep EEG coherence

Although the increases in cognitive capacities of adolescent humans are concurrent with significant cortical restructuring, functional associations between these phenomena are unclear. We examined the association between cortical development, as measured by the sleep EEG, and cognitive performance in a sample of 9/10 year olds followed up 1 to 3 years later. Our cognitive measures included a response inhibition task (Stroop), an executive control task (Trail Making), and a verbal fluency task (FAS). We correlated sleep EEG measures of power and intra-hemispheric coherence at the initial assessment with performance at that assessment. In addition we correlated the rate of change across assessments in sleep EEG measures with the rate of change in performance. We found no correlation between sleep EEG power and performance on cognitive tasks for the initial assessment. In contrast, we found a significant correlation of the rate of change in intra-hemispheric coherence for the sigma band (11 to 16 Hz) with rate of change in performance on the Stroop (r = 0.61; p<0.02) and Trail Making (r =  -0.51; p<0.02) but no association for the FAS. Thus, plastic changes in connectivity (i.e., sleep EEG coherence) were associated with improvement in complex cognitive function.

The relation between cognitive and motor performance and their relevance for children’s transition to school: A latent variable approach

Both theoretically and empirically there is a continuous interest in understanding the specific relation between cognitive and motor development in childhood. In the present longitudinal study including three measurement points, this relation was targeted. At the beginning of the study, the participating children were 5-6-year-olds. By assessing participants' fine motor skills, their executive functioning, and their non-verbal intelligence, their cross-sectional and cross-lagged interrelations were examined. Additionally, performance in these three areas was used to predict early school achievement (in terms of mathematics, reading, and spelling) at the end of participants' first grade. Correlational analyses and structural equation modeling revealed that fine motor skills, non-verbal intelligence and executive functioning were significantly interrelated. Both fine motor skills and intelligence had significant links to later school achievement. However, when executive functioning was additionally included into the prediction of early academic achievement, fine motor skills and non-verbal intelligence were no longer significantly associated with later school performance suggesting that executive functioning plays an important role for the motor-cognitive performance link.

Enhancing multidirectional communication for cognitive cities

This paper presents the technical background and functionality of a meta-application (meta-app) for cognitive cities. This app enhances communication and thereby facilitates e-governance. This paper focuses on a user-centered implementation of the Fuzzy Analytical Hierarchy Process (FAHP) by presenting its technical specifications in relation with cognitive cities. For didactical reasons, a use case from the user perspective is included. Finally the findings are summed up and future work is presented

Fuzzy knowledge representation in cognitive cities

This paper gives an insight into cognitive computing for smart cities, resulting in cognitive cities. Cognitive cities and cognitive computing research with the underlying concepts of knowledge graphs and fuzzy cognitive maps are presented and supported by existing tools (i.e., IBM Watson and Google Now) and intended tools (meta-app). The paper illustrates FCM as a suiting instrument to represent information/knowledge in a city environment driven by human-technology interaction, enforcing the concept of cognitive cities. A proposed paper prototype combines the findings of the paper and shows the next step in the implementation of the proposed meta-app.

Digital Personal Assistant for Cognitive Cities: A Paper Prototype

This chapter presents an evaluation and initial testing of a meta-application (meta-app) for enhanced communication and improved interaction (e.g., appointment scheduling) between stakeholders (e.g., citizens) in cognitive cities. The underlying theoretical models as well as the paper prototype are presented to ensure the comprehensibility of the user interface. This paper prototype of the meta-app was evaluated through interviews with various experts in different fields (e.g., a strategic consultant, a small and medium-sized enterprises cofounder in the field of online marketing, an IT project leader, and an innovation manager). The results and implications of the evaluation show that the idea behind this meta-app has the potential to improve the living standards of citizens and to lead to a next step in the realization and maturity of the meta-app. The meta-app helps citizens more effectively manage their time and organize their personal schedules and thus allows them to have more leisure time and take full advantage of it to ensure a good work-life balance to enable them to be the most efficient and productive during their working time.

Verbalization of Dependencies Between Concepts Built Through Fuzzy Cognitive Maps

The new computing paradigm known as cognitive computing attempts to imitate the human capabilities of learning, problem solving, and considering things in context. To do so, an application (a cognitive system) must learn from its environment (e.g., by interacting with various interfaces). These interfaces can run the gamut from sensors to humans to databases. Accessing data through such interfaces allows the system to conduct cognitive tasks that can support humans in decision-making or problem-solving processes. Cognitive systems can be integrated into various domains (e.g., medicine or insurance). For example, a cognitive system in cities can collect data, can learn from various data sources and can then attempt to connect these sources to provide real time optimizations of subsystems within the city (e.g., the transportation system). In this study, we provide a methodology for integrating a cognitive system that allows data to be verbalized, making the causalities and hypotheses generated from the cognitive system more understandable to humans. We abstract a city subsystem—passenger flow for a taxi company—by applying fuzzy cognitive maps (FCMs). FCMs can be used as a mathematical tool for modeling complex systems built by directed graphs with concepts (e.g., policies, events, and/or domains) as nodes and causalities as edges. As a verbalization technique we introduce the restriction-centered theory of reasoning (RCT). RCT addresses the imprecision inherent in language by introducing restrictions. Using this underlying combinatorial design, our approach can handle large data sets from complex systems and make the output understandable to humans.

Granular computing as a tool of human data interaction - a cognitive cities use case

The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.

A Dynamic Route Planning Prototype for Cognitive Cities

A software prototype for dynamic route planning in the travel industry for cognitive cities is presented in this paper. In contrast to existing tools, the prototype enhances the travel experience (i.e., sightseeing) by allowing additional flexibility to the user. The theoretical background of the paper strengthens the understanding of the introduced concepts (e.g., cognitive cities, fuzzy logic, graph databases) to comprehend the presented prototype. The prototype applies an instantiation and enhancement of the graph database Neo4j . For didactical reasons and to strengthen the understanding of this prototype a scenario, applied to route planning in the city of Bern (Switzerland) is shown in the paper.