Neural Processing of Narratives: From Individual Processing to Viral Propagation
Narratives, in the form of, e.g., written stories, mouth-to-mouth accounts, audiobooks, fiction movies, and media-feeds, powerfully shape the perception of reality and widely influence human decision-making. In this review, we describe findings from recent neuroimaging studies unraveling how narratives influence the human brain, thus shaping perception, cognition, emotions, and decision-making. It appears that narrative sense-making relies on default-mode network (DMN) structures of the brain, especially precuneus. Activity in precuneus further seems to differ for fictitious vs. real narratives. Notably, high inter-subject correlation (ISC) of brain activity during narrative processing seems to predict the efficacy of a narrative. Factors that enhance the ISC of brain activity during narratives include higher levels of attention, emotional arousal, and negative emotional valence. Higher levels of attentional suspense seem to co-vary with activity in the temporoparietal junction, emotional arousal with activity in dorsal attention network, and negative emotional valence with activity in DMN. Lingering after-effects of emotional narratives have been further described in DMN, amygdala, and sensory cortical areas. Finally, inter-individual differences in personality, and cultural-background related analytical and holistic thinking styles, shape ISC of brain activity during narrative perception. Together, these findings offer promising leads for future studies elucidating the effects of narratives on the human brain, and how such effects might predict the efficacy of narratives in modulating decision-making.
The distractive effects on attentional task performance in different paradigms are analyzed in this paper. I demonstrate how distractors may negatively affect (interference effect), positively (redundancy effect) or neutrally (null effect). Distractor effects described in literature are classified in accordance with their hypothetical source. The general rule of the theory is also introduced. It contains the formal prediction of the particular distractor effect, based on entropy and redundancy measures from the mathematical theory of communication (Shannon, 1948). Single- vs dual-process frameworks are considered for hypothetical mechanisms which underpin the distractor effects. Distractor profiles (DPs) are also introduced for the formalization and simple visualization of experimental data concerning the distractor effects. Typical shapes of DPs and their interpretations are discussed with examples from three frequently cited experiments. Finally, the paper introduces hierarchical hypothesis that states the level-fashion modulating interrelations between distractor effects of different classes.
The first volume involves the Russian Federation as a common denominator with either Norway (oldest multilateral region in the Arctic) or the United States (sharing with Russia the longest maritime boundary in the world) to interpret changes with connected biophysical and socio-economic systems that underscore decisions across a “continuum of urgencies” from security to sustainability time scales. The second and third volumes will emerge from presentations during the annual Arctic Frontiers Conferences in Tromsø, Norway, starting in January 2020. Volume 2 will consider circumstances associated with areas beyond sovereign jurisdictions from Arctic and non-Arctic perspectives, recognizing the international community has unambiguous rights and responsibilities in the Arctic High Seas under the law of the sea. Volume 3 is intended to synthesize insights on a pan-Arctic scale, analogous to the world ocean across all sea zones, involving decisions to achieve ongoing progress with sustainability, coupling governance mechanisms and built infrastructure. Throughout this book series, which we expect to expand beyond the Arctic, science diplomacy will be applied as an international, interdisciplinary, and inclusive (holistic) process, facilitating informed decisionmaking to balance national interests and common interests for the benefit of all on Earth across generations. With holistic integration, this book series will reveal skills, methods, and theory of informed decisionmaking that will continue to evolve, contributing to balance, resilience, and stability that underlie progress with sustainability across our home planet.
This abstract offers a method for ranking alternatives in a decison making problem. It determines importance of the criteria with help of factor analysis. Though the alternatives are evaluated by each of the criteria by a group of experts, the weights for the criteria are to be found with the help of factor analysis.
The algorithm of the method is as follows:
1. Under the constraint that the problem handles several evaluation criteria, several items to compare (alternatives) and several experts to give their evaluation.
2. Find the principal components that replace the input criteria implicitly.
3. To find the final mark for each of the alternatives the marks given by experts are multiplied with the regression coefficients, found in the step 2.
4. The final marks are represented in axes „crieria“ and „mark“ so that each alternative is described with a curve (trajectory). These curves represent the map of graded alternatives. Depending on the problem to be solved (min or max,) a record for each main criteria is to be found.
5. With help of special deviation measure procedures (Minkowski, Chebyshev e.t.s) a matrix of deviations from ideal solution is to be built.
6. The alternatives are to be rated in accordance to the deviation from the ideal trajectory.
To prove the effectiveness of the method it was applied to a problem for 5 alternatives, 3 experts and 38 evaluation criteria. The problem was also solved with the help of most popular method of Weighted Sum Model (WSM) and TOPSIS method. The problem was also being solved by finding the geometric mean for each alternative. The results for approaches were compared and the method, offered in this abstrat, proved itself as a feasible one.
The paper presents the results of empirical research enterpreniur decision making process. The features of modern Russian entrepreneurship, decision-making process, psychological characteristics required for different types of decision-making in organizations is identified.
Soft Computing (SC) is a consortium of fuzzy logic (FL), neurocomputing (NC), evolutionary computing (EC), probabilistic computing (PC), chaotic computing (CC) and parts of machine learning theory (ML). SC is the foundation for computational intelligence and is leading to the development of numerous hybrid intelligent information, control and decision-making systems. The methodology of computing with words (CW) is an important event in the evolution of cognitive science, natural language processing, artificial intelligence, and different existing scientific theories. This is because CW can enrich the existing scientific theories and the above-mentioned science fields giving them the capability of using natural languages to operate on perception-based information, not only measurement-based information. Indeed in many real-world problems in natural sciences as well as in industrial engineering, economics, and business, often there is a need to deal with both perception and measurement based information. In the case of perception based information, the available information is not precise enough to justify the use of numbers. Such information is usually described in natural languages rather than in strict (idealized) mathematical expressions. So a strong need has appeared for a new approach, theory and technology for the development of knowledge representation, computing, and reasoning tools that allow creation of systems with high MIQ. The sessions of the ICSCCW-2011 will focus on the development and application of Soft Computing technology and computing with words paradigm in system analysis, decision and control.
The paper proposes a method of multicriteria optimization under interval stochastic uncertainty of estimates given by the subject for the relative importance of one criterion over the other and the different alternatives to each other for each criterion. The method is an extension of the deterministic Analytic Hierarchy Process (AHP) for multicriteria optimization. It is use deterministic point estimates of the importance of criteria and alternatives for each criterion . While deterministic AHP allows to select the best alternative by a point maximum value of a global priority in the developed article interval stochastic AHP the global priorities are interval, making it difficult to make the best decision . To select the best interval alternative in this article introduce two criteria, whose values are maximized. The first criterion corresponds to the maximum of the lower and upper bounds of the intervals of global priorities of alternatives. The second criteria is the maximum of interval stability of alternatives. Application of the proposed approach is illustrated by a specific example. Also a comparison with the results obtained on the basis of interval arithmetic, show the failure of the latter, carried out.
The Seventh International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control aims at the development of Soft Computing and its Application is the Seventh of its kind. These fields have built upon mainly Fuzzy Logic originally introduced by L. Zadeh. Soft Computing (SC) is a consortium of fuzzy logic (FL), neurocomputing (NC), evolutionary computing (EC), probabilistic computing (PC), chaotic computing (CC) and parts of machine learning theory (ML). SC is the foundation for computational intelligence and is leading to the development of numerous hybrid intelligent information, control and decision making systems. The methodology of computing with words (CW) is an important event in the evolution of cognitive science, natural language processing, artificial intelligence, and different existing scientific theories. This is because CW can enrich the existing scientific theories and the above-mentioned science fields giving them the capability of using natural languages to operate on perception-based information, not only measurement-based information. Indeed, in many real-world problems in natural sciences as well as in industrial engineering, economics, and business, often there is a need to deal with both perception and measurement based information. In the case of perception based information, the available information is not precise enough to justify the use of numbers. Such information is usually described in natural languages or by means of visual images rather than in strict (idealized) mathematical expressions.So a strong need has appeared for a new approach, theory and technology for the development of knowledge representation, computing, and reasoning tools that allow creation of systems with high MIQ. The sessions of the ICSCCW-2013 will focus on the development and application of Soft Computing technology and computing with words paradigm in system analysis, decision and control.
This article describes the expierence of studying factors influencing the social well-being of educational migrants as mesured by means of a psychological well-being scale (A. Perrudet-Badoux, G.A. Mendelsohn, J.Chiche, 1988) previously adapted for Russian by M.V. Sokolova. A statistical analysis of the scale's reliability is performed. Trends in dynamics of subjective well-being are indentified on the basis the correlations analysis between the condbtbions of adaptation and its success rate, and potential mechanisms for developing subjective well-being among student migrants living in student hostels are described. Particular attention is paid to commuting as a factor of adaptation.