An fMRI Study of Emotional engagement in decicion-making

It has been suggested that decision making depends on sensitive feelings associated with cognitive processing rather than cognitive processing alone. From human lesions, we know the medial anterior inferior-ventral prefrontal cortex processes the sensitivity associated with cognitive processing, it being essentially responsible for decision making. In this fMRI (functional Magnetic Resonance Image) study 15 subjects were analyzed using moral dilemmas as probes to investigate the neural basis for painful-emotional sensitivity associated with decision making. We found that a network comprising the posterior and anterior cingulate and the medial anterior prefrontal cortex was significantly and specifically activated by painful moral dilemmas, but not by non-painful dilemmas. These findings provide new evidence that the cingulate and medial anterior prefrontal are involved in processing painful emotional sensibility, in particular, when decision making takes place. We speculate that decision making has a cognitive component processed by cognitive brain areas and a sensitivity component processed by emotional brain areas. The structures activated suggest that decision making depends on painful emotional feeling processing rather than cognitive processing when painful feeling processing happens

Embedding Emotional Context in Recommender Systems

Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems

An LMI approach to H∞ synchronization of second-order neutral master-slave systems

The H∞ synchronization problem of the master and slave structure of a second-order neutral master-slave systems with time-varying delays is presented in this paper. Delay-dependent sufficient conditions for the design of a delayed output-feedback control are given by Lyapunov-Krasovskii method in terms of a linear matrix inequality (LMI). A controller, which guarantees H∞ synchronization of the master and slave structure using some free weighting matrices, is then developed. A numerical example has been given to show the effectiveness of the method

New delay-dependent stability criteria for uncertain neutral systems with mixed time-varying delays and nonlinear perturbations

The problem of stability analysis for a class of neutral systems with mixed time-varying neutral, discrete and distributed delays and nonlinear parameter perturbations is addressed. By introducing a novel Lyapunov-Krasovskii functional and combining the descriptor model transformation, the Leibniz-Newton formula, some free-weighting matrices, and a suitable change of variables, new sufficient conditions are established for the stability of the considered system, which are neutral-delay-dependent, discrete-delay-range dependent, and distributeddelay-dependent. The conditions are presented in terms of linear matrix inequalities (LMIs) and can be efficiently solved using convex programming techniques. Two numerical examples are given to illustrate the efficiency of the proposed method