Altered decision-making in multiple sclerosis: a sign of impaired emotional reactivity?

We assessed decision-making capacity and emotional reactivity in 20 patients with multiple sclerosis (MS) and in 16 healthy subjects using the Gambling Task (GT), a model of real-life decision making, and the skin conductance response (SCR). Demographic, neurological, affective, and cognitive parameters were analyzed in MS patients for their effect on decision-making performance. MS patients persisted longer (slope, -3.6%) than the comparison group (slope, -6.4%) in making disadvantageous choices as the GT progressed (p < 0.001), suggesting significant slower learning in MS. Patients with higher Expanded Disability Status Scale scores (EDSS >2.0) showed a different pattern of impairment in the learning process compared with patients with lower functional impairment (EDSS </=2.0). This slower learning was associated with impaired emotional reactivity (anticipatory SCR 3.9 vs 6.1 microSiemens [microS] for patients vs the comparison group, p < 0.0001; post-choice SCR 3.9 vs 6.2 microS, p < 0.0001), but not with executive dysfunction. Impaired emotional dimensions of behavior (assessed using the Dysexecutive Questionnaire, p < 0.002) also correlated with slower learning. Given the considerable consequences that impaired decision making can have on daily life, we suggest that this factor may contribute to handicap and altered quality of life secondary to MS and is dependent on emotional experience. Ann Neurol 2004.

"Suddenly I get into the zone": Examining discontinuities and nonlinear changes in flow experiences at work

Work-related flow is defined as a sudden and enjoyable merging of action and awareness that represents a peak experience in the daily lives of workers. Employees" perceptions of challenge and skill and their subjective experiences in terms of enjoyment, interest and absorption were measured using the experience sampling method, yielding a total of 6981 observations from a sample of 60 employees. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes. According to the R2, AICc and BIC indexes, the nonlinear dynamical systems model (i.e. cusp catastrophe model) fit the data better than the linear and logistic regression models. Likewise, the cusp catastrophe model appears to be especially powerful for modelling those cases of high levels of flow. Overall, flow represents a nonequilibrium condition that combines continuous and abrupt changes across time. Research and intervention efforts concerned with this process should focus on the variable of challenge, which, according to our study, appears to play a key role in the abrupt changes observed in work-related flow.

Factor structure of early smoking experiences and associations with smoking behavior: valence or sensitivity model?

The Early Smoking Experience (ESE) questionnaire is the most widely used questionnaire to assess initial subjective experiences of cigarette smoking. However, its factor structure is not clearly defined and can be perceived from two main standpoints: valence, or positive and negative experiences, and sensitivity to nicotine. This article explores the ESE's factor structure and determines which standpoint was more relevant. It compares two groups of young Swiss men (German- and French-speaking). We examined baseline data on 3,368 tobacco users from a representative sample in the ongoing Cohort Study on Substance Use Risk Factors (C-SURF). ESE, continued tobacco use, weekly smoking and nicotine dependence were assessed. Exploratory structural equation modeling (ESEM) and structural equation modeling (SEM) were performed. ESEM clearly distinguished positive experiences from negative experiences, but negative experiences were divided in experiences related to dizziness and experiences related to irritations. SEM underlined the reinforcing effects of positive experiences, but also of experiences related to dizziness on nicotine dependence and weekly smoking. The best ESE structure for predictive accuracy of experiences on smoking behavior was a compromise between the valence and sensitivity standpoints, which showed clinical relevance.

Assessment of emotional reactivity produced by exposure to virtual environments in patients with eating disorders

The aim of this study was to assess the usefulness of virtual environments representing situations that are emotionally significant to subjects with eating disorders (ED). These environments may be applied with both evaluative and therapeutic aims and in simulation procedures to carry out a range of experimental studies. This paper is part of a wider research project analyzing the influence of the situation to which subjects are exposed on their performance on body image estimation tasks. Thirty female patients with eating disorders were exposed to six virtual environments: a living-room (neutral situation), a kitchen with highcalorie food, a kitchen with low-calorie food, a restaurant with high-calorie food, a restaurant with low-calorie food, and a swimming-pool. After exposure to each environment the STAI-S (a measurement of state anxiety) and the CDB (a measurement of depression) were administered to all subjects. The results show that virtual reality instruments are particularly useful for simulating everyday situations that may provoke emotional reactions such as anxiety and depression, in patients with ED. Virtual environments in which subjects are obliged to ingest high-calorie food provoke the highest levels of state anxiety and depression.

Let's get emotional!

Artikkelissa kerrotaan luennoista, jotka brittiläinen professori Rob Briner piti Suomessa toukokuussa 2003

Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

Comprender la experiencia de la mujer ingresada con pre-eclampsia y eclampsia

Introducción: La preeclampsia/eclampsia es una enfermedad del embarazo que puede producir cambios en el estado emocional de la mujer por su prolongado ingreso hospitalario. Objetivo: Conocer las experiencias vividas por las mujeres con preeclampsia/eclampsia durante el ingreso hospitalario. Los objetivos que se tendrán en cuenta serán conocer cómo se modifica el rol propio dentro de la organización familiar, conocer cómo impacta su ingreso respecto a suestado emocional, conocer cómo les afecta la estructura de la unidad a su estado emocional y conocer qué necesidades y/o cuidados terapéuticos reciben respeto al equipo sanitario. Ámbito: El estudio se realizará en el Hospital de la Vall d’ Hebrón de Barcelona. Metodología: Estudio fenomenológico. La muestra se escogerá intencionadamente que cumplirá con los criterios de inclusión (mujeres ingresadas por preeclampsia/eclampsia en launidad de materno infantil de la Vall d’ Hebrón de Barcelona), y se terminará hasta llegar al nivel de saturación teórico. Los datos se recogerán a través de entrevistas semi-estructuradas y de la observación participante. Consideraciones finales: Dada la baja incidencia que existe tanto a nivel nacional como internacional en estudios de este tipo, un estudio cualitativo que ayude a conocer las experiencias de las mujeres ingresadas por preeclampsia podría ayudar a mejorar la calidad y práctica asistencial enfermera.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.

Differences of Functional Connectivity Brain Network in Emotional Judgment

Using combined emotional stimuli, combining photos of faces and recording of voices, we investigated the neural dynamics of emotional judgment using scalp EEG recordings. Stimuli could be either combioned in a congruent, or a non-congruent way.. As many evidences show the major role of alpha in emotional processing, the alpha band was subjected to be analyzed. Analysis was performed by computing the synchronization of the EEGs and the conditions congruent vs. non-congruent were compared using statistical tools. The obtained results demonstrate that scalp EEG ccould be used as a tool to investigate the neural dynamics of emotional valence and discriminate various emotions (angry, happy and neutral stimuli).

Remote collaborative multi-user informal learning experiences: design and evaluation

This paper presents a customizable system used to develop a collaborative multi-user problem solving game. It addresses the increasing demand for appealing informal learning experiences in museum-like settings. The system facilitates remote collaboration by allowing groups of learners tocommunicate through a videoconferencing system and by allowing them to simultaneously interact through a shared multi-touch interactive surface. A user study with 20 user groups indicates that the game facilitates collaboration between local and remote groups of learners. The videoconference and multitouch surface acted as communication channels, attracted students’ interest, facilitated engagement, and promoted inter- and intra-group collaboration—favoring intra-group collaboration. Our findings suggest that augmentingvideoconferencing systems with a shared multitouch space offers newpossibilities and scenarios for remote collaborative environments and collaborative learning.