912 resultados para discrete emotion


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Theoretical accounts suggest that mirror neurons play a crucial role in social cognition. The current study used transcranial-magnetic stimulation (TMS) to investigate the association between mirror neuron activation and facialemotion processing, a fundamental aspect of social cognition, among healthy adults (n = 20). Facial emotion processing of static (but not dynamic) images correlated significantly with an enhanced motor response, proposed to reflect mirror neuron activation. These correlations did not appear to reflect general facial processing or pattern recognition, and provide support to current theoretical accounts linking the mirror neuron system to aspects of social cognition. We discuss the mechanism by which mirror neurons might facilitate facial emotion recognition.

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Selection of features that will permit accurate pattern classification is a difficult task. However, if a particular data set is represented by discrete valued features, it becomes possible to determine empirically the contribution that each feature makes to the discrimination between classes. This paper extends the discrimination bound method so that both the maximum and average discrimination expected on unseen test data can be estimated. These estimation techniques are the basis of a backwards elimination algorithm that can be use to rank features in order of their discriminative power. Two problems are used to demonstrate this feature selection process: classification of the Mushroom Database, and a real-world, pregnancy related medical risk prediction task - assessment of risk of perinatal death.

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People with schizophrenia perform poorly when recognising facial expressions of emotion, particularly negative emotions such as fear. This finding has been taken as evidence of a “negative emotion specific deficit”, putatively associated with a dysfunction in the limbic system, particularly the amygdala. An alternative explanation is that greater difficulty in recognising negative emotions may reflect a priori differences in task difficulty. The present study uses a differential deficit design to test the above argument. Facial emotion recognition accuracy for seven emotion categories was compared across three groups. Eighteen schizophrenia patients and one group of healthy age- and gender-matched controls viewed identical sets of stimuli. A second group of 18 age- and gender-matched controls viewed a degraded version of the same stimuli. The level of stimulus degradation was chosen so as to equate overall level of accuracy to the schizophrenia patients. Both the schizophrenia group and the degraded image control group showed reduced overall recognition accuracy and reduced recognition accuracy for fearful and sad facial stimuli compared with the intact-image control group. There were no differences in recognition accuracy for any emotion category between the schizophrenia group and the degraded image control group. These findings argue against a negative emotion specific deficit in schizophrenia.

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Empirical evidence suggests impaired facial emotion recognition in schizophrenia. However, the nature of this deficit is the subject of ongoing research. The current study tested the hypothesis that a generalized deficit at an early stage of face-specific processing (i.e. putatively subserved by the fusiform gyrus) accounts for impaired facial emotion recognition in schizophrenia as opposed to the Negative Emotion-specific Deficit Model, which suggests impaired facial information processing at subsequent stages. Event-related potentials (ERPs) were recorded from 11 schizophrenia patients and 15 matched controls while performing a gender discrimination and a facial emotion recognition task. Significant reduction of the face-specific vertex positive potential (VPP) at a peak latency of 165 ms was confirmed in schizophrenia subjects whereas their early visual processing, as indexed by P1, was found to be intact. Attenuated VPP was found to correlate with subsequent P3 amplitude reduction and to predict accuracy when performing a facial emotion discrimination task. A subset of ten schizophrenia patients and ten matched healthy control subjects also performed similar tasks in the magnetic resonance imaging scanner. Patients showed reduced blood oxygenation level-dependent (BOLD) activation in the fusiform, inferior frontal, middle temporal and middle occipital gyrus as well as in the amygdala. Correlation analyses revealed that VPP and the subsequent P3a ERP components predict fusiform gyrus BOLD activation. These results suggest that problems in facial affect recognition in schizophrenia may represent flow-on effects of a generalized deficit in early visual processing.

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Social marketing by Western governments that use fear tactics and threatening information to promote anti-drinking messages has polarized ‘binge drinking’ and ‘moderate drinking’ through a continuum that implies benefits and harms for both individuals and society. With the goal of extending insights into social marketing approaches that promote safer drinking cultures in Australia, we discuss findings from a study that examines alcohol consumers' moderate-drinking intentions. By applying the theory of planned behaviour and emotions theory, we discuss survey results from a sample of alcohol consumers, which demonstrate that positively framed value propositions that evoke happiness and love are more influential in the processing of an alcohol moderation message for alcohol consumers. The key limitations of this study are the cross-sectional nature of the data and the focal-dependent variable being behavioural intentions rather than behaviours. Research insight into the stronger influence of positive emotions on processing an alcohol moderation message establishes an important avenue for future social marketing communications that moves beyond negative, avoidance appeals to promote behaviour change in drinkers. These research findings will benefit professionals involved in developing social change campaigns that promote and reinforce consumers' positive intentions, with messages about the benefits of controlled, moderate drinking.

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Patients with a number of psychiatric and neuropathological conditions demonstrate problems in recognising facial expressions of emotion. Research indicating that patients with schizophrenia perform more poorly in the recognition of negative valence facial stimuli than positive valence stimuli has been interpreted as evidence of a negative emotion specific deficit. An alternate explanation rests in the psychometric properties of the stimulus materials. This model suggests that the pattern of impairment observed in schizophrenia may reflect initial discrepancies in task difficulty between stimulus categories, which are not apparent in healthy subjects because of ceiling effects. This hypothesis is tested, by examining the performance of healthy subjects in a facial emotion categorisation task with three levels of stimulus resolution. Results confirm the predictions of the model, showing that performance degrades differentially across emotion categories, with the greatest deterioration to negative valence stimuli. In the light of these results, a possible methodology for detecting emotion specific deficits in clinical samples is discussed.

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The characterisation of facial expression through landmark-based analysis methods such as FACEM (Pilowsky & Katsikitis, 1994) has a variety of uses in psychiatric and psychological research. In these systems, important structural relationships are extracted from images of facial expressions by the analysis of a pre-defined set of feature points. These relationship measures may then be used, for instance, to assess the degree of variability and similarity between different facial expressions of emotion. FaceXpress is a multimedia software suite that provides a generalised workbench for landmark-based facial emotion analysis and stimulus manipulation. It is a flexible tool that is designed to be specialised at runtime by the user. While FaceXpress has been used to implement the FACEM process, it can also be configured to support any other similar, arbitrary system for quantifying human facial emotion. FaceXpress also implements an integrated set of image processing tools and specialised tools for facial expression stimulus production including facial morphing routines and the generation of expression-representative line drawings from photographs.

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Neuroimaging research has shown localised brain activation to different facial expressions. This, along with the finding that schizophrenia patients perform poorly in their recognition of negative emotions, has raised the suggestion that patients display an emotion specific impairment. We propose that this asymmetry in performance reflects task difficulty gradations, rather than aberrant processing in neural pathways subserving recognition of specific emotions. A neural network model is presented, which classifies facial expressions on the basis of measurements derived from human faces. After training, the network showed an accuracy pattern closely resembling that of healthy subjects. Lesioning of the network led to an overall decrease in the network’s discriminant capacity, with the greatest accuracy decrease to fear, disgust and anger stimuli. This implies that the differential pattern of impairment in schizophrenia patients can be explained without having to postulate impairment of specific processing modules for negative emotion recognition.

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Human emotional responses are highly individual. A comprehensive analysis of emotion research in cognitive psychology and physiology, including laboratory-based experiments, showed that understanding human emotions requires a dynamic systems approach incorporating insights from scientific disciplines beyond psychology. Importantly, subjective and automatic evaluations of emotive information are context-sensitive and changeable, confirming the dynamic nature of emotion and role of individual differences. Furthermore, a comparison of different statistical approaches established that statistical estimation, rather than averages, best captures our highly individual emotional responses. Emotion research needs a cross-disciplinary approach.

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Magnetic resonance is a well-established tool for structural characterisation of porous media. Features of pore-space morphology can be inferred from NMR diffusion-diffraction plots or the time-dependence of the apparent diffusion coefficient. Diffusion NMR signal attenuation can be computed from the restricted diffusion propagator, which describes the distribution of diffusing particles for a given starting position and diffusion time. We present two techniques for efficient evaluation of restricted diffusion propagators for use in NMR porous-media characterisation. The first is the Lattice Path Count (LPC). Its physical essence is that the restricted diffusion propagator connecting points A and B in time t is proportional to the number of distinct length-t paths from A to B. By using a discrete lattice, the number of such paths can be counted exactly. The second technique is the Markov transition matrix (MTM). The matrix represents the probabilities of jumps between every pair of lattice nodes within a single timestep. The propagator for an arbitrary diffusion time can be calculated as the appropriate matrix power. For periodic geometries, the transition matrix needs to be defined only for a single unit cell. This makes MTM ideally suited for periodic systems. Both LPC and MTM are closely related to existing computational techniques: LPC, to combinatorial techniques; and MTM, to the Fokker-Planck master equation. The relationship between LPC, MTM and other computational techniques is briefly discussed in the paper. Both LPC and MTM perform favourably compared to Monte Carlo sampling, yielding highly accurate and almost noiseless restricted diffusion propagators. Initial tests indicate that their computational performance is comparable to that of finite element methods. Both LPC and MTM can be applied to complicated pore-space geometries with no analytic solution. We discuss the new methods in the context of diffusion propagator calculation in porous materials and model biological tissues.

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Objective The aim of this study was to explore the mediating and moderating relationships between emotional perceptions of coeliac disease, negative emotional states, emotion regulation, emotional eating and gluten-free diet adherence. Method Adults with coeliac disease (N = 253) were recruited from state organisations of Coeliac Australia and completed an online questionnaire measuring illness perceptions, emotion regulation strategies, negative emotional states, emotional eating and gluten-free diet adherence. Results Participants' levels of depression and anxiety, but not stress or emotional eating, were associated with gluten-free diet adherence. Emotional perception of coeliac disease was also associated with gluten-free diet adherence, and this relationship was partially mediated by depression and anxiety. Furthermore, the emotion regulation strategies of cognitive reappraisal and expressive suppression moderated the relationship between emotional perceptions and depression, but not emotional perceptions and anxiety. Conclusions Interventions to improve dietary adherence for adults with coeliac disease displaying depressive symptoms should aim to increase the use of cognitive reappraisal and reduce the use of expressive suppression. Future studies should also explore mechanisms that may moderate the relationship between emotional perceptions and anxiety.

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Automatic Vehicle Identification Systems are being increasingly used as a new source of travel information. As in the last decades these systems relied on expensive new technologies, few of them were scattered along a networks making thus Travel-Time and Average Speed estimation their main objectives. However, as their price dropped, the opportunity of building dense AVI networks arose, as in Brisbane where more than 250 Bluetooth detectors are now installed. As a consequence this technology represents an effective means to acquire accurate time dependant Origin Destination information. In order to obtain reliable estimations, however, a number of issues need to be addressed. Some of these problems stem from the structure of a network made out of isolated detectors itself while others are inherent of Bluetooth technology (overlapping detection area, missing detections,\...). The aim of this paper is threefold: First, after having presented the level of details that can be reached with a network of isolated detectors we present how we modelled Brisbane's network, keeping only the information valuable for the retrieval of trip information. Second, we give an overview of the issues inherent to the Bluetooth technology and we propose a method for retrieving the itineraries of the individual Bluetooth vehicles. Last, through a comparison with Brisbane Transport Strategic Model results, we highlight the opportunities and the limits of Bluetooth detectors networks. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.

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The mathematical problem of determining the shape of a steadily propagating Saffman–Taylor finger in a rectangular Hele-Shaw cell is known to have a countably infinite number of solutions for each fixed surface tension value. For sufficiently large surface tension values, we find that fingers on higher solution branches are non-convex. The tips of the fingers have increasingly exotic shapes as the branch number increases.

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Science activities that evoke positive emotional responses make a difference to students’ emotional experience of science. In this study, we explored 8th Grade students’ discrete emotions expressed during science activities in a unit on Energy. Multiple data sources including classroom videos, interviews and emotion diaries completed at the end of each lesson were analysed to identify individual student's emotions. Results from two representative students are presented as case studies. Using a theoretical perspective drawn from theories of emotions founded in sociology, two assertions emerged. First, during the demonstration activity, students experienced the emotions of wonder and surprise; second, during a laboratory activity, students experienced the intense positive emotions of happiness/joy. Characteristics of these activities that contributed to students’ positive experiences are highlighted. The study found that choosing activities that evoked strong positive emotional experiences, focused students’ attention on the phenomenon they were learning, and the activities were recalled positively. Furthermore, such positive experiences may contribute to students’ interest and engagement in science and longer term memorability. Finally, implications for science teachers and pre-service teacher education are suggested.