989 resultados para facial emotion processing


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The investigation of biologically initiated pathways to psychological disorder is critical to advance our understanding of mental illness. Research has suggested that attention bias to emotion may be an intermediate trait for depression associated with biologically plausible candidate genes, such as the serotonin transporter (5-HTTLPR) and catechol-o-methyl-transferase (COMT) genes, yet there have been mixed findings in regards to the precise direction of effects. The experience of recent stressful life events (SLEs) may be an important, yet currently unstudied, moderator of the relationship between genes and attention bias as SLEs have been associated with both gene expression and attention to emotion. Additionally, although attention biases to emotion have been studied as a possible intermediate trait associated with depression, no study has examined whether attention biases within the context of measured genetic risk lead to increased risk for clinical depressive episodes over time. Therefore, this research investigated both whether SLEs moderate the link between genetic risk (5-HTTLPR and COMT) and attention bias to emotion and whether 5-HTTLPR and COMT moderated the relationship between attention biases to emotional faces and clinical depression onset prospectively across 18 months within a large community sample of youth (n= 467). Analyses revealed a differential effect of gene. Youth who were homozygous for the low expressing allele of 5-HTTLPR (S/S) and had experienced more recent SLEs within the last three months demonstrated preferential attention toward negative emotional faces (angry and sad). However, youth who were homozygous for the high expressing COMT genotype (Val/Val) and had experienced more recent SLEs showed attentional avoidance of positive facial expressions (happy). Additionally, youth who avoided negative emotion (i.e., anger) and were homozygous for the S allele of the 5-HTTLPR gene were at greater risk for prospective depressive episode onset. Increased risk for depression onset was specific to the 5-HTTLPR gene and was not found when examining moderation by COMT. These findings highlight the importance of examining risk for depression across multiple levels of analysis, such as combined genetic, environmental, and cognitive risk, and is the first study to demonstrate clear evidence of attention biases to emotion functioning as an intermediate trait predicting depression.

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The observation that snakes and spiders are found faster among flowers and mushrooms than vice versa and that this search advantage is independent of set size supports the notion that fear-relevant stimuli are processed preferentially in a dedicated fear module. Experiment I replicated the faster identification of snakes and spiders but also found a set size effect in a blocked, but not in a mixed-trial, sequence. Experiment 2 failed to find faster identification of snake and spider deviants relative to other animals among flowers and mushrooms and provided evidence for a search advantage for pictures of animals, irrespective of their fear relevance. These findings suggest that results from the present visual search task cannot support the notion of preferential processing of fear relevance.

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We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P

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Anxiety and fear are often confounded in discussions of human emotions. However, studies of rodent defensive reactions under naturalistic conditions suggest anxiety is functionally distinct from fear. Unambiguous threats, such as predators, elicit flight from rodents (if an escape-route is available), whereas ambiguous threats (e.g., the odor of a predator) elicit risk assessment behavior, which is associated with anxiety as it is preferentially modulated by anti-anxiety drugs. However, without human evidence, it would be premature to assume that rodent-based psychological models are valid for humans. We tested the human validity of the risk assessment explanation for anxiety by presenting 8 volunteers with emotive scenarios and asking them to pose facial expressions. Photographs and videos of these expressions were shown to 40 participants who matched them to the scenarios and labeled each expression. Scenarios describing ambiguous threats were preferentially matched to the facial expression posed in response to the same scenario type. This expression consisted of two plausible environmental-scanning behaviors (eye darts and head swivels) and was labeled as anxiety, not fear. The facial expression elicited by unambiguous threat scenarios was labeled as fear. The emotion labels generated were then presented to another 18 participants who matched them back to photographs of the facial expressions. This back-matching of labels to faces also linked anxiety to the environmental-scanning face rather than fear face. Results therefore suggest that anxiety produces a distinct facial expression and that it has adaptive value in situations that are ambiguously threatening, supporting a functional, risk-assessing explanation for human anxiety.

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Verbal working memory and emotional self-regulation are impaired in Bipolar Disorder (BD). Our aim was to investigate the effect of Lamotrigine (LTG), which is effective in the clinical management of BD, on the neural circuits subserving working memory and emotional processing. Functional Magnetic Resonance Imaging data from 12 stable BD patients was used to detect LTG-induced changes as the differences in brain activity between drug-free and post-LTG monotherapy conditions during a verbal working memory (N-back sequential letter task) and an angry facial affect recognition task. For both tasks, LGT monotherapy compared to baseline was associated with increased activation mostly within the prefrontal cortex and cingulate gyrus, in regions normally engaged in verbal working memory and emotional processing. Therefore, LTG monotherapy in BD patients may enhance cortical function within neural circuits involved in memory and emotional self-regulation. © 2007 Elsevier B.V. and ECNP.

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Various neuroimaging investigations have revealed that perception of emotional pictures is associated with greater visual cortex activity than their neutral counterparts. It has further been proposed that threat-related information is rapidly processed, suggesting that the modulation of visual cortex activity should occur at an early stage. Additional studies have demonstrated that oscillatory activity in the gamma band range (40-100 Hz) is associated with threat processing. Magnetoencephalography (MEG) was used to investigate such activity during perception of task-irrelevant, threat-related versus neutral facial expressions. Our results demonstrated a bilateral reduction in gamma band activity for expressions of threat, specifically anger, compared with neutral faces in extrastriate visual cortex (BA 18) within 50-250 ms of stimulus onset. These results suggest that gamma activity in visual cortex may play a role in affective modulation of visual processing, in particular with the perception of threat cues.

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Sixteen clinically depressed patients and sixteen healthy controls were presented with a set of emotional facial expressions and were asked to identify the emotion portrayed by each face. They, were subsequently given a recognition memory test for these faces. There was no difference between the groups in terms of their ability to identify emotion between from faces. All participants identified emotional expressions more accurately than neutral expressions, with happy expressions being identified most accurately. During the recognition memory phase the depressed patients demonstrated superior memory for sad expressions, and inferior memory for happy expressions, relative to neutral expressions. Conversely, the controls demonstrated superior memory for happy expressions, and inferior memory for sad expressions, relative to neutral expressions. These results are discussed in terms of the cognitive model of depression proposed by Williams, Watts, MacLeod, and Mathews (1997).

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Motion is an important aspect of face perception that has been largely neglected to date. Many of the established findings are based on studies that use static facial images, which do not reflect the unique temporal dynamics available from seeing a moving face. In the present thesis a set of naturalistic dynamic facial emotional expressions was purposely created and used to investigate the neural structures involved in the perception of dynamic facial expressions of emotion, with both functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG). Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend the distributed neural system for face perception (Haxby et al.,2000). Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as inferior occipital gyri and superior temporal sulci, along with coupling between superior temporal sulci and amygdalae, as well as with inferior frontal gyri. MEG and Synthetic Aperture Magnetometry (SAM) were used to examine the spatiotemporal profile of neurophysiological activity within this dynamic face perception network. SAM analysis revealed a number of regions showing differential activation to dynamic versus static faces in the distributed face network, characterised by decreases in cortical oscillatory power in the beta band, which were spatially coincident with those regions that were previously identified with fMRI. These findings support the presence of a distributed network of cortical regions that mediate the perception of dynamic facial expressions, with the fMRI data providing information on the spatial co-ordinates paralleled by the MEG data, which indicate the temporal dynamics within this network. This integrated multimodal approach offers both excellent spatial and temporal resolution, thereby providing an opportunity to explore dynamic brain activity and connectivity during face processing.

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The functional catechol-O-methyltransferase (COMT Val108/158Met) polymorphism has been shown to have an impact on tasks of executive function, memory and attention and recently, tasks with an affective component. As oestrogen reduces COMT activity, we focused on the interaction between gender and COMT genotype on brain activations during an affective processing task. We used functional MRI (fMRI) to record brain activations from 74 healthy subjects who engaged in a facial affect recognition task; subjects viewed and identified fearful compared to neutral faces. There was no main effect of the COMT polymorphism, gender or genotypegender interaction on task performance. We found a significant effect of gender on brain activations in the left amygdala and right temporal pole, where females demonstrated increased activations over males. Within these regions, Val/Val carriers showed greater signal magnitude compared to Met/Met carriers, particularly in females. The COMT Val108/158Met polymorphism impacts on gender-related patterns of activation in limbic and paralimbic regions but the functional significance of any oestrogen-related COMT inhibition appears modest. Copyright © 2008 CINP.

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Background: Bipolar disorder is associated with dysfunction in prefrontal and limbic areas implicated in emotional processing. Aims: To explore whether lamotrigine monotherapy may exert its action by improving the function of the neural network involved in emotional processing. Method: We used functional magnetic resonance imaging to examine changes in brain activation during a sad facial affect recognition task in 12 stable patients with bipolar disorder when medication-free compared with healthy controls and after 12 weeks of lamotrigine monotherapy. Results: At baseline, compared with controls, patients with bipolar disorder showed overactivity in temporal regions and underactivity in the dorsal medial and right ventrolateral prefrontal cortex, and the dorsal cingulate gyrus. Following lamotrigine monotherapy, patients demonstrated reduced temporal and increased prefrontal activation. Conclusions: This preliminary evidence suggests that lamotrigine may enhance the function of the neural circuitry involved in affect recognition.

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Impaired facial expression recognition has been associated with features of major depression, which could underlie some of the difficulties in social interactions in these patients. Patients with major depressive disorder and age- and gender-matched healthy volunteers judged the emotion of 100 facial stimuli displaying different intensities of sadness and happiness and neutral expressions presented for short (100 ms) and long (2,000 ms) durations. Compared with healthy volunteers, depressed patients demonstrated subtle impairments in discrimination accuracy and a predominant bias away from the identification as happy of mildly happy expressions. The authors suggest that, in depressed patients, the inability to accurately identify subtle changes in facial expression displayed by others in social situations may underlie the impaired interpersonal functioning.

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Most research in the area of emotion detection in written text focused on detecting explicit expressions of emotions in text. In this paper, we present a rule-based pipeline approach for detecting implicit emotions in written text without emotion-bearing words based on the OCC Model. We have evaluated our approach on three different datasets with five emotion categories. Our results show that the proposed approach outperforms the lexicon matching method consistently across all the three datasets by a large margin of 17–30% in F-measure and gives competitive performance compared to a supervised classifier. In particular, when dealing with formal text which follows grammatical rules strictly, our approach gives an average F-measure of 82.7% on “Happy”, “Angry-Disgust” and “Sad”, even outperforming the supervised baseline by nearly 17% in F-measure. Our preliminary results show the feasibility of the approach for the task of implicit emotion detection in written text.

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Holistic face perception, i.e. the mandatory integration of featural information across the face, hasbeen considered to play a key role when recognizing emotional face expressions (e.g., Tanaka et al.,2002). However, despite their early onset holistic processing skills continue to improvethroughout adolescence (e.g., Schwarzer et al., 2010) and therefore might modulate theevaluation of facial expressions. We tested this hypothesis using an attentional blink (AB)paradigm to compare the impact of happy, fearful and neutral faces in adolescents (10–13 years)and adults on subsequently presented neutral target stimuli (animals, plants and objects) in a rapidserial visual presentation stream. Adolescents and adults were found to be equally reliable whenreporting the emotional expression of the face stimuli. However, the detection of emotional butnot neutral faces imposed a significantly stronger AB effect on the detection of the neutral targetsin adults compared to adolescents. In a control experiment we confirmed that adolescents ratedemotional faces lower in terms of valence and arousal than adults. The results suggest a protracteddevelopment of the ability to evaluate facial expressions that might be attributed to the latematuration of holistic processing skills.

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The need to provide computers with the ability to distinguish the affective state of their users is a major requirement for the practical implementation of affective computing concepts. This dissertation proposes the application of signal processing methods on physiological signals to extract from them features that can be processed by learning pattern recognition systems to provide cues about a person's affective state. In particular, combining physiological information sensed from a user's left hand in a non-invasive way with the pupil diameter information from an eye-tracking system may provide a computer with an awareness of its user's affective responses in the course of human-computer interactions. In this study an integrated hardware-software setup was developed to achieve automatic assessment of the affective status of a computer user. A computer-based "Paced Stroop Test" was designed as a stimulus to elicit emotional stress in the subject during the experiment. Four signals: the Galvanic Skin Response (GSR), the Blood Volume Pulse (BVP), the Skin Temperature (ST) and the Pupil Diameter (PD), were monitored and analyzed to differentiate affective states in the user. Several signal processing techniques were applied on the collected signals to extract their most relevant features. These features were analyzed with learning classification systems, to accomplish the affective state identification. Three learning algorithms: Naïve Bayes, Decision Tree and Support Vector Machine were applied to this identification process and their levels of classification accuracy were compared. The results achieved indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in the emotional states of the experimental subjects. These results also revealed that the inclusion of pupil diameter information significantly improved the performance of the emotion recognition system. ^

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This research pursued the conceptualization and real-time verification of a system that allows a computer user to control the cursor of a computer interface without using his/her hands. The target user groups for this system are individuals who are unable to use their hands due to spinal dysfunction or other afflictions, and individuals who must use their hands for higher priority tasks while still requiring interaction with a computer. ^ The system receives two forms of input from the user: Electromyogram (EMG) signals from muscles in the face and point-of-gaze coordinates produced by an Eye Gaze Tracking (EGT) system. In order to produce reliable cursor control from the two forms of user input, the development of this EMG/EGT system addressed three key requirements: an algorithm was created to accurately translate EMG signals due to facial movements into cursor actions, a separate algorithm was created that recognized an eye gaze fixation and provided an estimate of the associated eye gaze position, and an information fusion protocol was devised to efficiently integrate the outputs of these algorithms. ^ Experiments were conducted to compare the performance of EMG/EGT cursor control to EGT-only control and mouse control. These experiments took the form of two different types of point-and-click trials. The data produced by these experiments were evaluated using statistical analysis, Fitts' Law analysis and target re-entry (TRE) analysis. ^ The experimental results revealed that though EMG/EGT control was slower than EGT-only and mouse control, it provided effective hands-free control of the cursor without a spatial accuracy limitation, and it also facilitated a reliable click operation. This combination of qualities is not possessed by either EGT-only or mouse control, making EMG/EGT cursor control a unique and practical alternative for a user's cursor control needs. ^