Facial Expression Recognition Task Research Articles

Recognition of disgusted facial expressions in severe depression

Facial emotion processing was examined in patients with severe depression (n = 68) and a healthy control group (n = 50), using the Facial Expression Recognition Task. A negative interpretation bias was observed in the depression group: neutral faces were more likely to be interpreted as sad and less likely to be interpreted as happy, compared with controls. The depression group also displayed a specific deficit in the recognition of facial expressions of disgust, compared with controls. This may relate to impaired functioning of frontostriatal structures, particularly the basal ganglia.

Sex differences in scanning faces: Does attention to the eyes explain female superiority in facial expression recognition?

Previous meta-analyses support a female advantage in decoding non-verbal emotion (Hall, 1978, 1984), yet the mechanisms underlying this advantage are not understood. The present study examined whether the female advantage is related to greater female attention to the eyes. Eye-tracking techniques were used to measure attention to the eyes in 19 males and 20 females during a facial expression recognition task. Women were faster and more accurate in their expression recognition compared with men, and women looked more at the eyes than men. Positive relationships were observed between dwell time and number of fixations to the eyes and both accuracy of facial expression recognition and speed of facial expression recognition. These results support the hypothesis that the female advantage in facial expression recognition is related to greater female attention to the eyes.

Electrocortical effects of acute tryptophan depletion on emotive facial processing in depression-prone individuals

This study assessed the effects of acute tryptophan depletion (ATD), which transiently lowers CNS 5-HT, on electrocortical responses to facial expression processing in individuals with a family history of depression (FH+). Electroencephalograph (EEG)-derived event-related potentials (ERPs) were acquired from 18 FH+ individuals during a facial expression recognition task (neutral and sad, joy and surprise at 50% and 100% intensities). Both early positive (P1 and P2) and the face-specific N170 ERP components were differentially altered by emotional intensity and valence. Increased depression, confusion and total mood disturbance scores, and decreased calmness, were observed with ATD (versus placebo). ATD was also associated with enhanced P1 and P2 amplitudes for sad versus joyful expressions. The N170 was not modulated by treatment, but was affected by emotive valence. Therefore, ATD enhanced ERP-indexed early processing of sad facial expressions, and altered the processing of positive ones, in FH+ individuals.

Basic Emotion Recognition and Psychopathology in Schizophrenia

Socio-emotional competence is a key aspect of schizophrenia, both in terms of psychopathological vulnerability and outcome. In this respect, current research increasingly emphasizes the importance of deficits in facial expression recognition. The focus of the present study is the performance in recognizing 6 basic emotions (sadness, anger, happiness, fear, disgust, surprise) which play an essential role in shaping daily function and interpersonal interactions. A group of 20 patients diagnosed with DSM-IV schizophrenia were compared with a group of 20 matched controls on a facial expression recognition task, derived from the Karolinska Directed Emotional Faces (Lundqvist D, Flykt A, Ohmann A (1998) The Karolinska Directed Emotional Faces (KDEF). Stockholm (Sweden): Karolinska Institute), and were subsequently assessed with the Positive and Negative Syndrome Scale (PANSS). Facial expression recognition performance was significantly more impaired in patients, and was selectively correlated with the positive and cognitive dimensions of the positive and negative syndrome scale. Furthermore, significant group differences were found with respect to happiness and surprise.

Diminished Neural and Cognitive Responses to Facial Expressions of Disgust in Patients with Psoriasis: A Functional Magnetic Resonance Imaging Study

Psoriasis produces significant psychosocial disability; however, little is understood about the neurocognitive mechanisms that mediate the adverse consequences of the social stigma associated with visible skin lesions, such as disgusted facial expressions of others. Both the feeling of disgust and the observation of disgust in others are known to activate the insula cortex. We investigated whether the social impact of psoriasis is associated with altered cognitive processing of disgust using (i) a covert recognition of faces task conducted using functional magnetic resonance imaging (fMRI) and (ii) the facial expression recognition task (FERT), a decision-making task, conducted outside the scanner to assess the ability to recognize overtly different intensities of disgust. Thirteen right-handed male patients with psoriasis and 13 age-matched male controls were included. In the fMRI study, psoriasis patients had significantly (P<0.005) smaller signal responses to disgusted faces in the bilateral insular cortex compared with healthy controls. These data were corroborated by FERT, in that patients were less able than controls to identify all intensities of disgust tested. We hypothesize that patients with psoriasis, in this case male patients, develop a coping mechanism to protect them from stressful emotional responses by blocking the processing of disgusted facial expressions.

Facial mimicry is not necessary to recognize emotion: Facial expression recognition by people with Moebius syndrome

According to the reverse simulation model of embodied simulation theory, we recognize others' emotions by subtly mimicking their expressions, which allows us to feel the corresponding emotion through facial feedback. Previous studies examining whether facial mimicry is necessary for facial expression recognition were limited by potentially distracting manipulations intended to artificially restrict facial mimicry or very small samples of people with facial paralysis. We addressed these limitations by collecting the largest sample to date of people with Moebius syndrome, a condition characterized by congenital bilateral facial paralysis. In this Internet-based study, 37 adults with Moebius syndrome and 37 matched control participants completed a facial expression recognition task. People with Moebius syndrome did not differ from the control group or normative data in emotion recognition accuracy, and accuracy was not related to extent of ability to produce facial expressions. Our results do not support the hypothesis that reverse simulation with facial mimicry is necessary for facial expression recognition.

FEATURE EXTRACTION THROUGH CROSS-PHASE CONGRUENCY FOR FACIAL EXPRESSION ANALYSIS

Human face analysis has attracted a large number of researchers from various fields, such as computer vision, image processing, neurophysiology or psychology. One of the particular aspects of human face analysis is encompassed by facial expression recognition task. A novel method based on phase congruency for extracting the facial features used in the facial expression classification procedure is developed. Considering a set of image samples comprising humans expressing various expressions, this new approach computes the phase congruency map between the samples. The analysis is performed in the frequency space where the similarity (or dissimilarity) between sample phases is measured to form discriminant features. The experiments were run using samples from two facial expression databases. To assess the method's performance, the technique is compared to the state-of-the art techniques utilized for classifying facial expressions, such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA), and Gabor jets. The features extracted by the aforementioned techniques are further classified using two classifiers: a distance-based classifier and a Support Vector Machine-based classifier. Experiments reveal superior facial expression recognition performance for the proposed approach with respect to other techniques.

Quantitative Assessment of Perceived Visibility Enhancement with Image Processing for Single Face Images: A Preliminary Study

To develop a method to quantitatively assess the visibility enhancement of single face images gained with digital filters for people with maculopathy. To apply this method to obtaining preliminary results of visibility enhancement with subjectively preferred filters for people with maculopathy. Six subjects with normal vision and two with maculopathy were required to recognize seven facial expressions of single face images with different display durations of 2 seconds, 1 second, and 0.73 second. As a result, four facial expressions (anger, disgust, fear, and sadness) and a display duration of 0.73 second were chosen to measure single face image visibility enhancement with subjectively preferred digital filters. Finally, nine subjects with maculopathy viewed 30 images with four facial expressions that were either unfiltered or filtered with subjectively preferred digital filters. Each subject was required to identify the facial expression in a four-alternative, forced-choice paradigm. The errors with original and filtered images were calculated. The method with four facial expressions and display duration of 0.73 second prevented a ceiling effect. The nine subjects with maculopathy made significantly fewer errors with the filtered images than with the original ones images (P = 0.004). The developed method was effective in objective (quantitative) measurement of the enhancement in image visibility with digital filtering for people with maculopathy. There is a measurable improvement in facial expression recognition with subjectively preferred filters. The facial expression recognition task developed and validated in the present study is recommended as a method to be used in future studies of enhancement of face images.

NK1 receptor antagonism and emotional processing in healthy volunteers

The neurokinin-1 (NK(1)) receptor antagonist, aprepitant, showed activity in several animal models of depression; however, its efficacy in clinical trials was disappointing. There is little knowledge of the role of NK(1) receptors in human emotional behaviour to help explain this discrepancy. The aim of the current study was to assess the effects of a single oral dose of aprepitant (125 mg) on models of emotional processing sensitive to conventional antidepressant drug administration in 38 healthy volunteers, randomly allocated to receive aprepitant or placebo in a between groups double blind design. Performance on measures of facial expression recognition, emotional categorisation, memory and attentional visual-probe were assessed following the drug absorption. Relative to placebo, aprepitant improved recognition of happy facial expressions and increased vigilance to emotional information in the unmasked condition of the visual probe task. In contrast, aprepitant impaired emotional memory and slowed responses in the facial expression recognition task suggesting possible deleterious effects on cognition. These results suggest that while antagonism of NK(1) receptors does affect emotional processing in humans, its effects are more restricted and less consistent across tasks than those of conventional antidepressants. Human models of emotional processing may provide a useful means of assessing the likely therapeutic potential of new treatments for depression.

Comparing a novel model based on the transferable belief model with humans during the recognition of partially occluded facial expressions

Humans recognize basic facial expressions effortlessly. Yet, despite a considerable amount of research, this task remains elusive for computer vision systems. Here, we compared the behavior of one of the best computer models of facial expression recognition (Z. Hammal, L. Couvreur, A. Caplier, & M. Rombaut, 2007) with the behavior of human observers during the M. Smith, G. Cottrell, F. Gosselin, and P. G. Schyns (2005) facial expression recognition task performed on stimuli randomly sampled using Gaussian apertures. The model--which we had to significantly modify in order to give the ability to deal with partially occluded stimuli--classifies the six basic facial expressions (Happiness, Fear, Sadness, Surprise, Anger, and Disgust) plus Neutral from static images based on the permanent facial feature deformations and the Transferable Belief Model (TBM). Three simulations demonstrated the suitability of the TBM-based model to deal with partially occluded facial parts and revealed the differences between the facial information used by humans and by the model. This opens promising perspectives for the future development of the model.

Evidence for modulation of facial emotional processing bias during emotional expression decoding by serotonergic and noradrenergic antidepressants: an event-related potential (ERP) study

Serotonergic (SSRI) and noradrenergic (NRI) antidepressants modulate biases in emotional processing such that perceptual bias is shifted away from negative and towards positive emotional material. However, the effects of serotonergic and noradrenergic modulation on the temporal course (occurring in milliseconds) of emotional processing, and in particular, the rapid physiological changes associated with the different stages of emotional processing, are unknown. The current study assessed the effects of acute serotonergic (i.e. with citalopram) and noradrenergic (i.e. with reboxetine) augmentation on event-related potential (ERP) measures associated with 'structural encoding' (N170) and emotion expression decoding (N250 and late positive potential [LPP]) for positive (happy) and negative (sad) facial stimuli relative to neutral facial stimuli. This study employed a double-blind, placebo-controlled, cross-over design in which 12 healthy male participants completed a facial expression recognition task tested under three acute conditions: (a) placebo, (b) citalopram (20 mg) and (c) reboxetine (4 mg). Both citalopram and reboxetine had no effect on the N170 ERP component associated with structural encoding, but potentiated the N250 associated with happy (relative to neutral) emotional facial expression decoding. Both drugs had no valence effects on later ERP measures of emotion expression decoding (LPP). Citalopram and reboxetine have selective effects on the temporal course of emotional processing with evidence to suggest specific effects on emotion expression decoding of positive (happy) emotional facial stimuli as evidenced by changes in the attention-modulated N250 but not structural encoding. These findings provide physiological evidence that antidepressants may shift perceptual biases in emotional processing away from negative and towards positive stimuli.

Social Functioning and Facial Expression Recognition in Survivors of Pediatric Brain Tumors

To assess social functioning and facial expression recognition skill in survivors of pediatric brain tumors (BT) as compared to children with juvenile rheumatoid arthritis (JRA). The social functioning of 51 survivors of BT and 31 children with JRA was assessed using a facial expression recognition task, questionnaire ratings of social functioning, and an IQ screener. After controlling for estimated IQ, survivors of BT made significantly more errors interpreting adult facial expressions as compared to children with JRA. Additionally, history of therapy and diagnosis age predicted performance on the child portion of the facial recognition task. Finally, survivors of BT demonstrated significantly impaired social functioning across multiple measures when compared to children with JRA. Survivors of pediatric BT showed significant deficits in social functioning as compared to an illness comparison group. Errors in facial expression recognition represent another method for evaluating deficits that contribute to social outcomes.

Facial expression recognition based on two-dimensional discriminant locality preserving projections

In this paper, a novel method called two-dimensional discriminant locality preserving projections (2D-DLPP) is proposed. By introducing between-class scatter constraint and label information into two-dimensional locality preserving projections (2D-LPP) algorithm, 2D-DLPP successfully finds the subspace which can best discriminate different pattern classes. So the subspace obtained by 2D-DLPP has more discriminant power than 2D-LPP, and is more suitable for recognition tasks. The proposed method was applied to facial expression recognition tasks on JAFFE and Cohn-Kanade database and compared with other three widely used two-dimensional methods: 2D-PCA, 2D-LDA and 2D-LPP. The high recognition rates show the effectiveness of the proposed algorithm.

The influence of the fear facial expression on prosocial responding

Perceiving distress cues appears to be associated with prosocial responding. This being the case, it was hypothesised that the fear facial expression would elicit prosocial responding in perceivers. In Study 1, participants indicated that fear and sadness expressions would be associated with greater sympathy and willingness to help the expresser than would neutral expressions. In Study 2, participants were primed with fear or neutral expressions before reading vignettes featuring protagonists in mild distress. Fear-primed participants reported more sympathy and desire to help the protagonists than neutral-primed participants. Moreover, participants who recognised fear most accurately, as measured by a standard facial expression recognition task, showed the greatest increases in prosocial responding following fear expression primes. This corroborates the notion, supported by research as disparate as behavioural research on bystander intervention and clinical research on psychopaths, that exposure to and correct interpretation of certain distress cues may predict an individual's likelihood of behaving prosocially.

Emotional bias and waking salivary cortisol in relatives of patients with major depression

Biases in the processing of emotional information have been shown to be abnormal in subjects with major depression, both during an episode and after full recovery. However, it is unclear whether these biases are a cause or an effect of the depression. This study set out to explore whether such biases represent a vulnerability factor for depression by looking at unaffected first-degree relatives of those with major depressive disorder. We also measured waking salivary cortisol, as the regulation of the hypothalamo-pituitary-adrenal (HPA) axis is thought to be impaired in depressive disorder. Twenty-five female relatives and 21 age-matched controls completed a facial expression recognition task, an emotional categorization task with positive and negative personality characteristics, and had their waking salivary cortisol measured on a work day and a non-work day. The depressed relative group was significantly faster to recognize facial expressions of fear than controls. The depressed relative group also showed significantly increased reaction time to recognize positive versus negative personality characteristics in the categorization task. There was no difference in waking salivary cortisol between groups, although there was an effect of work day versus non-work day. Subtle biases in the processing of emotional information may exist in the unaffected first-degree relatives of those with depression. As such, this may represent a familial vulnerability factor to developing a depressive illness.

Bipolar Disorder: Imaging State Versus Trait

Bipolar Disorder: Imaging State Versus Trait

Evolutionary feature synthesis for facial expression recognition

Feature extraction is one of the key steps in object recognition. In this paper we propose a novel genetically inspired learning method for facial expression recognition (FER). Unlike current research on facial expression recognition that generally selects visually meaningful feature by hands, our learning method can discover the features automatically in a genetic programming-based approach that uses Gabor wavelet representation for primitive features and linear/nonlinear operators to synthesize new features. These new features are used to train a support vector machine classifier that is used for recognizing the facial expressions. The learned operator and classifier are used on unseen testing images. To make use of random nature of a genetic program, we design a multi-agent scheme to boost the performance. We compare the performance of our approach with several approaches in the literature and show that our approach can perform the task of facial expression recognition effectively.

Facial emotion recognition in trait anxiety

The study investigated the relationship between recognition of emotional facial expressions and trait anxiety. A nonclinical sample of 19 participants with high-trait anxiety was selected, using the trait version of the State-Trait Anxiety Inventory, and compared with a sample of 20 participants with low-trait anxiety on a facial expression recognition task. Visual stimuli were 42 faces, representing seven emotional expressions: anger, sadness, happiness, fear, surprise, disgust and neutral. Participants had to identify the emotion portrayed by each face. Results showed that participants with high-trait anxiety recognized fear faces significantly better while the two groups did not differ in recognition of other facial expressions.

The acute and sub-acute effects of ‘ecstasy’ (MDMA) on processing of facial expressions: preliminary findings

Rationale: There is evidence that serotonergic processes may modulate the processing of fearful facial expressions. It is therefore possible that the recreational drug ‘ecstasy’ (MDMA), which has marked serotonergic effects, may affect people's ability to recognise human facial expressions portraying fear. Objective: The present study therefore aimed to determine whether ecstasy users differed from controls in fear recognition at two time points: shortly after taking the drug and a few days later. Methods: Sixteen ecstasy users and 21 controls were compared on a facial expression recognition task involving the 6 basic emotions (happiness, surprise, sadness, anger, fear and disgust) and on self-ratings of mood on the night of drug use (day 0) and 4 days later (day 4). Results: In recognising fearful facial expressions, ecstasy users were more accurate than controls on day 0 but less accurate than them on day 4 when compared with their overall ability to recognise other basic emotions. Accuracy of fear recognition on day 4 was negatively correlated with both years of ecstasy use and number of ecstasy tablets taken on a typical session. On self-rated aggression scales, ecstasy users scored lower than controls on day 0 and higher on day 4. Conclusions: These results support the notion that 5-HT plays a role in modulating the recognition of fearful facial expressions. Increased accuracy of fear recognition may relate to 5-HT release following ecstasy use on day 0, and decreased accuracy may reflect subsequent depletion of 5-HT mid-week.

An investigation of the relationship between trait emotional intelligence and emotional task performance

This study examined the relationships between trait emotional intelligence (EI) and tasks involving the recognition of facial expressions of emotion. Two facial expression recognition tasks using the inspection time (IT) paradigm assessed speed of emotional information processing. An unspeeded emotion recognition task was also included, and a symbol IT task was used to assess speed of processing of non-emotional information. It was found that scores on all three emotion-related tasks were strongly intercorrelated, as were scores on the three IT tasks. The two emotional IT scores remained significantly correlated when symbol IT performance was partialled out. This finding, together with the associations between the speeded (IT) and unspeeded face tasks suggests that the association between the emotional IT tasks is not entirely accounted for by general processing speed, and that a general emotion-processing ability also contributes to performance on these tasks. An EI subscale assessing Appraisal of Emotions was significantly correlated with performance on the emotional IT tasks, suggesting that self-reports of emotional perception ability do relate to performance measures.