Validation of dynamic virtual faces for facial affect recognition

The ability to recognise facial emotions is essential for successful social interaction. The most common stimuli used when evaluating this ability are photographs. Although these stimuli have proved to be valid, they do not offer the level of realism that virtual humans have achieved. The objective of the present paper is the validation of a new set of dynamic virtual faces (DVFs) that mimic the six basic emotions plus the neutral expression. The faces are prepared to be observed with low and high dynamism, and from front and side views. For this purpose, 204 healthy participants, stratified by gender, age and education level, were recruited for assessing their facial affect recognition with the set of DVFs. The accuracy in responses was compared with the already validated Penn Emotion Recognition Test (ER-40). The results showed that DVFs were as valid as standardised natural faces for accurately recreating human-like facial expressions. The overall accuracy in the identification of emotions was higher for the DVFs (88.25%) than for the ER-40 faces (82.60%). The percentage of hits of each DVF emotion was high, especially for neutral expression and happiness emotion. No statistically significant differences were discovered regarding gender. Nor were significant differences found between younger adults and adults over 60 years. Moreover, there is an increase of hits for avatar faces showing a greater dynamism, as well as front views of the DVFs compared to their profile presentations. DVFs are as valid as standardised natural faces for accurately recreating human-like facial expressions of emotions.

Download Full-text

Behavioural and neurocognitive responses to sad facial affect are attenuated in patients with mania

Psychological Medicine ◽

10.1017/s0033291704002557 ◽

2004 ◽

Vol 34 (5) ◽

pp. 795-802 ◽

Cited By ~ 126

Author(s):

B. R. LENNOX ◽

R. JACOB ◽

A. J. CALDER ◽

V. LUPSON ◽

E. T. BULLMORE

Keyword(s):

Mood Disorders ◽

Facial Expressions ◽

Negative Emotions ◽

Brain Activation ◽

Facial Affect ◽

Anterior Cingulate ◽

Facial Emotion ◽

Subjective Rating ◽

Affect Recognition ◽

Facial Affect Recognition

Background. The processing of facial emotion involves a distributed network of limbic and paralimbic brain structures. Many of these regions are also implicated in the pathophysiology of mood disorders. Behavioural data indicate that depressed subjects show a state-related positive recognition bias for faces displaying negative emotions. There are sparse data to suggest there may be an analogous, state-related negative recognition bias for negative emotions in mania. We used functional magnetic resonance imaging (fMRI) to investigate the behavioural and neurocognitive correlates of happy and sad facial affect recognition in patients with mania.Method. Functional MRI and an explicit facial affect recognition task were used in a case-control design to measure brain activation and associated behavioural response to variable intensity of sad and happy facial expressions in 10 patients with bipolar I mania and 12 healthy comparison subjects.Results. The patients with mania had attenuated subjective rating of the intensity of sad facial expressions, and associated attenuation of activation in the subgenual anterior cingulate and bilateral amygdala, with increased activation in the posterior cingulate and posterior insula. No behavioural or neurocognitive abnormalities were found in response to presentation of happy facial expressions.Conclusions. Patients with mania showed a specific, mood-congruent, negative bias in sad facial affect recognition, which was associated with an abnormal profile of brain activation in paralimbic regions implicated in affect recognition and mood disorders. Functional imaging of facial emotion recognition may be a useful probe of cortical and subcortical abnormalities in mood disorders.

Download Full-text

Increased visual-ventral prefrontal cortical coupling during facial affect recognition

European Psychiatry ◽

10.1016/s0924-9338(11)72625-6 ◽

2011 ◽

Vol 26 (S2) ◽

pp. 920-920

Author(s):

D. Dima ◽

K.E. Stephan ◽

J.P. Roiser ◽

S. Frangou

Keyword(s):

Visual Cortex ◽

Facial Expressions ◽

Emotional Regulation ◽

Bayesian Model ◽

Bayesian Model Averaging ◽

Facial Affect ◽

Current Evidence ◽

Adaptive Behaviour ◽

Affect Recognition ◽

Facial Affect Recognition

IntroductionEmotional regulation is a crucial aspect of adaptive behaviour and social interaction, and is often disrupted in a range of psychiatric disorders.ObjectivesIn the past decade, neuroimaging studies have identified key components of the neural networks that underpin emotional processing during facial affect recognition. Although these networks are extremely interconnected, current evidence points to the ventral prefrontal cortex (VPFC) as having a pivotal role in emotional regulation.AimsWe were particularly interested in specifying the functional interrelationships of VPFC with component network regions and in exploring potential modulation by the valence of the facial affect.MethodsFunctional magnetic resonance imaging (fMRI) data were obtained from 40 healthy individuals during a facial affect recognition task involving fearful, sad and angry facial expressions. Within the networks engaged by the task, we used Dynamic Causal Modelling (DCM) to measure effective connectivity followed by Bayesian Model Selection to identify the model best model fitting our data and Bayesian Model Averaging to analyze the endogenous connections and the modulatory influence of affect.ResultsProcessing of all three facial expressions engaged the visual cortex, fusiform gyrus, amygdala and VPFC. DCM analysis showed that the connection between the visual cortex and the VPFC plays a more important role in the recognition of facial emotions than other regions.ConclusionsWe provide evidence for the central role of a valence independent increase in visual cortical and VPFC coupling during the processing of facial affect.

Download Full-text

Facial Affect Recognition Deficit as a Marker of Genetic Vulnerability to Schizophrenia

The Spanish Journal of Psychology ◽

10.1017/s1138741600001463 ◽

2009 ◽

Vol 12 (1) ◽

pp. 46-55 ◽

Cited By ~ 35

Author(s):

Margarita V. Alfimova ◽

Lilia I. Abramova ◽

Aleksandra I. Barhatova ◽

Polina E. Yumatova ◽

Galina L. Lyachenko ◽

...

Keyword(s):

Verbal Memory ◽

Molecular Genetic ◽

Facial Affect ◽

Affect Recognition ◽

Facial Affect Recognition ◽

Emotional States ◽

Basic Emotions ◽

Schizotypal Personality ◽

Black And White ◽

History Of

The aim of this study was to investigate the possibility that affect recognition impairments are associated with genetic liability to schizophrenia. In a group of 55 unaffected relatives of schizophrenia patients (parents and siblings) we examined the capacity to detect facially expressed emotions and its relationship to schizotypal personality, neurocognitive functioning, and the subject's actual emotional state. The relatives were compared with 103 schizophrenia patients and 99 healthy subjects without any family history of psychoses. Emotional stimuli were nine black-and-white photos of actors, who portrayed six basic emotions as well as interest, contempt, and shame. The results evidenced the affect recognition deficit in relatives, though milder than that in patients themselves. No correlation between the deficit and schizotypal personality measured with SPQ was detected in the group of relatives. Neither cognitive functioning, including attention, verbal memory and linguistic ability, nor actual emotional states accounted for their affect recognition impairments. The results suggest that the facial affect recognition deficit in schizophrenia may be related to genetic predisposition to the disorder and may serve as an endophenotype in molecular-genetic studies.

Download Full-text

Facial Affect Recognition by Patients with Schizophrenia Using Human Avatars

Journal of Clinical Medicine ◽

10.3390/jcm10091904 ◽

2021 ◽

Vol 10 (9) ◽

pp. 1904

Author(s):

Nora I. Muros ◽

Arturo S. García ◽

Cristina Forner ◽

Pablo López-Arcas ◽

Guillermo Lahera ◽

...

Keyword(s):

Facial Expressions ◽

Recognition Rate ◽

Facial Affect ◽

Affect Recognition ◽

Control Group ◽

Facial Affect Recognition ◽

Healthy Controls ◽

Virtual Humans ◽

Training Interventions ◽

Recognition Of Emotions

People with schizophrenia have difficulty recognizing the emotions in the facial expressions of others, which affects their social interaction and functioning in the community. Static stimuli such as photographs have been used traditionally to examine deficiencies in the recognition of emotions in patients with schizophrenia, which has been criticized by some authors for lacking the dynamism that real facial stimuli have. With the aim of overcoming these drawbacks, in recent years, the creation and validation of virtual humans has been developed. This work presents the results of a study that evaluated facial recognition of emotions through a new set of dynamic virtual humans previously designed by the research team, in patients diagnosed of schizophrenia. The study included 56 stable patients, compared with 56 healthy controls. Our results showed that patients with schizophrenia present a deficit in facial affect recognition, compared to healthy controls (average hit rate 71.6% for patients vs 90.0% for controls). Facial expressions with greater dynamism (compared to less dynamic ones), as well as those presented from frontal view (compared to profile view) were better recognized in both groups. Regarding clinical and sociodemographic variables, the number of hospitalizations throughout life did not correlate with recognition rates. There was also no correlation between functioning or quality of life and recognition. A trend showed a reduction in the emotional recognition rate as a result of increases in Positive and Negative Syndrome Scale (PANSS), being statistically significant for negative PANSS. Patients presented a learning effect during the progression of the task, slightly greater in comparison to the control group. This finding is relevant when designing training interventions for people with schizophrenia. Maintaining the attention of patients and getting them to improve in the proposed tasks is a challenge for today’s psychiatry.

Download Full-text