Computational methods for integrative evaluation of confidence, accuracy, and reaction time in facial affect recognition in schizophrenia.
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ABSTRACT:
SUBMITTER: Badal VD
PROVIDER: S-EPMC8093458 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: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.
| S-EPMC8124197 | biostudies-literature
Project description:While impaired facial emotion recognition and magnocellular deficits in visual perception are core features of schizophrenia, their relationship is still unclear. Our aim was to analyze the oscillatory background of these processes and to investigate the connection between the magnocellular pathway deficit and the abnormal facial affect processing. Thirty-nine subjects with schizophrenia and forty socially matched healthy controls subjects were enrolled. A 128 channel EEG was recorded in three experimental tasks: first, participants viewed magnocellular biased low-spatial frequency (LSF) and parvocellular biased high-spatial frequency (HSF) Gabor-patches, then faces and houses were presented and in the third task a facial affect recognition task was presented with happy, sad and neutral faces. Event-related theta (4-7 Hz) synchronization (ERS) (i.e. an increase in theta power) by magnocellular biased stimuli was decreased in patients relative to controls, while no similar differences were found between groups in the parvocellular biased condition. ERS was significantly lower in patients compared to healthy controls both in the face and in the emotion recognition task. Theta ERS to magnocellular biased stimuli, but not to parvocellular biased stimuli, were correlated with emotion recognition performance. These findings indicate a bottom up disruption of face perception and emotion recognition in schizophrenia.
| S-EPMC6586813 | biostudies-literature
Project description:Deficits in social cognition including facial affect recognition and their detrimental effects on functional outcome are well established in schizophrenia. Structured training can have substantial effects on social cognitive measures including facial affect recognition. Elucidating training effects on cortical mechanisms involved in facial affect recognition may identify causes of dysfunctional facial affect recognition in schizophrenia and foster remediation strategies. In the present study, 57 schizophrenia patients were randomly assigned to (a) computer-based facial affect training that focused on affect discrimination and working memory in 20 daily 1-hour sessions, (b) similarly intense, targeted cognitive training on auditory-verbal discrimination and working memory, or (c) treatment as usual. Neuromagnetic activity was measured before and after training during a dynamic facial affect recognition task (5 s videos showing human faces gradually changing from neutral to fear or to happy expressions). Effects on 10-13 Hz (alpha) power during the transition from neutral to emotional expressions were assessed via MEG based on previous findings that alpha power increase is related to facial affect recognition and is smaller in schizophrenia than in healthy subjects. Targeted affect training improved overt performance on the training tasks. Moreover, alpha power increase during the dynamic facial affect recognition task was larger after affect training than after treatment-as-usual, though similar to that after targeted perceptual-cognitive training, indicating somewhat nonspecific benefits. Alpha power modulation was unrelated to general neuropsychological test performance, which improved in all groups. Results suggest that specific neural processes supporting facial affect recognition, evident in oscillatory phenomena, are modifiable. This should be considered when developing remediation strategies targeting social cognition in schizophrenia.
| S-EPMC4215531 | biostudies-literature
Project description:Although Schizophrenia (SCZ) and Autism Spectrum Disorder (ASD) share impairments in emotion recognition, the mechanisms underlying these impairments may differ. The current study used the novel "Emotions in Context" task to examine how the interpretation and visual inspection of facial affect is modulated by congruent and incongruent emotional contexts in SCZ and ASD. Both adults with SCZ (n= 44) and those with ASD (n= 21) exhibited reduced affect recognition relative to typically-developing (TD) controls (n= 39) when faces were integrated within broader emotional scenes but not when they were presented in isolation, underscoring the importance of using stimuli that better approximate real-world contexts. Additionally, viewing faces within congruent emotional scenes improved accuracy and visual attention to the face for controls more so than the clinical groups, suggesting that individuals with SCZ and ASD may not benefit from the presence of complementary emotional information as readily as controls. Despite these similarities, important distinctions between SCZ and ASD were found. In every condition, IQ was related to emotion-recognition accuracy for the SCZ group but not for the ASD or TD groups. Further, only the ASD group failed to increase their visual attention to faces in incongruent emotional scenes, suggesting a lower reliance on facial information within ambiguous emotional contexts relative to congruent ones. Collectively, these findings highlight both shared and distinct social cognitive processes in SCZ and ASD that may contribute to their characteristic social disabilities.
| S-EPMC4838097 | biostudies-literature
Project description: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.
| S-EPMC7833130 | biostudies-literature
Project description:The development of biometric applications, such as facial recognition (FR), has recently become important in smart cities. Many scientists and engineers around the world have focused on establishing increasingly robust and accurate algorithms and methods for these types of systems and their applications in everyday life. FR is developing technology with multiple real-time applications. The goal of this paper is to develop a complete FR system using transfer learning in fog computing and cloud computing. The developed system uses deep convolutional neural networks (DCNN) because of the dominant representation; there are some conditions including occlusions, expressions, illuminations, and pose, which can affect the deep FR performance. DCNN is used to extract relevant facial features. These features allow us to compare faces between them in an efficient way. The system can be trained to recognize a set of people and to learn via an online method, by integrating the new people it processes and improving its predictions on the ones it already has. The proposed recognition method was tested with different three standard machine learning algorithms (Decision Tree (DT), K Nearest Neighbor(KNN), Support Vector Machine (SVM)). The proposed system has been evaluated using three datasets of face images (SDUMLA-HMT, 113, and CASIA) via performance metrics of accuracy, precision, sensitivity, specificity, and time. The experimental results show that the proposed method achieves superiority over other algorithms according to all parameters. The suggested algorithm results in higher accuracy (99.06%), higher precision (99.12%), higher recall (99.07%), and higher specificity (99.10%) than the comparison algorithms.
| S-EPMC7714107 | biostudies-literature
Project description:Facial affect recognition deficits following traumatic brain injury (TBI) have been well documented, as has their relationship with impairment in several other cognitive domains. However, little is known about the neurobiological mechanisms underlying affect recognition deficits, in particular mechanisms underlying different aspects of facial affect recognition (e.g., perceptual and interpretive processes). In the current study, 33 adults with moderate-to-severe TBI and 24 demographically matched healthy comparison (HC) participants completed an fMRI facial affect recognition study. While in the scanner, participants were asked to match the affect of a target face to either (a) one of two faces differing in affect (perceptual condition) or (b) one of two written affect labels (interpretative condition). In both groups we found activations in regions typically involved in affect recognition. Our results revealed that in the perceptual condition individuals with TBI tended to activate the left dorsolateral prefrontal cortex less than HCs, and within the HC group individuals with higher perceptual affect recognition scores showed higher levels of activation in the same brain region. Individuals with TBI who were specifically impaired at interpretative affect recognition showed less activation than HCs in the right fusiform gyrus. Moreover, in the labeling condition individuals with TBI tended to de-activate medial prefrontal regions less than HCs. A region of interest analysis revealed that individuals with TBI showed significantly less activation than HCs in the FFA for all the contrasts of interest. Our results suggest involvement of several brain regions in facial affect recognition impairment post TBI, and provide neurobiological support for the notion that distinct aspects of facial affect recognition can be differentially impaired following TBI.
| S-EPMC6222017 | biostudies-literature
Project description:Past research indicates that spontaneous mimicry facilitates the decoding of others' emotions, leading to enhanced social perception and interpersonal rapport. Individuals with schizophrenia (SZ) show consistent deficits in emotion recognition and expression associated with poor social functioning. Given the prominence of blunted affect in schizophrenia, it is possible that spontaneous facial mimicry may also be impaired. However, studies assessing automatic facial mimicry in schizophrenia have yielded mixed results. It is therefore unknown whether emotion recognition deficits and impaired automatic facial mimicry are related in schizophrenia. SZ and demographically matched controls (CO) participated in a dynamic emotion recognition task. Electromyographic activity in muscles responsible for producing facial expressions was recorded during the task to assess spontaneous facial mimicry. SZ showed deficits in emotion identification compared to CO, but there was no group difference in the predictive power of spontaneous facial mimicry for avatar's expressed emotion. In CO, facial mimicry supported accurate emotion recognition, but it was decoupled in SZ. The finding of intact facial mimicry in SZ bears important clinical implications. For instance, clinicians might be able to improve the social functioning of patients by teaching them to pair specific patterns of facial muscle activation with distinct emotion words.
| S-EPMC8080256 | biostudies-literature
Project description:Although deficits in facial affect processing have been reported in schizophrenia as well as in borderline personality disorder (BPD), these disorders have not yet been directly compared on facial affect labeling. Using degraded stimuli portraying neutral, angry, fearful and angry facial expressions, we hypothesized more errors in labeling negative facial expressions in patients with schizophrenia compared to healthy controls. Patients with BPD were expected to have difficulty in labeling neutral expressions and to display a bias towards a negative attribution when wrongly labeling neutral faces. Patients with schizophrenia (N = 57) and patients with BPD (N = 30) were compared to patients with somatoform disorder (SoD, a psychiatric control group; N = 25) and healthy control participants (N = 41) on facial affect labeling accuracy and type of misattributions. Patients with schizophrenia showed deficits in labeling angry and fearful expressions compared to the healthy control group and patients with BPD showed deficits in labeling neutral expressions compared to the healthy control group. Schizophrenia and BPD patients did not differ significantly from each other when labeling any of the facial expressions. Compared to SoD patients, schizophrenia patients showed deficits on fearful expressions, but BPD did not significantly differ from SoD patients on any of the facial expressions. With respect to the type of misattributions, BPD patients mistook neutral expressions more often for fearful expressions compared to schizophrenia patients and healthy controls, and less often for happy compared to schizophrenia patients. These findings suggest that although schizophrenia and BPD patients demonstrate different as well as similar facial affect labeling deficits, BPD may be associated with a tendency to detect negative affect in neutral expressions.
| S-EPMC4907495 | biostudies-literature
Project description:Individual genetic differences in the serotonin transporter-linked polymorphic region (5-HTTLPR) have been associated with variations in the sensitivity to social and emotional cues as well as altered amygdala reactivity to facial expressions of emotion. Amygdala activation has further been shown to trigger gaze changes toward diagnostically relevant facial features. The current study examined whether altered socio-emotional reactivity in variants of the 5-HTTLPR promoter polymorphism reflects individual differences in attending to diagnostic features of facial expressions. For this purpose, visual exploration of emotional facial expressions was compared between a low (n = 39) and a high (n = 40) 5-HTT expressing group of healthy human volunteers in an eye tracking paradigm. Emotional faces were presented while manipulating the initial fixation such that saccadic changes toward the eyes and toward the mouth could be identified. We found that the low vs. the high 5-HTT group demonstrated greater accuracy with regard to emotion classifications, particularly when faces were presented for a longer duration. No group differences in gaze orientation toward diagnostic facial features could be observed. However, participants in the low 5-HTT group exhibited more and faster fixation changes for certain emotions when faces were presented for a longer duration and overall face fixation times were reduced for this genotype group. These results suggest that the 5-HTT gene influences social perception by modulating the general vigilance to social cues rather than selectively affecting the pre-attentive detection of diagnostic facial features.
| S-EPMC4107864 | biostudies-literature