Facial Emotion Recognition Deficits Research Articles

Facial Emotion Recognition in Older Adults With Cognitive Complaints.

Facial emotion recognition deficits impact the daily life, particularly of Alzheimer's disease patients. We aimed to assess these deficits in the following three groups: subjective cognitive decline (SCD), mild cognitive impairment (MCI), and mild Alzheimer's dementia (AD). Additionally, we explored the associations between facial emotion recognition and cognitive performance. We used the Korean version of the Florida Facial Affect Battery (K-FAB) in 72 SCD, 76 MCI, and 76 mild AD subjects. The comparison was conducted using the analysis of covariance (ANCOVA), with adjustments being made for age and sex. The Mini-Mental State Examination (MMSE) was utilized to gauge the overall cognitive status, while the Seoul Neuropsychological Screening Battery (SNSB) was employed to evaluate the performance in the following five cognitive domains: attention, language, visuospatial abilities, memory, and frontal executive functions. The ANCOVA results showed significant differences in K-FAB subtests 3, 4, and 5 (p=0.001, p=0.003, and p=0.004, respectively), especially for anger and fearful emotions. Recognition of 'anger' in the FAB subtest 5 declined from SCD to MCI to mild AD. Correlations were observed with age and education, and after controlling for these factors, MMSE and frontal executive function were associated with FAB tests, particularly in the FAB subtest 5 (r=0.507, p<0.001 and r=-0.288, p=0.026, respectively). Emotion recognition deficits worsened from SCD to MCI to mild AD, especially for negative emotions. Complex tasks, such as matching, selection, and naming, showed greater deficits, with a connection to cognitive impairment, especially frontal executive dysfunction.

Specific facial emotion recognition deficits across the course of psychosis: A comparison of individuals with low-risk, high-risk, first-episode psychosis and multi-episode schizophrenia-spectrum disorders

Our study aimed to explore the recognition of specific emotions across the course of psychosis.A visual task representing the six basic emotions was used to assess facial emotion recognition (FER) in 204 healthy controls classified into 152 low-risk (LR) and 52 high-risk for psychosis (HR), following a psychometric risk approach; and 100 patients: 44 with first-episode psychosis (FEP) and 56 with multi-episode schizophrenia-spectrum disorders (MES). First, we performed a MANCOVA to compare the four conditions. Next, we conducted a logistic regression to explore whether specific FER deficits predicted the presence of psychosis. Finally, we investigated the relationships of FER with psychosis-like experiences (PLEs) and psychotic symptoms.Global FER, anger and fear recognition were impaired in HR, FEP and MES. No differences between HR and FEP appeared. Moreover, fear and anger correctly classified 83% of individuals into LR or psychosis. FER was associated with PLEs and psychotic symptoms.Concluding, FER is early impaired in HR individuals and increases along the psychosis continuum. However, fear recognition is similarly impaired throughout the illness, suggesting a possible vulnerability marker. Furthermore, deficits in anger and fear recognition predicted the presence of psychosis. Therefore, we suggest that FER may be essential in detecting psychosis risk.

Facial Emotion Recognition Deficit in Children with Moderate/Severe Obstructive Sleep Apnea.

Although previous studies have reported a facial expression classification deficit among adults with SDB, we do not know whether these findings can be generalized to children. In our study, children with sleep-disordered breathing (SDB) were divided into three groups: primary snoring (n = 51), mild obstructive sleep apnea (OSA) (n = 39), and moderate/severe OSA (n = 26). All participants, including 20 healthy controls, underwent an overnight polysomnography recording and the Emotional Expression Recognition Task. Psychosocial problems were evaluated using the parent-reported Strengths and Difficulties Questionnaire (SDQ). There was a borderline significant interaction between expression category and group on reaction times. Further analysis revealed that positive classification advantage (PCA) disappeared in the moderate/severe OSA group, whereas it persisted in the control, primary snoring, and mild OSA groups. Emotional symptoms were positively correlated with OAHI. In both the happy and sad conditions, RT was negatively related to age and body mass index (BMI) but was independent of the obstructive apnea-hypopnea index (OAHI), arterial oxygen (SaO2) and total sleep time. The accuracy of identifying a sad expression was negatively related to conduct problems. Children with moderate/severe OSA exhibited dysfunction in facial expression categorization, which could potentially affect social communication ability.

Facial emotion perception and recognition deficits in acute ischemic stroke

BackgroundFacial emotion perception and recognition (FEPR) deficits are the sources of disability, impaired social relationship, and reduced quality of life. Studies of unilateral acute ischemic stroke (AIS) remain controversial about FEPR deficits. MethodsClinical and neurocognitive data were collected and analyzed among normal controls (NC) and AIS patients with left brain damage (LBD), right brain damage (RBD), and infratentorial brain damage (IBD). To assess FEPR, all participants completed a localization test (the Southeastern China Brief Affect Recognition Test). Correlation analyses were conducted between the FEPR deficits and cognitive functions. ResultsCompared with NC, all three groups of AIS patients reported significant FEPR deficits. Although no statistical difference in FEPR deficits were observed among the LBD, RBD and IBD patients, the deficit patterns were markedly different. FEPR deficits were positively correlated with cognitive impairment. ConclusionsFEPR deficits may occur in AIS patients and are associated with impaired cognitive functions, where the cerebral hemispheres and the infratentorial brain are jointly involved. Early recognition and early intervention of FEPR deficits in AIS patients are critical for post-stroke rehabilitation, reconstruction of social function and improvement in life quality.

Social cognition training improves recognition of distinct facial emotions and decreases misattribution errors in healthy individuals.

Facial emotion recognition is a key component of social cognition. Impaired facial emotion recognition is tied to poor psychological wellbeing and deficient social functioning. While previous research has demonstrated the potential for social cognition training to improve overall facial emotion recognition, questions remain regarding what aspects of emotion recognition improve. We report results from a randomized controlled trial that evaluates whether computerized social cognition training can improve recognition of distinct facial emotions in healthy participants. This investigation was designed to better understand the therapeutic potential of social cognition training for individuals with neuropsychiatric disorders. Fifty-five healthy adult participants were randomly assigned to an internet-based intervention during which they either completed social cognition training (SCT) or played control computer games (CON) for 10.5 h over 2-3 weeks. Facial emotion recognition was measured with the Penn ER-40, which was conducted before and after training. The following variables were collected and analyzed: facial emotion recognition accuracy for each emotion (i.e., anger, fear, happy, neutral (no emotional expression), and sad), reaction times for each emotion, and response error types (i.e., frequency of an emotion being chosen incorrectly, frequency of an emotion being missed, and frequency of an emotion being confused for another particular emotion). ANOVAs and t-tests were used to elucidate intervention effects both within and between groups. Results showed that the SCT group improved their accuracy for angry and neutral faces. They also improved their reaction times for neutral, fearful, and sad faces. Compared to the CON group, the SCT group had significantly faster reaction times to neutral faces after training. Lastly, the SCT group decreased their tendency to confuse angry faces for no emotional expression and to confuse no emotional expression for sad faces. In contrast, the CON group did not significantly improve their accuracy or reaction times on any emotional expression, and they did not improve their response error types. We conclude that social cognition training can improve recognition of distinct emotions in healthy participants and decrease response error patterns, suggesting it has the potential to improve impaired emotion recognition and social functioning in individuals with facial emotion recognition deficits.

An fMRI examination of the neural basis of suicide attempts: The role of mentalizing in the context of mood.

Facial emotion recognition (FER) deficits in depressed mood disorder patients contribute to suicidality. Prior research shows that intrinsic brain activity patterns are altered by attempting suicide. Therefore, we investigated in depressed patients whether differences in FER contribute to their clinical symptoms of suicide. Neural activity in response to an FER task was compared across three groups: healthy controls (HCs, N=66), suicide non-attempter (SNA, N=50), suicide attempter (SA, N=25). Modulation of brain networks by the task and functional connectivity (FC) within (using spatial map, spectral power) and between (using functional network connectivity; FNC) were examined. The contribution of these differences to suicidal symptoms in each group was also examined. Patient groups displayed impaired FC both within and between networks but differed in nature and networks involved. They also showed differential modulation of networks by task, such that compared with both HC and SNA, SA displayed impaired FC within the default-mode network (DMN) and also its task modulation. In the SA group, FC within the DMN and FNC between two lateral prefrontal networks, and its interaction with the basal ganglia network contributed significantly to the clinical symptoms of suicide. This study affirms differences between SA and SNA brain activity patterns and suggests that suicidal activity probably emanates via different mechanisms in these patient groups. Perhaps, over-attribution of emotion impairs one's self-referential thought processes and coupled with diminished emotional control this makes depressed individuals vulnerable to suicide.

Is There a Difference in Facial Emotion Recognition after Stroke with vs. without Central Facial Paresis?

The Facial Feedback Hypothesis (FFH) states that facial emotion recognition is based on the imitation of facial emotional expressions and the processing of physiological feedback. In the light of limited and contradictory evidence, this hypothesis is still being debated. Therefore, in the present study, emotion recognition was tested in patients with central facial paresis after stroke. Performance in facial vs. auditory emotion recognition was assessed in patients with vs. without facial paresis. The accuracy of objective facial emotion recognition was significantly lower in patients with vs. without facial paresis and also in comparison to healthy controls. Moreover, for patients with facial paresis, the accuracy measure for facial emotion recognition was significantly worse than that for auditory emotion recognition. Finally, in patients with facial paresis, the subjective judgements of their own facial emotion recognition abilities differed strongly from their objective performances. This pattern of results demonstrates a specific deficit in facial emotion recognition in central facial paresis and thus provides support for the FFH and points out certain effects of stroke.

Facial emotion recognition deficits in first-degree relatives of patients with bipolar disorder: a systematic review protocol

IntroductionBipolar Disorder (BD) is one of the most challenging and severe psychiatric disorders. Considerable research in BD patients points to deficits in Facial Emotion Recognition (FER) as a potential BD endophenotype. Accordingly, such deficits have also been found in unaffected BD first-degree relatives, but no study has been conducted to synthetize this evidence.ObjectivesTo conduct a systematic review of studies exploring FER deficits in first-degree relatives of patients with BD.MethodsPRISMA 2020 recommendations will be followed. PubMed, Scopus, Web of Science and SciELO electronic bibliographic databases will be searched, as well as grey literature. Reference lists of the included studies will be hand-searched for additional eligible studies. Search strategy will include key-terms in accordance with the pre-established PICOS definition. No restrictions will apply regarding study design, setting, publication date nor language. Outcomes of interest will be FER deficits. Retrieved studies will be screened for eligibility by two independent reviewers using a two-phase approach. The methodological quality of primary studies will be assessed and data extracted independently using a standardized extraction form.Resultswill be described using narrative and tabular approaches. Studies heterogeneity will be verified and if adequate a meta-analysis will be conducted. Findings will be disseminated through a peer-reviewed publication.ConclusionsIt is expected that this systematic review will support the hypothesis that FER deficits may constitute a potential candidate for a BD endophenotype, which will not only improve the understanding of BD neurobiology, but also enable its identification in earlier stages, allowing timely treatments and better patients’ outcomes.DisclosureNo significant relationships.

The facial emotion recognition deficit in Parkinson's disease: Implications of a visual scanning strategy.

We explored the relationship between a visual scanning strategy and a facial emotion recognition deficit in Parkinson's disease (PD). Thirty nondemented PD patients (balanced for symptom side at onset) and 20 age, education and gender-matched healthy controls (HC) were enrolled. The PD group underwent a comprehensive neuropsychological battery also exploring the executive functions. In both groups, eye movements were recorded while subjects categorized facial emotion from Ekman's 60-faces test. We were particularly interested in the location of fixations on facial pictures (top vs. bottom) and in emotional valence (positive vs. negative). We also compared performance of the two groups on a verbal emotion attribution task. Compared to HC, PD patients performed worse on visual recognition of negative emotions such as anger, fear, and sadness (where the upper part of the face is more informative than the lower part); the two groups did not differ on the verbal emotion attribution task. HC modified their visual scanning strategy (both number and overall time duration of fixations) according to the valence of the emotion; by contrast, PD showed the same pattern regardless of the valence. In the PD group, accuracy in the visual recognition of negative emotions and fixation pattern correlated with performance on tasks exploring executive functions; however, no associations were observed with severity of motor state. Our results suggest that visual scanning strategy contributes significantly to the facial emotion recognition deficit of PD patients, especially at a "high level" related to cognitive control of eye movements. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Facial Emotion Recognition in Psychosis and Associations With Polygenic Risk for Schizophrenia: Findings From the Multi-Center EU-GEI Case–Control Study

Background and HypothesisFacial Emotion Recognition is a key domain of social cognition associated with psychotic disorders as a candidate intermediate phenotype. In this study, we set out to investigate global and specific facial emotion recognition deficits in first-episode psychosis, and whether polygenic liability to psychotic disorders is associated with facial emotion recognition.Study Design828 First Episode Psychosis (FEP) patients and 1308 population-based controls completed assessments of the Degraded Facial Affect Recognition Task (DFAR) and a subsample of 524 FEP and 899 controls provided blood or saliva samples from which we extracted DNA, performed genotyping and computed polygenic risk scores for schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MD).Study ResultsA worse ability to globally recognize facial emotion expressions was found in patients compared with controls [B= −1.5 (0.6), 95% CI −2.7 to −0.3], with evidence for stronger effects on negative emotions (fear [B = −3.3 (1.1), 95% CI −5.3 to −1.2] and anger [B = −2.3 (1.1), 95% CI −4.6 to −0.1]) than on happiness [B = 0.3 (0.7), 95% CI −1 to 1.7]. Pooling all participants, and controlling for confounds including case/control status, facial anger recognition was associated significantly with Schizophrenia Polygenic Risk Score (SZ PRS) [B = −3.5 (1.7), 95% CI −6.9 to −0.2].ConclusionsPsychosis is associated with impaired recognition of fear and anger, and higher SZ PRS is associated with worse facial anger recognition. Our findings provide evidence that facial emotion recognition of anger might play a role as an intermediate phenotype for psychosis.

Reading and reacting to faces, the effect of facial mimicry in improving facial emotion recognition in individuals with antisocial behavior and psychopathic traits

Individuals with antisocial behavior and psychopathic traits are characterized by deficits in processing facial expressions, which results in poor social adaptation and dysfunctional interpersonal relationships. However, it is not clear how individuals with varying levels of these traits differ in this emotional impairment and if these deficits are due to correctly identifying or reacting appropriately to facial expressions. The aim of the study was to examine how individuals with these traits recognized and responded to affective facial expressions by using FaceReader software (which analyses footage of faces) across different experimental conditions (imitation, suppression, and control). Imitating facial expressions was introduced to examine whether it could direct participants’ attention to the facial cues and improve participants’ performance on the facial task. A total of 643 individuals from the community were pre-screened and a sample (N = 107; M age = 21.08, SD = 1.55), differentiated on levels of antisocial personality disorder (APD) symptoms and psychopathic (PSY) traits, who were selected based on extreme scores (high/low), were invited to participate in the study. Individuals with higher levels of APD symptoms and PSY traits (APD + PSY) expressed more anger than other groups, while those in the APD-only group expressed more sadness, compared to other groups. Overall, participants were compliant in following the instructions to imitate facial expressions. However, only the group with predominantly APD symptoms and the group with combined symptoms (APD + PSY) showed improvement in their accuracy ratings specifically when instructed to imitate facial expressions, compared to when no instructions were provided. The study offers a promising direction for targeting deficits in facial emotion recognition, suggesting that the deficits found in individuals with behavioral problems (with and without psychopathic traits) can be improved by asking them to imitate facial expressions.

Real-time facial emotion recognition deficits across the psychosis spectrum: A B-SNIP Study

Affective and non-affective psychotic disorders are associated with variable levels of impairment in affective processing, but this domain typically has been examined via presentation of static facial images. We compared performance on a dynamic facial expression identification task across six emotions (sad, fear, surprise, disgust, anger, happy) in individuals with psychotic disorders (bipolar with psychotic features [PBD] = 113, schizoaffective [SAD] = 163, schizophrenia [SZ] = 181) and healthy controls (HC; n = 236) derived from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP). These same individuals with psychotic disorders were also grouped by B-SNIP-derived Biotype (Biotype 1 [B1] = 115, Biotype 2 [B2] = 132, Biotype 3 [B3] = 158), derived from a cluster analysis applied to a large biomarker panel that did not include the current data. Irrespective of the depicted emotion, groups differed in accuracy of emotion identification (P < 0.0001). The SZ group demonstrated lower accuracy versus HC and PBD groups; the SAD group was less accurate than the HC group (Ps < 0.02). Similar overall group differences were evident in speed of identifying emotional expressions. Controlling for general cognitive ability did not eliminate most group differences on accuracy but eliminated almost all group differences on reaction time for emotion identification. Results from the Biotype groups indicated that B1 and B2 had more severe deficits in emotion recognition than HC and B3, meanwhile B3 did not show significant deficits. In sum, this characterization of facial emotion recognition deficits adds to our emerging understanding of social/emotional deficits across the psychosis spectrum.

Alexithymia and facial emotion recognition in patients with craniofacial pain and association of alexithymia with anxiety and depression: a systematic review with meta-analysis.

BackgroundWe aimed to determine the presence of alexithymia in patients with craniofacial pain (CFP) compared with asymptomatic individuals. Our secondary aims were to assess the relationship of alexithymia with anxiety and depression levels, as well as to assess the presence of facial emotion recognition deficit.MethodsMedline, Scielo and Google Scholar were searched, with the last search performed in 8 September 2021. Standardized mean differences (SMDs) and 95% CIs were calculated for relevant outcomes and were pooled in a meta-analysis using the random effects model. In addition, meta-analyses of correlations and a meta-regression of alexithymia with depression and anxiety were performed.ResultsRegarding alexithymia, assessed through the Toronto Alexithymia Scale (TAS), the results showed significant differences, with higher values in patients compared with asymptomatic individuals, with a large clinical effect (SMD 0.46; 95% CI [0.22–0.71]; heterogeneity-Q 66.86; p < 0.001; inconsistency (I2) = 81%). We found statistically significant correlations with a small clinical effect of alexithymia with anxiety and depression. The meta-regression showed no significant association between the TAS and anxiety or depression. With respect to facial emotion recognition, the results showed statistically significant differences, with greater recognition difficulty in patients compared with asymptomatic individuals, with a large clinical effect (SMD −1.17; 95% CI [−2.01 to −0.33]; heterogeneity-Q 2.97; p = 0.080; I2 = 66%).ConclusionsPatients with CFP showed alexithymia with moderate evidence. There was also moderate evidence indicating that these patients had significant deficits in facial emotion recognition compared with asymptomatic individuals. Furthermore, alexithymia showed statistically significant correlations with anxiety and depression levels.

Facial emotion recognition and its association with quality of life and socio-occupational functioning in patients with bipolar disorder and their first-degree relatives

Facial emotion recognition deficits (FERD) are common even in the remitted phase of bipolar disorder (BD). Research regarding FERD in first-degree relatives is inconclusive. This study aimed to assess the facial emotion recognition in remitted patients of bipolar disorder and first-degree relatives(FDR) in comparison with healthy controls. Correlation between FERD and quality of life and socio-occupational functioning was also assessed. It was an observational, cross-sectional study done at a tertiary hospital in India. Study population (n=75) included remitted patients of bipolar disorder (n=27), first-degree relatives of BD patients (FDR) (n=20) and healthy controls (HC) (n=28). Facial emotion recognition, social and occupational functioning, and quality of life (QoL) was measured using Tool for Recognition of Emotions in Neuropsychiatric Disorders, Social & Occupational Functioning Assessment Scale and World Health Organization Quality of Life-Bref, respectively, in all the participants. The BD group did significantly worse in facial emotion recognition in comparison to FDR and HC groups (p<0.001). Emotion recognition of fear, anger, surprise, and happy were most affected. FDR did not vary significantly from HC in facial emotion recognition. Lower scores on facial emotion recognition were associated with lower QoL in the social domain(p=0.006) and poorer socio- occupational functioning scores (p=0.01), but it was not significant within the BD group. FERD is seen in remitted patients of bipolar disorder but not in the first -degree relatives. FERD affects social quality of life and functioning. Poorer social functioning in remitted patients of bipolar disorder might be multifactorial and cannot be attributed solely to FERD.

Examining facial emotion recognition as an intermediate phenotype for psychosis: Findings from the EUGEI study

BackgroundSocial cognition impairments, such as facial emotion recognition (FER), have been acknowledged since the earliest description of schizophrenia. Here, we tested FER as an intermediate phenotype for psychosis using two approaches that are indicators of genetic risk for schizophrenia: the proxy-genetic risk approach (family design) and the polygenic risk score for schizophrenia (PRS-SCZ). MethodsThe sample comprised 2039 individuals with schizophrenia, 2141 siblings, and 2049 healthy controls (HC). The Degraded Facial Affect Recognition Task (DFAR) was applied to measure the FER accuracy. Schizotypal traits in siblings and HC were assessed using the Structured Interview for Schizotypy-Revised (SIS-R). The PRS-SCZ was trained using the Psychiatric Genomics Consortium results. Regression models were applied to test the association of DFAR with psychosis risk, SIS-R, and PRS-SCZ. ResultsThe DFAR-total scores were lower in individuals with schizophrenia than in siblings (RR = 0.97 [95% CI 0.97, 0.97]), who scored lower than HC (RR = 0.99 [95% CI 0.99–1.00]). The DFAR-total scores were negatively associated with SIS-R total scores in siblings (B = −2.04 [95% CI −3.72, −0.36]) and HC (B = −2.93 [95% CI −5.50, −0.36]). Different patterns of association were observed for individual emotions. No significant associations were found between DFAR scores and PRS-SCZ. ConclusionsOur findings based on a proxy genetic risk approach suggest that FER deficits may represent an intermediate phenotype for schizophrenia. However, a significant association between FER and PRS-SCZ was not found. In the future, genetic mechanisms underlying FER phenotypes should be investigated trans-diagnostically.

Emotion Processing Deficit in Euthymic Bipolar Disorder: A Potential Endophenotype.

Background:Emotion processing deficits have been described in patients with bipolar disorder (BD) and are considered one of the core cognitive abnormalities in BD with endophenotype potential. However, the literature on specific impairments in emotion processing cognitive strategies (directive/cortical/higher versus intuitive/limbic/lower) in euthymic adult BD patients and healthy first-degree relatives/high-risk (HR) subjects in comparison with healthy controls (HCs) is sparse.Methods:We examined facial emotion recognition deficits (FERD) in BD (N = 30), HR (N = 21), and HC (N = 30) matched for age (years), years of education, and sex using computer-administered face emotions–Matching And Labeling Task (eMALT).Results:The three groups were significantly different based on labeling accuracy scores for fear and anger (FA) (P < 0.001) and sad and disgust (SD) (P < 0.001). On post-hoc analysis, HR subjects exhibited a significant deficit in the labeling accuracy of FA facial emotions (P < 0.001) compared to HC. The BD group was found to have significant differences in all FA (P = 0.004) and SD (P = 0.003) emotion matching as well as FA (P = 0.001) and SD (P < 0.001) emotion labeling accuracy scores.Conclusions:BD in remission exhibits FERD in general, whereas specific labeling deficits of fear and anger emotions, indicating impaired directive higher order aspect of emotion processing, were demonstrated in HR subjects. This appears to be a potential endophenotype. These deficits could underlie the pathogenesis in BD, with possible frontolimbic circuitry impairment. They may have potential implications in functional recovery and prognosis of BD.

Using machine learning to improve the discriminative power of the FERD screener in classifying patients with schizophrenia and healthy adults

Background Facial emotion recognition deficit (FERD) seems to be an obvious feature of patients with schizophrenia and has great potential for classifying patients and non-patients. The FERD screener was previously developed to classify patients from healthy adults. However, an obvious drawback of this screener is that the recommended cut-off scores could enhance either sensitivity or specificity (about 0.92) only, while the other one is at an only acceptable level (about 0.66). Machine learning (ML) algorithms are famous for their feature extraction and data classification abilities, which are promising for improving the discriminative power of screeners. This study aimed to improve the discriminative power of the FERD screener using an ML algorithm.Methods The data were extracted from a previous study. Artificial neural networks were generated to estimate the probability of being a patient with schizophrenia or a healthy adult based on the examinee's responses on the FERD screener (168 items). The performances of the ML-FERD screener were examined using a stratified five-fold cross-validation method.Results Across the five subsets of data, the ML-FERD screener showed extremely high areas under the receiver operating characteristic curve of 0.97–0.99. With the optimized cut-off scores, the average sensitivity and specificity of the ML-FERD screener were 0.90 (0.85–0.93) and 0.93 (0.86–1.00), respectively.Limitations The characteristics of patients were not representative, and the age was mismatched to control group.Conclusion The ML-FERD screener appears to have a better discriminative power to classify patients with schizophrenia and healthy adults than does the FERD screener.

The Child Emotion Facial Expression Set: A Database for Emotion Recognition in Children.

Background: This study developed a photo and video database of 4-to-6-year-olds expressing the seven induced and posed universal emotions and a neutral expression. Children participated in photo and video sessions designed to elicit the emotions, and the resulting images were further assessed by independent judges in two rounds.Methods: In the first round, two independent judges (1 and 2), experts in the Facial Action Coding System, firstly analysed 3,668 emotions facial expressions stimuli from 132 children. Both judges reached 100% agreement regarding 1,985 stimuli (124 children), which were then selected for a second round of analysis between judges 3 and 4.Results: The result was 1,985 stimuli (51% of the photographs) were produced from 124 participants (55% girls). A Kappa index of 0.70 and an accuracy of 73% between experts were observed. Lower accuracy was found for emotional expression by 4-year-olds than 6-year-olds. Happiness, disgust and contempt had the highest agreement. After a sub-analysis evaluation of all four judges, 100% agreement was reached for 1,381 stimuli which compound the ChildEFES database with 124 participants (59% girls) and 51% induced photographs. The number of stimuli of each emotion were: 87 for neutrality, 363 for happiness, 170 for disgust, 104 for surprise, 152 for fear, 144 for sadness, 157 for anger 157, and 183 for contempt.Conclusions: The findings show that this photo and video database can facilitate research on the mechanisms involved in early childhood recognition of facial emotions in children, contributing to the understanding of facial emotion recognition deficits which characterise several neurodevelopmental and psychiatric disorders.

Facial Emotions Are Accurately Encoded in the Neural Signal of Those With Autism Spectrum Disorder: A Deep Learning Approach

BackgroundIndividuals with autism spectrum disorder (ASD) exhibit frequent behavioral deficits in facial emotion recognition (FER). It remains unknown whether these deficits arise because facial emotion information is not encoded in their neural signal or because it is encodes but fails to translate to FER behavior (deployment). This distinction has functional implications, including constraining when differences in social information processing occur in ASD, and guiding interventions (i.e., developing prosthetic FER vs. reinforcing existing skills). MethodsWe utilized a discriminative and contemporary machine learning approach—deep convolutional neural networks—to classify facial emotions viewed by individuals with and without ASD (N = 88) from concurrently recorded electroencephalography signals. ResultsThe convolutional neural network classified facial emotions with high accuracy for both ASD and non-ASD groups, even though individuals with ASD performed more poorly on the concurrent FER task. In fact, convolutional neural network accuracy was greater in the ASD group and was not related to behavioral performance. This pattern of results replicated across three independent participant samples. Moreover, feature importance analyses suggested that a late temporal window of neural activity (1000–1500 ms) may be uniquely important in facial emotion classification for individuals with ASD. ConclusionsOur results reveal for the first time that facial emotion information is encoded in the neural signal of individuals with (and without) ASD. Thus, observed difficulties in behavioral FER associated with ASD likely arise from difficulties in decoding or deployment of facial emotion information within the neural signal. Interventions should focus on capitalizing on this intact encoding rather than promoting compensation or FER prostheses.

Facial emotion recognition and mood symptom course in young adults with childhood-onset bipolar disorder.

Facial emotion recognition deficits are common in bipolar disorder (BD) and associated with impairment. However, the relationship between facial emotion recognition and mood course is not well understood. This study examined facial emotion recognition and subsequent mood symptoms in young adults with childhood-onset BD versus typically developing controls (TDCs). The sample included 116 young adults (ages 18-30, 58% male, 78% White) with prospectively verified childhood-onset BD (n = 52) and TDCs (n = 64). At baseline, participants completed a facial emotion recognition task (Diagnostic Analysis of Non-Verbal Accuracy-2) and clinical measures. Then, participants with BD completed mood symptom assessments every 6months (M = 8.7 ± 5.2months) over two years. Analyses included independent-samples t tests and mixed-effects regression models. Participants with BD made significantly more recognition errors for child expressions than TDCs. There were no significant between-group differences for recognition errors for adult expressions, or errors for specific child or adult emotional expressions. Participants had moderate baseline mood symptoms. Significant time-by-facial emotion recognition interactions revealed more recognition errors for child emotional expressions predicted lower baseline mania and stable/consistent trajectory; fewer recognition errors for child expressions predicted higher baseline mania and decreasing trajectory. In addition, more recognition errors for adult sad expressions predicted stable/consistent depression trajectory and decreasing mania; fewer recognition errors for adult sad expressions predicted decreasing depression trajectory and stable/consistent mania. Effects remained when controlling for baseline demographics and clinical variables. Facial emotion recognition may be an important brain/behavior mechanism, prognostic indicator, and intervention target for childhood-onset BD, which endures into young adulthood and is associated with mood trajectory.