Emotion Recognition In Patients Research Articles

Deficits of Facial Emotion Recognition in Elderly Individuals with Mild Cognitive Impairment.

The study of facial emotion recognition is under-explored in subjects with mild cognitive impairment (MCI). We investigated whether deficits in facial emotion recognition are present in patients with MCI. We also analyzed the relationship between facial emotion recognition and different domains of cognitive function. This study included 300 participants aged 60 years or older with cognitive decline. We evaluated 181 MCI and 119 non-MCI subjects using the Seoul Neuropsychological Screening Battery-Core (SNSB-C) and facial emotion recognition task using six facial expressions (anger, disgust, fear, happiness, sadness and surprise). A Generalized Linear Model (GLM) was used to assess the association between cognitive performance and accuracy of facial emotion recognition and to compare facial emotion recognition in the MCI group based on the impairment of five different domains of cognitive function. The model was adjusted for age, sex, years of education, and depressive symptoms. Patients with MCI had a lower score for accurately recognizing total facial emotion (0.48 vs. 0.53; ρ = 0.0003) and surprise (0.73 vs. 0.81; ρ = 0.0215) when compared to cognitively healthy subjects. We also discovered that frontal/executive function domain (Digit Symbol Coding [DSC, 0.38 vs. 0.49; p < 0.0001], Controlled Oral Word Association Test [COWAT, 0.42 vs. 0.49; p = 0.0001], Korean-Trail Making Test [K-TMT, 0.37 vs. 0.48; p = 0.0073], Korean-Color Word Stroop Test [K-CWST, 0.43 vs. 0.49; p = 0.0219]) and language domain (Korean-Boston Naming Test [S-K-BNT, 0.46 vs. 0.47; p = 0.003]) were statistically associated with the deficits of facial emotion recognition in patients with MCI. We observed a significant association between deficits in facial emotion recognition and cognitive impairment in elderly individuals.

Alexithymia and facial emotion recognition in patients with functional neurological disorder

ObjectivesPatients with functional neurological disorder (FND) are known to have difficulties recognizing and processing emotions. Problems recognizing internal emotional states (alexithymia) are common in FND, but little is known about recognizing emotions expressed by other people. This study investigates whether patients with FND have higher levels of alexithymia and reduced facial emotion recognition compared to healthy controls. MethodsPatients with FND (n = 31, mean age=42.7 [SD=14.8] years, 54.8% women) were compared to healthy controls (n = 33, mean age=45.1 [SD=16.2] years, 63.6% women). The Bermond-Vorst Alexithymia Questionnaire (BVAQ) was used for the assessment of alexithymia and the Ekman 60 Faces Test (EFT) for facial emotion recognition. ResultsPatients with FND had higher levels of alexithymia than healthy controls (BVAQ=71.8 [SD=19.8] versus 59.3 [SD=20.3], p = .02, Cohen’s d=0.62). Facial emotion recognition did not significantly differ between FND patients and controls (EFT total score FND: 46.1 [SD=5.9], Controls: 47.5 [SD=5.5], p = .34, Cohen’s d=0.24). Only recognition of surprise differed between patients and controls (FND: 8.4 [SD=1.8], Controls: 9.2 [SD=1.0), p = .03, Cohen’s d= 0.56). Higher levels of alexithymia were associated with poorer facial emotion recognition, but this relationship was not statistically significant (FND: β= −0.20, p = .28; Controls: β=-0.03; p = .87). ConclusionsThe current data confirm prior observations that patients with FND have higher alexithymia levels than controls without FND. Difficulties recognizing emotions among patients with FND primarily involves recognition of internal emotional states rather than recognition of facially expressed emotions by others. These findings require replication in a larger and more divers sample.

Recognition and Perception of Emotions in Juvenile Myoclonic Epilepsy.

Perception and recognition of emotions are fundamental prerequisites of human life. Patients with juvenile myoclonic epilepsy (JME) may have emotional and behavioral impairments which might influence socially desirable interactions. We aimed to investigate perception and recognition of emotions in patients with JME by means of neuropsychological tests and functional MRI (fMRI). Sixty-five patients with JME (median age 27 years, IQR 23-34) were prospectively recruited at the Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria. Patients were compared to 68 healthy controls (median age 24 years, IQR 21-31), matched for sex, age and education. All study participants underwent the Networks of Emotion Processing test battery (NEmo), an fMRI paradigm of "dynamic fearful faces", structured interview for psychiatric and personality disorders and comprehensive neuropsychological testing. JME patients versus healthy controls, demonstrated significant deficits in emotion recognition in facial and verbal tasks of all emotions, especially fear. fMRI revealed decreased amygdala activation in JME patients as compared to healthy controls. Patients were at a higher risk of experiencing psychiatric disorders as compared to healthy controls. Cognitive evaluation revealed impaired attentional and executive functioning, namely psychomotor speed, tonic alertness, divided attention, mental flexibility, and inhibition of automated reactions. Duration of epilepsy correlated negatively with parallel prosodic and facial emotion recognition in NEmo. Deficits in emotion recognition were not associated with psychiatric comorbidities, impaired attention and executive functions, types of seizures and treatment. This prospective study demonstrated that as compared to healthy subjects, patients with JME had significant deficits in recognition and perception of emotions as shown by neuropsychological tests and fMRI. The results of this study may have importance for psychological/psychotherapeutical interventions in the management of patients with JME.

P01.10.B EMOTION RECOGNITION IN PATIENTS WITH LOW-GRADE GLIOMA: THE RELATIONSHIP WITH TUMOR LOCATION AND TUMOR VOLUME

Abstract BACKGROUND Patients with low-grade gliomas (LGG), generally function well at the time of diagnosis and have a favourable prognosis. However, LGG can have impact on cognitive functioning of patients. To date, little is known about social cognition (SC) in patients with LGG. Social cognitive functions allow the processing of complex social information, with as important element the ability to recognize other people’s emotional expressions. Inaccurate recognition or misinterpretation of emotional facial expressions can lead to impairments in social functioning, which can have adverse effects on quality of life. Therefore, the aim of the present study was to investigate emotion recognition in patients with LGG and the relationship with tumor location and tumor volume. MATERIAL AND METHODS 125 patients with IDH mutated astrocytoma and oligodendroglioma grade 2 and 3, were matched with 169 healthy controls (HC). Tumor location and volume were evaluated pre-radiotherapy based on MRI scans. As a parameter for LGG volume the clinical radiotherapy target volume was used. SC was measured with a test for emotion recognition, i.e. the Facial Expressions of Emotion Stimuli and Tests (FEEST), after surgery. Descriptive statistics and between-group comparisons were performed. RESULTS On a group level, patients with LGG performed significantly lower on the FEEST total score compared to HC. Also, compared to norm data used in clinical practice, 32.8% of the patients showed an impaired performance. Larger LGG volume was significantly associated (p < 0.001) with poorer performance on emotion recognition. However, no direct association between LGG location (frontal, temporal, parietal) and emotion recognition was found. CONCLUSION In patients with LGG, impaired emotion recognition is often present before start of radiotherapy, and is related to larger LGG volume but not to location. Because of the relatively favourable prognosis of patients with LGG, maintaining quality of life is of high importance. Therefore, a thorough neuropsychological examination, including measurements for SC, is necessary to inform patients with LGG about possible changes in SC, and offer appropriate psychoeducation and care.

The impact of deep brain stimulation of the subthalamic nucleus on facial emotion recognition in patients with Parkinson's disease.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is successful in patients with advanced Parkinson's disease (PD) but may worsen cognitive outcome, including facial emotion recognition (FER). Data-analyses on 59 consecutive PD patients with complete pre- and postoperative assessments, using a sensitive FER test, showed no changes in FER 1 year after STN-DBS surgery, both after group and individual analyses. These findings do however not exclude the impact of FER in and on itself on the outcome after STN-DBS.

Facial Emotion Recognition in Patients with Juvenile Myoclonic Epilepsy.

Previous studies have found facial emotion recognition (FER) impairments in individuals with epilepsy. While such deficits have been extensively explored in individuals with focal temporal lobe epilepsy, studies on individuals with generalized epilepsies are rare. However, studying FER specifically in individuals with juvenile myoclonic epilepsy (JME) is particularly interesting since they frequently suffer from social and neuropsychological difficulties in addition to epilepsy-specific symptoms. Furthermore, recent brain imaging studies have shown subtle microstructural alterations in individuals with JME. FER is considered a fundamental social skill that relies on a distributed neural network, which could be disturbed by network dysfunction in individuals with JME. This cross-sectional study aimed to examine FER and social adjustment in individuals with JME. It included 27 patients with JME and 27 healthy controls. All subjects underwent an Ekman-60 Faces Task to examine FER and neuropsychological tests to assess social adjustment as well as executive functions, intelligence, depression, and personality traits. Individuals with JME performed worse in global FER and fear and surprise recognition than healthy controls. However, probably due to the small sample size, no significant difference was found between the two groups. A potential FER impairment needs to be confirmed in further studies with larger sample size. If so, patients with JME could benefit from addressing possible deficits in FER and social difficulties when treated. By developing therapeutic strategies to improve FER, patients could be specifically supported with the aim of improving social outcomes and quality of life.

Facial emotion recognition in patients with depression compared to healthy controls when using human avatars

The negative, mood-congruent cognitive bias described in depression, as well as excessive rumination, have been found to interfere with emotional processing. This study focuses on the assessment of facial recognition of emotions in patients with depression through a new set of dynamic virtual faces (DVFs). The sample consisted of 54 stable patients compared to 54 healthy controls. The experiment consisted in an emotion recognition task using non-immersive virtual reality (VR) with DVFs of six basic emotions and neutral expression. Patients with depression showed a worst performance in facial affect recognition compared to healthy controls. Age of onset was negatively correlated with emotion recognition and no correlation was observed for duration of illness or number of lifetime hospitalizations. There was no correlation for the depression group between emotion recognition and degree of psychopathology, excessive rumination, degree of functioning, or quality of life. Hence, it is important to improve and validate VR tools for emotion recognition to achieve greater methodological homogeneity of studies and to be able to establish more conclusive results.

IoT-Enabled WBAN and Machine Learning for Speech Emotion Recognition in Patients

Internet of things (IoT)-enabled wireless body area network (WBAN) is an emerging technology that combines medical devices, wireless devices, and non-medical devices for healthcare management applications. Speech emotion recognition (SER) is an active research field in the healthcare domain and machine learning. It is a technique that can be used to automatically identify speakers' emotions from their speech. However, the SER system, especially in the healthcare domain, is confronted with a few challenges. For example, low prediction accuracy, high computational complexity, delay in real-time prediction, and how to identify appropriate features from speech. Motivated by these research gaps, we proposed an emotion-aware IoT-enabled WBAN system within the healthcare framework where data processing and long-range data transmissions are performed by an edge AI system for real-time prediction of patients' speech emotions as well as to capture the changes in emotions before and after treatment. Additionally, we investigated the effectiveness of different machine learning and deep learning algorithms in terms of performance classification, feature extraction methods, and normalization methods. We developed a hybrid deep learning model, i.e., convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), and a regularized CNN model. We combined the models with different optimization strategies and regularization techniques to improve the prediction accuracy, reduce generalization error, and reduce the computational complexity of the neural networks in terms of their computational time, power, and space. Different experiments were performed to check the efficiency and effectiveness of the proposed machine learning and deep learning algorithms. The proposed models are compared with a related existing model for evaluation and validation using standard performance metrics such as prediction accuracy, precision, recall, F1 score, confusion matrix, and the differences between the actual and predicted values. The experimental results proved that one of the proposed models outperformed the existing model with an accuracy of about 98%.

Dysfunctional cerebello-cerebral network associated with vocal emotion recognition impairments.

Vocal emotion recognition, a key determinant to analyzing a speaker's emotional state, is known to be impaired following cerebellar dysfunctions. Nevertheless, its possible functional integration in the large-scale brain network subtending emotional prosody recognition has yet to be explored. We administered an emotional prosody recognition task to patients with right versus left-hemispheric cerebellar lesions and a group of matched controls. We explored the lesional correlates of vocal emotion recognition in patients through a network-based analysis by combining a neuropsychological approach for lesion mapping with normative brain connectome data. Results revealed impaired recognition among patients for neutral or negative prosody, with poorer sadness recognition performances by patients with right cerebellar lesion. Network-based lesion-symptom mapping revealed that sadness recognition performances were linked to a network connecting the cerebellum with left frontal, temporal, and parietal cortices. Moreover, when focusing solely on a subgroup of patients with right cerebellar damage, sadness recognition performances were associated with a more restricted network connecting the cerebellum to the left parietal lobe. As the left hemisphere is known to be crucial for the processing of short segmental information, these results suggest that a corticocerebellar network operates on a fine temporal scale during vocal emotion decoding.

Alexithymia and facial emotion recognition in patients with functional neurological disorder

Alexithymia and facial emotion recognition in patients with functional neurological disorder

Blunted superior temporal gyrus activity to negative emotional expression after mindfulness-based cognitive therapy for late-life depression.

Facial emotion recognition plays an important role in social functioning. Patients with late-life depression (LLD) often have abnormal facial emotion recognition. Mindfulness-based cognitive therapy (MBCT) is beneficial in treating depression. This study examined whether MBCT can act as an effective augmentation of antidepressants and improve facial emotion recognition in patients with LLD and its underlying neural mechanism. Patients with LLD were randomized into two groups (n = 30 per group). The MBCT group received an eight-week MBCT in conjunction with stable medication treatment. The other group was treated as usual (TAU group) with stable medication treatment. The positive affect (PA) scale, negative affect (NA) scale, and facial emotion recognition task with an fMRI scan were performed before and after the trial. After eight weeks of treatment, the repeated ANOVA showed that the PA score in the MBCT group significantly increased [F (1,54) = 13.31, p = 0.001], but did not change significantly [F (1,54) = 0.58, p = 0.449] in the TAU group. The NA scores decreased significantly in both the MBCT group [F (1,54) = 19.01, p < 0.001] and the TAU group [F (1,54) = 16.16, p < 0.001]. Patients showed an increase in recognition accuracy and speed of angry and sad faces after 8 weeks of MBCT. No improvement was detected in the TAU group after treatment. A significant interaction effect was found in the change of activation of the left superior temporal gyrus (L-STG) to negative emotional expression between time and groups. Furthermore, a decrease in activation of L-STG to negative emotional expression was positively correlated with the increase in PA score. The MBCT is beneficial for improving affect status and facial emotion recognition in patients with LLD, and the L-STG is involved in this process.

Emotion Recognition in Patients with Low-Grade Glioma before and after Surgery.

Research on patients with low-grade gliomas (LGGs) showed neurocognitive impairments in various domains. However, social cognition has barely been investigated. Facial emotion recognition is a vital aspect of social cognition, but whether emotion recognition is affected in LGG patients is unclear. Therefore, we aimed to investigate the effect of LGG and resection by examining emotion recognition pre- and postoperatively. Additionally, the relationships among emotion recognition and general cognition and tumor location were investigated. Thirty patients with LGG who underwent resective surgery were included and matched with 63 healthy control participants (HCs). Emotion recognition was measured with the Facial Expressions of Emotion–Stimuli and Tests (FEEST) and general cognition with neuropsychological tests. Correlations and within-group and between-group comparisons were calculated. Before surgery, patients performed significantly worse than the HCs on FEEST-Total and FEEST-Anger. Paired comparisons showed no significant differences between FEEST scores before and post-surgery. No significant correlations with general cognition and tumor location were found. To conclude, the results of this study indicate that the tumor itself contributes significantly to social cognitive dysfunction and that surgery causes no additional deficit. Impairments were not related to general cognitive deficits or tumor location. Consequently, incorporating tests for emotion recognition into the neuropsychological assessment of patients with LGG is important.

Facial Emotion Recognition in Patients with Post-Paralytic Facial Synkinesis-A Present Competence.

Facial palsy is a movement disorder with impacts on verbal and nonverbal communication. The aim of this study is to investigate the effects of post-paralytic facial synkinesis on facial emotion recognition. In a prospective cross-sectional study, we compared facial emotion recognition between n = 30 patients with post-paralytic facial synkinesis (mean disease time: 1581 ± 1237 days) and n = 30 healthy controls matched in sex, age, and education level. Facial emotion recognition was measured by the Myfacetraining Program. As an intra-individual control condition, auditory emotion recognition was assessed via Montreal Affective Voices. Moreover, self-assessed emotion recognition was studied with questionnaires. In facial as well as auditory emotion recognition, on average, there was no significant difference between patients and healthy controls. The outcomes of the measurements as well as the self-reports were comparable between patients and healthy controls. In contrast to previous studies in patients with peripheral and central facial palsy, these results indicate unimpaired ability for facial emotion recognition. Only in single patients with pronounced facial asymmetry and severe facial synkinesis was an impaired facial and auditory emotion recognition detected. Further studies should compare emotion recognition in patients with pronounced facial asymmetry in acute and chronic peripheral paralysis and central and peripheral facial palsy.

Emotional Recognition in Patients With Mesial Temporal Epilepsy Associated With Enlarged Amygdala.

Background:Amygdalae play a central role in emotional processing by interconnecting frontal cortex and other brain structures. Unilateral amygdala enlargement (AE) is associated with mesial temporal lobe epilepsy (mTLE). In a relatively large sample of patients with mTLE and AE, we aimed to evaluate functional integration of AE in emotion processing and to determine possible associations between fMRI activation patterns in amygdala and deficits in emotion recognition as assessed by neuropsychological testing.Methods:Twenty-two patients with drug resistant unilateral mTLE due to ipsilateral AE were prospectively recruited in a large epilepsy unit and compared with 17 healthy control subjects in terms of amygdala volume, fMRI activation patterns and performance in emotion recognition as assessed by comprehensive affect testing system (CATS) and Ekman faces. All patients underwent structural and functional 1.5 Tesla MRI, electro-clinical assessment and neuropsychological testing.Results:We observed BOLD signal ipsilateral to AE (n = 7; group PAT1); contralateral to AE (n = 6; group PAT2) and no activation (n = 9; group PAT3). In the region of interest (ROI) analysis, beta estimates for fearful face > landscape contrast in the left amygdala region did not differ significantly in patients with left TLE vs. patients with right TLE [T(16) = −1.481; p = 0.158]. However, beta estimates for fearful face > landscape contrast in the right amygdala region were significantly reduced in patients with right TLE vs. patients with left TLE [T(16) = −2,922; p = 0.010]. Patients showed significantly lower total scores in CATS and Ekman faces compared to healthy controls.Conclusion:In our cohort, patients with unilateral mesial TLE and ipsilateral AE, an amygdala could display either functional integration in emotion recognition or dysfunction as demonstrated by fMRI. Perception and recognition of emotions were impaired more in right-sided mTLE as compared to left-sided mTLE. Neuropsychological tests showed deficits in emotion recognition in patients as compared to healthy controls.

Error patterns of facial emotion recognition in patients with schizophrenia

Error patterns of facial emotion recognition (FER) indicate how individuals misinterpret others’ facial expressions, which helps clinicians to manage related deficits. However, previous investigations are limited and may have been biased due to methodological issues (e.g., no consideration of response bias). This study aimed to propose a detectability index (d’) for adjusting response bias and examine the error patterns of FER in patients with schizophrenia.Responses to 168 photos showing seven basic emotions, obtained from 351 patients with schizophrenia and 101 healthy adults, were extracted from a previous study. The differences in the d’s between the two groups (Δd’) were calculated to examine the error patterns of FER among the seven emotions.The findings were generally overlapped with those identified by the traditional confusion matrix. Four error patterns were found. First, the patients were insensitive to some negative emotions (i.e., sadness [Δd’ = 0.83] and fear [Δd’ = 0.72]). Second, they misrecognized happy faces as showing negative emotions (e.g., disgust [Δd’ = 0.43] and sadness [Δd’ = 0.37]). Third, they misinterpreted surprised faces as all the other emotions (Δd’ = 0.41–0.87), except neutral. Fourth, they confused some negative emotions (e.g., misrecognizing fear as anger [Δd’ = 0.87]).Our findings suggest that patients with schizophrenia show four error patterns of FER compared to healthy adults. Accordingly, interventions could be selected to improve their sensitivity to faces with negative emotions, differentiation of faces among positive and negative emotions, understanding of surprised faces, and discrimination of faces with negative emotions.

The effect of facial expression intensity on emotion recognition and psychosocial performance in patients with frontal or temporal lobe epilepsy

PurposeNo studies have examined the relationship between the intensity of facial emotion expression and theory of mind (ToM) ability in people with epilepsy. This study aimed to explore facial emotion recognition in a group of patients with frontal (FLE) or temporal lobe epilepsy (TLE) and its relationship with the intensities of perceived facial emotion expressions, ToM, and social functioning. MethodsTwenty-six patients with FLE or TLE and 30 matched controls were included in the study. All participants completed the facial emotion recognition test, Faux Pas Recognition (FPR) test measuring advanced ToM, Symptom Checklist-90-Revised, Social and Occupational Functioning Scale for Epilepsy (SOFSE), and background neuropsychological tests. ResultsThe patient group was significantly worse than the control group in recognizing facial expressions of negative emotions, particularly for medium-intensity facial expression of fear. There was no significant difference between the groups in recognizing high-intensity fear facial expressions. The scores of FPR (overall and affective ToMs) in the patient group were significantly lower than those in the control group. Additionally, the facial emotion recognition was significantly associated with the total score of FPR, and the FPR total score remarkably correlated with the Communication subscale score of the SOFSE. ConclusionsPatients with FLE or TLE had impaired ability to recognize medium-intensity facial expressions of fear. Moreover, patients’ ToM deficit significantly correlated not only with their emotion recognition problem but also with their social-communicative competence. Nevertheless, we also found that increasing the intensity of expression can improve the accuracy of emotion recognition in patients with epilepsy. These findings may provide considerations for further longitudinal studies and interventions on the social difficulties of people with epilepsy.

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.

Impaired Visual Emotion Recognition After Minor Ischemic Stroke

ObjectiveTo assess the prevalence of impaired visual emotion recognition in patients who have experienced a minor ischemic stroke in the subacute phase and to determine associated factors of impaired visual emotion recognition. DesignA prospective observational study. SettingStroke unit of a teaching hospital. ParticipantsPatients with minor ischemic stroke (N=112). InterventionsNot applicable. Main Outcome MeasuresPatients with minor stroke underwent a neuropsychological assessment in the subacute phase for visual emotion recognition by the Ekman 60 Faces Test and for general cognition. Univariable linear regression analyses were performed to identify associated factors of emotion recognition impairment. ResultsIn 112 minor stroke patients, we found a prevalence of 25% of impaired visual emotion recognition. This was significantly correlated with impaired general cognition. Nevertheless, 10.9% of patients with normal general cognition still had impaired emotion recognition. Mood was negatively associated. Stroke localization, hemisphere side, and sex were not associated. ConclusionImpaired visual emotion recognition is found in about one-quarter of patients with minor ischemic stroke.

Auditory emotion recognition deficits in schizophrenia: A systematic review and meta-analysis.

Auditory emotion recognition (AER) deficits refer to the abnormal identification and interpretation of tonal or prosodic features that transmit emotional information in sounds or speech. Evidence suggests that AER deficits are related to the pathology of schizophrenia. However, the effect size of the deficit in specific emotional category recognition in schizophrenia and its association with psychotic symptoms have never been evaluated through a meta-analysis. A systematic search for literature published in English or Chinese until November 30, 2020 was conducted in PubMed, Embase, Web of Science, PsychINFO, and China National Knowledge Infrastructure (CNKI), WanFang and Weip Databases. AER differences between patients and healthy controls (HCs) were assessed by the standardized mean differences (SMDs). Subgroup analyses were conducted for the type of emotional stimuli and the diagnosis of schizophrenia or schizoaffective disorders (Sch/SchA). Meta-regression analyses were performed to assess the influence of patients' age, sex, illness duration, antipsychotic dose, positive and negative symptoms on the study SMDs. Eighteen studies containing 615 psychosis (Sch/SchA) and 488 HCs were included in the meta-analysis. Patients exhibited moderate deficits in recognizing the neutral, happy, sad, angry, fear, disgust, and surprising emotion. Neither the semantic information in the auditory stimuli nor the diagnosis subtype affected AER deficits in schizophrenia. Sadness, anger, and disgust AER deficits were each positively associated with negative symptoms in schizophrenia. Patients with schizophrenia have moderate AER deficits, which were associated with negative symptoms. Rehabilitation focusing on improving AER abilities may help improve negative symptoms and the long-term prognosis of schizophrenia.

The correlation of facial emotion recognition in patients with drug-naïve depression and suicide ideation

BackgroundThe ability of facial emotion recognition is often impaired in Major depressive disorder (MDD). The impairment of recognizing facial emotions may contribute to the disruption of interpersonal interaction. Perceived social isolation and social rejection are risk factors for suicide. This study aimed to investigate the ability of facial emotion recognition in drug-naïve MDD patients with first-episode with suicidal ideation. Methods98 drug-naïve outpatients with the first episode of depression were recruited, including 53 patients with suicidal ideation (SI) and 45 patients without suicidal ideation (NSI). The Beck Scale for Suicide Ideation—Chinese Version was adopted to evaluate the suicidal ideation and suicidal risk in the latest week. Depressive symptoms were assessed with the Hamilton Depression Rating Scale-17 (HDRS-17). Facial Emotion Recognition Test and the repeatable battery for the assessment of neuropsychological status (RBANS) were administered to assess the ability of emotion recognition and cognitive function. ResultsOur finding indicated that recognizing fear emotions was more accurate in the SI than the NSI group (OR = 1.142; 95% CI = 1.020, 1.280; p = 0.022). Patients with high suicidal risk may have more difficulties recognizing the neutral facial expressions (B=-0.310, 95% CI = -5.031, -0.845, p = 0.007). LimitationsLimitations include a small sample size and use of cross-sectional data. ConclusionsOur finding suggests that the variation of facial emotion recognition in drug-naïve MDD patients with first-episode with suicidal ideation and targeting this signal may help identify suicidal ideation to decrease the risk of suicide behavior in MDD.