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 Human faces convey important messages, such as identity, age, sex, eye gaze, and emotional expression, that are relevant for social communication. Among the dynamic facial features, facial expressions play a crucial role in interpersonal interaction. Impairments in facial expression recognition have been demonstrated in neurologic pathologies such as frontotemporal dementia (1) and Parkinson’s disease (2) and in psychiatric disorders such as depression (3) and schizophrenia (4). Conversely, recognition of invariant facial features such as age and identity may not be impaired in schizophrenia (5). Poor emotion recognition in schizophrenia (6) may contribute to aberrant interpersonal interactions and poor social functioning (7,8) and may be a predictor of functional outcome in these patients (9). Consistently, performance in facial and vocal emotion recognition correlates with social dysfunction in schizophrenia (10). Moreover, performance in facial expression recognition relates to negative symptoms of schizophrenia, implying poor socialization (11). The cognitive model of face perception developed by Haxby and colleagues (12) emphasizes a distinction between the neural processes involved in the recognition of invariant and changeable facial features. The region of the lateral fusiform gyrus is particularly involved in the recognition of identity, whereas the region of the superior temporal sulcus and gyrus participates in the recognition of face-changeable aspects (13). This distinction is supported by several behavioural studies that show double dissociation between facial identity and facial expression recognition in patients with focal brain damage (14). Imaging studies also support the existence of distinct neural systems involved in the recognition of identity and expression, eye gaze, and lip-reading (13). Studies in primates have shown that some neurons respond selectively to identity in the inferior temporal gyrus, whereas others respond preferentially to emotional expression in the superior temporal sulcus (15). Scalp (16) and intracranial (17) event-related potential studies in humans also support the existence of distinct pathways. Considering Haxby’s model, a deficit in facial expression recognition may imply a dysfunction of the corticolimbic network involved in emotion processing. Numerous studies have demonstrated structural and histological abnormalities in several brain regions in schizophrenia, including those that are involved in facial expression processing, for example, the temporal and frontal cortices, the superior temporal gyrus, and the thalamus (18). Studies addressing facial expression recognition deficit in schizophrenia patients have almost always been based on prototypic facial expressions of emotions. It was recently suggested that increasing test sensitivity by including different emotion intensities may be more appropriate for studying emotional facial expression processing deficit in schizophrenia patients (19). Such highly sensitive methods have only been used once in patients with schizophrenia (4). However, as was discussed in a methodological review, the authors did not include a control task or a psychiatric control group (20). Studies including psychiatric control subjects are rare. Whether a comparable deficit in facial emotional expression recognition can be observed in another psychiatric disorder involving social and communication impairments (for example, major depression) is controversial (21). Whether this impairment is selective of facial emotional expression recognition in contrast to invariant facial feature recognition remains unclear and not directly investigated. In this study, we first addressed the question of the specificity of facial expression recognition deficit in schizophrenia compared with major depression—another psychiatric affection involving social behaviour impairments. Second, we compared it with sex recognition, an invariant facial feature. We engaged schizophrenia patients and depression patients in a facial emotional expression task and in a facial sex recognition task with an innovating and sensitive technique built with morphed faces depicting various degrees of expression and sex. We used various intensities of both expression and sex, obtained by morphing techniques, to improve the sensitivity and specificity of the tests (22). MethodSubjects The study sample comprised patients with schizophrenia (n = 29) or major depression (n = 20), diagnosed according to DSM-IV criteria and with no concurrent diagnosis on Axis I, and healthy control subjects (n = 20). We used the PANSS (23) to assess schizophrenia symptoms and the MADRS (24) to assess depressive symptoms. Control subjects (n = 20) were healthy volunteers recruited within the hospital staff. They were free from DSM-IV Axis I diagnosis and from a history of psychiatric illness. None of them had ever received psychotropic medication. In all groups, major medical illness, neurologic disorder, current substance abuse, severe head injury, and visual impairment were exclusion criteria. The study was conducted in accordance with the latest version of the Declaration of Helsinki (see www.wma.net/e/policy/b3.htm), and its design has been approved by the local ethical committee. We obtained informed consent from all participants. Table 1 summarizes demographic, clinical, and treatment characteristics of the population.
Stimuli Static colour photographic images of 3 basic facial emotional expressions (disgust, fear, and happiness) were morphed with neutral faces to create an expression continuum. We did not include sadness, anger, and surprise because these facial expressions have often been confounded with others (sadness with neutral, anger with disgust, and surprise with fear; 20). The morphed faces depicted disgust, fear, or happiness of different intensities for 2 men and 2 women. For each emotional category and for each individual face, a range of 9 intensity levels was obtained by computer graphical manipulation (25). The 10% through 90% emotional expression faces were interpolated with computer morphing procedures to shift the shape and pigmentation of the 0% emotion face (neutral) toward the 100% emotion photograph (disgust, fear, and happiness). Likewise, photographic images of the 2 sexes (male and female) were morphed with a face depicting “no sex” to create a sex continuum. The “no sex” face was obtained by averaging 20 male and 20 female faces. For each male and each female face, a range of 9 intensity levels of sex features was obtained by computer graphical manipulation. The 10% through 90% sex faces were interpolated with computer morphing procedures to shift the shape and pigmentation of the “no sex” face toward the 100% male or female prototype. All faces were successively flashed on a computer screen during 400 ms and followed by a black screen lasting 1600 ms. Presentation order was randomized within and across subjects. Stimulus examples are presented in Table 2 and Table 3.
Tasks Subjects were engaged in 2 successive facial feature recognition tasks. The order of task completion was randomized across subjects. Expression Recognition Task. Subjects viewed the 132 expression-morphed images introduced above. After each face presentation, subjects had to report which facial expression was depicted by choosing among disgust, fear, happiness, and neutral and pressing the corresponding key. Sex Recognition Task (Control Task). Subjects viewed the 132 sex-morphed images introduced above. After each face presentation, subjects had to report which sex was depicted by choosing between man and woman and pressing the corresponding key. Statistical Analyses Correct response rates were included in statistical analyses. For each emotion and sex morphing, trials were gathered into 3 ranges of intensity: Trials containing morphed faces with 10% through 30% of facial expression or sex were pooled in a mild intensity range. Trials containing morphed faces with 40% to 70% of facial expression or sex were pooled in a moderate intensity range. Trials containing morphed faces with 80% to 100% of facial expression or sex were pooled in a high intensity range. Since conditions for parametric statistics were not reached, we performed nonparametric analyses.The factors were group (patients with schizophrenia vs depression patients vs control subjects), task (emotion recognition vs sex recognition), emotion (disgust, fear, and happiness), sex (male vs female), and intensity (mild, moderate, and high). The first factor was a between-subject factor, and the other 4 were within-subject factors. Dependent variables were a percentage of correct responses; level of significance was retained at 0.05. A 3 (group) × 2 (task) Kruskal–Wallis 1-way variance analysis was performed to compare participants’ performances in the emotion recognition and sex recognition tasks. Then, the following Kruskal–Wallis 1-way variance analyses were conducted: a 3 (group) × 3 (emotion) followed by a 3 (group) × 3 (emotional intensity) and a 3 (group) × 2 (sex) analysis followed by a 3 (group) × 3 (sex intensity) analysis. Post hoc Mann–Whitney tests were performed to compare schizophrenia patients with control subjects, major depression patients with control subjects, and schizophrenia patients with depression patients, when variance analyses were significant. Uncorrected Spearman coefficients of correlations were calculated between performances and either clinical (illness duration, PANSS or MADRS scores, or treatment dosage) or demographic (age, education level, or sex) characteristics of each group. ResultsPerformances in the expression recognition task and in the sex recognition task are presented in Figures 1, 2, and 3.
Schizophrenia Patients Have a Selective Impairment in Facial Expression Recognition. The group × task Kruskal–Wallis 1-way analysis revealed a significant main effect in the expression recognition task (H2 = 10.072, P = 0.007) but not in the sex recognition task (H2 = 0.299, P = 0.8). Post hoc Mann–Whitney revealed that patients with schizophrenia achieved significantly lower scores than both control subjects (U = 147; z = 2.91; P = 0.003) and depression patients (U = 178.5; z = 2.269; P = 0.02) in the expression recognition task. Differences between depression patients and control subjects in the expression recognition task, as well as all other group differences in the sex recognition task, were not significant. Schizophrenia Patients Are Impaired in the Recognition of Specific Emotions. The group × emotion Kruskal–Wallis 1-way analysis revealed a significant main effect for disgust (H2 = 8.960, P = 0.01) and for fear (H2 = 16.536, P = 0.0003) but not for happiness. Post hoc Mann–Whitney revealed significant group differences. For disgust, schizophrenia patients achieved lower scores than healthy control subjects (U = 145.5, z = 2.74, P = 0.003). For fear, patients with schizophrenia achieved lower scores than both control subjects (U = 135.5, z = 3.14, P = 0.002) and depression patients (U = 111.00, z = 3.643, P = 0.0002). No difference was found between depression patients and control subjects in the recognition of disgust and fear. Likewise, group differences in the recognition of happiness were not significant. Facial Expression Recognition Is Impaired at Moderate and High Intensities in the Schizophrenia Group. To our knowledge, this is the first study confirming a selective impairment in facial expression recognition, compared with preserved sex recognition, in schizophrenia patients. Of particular interest is the inclusion of different intensities of facial features that increase test sensitivity. Considering this, patients with schizophrenia achieved lower scores than both other groups in the recognition of moderate and high-intensity facial expressions. Moreover, the difference between groups was more significant with high intensities than with moderate ones, although this last condition may be reasonably more difficult. With mild intensities, all groups were at chance level. This result suggests that schizophrenia patients do not benefit from increased intensity of emotional expression. Therefore, it is unlikely that task difficulty accounts solely for schizophrenia patients’ deficit in processing facial expressions. The use of morphed faces simulating increasing intensities of facial features may render the test more sensitive and probably more appropriate for subjects who may have intermediate performance between patients and control subjects, such as subjects at risk for schizophrenia (45–49). The use of morphed images depicting various intensities of facial features may be useful for future research. LimitationsSome limitations should be discussed. First, differences in age and in education level might explain significant group differences (20). However, statistical analyses did not reveal any influence of age or education on performance, and no significant correlation was found between performance in facial expression or facial sex recognition and clinical or demographic characteristics. Moreover, demographic characteristics (for example, age and education level) do not affect facial expression recognition (50). Second, all patients with schizophrenia, as well as most depression patients, were under medication. However, many reports have failed to find any influence of medication on facial expression recognition (51). ConclusionsPatients with schizophrenia exhibit a deficit in fear and disgust recognition, whereas sex recognition is unimpaired. This confirms a selective impairment in the recognition of changeable facial features that are particularly involved in social cognition. Schizophrenia patients’ deficit in facial expression recognition may rely on a dysfunction of the corticolimbic neural network subserving facial expression recognition, whereas posterior ventral occipitotemporal regions processing invariant facial features may function adequately. Top-down retrograde modulation coming from downstream prefrontal cortex, amygdala, and insula may also malfunction. The absence of deficit in major depression patients further reinforces the idea of a neural dysfunction rather than a pure behavioural disorder in schizophrenia. Funding and SupportWe sincerely thank the Conseil Scientifique de la Recherche from Centre Hospitalier Le Vinatier for their financial support. References1. Keane J, Calder AJ, Hodges JR, Young AW. Face and emotion processing in frontal variant frontotemporal dementia. 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Schizophr Res 1999;40:121–30. 48. Loughland CM, Williams LM, Harris AW. Visual scanpath dysfunction in first-degree relatives of schizophrenia probands: evidence for a vulnerability marker? Schizophr Res 2004;67(1):11–21. 49. Bolte S, Poustka F. The recognition of facial affect in autistic and schizophrenic subjects and their first-degree relatives. Psychol Med 2003;33:907–15. 50. Bryson G, Bell M, Lysaker P. Affect recognition in schizophrenia: a function of global impairment or a specific cognitive deficit. Psychiatry Res 1997;71:105–13. 51. Mueser KT, Penn DL, Blanchard JJ, Bellack AS. Affect recognition in schizophrenia: a synthesis of findings across three studies. Psychiatry 1997;60:301–8. Author(s)Manuscript received October 2004, revised, and accepted January 2005. 1. Centre Hospitalier Le Vinatier, 95 Bd Pinel, 69677 Bron cedex, France; Hôpital Neurologique, Lyon, France. 2. Institut national de la santé et de la recherche médicale (INSERM), Lyon, France; Hôpital Neurologique, Lyon, France. 3. School of Psychology, University of St Andrews, St Andrews, Scotland. Address for correspondence: Dr T d’Amato, EA 3092 - Centre Hospitalier Le Vinatier, Service du Pr Dalery, 95 Boulevard Pinel, 69 677, Bron Cedex, France. e-mail: thierry.damato@ch-le-vinatier.fr
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