Disengagement of attention from facial emotion in unipolar depression

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1 Blackwell Science, LtdOxford, UKPCNPsychiatry and Clinical Neurosciences Blackwell Science Pty LtdDecember Original ArticleDisengagement of attention in depressions. P. Karparova et al. Psychiatry and Clinical Neurosciences (2005), 59, Regular Article Disengagement of attention from facial emotion in unipolar depression STANISLAVA PETKOVA KARPAROVA, ANETTE KERSTING, md AND THOMAS SUSLOW, phd Department of Psychiatry, University of Münster, Münster, Germany Abstract Abnormal processing of facial expressions is assumed to be an important factor mediating the course of depression. The aim of the present study was to investigate the ability to disengage attention from facial emotion in depressed patients in the course of an inpatient treatment program. It was hypothesized that in depression disengagement of visual attention from negative facial expression is delayed, while disengagement from positive facial expression is facilitated. A face-in-thecrowd task using schematic stimuli and crowds of neutral and emotion faces as distractor stimuli was administered to depressed patients and normal controls matched for age, sex, and education. Patients with major depression (n = 15) and normal controls (n = 15) were tested twice, about 6 weeks apart. From test 1 to test 2, patients depressivity decreased significantly. Depressives showed higher response latencies and error rates than control subjects. However, depressed patients exhibited the same scanning pattern for facial emotion as healthy individuals across both test sessions. Participants detected a negative face more rapidly in a crowd of faces than a positive face. When displays consisted of repetitions of the same face, subjects were generally slower (and less accurate) when faces were negative relative to positive or neutral. The present data suggest that the ability to disengage attention from facial emotion in visual search is not impaired in depression. Key words attention disengagement, depression, face-in-the-crowd, facial emotion. INTRODUCTION Facial emotions are archetypal social cues that are easily recognizable and that call forth interpersonal behavior. 1 Recognition of facial expressions of basic emotions has been found to be biased or impaired among depressed individuals. 2 An abnormal processing of emotional facial expressions is thought to be relevant for the development of interpersonal difficulties and the persistence of illness in depressives. 3 It has frequently been suggested that depression is characterized by a mood-congruent negative bias which operates on all aspects of cognitive processing. 4 However, according to several authors in case of multistimulus representations heightened depression is Correspondence address: Thomas Suslow, PhD, Department of Psychiatry, University of Münster, Albert-Schweitzer-Str. 11, Münster, Germany. Suslow@uni-muenster.de Received 8 March 2005; accepted 19 June associated in particular with the loss of an attentional bias favoring positive information. 5,6 Data from a recent study based on event-related brain potentials show that depressives allocate equal amounts of resources when recognizing positive and negative facial affect, while healthy subjects allocate more resources to positive faces. 7 The processing of facial expressions is assumed to be highly efficient. 8 However, there exist substantial differences in the spatial processing of negative and positive facial expressions. Search functions for the detection of an angry or sad face are flatter than for the detection of a happy face Detection latencies for angry faces but not for happy faces were found to be largely independent of the number of faces: angry faces appear to pop-out from a crowd suggesting an automatic search for angry faces for normal subjects. The attentional system appears not unitary but can be divided into at least three distinct subsystems: engagement, shifting and disengagement of visual attention. 12 The face-in-the-crowd search paradigm

2 724 S. P. Karparova et al. seems to be most relevant for the engagement and the disengagement components of visual attention because the facial displays always appear within a centrally located spatial region. 9 Even though the detection of negative facial expression is faster and more efficient than the detection of positive facial expression, negative facial expression appears to hold visual attention to a greater extent than positive facial expression. 9,11,13 In addition, the efficiency for searches through neutral crowds is higher than the efficiency for searches through crowds of faces with an emotional expression. 9 These findings can be interpreted as reflecting enhanced dwell time of attention for emotional and especially threatening information. For adaptive reasons priority should be given to stimuli signaling harmful or rewarding consequences. If a threatening face is present then engagement of attention on that facial expression should be rapid, while attentional disengagement should be slow. These processes favor a fast detection and a more detailed analysis and a deeper encoding of biologically relevant signals. Since research on detection of emotional facial expression has demonstrated that the pop out of faces can be driven by low level features such as shadows or blobs of contrast, 14 schematic line drawings seem to be more appropriate than photographs as stimulus material in studies on spatial face processing. 15 Research on depression has largely neglected hitherto the spatial processing of emotional facial expression but it could be of considerable importance, because any impairments in detection could bias subsequent processing. Suslow et al. first applied a face-inthe-crowd task to examine the relationship between depression and spatial detection of facial expression of positive and negative emotions (in crowds of neutral faces). 16 Clinically stabilized depressed inpatients showed no performance differences in the detection of negative faces and no differences in decision latency for the control condition (all neutral faces) compared to normal subjects. However, they were significantly slower in responding to positive faces than normal subjects. Severity of depression was found to be associated with a reduced spatial attention (or attention engagement) to positive facial expression. The results of a subsequent longitudinal study in which emotion faces had to be detected in crowds of neutral faces suggest a persistence of spatial processing (or attention engagement) deficits for positive facial expression especially in depressives with a comorbid anxiety disorder during remission. 17 It was concluded that a slowed processing of positive faces in combination with an efficient detection of negative faces might represent a cognitive vulnerability factor in remitted depressives to relapse. The aim of the present experiment was to investigate the ability to disengage attention from facial emotion in depressed patients in the course of an inpatient treatment program. A face-in-the-crowd task using schematic stimuli and crowds of neutral and emotion faces as distractor stimuli was administered to depressed patients and normal controls matched for age, sex, and education. It was hypothesized that depressed patients should be slower (and/or less accurate, i.e. more distracted) than normal subjects in scanning crowds of negative faces and faster (and/or more accurate, i.e. less distracted) in scanning crowds of positive faces compared to neutral crowds. In other words, it was assumed that in depression disengagement of visual attention from negative facial expression should be delayed, while attentional disengagement from positive facial expression should be facilitated. Finally, based on our previous findings it was expected that spatial face processing abnormalities of depressed patients persist during remission. METHODS Participants Fifteen patients (11 women) fulfilling the criteria for a DSM-IV diagnosis of major depression as assessed by the Structured Clinical Interview for DSM-IV (SCID-I) 18 participated in the study. Patients were aged between 21 and 51 years of age (mean 36.5; SD 10.1). Ten of the depressed patients were suffering also from an anxiety disorder (panic disorder, agoraphobia, social phobia, specific phobia, or generalized anxiety disorder). In the case of two patients the episode of major depression was superimposed on chronic depression (dysthymia). Subjects with a neurological disease, substance dependence, organic impairments, subnormal intelligence, or electroconvulsive therapy were excluded. Most patients were being treated with newer antidepressant medication (selective serotonin reuptake inhibitors, e.g. citalopram, or non-ssris, e.g. mirtazapin). Two patients were unmedicated at test session 1, and all patients were medicated at test session 2. Patients were tested near intake and on average after approximately 6 weeks of psychotherapeutic inpatient treatment (mean 6.5; SD 1.7). The median lifetime duration of illness was 11.0 months (range 1 168) and the median lifetime duration of psychiatric hospitalization was 4.0 months (range 0 48). The median duration of the index episode was 24 weeks (range 4 576). The Montgomery-Asberg Depression Rating Scale (MADRS) 19 was used to assess severity of depression in the patient sample. The MADRS scores at intake (mean 22.0, SD 13.6) and at test session 2

3 Disengagement of attention in depression 725 (mean 8.5, SD 4.8) differed significantly (t (14) = 15.48, P < 0.001). All participating subjects had normal or corrected-to-normal vision. The study was approved by the institutional ethics committee. Informed consent was obtained from all subjects prior to the commencement of the study. Fifteen never-depressed volunteers (11 women) participated in this study as normal controls. The mean age of control subjects was 36.7 years (SD 10.2). In addition to the general inclusion criteria they met the criterion of no previous psychiatric hospitalizations. For controls the interval between the testing sessions was also 6 weeks (mean 6.1, SD 1.7). Control subjects did not differ from patients regarding education (mean 14.8 years (SD 2.0) vs. mean 14.3 years (SD = 3.0); t (28) = 0.5, P = 0.62). Face-in-the-crowd task Stimuli Seven types of display (black-and-white line drawings) were constructed (see Experiment 2 of Fox et al. 9 ). The three same displays consisted of four faces all displaying the same expression (all neutral, all negative, all positive). The four different displays consisted of three faces expressing the same emotion and one face expressing a discrepant emotion: one negative, three neutral; one negative, three positive; one positive, three neutral; and one positive, three negative. Schematic faces were used as stimuli and were presented black on a white background (Fig. 1 for examples). Each of the same displays was presented 32 times giving a total of 96 same displays. There were also 96 different displays with each of the four different conditions being presented 24 times. Negative, positive, and neutral faces differed only with regard to the mouth-line. Horizontal mouths contribute little to meaning. They tend not to be seen as happy or angrysad. 20 Negative faces had an identical mouth-line rotated 180 degrees from the positive faces. Face locations were the eight cardinal compass points of an imaginary circle. Each face had a diameter of 4 cm. Procedure Displays of schematic faces were presented to subjects for high-speed responses on whether they had the same expression or whether one had an expression differing from the other or others. Each trial had the same routine: a dot appeared for 500 msec and was immediately followed by a display for 800 msec. The intertrial interval was 2.5 s. Displays were presented in four blocks of 48. In each block there were equal numbers of displays for each of the seven presentation conditions. Within each block displays were randomly ordered (for each participant). Participants had 21 practice trials. Subjects took a break after each block. The experimenter remained in the room with the participant throughout the task. Procedure Clinical subjects participated in an interview in which the SCID-I was administered. At both testing sessions self-descriptive instruments (Beck Depression Inventory [BDI], 21 Automatic Thoughts Questionnaire [ATQ], 22 and State-Trait-Anxiety Inventory [STAI] 23 ) were given to assess state affectivity. The interview and the testing session took place on separate days. Testing sessions were always conducted in a quiet room free from visual and auditory distractions. The computer monitor was placed directly in front of the participant with the participant s eyes about 90 cm from the screen. A Pentium II microcomputer with a super- VGA color monitor (Belinea, 17 ) with a refresh rate of 60 Hz was used for stimulus presentation. The detection experiments were carried out with the help of the software package Experimental RunTime System. 24 Non-clinical subjects were only screened and then took part in a single testing session in which they were given the experimental task and the questionnaires. A B Figure 1. Examples of schematic face displays. (A) All negative faces, (B) positive face among neutral faces.

4 726 S. P. Karparova et al. RESULTS To examine the time course of affective characteristics in depressed patients compared to healthy subjects 2 2 anova with group as a between-groups factor (depressed patients vs control subjects) and time as a within-group factor (test 1 vs test 2) were calculated for each affect scale separately. For the BDI, significant main effects of group (F 1,28 = 38.0, P < 0.001) and time (F 1,28 = 18.3, P < 0.001) were found. In addition, the interaction of group and time was significant (F 1,28 = 7.2, P < 0.05). Depressivity was more pronounced in the patient group than in the control group but declined from test 1 to test 2 (see Table 1). For the ATQ, significant main effects of group (F 1,28 = 44.1, P < 0.001) and time (F 1,28 = 10.3, P < 0.01) were observed. Frequency of negative thoughts was higher in the depressed group than in the control group and decreased from test 1 to test 2. In the case of the STAI State, there was only a significant main effect of group (F 1,28 = 29.9, P < 0.001). Depressives were more state anxious than controls at both test sessions and state anxiety did not change from test 1 to test 2. Depressives with a comorbid anxiety disorder did not differ from non-comorbid depressives on the BDI, ATQ, or STAI at both test sessions (t (13) < 1.3, P > 0.24). Reaction latency and number of errors committed were the dependent variables in the face-in-the-crowd task. The error rate in the face-in-the-crowd task was 6.3% at test 1 and 5.7% at test 2. Latencies shorter than 100 msec or reaction times longer than 2 SD above the participant s mean overall reaction time were considered extreme outlier responses and excluded from further analysis. A total of 3.5% of latencies at test 1 and 3.7% of latencies at test 2 were extreme outliers. It was decided a priori to exclude subjects from analysis who committed more than 40% errors on the test. 9 However, in the present sample no participant exhibited such a high error rate. Depressives did not differ significantly from control subjects regarding number of outlier responses at both test sessions. Because of the unbalanced design, separate analyses were computed for same trials and for different trials. For the same displays a anova on search latencies with group as a between-groups factor (depressed patients vs control subjects) and time (test 1 vs test 2) and face valence (all neutral, all negative, all positive) as within-group factors yielded significant main effects of group (F 1,28 = 6.9, P < 0.05) and face valence (F 2,27 = 37.1, P < 0.001). Depressives showed slower responses than normal subjects. According to Tukey HSD post-hoc tests, response latencies in the all neutral condition were significantly faster than in the display conditions all positive and all negative (P < 0.001) (Fig. 2). In addition, response latencies in the all positive faces condition were faster than in the all negative faces condition (P < 0.05). The interaction of group and time was also significant (F 1,28 = 6.8, P < 0.05). At test 1 depressives responded slower to the same displays than at test 2. For control subjects, reaction times did not differ between test sessions. Analysis of the error data for the same displays revealed also main effects of group (F 1,28 = 5.5, P < 0.05) and face valence (F 2,27 = 10.5, P < 0.001). Depressives committed more errors than normal subjects. Error rate in the all negative condition was higher than in the conditions all neutral and all positive (P < 0.001). No other significant effects were obtained. For the different displays a anova on search latencies with group as a between-groups factor and time and search condition (one negative, three neutral; one negative, three positive; one positive, three neutral; one positive, three negative) as withingroup factors revealed significant main effects of group (F 1,28 = 5.6, P < 0.05) and search condition (F 3,26 = 76.8, P < 0.001). Depressives showed slower responses than normal subjects. Finding a negative face in a neutral crowd was faster than finding a positive face in a neutral crowd (P < 0.001). Furthermore, finding a negative face in a neutral crowd was faster than finding a negative face in a crowd of positive faces (P < 0.001). Finally, finding a positive face in a neutral crowd was faster than finding a positive face in a crowd of negative faces (P < 0.001). The interaction of group and time (F 1,28 = 4.6, P < 0.05) and time and condition (F 3,26 = 3.6, P < 0.05) were also significant. At test 1 Table 1. Affective characteristics of study participants at the two test sessions Depressed patients Normal subjects Test 1 Test 2 Test 1 Test 2 Mean SD Mean SD Mean SD Mean SD Beck Depression Inventory Automatic Thoughts Questionnaire Spielberger State Trait Inventory state version

5 Disengagement of attention in depression 727 Figure 2. Mean of correct reaction time (in msec) in the face-in-thecrowd task for same displays and for different displays at test 1 and test 2 (neu = neutral, neg = negative, pos = positive). Table 2. Mean error rates of study participants on the face-in-the-crowd task at the two test sessions Depressed patients Normal subjects Test 1 Test 2 Test 1 Test 2 Mean SD Mean SD Mean SD Mean SD All neutral All negative All positive Negative among neutral Negative among positive Positive among neutral Positive among negative depressives responded slower to the different displays than at test 2 (P < 0.05). For control subjects, reaction times did not differ between test sessions. In the display conditions one negative, three neutral, one negative, three positive and one positive, three neutral response latencies decreased from test 1 to test 2 (P < 0.001), while for the one positive, three negative displays response latencies did not change significantly between test sessions. Analysis of the error data for the different displays revealed only a significant main effect of search condition (F 3,26 = 9.2, P < 0.001) (Table 2). Finding a negative face in a neutral crowd produced fewer errors than finding a negative face in a crowd of positive faces (P < 0.01). Furthermore, finding a positive face in a neutral crowd was associated with fewer errors than finding a positive face in a crowd of negative faces (P < 0.001). DISCUSSION The results of the present study do not support the hypothesis that when scanning crowds of faces depressed patients take longer to disengage attention from negative faces (relative to neutral faces) than normal subjects and are faster to disengage attention from positive faces (relative to neutral faces). Depressed patients had in general higher response latencies than healthy individuals and produced more errors in the face-in-the-crowd task but they exhibited the same scanning or search pattern for facial emotion as healthy individuals. High response latencies of depressives can be due to a general motor slowing or to impairments in effortful information processing. 25,26 The face-in-thecrowd task administered in the present study consisted of seven different types of displays requiring rather

6 728 S. P. Karparova et al. complex attentive search strategies. However, our data suggest that the ability to disengage attention from facial emotion in visual search is not impaired in depressives (or at least in depressives with an anxiety disorder) even in a state of acute depression. Diagnoses of depression and anxiety co-occur very frequently. According to Kessler et al. the 12-month prevalence rate of a comorbidity of depression and anxiety is about 50%. 27 In the present study displays of faces were shown briefly (800 msec) so that rather fast acting attentional engagement and disengagement processes were assessed involving perhaps also iconic memory. Loughland et al. used a naturalistic visual scanning approach presenting a single face as target for approximately 10 s to study visual scanpaths to facial expression. 28 Their findings indicate that depressed patients avoid facial features in general across different facial expressions (neutral, happy, and sad) but that they are not impaired in the recognition of facial emotions. The avoidance to explore facial expressions of other persons for a longer period of time could be part of a social inhibition syndrome which is frequently observed in depression. Results from a recent study in which the Garner task was applied suggest that depressed patients could have difficulties in selectively ignoring facial expressions of emotion. 29 In this experiment participants had to selectively focus on a relevant dimension (e.g. gender), while ignoring variations of other, irrelevant ones (emotions). It was observed that depressed individuals were more distracted by (task irrelevant) facial emotion than normal subjects. The authors concluded that depressives might have difficulty in stopping attending to facial emotions. Thus, it seems that depressed individuals could be slower in disengaging from facial emotion information when processing a single face. However, according to our data when searching through crowds of faces depressives appear not to be impaired in disengaging attention from facial emotion. All subjects, regardless of clinical status, detected a negative face more rapidly in a crowd of faces than a positive face which is in line with results from previous experiments. 9 11,16,17 More importantly, when displays consisted of repetitions of the same face, subjects were generally slower (and less accurate) when the faces were negative relative to positive or neutral. The negative facial expression appears to hold visual attention, much like a Stroop-like interference effect. Processing of negative and positive faces was differentially effective even though negative and positive schematic faces were built by identical physical features (negative faces had an identical mouth-line rotated 180 degrees from the positive faces). Thus, greater detectability of (and greater distraction from) negative expression cannot be attributed to some low level visual confound in the facial stimuli. Our results fully support the suggestion of Fox et al. that there is an enhancement of the detection of a single negative face as well as a general distraction from crowds of negative faces. 9 An adaptively operating visual system should be fast in detecting potential threat or harm but should also maintain attentive processing in the location of potential threat once it has been detected. Our depressed patients showed a significant reduction of depressive symptoms after 6 weeks of inpatient treatment. The BDI data suggest that depressed patients were only partially remitted at the second test session. The mean BDI score of 18.4 indicates still a moderate depression level in the patient sample. 30 Interestingly, even though depressivity (and response latencies) decreased significantly from test 1 to test 2 the profile of depressed patients search and detection performance remained stable. This result pattern indicates a relative independence of clinical symptoms and cognitive characteristics during the recovery phase (see for analogous findings 31 ). Certain limitations to the present investigation should be acknowledged. Comorbid depressed patients were heterogeneous with regard to anxiety disorders. The majority of the patients examined in our study were medicated at both test sessions. The impact of medication treatment on search processes remains to be clarified. The negative schematic faces used in our study are ambiguous. They can be interpreted as angry or sad facial expressions. Future studies on visual processing of facial emotion should administer schematic faces with eyebrows, so that the facial expressions of anger and sadness can be studied separately. 15 Schematic instead of real emotional expressions were used in our face-in-the-crowd task, so we have to be cautious about generalizing our findings. REFERENCES 1. McArthur LZ, Baron RM. Toward an ecological theory of social perception. Psychol. Rev. 1983; 90: Surguladze SS, Young AW, Senior C, Brebion G, Travis MJ, Phillips ML. Recognition accuracy and response bias to happy and sad facial expressions in patients with major depression. Neuropsychology 2004; 18: Bouhuys AL, Geerts E, Gordijn MCM. Depressed patients perceptions of facial emotions in depressed and remitted states are associated with relapse: a longitudinal study. J. Nerv. Ment. Dis. 1999; 187: Mathews A, MacLeod C. 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