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Global visual scanning abnormalities in schizophrenia and bipolar disorder
Schizophrenia Research 87 (2006) 212 – 222 www.elsevier.com/locate/schres
Global visual scanning abnormalities in schizophrenia and bipolar disorder Patricia E.G. Bestelmeyer a,⁎, Benjamin W. Tatler b , Louise H. Phillips a , Gillian Fraser c , Philip J. Benson a , David St.Clair c a
School of Psychology, William Guild Building, University of Aberdeen, Aberdeen, AB24 2UB, UK b Department of Psychology, University of Dundee, Dundee, DD1 4HN, UK c Department of Mental Health, University of Aberdeen, Aberdeen, AB25 2ZD, UK Received 8 March 2006; received in revised form 7 June 2006; accepted 8 June 2006 Available online 24 July 2006
Abstract Visual scanning of face images is widely reported to be abnormal in schizophrenia. This impaired processing has been proposed to be partly responsible for patients' disturbance in social interactions. The present study was designed to determine whether abnormal scanning is specific to images with social content or extends to other types of stimuli. Individuals with schizophrenia (n = 22), bipolar disorder (n = 19) and healthy controls (n = 37) were asked to view a series of 28 images with or without socially important content (i.e. faces, landscapes, fractals and noise patterns) while their eye movements were recorded videooculographically. Temporal and spatial characteristics of scan paths were compared for each patient group and picture type. Independent of image content, patients with schizophrenia exhibited fewer fixations, longer fixation duration, longer saccade duration and peak velocity, and smaller saccade amplitude compared with healthy controls. Patients with schizophrenia and bipolar disorder did not differ significantly from one another on any of the temporal variables recorded. Fixation location distributions of participants with schizophrenia differed significantly from that of healthy controls on all picture types and from patients with bipolar disorder on all but face images. Abnormal scanning in schizophrenia and also bipolar disorder was independent of stimulus type and therefore reflects a global visual scanning impairment not specific to faces. Spatial scanning characteristics but not temporal ones may serve as biomarkers in the functional psychoses. © 2006 Elsevier B.V. All rights reserved. Keywords: Schizophrenia; Bipolar disorder; Eye movements; Scan paths; Trait marker
1. Introduction Visual scan path is a pattern of foveal fixations and voluntary saccades produced when an individual views an image (Norton and Stark, 1971). Scan path abnormalities have been proposed to serve as a trait marker for schizo⁎ Corresponding author. Tel.: +44 1224 273279; fax: +44 1224 273426. E-mail address: [email protected] (P.E.G. Bestelmeyer). 0920-9964/$ - see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2006.06.015
phrenia (Loughland et al., 2002a, 2004; Streit et al., 1997). Diagnosis of schizophrenia is currently symptom based and there are no external markers with which to validate the current diagnostic boundaries. The identification of a robust behavioral marker associated with schizophrenia would be of great benefit. Establishing reliable and valid diagnostic boundaries, especially in the early stage of illness, is essential for properly targeted medicine. So far, most clinical scan path studies have focused on the investigation of eye movements to images of
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social scenes, or most commonly, of faces. Typically, healthy participants tend to fixate salient features of a face such as the eyes, nose or mouth compared to nonsalient features such as the cheek or chin (Walker-Smith et al., 1977). Gordon et al. (1992) were the first to investigate the scan paths of patients with schizophrenia to faces. Patients with schizophrenia were found to make fewer visual fixations and tended to focus less on salient facial features compared to normal controls. Restricted visual scan paths to faces and social scenes have been confirmed repeatedly (Gaebel et al., 1987; Loughland et al., 2002b; Phillips and David, 1997; 1998; Williams et al., 1999) and have been used to explain, at least in part, the social disturbances most individuals with schizophrenia experience (Williams et al., 1999, 2003). Studies have examined whether visual scanning of images without any social content is impaired in schizophrenia and the results are equivocal. For example, Kojima et al. (1992) explored scan path behavior to line drawings and found that patients with schizophrenia compared to healthy controls exhibited fewer visual fixations (see also Ryu et al., 2001 for a similar study and Green et al., 2000 for a comprehensive review of studies using mainly geometric figures). Similarly, Minassian et al. (2005) demonstrated that patients with schizophrenia displayed fewer fixations of longer duration to abstract Rorschach stimuli compared to healthy controls. Minassian et al. (2005) suggested that patients with schizophrenia have a general impairment with regards to visual scanning. However, in contrast to images of faces, Rorschach stimuli and line drawings are neither aesthetically interesting nor biologically important. Therefore increased staring behavior to these abstract pictures may have occurred due to a lack of motivation or disinterest of the patients in the displayed images rather than an actual visual scanning impairment. A selection of image categories of equivalent complexity and/or interest to that of a face may be crucial to determine whether these scanning impairments are global or confined to socially salient stimuli. To our knowledge, only one published study has investigated the specificity of restricted scan paths in patients with schizophrenia to socially salient stimuli by directly comparing the scan paths to an image of a face and the Rey complex figure (Manor et al., 1999). Manor et al. (1999) concluded that in comparison to controls, individuals with schizophrenia have dysfunctional scanning of faces, leading to social deficits. Inspection of their results reveals that overall length of the scan path in response to the face images was significantly
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shorter for patients with schizophrenia as compared to healthy controls. However, there was no statistically significant difference in the number of fixations or fixation duration between the two groups for faces or the Rey figure. In addition, qualitative differences between the group of patients with schizophrenia and the control group were evident to the Rey figure as well as the face image. Other explanations for the overall shorter scan path length to the face image are possible. The novelty of the Rey figure and the fact that this figure was always presented first may have caused patients with schizophrenia to scan more extensively than they would usually do if several of these two categories of stimuli had been presented in a random order. A more serious confound is that the Rey figure subtended a larger visual angle than the face stimulus which may well explain the greater scan path length for the Rey figure compared to the face stimulus. These methodological confounds cast serious doubts on Manor et al.'s (1999) conclusion and the accepted view in the literature that restricted visual scanning in schizophrenia is specific to faces which has been used to partly explain patients' difficulties in social functioning (Loughland et al., 2002a). Furthermore, some preliminary evidence reported by Leonards et al. (2002) suggests that visual scanning abnormalities in patients with schizophrenia extended to non-social stimuli. A thorough investigation of the nature and extent of the scanning impairment in schizophrenia in response to complex social and non-social stimuli is therefore warranted. When analyzing the spatial distribution of fixations to a face, most researchers have divided the image into salient and non-salient facial features. Spatial analysis of visual fixation distributions of objects that do not share the same features has been difficult. One limitation of the studies by Kojima et al. (1992), Manor et al. (1999) and Minassian et al. (2005) is that they have concentrated on variables that describe the temporal characteristics of scan paths rather than their spatial extent. An exploration of the differences in what aspects of an image patients and healthy controls select for fixation when viewing images might reveal insights that are not apparent from the temporal data alone. We therefore extend previous studies by comparing not only temporal but also spatial characteristics of the scan paths. Most current approaches for assessing the spatial similarity between scan paths take the form of nearest saccade metrics, often based upon the sum of squared differences between fixations (e.g. Mannan et al., 1995, 1996, 1997). However, there is no logical reason to
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suggest that fixations 20 degrees apart are twice as different as those 10 degrees apart (or four times if using a squared difference). The technique developed by Tatler et al. (2005) avoids this problem and simply classes fixations within the radius of the fovea as the same, and those beyond the radius of the fovea as different. Tatler et al.'s (2005) technique involves estimating spatial probability distributions of the fixation locations and uses a technique known as the Kullback–Leibler divergence to estimate the difference between these distributions (for a full discussion of the benefits of this metric see Tatler et al., 2005). For scan paths to serve as a useful diagnostic tool for schizophrenia, scanning abnormalities should be present in most, if not all affected individuals. In addition, this abnormality should be specific to schizophrenia and should not be observed in patient groups suffering from other kinds of functional psychoses. An interesting study by Loughland et al. (2002a) has addressed the issue of specificity of visual scanning impairments in schizophrenia by comparing scan paths of patients with schizophrenia to that of a mixed group of patients with affective disorder (i.e. patients with unipolar depression and bipolar disorder). Loughland et al. (2002a) found that the temporal variables of affective disorder patients fell between those of healthy controls and patients with schizophrenia and were significantly different only from those of the participants with schizophrenia but not healthy controls. Loughland et al. (2002a) concluded that the scan path aberrations of affective disorder patients were relatively minor and that more serious scan path abnormalities are specific to schizophrenia. The first aim of the present study was to conduct an extensive investigation to clarify whether abnormal visual scanning behavior in schizophrenia is specific to faces or whether this abnormal scanning can be found to a wider range of image categories. To examine this issue we asked participants to view a series of socially and biologically important stimuli (faces), aesthetically and biologically important images (landscapes), non-biological, aesthetically interesting images (fractals) and complex images which were neither biologically relevant nor aesthetically pleasing (pink noise, i.e. meaningless images with a fog-like appearance). If restricted scanning in schizophrenia is specific to faces, scanning of all but face images should be no different from that of healthy controls. If, however, restricted scanning is specific to evolutionarily important stimuli, restricted scanning should be evident to faces as well as landscapes but not to artificially generated images. Similarly, if restricted scanning in schizophrenia represents a global impairment, scanning
abnormalities should be manifest in all image categories. As well as differences in temporal variables of scan paths, we hypothesized that the spatial distribution of fixations will also differ between participant groups irrespective of image type. The second aim was to investigate whether restricted scan paths are specific to schizophrenia. If scan path aberrations are to serve as a possible trait marker for schizophrenia the scan path variables of the patient group with schizophrenia should differ significantly from healthy controls. The specificity of abnormal scan paths in schizophrenia versus other neuropsychiatric groups should determine not only their potential diagnostic value but could help to address some of the current uncertainties concerning the diagnostic boundaries of schizophrenia versus the affective psychoses (Cardno et al., 2002; Craddock et al., 2005). 2. Methods 2.1. Participants Twenty-two patients with schizophrenia, 19 patients with bipolar disorder and 37 healthy, unmedicated control participants without a family history of mental illnesses took part in the experiment. Patients1 were recruited from the Royal Cornhill Hospital, a psychiatric teaching hospital affiliated with the University of Aberdeen. The study was approved by Grampian Research Ethics Committee and additional permission was granted by the responsible psychiatrist. All participants gave written informed consent. Diagnosis of schizophrenia and bipolar 1 patients was made using The Operational Criteria Checklist (McGuffin et al., 1991) by case note review and clinical interview. DSMIV diagnoses of all patients were confirmed by two experienced clinicians. Group characteristics such as age, gender ratio, education level, and illness duration
1
Nineteen patients with schizophrenia received antipsychotic pharmacologic treatment consisting of a mean daily chlorpromazine (CPZ) equivalent of 313 mg (S.D. = 151.74) (BNF, 2005). Eleven patients with bipolar disorder were on pharmacologic mood stabilizing treatment with a daily mean intake of 890 mg (S.D. = 164.0) of lithium and two patients were on 800 mg of carbamazepine. The remaining bipolar patients were either on antipsychotic treatment alone or received a mixture of mood stabilizing and antipsychotic treatment (1 on 400 CPZ equivalent; 1 on 132 mg CPZ equivalent plus 40 mg of imipramine; 1 on lithium 800 mg plus chlorpromazine 250 mg; 1 on 400 mg of CPZ equivalent plus 600 mg of carbamazepine and 600 mg of lithium; 1 on 800 mg of lithium plus 20 mg of fluoxetine and 1 on 800 of lithium plus 200 mg of chlorpromazine and 400 mg of carbamazepine).
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are listed in Table 1 for all participant groups. Participants were free of any diagnosed neurological disorders and had normal or corrected to normal vision. All patients were in remission at the time of testing. Travel expenses were reimbursed in full for all participants. 2.2. Materials Twenty-eight color photographs of 24-bit 800 × 600 pixels were used. All images except faces subtended a visual area of 34° horizontally and 25° vertically at a viewing distance of 60 cm. Face images subtended a visual area of 19° × 25°. There were seven images in each of the four different categories: faces, landscapes, fractals, and pink noise patterns. The seven facial stimuli were drawn from “The Averaged Karolinska Directed Emotional Faces” CD ROM (Lundqvist and Litton, 1998) and each displayed one of the seven main emotions. Pictures of four emotional expressions were that of a female poser (anger, fear, neutral, sadness) and three stimuli of a male poser (disgust, happiness, surprise). Seven natural scenes depicted landscapes without any man made structures. Seven Mandelbrot and Julia fractals were created using ChaosPro 3.02 (Pfingstl, 2004). Finally, seven different pink noise pictures were used as control stimuli. 2.3. Apparatus Eye movements were recorded using an EyeLink I (SR Research Ltd.) video-based eye tracker which employs infra red pupil tracking to record eye position data at 250 Hz and compensates for minor head movements. Eye movement data were collected monocularly. A 3 × 3 target display was used for calibration of eye position. The same display was used to validate the calibration. Analysis of the recorded eye movement data was conducted off-line using custom made analysis scripts in MATLAB 7 (The MathWorks, Inc.).
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2.4. Procedure Participants were given a free viewing task, i.e. volunteers were asked to view each image presented on a computer screen in any way they liked. In addition, participants were advised to ask for breaks during the experiment whenever necessary. After acquaintance of the participant with the equipment and the initial instructions the head mounted eye tracker was fitted. Eye movement recordings were conducted in a quiet and darkened room. Each of the 28 trials consisted of a central black fixation dot on a grey background followed by the presentation of an image for 5 s after which the display returned to the initial background. After successful calibration and validation of eye movement position each participant was presented with the same pseudo-randomized sequence of images. Visual fixation had to be maintained on the central dot at the start of each trial to be able to trigger the display of the image. The experiment took approximately 15 min to complete. 2.5. Data analysis Saccade detection required a deflection, within a 4 ms period, of greater than 0.1° (degree), with a minimum velocity of 30°/s (degrees per second) and a minimum acceleration of 8500°/s2 (SR Research Ltd.). Fixations were classified as those times in which the eye did not deviate by this amount and a minimum fixation duration of 100 ms was employed (Manor and Gordon, 2003). For each trial temporal and spatial variables were extracted. Temporal scan path variables examined were number of fixations, fixation duration, saccade duration, saccade amplitude, and peak velocity, and were measured separately for each of the four image categories. Eye movement variables were subjected to separate mixed design analyses of variance (ANOVA). In order to consider the spatial properties of visual inspection by the different participant groups, we used an information theoretic measure employed by Tatler et
Table 1 Means and standard deviations (S.D.) of participant demographics Participants
N
Age (years)
Gender
Mean (S.D.)
Male
SZ BP HC
22 19 37
40.8 (12.31) 49.2 (10.63) 37.7 (11.05)
16 7 18
Education (years)
Illness duration (years)
Female
Mean (S.D.)
Mean (S.D.)
6 12 19
11.6 (2.28) 12.4 (2.79) 14.2 (3.60)
Patients with schizophrenia (SZ); patients with bipolar disorder (BP); healthy control participants (HC).
16.3 (11.14) 22.7 (12.44) 0
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al. (2005) and based upon the Kullback–Leibler (KL) divergence. For each image category, we converted the spatial distribution of fixations made by each patient with schizophrenia into probability distributions (using a binning technique with 2° × 2° bins) and then compared the distribution for that patient with distributions created from all other patients with schizophrenia. This KL measure reflects the within-group differences for the participants with schizophrenia. We then compared the fixation distribution from each patient with schizophrenia with the distributions of fixations for participants in the healthy control group and the patient group with bipolar disorder. These two measures reflect the between-group differences in spatial distribution of fixations between the patient group with schizophrenia and each of the other two participant groups. This procedure was repeated for the data of the patients with bipolar disorder. Possible confounding effects of age, level of education, illness duration and gender were examined. Influences of age and level of education were assessed using analysis of covariance and neither co-varied significantly with any of the scan path variables. In addition, there were no significant interactions between gender, diagnosis, and image type on any scan path variables. Relationships between illness duration and scan path variables of patients with schizophrenia and bipolar disorder were calculated but no significant correlations emerged. 3. Results 3.1. Analysis of temporal scan path variables Fig. 1 illustrates representative visual scan paths of one participant from each group on each type of stimulus. Restricted visual scanning was evident for both patient groups compared to controls, across all types of image. Table 2 lists the means and standard deviations for all scan path variables separately for image type and patient group. Table 2 also demonstrates that patients with schizophrenia were most different from healthy controls and that patients with bipolar disorder tended to occupy an intermediate position for all scan path variables. The same pattern for all groups was evident independent of image type. To statistically test whether patients with schizophrenia had a specific impairment for the scanning of faces compared to other stimulus types, mixed design ANOVAs were carried out on each of the five temporal scan path variables, with stimulus type as a repeated measure, and patient group as a between-group factor.
All within-group effects were reported with Greenhouse–Geisser corrections due to the violation of sphericity. Tukey's HSD corrections were applied to post hoc tests. The results of post hoc tests of these mixed design ANOVAs for the patient group are summarized in Table 3. Patient group and stimulus type significantly affected number of fixations (F = 7.54, df = 2, 75, p < 0.001, partial eta squared (pη2) = 0.17 and F = 68.58, df = 2.31, 173.40, p < 0.001, pη2 = 0.48, respectively). Patients with schizophrenia made significantly fewer fixations compared with healthy controls. Patients with bipolar disorder were not significantly different from either patients with schizophrenia or healthy controls. Fewest fixations were made in response to the pink noise pictures compared to all remaining pictures (p < 0.001) and significantly more fixations were made in response to the landscape pictures compared with the fractal patterns (p < 0.001). In support of the hypothesis that scanning abnormalities in schizophrenia apply to both social and non-social stimuli, no interaction was found between patient group and stimulus type (F = 0.59, df = 4.62, 173.40, p > 0.70, pη2 = 0.02). Stimulus type (F = 17.22, df = 1.84, 138.17, p < 0.001, pη2 = 0.19) but not patient group (F = 2.62, df = 2, 75, p > 0.05, pη 2 = 0.07) significantly affected fixation duration. Nevertheless, post hoc tests revealed that patients with schizophrenia have longer fixation durations compared with healthy controls. Patients with bipolar disorder were not significantly different from either patients with schizophrenia or healthy controls. Fixation duration was longest to noise images compared with all other image types (p < 0.001) and longer to fractals than to landscape images. Again, no significant interaction was found between patient group and stimulus type (F = 0.69, df = 3.68, 138.17, p > 0.60, pη2 = 0.02). Saccade duration was significantly affected by patient group (F = 3.96, df = 2, 75, p < 0.05, pη2 = 0.10) and stimulus type (F = 23.02, df = 1.47, 110.02, p < 0.001, pη 2 = 0.24). Patients with schizophrenia exhibited significantly longer saccade durations compared to healthy controls. Patients with bipolar disorder were not significantly different from either patients with schizophrenia or healthy controls. Saccade duration was longest for noise pictures (p < 0.001) and shortest for face images compared to landscapes (p < 0.01) and fractals (p < 0.001). Saccade duration was longer for fractals compared to landscape images (p < 0.05). No significant interaction was obtained between patient group and stimulus type (F = 1.32, df = 2.93, 110.02, p > 0.25, pη2 = 0.03).
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Fig. 1. Representative visual scan paths to each stimulus type for one participant from each of the three groups. Participants who showed close to the average scan path characteristics of their group as listed in Table 2 were chosen; the three participants were matched for age and gender. Diameter of the circles is proportional to fixation duration (ms). Note that the brightness of the landscape and fractal images has been altered to ease presentation of scan paths.
Saccade peak velocity was significantly affected by patient group (F = 6.34, df = 2, 75, p < 0.01, pη2 = 0.15) and stimulus type (F = 72.49, df = 2.46, 184.84, p < 0.001, pη2 = 0.49). Both patient groups had significantly lower peak velocities compared to healthy controls. Furthermore, eye movements reached highest peak velocities for landscape and fractal patterns compared to faces (p < 0.001) and noise images (p < 0.01). Peak velocities were slowest for face images (p < 0.001). A significant interaction for patient group and stimulus type was obtained (F = 3.11, df = 4.92,
184.84, p < 0.05, pη2 = 0.08). Independent samples ttests revealed that the peak velocity of patients with schizophrenia was significantly longer than that of healthy controls in response to landscapes (t = − 2.61, df = 57, p < 0.05), fractals (t = − 3.75, df = 57, p < 0.001), and noise images (t = − 2.16, df = 57, p < 0.05) but not face stimuli (t = − 1.59, df = 57 p = 0.12). Saccade amplitude was significantly affected by patient group ( F = 10.16, df = 2, 75 p < 0.001, pη2 = 0.21) and stimulus type (F = 196.83, df = 2.40, 180.00, p < 0.001, pη 2 = 0.72). Both patient groups
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Table 2 Group means and S.D. for each participant group and image type on all scan path parameters Image type
Landscapes
Fractals
Faces
Noise
Scan path variables
Participant group
Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°) Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°) Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°) Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°)
HC
SZ
BP
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
14.1 (1.95) 285.8 (40.81) 43.3 (9.63) 289.1 (69.41) 5.0 (0.95) 13.1 (3.02) 313.6 (97.82) 46.9 (17.70) 296.6 (84.34) 4.9 (0.84) 13.6 (2.77) 332.0 (93.43) 34.8 (8.12) 200.6 (53.69) 1.9 (0.60) 10.2 (3.55) 439.2 (280.44) 59.3 (47.46) 255.3 (66.55) 4.1 (1.36)
11.7 (3.10) 371.8 (190.95) 50.1 (19.46) 242.9 (59.25) 4.4 (1.12) 9.8 (3.62) 422.7 (188.46) 63.7 (32.91) 221.7 (52.42) 3.6 (0.98) 11.5 (2.94) 378.5 (113.67) 45.2 (21.30) 179.6 (39.99) 1.7 (0.92) 7.3 (3.01) 518.8 (244.85) 88.6 (54.21) 213.9 (78.99) 2.5 (1.44)
12.9 (2.67) 314.7 (75.98) 48.5 (22.34) 241.6 (48.88) 4.2 (1.26) 12.0 (3.76) 352.2 (140.78) 50.2 (22.97) 239.6 (67.70) 3.8 (1.09) 12.7 (2.97) 341.9 (98.03) 42.0 (15.98) 170.6 (35.05) 1.7 (0.75) 9.2 (3.14) 411.9 (154.74) 68.1 (44.24) 217.1 (45.81) 3.0 (1.58)
Healthy control participants (HC); patients with schizophrenia (SZ); patients with bipolar disorder (BP). Duration is measured in milliseconds (ms); saccade peak velocity is measured in degrees per second (°/s); saccade amplitude is measured in pixels per degree (°).
displayed significantly smaller saccade amplitudes than healthy controls. Saccade amplitudes were significantly different for all image types (all at p < p < 0.001) such that largest saccade amplitudes were made to the landscape pictures, then to fractals, after that to faces and smallest amplitudes were made in response to noise images. A significant interaction between patient group and stimulus type was obtained (F = 5.26, df = 4.80, 180.00, p < 0.001, pη 2 = 0.12). Independent samples t-tests revealed that the saccade amplitude of patients with schizophrenia was significantly smaller than that of
Table 3 Summary of Tukey's HSD post hoc analyses between participant groups on the measured scan path variables independent of picture type Scan path variables
HC vs. SZ
HC vs. BP
SZ vs. BP
Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°)
⁎⁎⁎ ⁎ ⁎ ⁎⁎ ⁎⁎⁎
n.s. n.s. n.s. ⁎ ⁎⁎
n.s. n.s. n.s. n.s. n.s.
Healthy control participants (HC); patients with schizophrenia (SZ); patients with bipolar disorder (BP). ⁎ p < 0.05; ⁎⁎ p < 0.01; ⁎⁎⁎p < 0.001; n.s. (difference is not significant at the 0.05 level).
healthy controls in response to landscapes (t = − 2.30, df = 57, p < 0.05), fractals (t = − 5.48, df = 57 p < 0.001), and noise images (t = − 4.17, df = 57, p < 0.001) but not face stimuli (t = − 1.11, df = 57, p = 0.27). 3.2. Analysis of spatial scan path variables Tables 4a and 4b lists group differences in visual fixation distribution in terms of Kullback–Leibler (KL) divergence for all picture types for using (a) the patient Table 4a Mean Kullback–Leibler Divergence (bits) and S.D. for the schizophrenia reference group
Landscapes Fractals Faces Noise
SZ–SZ
SZ–BP
SZ–HC
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
3.9 (0.79) 3.8 (0.93) 2.6 (1.01) 3.7 (0.95)
4.3 4.6 2.7 4.9
5.0 (0.76) 5.1 (0.75) 2.8 (1.08) 5.0 (0.71)
(0.72) (0.85) (1.38) (0.99)
SZ–SZ, schizophrenia within-group comparison. SZ–BP, between-group differences for the patients with schizophrenia compared to patients with bipolar disorder. SZ–HC, between-group differences for the patients with schizophrenia compared to the healthy control group.
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group with schizophrenia as the reference and in a separate comparison (b) the patient group bipolar group as the reference group. The KL values show the magnitudes of the differences between distributions of fixations. The exact values in bits are uninformative as they are sensitive to the binning technique used in creating the probability distributions, but the relative differences are informative. For example, in Table 4a, SZ–HC comparisons have higher KL values than do SZ–BP. This shows that there are greater differences between the patients with schizophrenia and healthy controls than there are between patients with schizophrenia and bipolar disorder. A 3 (group) ×4 (stimulus type) ANOVA on the KL divergence of the patients with schizophrenia compared to the two other groups revealed significant main effects of patient group (F = 138.52, df = 1.64, 34.38, p < 0.001, pη2 = 0.87) and picture type (F = 30.31, df = 2.18, 45.84, p < 0.001, pη2 = 0.59). There was also a significant interaction between patient group and picture type (F = 24.13, df = 2.72, 57.19, p < 0.001, pη 2 = 0.54). Planned comparisons using paired t-tests explored these effects. The divergence within schizophrenia patients (SZ–SZ) was significantly smaller than the divergence between patients with schizophrenia and healthy controls (SZ–HC) for landscapes, fractals, noise (p < 0.001) and faces (p < 0.05). Therefore, for all image types, there was greater similarity within the patient group with schizophrenia in terms of eye movement behavior than between the patients with schizophrenia and the healthy controls (Table 4a). The divergence within patients with schizophrenia (SZ–SZ) was significantly smaller than the divergence between Table 4b Mean Kullback–Leibler Divergence (bits) and S.D. for the bipolar disorder reference group BP–BP
Landscapes Fractals Faces Noise
BP–SZ
BP–HC
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
3.5 3.9 1.4 4.1
3.9 4.0 2.4 4.2
4.6 (0.73) 4.7 (0.78) 2.1 (0.72) 4.7 (0.93)
(0.71) (0.89) (0.56) (1.14)
(0.60) (0.79) (0.77) (1.02)
BP–BP, bipolar disorder within-group comparison. BP–SZ, Between-group differences for the patients with bipolar disorder compared to patients with schizophrenia. BP–HC, Between-group differences for the patients with bipolar disorder compared to the healthy control group. Note that the absolute values of the KL divergence reported in this table depend upon the binning technique used when creating the probability distributions (see Methods). The important comparisons are the differences in the KL divergence between the different groups and stimulus types.
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patients with schizophrenia and bipolar disorder (SZ– BP) for landscapes, fractals, and noise (p < 0.001) but not for faces. Therefore, for landscapes, fractals, and noise images, there is greater consistency within the patients with schizophrenia than between the patients with schizophrenia and bipolar disorder. To summarize, in all but the face stimuli, the variation in the spatial distribution of fixations was substantially greater between the schizophrenia and the other two participant groups, than the individual differences among patients with schizophrenia. Consequently, patients with schizophrenia were distributing their fixations differently from the other two groups of observers when viewing these images. A 3 (group) ×4 (stimulus type) ANOVA on the KL divergence of the patients with bipolar disorder compared to the healthy controls and the patients with schizophrenia revealed significant main effects of group (F = 66.16, df = 1.28, 22.98, p < 0.001, pη2 = 0.79) and picture type (F = 63.09, df = 2.23, 40.11, p < 0.001, pη2 = 0.78). There was also a significant interaction between patient group and picture type (F = 23.13, df = 3.79, 68.27, p < 0.001, pη2 = 0.56). Further planned comparisons using paired t-tests explored these effects. The divergence within patients with bipolar disorder (BP–BP) was significantly smaller than the divergence between patients with bipolar disorder and healthy controls (BP–HC) for landscapes, fractals, faces, and noise (all p < 0.001). Therefore, for all image types, there was greater similarity within the eye movement behavior of the patients with bipolar disorder than between the patients with bipolar disorder and the healthy controls (Table 4b). The divergence within the group of patients with bipolar disorder was significantly smaller than between the group of patients with bipolar disorder and schizophrenia (BP–SZ) for landscapes and faces (both p < 0.001) but not for fractals or noise. Therefore, for landscapes, and faces, there is greater consistency within the patients with bipolar disorder than between the patients with bipolar disorder and schizophrenia. 4. Discussion The first aim of this study was to determine whether abnormal visual scanning in schizophrenia is specific to faces or whether it can also be observed to other types of stimuli. The second aim was to investigate whether scanning abnormalities are specific to schizophrenia. For this purpose eye movements of participants with schizophrenia, bipolar disorder and healthy controls were recorded in response to a series of images
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comprising faces, landscapes, fractals, and pink noise patterns. In contrast to healthy controls, scanning abnormalities in the two patient groups were evident independent of image type. The two patient groups were indistinguishable on the basis of temporal scan path variables. However, the fixation distributions of participants with schizophrenia differed significantly from that of healthy controls on all image types and from patients with bipolar disorder on all but face images. Temporal variables of visual scan paths of patients with schizophrenia differed significantly from those of healthy controls. As in previous studies investigating scan paths to faces (Green et al., 2003; Phillips and David, 1997; Streit et al., 1997) the patient group with schizophrenia showed scan path abnormalities such as fewer fixations and a tendency for longer fixation duration compared to healthy controls. Typically, studies of eye movements to faces in schizophrenia have investigated visual scanning while the participants were instructed to identify the displayed emotional expression (e.g. Loughland et al., 2002b, 2004; Phillips and David, 1998). In the current study participants were simply asked to freely view the images. Despite this difference in task instructions we were able to replicate the well-established finding of restricted visual scanning of faces in schizophrenia. However, these group effects were not restricted to faces, and were present in all types of image. There was no evidence to suggest that individuals with schizophrenia were more impaired on socially salient stimuli (i.e. faces) compared to images without social content (landscapes, fractals, noise). Therefore the argument that abnormal visual scanning in schizophrenia is particular to social stimuli such as faces (Loughland et al., 2002a; Manor et al., 1999) is not supported. Instead, the abnormalities seen in schizophrenia are more likely to reflect a global scanning impairment. On most temporal variables (e.g. number of fixation, fixation and saccade duration) the interaction between patient group and image type did not reach statistical significance, indicating that the image content did not differentially change the participants' viewing behavior. Where interactions between group and stimulus type did reach significance (i.e. for saccade amplitude and peak velocity) the direction of effects did not support the theory of specific abnormalities of social processing in patients with schizophrenia. In other words, on these two variables there was no significant difference between healthy controls and patients with schizophrenia on face images, in contrast to significant group differences on the non-social stimuli. This finding can be explained by the overall smaller width of the face
images compared to other images, which covered the entire screen. For example, saccade amplitude to the face stimuli was short in all participants due to less available area to be scanned. In terms of the spatial distribution of fixations, differences between the patients with schizophrenia and healthy controls were greater than the schizophrenia within-group variations on all categories of images. This result can be explained in one of two ways. Firstly, it might be that individuals with schizophrenia were systematically selecting different locations on the image to fixate, from those selected by healthy controls. Secondly, patients with schizophrenia may have been systematically less extensive in their visual exploration of the images, but still have selected a subset of locations fixated by healthy controls. Our measure cannot readily distinguish these two possibilities2 . However, given generally smaller saccade amplitude, increased number of fixations of longer duration and slower overall eye movements (as indicated by lower peak velocity and longer saccade duration) in patients with schizophrenia compared to healthy controls the latter explanation seems more plausible. The example scan paths in Fig. 1 illustrate that members of the two psychiatric samples fixated a subset of locations selected by the healthy group. In contrast to Loughland et al. (2002a), temporal variables from the present study could not confirm a clear-cut difference between patients with schizophrenia and affective disorder. A visual scanning abnormality was evident in the group of patients with schizophrenia and to a lesser extent in the sample of patients with bipolar disorder such that the means of the temporal characteristics of the scan paths fell in between those of the schizophrenia and healthy group, and on none of these measures did patients with schizophrenia or bipolar disorder significantly differ. The proposal that temporal characteristics of visual scan paths may aid in establishing differential diagnosis of psychiatric conditions is not supported by the current data. Our finding adds to the accumulating evidence from other areas such as genetics showing that there is substantial overlap between schizophrenia and bipolar disorder (Bramon and Sham, 2001). Contrary to the current findings, Loughland et al. (2002a) did discover significant differences between 2 It should be noted that none of the current metrics available for quantifying differences between spatial distributions of fixations would be able to distinguish these two possibilities: all require further measures and findings to make inferences about the most likely explanation.
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patients with schizophrenia and affective disorder on temporal scan path measures when viewing faces. However, this apparent difference in results may be due to differences in the samples of affective patients used. The sample recruited by Loughland et al. (2002a) included patients with unipolar depression as well as bipolar disorder, whereas the affective sample in the present study only included patients with bipolar disorder. As the critical diagnostic issue in psychiatry is specifically in distinguishing bipolar disorder from schizophrenia, the current results are more pertinent in exploring the trait specificity of scan path abnormalities. Regarding the spatial distribution of fixations in the present study, differences between patients with bipolar disorder and healthy controls were greater than the within-group differences of the patients with bipolar disorder for all image types. Differences between patients with bipolar disorder and schizophrenia were greater than the within-group variations of the patients with bipolar disorder only on face and landscape images. Tables 4a and 4b demonstrates that the withingroup variations for the patients with schizophrenia were larger than the within-group variations for the patients with bipolar disorder, particularly for face stimuli. In other words, the sample of patients with bipolar disorder showed a more homogeneous spatial distribution of scanning of social stimuli compared to the sample of patients with schizophrenia. This may explain why the schizophrenia within-group variation was significantly different from the bipolar disorder within-group variation on all but face images. The KL divergence technique has shown that spatial differences between groups do exist; yet, the KL measure alone cannot explain where these differences lie. Our findings are interesting since they suggest that analysis of spatial measures of visual scan path may reveal differences within the psychoses not necessarily detectable by temporal measures alone. Larger numbers are required to confirm these novel observations and to determine the overall value of spatial measures as biomarkers for stratifying the functional psychoses. Previous researchers have argued that restricted scanning in schizophrenia indicates abnormal social or emotional processing and suggests a specific deficit in visual scanning of interpersonal information (Phillips and David, 1995; Williams et al., 1999, 2003). The current study provides clear evidence against the idea of socially specific visual abnormalities in schizophrenia (and also bipolar disorder). Abnormal visual scan parameters were found to both social and non-social stimuli, and the scan path abnormalities were no greater to faces compared to other stimuli in both patient
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groups. However, the current results also indicate that restricted scan paths to all types of complex stimuli may impair information processing of all aspects of the environment, with wider implications for cognitive and behavioral function. Contrary to arguments that schizophrenia and affective disorders might show different temporal scan path characteristics (Loughland et al., 2002a) in the current sample no clear difference was found. However, spatial differences in scanning did emerge between the participant groups. Our data highlight an important new direction in the study of visual scan paths as behavioral trait markers. By using information from both spatial and temporal characteristics of scan paths it may be possible to partition schizophrenia and other major psychiatric illnesses along novel lines that are of etiologic and therapeutic value. Acknowledgements We would like to thank all consultants for their help and all participants for generously giving their time to take part in this experiment. Thanks to Larry Cormack for calculating the pink noise images, Victoria Bourne for helpful stats advice and an anonymous reviewer for very constructive comments. We also thank Caroline Crombie, Gillian Fraser and particularly Maggie Sinclair for conducting OPCRITs on patients recruited for another study led by DSC. This research was supported by a grant from GlaxoSmithKline Ltd to DSC and PJB in 2004 (EPI 40256) and an equipment grant to PJB in 2001 from the Royal Society of London (RSRG 22226). PEGB is supported by a PhD studentship sponsored by the University of Aberdeen. References Bramon, E., Sham, P.C., 2001. The common genetic liability between schizophrenia and bipolar disorder: a review. Curr. Psychiatry Rep. 3, 332–337. Cardno, A.G., Rijsdijk, F.V., Sham, P.C., Murray, R.M., McGuffin, P., 2002. A twin study of genetic relationships between psychotic symptoms. Am. J. Psychiatry 159, 539–545. Craddock, N., O'Donovan, M.C., Owen, M.J., 2005. The genetics of schizophrenia and bipolar disorder: dissecting psychosis. J. Med. Genet. 42, 193–204. Gaebel, W., Ulrich, G., Frick, K., 1987. Visuomotor performance of schizophrenic patients and normal controls in a picture viewing task. Biol. Psychiatry 22, 1227–1237. Gordon, E., Coyle, S., Anderson, J., Healy, P., Cordaro, J., Latimer, C., Meares, R., 1992. Eye movement response to a facial stimulus in schizophrenia. Biol. Psychiatry 31, 626–629. Green, M.J., Williams, L.M., Hemsley, D.R., 2000. Cognitive theories of delusion formation: the contribution of visual scanpath research. Cogn. Neuropsychiatry 5, 63–74.
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Green, M.J., Williams, L.M., Davidson, D., 2003. Visual scanpaths to threat-related faces in deluded schizophrenia. Psychiatry Res. 119, 271–285. Joint Formulary Committee, 2005. British National Formulary, 50 ed. British Medical Association and Royal Pharmaceutical Society of Great Britain, London. Kojima, T., Matsushima, E., Ando, K., Ando, H., Sakurada, M., Ohta, K., Moriya, H., Shimazono, Y., 1992. Exploratory eye-movements and neuropsychological tests in schizophrenic-patients. Schizophr. Bull. 18, 85–94. Leonards, U., Duhoux, S., Rey-Bellet, P., Ibanez, V., Merlo, M., 2002. Do disturbances in social interaction influence visual scene exploration in psychotic patients? Perception 31, 182. Loughland, C.M., Williams, L.M., Gordon, E., 2002a. Schizophrenia and affective disorder show different visual scanning behavior for faces: a trait versus state-based distinction? Biol. Psychiatry 52, 338–348. Loughland, C.M., Williams, L.M., Gordon, E., 2002b. Visual scanpaths to positive and negative facial emotions in an outpatient schizophrenia sample. Schizophr. Res. 55, 159–170. Loughland, C.M., Williams, L.M., Harris, A.W., 2004. Visual scanpath dysfunction in first-degree relatives of schizophrenia probands: evidence for a vulnerability marker? Schizophr. Res. 67, 11–21. Lundqvist, D., Litton, J.-E., 1998. The Averaged Karolinska Directed Emotional Faces- AKDEF. AKDEF CD ROM. Psychology section, Karolinska Institutet, Stockholm. Manor, B.R., Gordon, E., 2003. Defining the temporal threshold for ocular fixation in free-viewing visuocognitive tasks. J. Neurosci. Methods 128, 85–93. Mannan, S.K., Ruddock, K.H., Wooding, D.S., 1995. Automatic control of saccadic eye movements made in visual inspection of briefly presented 2-D images. Spat. Vis. 9, 363–386. Mannan, S.K., Ruddock, K.H., Wooding, D.S., 1996. The relationship between the locations of spatial features and those of fixations made during visual examination of briefly presented images. Spat. Vis. 10, 165–188. Mannan, S.K., Ruddock, K.H., Wooding, D.S., 1997. Fixation patterns made during brief examination of two-dimensional images. Perception 26, 1059–1072. Manor, B.R., Gordon, E., Williams, L.M., Rennie, C.J., Bahramali, H., Latimer, C.R., Barry, R.J., Meares, R.A., 1999. Eye movements
reflect impaired face processing in patients with schizophrenia. Biol. Psychiatry 46, 963–969. McGuffin, P., Farmer, A., Harvey, I., 1991. A polydiagnostic application of operational criteria in studies of psychotic illness. Arch. Gen. Psychiatry 48, 764–770. Minassian, A., Granholm, E., Verney, S., Perry, W., 2005. Visual scanning deficits in schizophrenia and their relationship to executive functioning impairment. Schizophr. Res. 74, 69–79. Norton, D., Stark, I., 1971. Eye movements and visual perception. Sci. Am. 224, 35–43. Pfingstl, M., 2004. Chaos Pro, 3.02 ed: Internet. (http://www.chaospro. de/index.php). Phillips, M.L., David, A.S., 1995. Facial processing in schizophrenia and delusional misidentification: cognitive neuropsychiatric approaches. Schizophr. Res. 17, 109–114. Phillips, M.L., David, A.S., 1997. Visual scan paths are abnormal in deluded schizophrenics. Neuropsychologia 35, 99–105. Phillips, M.L., David, A.S., 1998. Abnormal visual scan paths: a psychophysiological marker of delusions in schizophrenia. Schizophr. Res. 29, 235–245. Ryu, H., Morita, K., Shoji, Y., Waseda, Y., Maeda, H., 2001. Abnormal exploratory eye movements in schizophrenic patients vs healthy subjects. Acta Neurol. Scand. 104, 369–376. Streit, M., Wolwer, W., Gaebel, W., 1997. Facial-affect recognition and visual scanning behaviour in the course of schizophrenia. Schizophr. Res. 24, 311–317. Tatler, B.W., Baddeley, R.J., Gilchrist, I.D., 2005. Visual correlates of fixation selection: effects of scale and time. Vis. Res. 45, 643–659. Walker-Smith, G.J., Gale, A.G., Findlay, J.M., 1977. Eye movement strategies involved in face perception. Perception 6, 313–326. Williams, L.M., Loughland, C.M., Gordon, E., Davidson, D., 1999. Visual scanpaths in schizophrenia: is there a deficit in face recognition? Schizophr. Res. 40, 189–199. Williams, L.M., Loughland, C.M., Green, M.J., Harris, A.W.F., Gordon, E., 2003. Emotion perception in schizophrenia: an eye movement study comparing the effectiveness of risperidone vs. haloperidol. Psychiatry Res. 120, 13–27.
Global visual scanning abnormalities in schizophrenia and bipolar disorder Patricia E.G. Bestelmeyer a,⁎, Benjamin W. Tatler b , Louise H. Phillips a , Gillian Fraser c , Philip J. Benson a , David St.Clair c a
School of Psychology, William Guild Building, University of Aberdeen, Aberdeen, AB24 2UB, UK b Department of Psychology, University of Dundee, Dundee, DD1 4HN, UK c Department of Mental Health, University of Aberdeen, Aberdeen, AB25 2ZD, UK Received 8 March 2006; received in revised form 7 June 2006; accepted 8 June 2006 Available online 24 July 2006
Abstract Visual scanning of face images is widely reported to be abnormal in schizophrenia. This impaired processing has been proposed to be partly responsible for patients' disturbance in social interactions. The present study was designed to determine whether abnormal scanning is specific to images with social content or extends to other types of stimuli. Individuals with schizophrenia (n = 22), bipolar disorder (n = 19) and healthy controls (n = 37) were asked to view a series of 28 images with or without socially important content (i.e. faces, landscapes, fractals and noise patterns) while their eye movements were recorded videooculographically. Temporal and spatial characteristics of scan paths were compared for each patient group and picture type. Independent of image content, patients with schizophrenia exhibited fewer fixations, longer fixation duration, longer saccade duration and peak velocity, and smaller saccade amplitude compared with healthy controls. Patients with schizophrenia and bipolar disorder did not differ significantly from one another on any of the temporal variables recorded. Fixation location distributions of participants with schizophrenia differed significantly from that of healthy controls on all picture types and from patients with bipolar disorder on all but face images. Abnormal scanning in schizophrenia and also bipolar disorder was independent of stimulus type and therefore reflects a global visual scanning impairment not specific to faces. Spatial scanning characteristics but not temporal ones may serve as biomarkers in the functional psychoses. © 2006 Elsevier B.V. All rights reserved. Keywords: Schizophrenia; Bipolar disorder; Eye movements; Scan paths; Trait marker
1. Introduction Visual scan path is a pattern of foveal fixations and voluntary saccades produced when an individual views an image (Norton and Stark, 1971). Scan path abnormalities have been proposed to serve as a trait marker for schizo⁎ Corresponding author. Tel.: +44 1224 273279; fax: +44 1224 273426. E-mail address: [email protected] (P.E.G. Bestelmeyer). 0920-9964/$ - see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2006.06.015
phrenia (Loughland et al., 2002a, 2004; Streit et al., 1997). Diagnosis of schizophrenia is currently symptom based and there are no external markers with which to validate the current diagnostic boundaries. The identification of a robust behavioral marker associated with schizophrenia would be of great benefit. Establishing reliable and valid diagnostic boundaries, especially in the early stage of illness, is essential for properly targeted medicine. So far, most clinical scan path studies have focused on the investigation of eye movements to images of
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social scenes, or most commonly, of faces. Typically, healthy participants tend to fixate salient features of a face such as the eyes, nose or mouth compared to nonsalient features such as the cheek or chin (Walker-Smith et al., 1977). Gordon et al. (1992) were the first to investigate the scan paths of patients with schizophrenia to faces. Patients with schizophrenia were found to make fewer visual fixations and tended to focus less on salient facial features compared to normal controls. Restricted visual scan paths to faces and social scenes have been confirmed repeatedly (Gaebel et al., 1987; Loughland et al., 2002b; Phillips and David, 1997; 1998; Williams et al., 1999) and have been used to explain, at least in part, the social disturbances most individuals with schizophrenia experience (Williams et al., 1999, 2003). Studies have examined whether visual scanning of images without any social content is impaired in schizophrenia and the results are equivocal. For example, Kojima et al. (1992) explored scan path behavior to line drawings and found that patients with schizophrenia compared to healthy controls exhibited fewer visual fixations (see also Ryu et al., 2001 for a similar study and Green et al., 2000 for a comprehensive review of studies using mainly geometric figures). Similarly, Minassian et al. (2005) demonstrated that patients with schizophrenia displayed fewer fixations of longer duration to abstract Rorschach stimuli compared to healthy controls. Minassian et al. (2005) suggested that patients with schizophrenia have a general impairment with regards to visual scanning. However, in contrast to images of faces, Rorschach stimuli and line drawings are neither aesthetically interesting nor biologically important. Therefore increased staring behavior to these abstract pictures may have occurred due to a lack of motivation or disinterest of the patients in the displayed images rather than an actual visual scanning impairment. A selection of image categories of equivalent complexity and/or interest to that of a face may be crucial to determine whether these scanning impairments are global or confined to socially salient stimuli. To our knowledge, only one published study has investigated the specificity of restricted scan paths in patients with schizophrenia to socially salient stimuli by directly comparing the scan paths to an image of a face and the Rey complex figure (Manor et al., 1999). Manor et al. (1999) concluded that in comparison to controls, individuals with schizophrenia have dysfunctional scanning of faces, leading to social deficits. Inspection of their results reveals that overall length of the scan path in response to the face images was significantly
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shorter for patients with schizophrenia as compared to healthy controls. However, there was no statistically significant difference in the number of fixations or fixation duration between the two groups for faces or the Rey figure. In addition, qualitative differences between the group of patients with schizophrenia and the control group were evident to the Rey figure as well as the face image. Other explanations for the overall shorter scan path length to the face image are possible. The novelty of the Rey figure and the fact that this figure was always presented first may have caused patients with schizophrenia to scan more extensively than they would usually do if several of these two categories of stimuli had been presented in a random order. A more serious confound is that the Rey figure subtended a larger visual angle than the face stimulus which may well explain the greater scan path length for the Rey figure compared to the face stimulus. These methodological confounds cast serious doubts on Manor et al.'s (1999) conclusion and the accepted view in the literature that restricted visual scanning in schizophrenia is specific to faces which has been used to partly explain patients' difficulties in social functioning (Loughland et al., 2002a). Furthermore, some preliminary evidence reported by Leonards et al. (2002) suggests that visual scanning abnormalities in patients with schizophrenia extended to non-social stimuli. A thorough investigation of the nature and extent of the scanning impairment in schizophrenia in response to complex social and non-social stimuli is therefore warranted. When analyzing the spatial distribution of fixations to a face, most researchers have divided the image into salient and non-salient facial features. Spatial analysis of visual fixation distributions of objects that do not share the same features has been difficult. One limitation of the studies by Kojima et al. (1992), Manor et al. (1999) and Minassian et al. (2005) is that they have concentrated on variables that describe the temporal characteristics of scan paths rather than their spatial extent. An exploration of the differences in what aspects of an image patients and healthy controls select for fixation when viewing images might reveal insights that are not apparent from the temporal data alone. We therefore extend previous studies by comparing not only temporal but also spatial characteristics of the scan paths. Most current approaches for assessing the spatial similarity between scan paths take the form of nearest saccade metrics, often based upon the sum of squared differences between fixations (e.g. Mannan et al., 1995, 1996, 1997). However, there is no logical reason to
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suggest that fixations 20 degrees apart are twice as different as those 10 degrees apart (or four times if using a squared difference). The technique developed by Tatler et al. (2005) avoids this problem and simply classes fixations within the radius of the fovea as the same, and those beyond the radius of the fovea as different. Tatler et al.'s (2005) technique involves estimating spatial probability distributions of the fixation locations and uses a technique known as the Kullback–Leibler divergence to estimate the difference between these distributions (for a full discussion of the benefits of this metric see Tatler et al., 2005). For scan paths to serve as a useful diagnostic tool for schizophrenia, scanning abnormalities should be present in most, if not all affected individuals. In addition, this abnormality should be specific to schizophrenia and should not be observed in patient groups suffering from other kinds of functional psychoses. An interesting study by Loughland et al. (2002a) has addressed the issue of specificity of visual scanning impairments in schizophrenia by comparing scan paths of patients with schizophrenia to that of a mixed group of patients with affective disorder (i.e. patients with unipolar depression and bipolar disorder). Loughland et al. (2002a) found that the temporal variables of affective disorder patients fell between those of healthy controls and patients with schizophrenia and were significantly different only from those of the participants with schizophrenia but not healthy controls. Loughland et al. (2002a) concluded that the scan path aberrations of affective disorder patients were relatively minor and that more serious scan path abnormalities are specific to schizophrenia. The first aim of the present study was to conduct an extensive investigation to clarify whether abnormal visual scanning behavior in schizophrenia is specific to faces or whether this abnormal scanning can be found to a wider range of image categories. To examine this issue we asked participants to view a series of socially and biologically important stimuli (faces), aesthetically and biologically important images (landscapes), non-biological, aesthetically interesting images (fractals) and complex images which were neither biologically relevant nor aesthetically pleasing (pink noise, i.e. meaningless images with a fog-like appearance). If restricted scanning in schizophrenia is specific to faces, scanning of all but face images should be no different from that of healthy controls. If, however, restricted scanning is specific to evolutionarily important stimuli, restricted scanning should be evident to faces as well as landscapes but not to artificially generated images. Similarly, if restricted scanning in schizophrenia represents a global impairment, scanning
abnormalities should be manifest in all image categories. As well as differences in temporal variables of scan paths, we hypothesized that the spatial distribution of fixations will also differ between participant groups irrespective of image type. The second aim was to investigate whether restricted scan paths are specific to schizophrenia. If scan path aberrations are to serve as a possible trait marker for schizophrenia the scan path variables of the patient group with schizophrenia should differ significantly from healthy controls. The specificity of abnormal scan paths in schizophrenia versus other neuropsychiatric groups should determine not only their potential diagnostic value but could help to address some of the current uncertainties concerning the diagnostic boundaries of schizophrenia versus the affective psychoses (Cardno et al., 2002; Craddock et al., 2005). 2. Methods 2.1. Participants Twenty-two patients with schizophrenia, 19 patients with bipolar disorder and 37 healthy, unmedicated control participants without a family history of mental illnesses took part in the experiment. Patients1 were recruited from the Royal Cornhill Hospital, a psychiatric teaching hospital affiliated with the University of Aberdeen. The study was approved by Grampian Research Ethics Committee and additional permission was granted by the responsible psychiatrist. All participants gave written informed consent. Diagnosis of schizophrenia and bipolar 1 patients was made using The Operational Criteria Checklist (McGuffin et al., 1991) by case note review and clinical interview. DSMIV diagnoses of all patients were confirmed by two experienced clinicians. Group characteristics such as age, gender ratio, education level, and illness duration
1
Nineteen patients with schizophrenia received antipsychotic pharmacologic treatment consisting of a mean daily chlorpromazine (CPZ) equivalent of 313 mg (S.D. = 151.74) (BNF, 2005). Eleven patients with bipolar disorder were on pharmacologic mood stabilizing treatment with a daily mean intake of 890 mg (S.D. = 164.0) of lithium and two patients were on 800 mg of carbamazepine. The remaining bipolar patients were either on antipsychotic treatment alone or received a mixture of mood stabilizing and antipsychotic treatment (1 on 400 CPZ equivalent; 1 on 132 mg CPZ equivalent plus 40 mg of imipramine; 1 on lithium 800 mg plus chlorpromazine 250 mg; 1 on 400 mg of CPZ equivalent plus 600 mg of carbamazepine and 600 mg of lithium; 1 on 800 mg of lithium plus 20 mg of fluoxetine and 1 on 800 of lithium plus 200 mg of chlorpromazine and 400 mg of carbamazepine).
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are listed in Table 1 for all participant groups. Participants were free of any diagnosed neurological disorders and had normal or corrected to normal vision. All patients were in remission at the time of testing. Travel expenses were reimbursed in full for all participants. 2.2. Materials Twenty-eight color photographs of 24-bit 800 × 600 pixels were used. All images except faces subtended a visual area of 34° horizontally and 25° vertically at a viewing distance of 60 cm. Face images subtended a visual area of 19° × 25°. There were seven images in each of the four different categories: faces, landscapes, fractals, and pink noise patterns. The seven facial stimuli were drawn from “The Averaged Karolinska Directed Emotional Faces” CD ROM (Lundqvist and Litton, 1998) and each displayed one of the seven main emotions. Pictures of four emotional expressions were that of a female poser (anger, fear, neutral, sadness) and three stimuli of a male poser (disgust, happiness, surprise). Seven natural scenes depicted landscapes without any man made structures. Seven Mandelbrot and Julia fractals were created using ChaosPro 3.02 (Pfingstl, 2004). Finally, seven different pink noise pictures were used as control stimuli. 2.3. Apparatus Eye movements were recorded using an EyeLink I (SR Research Ltd.) video-based eye tracker which employs infra red pupil tracking to record eye position data at 250 Hz and compensates for minor head movements. Eye movement data were collected monocularly. A 3 × 3 target display was used for calibration of eye position. The same display was used to validate the calibration. Analysis of the recorded eye movement data was conducted off-line using custom made analysis scripts in MATLAB 7 (The MathWorks, Inc.).
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2.4. Procedure Participants were given a free viewing task, i.e. volunteers were asked to view each image presented on a computer screen in any way they liked. In addition, participants were advised to ask for breaks during the experiment whenever necessary. After acquaintance of the participant with the equipment and the initial instructions the head mounted eye tracker was fitted. Eye movement recordings were conducted in a quiet and darkened room. Each of the 28 trials consisted of a central black fixation dot on a grey background followed by the presentation of an image for 5 s after which the display returned to the initial background. After successful calibration and validation of eye movement position each participant was presented with the same pseudo-randomized sequence of images. Visual fixation had to be maintained on the central dot at the start of each trial to be able to trigger the display of the image. The experiment took approximately 15 min to complete. 2.5. Data analysis Saccade detection required a deflection, within a 4 ms period, of greater than 0.1° (degree), with a minimum velocity of 30°/s (degrees per second) and a minimum acceleration of 8500°/s2 (SR Research Ltd.). Fixations were classified as those times in which the eye did not deviate by this amount and a minimum fixation duration of 100 ms was employed (Manor and Gordon, 2003). For each trial temporal and spatial variables were extracted. Temporal scan path variables examined were number of fixations, fixation duration, saccade duration, saccade amplitude, and peak velocity, and were measured separately for each of the four image categories. Eye movement variables were subjected to separate mixed design analyses of variance (ANOVA). In order to consider the spatial properties of visual inspection by the different participant groups, we used an information theoretic measure employed by Tatler et
Table 1 Means and standard deviations (S.D.) of participant demographics Participants
N
Age (years)
Gender
Mean (S.D.)
Male
SZ BP HC
22 19 37
40.8 (12.31) 49.2 (10.63) 37.7 (11.05)
16 7 18
Education (years)
Illness duration (years)
Female
Mean (S.D.)
Mean (S.D.)
6 12 19
11.6 (2.28) 12.4 (2.79) 14.2 (3.60)
Patients with schizophrenia (SZ); patients with bipolar disorder (BP); healthy control participants (HC).
16.3 (11.14) 22.7 (12.44) 0
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al. (2005) and based upon the Kullback–Leibler (KL) divergence. For each image category, we converted the spatial distribution of fixations made by each patient with schizophrenia into probability distributions (using a binning technique with 2° × 2° bins) and then compared the distribution for that patient with distributions created from all other patients with schizophrenia. This KL measure reflects the within-group differences for the participants with schizophrenia. We then compared the fixation distribution from each patient with schizophrenia with the distributions of fixations for participants in the healthy control group and the patient group with bipolar disorder. These two measures reflect the between-group differences in spatial distribution of fixations between the patient group with schizophrenia and each of the other two participant groups. This procedure was repeated for the data of the patients with bipolar disorder. Possible confounding effects of age, level of education, illness duration and gender were examined. Influences of age and level of education were assessed using analysis of covariance and neither co-varied significantly with any of the scan path variables. In addition, there were no significant interactions between gender, diagnosis, and image type on any scan path variables. Relationships between illness duration and scan path variables of patients with schizophrenia and bipolar disorder were calculated but no significant correlations emerged. 3. Results 3.1. Analysis of temporal scan path variables Fig. 1 illustrates representative visual scan paths of one participant from each group on each type of stimulus. Restricted visual scanning was evident for both patient groups compared to controls, across all types of image. Table 2 lists the means and standard deviations for all scan path variables separately for image type and patient group. Table 2 also demonstrates that patients with schizophrenia were most different from healthy controls and that patients with bipolar disorder tended to occupy an intermediate position for all scan path variables. The same pattern for all groups was evident independent of image type. To statistically test whether patients with schizophrenia had a specific impairment for the scanning of faces compared to other stimulus types, mixed design ANOVAs were carried out on each of the five temporal scan path variables, with stimulus type as a repeated measure, and patient group as a between-group factor.
All within-group effects were reported with Greenhouse–Geisser corrections due to the violation of sphericity. Tukey's HSD corrections were applied to post hoc tests. The results of post hoc tests of these mixed design ANOVAs for the patient group are summarized in Table 3. Patient group and stimulus type significantly affected number of fixations (F = 7.54, df = 2, 75, p < 0.001, partial eta squared (pη2) = 0.17 and F = 68.58, df = 2.31, 173.40, p < 0.001, pη2 = 0.48, respectively). Patients with schizophrenia made significantly fewer fixations compared with healthy controls. Patients with bipolar disorder were not significantly different from either patients with schizophrenia or healthy controls. Fewest fixations were made in response to the pink noise pictures compared to all remaining pictures (p < 0.001) and significantly more fixations were made in response to the landscape pictures compared with the fractal patterns (p < 0.001). In support of the hypothesis that scanning abnormalities in schizophrenia apply to both social and non-social stimuli, no interaction was found between patient group and stimulus type (F = 0.59, df = 4.62, 173.40, p > 0.70, pη2 = 0.02). Stimulus type (F = 17.22, df = 1.84, 138.17, p < 0.001, pη2 = 0.19) but not patient group (F = 2.62, df = 2, 75, p > 0.05, pη 2 = 0.07) significantly affected fixation duration. Nevertheless, post hoc tests revealed that patients with schizophrenia have longer fixation durations compared with healthy controls. Patients with bipolar disorder were not significantly different from either patients with schizophrenia or healthy controls. Fixation duration was longest to noise images compared with all other image types (p < 0.001) and longer to fractals than to landscape images. Again, no significant interaction was found between patient group and stimulus type (F = 0.69, df = 3.68, 138.17, p > 0.60, pη2 = 0.02). Saccade duration was significantly affected by patient group (F = 3.96, df = 2, 75, p < 0.05, pη2 = 0.10) and stimulus type (F = 23.02, df = 1.47, 110.02, p < 0.001, pη 2 = 0.24). Patients with schizophrenia exhibited significantly longer saccade durations compared to healthy controls. Patients with bipolar disorder were not significantly different from either patients with schizophrenia or healthy controls. Saccade duration was longest for noise pictures (p < 0.001) and shortest for face images compared to landscapes (p < 0.01) and fractals (p < 0.001). Saccade duration was longer for fractals compared to landscape images (p < 0.05). No significant interaction was obtained between patient group and stimulus type (F = 1.32, df = 2.93, 110.02, p > 0.25, pη2 = 0.03).
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Fig. 1. Representative visual scan paths to each stimulus type for one participant from each of the three groups. Participants who showed close to the average scan path characteristics of their group as listed in Table 2 were chosen; the three participants were matched for age and gender. Diameter of the circles is proportional to fixation duration (ms). Note that the brightness of the landscape and fractal images has been altered to ease presentation of scan paths.
Saccade peak velocity was significantly affected by patient group (F = 6.34, df = 2, 75, p < 0.01, pη2 = 0.15) and stimulus type (F = 72.49, df = 2.46, 184.84, p < 0.001, pη2 = 0.49). Both patient groups had significantly lower peak velocities compared to healthy controls. Furthermore, eye movements reached highest peak velocities for landscape and fractal patterns compared to faces (p < 0.001) and noise images (p < 0.01). Peak velocities were slowest for face images (p < 0.001). A significant interaction for patient group and stimulus type was obtained (F = 3.11, df = 4.92,
184.84, p < 0.05, pη2 = 0.08). Independent samples ttests revealed that the peak velocity of patients with schizophrenia was significantly longer than that of healthy controls in response to landscapes (t = − 2.61, df = 57, p < 0.05), fractals (t = − 3.75, df = 57, p < 0.001), and noise images (t = − 2.16, df = 57, p < 0.05) but not face stimuli (t = − 1.59, df = 57 p = 0.12). Saccade amplitude was significantly affected by patient group ( F = 10.16, df = 2, 75 p < 0.001, pη2 = 0.21) and stimulus type (F = 196.83, df = 2.40, 180.00, p < 0.001, pη 2 = 0.72). Both patient groups
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Table 2 Group means and S.D. for each participant group and image type on all scan path parameters Image type
Landscapes
Fractals
Faces
Noise
Scan path variables
Participant group
Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°) Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°) Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°) Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°)
HC
SZ
BP
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
14.1 (1.95) 285.8 (40.81) 43.3 (9.63) 289.1 (69.41) 5.0 (0.95) 13.1 (3.02) 313.6 (97.82) 46.9 (17.70) 296.6 (84.34) 4.9 (0.84) 13.6 (2.77) 332.0 (93.43) 34.8 (8.12) 200.6 (53.69) 1.9 (0.60) 10.2 (3.55) 439.2 (280.44) 59.3 (47.46) 255.3 (66.55) 4.1 (1.36)
11.7 (3.10) 371.8 (190.95) 50.1 (19.46) 242.9 (59.25) 4.4 (1.12) 9.8 (3.62) 422.7 (188.46) 63.7 (32.91) 221.7 (52.42) 3.6 (0.98) 11.5 (2.94) 378.5 (113.67) 45.2 (21.30) 179.6 (39.99) 1.7 (0.92) 7.3 (3.01) 518.8 (244.85) 88.6 (54.21) 213.9 (78.99) 2.5 (1.44)
12.9 (2.67) 314.7 (75.98) 48.5 (22.34) 241.6 (48.88) 4.2 (1.26) 12.0 (3.76) 352.2 (140.78) 50.2 (22.97) 239.6 (67.70) 3.8 (1.09) 12.7 (2.97) 341.9 (98.03) 42.0 (15.98) 170.6 (35.05) 1.7 (0.75) 9.2 (3.14) 411.9 (154.74) 68.1 (44.24) 217.1 (45.81) 3.0 (1.58)
Healthy control participants (HC); patients with schizophrenia (SZ); patients with bipolar disorder (BP). Duration is measured in milliseconds (ms); saccade peak velocity is measured in degrees per second (°/s); saccade amplitude is measured in pixels per degree (°).
displayed significantly smaller saccade amplitudes than healthy controls. Saccade amplitudes were significantly different for all image types (all at p < p < 0.001) such that largest saccade amplitudes were made to the landscape pictures, then to fractals, after that to faces and smallest amplitudes were made in response to noise images. A significant interaction between patient group and stimulus type was obtained (F = 5.26, df = 4.80, 180.00, p < 0.001, pη 2 = 0.12). Independent samples t-tests revealed that the saccade amplitude of patients with schizophrenia was significantly smaller than that of
Table 3 Summary of Tukey's HSD post hoc analyses between participant groups on the measured scan path variables independent of picture type Scan path variables
HC vs. SZ
HC vs. BP
SZ vs. BP
Number of fixations Fixation duration (ms) Saccade duration (ms) Saccade peak velocity (°/s) Saccade amplitude (°)
⁎⁎⁎ ⁎ ⁎ ⁎⁎ ⁎⁎⁎
n.s. n.s. n.s. ⁎ ⁎⁎
n.s. n.s. n.s. n.s. n.s.
Healthy control participants (HC); patients with schizophrenia (SZ); patients with bipolar disorder (BP). ⁎ p < 0.05; ⁎⁎ p < 0.01; ⁎⁎⁎p < 0.001; n.s. (difference is not significant at the 0.05 level).
healthy controls in response to landscapes (t = − 2.30, df = 57, p < 0.05), fractals (t = − 5.48, df = 57 p < 0.001), and noise images (t = − 4.17, df = 57, p < 0.001) but not face stimuli (t = − 1.11, df = 57, p = 0.27). 3.2. Analysis of spatial scan path variables Tables 4a and 4b lists group differences in visual fixation distribution in terms of Kullback–Leibler (KL) divergence for all picture types for using (a) the patient Table 4a Mean Kullback–Leibler Divergence (bits) and S.D. for the schizophrenia reference group
Landscapes Fractals Faces Noise
SZ–SZ
SZ–BP
SZ–HC
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
3.9 (0.79) 3.8 (0.93) 2.6 (1.01) 3.7 (0.95)
4.3 4.6 2.7 4.9
5.0 (0.76) 5.1 (0.75) 2.8 (1.08) 5.0 (0.71)
(0.72) (0.85) (1.38) (0.99)
SZ–SZ, schizophrenia within-group comparison. SZ–BP, between-group differences for the patients with schizophrenia compared to patients with bipolar disorder. SZ–HC, between-group differences for the patients with schizophrenia compared to the healthy control group.
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group with schizophrenia as the reference and in a separate comparison (b) the patient group bipolar group as the reference group. The KL values show the magnitudes of the differences between distributions of fixations. The exact values in bits are uninformative as they are sensitive to the binning technique used in creating the probability distributions, but the relative differences are informative. For example, in Table 4a, SZ–HC comparisons have higher KL values than do SZ–BP. This shows that there are greater differences between the patients with schizophrenia and healthy controls than there are between patients with schizophrenia and bipolar disorder. A 3 (group) ×4 (stimulus type) ANOVA on the KL divergence of the patients with schizophrenia compared to the two other groups revealed significant main effects of patient group (F = 138.52, df = 1.64, 34.38, p < 0.001, pη2 = 0.87) and picture type (F = 30.31, df = 2.18, 45.84, p < 0.001, pη2 = 0.59). There was also a significant interaction between patient group and picture type (F = 24.13, df = 2.72, 57.19, p < 0.001, pη 2 = 0.54). Planned comparisons using paired t-tests explored these effects. The divergence within schizophrenia patients (SZ–SZ) was significantly smaller than the divergence between patients with schizophrenia and healthy controls (SZ–HC) for landscapes, fractals, noise (p < 0.001) and faces (p < 0.05). Therefore, for all image types, there was greater similarity within the patient group with schizophrenia in terms of eye movement behavior than between the patients with schizophrenia and the healthy controls (Table 4a). The divergence within patients with schizophrenia (SZ–SZ) was significantly smaller than the divergence between Table 4b Mean Kullback–Leibler Divergence (bits) and S.D. for the bipolar disorder reference group BP–BP
Landscapes Fractals Faces Noise
BP–SZ
BP–HC
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
3.5 3.9 1.4 4.1
3.9 4.0 2.4 4.2
4.6 (0.73) 4.7 (0.78) 2.1 (0.72) 4.7 (0.93)
(0.71) (0.89) (0.56) (1.14)
(0.60) (0.79) (0.77) (1.02)
BP–BP, bipolar disorder within-group comparison. BP–SZ, Between-group differences for the patients with bipolar disorder compared to patients with schizophrenia. BP–HC, Between-group differences for the patients with bipolar disorder compared to the healthy control group. Note that the absolute values of the KL divergence reported in this table depend upon the binning technique used when creating the probability distributions (see Methods). The important comparisons are the differences in the KL divergence between the different groups and stimulus types.
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patients with schizophrenia and bipolar disorder (SZ– BP) for landscapes, fractals, and noise (p < 0.001) but not for faces. Therefore, for landscapes, fractals, and noise images, there is greater consistency within the patients with schizophrenia than between the patients with schizophrenia and bipolar disorder. To summarize, in all but the face stimuli, the variation in the spatial distribution of fixations was substantially greater between the schizophrenia and the other two participant groups, than the individual differences among patients with schizophrenia. Consequently, patients with schizophrenia were distributing their fixations differently from the other two groups of observers when viewing these images. A 3 (group) ×4 (stimulus type) ANOVA on the KL divergence of the patients with bipolar disorder compared to the healthy controls and the patients with schizophrenia revealed significant main effects of group (F = 66.16, df = 1.28, 22.98, p < 0.001, pη2 = 0.79) and picture type (F = 63.09, df = 2.23, 40.11, p < 0.001, pη2 = 0.78). There was also a significant interaction between patient group and picture type (F = 23.13, df = 3.79, 68.27, p < 0.001, pη2 = 0.56). Further planned comparisons using paired t-tests explored these effects. The divergence within patients with bipolar disorder (BP–BP) was significantly smaller than the divergence between patients with bipolar disorder and healthy controls (BP–HC) for landscapes, fractals, faces, and noise (all p < 0.001). Therefore, for all image types, there was greater similarity within the eye movement behavior of the patients with bipolar disorder than between the patients with bipolar disorder and the healthy controls (Table 4b). The divergence within the group of patients with bipolar disorder was significantly smaller than between the group of patients with bipolar disorder and schizophrenia (BP–SZ) for landscapes and faces (both p < 0.001) but not for fractals or noise. Therefore, for landscapes, and faces, there is greater consistency within the patients with bipolar disorder than between the patients with bipolar disorder and schizophrenia. 4. Discussion The first aim of this study was to determine whether abnormal visual scanning in schizophrenia is specific to faces or whether it can also be observed to other types of stimuli. The second aim was to investigate whether scanning abnormalities are specific to schizophrenia. For this purpose eye movements of participants with schizophrenia, bipolar disorder and healthy controls were recorded in response to a series of images
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comprising faces, landscapes, fractals, and pink noise patterns. In contrast to healthy controls, scanning abnormalities in the two patient groups were evident independent of image type. The two patient groups were indistinguishable on the basis of temporal scan path variables. However, the fixation distributions of participants with schizophrenia differed significantly from that of healthy controls on all image types and from patients with bipolar disorder on all but face images. Temporal variables of visual scan paths of patients with schizophrenia differed significantly from those of healthy controls. As in previous studies investigating scan paths to faces (Green et al., 2003; Phillips and David, 1997; Streit et al., 1997) the patient group with schizophrenia showed scan path abnormalities such as fewer fixations and a tendency for longer fixation duration compared to healthy controls. Typically, studies of eye movements to faces in schizophrenia have investigated visual scanning while the participants were instructed to identify the displayed emotional expression (e.g. Loughland et al., 2002b, 2004; Phillips and David, 1998). In the current study participants were simply asked to freely view the images. Despite this difference in task instructions we were able to replicate the well-established finding of restricted visual scanning of faces in schizophrenia. However, these group effects were not restricted to faces, and were present in all types of image. There was no evidence to suggest that individuals with schizophrenia were more impaired on socially salient stimuli (i.e. faces) compared to images without social content (landscapes, fractals, noise). Therefore the argument that abnormal visual scanning in schizophrenia is particular to social stimuli such as faces (Loughland et al., 2002a; Manor et al., 1999) is not supported. Instead, the abnormalities seen in schizophrenia are more likely to reflect a global scanning impairment. On most temporal variables (e.g. number of fixation, fixation and saccade duration) the interaction between patient group and image type did not reach statistical significance, indicating that the image content did not differentially change the participants' viewing behavior. Where interactions between group and stimulus type did reach significance (i.e. for saccade amplitude and peak velocity) the direction of effects did not support the theory of specific abnormalities of social processing in patients with schizophrenia. In other words, on these two variables there was no significant difference between healthy controls and patients with schizophrenia on face images, in contrast to significant group differences on the non-social stimuli. This finding can be explained by the overall smaller width of the face
images compared to other images, which covered the entire screen. For example, saccade amplitude to the face stimuli was short in all participants due to less available area to be scanned. In terms of the spatial distribution of fixations, differences between the patients with schizophrenia and healthy controls were greater than the schizophrenia within-group variations on all categories of images. This result can be explained in one of two ways. Firstly, it might be that individuals with schizophrenia were systematically selecting different locations on the image to fixate, from those selected by healthy controls. Secondly, patients with schizophrenia may have been systematically less extensive in their visual exploration of the images, but still have selected a subset of locations fixated by healthy controls. Our measure cannot readily distinguish these two possibilities2 . However, given generally smaller saccade amplitude, increased number of fixations of longer duration and slower overall eye movements (as indicated by lower peak velocity and longer saccade duration) in patients with schizophrenia compared to healthy controls the latter explanation seems more plausible. The example scan paths in Fig. 1 illustrate that members of the two psychiatric samples fixated a subset of locations selected by the healthy group. In contrast to Loughland et al. (2002a), temporal variables from the present study could not confirm a clear-cut difference between patients with schizophrenia and affective disorder. A visual scanning abnormality was evident in the group of patients with schizophrenia and to a lesser extent in the sample of patients with bipolar disorder such that the means of the temporal characteristics of the scan paths fell in between those of the schizophrenia and healthy group, and on none of these measures did patients with schizophrenia or bipolar disorder significantly differ. The proposal that temporal characteristics of visual scan paths may aid in establishing differential diagnosis of psychiatric conditions is not supported by the current data. Our finding adds to the accumulating evidence from other areas such as genetics showing that there is substantial overlap between schizophrenia and bipolar disorder (Bramon and Sham, 2001). Contrary to the current findings, Loughland et al. (2002a) did discover significant differences between 2 It should be noted that none of the current metrics available for quantifying differences between spatial distributions of fixations would be able to distinguish these two possibilities: all require further measures and findings to make inferences about the most likely explanation.
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patients with schizophrenia and affective disorder on temporal scan path measures when viewing faces. However, this apparent difference in results may be due to differences in the samples of affective patients used. The sample recruited by Loughland et al. (2002a) included patients with unipolar depression as well as bipolar disorder, whereas the affective sample in the present study only included patients with bipolar disorder. As the critical diagnostic issue in psychiatry is specifically in distinguishing bipolar disorder from schizophrenia, the current results are more pertinent in exploring the trait specificity of scan path abnormalities. Regarding the spatial distribution of fixations in the present study, differences between patients with bipolar disorder and healthy controls were greater than the within-group differences of the patients with bipolar disorder for all image types. Differences between patients with bipolar disorder and schizophrenia were greater than the within-group variations of the patients with bipolar disorder only on face and landscape images. Tables 4a and 4b demonstrates that the withingroup variations for the patients with schizophrenia were larger than the within-group variations for the patients with bipolar disorder, particularly for face stimuli. In other words, the sample of patients with bipolar disorder showed a more homogeneous spatial distribution of scanning of social stimuli compared to the sample of patients with schizophrenia. This may explain why the schizophrenia within-group variation was significantly different from the bipolar disorder within-group variation on all but face images. The KL divergence technique has shown that spatial differences between groups do exist; yet, the KL measure alone cannot explain where these differences lie. Our findings are interesting since they suggest that analysis of spatial measures of visual scan path may reveal differences within the psychoses not necessarily detectable by temporal measures alone. Larger numbers are required to confirm these novel observations and to determine the overall value of spatial measures as biomarkers for stratifying the functional psychoses. Previous researchers have argued that restricted scanning in schizophrenia indicates abnormal social or emotional processing and suggests a specific deficit in visual scanning of interpersonal information (Phillips and David, 1995; Williams et al., 1999, 2003). The current study provides clear evidence against the idea of socially specific visual abnormalities in schizophrenia (and also bipolar disorder). Abnormal visual scan parameters were found to both social and non-social stimuli, and the scan path abnormalities were no greater to faces compared to other stimuli in both patient
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groups. However, the current results also indicate that restricted scan paths to all types of complex stimuli may impair information processing of all aspects of the environment, with wider implications for cognitive and behavioral function. Contrary to arguments that schizophrenia and affective disorders might show different temporal scan path characteristics (Loughland et al., 2002a) in the current sample no clear difference was found. However, spatial differences in scanning did emerge between the participant groups. Our data highlight an important new direction in the study of visual scan paths as behavioral trait markers. By using information from both spatial and temporal characteristics of scan paths it may be possible to partition schizophrenia and other major psychiatric illnesses along novel lines that are of etiologic and therapeutic value. Acknowledgements We would like to thank all consultants for their help and all participants for generously giving their time to take part in this experiment. Thanks to Larry Cormack for calculating the pink noise images, Victoria Bourne for helpful stats advice and an anonymous reviewer for very constructive comments. We also thank Caroline Crombie, Gillian Fraser and particularly Maggie Sinclair for conducting OPCRITs on patients recruited for another study led by DSC. This research was supported by a grant from GlaxoSmithKline Ltd to DSC and PJB in 2004 (EPI 40256) and an equipment grant to PJB in 2001 from the Royal Society of London (RSRG 22226). PEGB is supported by a PhD studentship sponsored by the University of Aberdeen. References Bramon, E., Sham, P.C., 2001. The common genetic liability between schizophrenia and bipolar disorder: a review. Curr. Psychiatry Rep. 3, 332–337. Cardno, A.G., Rijsdijk, F.V., Sham, P.C., Murray, R.M., McGuffin, P., 2002. A twin study of genetic relationships between psychotic symptoms. Am. J. Psychiatry 159, 539–545. Craddock, N., O'Donovan, M.C., Owen, M.J., 2005. The genetics of schizophrenia and bipolar disorder: dissecting psychosis. J. Med. Genet. 42, 193–204. Gaebel, W., Ulrich, G., Frick, K., 1987. Visuomotor performance of schizophrenic patients and normal controls in a picture viewing task. Biol. Psychiatry 22, 1227–1237. Gordon, E., Coyle, S., Anderson, J., Healy, P., Cordaro, J., Latimer, C., Meares, R., 1992. Eye movement response to a facial stimulus in schizophrenia. Biol. Psychiatry 31, 626–629. Green, M.J., Williams, L.M., Hemsley, D.R., 2000. Cognitive theories of delusion formation: the contribution of visual scanpath research. Cogn. Neuropsychiatry 5, 63–74.
222
P.E.G. Bestelmeyer et al. / Schizophrenia Research 87 (2006) 212–222
Green, M.J., Williams, L.M., Davidson, D., 2003. Visual scanpaths to threat-related faces in deluded schizophrenia. Psychiatry Res. 119, 271–285. Joint Formulary Committee, 2005. British National Formulary, 50 ed. British Medical Association and Royal Pharmaceutical Society of Great Britain, London. Kojima, T., Matsushima, E., Ando, K., Ando, H., Sakurada, M., Ohta, K., Moriya, H., Shimazono, Y., 1992. Exploratory eye-movements and neuropsychological tests in schizophrenic-patients. Schizophr. Bull. 18, 85–94. Leonards, U., Duhoux, S., Rey-Bellet, P., Ibanez, V., Merlo, M., 2002. Do disturbances in social interaction influence visual scene exploration in psychotic patients? Perception 31, 182. Loughland, C.M., Williams, L.M., Gordon, E., 2002a. Schizophrenia and affective disorder show different visual scanning behavior for faces: a trait versus state-based distinction? Biol. Psychiatry 52, 338–348. Loughland, C.M., Williams, L.M., Gordon, E., 2002b. Visual scanpaths to positive and negative facial emotions in an outpatient schizophrenia sample. Schizophr. Res. 55, 159–170. Loughland, C.M., Williams, L.M., Harris, A.W., 2004. Visual scanpath dysfunction in first-degree relatives of schizophrenia probands: evidence for a vulnerability marker? Schizophr. Res. 67, 11–21. Lundqvist, D., Litton, J.-E., 1998. The Averaged Karolinska Directed Emotional Faces- AKDEF. AKDEF CD ROM. Psychology section, Karolinska Institutet, Stockholm. Manor, B.R., Gordon, E., 2003. Defining the temporal threshold for ocular fixation in free-viewing visuocognitive tasks. J. Neurosci. Methods 128, 85–93. Mannan, S.K., Ruddock, K.H., Wooding, D.S., 1995. Automatic control of saccadic eye movements made in visual inspection of briefly presented 2-D images. Spat. Vis. 9, 363–386. Mannan, S.K., Ruddock, K.H., Wooding, D.S., 1996. The relationship between the locations of spatial features and those of fixations made during visual examination of briefly presented images. Spat. Vis. 10, 165–188. Mannan, S.K., Ruddock, K.H., Wooding, D.S., 1997. Fixation patterns made during brief examination of two-dimensional images. Perception 26, 1059–1072. Manor, B.R., Gordon, E., Williams, L.M., Rennie, C.J., Bahramali, H., Latimer, C.R., Barry, R.J., Meares, R.A., 1999. Eye movements
reflect impaired face processing in patients with schizophrenia. Biol. Psychiatry 46, 963–969. McGuffin, P., Farmer, A., Harvey, I., 1991. A polydiagnostic application of operational criteria in studies of psychotic illness. Arch. Gen. Psychiatry 48, 764–770. Minassian, A., Granholm, E., Verney, S., Perry, W., 2005. Visual scanning deficits in schizophrenia and their relationship to executive functioning impairment. Schizophr. Res. 74, 69–79. Norton, D., Stark, I., 1971. Eye movements and visual perception. Sci. Am. 224, 35–43. Pfingstl, M., 2004. Chaos Pro, 3.02 ed: Internet. (http://www.chaospro. de/index.php). Phillips, M.L., David, A.S., 1995. Facial processing in schizophrenia and delusional misidentification: cognitive neuropsychiatric approaches. Schizophr. Res. 17, 109–114. Phillips, M.L., David, A.S., 1997. Visual scan paths are abnormal in deluded schizophrenics. Neuropsychologia 35, 99–105. Phillips, M.L., David, A.S., 1998. Abnormal visual scan paths: a psychophysiological marker of delusions in schizophrenia. Schizophr. Res. 29, 235–245. Ryu, H., Morita, K., Shoji, Y., Waseda, Y., Maeda, H., 2001. Abnormal exploratory eye movements in schizophrenic patients vs healthy subjects. Acta Neurol. Scand. 104, 369–376. Streit, M., Wolwer, W., Gaebel, W., 1997. Facial-affect recognition and visual scanning behaviour in the course of schizophrenia. Schizophr. Res. 24, 311–317. Tatler, B.W., Baddeley, R.J., Gilchrist, I.D., 2005. Visual correlates of fixation selection: effects of scale and time. Vis. Res. 45, 643–659. Walker-Smith, G.J., Gale, A.G., Findlay, J.M., 1977. Eye movement strategies involved in face perception. Perception 6, 313–326. Williams, L.M., Loughland, C.M., Gordon, E., Davidson, D., 1999. Visual scanpaths in schizophrenia: is there a deficit in face recognition? Schizophr. Res. 40, 189–199. Williams, L.M., Loughland, C.M., Green, M.J., Harris, A.W.F., Gordon, E., 2003. Emotion perception in schizophrenia: an eye movement study comparing the effectiveness of risperidone vs. haloperidol. Psychiatry Res. 120, 13–27.