A preferential increase in the extrastriate response to signals of danger

NeuroImage 19 (2003) 1317–1328

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A preferential increase in the extrastriate response to signals of danger Simon A. Surguladze,a,* Michael J. Brammer,b Andrew W. Young,c Christopher Andrew,d Michael J. Travis,e Steven C.R. Williams,d and Mary L. Phillipsa a

Section of Neuroscience and Emotion, Division of Psychological Medicine, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK b Brain Image Analysis Unit, Division of Psychological Medicine, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK c Department of Psychology, University of York, Heslington, York, YO10 5DD, UK d Neuroimaging Research Group, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK e Section of Clinical Neuropharmacology, Division of Psychological Medicine, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK Received 5 August 2002; accepted 23 January 2003

Abstract This study examined neural responses in nine right-handed healthy individuals while they viewed mild and intense expressions of four emotions (fear, disgust, happiness, and sadness) contrasted with neutral faces in four event-related functional magnetic resonance imaging experiments. Orthogonal polynomial trend analysis revealed a significant linear increase in the fusiform extrastriate cortical response to increasing intensities of all four emotional expressions, which was significantly greater to increasing intensities of fear and disgust than happiness and sadness, and a significant linear decrease in response to sadness in another extrastriate region. The amygdala was activated by high-intensity fearful expressions, consistent with findings from previous studies, and by low- but not high-intensity sad expressions. Significant linear increases in response to increasing intensities of fear, disgust, and happiness occurred within the hippocampus, anterior insula, and putamen, respectively. Conversely, significant linear decreases in hippocampal and putamen responses occurred to increasing intensities of sadness. We provide the first demonstration of differential increases in extrastriate and limbic responses to signals of increasing danger than to those of other emotions, and significant decreases in these responses to signals of increasing sadness in others. We suggest that this differential pattern of response to different categories of emotional signals allows the preferential direction of visual attention to signals of imminent danger than to other, less-salient emotional stimuli. © 2003 Elsevier Science (USA). All rights reserved.

Introduction Critical to survival is the ability to identify environmental danger (Darwin, 1872/1998). Recognition of facial expressions signalling danger (e.g., fear and disgust) allows this to be performed rapidly and efficiently (Darwin, 1872/ 1998; LeDoux, 2000), with facial expressions of fear having evolved to signal the presence of imminent threat, and those of disgust, to enable the avoidance of ingestion of harmful substances (Rozin et al., 1994). Furthermore, while the circumstances in which it is appropriate or inappropriate to display emotion, i.e., display rules (Ekman, 1972), may vary widely across individuals, characteristics of specific facial

* Corresponding author. King’s College Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK. Fax: ⫹44-207848-0379. E-mail address: [email protected] (S.A. Surguladze).

expressions do not differ significantly across different cultures. Facial expressions therefore act as easily identifiable signals of the presence of important environmental events, including imminent danger. The relative importance to survival of the identification of happy or sad facial expressions may be less important as these do not act as signals of immediate danger. Neurophysiological studies of nonhuman primates have indicated that happy facial expressions may act as positive reinforcers of appropriate behaviours (Rolls, 1999), while other studies have suggested that recognition of sad facial expressions is associated with the control of aggression and the elicitation of prosocial behaviour (Eisenberg et al., 1989), or the development of empathy and moral socialisation (Blair and Frith 2000). These findings remain to be clarified, however. Previous studies have demonstrated greater activation in extrastriate cortex to fearful compared with neutral faces,

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specifically within the fusiform gyrus, an extrasriate cortical region implicated in face processing (Haxby et al., 2000; Morris et al., 1998; Vuilleumier et al., 2001). Additionally, in response to visual presentations of different types of emotional compared with nonemotional scene, greater activation within these visual regions have been reported (Reiman et al., 1997; Lane et al., 1997, 1999), irrespective of the perceptual complexity of the stimuli (Taylor et al., 2000; Junghoefer et al., 2001) or eye movements in response to these (Lang et al., 1998). The detection of emotional stimuli, and, in particular, those signalling danger, leads to an alteration of priorities and subsequent behaviours, and is necessarily followed by altered thresholds for the detection of other sources of threat and enhanced vigilance to such signals. Modulation of extrastriate cortical responses may therefore form a crucial component of a neural system able to achieve this, and may be mediated via the amygdala (Morris et al., 1998; Davis and Whalen, 2001), potentially via reentrant projections from the amygdala back to visual cortex (Amaral et al., 1992), although the degree to which this occurs for different types of emotional stimuli remains to be clarified. To date, these studies have indicated increased extrastriate cortical responses predominantly within the fusiform gyrus to facial expressions of fear compared with neutral expressions. No study, however, has compared changes in the extrastriate cortical response to different categories of negative and positive emotional and neutral facial expressions. The extent to which the increase in the extrastriate cortical response to emotional compared with neutral stimuli reflects the requirement for increased visual attention to nonneutral stimuli per se, or a preferential response to signals of environmental danger compared with other, nonneutral stimuli, is therefore unclear. Furthermore, although several previous studies have highlighted the role of the amygdala in the response to facial expressions of fear (Breiter et al., 1996; Morris et al., 1996; Phillips et al., 1997; Sprengelmeyer et al., 1998; Calder et al., 2001), findings regarding the role of this structure in the response to facial expressions of other emotions are less consistent (e.g., Breiter et al., 1996; Schneider et al., 1997; Blair et al., 1999; Critchley et al., 2000), with studies indicating that the anterior insula, rather than the amygdala, may have a more prominent role in the response to facial expressions of disgust (e.g., Phillips et al., 1997; Sprengelmeyer et al., 1998). We examined neural responses to increasing intensities of facial expressions signalling danger, those of fear and disgust, and those signalling other emotions, happiness and sadness. We employed a standardised series of facial expressions (Young et al., 2002) depicting these four emotions at different intensities, and used event-related functional magnetic resonance imaging (fMRI) and a novel method of orthogonal polynomial trend analysis to study this. We reasoned that the ability to detect and direct attention to signals of danger is of greater value to survival than the

detection of other nonneutral stimuli. We therefore predicted significantly greater linear increases in neural response within extrastriate cortex, and in particular, the fusiform gyrus, to increasing intensities of expressions of fear and disgust, than to increasing intensities of expressions of either happiness or sadness. We also predicted linear increases in response in the amygdala to increasing intensities of fearful expressions, and within the anterior insula to increasing intensities of expressions of disgust, but were unable to make specific predictions regarding the responses in these regions to increasing intensities of happiness or sadness.

Materials and methods Subjects Nine, right-handed healthy volunteers (4 female) with no history of psychiatric disorder, traumatic brain injury, or recent substance abuse (mean age, 39.6 years; range, 23– 63 years; mean years of education, 14.6; range, 11–19) participated in the study. All subjects had normal or correctedto-normal vision. Written informed consent was obtained from all participants. The protocol was approved by the Research Ethics Committees of the South London and Maudsley Trust and Institute of Psychiatry. Imaging study Procedure Subjects participated in four 6-min experiments employing event-related fMRI. In each experiment, subjects were presented with 10 different facial identities expressing 50% and 100% intensities of one emotion (either sadness, happiness, disgust, or fear), in addition to a neutral expression. Each facial stimulus was presented for 2 s. During the interstimulus interval, the duration of which was varied from 3 to 8 s according to a Poisson distribution with average interval 4.9 s, subjects viewed a fixation cross (Fig. 1). Previous studies have demonstrated that neural responses to emotional stimuli are dependent upon the nature of the task performed during viewing of the stimuli, and that while performance of explicit, emotion labelling tasks is associated with reduced limbic and increased middle temporal and prefrontal activation (e.g., Critchley et al., 2000; Lange et al., 2003), an implicit (sex decision) task is reliably associated with responses in limbic and extrastriate cortical regions (Morris et al., 1996; Phillips et al., 1997). Subjects in this study were requested to decide upon the sex of each face and press one of two buttons accordingly with the right thumb. All subjects in this study were able to identify the sex of the faces correctly. After scanning, subjects participated in a facial emotion recognition task in which they viewed 10 different identities displaying facial expressions of happiness, sadness, fear,

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Fig. 1. The design of each of the four experiments was as depicted above. Subjects viewed mild (50%) and severe (100%) intensities of facial expressions, together with neutral expressions. This example depicts happy expressions. Visual stimuli were projected on the screen in a randomised order, and each stimulus was presented for 2 s. A Poisson distribution allowed the interstimulus interval, during which subjects viewed a fixation cross, to vary between 3 and 8 s. Subjects judged the sex of the face and pressed one of two buttons accordingly.

and disgust from a standardised series (Young et al., 2002) manipulated with computer software to depict different intensities (25%, 50%, and 100%) of emotion, in addition to 100% neutral expressions. The emotional stimuli were presented in two separate computerised tasks. In one task, subjects viewed neutral, and the three different intensities of happy and sad facial expressions, and in another task, neutral, and the three different intensities of fearful and disgusted facial expressions. We report on the data where each emotional expression was presented for 2000 ms and at three different intensities in a randomised order; 10 neutral faces were presented for 2000 ms. In each emotion recognition task, 70 stimuli in total were presented with an interstimulus interval of 2000 ms, during the last 500 ms of which was presented a fixation cross. Subjects were requested to decide upon the emotion depicted in each face by choosing one of three emotion labels (happy, sad, or neutral, in one experiment, or fear, disgust, and neutral in another) and moving a computer joystick accordingly. All subjects participated in both behavioural tasks. The order of experiments was randomised across subjects. Acquisition Gradient echo echoplanar imaging (EPI) data were acquired on a GE Signa 1.5-T system (General Electric, Milwaukee WI, USA) at the Maudsley Hospital, London. A quadrature birdcage headcoil was used for Radio Frequency (RF) transmission and reception; 180 T2*-weighted images depicting Blood Oxygenation Level Dependent (BOLD)

contrast (Kwong et al., 1992) were acquired over 6.02 min (for each task) at each of 16 near-axial noncontiguous 7-mm-thick planes parallel to the intercommissural (AC-PC) line: TE 40 ms, TR 2 s, in-plane resolution 3.44 mm, interslice gap 0.7 mm, flip angle 70 degrees, matrix size 64 ⫻ 64, field of view (FOV) 24 cm. In the same scanning session a high-resolution EPI dataset was acquired with 2 pulse sequences, gradient echo EPI and spin echo EPI. The structural images were acquired at 43 near-axial 3-mm-thick planes parallel to the AC-PC line: TE 73 ms, TI 180 ms, TR 16 s, in-plane resolution 1.72 mm, interslice gap 0.3 mm, matrix size 128 ⫻ 128 ⫻ 43; FOV 24 cm. This higher resolution EPI dataset provided whole brain coverage and was later used to register the fMRI datasets acquired from each individual in standard stereotactic space. Prior to each imaging run, four dummy scans were acquired to reach equilibrium magnetization. An autoshimming routine was used on each run. Analysis Generic brain activation mapping. Prior to time-series analysis, data were processed to remove low-frequency signal changes and motion-related artefacts (Bullmore et al., 1999a). The responses at each voxel were then analysed by regressing the corrected time-series data on a linear model produced by convolving each contrast vector to be studied with two Poisson functions parameterising haemodynamic delays of 4 and 8 s (Bullmore et al., 2001). Following least squares fitting of this model, a goodness of fit statistic (sum

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of square ratio, SSQ) composed of the ratio of model to residual sum of squares was calculated (Edgington, 1995) for each contrast. The distribution of the same statistics under the null hypothesis of no experimental effect were then calculated by wavelet-based resampling of the timeseries at each voxel and refitting the models to the resampled data (Bullmore et al., 2001). An experimentally derived null distribution of the goodness of fit statistic was then derived by following this procedure 10 times at each intracerebral voxel and combining the resulting data. This method has been shown to give excellent control of nominal type I error rates in fMRI data from a variety of scanners. Activations for any contrast at any required P value can then be determined by obtaining the appropriate critical values from the null distribution (see Bullmore et al., 1996). Generic group activation maps were constructed by mapping the observed and randomised test statistics for each individual into the standard stereotactic space (Talairach and Tournoux, 1988) and computing and testing median activation maps as previously described (Brammer et al., 1997). Trend analysis. Three different levels (neutral faces, 50% intensity of emotion, and 100% of intensity) of stimulation were presented, in a randomised order and contrasted with a fixed background (fixation cross). Maps of the ratios of the model to residual sum of squares (SSQ ratio) were calculated for each of the three stimulation levels for each individual and transformed into standard space. These standard space maps were then analysed by fitting orthogonal linear and quadratic trends at each voxel for all individuals at the three levels of stimulation (orthogonal polynomial trend analysis). Given that there were only three different levels of expression intensity (0, or 100% neutral, 50% and 100% of emotion, each compared with the baseline fixation cross condition), we decided to analyse only linear trends of cortical activation rather than any other higher order relationships, e.g., quadratic trends. Null distributions of each trend were constructed by systematic permutation of the data at each voxel and the voxel-wise probability of each trend calculated with reference to these distributions (see Edgington, 1995). Analysis at cluster level was also performed by using the methods described in detail by Bullmore et al. (1999b). Essentially this involved first thresholding at a voxel-wise probability of false activation of 0.05, combining all 3D contiguous activated voxels into clusters and then assessing the probability of occurrence of clusters under the null hypothesis by reference the distributions produced when the “null” data produced by time-series permutation (Bullmore et al., 1996) were similarly analysed. At a cluster-wise probability of false activation of 0.01 in this series of experiments, the expected number of false positive activations over the whole of standard space was 1. Comparison of trends. To assess the significance of differences in linear trends in neural response between pairs of

experiments, the voxel-wise estimates of trend in each individual in the two experiments were fitted to a linear model of the form Y ij ⫽ a 0 ⫹ a 1G ij ⫹ e ij where y is the observed trend for the ith individual in the jth experiment, G is a classification variable describing the experiment (1 for the first experiment ⫺ 1 for the second), and e is the random error in the trend in the ith individual in the jth experiment. a0 and a1 are the regression parameters obtained from the fitting process. The null distribution of the regression slope (a1) was obtained by systematic data permutation between the two experiments (to produce all possible rearrangements of the data except the original, or a random subset of these with large groups sizes) and refitting the model. Following computation of the observed and null distributions of the regression slope, the voxel and clusterwise significance of differences in trend between the experiment were obtained by the analysis methods described above (Bullmore et al., 1999b). Postscanning facial expression recognition task. Accuracy for facial expression recognition (Pr) was determined for each emotion, using two-high threshold theory (Corwin, 1994). Using this method, the ability to discriminate between a specific emotional expression (e.g., a fearful facial expression) and the distractor (a neutral facial expression) can be calculated by subtracting the false positive score rate from the correct response rate. The data derived from such a transformation could be considered as reflecting percentage of correct responses (actually, percentage correct is a linear transformation of Pr). The use of the mean discrimination rates for emotional versus neutral facial expressions from each of the two recognition tasks allowed the data for the four different emotions to be comparable across the two tasks.

Results Generic brain activation maps Neutral facial expressions versus fixation cross Major regions of generic brain activation elicited by the contrast of neutral faces versus the fixation cross in each of the four experimental tasks included similar regions within extrastriate cortex, i.e., bilateral fusiform (BA 19/37) and lingual gyri (BA18), in addition to dorsomedial frontal cortex (BA 6). Cluster-level analyses of variance (ANOVAs) revealed no significant difference among the four experimental conditions (P ⫽ 0.01) in generic activation during the neutral fixation cross contrasts. We then examined major regions of generic activation to contrasts of high- and low-intensity emotional expression versus neutral faces for each of the four emotions.

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Table 1 Generic brain activation to facial expressions of high- and low-intensity fear compared with neutral facesa Brain region

Size

50% fear vs. neutral faces Fusiform gyrus (19/37) 100% fear vs. neutral faces Fusiform gyrus (37) Precuneus (7) Ventromedial prefrontal cortex (10) Amygdala

x

y

z

SSQ

P

16

36

⫺43

⫺18

0.0439

0.001603

100 31 13 13 4

⫺47 32 ⫺25 7 ⫺15

⫺50 ⫺46 ⫺43 46 ⫺7

⫺18 ⫺18 53 ⫺7 ⫺13

0.0341 0.0457 0.0411 0.0345 0.0325

0.001651 0.000216 0.000474 0.001525 0.002179

a The cluster with the largest number of voxels within each region is reported. Talairach coordinates refer to the voxel with the maximum sum of square ratio (SSQ) in each cluster. All such voxels were identified by a one-tailed test of the null hypothesis that median standardised power is not determined by experimental design. The probability threshold, P, for activation in each cluster is also demonstrated.

Generic brain activation to facial expressions of highand low-intensity fear compared with neutral faces Both intensities of expressions of fear contrasted with neutral facial expressions activated the right fusiform gyrus (BA 37/19). High-intensity fearful expressions also activated left-sided extrastriate cortical regions (fusiform gyrus, BA 37, and precuneus, BA 7), the right ventromedial prefrontal cortex (BA 10), and the left amygdala (Table 1). Generic brain activation to facial expressions of highand low-intensity disgust compared with neutral faces Both intensities of expressions of disgust contrasted with neutral facial expressions, activated bilateral fusiform gyri (BA 19/37). High-intensity expressions of disgust also activated the left posterior cingulate gyrus (BA 31; Table 2). Generic brain activation to facial expressions of highand low-intensity happiness compared with neutral faces Both intensities of expressions of happiness contrasted with neutral facial expressions activated the left fusiform gyrus (BA 19) and the right superior frontal gyrus (BA 8). Low-intensity happy expressions also activated the left posterior cingulate gyrus (BA 30), and high-intensity expressions, the right posterior cingulate gyrus (BA 31; Table 3). Generic brain activation to facial expressions of highand low-intensity sadness compared with neutral faces Low-intensity expressions of sadness contrasted with neutral facial expressions activated the left fusiform gyrus

(BA 19), bilateral posterior cingulate gyri (BA 30), the right inferior frontal gyrus (BA 47), the right thalamus and right amygdala. Postcentral gyrus (BA 40) and dorsomedial frontal gyrus (BA 6) were activated by high-intensity expressions of sadness (Table 4). Linear trend analysis Expressions of fear Cluster-wise analyses of linear increases in activation associated with increasing intensity of emotional facial expression from neutral to 50% and to 100% fear vs. fixation cross revealed significant linear increases in activation predominantly within bilateral extrastriate cortical regions (fusiform gyri, BA 37/19; x ⫽ ⫺36; y ⫽ ⫺70; z ⫽ ⫺7, and x ⫽ 36; y ⫽ ⫺59; z ⫽ ⫺13) and dorsomedial frontal gyrus (BA 6; x ⫽ 0; y ⫽ ⫺18; z ⫽ 53), P ⫽ 0.01; number of activated clusters ⫽ 13; expected number of false positive clusters ⫽ 1. Voxel-wise analysis revealed similar significant linear increases in activation, and additionally within the hippocampus (x ⫽ 18; y ⫽ ⫺30; z ⫽ ⫺13; P ⫽ 0.007) (Fig. 2A). Expressions of disgust Cluster-wise analyses of linear increases in activation associated with increasing intensity of emotional facial expression from neutral to 50% and to 100% disgust vs. fixation cross revealed significant linear increases in activa-

Table 2 Generic brain activation to facial expressions of high- and low-intensity disgust compared with neutral facesa Brain region 50% disgust vs. neutral faces Fusiform gyrus (37) 100% disgust vs. neutral faces Fusiform gyrus (19/37) Posterior cingulate gyrus (23) a

Legend as for Table 1.

Size

x

y

z

SSQ

P

7 6

⫺36 40

⫺50 ⫺50

⫺13 ⫺18

0.0484 0.0701

0.000523 0.000018

39 27 17

⫺40 40 ⫺7

⫺46 ⫺50 ⫺52

⫺13 ⫺18 15

0.0340 0.0475 0.0460

0.001411 0.000140 0.000164

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Table 3 Generic brain activation to facial expressions of high- and low-intensity happiness compared with neutral facesa Brain region 50% happy vs. neutral faces Fusiform gyrus (19) Posterior cingulate gyrus (30) Superior frontal gyrus (8) 100% happy vs. neutral Fusiform gyrus (19) Posterior cingulate gyrus (31) Superior frontal gyrus (8) a

Size

x

y

z

SSQ

P

25 19 11

⫺40 ⫺7 17

⫺60 ⫺43 33

⫺7 15 42

0.03637 0.0331 0.03890

0.000748 0.001418 0.000519

17 11 5

⫺40 7 11

⫺67 ⫺46 33

⫺7 26 48

0.0531 0.0308 0.0273

0.000012 0.001334 0.002686

Legend as for Table 1.

tion predominantly within bilateral extrastriate cortical regions (bilateral fusiform gyri, BA 18/37; x ⫽ ⫺35; y ⫽ ⫺66; z ⫽ ⫺11, and x ⫽ 40; y ⫽ ⫺60; z ⫽ ⫺18) and inferior occipital gyri (BA 18; x ⫽ ⫺36; y ⫽ ⫺82; z ⫽ ⫺7, and x ⫽ 32; y ⫽ ⫺78; z ⫽ ⫺2), P ⫽ 0.01; number of activated clusters ⫽ 10; expected number of false positive clusters ⫽ 1. Voxel-wise analysis revealed similar significant linear increases in activation and additionally within bilateral anterior insulae (x ⫽ 36; y ⫽ 23; z ⫽ 4, and x ⫽ ⫺36; y ⫽ 23; z ⫽ ⫺2), P ⫽ 0.05 (Fig. 2B). Expressions of happiness Cluster-wise analyses of linear increases in activation associated with increasing intensity of emotional facial expression from neutral to 50% and to 100% happiness vs. fixation cross revealed significant linear increases in activation predominantly within bilateral extrastriate cortical regions (bilateral fusiform gyri, BA 19/37; x ⫽ ⫺36; y ⫽ ⫺65; z ⫽ ⫺7, and x ⫽ 40; y ⫽ ⫺65; z ⫽ ⫺12), the left inferior occipital gyrus (BA 18; x ⫽ ⫺29; y ⫽ ⫺85; z ⫽ ⫺2), and the right putamen (x ⫽ 23; y ⫽ 4; z ⫽ ⫺12), P ⫽ 0.01; number of activated clusters ⫽ 17; expected number of false positive clusters ⫽ 1 (Fig. 2C). Results of the voxel-wise analysis did not differ from those of the clusterwise approach. Expressions of sadness Cluster-wise analyses of linear increases in activation associated with increasing intensity of emotional facial ex-

pression from neutral to 50% and to 100% sadness vs. fixation cross revealed significant linear increases in activation within right extrastriate cortex (right fusiform gyrus, BA 19; x ⫽ 36; y ⫽ ⫺67; z ⫽ ⫺13), left posterior inferior temporal cortex (BA 37; x ⫽ ⫺40; y ⫽ ⫺62; z ⫽ ⫺12), and bilateral dorsomedial frontal gyri (BA 6; x ⫽ 0; y ⫽ ⫺17; z ⫽ 53). Significant linear decreases in activation were demonstrated within bilateral extrastriate cortical regions (bilateral cuneus, BA 17; x ⫽ ⫺4; y ⫽ ⫺89; z ⫽ 9, and x ⫽ 4; y ⫽ ⫺89; z ⫽ 4) and hippocampus (x ⫽ ⫺14; y ⫽ ⫺37; z ⫽ ⫺7), P ⫽ 0.01; number of activated clusters ⫽ 19; expected number of false positive clusters ⫽ 1. Voxelwise analysis revealed similar linear trends in activation, and a significant linear decrease additionally within the putamen (x ⫽ ⫺22; y ⫽ 7; z ⫽ ⫺7; P ⫽ 0.01) (Fig. 2D). Comparison of significant linear trends in activation across the four experimental conditions Linear increases in activation were significantly greater (P ⫽ 0.01) to increasing intensities of expressions of fear compared with those of happiness, or sadness, within bilateral fusiform gyri (BA 37) (Fig. 3A). Linear increases in activation were greater to increasing intensities of expressions of disgust compared with those of happiness, and sadness, within the right fusiform gyrus (BA 37) (Fig. 3B). There was no significant difference in the magnitude of the linear increase in activation within these regions to increasing intensities of expressions of fear compared with expres-

Table 4 Generic brain activation to facial expressions of high- and low-intensity sadness compared with neutral facesa Brain region 50% sad vs. neutral Inferior frontal gyrus (47) Posterior cingulate gyrus (30) Fusiform gyrus (19) Thalamus Amygdala 100% sad vs. neutral Postcentral gyrus (40) Dorsomedial frontal gyrus (6) a

Legend as for Table 1.

Size

x

y

z

SSQ

P

10 10 7 8 5

21 0 ⫺32 7 15

13 ⫺52 ⫺69 ⫺20 0

⫺13 20 ⫺13 15 ⫺18

0.0407 0.0540 0.0432 0.0518 0.0441

0.001723 0.000223 0.001163 0.000325 0.001006

8 5

⫺53 0

⫺17 ⫺10

20 53

0.0321 0.0391

0.001284 0.000289

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sions of disgust, or to increasing intensities of expressions of sadness compared with expressions of happiness. Facial expression recognition The mean discrimination scores for each of the four emotions were as follows: happy 0.59, disgusted 0.46, fearful 0.39, and sad 0.38, the maximal possible rate of discrimination approaching 1.0. The derived rates were analysed with repeated-measures ANOVA for one within-subject factor: emotion, and adjusted for multiple comparisons (Bonferroni correction). There was a significant main effect of emotion (F[3,24] ⫽ 10.364; P ⬍ 0.001). Pairwise comparisons (with Bonferroni corrections) demonstrated different degrees of accuracy in the discrimination of happy faces compared with the discrimination of fearful and sad faces. The difference in discrimination of happy compared with sad faces was significant within a 95% confidence interval (0.068; 0.359), P ⫽ 0.005, and with fearful faces, within a 95% confidence interval (0.089; 0.329), P ⫽ 0.002. The discrimination scores for the happy and disgusted faces did not differ significantly. Thus, happy expressions were discriminated most accurately from neutral expressions, followed by expressions of disgust, fear, and sadness.

Discussion Survival is dependent upon the accurate detection of salient and emotive environmental stimuli, particularly those signalling danger. Previous reports have demonstrated increased activity within extrastriate cortical regions to emotional compared with neutral faces and scenes (Junghoefer et al., 2001; Lane et al., 1997; 1999; Morris et al., 1998). Modulation of the extrastriate cortical response may therefore be a vital component of a neural system able to detect and respond to emotionally salient information, but it remains unclear as to whether this system responds preferentially to signals of danger, or indiscriminately to nonneutral stimuli per se. We report findings from the first study comparing the magnitude of the extrastriate cortical response to signals of increasing danger, facial expressions of increasing intensity of fear and disgust, with the response to signals of other negative and positive emotions, facial expressions of increasing intensity of sadness and happiness. Using an event-related fMRI paradigm, we demonstrated in response to facial expressions of high and low intensity of fear, disgust, and happiness, and to facial expressions of low-intensity sadness contrasted with neutral facial expressions, activation within the fusiform gyrus, an extrastriate cortical region important for facial and object processing (Haxby et al., 1994; 2000; Puce et al., 1995; 1996; Kanwisher et al., 1997). We then employed a novel method of orthogonal polynomial trend analysis to determine the effect of increasing intensity of emotional facial expression upon the magnitude of the extrastriate cortical response to these

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expressions. While we demonstrated a significant linear increase in the extrastriate cortical response to expressions of increasing intensity of fear, disgust, and happiness within bilateral fusiform gyri, a significant linear decrease in the extrastriate cortical response in bilateral cuneus occurred to expressions of increasing intensity of sadness. These negative trends in response to sad expressions may partially explain findings of previous studies of little or no activation to sad faces (Phillips et al., 1998; Kesler/West et al., 2001). Furthermore, comparison of the magnitude of the linear increases in neural response to facial expressions of the four different emotions revealed significantly greater linear increases in the extrastriate cortical response, predominantly within bilateral fusiform gyri, to increasing intensities of expressions of fear than to those of happiness, or sadness, and a significantly greater linear increase in the extrastriate cortical response within the right fusiform gyrus to increasing intensities of disgust than to those of happiness, or sadness. The latter finding may reflect the relatively greater importance of the right hemisphere in the processing of emotions, and particularly negative emotions (Adolphs et al., 1996; Davidson and Irwin, 1999). We predicted linear increases in the amygdalar response to increasing intensities of fearful expressions, and within the anterior insula to increasing intensities of expressions of disgust. Consistent with these predictions, activation within the amygdala occurred to expressions of high- but not lowintensity fear compared with neutral expressions, and a significant linear increase in the anterior insular response occurred to expressions of increasing intensity of disgust. Contrary to our predictions, a significant linear increase in the hippocampal but not the amygdalar response was observed to expressions of increasing intensity of fear. Activation within the hippocampus has been demonstrated previously to fearful sounds (Phillips et al., 1998) and to fearful facial expressions (Williams et al., 2001). Interestingly, in the latter study, activation within the hippocampus to fearful facial expressions was not associated with autonomic arousal, as measured by the skin conductance response, while activation within the amygdala to these facial expressions was accompanied by this autonomic response. These findings suggest dissociable roles for the amygdala and hippocampus in processing the content and context, respectively, of fear. The findings in the current study further suggest that while this hippocampal response to facial expressions may be linear, reflecting a linear increase in the fearful context (the intensity of fear displayed in the face), the amygdalar response is nonlinear, reflecting a nonlinear increase in the arousal response to high- vs. low-intensity fearful expressions. A significant linear increase in the putamen response to expressions of increasing intensity of happiness was observed. This is consistent with the results of previous studies examining neural responses to happy facial expressions (Phillips et al., 1998) or emotionally pleasant pictures (Canli et al., 2001). Other studies have highlighted the role of the

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Fig. 3. Comparison of trends. (A) Significant differences (P ⫽ 0.01) between the linear increases in activation when subjects viewed increasing intensities of facial expressions of fear compared with those of happiness, and sadness, were demonstrated within bilateral fusiform gyri, BA 37 (x ⫽ ⫺40; y ⫽ ⫺63; z ⫽ ⫺15, and x ⫽ 36; y ⫽ ⫺57; z ⫽ ⫺17) and (x ⫽ ⫺40; y ⫽ ⫺63; z ⫽ ⫺14, and x ⫽ 37; y ⫽ ⫺58; z ⫽ ⫺17), respectively, and are displayed on transverse and coronal brain slices with corresponding z and y coordinates. (B) Significant differences (P ⫽ 0.01) between the linear increases in activation when subjects viewed increasing intensities of facial expressions of disgust compared with those of happiness, and sadness, were demonstrated within the right fusiform gyrus, BA 37 (x ⫽ 37; y ⫽ ⫺63; z ⫽ ⫺18), and (x ⫽ 36; y ⫽ ⫺68; z ⫽ ⫺13), respectively, and are displayed on transverse and coronal brain slices with corresponding z and y coordinates.

ventral putamen during time-locked processing of reward prediction (Pagnoni et al., 2002), or amphetamine-induced euphoria (Drevets et al., 2001).

Activation within the amygdala was demonstrated to low- but not to high-intensity expressions of sadness, and a significant linear decrease rather than increase in hippocam-

Fig. 2. Activation trends in response to different expressions. (A) Significant linear increases in activation associated with increasing intensity of emotional facial expression from neutral to 50% and to 100% fear vs. fixation cross are demonstrated within bilateral extrastriate cortical regions (fusiform gyri, BA 37/19; x ⫽ ⫺36; y ⫽ ⫺66; z ⫽ ⫺7, and x ⫽ 36; y ⫽ ⫺66; z ⫽ ⫺13; P ⫽ 0.01) and the hippocampus (x ⫽ 18; y ⫽ ⫺30; z ⫽ ⫺13; P ⫽ 0.007) in coronal section. (B) Significant linear increases in activation associated with increasing intensity of emotional facial expression from neutral to 50% and to 100% disgust vs. fixation cross are demonstrated within bilateral fusiform gyrus BA 19 (x ⫽ ⫺35; y ⫽ ⫺66; z ⫽ ⫺11, and x ⫽ 40; y ⫽ ⫺60; z ⫽ ⫺18; P ⫽ 0.01) in coronal section, and in the anterior insula (1): x ⫽ ⫺36; y ⫽ 23; z ⫽ ⫺2, and x ⫽ ⫺36; y ⫽ 23; z ⫽ 4; P ⫽ 0.05. (C) Significant linear increases in activation associated with increasing intensity of emotional facial expression from neutral to 50% and to 100% happiness vs. fixation cross are demonstrated within left fusiform gyrus BA 19 (coronal section: x ⫽ ⫺36; y ⫽ ⫺65; z ⫽ ⫺7) and right fusiform gyrus BA 19 (transverse section: x ⫽ 40; y ⫽ ⫺65; z ⫽ ⫺12; P ⫽ 0.01), and the right putamen (P): x ⫽ 23; y ⫽ 4; z ⫽ ⫺12 (P ⫽ 0.01). (D) Significant linear decreases in activation associated with increasing intensity of emotional facial expression from neutral to 50% and to 100% sadness vs. fixation cross are demonstrated in the left hippocampus (H): x ⫽ ⫺14; y ⫽ ⫺37; z ⫽ ⫺7 (P ⫽ 0.01), and left putamen (P): x ⫽ ⫺22; y ⫽ 7; z ⫽ ⫺7 (P ⫽ 0.01), and bilateral cuneus, BA 17 (x ⫽ 4; y ⫽ ⫺89; z ⫽ 4, and x ⫽ ⫺4; y ⫽ ⫺89; z ⫽ 9; P ⫽ 0.01). In transverse section are also demonstrated parts of the larger clusters with increasing activation: bilateral fusiform gyrus BA 19/37: x ⫽ 36; y ⫽ ⫺57; z ⫽ ⫺7, and x ⫽ ⫺40; y ⫽ ⫺62; z ⫽ ⫺7 (P ⫽ 0.01). The right and the left sides of each brain slice are displayed on the right and left sides of each image, respectively.

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pal and putamen responses were demonstrated to increasing intensity of this expression. These findings suggest that the neural regions previously highlighted as important in emotion processing respond preferentially to signals of danger, rather than to signals of other emotions. Our findings indicate that the magnitude of the extrastriate cortical response to an emotional stimulus is dependent upon the type of emotion displayed in the stimulus, whereby the signals of environmental danger, expressions of fear and disgust, were associated with a significantly greater extrastriate response than signals of other emotions. Furthermore, we have demonstrated that specific regions important for the response to emotional stimuli, the amygdala, hippocampus, and anterior insula, respond preferentially to signals of danger, expressions of fear and disgust, and the putamen to reward. Previous authors have suggested that the degree of stimulus ambiguity may determine the extent of cortical engagement (Davis and Whalen, 2001), with less accurately recognisable stimuli eliciting greater cortical responses. One explanation for our findings of increased extrastriate cortical responses to expressions of fear and disgust is that these expressions were more ambiguous and therefore less accurately recognised than expressions of happiness and sadness. Our findings indicate that sad facial expressions were the least accurately recognised and therefore potentially the most ambiguous of all expressions; however, but we did not demonstrate increased extrastriate cortical responses to these stimuli. Furthermore, linear increases in extrastriate cortical response were demonstrated to all expressions as expression intensity, and recognition accuracy, increased. It is unlikely, therefore, that the pattern of extrastriate cortical response we demonstrated to the different facial expressions was a response primarily to the extent of ambiguity within these stimuli. Another explanation for our findings is that general attention or arousal levels differed over the four emotion conditions. Generic activation to the contrast of neutral faces and the baseline fixation cross included a similar pattern of extrastriate cortical response in each of the four emotion conditions, however. It is therefore more plausible that the observed differences in linear trends in extrastriate cortical response to increasing intensity of expression for the four emotions is attributable to differences in the type of emotion displayed in each condition. The four emotional expressions were additionally distinguished by a second, orthogonal factor regarding the physical attributes of the stimuli. Expressions of prototypical fear and happiness comprise patterns of facial features deviating further away in position, and more easily distinguishable, from neutral than expressions of prototypical disgust and sadness (Calder et al., 1997). Our results support this, with happy facial expressions being the expressions most accurately, and sad, the expressions least accurately discriminated from others. This may have had an additional effect upon the extent of modulation of the extrastriate

cortical response to the facial expressions. We demonstrated, however, that the increase in extrastriate cortical activation was significantly greater to increasing intensity of expressions that signalled the presence of danger (fear and disgust) than to those signalling the presence of reward or distress in others (happiness and sadness), or to those expressions that were more easily distinguished from neutral (happiness). The magnitude of the extrastriate cortical response to a visual stimulus is therefore determined not only by the emotional intensity displayed by the stimulus per se, nor is it merely a reflection of the ease with which the stimulus is distinguished from neutral, but is determined predominantly by the extent of danger signalled by the stimulus. In a previous study, sex differences in extrastriate activation to emotional facial expressions were demonstrated, with men, but not women, having greater activation in extrastriate cortex in response to angry compared with happy faces (Kesler/West et al., 2001). These differences were not, however, demonstrated in conditions involving frightened faces (which have been used in our study). It is therefore unlikely that sex differences accounted for our findings of differences in extrastriate cortical activation to the different emotional expressions. Other regions activated but not consistently in response to emotional expressions in comparison with neutral faces included dorsomedial, inferior frontal, superior frontal, and ventromedial prefrontal cortices. The role of these frontal regions in the response to emotional stimuli remains unclear, although may involve appraisal and attentional processes (Drevets, 2000). In evolutionary terms, survival may be more dependent upon the ability of the individual to attend to the presence and extent of danger in the environment, and form appropriate responses to these signals, than it is upon the ability of the individual to recognise the degree of happiness and distress in others. Our findings are the first to indicate that the magnitude of the extrastriate cortical response to an emotionally salient visual stimulus is determined predominantly by the extent of danger rather than the intensity of emotion per se signalled by the stimulus, and that specific regions important for the response to emotional stimuli, including the amygdala and hippocampus, and anterior insula, are activated preferentially by signals of fear, and disgust, respectively, than by signals of either happiness or sadness. Our findings demonstrate that the activation within the extrastriate cortex is a major component of the response within a distributed neural system responding to emotionally salient visual stimuli. We also suggest that the differential pattern of extrastriate cortical response to different categories of emotional stimuli reflects the preferential direction of visual attention to signals of imminent danger, rather than to other emotional stimuli whose identification is of lower importance to survival.

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Acknowledgments This study was supported by the James McDonnell-Pew Foundation. We wish to acknowledge Krish Singh for use of the Brain Tools programme. We have used this programme to display our data.

References Adolphs, R., Damasio, H., Tranel, D., Damasio, A.R., 1996. Cortical systems for the recognition of emotion in facial expressions. J. Neurosci 16, 7678 –7687. Amaral, D.G., Price, J.L., Pitkanen, A., Carmichael, S.T., 1992. Anatomical organization of the primate amygdaloid complex, in: Aggleton, J.P. (Ed.), The Amygdala: Neurobiological Aspects of Emotion, Memory and Mental Dysfunction, Wiley, New York, pp. 1– 66. Blair, R.J., Frith, U., 2000. Neurocognitive explanations of the antisocial personality. Crim. Behav. Mental Health 10, S66 –S82. Blair, R.J.R., Morris, J.S., Frith, C.D., Perrett, D.I., Dolan, R.J., 1999. Dissociable neural responses to facial expressions of sadness and anger. Brain 122, 883– 893. Brammer, M.J., Bullmore, E.T., Simmons, A., Williams, S.C.R., Grasby, P.M., Howard, R.J., Woodruff, P.W., Rabe-Hesketh, S., 1997. Generic brain activation mapping in functional magnetic resonance imaging: a nonparametric approach. Magn. Reson. Imaging 15, 763–770. Breiter, H.C., Etcoff, N.L., Whalen, P.J., Kennedy, W.A., Rauch, S.L., Buckner, R.L., Strauss, M.M., Hyman, S.E., Rosen, B.R., 1996. Response and habituation of the human amygdala during visual processing of facial expressions. Neuron 17, 875– 887. Bullmore, E., Brammer, M., Williams, S.C.R., Rabe-Hesketh, S., Janot, N., Mellers, J., Howard, R., Sham, P., 1996. Statistical methods of estimation and inference for functional MR image analysis. Magn. Reson. Med 35, 261–277. Bullmore, E., Long, C., Suckling, J., Fadili, J., Calvert, G., Zelaya, F., Carpenter, T.A., Brammer, M., 2001. Colored noise and computational inference in neurophysiological (fMRI) time series analysis: resampling methods in time and wavelet domains. Hum. Brain Mapp 12, 61–78. Bullmore, E.T., Brammer, M.J., Rabe-Hesketh, S., Curtis, V.A., Morris, R.G., Williams, S.C.R., Sharma, T., Murray, R.M., McGuire, P.K., 1999a. Methods for diagnosis and treatment of stimulus correlated motion in generic brain activation studies using fMRI. Hum. Brain Mapp 7, 38 – 48. Bullmore, E.T., Suckling, J., Overmeyer, S., Rabe-Hesketh, S., Taylor, E., Brammer, M.J., 1999b. Global, voxel and cluster tests, by theory and permutation for a difference between two groups of structural MR images of the brain. IEEE Trans. Med. Imaging 18, 32– 42. Calder, A.J., Lawrence, A.D., Young, A.W., 2001. Neuropsychology of fear and loathing. Nat. Rev. Neurosci 2, 352–363. Calder, A.J., Young, A.W., Rowland, D., Perrett, D.I., 1997. Computerenhanced emotion in facial expressions. Proc. R. Soc. Lond. B Biol. Sci 264, 919 –925. Canli, T., Zhao, Z., Desmond, J., Kang, E., Gross, J., Gabrieli, J., 2001. An fMRI study of personality influences on brain reactivity to emotional stimuli. Behav. Neurosci 115, 33– 42. Corwin, J., 1994. On measuring discrimination and response bias: unequal number of targets and distractors and two classes of distractors. Neuropsychology 8, 110 –117. Critchley, H.D., Daly, E.M., Phillips, M., Brammer, M., Bullmore, E., Williams, S., Van Amelsvoort, T., Robertson, D., Murphy, D., 2000. Explicit and implicit neural mechanisms for processing of social infor-

1327

mation from facial expressions: a functional magnetic resonance imaging study. Hum. Brain Mapp 9, 93–105. Darwin, Ch., 1872/1998. The Expression of the Emotions in Man and Animals. HarperCollins, London. Davidson, R.J., Irwin, W., 1999. The functional neuroanatomy of emotion and affective style. Trends Cogn. Sci 3, 11–21. Davis, M., Whalen, P.J., 2001. The amygdala: vigilance and emotion. Mol. Psychiatry 6, 13–34. Drevets, W.C., 2000. Neuroimaging studies of mood disorders. Biol. Psychiatry 48, 813– 829. Drevets, W.C., Gautier, C., Price, J.C., Kupfer, D.J., Kinahan, P.E., Grace, A.A., Price, J.L., Mathis, C.A., 2001. Amphetamine-induced dopamine release in human ventral striatum correlates with euphoria. Biol. Psychiatry 49, 81–96. Edgington, E.S., 1995. Randomization Tests. Marcel Dekker, Inc, New York. Eisenberg, N., Fabes, R.A., Miller, P.A., Fultz, J., Shell, R., Mathy, R.M., Reno, R.R., 1989. Relation of sympathy and personal distress to prosocial behavior: a multi-method study. J. Pers. Soc. Psychol 57, 55– 66. Ekman, P., 1972. Universals and cultural differences in facial expressions of emotion, in: Cole, J.K. (Ed.), Nebraska Symposium on Motivation, University of Nebraska Press, Lincoln, Nebraska, pp. 207–283. Haxby, J.V., Hoffman, E.A., Gobbini, M.I., 2000. The distributed human neural system for face perception. Trends Cogn. Sci 4, 23–233. Haxby, J.V., Horwitz, B., Ungerleider, L.G., Maisog, J.M., Pietrini, P., Grady, C.L., 1994. The functional organization of human extrastriate cortex: a PET-rCBF study of selective attention to faces and locations. J. Neurosci 14, 6336 – 6353. Junghoefer, M., Bradley, M., Ebert, T., Lang, P., 2001. Fleeting images: a new look at early emotion discrimination. Psychophysiology 38, 175– 178. Kanwisher, N., McDermott, J., Chun, M.M., 1997. The fusiform face area: a module in human extrastriate cortex specialized for face perception. J. Neurosci 17, 4302– 4311. Kesler/West, M.L., Andersen, A.H., Smith, C., Avison, M.J., Davis, C.E., Kryscio, R.J., Blonder, L.X., 2001. Neural substrates of facial emotion processing using fMRI. Cogn. Brain Res 11, 213–226. Kwong, K.K., Belliveau, J.W., Chesler, D.A., Goldberg, I.E., Weiskoff, R.M., Poncelet, B.P., Kennedy, D.N., Hoppel, B.E., Cohen, M.S., Turner, R., Cheng, H-M, Brady, T.J., Rosen, B.R., 1992. Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc. Natl. Acad. Sci. USA 89, 5675–5679. Lane, R.D., Chua, P.M., Dolan, R.J., 1999. Common effects of emotional valence, arousal and attention on neural activation during visual processing of pictures. Neuropsychologia 37, 989 –997. Lane, R.D., Reiman, E.M., Bradley, M.M., Lang, P.J., Ahern, G.L., Davidson, R.J., Schwartz, G.E., 1997. Neuroanatomical correlates of pleasant and unpleasant emotion. Neuropsychologia 35, 1437–1444. Lang, P.J., Bradley, M.M., Fitzsimmons, J.R., Cuthbert, B.N., Scott, J.D., Moulder, B., Nangia, V., 1998. Emotional arousal and activation of the visual cortex: an fMRI analysis. Psychophysiology 35, 199 –210. Lange, K., Williams, L.M., Young, A.W., Bullmore, E.T., Williams, S.C.R., Brammer, M.J., Gray, J.A., Phillips, M.L., 2003. Task instructions modulate neural responses to fearful facial expressions. Biol. Psychiatry 53, 226 –232. LeDoux, J., 2000. Emotion circuits in the brain. Annu. Rev. Neurosci 23, 155–184. Morris, J.S., Friston, K.J., Buechel, C., Frith, C.D., Young, A.W., Calder, A.J., Dolan, R.J., 1998. A neuromodulatory role for the human amygdala in processing emotional facial expressions. Brain 121, 47–57. Morris, J.S., Frith, C.D., Perrett, D.I., Rowland, D., Young, A.W., Calder, A.J., Dolan, R.J., 1996. A differential neural response in the human amygdala to fearful and happy facial expressions. Nature 383, 812– 815. Pagnoni, G., Zink, C.F., Montague, P.R., Berns, G.S., 2002. Activity in human ventral striatum locked to errors of reward prediction. Nat. Neurosci 5, 97–98.

1328

S.A. Surguladze et al. / NeuroImage 19 (2003) 1317–1328

Phillips, M.L., Young, A.W., Scott, S.K., Calder, A.J., Andrew, C., Giampietro, V., Williams, S.C.R., Bullmore, E.T., Brammer, M., Gray, J.A., 1998. Neural responses to facial and vocal expressions of fear and disgust. Proc. R. Soc. Lond. B Biol. Sci 265, 1809 –1817. Phillips, M.L., Young, A.W., Senior, C., Brammer, M., Andrew, C., Calder, A.J., Bullmore, E.T., Perrett, D.I., Rowland, D., Williams, S.C.R., Gray, J.A., David, A.S., 1997. A specific neural substrate for perceiving facial expressions of disgust. Nature 389, 495– 498. Puce, A., Allison, T., Asgari, M., Gore, J.C., McCarthy, G., 1996. Differential sensitivity of human visual cortex to faces, letter strings and textures: a functional magnetic resonance imaging study. J. Neurosci 16, 5205–5215. Puce, A., Allison, T, Gore, J.C., McCarthy, G., 1995. Face-sensitive regions in human extra-striate cortex studied by functional MRI. J. Neurophysiol 74, 1192–2005. Reiman, E.M., Lane, R.D., Ahern, G.L., Schwartz, G.E., Davidson, R.J., Friston, K.J., 1997. Neuroanatomical correlates of externally and internally generated human emotion. Am. J. Psychiatry 154, 918 –925. Rozin, P., Lowery, L., Ebert, R., 1994. Varieties of disgust faces and the structure of disgust. J. Pers. Soc. Psychol 66, 870 – 881. Rolls, E.T., 1999. The Brain and Emotion. Oxford University Press, New York.

Schneider, F., Grodd, W., Weiss, U., Klose, U., Mayer, K.R., Nagele, T., Gur, R., 1997. Functional MRI reveals left amygdala activation during emotion. Psychiatry Res: Neuroimag 76, 75– 82. Sprengelmeyer, R., Rausch, M., Eysel, U.T., Przuntek, H., 1998. Neural structures associated with recognition of facial expressions of basic emotions. Proc. R. Soc. Lond. B Biol. Sci 265, 1927–1931. Talairach, J., Tournoux, P., 1988. Co-Planar Stereotaxic Atlas of the Human Brain. Thieme, Stuttgart, New York. Taylor, S.F., Liberzon, I., Koeppe, R.A., 2000. The effect of graded aversive stimuli on limbic and visual activation. Neuropsychologia 38, 1415–1425. Vuilleumier, P., Armony, J.L., Driver, J., Dolan, R.J., 2001. Effects of attention and emotion on face processing in the human brain: an event-related fMRI study. Neuron 30, 829 – 841. Williams, L.M., Phillips, M.L., Brammer, M.J., Rennie, C., Bahramali, H., Olivieri, G., Peduto, A., David, A., Skerrett, D., Lagopoulos, J., Gordon, E., 2001. Arousal dissociates amygdala and hippocampal fear responses: evidence from simultaneous fMRI and skin conductance recording. Neuroimage 14, 1070 –1107. Young, A.W., Perrett, D.I., Calder, A.J., Sprengelmeyer, R., Ekman, P., 2002. Facial Expressions of Emotion: Stimuli and Tests (FEEST). Thames Valley Test Company, Bury St. Edmunds.