SEARCH

SEARCH BY CITATION

Keywords:

  • Amygdala;
  • connectivity;
  • fMRI;
  • serotonin transporter;
  • visual cortex

Abstract

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments
  8. Supporting Information

A distributed, serotonergically innervated neural system comprising extrastriate cortex, amygdala and ventral prefrontal cortex is critical for identification of socially relevant emotive stimuli. The extent to which a genetic variation of serotonin transporter gene 5-HTTLPR impacts functional connectivity between the amygdala and the other components of this neural system remains little examined. In our study, neural activity was measured using event-related functional magnetic resonance imaging in 29 right-handed, white Caucasian healthy subjects as they viewed mild or prototypical fearful and neutral facial expressions. 5-HTTLPR genotype was classified as homozygous for the short allele (S/S), homozygous for the long allele (L/L) or heterozygous (S/L). S/S showed greater activity than L/L within right fusiform gyrus (FG) to prototypically fearful faces. To these fearful faces, S/S more than other genotype subgroups showed significantly greater positive functional connectivity between right amygdala and FG and between right FG and right ventrolateral prefrontal cortex (VLPFC). There was a positive association between measure of psychoticism and degree of functional connectivity between right FG and right VLPFC in response to prototypically fearful faces. Our data are the first to show that genotypic variation in 5-HTTLPR modulates both the amplitude within and the functional connectivity between different components of the visual object-processing neural system to emotionally salient stimuli. These effects may underlie the vulnerability to mood and anxiety disorders potentially triggered by socially salient, emotional cues in individuals with the S allele of 5-HTTLPR.

For intact emotional function, the ability to recognize emotionally salient signals in others is essential, e.g. facial expressions of emotion. Specific components of a visual object-processing system including fusiform gyrus (FG), amygdala and ventral and dorsal prefrontal cortex (Haxby et al. 2000; Phillips et al. 2003) have been identified as especially important for the perception of facial expressions.

The serotonin (5-HT) system is critical for the development of normal adult behaviour (Gaspar et al. 2003). The studies showed that the lower expressing short allele, S (as opposed to the long allele, L) of the variable repeat sequence within the promoter region of the gene for the serotonin transporter (5-HTTLPR) has been associated with anxiety (Holmes et al. 2003; Lesch et al. 1996). The risk for depression has been associated with an interaction of genotype (S allele) with stressful life events as reported in some but not all studies of the subject – for review, see Uher and McGuffin (2008). Canli and Lesch (2007) indicated an important role of genotypic variation within 5-HTTLPR in moderating social cognition in general.

Recent neuroimaging studies showed significantly greater amygdala activity in individuals with the S allele relative to those homozygous for the L allele during the processing of fearful faces (Bertolino et al. 2005; Hariri et al. 2002, 2005) in aversive situations (Furmark et al. 2004) or attending to potentially stressful stimuli (Heinz et al. 2007). Studies have also shown an impact of genotypic variation in 5-HTTLPR upon amygdala–prefrontal functional relationships, specifically that S allele carriers show decreased coupling between amygdala and ventral prefrontal cortex (subgenual cingulate gyrus) to fearful expressions (Pezawas et al. 2005) but show increased coupling between amygdala and dorsomedial prefrontal cortex to emotive scenes (Heinz et al. 2005). Importantly, in behavioural experiments (Beevers et al. 2007), 5-HTTLPR biased the attention of psychiatric sample towards anxiety-related words that may serve as an external measure of the genetic modulation of brain response to emotional signals.

Previous studies of individuals with mood and anxiety disorders have shown increased activity not only in the amygdala (Drevets et al. 1992) but also in extrastriate visual cortex (Surguladze et al. 2005) to negative emotional stimuli. Furthermore, in healthy individuals, there have been findings indicating a modulation of extrastriate visual cortical activity by the emotional content of a visual stimulus (Pourtois et al. 2006; Surguladze et al. 2003; Taylor et al. 2000) that was associated with amygdala activity (Das et al. 2005; Morris et al. 1998).

The extent to which activity within components of the visual object-processing neural system is modulated by genotypic variation in 5-HTTLPR remains little examined.

The main goal of the present study was, therefore, to examine the extent to which genotypic variation in 5-HTTLPR modulated activity within the visual object-processing system and the amygdala during processing of facial emotional expressions. We hypothesized that homozygous for the short allele (S/S) carriers would show a significantly greater activity than homozygous for the long allele (L/L) carriers within and significantly greater functional connectivity between these neural regions to more salient prototypically fearful but not to less salient neutral or mildly fearful facial expressions.

The second goal of our study was to examine relationships between personality factors and genotype and the extent to which these personality factors were associated with neuroimaging measures in individuals with different 5-HTTLPR polymorphisms.

Materials and methods

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments
  8. Supporting Information

Participants

A total of 32 right-handed, white Caucasian healthy individuals without previous medical or psychiatric history were approached to take part in the study. Three individuals did not consent to genotyping. Of the remaining 29, 3 did not complete one of the neuroimaging tasks (either sad faces or happy faces experiment). We therefore report here data from one neuroimaging experiment (fearful vs. neutral faces) completed by all 29 subjects for whom genetic data were available. Participants were not genetically related to each other; 41% were female. The age of participants ranged between 22 and 65 years (mean 37.5 years). Total years of full-time education ranged from 10 to 22 years (mean 16.2 years). Buccal cheek swabs were taken to collect DNA, which was amplified using polymerase chain techniques. 5-HTTLPR genotype was analysed using the method previously described (Gelernter et al. 1997). Alleles were categorized as either long L or short S following the method used by Lesch et al. (1996). About 419 bp products, with 16 repeats, were classified as L, and 375 bp products, with 14 repeats, were classified as S. Although frequencies are known to vary substantially across populations (Gelernter et al. 1997), the genotype distributions in our cohort were similar to those reported by Lesch et al. (1996). S/S comprised 27.6% of the sample (expected 19%), heterozygous (S/L) 48.3% (expected 49%) and L/L 24.1% (expected 32%). There was no significant difference in sex ratio (chi-square, = 0.8) between the genotype subgroups (Table S1). The study was approved by the Institute of Psychiatry Research Ethics Committee, and the study participants gave informed, written consent.

Neuroimaging procedure

Individuals participated in three neuroimaging experiments where different emotional facial expressions were presented: happy, fearful and sad (all vs. neutral facial expressions) in three separate runs, randomized across participants. We report here data from one experiment employing fearful faces for all 29 participants with complete neuroimaging and genetic data. Here, during a 6-min experiment, participants were presented with 10 different facial identities expressing neutral, mild (50%) or prototypical (100%) fearful expressions. In total, participants viewed 20 prototypically fearful (10 identities presented twice), 20 mildly fearful and 20 neutral expressions presented in a randomized order within experiment. Morphed presentations (Young et al. 2002) based on the standard Pictures of Facial Affect series (Ekman & Friesen 1976) were employed in the study. An event-related functional magnetic resonance imaging (fMRI) design was used, involving a variable interstimulus interval, to reduce habituation of the Blood Oxygenation Level-Dependent (BOLD) response in regions such as the amygdala because habituation is a problem in block designs with highly repetitive and predictable stimulus presentation (Breiter et al. 1996). Each facial stimulus was presented for 2 seconds. During the interstimulus interval, the duration of which varied from 3 to 8 seconds according to a Poisson distribution with average interval 4.9 seconds, participants viewed a fixation cross. Previous studies have shown that an implicit (sex decision) task is reliably associated with responses in limbic and extrastriate cortical regions (Morris et al. 1996; Phillips et al. 1997). Participants in this study were therefore requested to decide the gender of each face and press one of two buttons accordingly. The details of this paradigm have been reported elsewhere (Surguladze et al. 2003).

Neuroimaging data acquisition

Gradient echo echoplanar imaging (EPI) data were acquired on a GE Signa 1.5 T system (General Electric, Milwaukee, WI, USA) at Maudsley Hospital, London. A quadrature birdcage head coil was used for radio frequency (RF) transmission and reception. A total of 180 T2*-weighted images depicting BOLD contrast (Ogawa et al. 1992) were acquired over 6.02 min at each of 16 near-axial, non-contiguous, 7-mm thick planes parallel to the intercommissural (AC-PC) line: echo time (TE), 40 milliseconds; repetition time (TR), 2 seconds; in-plane resolution, 3.44 mm; interslice gap, 0.7 mm; flip angle for functional acquisition, 70°; matrix size, 64 × 64 pixels and field of view (FOV), 24 cm. An inversion recovery EPI dataset was acquired at 43 near-axial 3-mm-thick planes parallel to the AC-PC line: TE, 73 milliseconds; inversion time (TI), 180 milliseconds; TR, 16 seconds; in-plane resolution, 1.72 mm; interslice gap, 0.3 mm; matrix size, 128 × 128 × 43 pixels and 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 in order to reach equilibrium magnetization. An autoshimming routine was used on each run.

Generic brain activation mapping

Neuroimaging data were analysed using the method xbam (v.3.4) developed at the Institute of Psychiatry and based on permutation testing (Brammer et al. 1997). Specifically, the statistic used in xbam consists of the ratio of the sum of squares of deviations from the mean image intensity (over the whole time series) resulting from the model:sum of squares of deviations because of the residuals (SSQratio). This statistic is used to overcome the problem inherent in the use of the F (variance ratio) statistic, which is that the residual degrees of freedom are often unknown in fMRI time series because of the presence of coloured noise in the signal. The computation of a standardized measure of effect, the SSQratio, at the individual level followed by analysis of the median SSQratio maps over all individuals treats intrasubject and intersubject variations in effect separately, constituting a mixed effect approach to analysis that is deemed desirable in fMRI.

Prior to time series analysis, data were processed to remove low-frequency signal changes and motion-related artefacts (Bullmore et al. 1999). 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 parameterizing haemodynamic delays of 4 and 8 seconds (Bullmore et al. 2001). Following least squares fitting of this model, the goodness of fit statistic, the SSQratio, was calculated (Edgington 1995) for each contrast. Generic individual and group activation maps were then constructed by mapping the observed and randomized test statistics for each individual into standard stereotactic space (Talairach & Tournoux 1988) and computing and testing median activation maps as previously described (Brammer et al. 1997). Each event (neutral, mild or prototypical faces) was contrasted with the fixation cross. The analysis also produced further group map contrasts: a group map for the contrasts for greater activation to faces compared with fixation cross as well as maps pertaining to greater activation to the fixation cross relative to neutral (mild and prototypical) faces.

The following planned analyses were next performed to test our hypotheses regarding the main goals of the study:

  • 1 Examination of the effect of 5-HTTLPR genotype (S/S, S/L and L/L) and emotion condition (neutral, mild fear and prototypical fear) upon whole brain neural activity. The 3 × 3 analysis of variance (anova) employed to explore the main effects of emotion intensity, genetic subgroup and possible interaction of emotion intensity with the subgroup.

  • 2 A region of interest (ROI) analysis focusing specifically on amygdala activity using the same 3 × 3 anova approach as above, with the condition (neutral, mild fear and prototypical fear) and subgroup (S/S, S/L and L/L) as independent variables, to examine a possible genotype effect on amygdala activation.

  • 3 Examination of the effect of 5-HTTLPR genotype upon functional connectivity between the neural regions obtained in the above analysis in each condition.

Functional connectivity analysis

In accordance with Friston et al. (1993), by functional connectivity, we understand a ‘temporal correlation between two electro/neurophysiological measurements from different parts of the brain (p. 6)’. We therefore used this definition to structure our analyses in the present study. Prior to connectivity analysis, the motion-corrected fMRI time series were extracted for each subject from the most discriminative three-dimensional clusters of voxels in ROIs resulting from the comparison map of generic responses to each condition, i.e. prototypically fearful, mildly fearful and neutral facial expressions vs. baseline.

The haemodynamic response functions (HRF) for each condition were then obtained by averaging the event-related responses of all trials belonging to one particular condition acquired during the first 10 scan volumes following stimulus onset (= 20 trials and TR = 2 seconds). To assess the degree of functional connectivity between ROIs for each condition and group, the HRFs of individual participants in each genotype subgroup were concatenated. For each subgroup, Pearson correlation coefficients were calculated across the concatenated HRFs in the different ROIs resulting in one correlation coefficient per subgroup and region-pair. In order to test whether there was a significant effect of genotype subgroup on the degree of functional connectivity between ROIs (H0: ρS/S ρS/L ρL/L), correlation coefficients were initially transformed using Fisher’s Z transformation (Fisher 1915). The SSQ parameter is approximately χ2 distributed with (− 1) degrees of freedom. The significance level for the main effect of genotype subgroup on each independent region-pair correlation coefficient was set at α < 0.05. Bonferroni corrections were then employed in post hoc analyses of pairwise, between-subgroup comparisons for each condition (using α < 0.005 to control for multiple tests involving three subgroups and three conditions).

Mood, anxiety and personality ratings

The following clinical rating scales were employed to measure any potential effect of genotype upon mood state in study participants: (1) the Beck Depression Inventory (BDI; Beck et al. 1986), (2) the Hamilton observer rating scale for depression (HAMD; Hamilton 1960), (3) the Hamilton rating scale for anxiety (HAMA; Hamilton 1959) and (4) the State-Trait Anxiety Inventory (STAI; Spielberger 1983). The following three personality measures were also employed to measure any potential relationships between these measures and genotype and between these personality and neuroimaging measures in study participants: (1) the Temperament and Character Inventory (TCI; Cloninger et al. 1993), a self-rating questionnaire measuring four temperament dimensions (novelty seeking, harm avoidance, reward dependence and persistence) and three character dimensions (self-directedness, cooperativeness and self-transcendence), (2) the Revised NEO Personality Inventory (NEO PI-R) (Costa & McCrae 1997), a measure of five major domains of personality (neuroticism, extraversion, openness to experience, agreeableness and conscientiousness) that includes six facets defining each domain to facilitate a comprehensive and detailed assessment of normal adult personality and (3) the Eysenck Personality Questionnaire-Revised (EPQ-R;, Eysenck et al. 1985) that measures three dimensions of personality (psychoticism, extraversion and neuroticism).

anovas were then employed to examine the effect of genotype subgroup upon these mood, anxiety and personality measures.

Results

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments
  8. Supporting Information

On-line task performance

All participants were able to identify the gender of the faces with mean per cent accuracy 82.2%. There were no differences between the groups with regard to accuracy of gender identification or reaction time.

Generic brain maps

All participants showed significant activity to neutral faces vs. fixation cross in left insula, right FG, left inferior occipital gyrus, bilateral inferior parietal gyrus and cerebellum, mid-anterior cingulate gyrus and right inferior frontal gyrus; to mild fear vs. fixation cross bilaterally in cerebellum, inferior parietal gyri, right inferior occipital and fusiform gyri, mid-anterior cingulate, right inferior frontal gyrus and right insula and to prototypically fearful faces vs. fixation cross in right and left FG, left inferior occipital gyrus, bilateral inferior parietal gyrus and cerebellum, bilateral insula, mid-anterior cingulate gyrus, right inferior frontal gyrus, right thalamus, right amygdala and right and left hippocampus (Tables S2–S4).

Analyses of variance

A 3 × 3 anova of the whole brain activation with emotion condition (neutral, mild fear and prototypical fear) as the within-subject variable and genotype subgroup (S/S, S/L and L/L) as the between-subject variable produced a brain map with two clusters: in right FG BA 19 (= 25, = −81 and = −13) and right ventrolateral prefrontal cortex BA 47 (VLPFC, = 41, = 21 and = −10). Here, we employed a significance level of < 0.001 to ensure a probability of less than 0.5 false positive cluster observed in the whole brain map.

For the cluster in right FG, there was a significant main effect of intensity (F1,26 = 18.1; < 0.0001) and an interaction of group by intensity (F2,26 = 3.4; < 0.005). Further anovas were performed to examine the effect of intensity upon right FG activity in each genotype group to explore the group × intensity interaction. There was no main effect of intensity in L/L. Within S/S and S/L, there were significant effects of intensity: F2,6 = 8.2; = 0.024 and F2,12 = 18.7; = 0.001, respectively. In the S/S group, there was a greater activation to prototypically fearful compared with the mildly fearful (= 2.5; = 0.042) and neutral faces (= 2.9; = 0.024). In the S/L group, there was a greater activation to prototypically fearful compared with the mildly fearful (= 4.6; < 0.001) and neutral faces (= 4.3; = 0.001). Thus, the main effect of intensity in the whole sample was accounted for by the significantly greater activation in both S/S and S/L groups in response to prototypically fearful faces compared with mildly fearful and neutral faces.

Additional comparisons of S/S, S/L and L/L groups showed a greater activity in right FG to prototypically fearful faces in S/S compared with L/L (t13 = 2.2; = 0.01).

There was no significant difference between S/L and S/S or between S/L and L/L in activity in right FG to prototypically fearful faces.

We therefore suggest that the interaction of group by intensity upon activity in right FG was determined by both increase of activation in S/S to prototypical fear vs. neutral faces and lack of modulation of activity by emotional intensity in L/L.

All participants showed activity in the right FG to neutral and mildly fearful faces, but this did not differ significantly between genotype subgroups (Fig. 1).

image

Figure 1. Interaction of group by intensity upon neural activity in right FG to fearful and neutral faces. (a) Axial slice of the brain map showing the BOLD response to prototypical and mild fearful and neutral faces. The map depicts a cluster in the right FG BA 19 (= 25, = −81 and = −13) where S/S individuals had greater activation in response to prototypically fearful faces compared with L/L. Right side of the image corresponds to the right side of the brain. (b) The graph depicts the effect of genotype upon magnitude of activity in right FG. *S/S L/L (= 0.01).

Download figure to PowerPoint

For the cluster within right VLPFC, there was a main effect of emotion intensity (F2,26 = 5.9; = 0.023) but no other main effects or interactions. The main effect of intensity resulted from increasing neural activity in this cluster in all participants to increasing intensity of fear, i.e. prototypical fear > mild fear > neutral face (Fig. 2).

image

Figure 2. Trends in VLPFC activity to facial expressions. (a) Axial slice of the brain map showing the positive trend in BOLD response to mild, prototypically fearful and neutral faces. The map depicts the cluster in right VLPFC BA 47 (= 41, = 21 and = −10) where the activation in prototypical fear > mild fear > neutral faces in the whole sample. Right side of the image corresponds to the right side of the brain. (b) The graph depicts the main effect of condition upon magnitude of activity in right VLPFC: activation in the whole group increases from neutral to mild to prototypically fearful faces. F2,26 = 5.9; = 0.023.

Download figure to PowerPoint

Because we included the amygdala in our main hypotheses regarding the nature of key neural regions implicated in response to facial expressions employed in this study, we further examined the effect of genotype subgroup and condition upon mean BOLD signal change in the amygdala. The activation in amygdalar ROI was defined empirically – by the observed BOLD effect in the right amygdala (= 18, = −7 and = −13) during the processing of prototypically fearful faces vs. fixation cross. There was no significant effect of genotype or interaction between genotype and emotion condition in this amygdala region.

Functional connectivity analyses

Subsequent analyses were performed to examine the extent to which 5-HTTLPR genotype differentially modulated functional connectivity between the amygdala and the components of the visual object-processing system identified above that showed the main effect of emotion in the whole group. Namely, we constrained our analyses to the examination of functional connectivity between the right-sided amygdala, the right FG and the right VLPFC, resulting in three possible functional relationships between the regions: right amygdala–right FG; right FG–right VLPFC and right VLPFC–right amygdala. To examine whether the genotype modulates the connectivity difference between prototypically fearful vs. neutral faces, a 2 × 3 × 3 repeated measures anova was performed with two conditions (neutral and prototypically fearful faces), three inter-regional links (right amygdala–right FG, right FG–right VLPFC and right VLPFC–right amygdala) as within-subjects variables and three groups (S/S, S/L and S/S) as between-subjects variables.

This analysis produced the following results. There were main effects of condition (F1,26 = 9.6; = 0.005), cluster (F2,25 = 6.0; = 0.02) and an interaction condition × genotype (F2,26 = 3.7; = 0.04). The main effect of condition was accounted for by prototypically fearful faces condition having a greater connectivity than neutral faces in each inter-regional link in the whole sample. The main effect of cluster reflected the fact that the connectivity values in right VLPFC–right amygdala link were lower than in two other inter-regional links. To explore the condition × genotype interaction, we performed a one-way anova for three genotype groups per condition with post hoc tests using Bonferroni correction. The only significant differences between genotype groups were found in prototypically fearful faces conditions in links of right amygdala–right FG (F2,26 = 13.5; < 0.001) and right FG–right VLPFC (F2,26 = 4.9; = 0.015) (Fig. 3). There was no genotype effect in either condition in the right VLPFC–right amygdala link. In the right amygdala–right FG link, the connectivity in S/S was significantly greater than either in L/L (P < 0.001) or in S/L (= 0.001). Within the right FG–right VLPFC link, the connectivity in the S/S group was significantly greater than either in L/L (= 0.026) or in S/L (= 0.038) group.

image

Figure 3. Differences in connectivity between subgroups in response to prototypically fearful faces. The plot represents the differences in functional connectivity between genetic subgroups. Right-sided connectivity between the amygdala and the FG (connectivity right amygdala (RAM)–FG): S/S individuals showed significantly increased functional connectivity between right amygdala and FG compared with both L/L and S/L individuals. Right-sided connectivity between FG and VLPFC (connectivity FG–VLPFC): S/S individuals showed significantly increased functional connectivity between right FG and right VLPFC compared with L/L and S/L individuals. ***< 0.001; **< 0.01; *< 0.05.

Download figure to PowerPoint

Mood, anxiety and personality ratings

The mean BDI score (SD) for the whole sample was 2.3 (3.2), range 0–9; mean HAMD score (SD) 0.4 (1.1), range 0–4 and HAMA (SD) 0.2 (0.53), range 0–2. All these measures were within the normal range. There were no significant differences between the different genotype subgroups regarding mood (BDI and HAMD), anxiety (HAMA and STAI) or personality measures (NEO PI-R, TCI and EPQ-R) (Table S1). Because STAI is considered as the measure more sensitive to state/trait characteristics in healthy subjects, we explored a possible contribution of STAI composite score on the connectivity differences between genotype groups. Univariate anova with connectivity in right amygdala–right FG as a dependent measure, genotype as a between-group factor and STAI as a covariate confirmed the significant between-group difference observed above: F2,26 = 13.2; = 0.001. Partial eta squared for group = 0.67; partial eta squared for STAI = 0.02. Univariate anova with the connectivity in right FG–right VLPFC as a dependent measure, genotype as a between-group factor and STAI as a covariate again confirmed the significant between-group difference observed above: F2,26 = 5.1; = 0.023. Partial eta squared for group = 0.44; partial eta squared for STAI = 0.07. Thus, the degree of STAI score association with the connectivity values was negligible.

Correlational analyses to examine relationships between personality and functional connectivity measures

In our correlational analyses, we were guided by the previous study (Pezawas et al. 2005) that reported significant correlation between the harm avoidance dimension of TCI (Cloninger et al. 1993) and the amygdala–anterior cingulate cortex connectivity, whereas the measures of amplitude of regional activation were of no predictive value. We examined the extent to which different personality measures contributed to the functional connectivity index in two significant functional relationships observed, i.e. right amygdala–right FG and right FG–right VLPFC connectivity. Here, we used a stringent threshold of = 0.001 to control for multiple tests as there were 15 different personality measures (Table S1). We have applied a non-parametric Spearman’s method of correlation as our sample was small. Only the EPQ psychoticism dimension showed a trend positive correlation with the connectivity index between right FG and right VLPFC: Spearman’s ρ = 0.48; < 0.05 (= 28) in the prototypical fear vs. fixation cross condition. There were no other significant or trend relationships between any of the other personality measures.

In all participants, measures of connectivity between amygdala and right FG in response to prototypical fear correlated positively and significantly with those of the right VLPFC–right FG connectivity: ρ = 0.40; < 0.05 (= 29).

Discussion

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments
  8. Supporting Information

Our findings show a differential modulation by 5-HTTLPR genotype of activity within components of the visual object-processing neural system to fearful faces. In particular, S/S individuals showed greater activity than L/L individuals in the right FG to prototypically fearful relative to neutral faces. S/S further showed significantly greater positive functional connectivity than other genotype subgroups (S/L and L/L) between right amygdala and right FG and between right FG and right VLPFC in response to prototypically fearful faces. Thus, we found that the effect of S allele was most pronounced in homozygotes (S/S).

Previous studies reported increases in extrastriate visual cortical activity to fearful relative to neutral faces (Vuilleumier & Pourtois 2007). Importantly, increased visual cortical activity to affectively arousing stimuli was associated with S/S genotype in a recent study employing an event-related potential paradigm (Herrmann et al. 2006). Our findings add to this literature by showing an effect of genotypic variation in 5-HTTLPR upon the amplitude of FG activation as measured by fMRI. The observed increase in magnitude of activity within the right FG occurring in individuals with the low 5-HTT-expressing S/S genotype to fearful faces was accompanied by an increased positive functional connectivity between this region and regions also implicated in the response to facial expressions, the amygdala and VLPFC.

It is known that visual cortex has both forward and backward projections to and from the amygdala (Amaral 2002). Anatomical connections between occipital cortex/FG and inferolateral prefrontal cortex through the inferior fronto-occipital fasciculus have also been verified (Catani et al. 2002; Nieuwenhuys et al. 1988). These projections may underlie the functional connectivity between the above neural regions. Our findings indicate that genotypic variation in 5-HTTLPR may modulate the functional relationship between right-sided amygdala and FG as well as between FG and VLPFC to fearful faces. Importantly, we observed a positive correlation between amygdala–fusiform and frontal–occipital connectivity in the whole sample of subjects that provides further evidence for a system-wide participation of the above neural regions in the processing of emotional signals.

Our findings raise an important question: whether the vulnerability to mood and anxiety disorders in carriers of the S allele is mediated by increased functional connectivity between brain regions implicated in emotion and visual object processing. Previous studies have shown increased activity in amygdala (Drevets et al. 1992; Fu et al. 2004) and extrastriate visual cortex (Phillips et al. 2000; Surguladze et al. 2005) to negative emotional stimuli in mood- and anxiety-disordered adults and increased activity within VLPFC both in anxiety-disordered adults (Rauch et al. 1997) and in adolescents (Monk et al. 2006). Increases in magnitude of activity in FG and connectivity between amygdala–FG and FG–VLPFC to negative emotional stimuli in anxiety-prone individuals (S/S) may therefore underlie the increased salience of, and increased visual attention to, negative emotional stimuli that predispose to mood and anxiety disorders. It has also been shown (Anand et al. 2005a,b) that depression was associated with decreased connectivity between limbic structures (including amygdala) and medial prefrontal/anterior cingulate regions. These findings are consistent with reports of increased medial prefrontal cortical activity postrecovery from depression (Mayberg et al. 2000). We suggest that our results do not contradict the above data but add to the understanding of a neural system-wide dysfunction associated with the risk for depression. A perceptual bias for emotionally salient visual signals might result on the one hand from increased connectivity between amygdala–FG and FG–VLPFC and, on the other hand, from the lack of inhibitory control related to the reduced connectivity between medial prefrontal cortex/anterior cingulate cortex (ACC) and amygdala. This again fits well with the data on decreased connectivity between subgenual cingulate gyrus and amygdala in S/S individuals (Pezawas et al. 2005).

The mechanism of serotonergic modulation of functional connectivity can be conceptualized as follows: serotonin is known to inhibit amygdala and visual cortical activity via gamma-aminobutyric acid (GABA)-producing interneurons (Stutzmann & LeDoux 1999) whereby even a moderate serotonergic input may be propagated into large cellular assemblies. The ultimate physiological effect of 5-HT, however, is not simply excitation or inhibition but rather a subtle modification of neuronal excitability (Lima et al. 1988) and synchronization of cortical activity (Paspalas & Papadopoulos 2001). This supports previous suggestions that serotonin is involved in the facilitation of sensory encoding of emotional signals in visual cortex (Herrmann et al. 2006) or in the fine-tuning of sensory networks in general (Hurley et al. 2004). The low expression of 5-HTT, and therefore increased synaptic levels of 5-HT, in individuals homozygous for S allele may result in a downregulation of presynaptic 5-HT1A autoreceptors as well as postsynaptic terminals (as suggested by Hariri et al. 2005) implicated in the inhibitory effect, which would lead subsequently to increased excitability or synchronization of activity within an amygdala-cortical circuit. Indeed, an additive effect of 5-HT1A gene (5-HT1A-1019C/G) and 5-HTTLPR on amygdala activity to emotional facial expressions has been recently confirmed (Dannlowski et al. 2007). Another line of evidence supporting the involvement of 5-HT metabolism in emotion regulation comes from the tryptophan depletion (TD) studies. For example, a mood-lowering effect of TD in healthy female individuals with positive family history of major depression was associated with the increased right amygdala response to fearful faces in comparison to happy faces (Van et al. 2007). In male subjects, the investigators (Cools et al. 2005) found that TD leads to increase of activity in amygdala/hippocampus as well as the fusiform face area and the right dorsolateral prefrontal cortex. Especially relevant to our study were findings of a direct modulation by 5-HTTLPR polymorphisms of regional glucose metabolism in cortico-limbic structures in people with recurrent major depression (Neumeister et al. 2006).

We found a trend of association of FG–VLPFC connectivity in response to prototypical fear with the psychoticism dimension of EPQ, which has been found to be familial and linked to depression in a sib-pairs study (Pickering et al. 2003). Some (Bertolino et al. 2005; Furmark et al. 2004; Pezawas et al. 2005), but not other (Hariri et al. 2002, 2005; Rao et al. 2007), neuroimaging studies report an effect of genotype upon personality style. We suggest that the link between psychoticism and increased FG–VLPFC connectivity in S/S individuals may indicate one of the pathways underlying the vulnerability to depression. Here, proneness to negative affect (as reflected in the psychoticism score) is associated with increased connectivity in neural systems processing emotionally salient visual signals. This clearly warrants replication.

Our study has some limitations. First, the sample size was relatively small, which may explain why, in contrast to findings of other authors, there was no significant effect of genotypic variation in 5-HTTLPR on magnitude of the right amygdala response to fearful faces. A recent comprehensive meta-analysis (Munafo et al. 2007) suggests that in order to detect a significant effect of genotype on amygdala activation, any given study would require a sample of over 70 subjects (assuming equal number of short and long genotypes). Although the sample of our study was not large enough to show a differential amplitude of amygdala response in S/S vs. L/L genotypes, we were able to show significant findings involving the amygdala in our connectivity analysis. The connectivity approach we have used is based on many repeated measures of BOLD response in each significantly activated cluster (10 time series measurements per subject in connectivity analysis – in contrast to 1 measurement of BOLD signal in the amplitude analysis), which therefore provides for a more powerful output. Thus, even with a small sample size, these findings from connectivity analysis make a significant contribution to the field of neuroimaging genomics.

Another possible limiting factor is the absence of data pertaining to the novel variants of L allele, e.g. single nucleotide polymorphism rs25531 within 5-HTTLPR L allele (A/G) (Kraft et al. 2005; Nakamura et al. 2000; Wendland et al. 2006) posited that only the A variant of the L allele was associated with high levels of 5-HTT expression, whereas the G variant was similar to the S allele. Including these variants would have allowed for more subtle analyses of genotype association with the BOLD response. In particular, one study (Smolka et al. 2007) reported that the 5-HTTLPR effect on amygdala and anterior cingulate cortex activity to unpleasant pictures is stronger if the triallelic variant is considered compared with the 5-HTTLPR effect alone. Dannlowski et al. (2008) reported increased amygdala activity in a sample comprising healthy and depressed individuals, classified according to A/G variants of the L allele. Interestingly, the latter study reported greater activity in the amygdala to emotional signals of different valence, i.e. sad, fearful and happy faces. Still, even the inclusion of these A/G variants did not prove to be effective in detecting an effect of genotype upon amygdala activity in healthy subsamples. Unfortunately, the design of our study at the time did not include the A/G variants of L allele. We suggest, however, that failure to account for A and G variants would have led to a type II, but not type I, error, which may hold true for all previous studies reporting a robust effect of S/S vs. L/L groups.

Together, our data therefore provide further evidence for two aspects of genome-based modulation of activity in neural systems implicated in facial expression processing: one related to the amplitude of neural response, particularly within right FG, and another to the connectivity between different components of this neural system, particularly between amygdala, FG and VLPFC. Furthermore, while previous studies (Heinz et al. 2005; Pezawas et al. 2005) focused upon examination of the modulation by 5-HTTLPR genotype on amygdala–prefrontal cortical functional connectivity to emotional stimuli, our findings suggest a wider impact of such genotypic variation on system-wide functional connectivity during processing of fearful faces.

In summary, our data add to previous findings showing a modulation of neural response to emotional stimuli by genotypic variation in 5-HTTLPR. The effects of such genetic variation may underlie the vulnerability to mood and anxiety disorders potentially triggered by socially salient cues, e.g. others’ faces in social interactions, in individuals with the S allele (Caspi et al. 2003). Our findings highlight the importance of a neural system rather than neural regional approach to the examination of the modulatory effect of genotypic variation in 5-HTTLPR on neural activity to socially salient emotional visual stimuli in healthy and psychiatric populations.

References

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments
  8. Supporting Information
  • Amaral, D.G. (2002) The primate amygdala and the neurobiology of social behavior: implications for understanding social anxiety. Biol Psychiatry 51, 1117.
  • Anand, A., Li, Y., Wang, Y., Wu, J., Gao, S., Bukhari, L., Mathews, V.P., Kalnin, A. & Lowe, M.J. (2005a) Activity and connectivity of brain mood regulating circuit in depression: a functional magnetic resonance study. Biol Psychiatry 57, 10791088.
  • Anand, A., Li, Y., Wang, Y., Wu, J., Gao, S., Bukhari, L., Mathews, V.P., Kalnin, A. & Lowe, M.J. (2005b) Antidepressant effect on connectivity of the mood-regulating circuit: an fMRI study. Neuropsychopharmacology 30, 13341344.
  • Beck, A.T., Steer, R.A. & Brown, G.K. (1986) Beck Depression Inventory – Second Edition Manual. Psychological Corporation– Harcourt Brace, San Antonio, TX.
  • Beevers, C.G., Gibb, B.E., McGeary, J.E. & Miller, I.W. (2007) Serotonin transporter genetic variation and biased attention for emotional word stimuli among psychiatric inpatients. J Abnorm Psychol 116, 208212.
  • Bertolino, A., Arciero, G., Rubino, V., Latorre, V., De Candia, M., Mazzola, V., Blasi, G., Caforio, G., Hariri, A.R. & Kolachana, B. (2005) Variation of human amygdala response during threatening stimuli as a function of 5’HTTLPR genotype and personality style. Biol Psychiatry 57, 15171525.
  • 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, 763770.
  • 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 expression. Neuron 17, 875887.
  • 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. (1999) Methods for diagnosis and treatment of stimulus correlated motion in generic brain activation studies using fMRI. Hum Brain Mapp 7, 3848.
  • Bullmore, E.T., Long, C., Suckling, J., Fadili, J., Calvert, G., Zelaya, F., Carpenter, T.A. & Brammer, M.J. (2001) Colored noise and computational inference in neurophysiological (fMRI) time series analysis: resampling methods in time and wavelet domains. Hum Brain Mapp 12, 6178.
  • Canli, T. & Lesch, K.P. (2007) Long story short: the serotonin transporter in emotion regulation and social cognition. Nat Neurosci 10, 11031109.
  • Caspi, A., Sugden, K., Moffitt, T.E., Taylor, A., Craig, I.W., Harrington, H., McClay, J., Mill, J., Martin, J., Braithwaite, A. & Poulton, R. (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301, 386389.
  • Catani, M., Howard, R.J., Pajevic, S. & Jones, D.K. (2002) Virtual in vivo interactive dissection of white matter fasciculi in the human brain. Neuroimage 17, 7794.
  • Cloninger, C.R., Svrakic, D.M. & Przybeck, T.R. (1993) A psychobiological model of temperament and character. Arch Gen Psychiatry 50, 975990.
  • Cools, R., Calder, A.J., Lawrence, A.D., Clark, L., Bullmore, E. & Robbins, T.W. (2005) Individual differences in threat sensitivity predict serotonergic modulation of amygdala response to fearful faces. Psychopharmacology (Berl) 180, 670679.
  • Costa, P.T. Jr & McCrae, R.R. (1997) Stability and change in personality assessment: the revised NEO Personality Inventory in the year 2000. J Pers Assess 68, 8694.
  • Dannlowski, U., Ohrmann, P., Bauer, J., Deckert, J., Hohoff, C., Kugel, H., Arolt, V., Heindel, W., Kersting, A., Baune, B.T. & Suslow, T. (2008) 5-HTTLPR biases amygdala activity in response to masked facial expressions in major depression. Neuropsychopharmacology 33, 418424.
  • Dannlowski, U., Ohrmann, P., Bauer, J., Kugel, H., Baune, B.T., Hohoff, C., Kersting, A., Arolt, V., Heindel, W., Deckert, J. & Suslow, T. (2007) Serotonergic genes modulate amygdala activity in major depression. Genes Brain Behav 6, 672676.
  • Das, P., Kemp, A.H., Liddell, B.J., Brown, K.J., Olivieri, G., Peduto, A., Gordon, E. & Williams, L.M. (2005) Pathways for fear perception: modulation of amygdala activity by thalamo-cortical systems. Neuroimage 26, 141148.
  • Drevets, W.C., Videen, T.O., Price, J.L., Preskorn, S.H., Carmichael, S.T. & Raichle, M.E. (1992) A functional anatomical study of unipolar depression. J Neurosci 12, 36283641.
  • Edgington, E.S. (1995) Randomization Tests. Marcel Dekker, Inc., New York.
  • Ekman, P. & Friesen, W.V. (1976) Pictures of Facial Affect. Consulting Psychologists Press, Palo Alto, CA.
  • Eysenck, H.J., Eysenck, S.B.G. & Barrett, P. (1985) A revised version of the psychoticism scale. Pers Individ Dif 6, 2129.
  • Fisher, R.A. (1915) Frequency distribution of the values of the correlation coefficient in samples of an indefinitely large population. Biometrika 10, 507521.
  • Friston, K.J., Frith, C.D., Liddle, P.F. & Frackowiak, R.S.J. (1993) Functional connectivity: the principal-component analysis of large (PET) data sets. J Cereb Blood Flow Metab 13, 514.
  • Fu, C.H., Williams, S.C., Cleare, A.J., Brammer, M.J., Walsh, N.D., Kim, J., Andrew, C.M., Pich, E.M., Williams, P.M., Reed, L.J., Mitterschiffthaler, M.T., Suckling, J. & Bullmore, E.T. (2004) Attenuation of the neural response to sad faces in major depression by antidepressant treatment: a prospective, event-related functional magnetic resonance imaging study. Arch Gen Psychiatry 61, 877889.
  • Furmark, T., Tillfors, M., Garpenstrand, H., Marteinsdottir, I., Langstrom, B., Oreland, L. & Fredrikson, M. (2004) Serotonin transporter polymorphism related to amygdala excitability and symptom severity in patients with social phobia. Neurosci Lett 362, 189192.
  • Gaspar, P., Cases, O. & Maroteaux, L. (2003) The developmental role of serotonin: news from mouse molecular genetics. Nat Rev Neurosci 4, 10021012.
  • Gelernter, J., Kranzler, H. & Cubells, J.F. (1997) Serotonin transporter protein (SLC6A4) allele and haplotype frequencies and linkage disequilibria in African- and European-American and Japanese populations and in alcohol-dependent subjects. Hum Genet 101, 243246.
  • Hamilton, M. (1959) The assessment of anxiety states by rating. Br J Med Psychol 32, 5055.
  • Hamilton, M. (1960) A rating scale for depression. J Neurol Neurosurg Psychiatry 23, 5662.
  • Hariri, A.R., Mattay, V.S., Tessitore, A., Kolachana, B., Fera, F., Goldman, D., Egan, M.F. & Weinberger, D.R. (2002) Serotonin transporter genetic variation and the response of the human amygdala. Science 297, 400403.
  • Hariri, A.R., Drabant, E.M., Munoz, K.E., Kolachana, B.S., Mattay, V.S., Egan, M.F. & Weinberger, D.R. (2005) A susceptibility gene for affective disorders and the response of the human amygdala. Arch Gen Psychiatry 62, 146152.
  • Haxby, J.V., Hoffman, E.A. & Gobbini, M.I. (2000) The distributed human neural system for face perception. Trends Cogn Sci 4, 223233.
  • Heinz, A., Braus, D.F., Smolka, M.N., Wrase, J., Puls, I. & Hermann, D. (2005) Amygdala-prefrontal coupling depends on a genetic variation of the serotonin transporter. Nat Neurosci 8, 2021.
  • Heinz, A., Smolka, M.N., Braus, D.F., Wrase, J., Beck, A., Flor, H., Mann, K., Schumann, G., Buchel, C., Hariri, A.R. & Weinberger, D.R. (2007) Serotonin transporter genotype (5-HTTLPR): effects of neutral and undefined conditions on amygdala activation. Biol Psychiatry 61, 10111014.
  • Herrmann, M.J., Huter, T., Muller, F., Muhlberger, A., Pauli, P., Reif, A., Renner, T., Canli, T., Fallgatter, A.J. & Lesch, K.P. (2006) Additive effects of serotonin transporter and tryptophan hydroxylase-2 gene variation on emotional processing. Cereb Cortex 17, 11601163.
  • Holmes, A., Li, Q., Murphy, D.L., Gold, E. & Crawley, J.N. (2003) Abnormal anxiety-related behavior in serotonin transporter null mutant mice: the influence of genetic background. Genes Brain Behav 2, 365380.
  • Hurley, L.M., Devilbiss, D.M. & Waterhouse, B.D. (2004) A matter of focus: monoaminergic modulation of stimulus coding in mammalian sensory networks. Curr Opin Neurobiol 14, 488495.
  • Kraft, J.B., Slager, S.L., McGrath, P.J. & Hamilton, S.P. (2005) Sequence analysis of the serotonin transporter and associations with antidepressant response. Biol Psychiatry 58, 374381.
  • Lesch, K.P., Bengel, D., Heils, A., Sabol, S.Z., Greenberg, B.D., Petri, S., Benjamin, J., Muller, C.R., Hamer, D.H. & Murphy, D.L. (1996) Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science 274, 15271531.
  • Lima, A.D., Bloom, F.E. & Morrison, J.H. (1988) Synaptic organization of serotonin-immunoreactive fibers in primary visual cortex of the macaque monkey. J Comp Neurol 274, 280294.
  • Mayberg, H.S., Brannan, S.K., Tekell, J.L., Silva, J.A., Mahurin, R.K., McGinnis, S. & Jerabek, P.A. (2000) Regional metabolic effects of fluoxetine in major depression: serial changes and relationship to clinical response. Biol Psychiatry 48, 830843.
  • Monk, C.S., Nelson, E.E., McClure, E.B., Mogg, K., Bradley, B.P., Leibenluft, E., Blair, R.J., Chen, G., Charney, D.S., Ernst, M. & Pine, D.S. (2006) Ventrolateral prefrontal cortex activation and attentional bias in response to angry faces in adolescents with generalized anxiety disorder. Am J Psychiatry 163, 10911097.
  • 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, 812815.
  • 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, 4757.
  • Munafò, M.R., Brown, S.M. & Hariri, A.R. (2007) Serotonin transporter (5-HTTLPR) genotype and amygdala activation: a meta-analysis. Biol Psychiatry (Epub ahead of print).
  • Nakamura, M., Ueno, S., Sano, A. & Tanabe, H. (2000) The human serotonin transporter gene linked polymorphism (5-HTTLPR) shows ten novel allelic variants. Mol Psychiatry 5, 3238.
  • Neumeister, A., Hu, X.Z., Luckenbaugh, D.A., Schwarz, M., Nugent, A.C., Bonne, O., Herscovitch, P., Goldman, D., Drevets, W.C. & Charney, D.S. (2006) Differential effects of 5-HTTLPR genotypes on the behavioral and neural responses to tryptophan depletion in patients with major depression and controls. Arch Gen Psychiatry 63, 978986.
  • Nieuwenhuys, R.J., Voogd, J. & Van Huijzen, C. (1988) The Human Central Nervous System. Springer-Verlag, Berlin.
  • Ogawa, S., Tank, D.W., Menon, R., Ellermann, J., Kim, S.-G., Merkle, H. & Ugurbil, K. (1992) Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci U S A 89, 59515955.
  • Paspalas, C.D. & Papadopoulos, G.C. (2001) Serotoninergic afferents preferentially innervate distinct subclasses of peptidergic interneurons in the rat visual cortex. Brain Res 891, 158167.
  • Pezawas, L., Meyer-Lindenberg, A., Drabant, E.M., Verchinski, B.A., Munoz, K.E., Kolachana, B.S., Egan, M.F., Mattay, V.S., Hariri, A.R. & Weinberger, D.R. (2005) 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression. Nat Neurosci 8, 828834.
  • Phillips, M.L., Young, A.W., Senior, C., Brammer, M.J., 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, 495498.
  • Phillips, M.L., Marks, I.M., Senior, C., Lythgoe, D., O’Dwyer, A.M., Meehan, O., Williams, S.C.R., Brammer, M.J., Bullmore, E.T. & McGuire, P.K. (2000) A differential neural response in obsessive-compulsive disorder patients with washing compared with checking symptoms to disgust. Psychol Med 30, 10371050.
  • Phillips, M.L., Drevets, W.C., Rauch, S.L. & Lane, R. (2003) Neurobiology of emotion perception I: the neural basis of normal emotion perception. Biol Psychiatry 54, 504514.
  • Pickering, A., Farmer, A., Harris, T., Redman, K., Mahmood, A., Sadler, S. & McGuffin, P. (2003) A sib-pair study of psychoticism, life events and depression. Pers Individ Dif 34, 613623.
  • Pourtois, G., Schwartz, S., Seghier, M.L., Lazeyras, F. & Vuilleumier, P. (2006) Neural systems for orienting attention to the location of threat signals: an event-related fMRI study. Neuroimage 31, 920933.
  • Rao, H., Gillihan, S.J., Wang, J., Korczykowski, M., Sankoorikal, G.M., Kaercher, K.A., Brodkin, E.S., Detre, J.A. & Farah, M.J. (2007) Genetic variation in serotonin transporter alters resting brain function in healthy individuals. Biol Psychiatry 62, 600606.
  • Rauch, S.L., Savage, C.R., Alpert, N.M., Fischman, A.J. & Jenike, M.A. (1997) The functional neuroanatomy of anxiety: a study of three disorders using positron emission tomography and symptom provocation. Biol Psychiatry 42, 446452.
  • Smolka, M.N., Buhler, M., Schumann, G., Klein, S., Hu, X.Z., Moayer, M., Zimmer, A., Wrase, J., Flor, H., Mann, K., Braus, D.F., Goldman, D. & Heinz, A. (2007) Gene-gene effects on central processing of aversive stimuli. Mol Psychiatry 12, 307317.
  • Spielberger, C. D. (1983) Manual for the State-Trait Anxiety Inventory: STAI. Consulting Psychologists Press, Palo Alto.
  • Stutzmann, G.E. & LeDoux, J.E. (1999) GABAergic antagonists block the inhibitory effects of serotonin in the lateral amygdala: a mechanism for modulation of sensory inputs related to fear conditioning. J Neurosci 19, RC8.
  • Surguladze, S.A., Brammer, M.J., Young, A.W., Andrew, C., Travis, M.J., Williams, S.C. & Phillips, M.L. (2003) A preferential increase in the extrastriate response to signals of danger. Neuroimage 19, 13171328.
  • Surguladze, S.A., Brammer, M.J., Keedwell, P., Giampietro, V., Young, A.W., Travis, M.J., Williams, S.C. & Phillips, M.L. (2005) A differential pattern of neural response toward sad versus happy facial expressions in major depressive disorder. Biol Psychiatry 57, 201209.
  • Talairach, J. & Tournoux, P. (1988) Co-Planar Stereotaxic Atlas of the Human Brain. Thieme, Stuttgart.
  • Taylor, S.F., Liberzon, I. & Koeppe, R.A. (2000) The effect of graded aversive stimuli on limbic and visual activation. Neuropsychologia 38, 14151425.
  • Uher, R. & McGuffin, P. (2008). The moderation by the serotonin transporter gene of environmental adversity in the aetiology of mental illness: review and methodological analysis. Mol Psychiatry 13, 131146.
  • Van, D.V., Evers, E.A., Deutz, N.E. & Schmitt, J.A. (2007) Effects of acute tryptophan depletion on mood and facial emotion perception related brain activation and performance in healthy women with and without a family history of depression. Neuropsychopharmacology 32, 216224.
  • Vuilleumier, P. & Pourtois, G. (2007) Distributed and interactive brain mechanisms during emotion face perception: evidence from functional neuroimaging. Neuropsychologia 45, 174194.
  • Wendland, J.R., Martin, B.J., Kruse, M.R., Lesch, K.P. & Murphy, D.L. (2006) Simultaneous genotyping of four functional loci of human SLC6A4, with a reappraisal of 5-HTTLPR and rs25531. Mol Psychiatry 11, 224226.
  • Young, A.W., Perret, 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.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments
  8. Supporting Information

We thank Professor M. Brammer and Dr M. Catani for their helpful comments on the manuscript.

Supporting Information

  1. Top of page
  2. Abstract
  3. Materials and methods
  4. Results
  5. Discussion
  6. References
  7. Acknowledgments
  8. Supporting Information

The following supplementary material is available for this article online from http://www.blackwell-synergy.com/doi/full/10.1111/j.1601-183X.2008.00390.x

Table S1. Sociodemographic, clinical and personality measures (means and SD)

Table S2. Areas of activation in response to neutral faces vs. fixation cross: whole group (29 subjects)

Table S3. Areas of activation in response to mildly fearful faces vs. fixation cross: whole group (29 subjects)

Table S4. Areas of activation in response to prototypically fearful faces vs. fixation cross: whole group (29 subjects)

Please note: Blackwell Publishing is not responsible for the content or functionality of any supplementary materials supplied by the authors.

[Correction added after online publication 29 May: The legends for the four Supplementary Tables have been inserted].

FilenameFormatSizeDescription
GBB_390_sm_TableS1.doc61KSupporting info item
GBB_390_sm_TableS2.doc37KSupporting info item
GBB_390_sm_TableS3.doc40KSupporting info item
GBB_390_sm_TableS4.doc46KSupporting info item

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.