The authors have declared that no competing interests exist.
Conceived and designed the experiments: CMP BD UH. Performed the experiments: CMP. Analyzed the data: CMP BD TK RCG UH. Contributed reagents/materials/analysis tools: TK FS UH. Wrote the manuscript: CMP BD FS UH. Discussions on the results of the analysis as well as the content of the paper: BD TK RCG FS UH.
Antisocial behavior and aggression are prominent symptoms in several psychiatric disorders including antisocial personality disorder. An established precursor to aggression is a frustrating event, which can elicit anger or exasperation, thereby prompting aggressive responses. While some studies have investigated the neural correlates of frustration and aggression, examination of their relation to trait aggression in healthy populations are rare. Based on a screening of 550 males, we formed two extreme groups, one including individuals reporting high (n=21) and one reporting low (n=18) trait aggression. Using functional magnetic resonance imaging (fMRI) at 3T, all participants were put through a frustration task comprising unsolvable anagrams of German nouns. Despite similar behavioral performance, males with high trait aggression reported higher ratings of negative affect and anger after the frustration task. Moreover, they showed relatively decreased activation in the frontal brain regions and the dorsal anterior cingulate cortex (dACC) as well as relatively less amygdala activation in response to frustration. Our findings indicate distinct frontal and limbic processing mechanisms following frustration modulated by trait aggression. In response to a frustrating event, HA individuals show some of the personality characteristics and neural processing patterns observed in abnormally aggressive populations. Highlighting the impact of aggressive traits on the behavioral and neural responses to frustration in non-psychiatric extreme groups can facilitate further characterization of neural dysfunctions underlying psychiatric disorders that involve abnormal frustration processing and aggression.
According to the frustration-aggression hypothesis, a feeling of frustration (thus a sense of tension, which occurs when our efforts to reach a desired goal are thwarted) evokes negative affect and anger [
In previous behavioral and fMRI studies, frustration has been investigated using various tasks [
A low tolerance for frustration and aggression are also core symptoms in several psychiatric disorders including antisocial personality disorder (ASPD) and psychopathy (PP). Investigations point to a disturbance in the interplay between the PFC (more specifically the ventromedial (vm)PFC/ orbitofrontal cortex (OFC)) and the amygdala in these disorders. This interplay is important for the processing and regulation of negative emotions, including anger and aggression [
Neuroimaging studies on trait aggression/ anger in healthy subjects have revealed similar results, compared to those involving pathologically aggressive groups, including decreased activation in the frontal brain regions (middle frontal cortex, dlPFC, OFC) and elevated activation in the amygdala [
To the best of our knowledge, no study till date has examined neural processing of frustration in healthy individuals with high and low trait aggression. To this end, we used a frustration task involving solvable and unsolvable anagrams [
Based on previous studies, we expected (1) more frustration and thus higher reports of negative affect and anger after the task in the group with high (HA) compared to the one with low trait aggression (LA) [
Finally, based on the above-mentioned findings of hypo- and hyper-reactivity in the limbic regions depending on the presence of PP traits, we aimed to further characterize our sample regarding possible concurrent PP characteristics by incorporating the Psychopathy Personality Inventory Revised [
550 male students from different faculties of RWTH Aachen University completed the Aggression Questionnaire (AQ) [
While HA and LA males differed in their reported AQ scores, for all other variables, such as age, education and various neuropsychological measures, no significant differences emerged (
Age (years) | 22.2 (2.2) | 22.6 (2.2) | - .510 | 37 | 0.613 |
MWT-B (IQ)a | 106.4 (11.9) | 110.8 (11.4) | - 1.187 | 37 | 0.243 |
TMT-Ab | 22.4 (7.3) | 21.4 (5.8) | .462 | 37 | 0.647 |
TMT-Bb | 38.4 (11.4) | 38.3 (12.5) | .028 | 36 | 0.978 |
Verbal Fluencyc | 21.5 (6.5) | 24.8 (6.0) | -1.649 | 37 | 0.108 |
AQ (total score) |
86.6 (9.8) | 52.4 (4.4) | 14.359 | 28.516 | 0.000 |
Physical aggression |
26.2 (5.8) | 13.8 (2.3) | 8.990 | 26.943 | 0.000 |
Verbal aggression |
17.2 (2.8) | 13.2 (2.1) | 5.148 | 37 | 0.000 |
Anger |
20.3 (3.8) | 10.7 (2.9) | 8.735 | 37 | 0.000 |
Hostility |
22.9 (5.0) | 14.7 (2.9) | 6.278 | 33.056 | 0.000 |
Values are presented as means (s.d.). p-value Bonferroni corrected for 5 tests: 0.01.
Degrees of freedom (df) have decimals when the Levene’s test for the equality of variances is significant.
p<.0.001
a MWT-B [
To assess aggressive tendencies in more detail, participants filled in the Psychopathic Personality Inventory Revised (PPI-R) [
PPI-R total** | 341.6 (20.8) | 316.6 (25.1) | 3.414 | 37 | 0.002 |
PPI-R_1 a | 113.6 (12.9) | 111.9 (13.0) | .415 | 37 | 0.680 |
PPI-R_2 b** | 157.8 (24.7) | 131.6 (11.8) | 4.326 | 29.605 | 0.001 |
FAI total ** | 14.5 (6.6) | 7.7 (4.3) | 3.700 | 37 | 0.001 |
FAI spontaneous aggression** | 4.8 (2.6) | 2.0 (2.1) | 3.714 | 36.97 | 0.001 |
FAI reactive aggression | 3.8 (2.3) | 2.5 (1.7) | 1.911 | 37 | 0.064 |
FAI impulsive aggression** | 5.9 (3.1) | 3.2 (1.9) | 3.323 | 33.81 | 0.002 |
FAI self-related aggression** | 3.5 (3.3) | 1.1 (0.9) | 3.163 | 23.978 | 0.004 |
FAI aggression inhibition** | 4.1 (2.2) | 5.9 (1.6) | -2.828 | 37 | 0.008 |
Values are presented as means (s.d.). p-value Bonferroni corrected for 9 tests: 0.006.
Degrees of freedom (df) have decimals when the Levene’s test for the equality of variances is significant.
** p<0.01,***p<.0.001
a PPI-R factor 1: fearless dominance, low behavioral inhibition; b PPI-R factor 2: antisocial impulsivity, strong behavioral activation
Participants were presented with 48 four-letter anagrams (24 solvable/ 24 unsolvable) of German nouns. The anagrams (white letters on black background) were shown for seven seconds. After four seconds, the participants were urged to answer by the request ‘Please respond’. Both the anagrams and the request were presented via MR compatible goggles. People responded by moving a cursor with the right hand’s index and ring fingers which were positioned on fMRI-compatible response buttons (LUMItouch™, Lightwave Technologies, Richmond, Canada). We instructed them to mark the first letter of the word they recognized by pressing a button with the right middle finger. Button press terminated the current trial. The first half of the task consisted of nineteen solvable and five unsolvable anagrams; the second half was constructed by reversing these frequencies. To further augment feelings of frustration while having to deal with the unsolvable anagrams, participants were informed that good performance would be rewarded with extra money. After each anagram, participants received feedback on their performance through the display of either a positive symbol (a smiley) and the sentence ‘You have won thirty Cents’ or a negative symbol (a frowney) and the sentence ‘You have lost thirty Cents’. The task was presented in a block design, where each block lasted 36 seconds and contained three anagrams (each anagram 7s + interstimulus interval minimum 3s + feedback 2s). After each block, a baseline (fixation cross) followed for 15s. Total duration of the task was 13.6min. The paradigm was programmed using the Presentation software package (Neurobehavioral Systems Inc., Albany, CA, USA). In order to assess possible behavioral performance differences between the groups, the number of anagrams solved and reaction times of solvable and unsolvable anagrams were measured.
Statistical analyses were performed using SPSS 18.0 (SPSS, Inc., IL, USA) and level of significance was set at p=0.05. Group differences on demographic, personality and behavioral data (accuracy and reaction times on solvable and unsolvable anagrams) were analyzed using independent samples t-tests. In cases of significant Levene’s test for homogeneity of variance, degrees of freedom were adapted using Satterthwaite’s correction. Results are corrected for multiple testing using Bonferroni correction. Repeated measures ANOVAs were applied with negative affect (PANAS pre and PANAS post) and anger (ESR pre and ESR post) as within-subjects factor and trait aggression (HA vs. LA) as between-subjects factor. For significant differences, estimates of effect size are given as partial η2 and Cohen’s d.
Functional scanning was performed on a Siemens Trio 3 Tesla magnetic resonance scanner. For the blood oxygen level dependent (BOLD)-sensitive MRI measurement, we used a T2*-weighted gradient echo sequence with the following parameters: TR = 2500, TE = 30ms, FoV = 200 mm, 38 axial slices (whole brain coverage), slice thickness = 3.1 mm, in-plane-resolution = 3.125 x 3.125 x 3.1 mm, flip-angle = 77°, Matrix size 64 x 64, slice gap = 0.31 mm. A total of 350 functional images parallel to the intercommissural line (anterior-posterior commissure) with an interleaved order of slice acquisition were acquired on each participant. Four dummy scans were acquired to allow steady-state magnetization and were discarded from further analysis After functional neuroimaging, a 4 min. magnetization-prepared rapid acquisition gradient echo image (MP-RAGE) T1-weighted sequence was applied to obtain structural images (TR = 1900 ms, TE = 2.52 ms, TI = 900 ms, matrix = 256 x 256, 176 slices, FoV: 250 x 250 mm2, flip angle = 9°, voxel size = 1 x 1 x 1 mm3).
Functional data were preprocessed and analyzed using SPM5 [
At the first level, a separate GLM was specified for each participant. The model included separate regressors for solvable (8 blocks) and unsolvable (8 blocks) anagrams, which were convolved with the canonical hemodynamic response function. Further, we entered the six realignment parameters as covariates of no interest in the first-level analysis. Data were high-pass filtered with a cut-off of 128 s to remove low-frequency drifts. Serial correlations were accounted for by a first-order autoregressive model.
In order to assess differences between the two extreme groups, contrast images of solvable and unsolvable conditions from all participants were included in a second-level random-effects analysis. Activation differences in brain regions were examined by a mixed effects two-way ANOVA with group (HA vs. LA) as between-subjects factor and condition (solvable vs. unsolvable anagrams) as within-subjects factor in order to detect significant main or interaction effects. The resulting statistical maps for the main effects of group and condition and the group x condition interaction (all F-contrasts) effect were thresholded at p<0.001 uncorrected with a voxel extent of 20 contiguous voxels (for illustration purposes) as has been applied in previous studies [
We performed an ROI analysis for the left and right amygdala with to maximize sensitivity to group differences in this region. We specifically aimed at investigating the amygdala’s role during frustration because of its function in emotion processing, trait anger [
Correlation analyses were performed for personality measures and amygdala activation scores (mean parameter estimates taken from the ROI analysis) separately in HA and LA. Personality measures included scores on the PPI-R, FAI and the LHA. Results are regarded significant at p<0.05.
One subject was excluded due to excessive head movement during scanning, leaving 21 HA individuals and 18 LA individuals for final analysis.
HA and LA showed no differences on number of anagrams solved (t(37)=0.046, p=0.963, two-tailed) and reaction times on solvable (t(37)=0.653, p=0.518, two-tailed) and unsolvable anagrams (t(25.702)=0.670, p=0.509, two-tailed).
Based on the difference scores on the PANAS (post- minus pre-scores), 13 participants (62%) were classified as responders (i.e. they showed an increase in negative affect or anger levels after the frustration task) in HA, while there were only 4 such responders (22%) in LA. Analysis of PANAS data revealed marginal significant pre vs. post main effect (F(1,37)=3.638, p=0.064) as well as a marginal significant time x group interaction effect (F(1,37)=3.638, p=0.064) and a significant main effect of group (F(1,37)=8.093, p=0.007, partial η2=0.18), demonstrating higher levels of negative affect in HA compared to LA. Assuming a greater increase in negative affect (from pre to post) in the HA group, the independent samples t-test on the PANAS difference scores decomposed the interaction effect and was significant (t(29.099)=2.007, p=0.027, d=0.63, one-tailed), thereby revealing a greater increase of negative affect in the HA compared to the LA group.
For the ESR data, we observed a significant pre vs. post effect (F(1,37)=5.374, p=0.026, partial η2=0.13) with higher values after compared to before the measurement, and group (F(1,37)=8.197, p=0.007, partial η2=0.18), indicating higher levels of anger in HA compared to LA. The interaction was not significant (F(1,37)=2.077, p=0.158).
Post-hoc analyses revealed that HA individuals showed significantly increased negative affect (PANAS, t(20)=2.24, p=0.036, two-tailed) and anger ratings (ESR, t(20)=2.12, p=0.047, two-tailed) after the frustration task (vs. before the task), while the results from these paired samples t-tests were not significant in LA (PANAS, t(17)=.000, p=1.00, two-tailed; ESR, t(17)=1.46, p=.163, two-tailed). Direct comparison between the two groups via independent samples t-tests revealed that HA exhibited a significantly higher level of negative affect (t(25.50)=3.62, p=0.001, d=1.13, two-tailed) and anger ratings (t(25.07)=2.48, p=0.020, d=0.78, two-tailed) compared to LA after the task (
Concerning the other emotions on the ESR, no significant group differences were observed (all p>0.186), except for sadness where HA revealed a trend effect before the task (t(20)=2.02, p =0.056) and significantly higher scores after the anagram task compared to LA (t(20)=2.34, p=0.030, d=0.73).
The
Analysis of parameter estimate values from the amygdala (x=-22, y=-6, z=-12), the dACC (x=-8, y=10, z=26) and the vlPFC (x=34, y=36, z=10) revealed relatively less activation in HA compared to LA during the unsolvable condition (amygdala: (t(37)=3.081, p=0.004, d=-6.13; dACC: t(37)=3.675, p=0.001, d=-1.18; vlPFC: t(37)=2.520, p=0.016, d=-0.80) but no difference between groups during the solvable condition (amygdala: (t(37)=1.080, p=0.287; dACC: t(37)=0.308, p=0.759; vlPFC: t(37)=0.640, p=0.526). Parameter estimate values for all other regions of the interaction effect can be found in
dACC: F(1,74), x=-8, y=10, z=26; amygdala (laterobasal group): F(1,74), x=-22, y=-6, z=-12; threshold: p<0.001 uncorr., k>20 voxel.
dorsal anterior cingulate cortex | -8 | 10 | 26 | L | 56 | 4.54 | 0.000 |
cerebellum | 0 | -68 | -24 | 41 | 3.97 | 0.000 | |
thalamus | 4 | -6 | 0 | R | 38 | 4.07 | 0.000 |
amygdala | -22 | -6 | -12 | L | 36 | 4.00 | 0.000 |
inferior parietal | -34 | -44 | 28 | L | 29 | 4.06 | 0.000 |
lateral globus pallidus | -24 | -18 | -2 | L | 29 | 3.80 | 0.000 |
parahippocampal gyrus | 10 | -6 | -18 | R | 27 | 3.55 | 0.000 |
vlPFC | 34 | 36 | 10 | R | 26 | 3.43 | 0.000 |
Claustrum | -26 | -12 | 22 | L | 24 | 3.50 | 0.000 |
cingulate gyrus | -12 | -10 | 32 | L | 23 | 3.76 | 0.000 |
Abbreviations: k = cluster size
The repeated-measures ANOVA revealed a significant effect of condition, F(1,37)=6.513, p=0.015, η2=0.15, indicating stronger amygdala activation during the solvable condition. Further, a significant main effect of laterality emerged, F(1,37)=8.27, p=0.007, η2=0.18, pointing to higher activation levels in the left compared to the right amygdala. This is in line with earlier propositions of left-lateralization of amygdala activity during affect processing [
Exploratory correlation analyses revealed several moderate associations: in HA, during unsolvable anagrams, negative correlations emerged between the left amygdala and levels of reactive aggression (r=-0.575, p=0.006), FAI summary score (r=-0.442, p=0.045) as well as LHA scores (r=-0.397, p=0.075). Furthermore, levels of spontaneous aggression were negatively correlated to left amygdala activation during unsolvable anagrams (r=-0.490, p=0.024), while there was a trend for the right amygdala (r=-0.424, p=0.056). All other tested correlations failed to reach significance (all p>0.101). Specifically in LA, no correlations between amygdala levels and questionnaire data were observed.
Our study was the first to look into the neural correlates of frustration and associated anger in healthy males with high and low trait aggression. Consistent with our hypothesis, HA reported significantly higher levels of negative affect and anger after the frustration task. The finding of stronger activation in LA compared to HA in the left vlPFC/ dlPFC and right dlPFC is in accordance with previous results relating frontal brain functioning to the regulation of aggression [
As hypothesized, the interaction revealed lower activation in the left dorsal anterior cingulate cortex (dACC) and the right vlPFC in HA compared to LA while working on the unsolvable anagrams. This is in line with previous results relating lower vlPFC activation to impulsivity [
Though our findings are in line with some previous studies reporting ACC but not OFC activation in response to stress and frustration [
Regarding activation in the frontal lobe, Potegal (2012) [
The observation of lower amygdala activation in HA with higher levels of anger was unexpected. Together with the lower frontal (i.e. dACC and vlPFC) activation in HA, this finding might reflect distinct processing strategies of the negative mood state in HA subjects. The prefrontal cortex has interconnections with the amygdala and thereby can modulate its activity [
Further, attenuated amygdala response has been reported in a range of aggressive populations, especially PP and PP traits [
In sum, our results resemble previous findings in abnormally aggressive individuals, emphasizing the role of the frontal cortex, the dACC, the amygdala and partly the insula in frustration processing and the resulting feelings of anger. The insula was found to be less activated in HA, which however could not be specifically linked to the processing of unsolvable anagrams. Based on our findings, which suggest distinct frontal and limbic processing mechanisms of frustration as a function of trait aggression, further research on aggression as a dimensional construct can lead to better understanding and consequently help reduce or prevent aggression and violence in clinical populations.
While this study provides new insight into the neural correlates of frustration and the impact of trait aggression, several methodological constraints have to be considered: The use of a non-frustration task that elicits another emotion (e.g. fear) would have been helpful in further disentangling the brain responses that are specific to frustration from those that are generally linked to emotion reactivity and regulation.
Further, a study stated that the groups in an extreme group approach (EGA) [
While the use of non-pathological extreme groups has its benefits (e.g. the absence of substance abuse, a history of child abuse), there might be important attributes of a pathological group regarding behavior, reaction and neural processing of anger and frustration that could not be explored or taken advantage of in our study. Overt aggression possibly constitutes the factor that particularly differentiates between healthy individuals with high trait aggression and abnormally aggressive individuals. Therefore, future studies incorporating a third group showing a pathological level of aggression can compare the groups on their underlying processing mechanisms of anger and frustration and related behavioral and personality characteristics.
Finally, earlier studies [
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We thank Andreas Finkelmeyer for helpful assistance with programming and data analysis and all participants. Prof. Michael Potegal and a second anonymous reviewer provided many insightful comments. We appreciate the time they took to give these valuable reviews.