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. 2015 Feb 9;36(6):2207–2214. doi: 10.1002/hbm.22765

Effect of trait anxiety on prefrontal control mechanisms during emotional conflict

Magali Comte 1, Aïda Cancel 1, Jennifer T Coull 2, Daniele Schön 3, Emmanuelle Reynaud 1, Sarah Boukezzi 1, Pierre‐François Rousseau 1, Gabriel Robert 4, Stéphanie Khalfa 1, Eric Guedj 1, Olivier Blin 1,5, Daniel R Weinberger 6, Eric Fakra 1,5,7,✉
PMCID: PMC6869046  PMID: 25664956

Abstract

Converging evidence points to a link between anxiety proneness and altered emotional functioning, including threat‐related biases in selective attention and higher susceptibility to emotionally ambiguous stimuli. However, during these complex emotional situations, it remains unclear how trait anxiety affects the engagement of the prefrontal emotional control system and particularly the anterior cingulate cortex (ACC), a core region at the intersection of the limbic and prefrontal systems. Using an emotional conflict task and functional magnetic resonance imaging (fMRI), we investigated in healthy subjects the relations between trait anxiety and both regional activity and functional connectivity (psychophysiological interaction) of the ACC. Higher levels of anxiety were associated with stronger task‐related activation in ACC but with reduced functional connectivity between ACC and lateral prefrontal cortex (LPFC). These results support the hypothesis that when one is faced with emotionally incompatible information, anxiety leads to inefficient high‐order control, characterized by insufficient ACC‐LPFC functional coupling and increases, possibly compensatory, in activation of ACC. Our findings provide a deeper understanding of the pathophysiology of the neural circuitry underlying anxiety and may offer potential treatment markers for anxiety disorders. Hum Brain Mapp 36:2207–2214, 2015. © 2015 Wiley Periodicals, Inc.

Keywords: anterior cingulate cortex, lateral prefrontal cortex, emotional conflict, fMRI, psychophysiological interaction, trait anxiety

INTRODUCTION

Vulnerability to anxiety is associated with negative emotional biases in selective attention [Bar‐Haim et al., 2007; Mathews et al., 1997] and higher susceptibility to emotionally ambiguous stimuli [Hirsch and Mathews, 1997; Richards et al., 2002]. These impairments in emotional processing appear to be linked to an imbalance in amygdala‐prefrontal circuitry, which promotes threat‐related responses [Bishop, 2007], and to contribute to the development and maintenance of anxious symptoms [Mathews and MacLeod, 2002]. A predominant hypothesis is that anxiety potentiates a preattentive threat‐evaluation system [Rauch et al., 2000]. Accordingly, increased amygdala BOLD signal has been observed in anxious volunteers in response to threat‐related distractors [Bishop et al., 2004b, 2006]. Nonetheless, more recent evidence associates anxiety with altered prefrontal engagement, including the lateral prefrontal cortex (LPFC) and anterior cingulate cortex (ACC), during attentional and interpretative processes [Bishop, 2007; Campbell‐Sills et al., 2011; Krug and Carter, 2010].

ACC has a strategic position at the crossroads of the corticolimbic circuit and extensive reciprocal connections with both the lateral prefrontal cortex [Saleem et al., 2014 ] and subcortical limbic regions, such as the amygdala [Van Hoesen et al., 1993], making it ideally suited for emotion–cognition integration. Accordingly, ACC is implicated in a complex set of functions, including modulation of attention, response selection/inhibition, and monitoring of competition, as well as appraisal of emotional information and regulation of affective responses [Bush et al., 2000]. In addition, ACC has been implicated in selective attention to emotional information, particularly in the detection of conflicting response tendencies [Bush et al., 2000; Etkin et al., 2006]. Altered functioning of ACC features prominently in the pathophysiology of anxiety disorder [Shin and Liberzon, 2010].

A more detailed analysis of brain function associated with anxiety involves analysis of dynamic cortical processing across brain regions rather than in specific brain areas [Etkin et al., 2010; Seeley et al., 2007]. Neuroimaging studies have started to investigate the impact of anxiety proneness on functional coupling during basic emotional tasks. These studies have mainly reported reduced functional coupling between amygdala and ACC/medial prefrontal (mPFC) regions [Gee et al., 2013; Kienast et al., 2008; Sripada et al., 2013], possibly reflecting the failure of mPFC to suppress amygdala activity [Pezawas et al., 2005]. In parallel, anxiety has been shown to predict defective functional interactions between prefrontal regions in cognitive tasks and at rest [Basten et al., 2012; Seeley et al., 2007] notably between LPFC and dorsal ACC in conflict conditions [Basten et al., 2011].

However, the effects of trait anxiety on the integrated prefrontal emotional control system during more complex emotional situations, such as conflicting emotional stimuli, are poorly known. This is unfortunate because conflicting emotional signals are abundantly present in everyday life and are crucially involved in social interactions. We propose to explore the relations between healthy participants' trait anxiety and variation in ACC activity and in functional connectivity during an emotional conflict task. The study focuses primarily on ACC, given its central role in processing conflicting information, and on its functional interactions with LPFC and amygdala, two regions strongly engaged in emotionally incongruent conditions [Etkin et al., 2006; Comte et al., 2014] and whose activity is modulated by anxiety severity [Bishop et al., 2004a, 2006; Ewbank et al., 2009].

Based on the link between anxiety and perturbed prefrontal functioning found in previous studies, we expected that trait anxiety magnitude would be associated with altered ACC BOLD response [Bishop, 2007; Bishop et al., 2004a;] and decreased functional coupling between ACC and LPFC during emotional conflict [Basten et al., 2011].

MATERIALS AND METHODS

Participants

The present study was conducted with 25 participants (9 women; 20–47 years old, mean age = 33 ±7.5 years old). All participants were right‐handed according to the Edinburgh Handedness Inventory [Oldfield, 1971]. The nonpatient version of the Structured Clinical Interview for DSM‐IV (SCID; [First et al. 2002]) was used to ensure the absence of psychiatric disorder or psychiatric history. Participants had no current or past serious medical or neurological condition; they were not taking any psychotropic drugs at the time of the study and had no contraindication for MRI.

This study was conducted in accordance with the principles of the declaration of Helsinki. Approval was obtained from the local ethics committee (Comité de protection des personnes, Marseille). Each participant gave informed written consent before entering the study.

Stimuli and Procedure

In the experimental task (Variable Attention and congruency Task [VAAT] [Comte et al., 2014]), participants were presented images composed of two parts. The central part of the image displayed photographs of faces expressing positive emotion (joy) or negative emotion (fear, disgust, or anger), from the NimStim Face stimulus set [Tottenham et al., 2009]. The peripheral part, on which the face images were superimposed, represented scenes with a pleasant or unpleasant emotional content, extracted from IAPS files [Lang et al., 2008]. Subjects had to focus on the part of the image framed in green (either the face or the scene) and determine its emotional content (pleasant versus unpleasant) by pressing the corresponding key.

The task consisted of 3 × 2 conditions varying according to emotional congruency (same or different emotional content in the face and the scene), emotional valence (positive or negative), and attentional load (attention focused on the face [low attention] or on the scene [high attention]). Because our primary interest in this study was the effect of trait anxiety on ACC functional activity and connectivity during emotional conflict, we focused the analyses on BOLD signal changes induced by the emotional congruency parameter variation (incongruent versus congruent trials). Relative to congruent conditions, incongruent ones elicited increased activation of the ACC as well as a significantly higher functional connectivity psychophysiological interaction (PPI) between ACC and LPFC, as well as between ACC and amygdala [Comte et al., 2014].

The task had a mixed event‐related/block design, comprising four sessions of 6 min 8 s each. The sessions were divided into 16 blocks that each lasted 20.4 s. Each block comprised four experimental trials, each lasting 3,000 ms, during which subjects provided their response. The valence parameter varied from trial to trial whereas the congruency and attention parameters varied from block to block. The interstimulus interval (ISI) and interblock interval (IBI) were randomly jittered with a respective mean of 1.4 and 1.6 s. Block order was randomized within sessions, and the order of the sessions was counterbalanced across subjects.

MRI Acquisition

Data were acquired on a 3‐T MEDSPEC 30/80 AVANCE imager (Bruker). After an initial localizing scan, functional data were acquired using a T2*‐weighted gradient echoplanar imaging (EPI) sequence (TR= 3,000 ms; TE = 30 ms; FOV= 19.2 × 19.2; 64 × 64 matrix; flip angle 84.8; voxel size 3 × 3 × 3 mm3). Four functional runs of 45 interleaved axial slices were acquired along the anterior–posterior commissure plane with a continuous slice thickness of 3 mm. After the fMRI scans, high‐resolution anatomical images were acquired for anatomical identification with a sagittal T1‐weighted MP‐RAGE sequence (TR = 9.4 ms; TE = 4.42 ms; TI= 800 ms; 256 × 256 × 180 matrix; flip angle 30; voxel size 1 × 1 × 1 mm3).

Self‐Report Anxiety Measures

Before fMRI sessions, participants completed the Spielberger State‐Trait Anxiety Inventory (STAI, [Spielberger, 1983]). Participants' state anxiety scores ranged from 24 to 58 (mean = 33.5, SD = 8), and trait anxiety scores from 23 to 57 (mean = 37.2, SD = 8). These scores are similar to the published norms (state: mean = 36, S.D. = 10; trait: mean = 36, S.D. = 10 [Spielberger, 1983]. To test the potential association between trait and state anxiety, a Pearson correlation analysis was performed between these two variables. In case of significant correlation, or a trend to a significant correlation (P < 0.1), another set of analyses were performed adding STAI state scores as covariate in order to disentangle the effects of trait anxiety form those of state anxiety.

Behavioral Data Analysis

Behavioral data consisted of reaction time and accuracy rate. To investigate the effect of trait anxiety on task performance, linear regression analyses were performed with, separately, response times (RTs) and accuracy as dependent variables, gender, and age as covariates. The threshold for statistical significance was P <0.05. Behavioral data were analyzed in SPSS (v18.0).

fMRI Data Analysis

All data were analyzed using SPM8 software (Wellcome department of Cognitive Neurobiology, University College London; http://www.fil.ion.ucl.ac.uk/spm/software/spm8). The first four volumes of each session, corresponding to signal stabilization, were excluded from the analysis. We performed standard preprocessing procedures, including slice timing correction, motion correction, EPI coregistration to the T1 image, normalization into the MNI (Montreal Neurological Institute) space, and smoothing with a 6 mm Gaussian kernel.

The preprocessed functional images were analyzed using a General Linear Model and an event‐related approach. Congruent and incongruent trials were separately modeled and convolved with a canonical hemodynamic response function to form regressors. The six movement parameters were included in the analysis as regressors of no interest to model residual effects due to head motion. A 128 s high‐pass filter was applied to the data to remove low‐frequency noise. For each participant, contrast images were calculated to estimate BOLD signal changes due to variation in emotional congruency (incongruent versus congruent conditions). The individual contrast images were then entered into a second‐level random effect model. We performed multiple regression analyses as implemented in SPM8, in which subjects' trait anxiety scores, age, and gender were entered as covariates. T‐contrasts were applied to identify brain regions whose activity in response to the emotional congruency variation was positively or negatively associated with STAI anxiety scores. We used a region of interest approach (ROI) focusing on the ACC. ACC ROI was functionally defined using an 18 mm (diameter) sphere centered on peak activations derived from an earlier study examining emotional conflict [Etkin et al., 2010]. The MNI coordinates for the center of this spherical ROI were the following: ACC (x = 5, y = 33, z = 31). We report results within this ROI, using small‐volume corrections (P < 0.05, family‐wise error (FWE) corrected at the voxel level).

Functional Connectivity Analyses

PPI analyses [Friston et al., 1997] were used to assess to what extent the ACC functional connectivity to LPFC and amygdala was modulated by the emotional congruency parameter (incongruent versus congruent conditions). For each subject, the seed region was determined, using a subject‐specific local maximum that was within 15 mm of the group maximum and within the ACC anatomical mask. The first eigenvariate time series of the BOLD‐signal, adjusted for the effects of interest, was extracted from a 5 mm sphere around the seed coordinates. A time series was calculated with the first eigenvariate from the time series of all voxels within the sphere. The PPI regressor was calculated as the product of the time series of the seed region (physiological factor) and the vector coding for the congruency parameter (psychological factor). The general linear model for the first level PPI analyses included the physiological, psychological, and interaction terms, as well as the nuisance variables described above. The individual contrast images testing for a PPI between the ACC and voxels in the other two regions of interest were then entered into second‐level random effect analyses, in exactly the same way as the second level analyses above. To test the effect of trait anxiety on the seed region connectivity, we employed a regression model within SPM, in which STAI scores, age, and gender were entered as covariates. These analyses served to identify brain regions showing congruency‐related changes in connectivity with ACC, positively or negatively associated with anxiety scores. Our analyses focused on two regions of interest (ROIs): the LPFC and amygdala. ROIs were created bilaterally using an 18 mm (diameter) sphere for the LPFC and a 12 mm (diameter) sphere for the amygdala. ROIs centers correspond to peak activations reported in earlier studies exploring emotional conflict and reporting strong LPFC activation [Ochsner et al., 2009], and ACC‐amygdala connectivity [Etkin et al., 2010] in conflict condition. The MNI coordinates for the center of these ROIs were as follows: LPFC (x = ±58, y = 22, z = 20); amygdala (x = ±22, y = −2, z = −18). We report results within our ROIs, using small‐volume corrections (P < 0.05, FWE at the voxel level). Anatomical localization of brain functional activity and connectivity was assessed using WFU PickAtlas software [Maldjian et al., 2003].

RESULTS

Self‐Report Anxiety Measures

The Pearson correlation analysis revealed a trend for trait anxiety to be positively associated with state anxiety (r = 0.375; P = 0.065).

Behavioral Data

Participants' accuracy was high, with a mean value of 92.8% (S.D. = 9.8). Overall mean reaction time was 1,345 ms (S.D. = 254). Regression analyses revealed a trend for STAI‐trait scores to be positively associated with longer reaction time (β = 0.455; P = 0.051) and higher error rate (β = 0.256; P = 0.090) in incongruent versus congruent conditions.

Imaging Data

Relations between brain activity and trait anxiety scores

Regression results indicated that trait anxiety was positively associated with the recruitment of ACC (x, y, z = 4, 26, 28; k = 24; T = 4.34; P [FWE] = 0.024) in incongruent relative to congruent conditions (Fig. 1). This cluster corresponded to Brodmann area 24 and 32. Similar results were obtained when controlling for state anxiety (ACC: x, y, z = 4, 26, 28; k = 15; T = 4.02; P [FWE] = 0.046). This finding is in line with trait anxiety being linked to increased engagement of ACC when emotional conflict occurs.

Figure 1.

Figure 1

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Effects of trait anxiety on ACC activity in incongruent compared to congruent trials. (A) Voxels in ACC showing significant positive relationship with STAI‐trait scores overlaid on canonical single‐subject T1 image. (B) Activation of ACC plotted against STAI‐trait scores. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]

Relations between functional connectivity and trait anxiety score

The PPI analysis revealed a negative relation between trait anxiety and the functional connectivity between the ACC seed region and the right LPFC (x, y, z = 54, 24, 18; k = 31; T = 4.14 P [FWE] = 0.041) in incongruent compared to congruent conditions (Fig. 2). This cluster corresponded to Brodmann area 45. Similar results were obtained when controlling for state anxiety (right LPFC: x, y, z = 54, 24, 18; k = 18; T = 3.90 P [FWE] = 0.066), albeit the relation no longer survived FWE voxel‐wise correction. This indicates that the higher the trait anxiety scores, the weaker the coupling between ACC and LPFC in situations of emotional conflict. In contrast, there was no significant modulatory effect of trait anxiety on ACC‐amygdala functional coupling.

Figure 2.

Figure 2

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Effects of trait anxiety on ACC‐LPFC connectivity in incongruent compared to congruent trials. (A) Voxels in LPFC displaying association between STAI‐trait scores and functional connectivity with ACC overlaid on canonical single‐subject T1 image. (B) ACC‐LPFC functional connectivity plotted against STAI‐trait scores. [Color figure can be viewed in the online issue, which is available at http://wileyonlinelibrary.com.]

DISCUSSION

The present study investigated the impact of anxiety proneness on ACC activity and functional connectivity while subjects performed an emotional conflict task. Findings revealed that in response to emotional conflict, subjects' trait anxiety was positively associated with the magnitude of ACC activity but negatively coupled with the strength of functional connectivity between ACC and right LPFC.

The association found between the ACC activity and individual STAI‐trait scores converges with previous neuroimaging studies reporting an impact of anxiety on prefrontal control systems and more specifically ACC recruitment in both cognitive and emotional tasks [Bishop et al., 2004a, 2006; Campbell‐Sills et al., 2011; Forster et al., 2013]. As stated before, through its privileged interactions with both executive lateral prefrontal regions and limbic emotional structures, ACC exercises a range of top‐down control functions over emotional processing [Bush et al., 2000; Phillips et al., 2008] such as affective conflict monitoring [Etkin et al., 2006; Ochsner et al., 2009].

Anxiety disorders and high trait anxiety are accompanied by a bias in selective attention towards negative/threat‐related stimuli [Bar‐Haim et al., 2007; Mathews et al., 1997]. Although most neuroimaging research on selective attention in anxiety has focused on the amygdala, some studies have linked this behavioral deficit to altered activity within prefrontal control regions, notably in ACC, in volunteers with high versus low levels of anxiety [Shin et al., 2001; Bishop et al., 2004a, 2006], suggesting that heightened anxiety leads to impaired recruitment of ACC top‐down control on emotional processing. In addition, anxious individuals show negative interpretative biases when attempting to disambiguate affective information [Richards et al., 2002]. Ambiguity processing happens when decision‐making relies on information that does not clearly suggest the selection of one option over another, because the information is incomplete, contradictory, or unclear [Simmons et al., 2008]. It is known that appraisal of emotional ambiguity involves a network of brain regions comprising ACC [Simmons et al., 2006]. Interestingly, one other study has shown altered ACC activity in anxiety‐prone subjects processing ambiguous sets of emotional facial expressions [Simmons et al., 2008]. Thus, our findings echo and extend these lines of investigation by indicating perturbed engagement of ACC linked to trait anxiety, possibly to overcome ambiguity arising from discordant affective information.

Results are, however, inconsistent regarding whether anxiety is associated with reduced or increased ACC engagement. Some studies have shown stronger “compensatory” activation [Campbell‐Sills et al., 2011; Paulus et al., 2004] whereas other evidence points to decreased “insufficient” activation in high relative to low anxious participants, along with equal or lower levels of performance [Bishop et al., 2004a, 2006]. Potential explanations for this discrepancy may come from variations in task demands, motivational factors, task performance, or the opportunity to prepare for task performance [Eysenck and Derakshan, 2011]. Our results appear consistent with attentional control theory [Eysenck and Derakshan, 2011], which predicts that high anxious individuals should show stronger brain activation, reflecting compensatory increases in neural effort and processing resources expended on task performance, in the effort to maintain good performance. However, a more parsimonious interpretation is that conflicting, emotionally charged stimuli induce a lesser “tuned activity” profile in anxious individuals [Winterer et al., 2006].

As we expected, connectivity analysis revealed a negative relation between trait anxiety and connectivity strength between ACC and right LPFC in incongruent relative to congruent conditions. It is assumed that to resolve conflict on incongruent trials, there has to be an effective interaction between ACC and LPFC where inputs from ACC signal the occurrence of conflict and lead to the recruitment of control mechanisms implemented by LPFC [Egner and Hirsch, 2005; Kerns et al., 2004]. A negative association between trait anxiety and functional connectivity between ACC and LPFC in conflict trials has been highlighted in a previous study using a color word Stroop task [Basten et al., 2011]. Our finding suggests that the diminished interplay between these prefrontal regions extends to situations in which both the task‐related and distractor stimuli are emotional. Insofar as the attenuated functional coupling of ACC and LPFC associated with trait anxiety is accompanied by a significantly stronger activation of ACC during incongruent trials, it is tempting to speculate that the exaggerated activation of ACC reflects a local compensation for deficient connectivity between this structure and LPFC. But here again, increased activation could, rather, reveal greater “noise” within ACC, and consequently, reduced likelihood that this region is as efficiently in phase with LPFC. Furthermore, the link seen here between vulnerability to anxiety and impoverished functional coupling between prefrontal regions supports the emerging view that psychiatric disorders arise as a result of abnormal integration or “dysconnection” between brain regions [Weinberger et al., 1992].

We did not find a significant relation between trait anxiety and functional coupling between ACC and the amygdala. The association between amygdala engagement and individual variation in trait anxiety has not consistently been found [Bishop et al., 2004a; Campbell‐Sills et al., 2011; Goldstein et al., 2013]. Previous works have shown weakened top‐down control of ACC/mPFC over amygdala in anxious individuals [Kienast et al., 2008], but impairment in ACC‐amygdala coupling has been noticed mainly in very simple emotional tasks or at rest [Kim et al., 2011; Pezawas et al., 2005]. One explanation may be that the emotional conflict task employed here, which mainly mobilized the prefrontal control processes rather than the emotional appraisal processes, could not uncover the effect of anxiety on limbic connectivity. Yet, Etkin et al. [2010] found dampened connectivity between ACC and the amygdala during the resolution of emotional conflict. That study, however, was conducted on clinical patients diagnosed with generalized anxiety disorder and not on healthy volunteers as in our study. We can thus speculate that the failure of ACC to inhibit the amygdala might be related to the symptomatic outcome of a clinical condition, rather than simply vulnerability to anxiety.

This study has some limitations. First, it could be argued that given the positive trend observed between trait and state anxiety scores, it is difficult to attribute the modulatory effects on prefrontal control mechanisms to trait anxiety scores only. To control for possible effects of state anxiety, we repeated the analyses adding state anxiety scores as nuisance covariate. The pattern of results was similar to that previously obtained, though less marked. This could be explained by a decrease in statistical power due to the addition of a third covariate, especially in the case of PPI analyses, which generally tend to lack power and generate a high proportion of false negatives [O'Reilly et al., 2012]. This suggests that even though an effect of state anxiety on our findings cannot be entirely ruled out, this effect is minor compared with that of trait anxiety. Second, the current study relies on self‐report measures of anxiety. Studies have consistently shown individual differences in the manner of response to self‐report items in such a way that the trait that is measured might be affected by other aspects of the subject's personality [Austin et al., 1998]. Thus, self‐measures may be influenced by a number of factors including participants' honesty, introspective ability, understanding/interpretation of the questions, and response styles (Ex: extreme responding, i.e., tendency to opt for the extremes of the response scale). Finally, although cannabis consumption constituted an exclusion criterion and none of the subjects reported using cannabis at the time of the study, we did not test for recent use of cannabis, and therefore the interference of such a confounding factor cannot be entirely ruled out.

CONCLUSION

Our findings, in line with previous works [Basten et al., 2011, 2012; Bishop et al., 2004a, 2006; Shin et al., 2001], suggest that dysfunction of prefrontal control mechanisms constitutes a core process in anxiety. This central feature may be implicated in a large array of cognitive tasks, in particular those encompassing emotional information. Also, high trait anxiety is a common feature among anxiety disorders [Watson, 2005], and a decrease in trait anxiety is a measure of the success of psychotherapies [Fisher and Durham, 1999]. Consequently, our findings might provide potential therapeutic targets, and markers of response to treatment.

ACKNOWLEDGMENT

The authors declare no competing financial interests.

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