Skip to main content
NCBI home page
Social Cognitive and Affective Neuroscience logoLink to Social Cognitive and Affective Neuroscience
. 2011 Apr 14;7(4):403–412. doi: 10.1093/scan/nsr024

Stress shifts brain activation towards ventral ‘affective’ areas during emotional distraction

Nicole Y L Oei 1,2,✉, Ilya M Veer 1,2,3, Oliver T Wolf 4, Philip Spinhoven 1,2,5, Serge A R B Rombouts 1,2,3, Bernet M Elzinga 1,2
PMCID: PMC3324570  PMID: 21498384

Abstract

Acute stress has been shown to impair working memory (WM), and to decrease prefrontal activation during WM in healthy humans. Stress also enhances amygdala responses towards emotional stimuli. Stress might thus be specifically detrimental to WM when one is distracted by emotional stimuli. Usually, emotional stimuli presented as distracters in a WM task slow down performance, while evoking more activation in ventral ‘affective’ brain areas, and a relative deactivation in dorsal ‘executive’ areas. We hypothesized that after acute social stress, this reciprocal dorsal–ventral pattern would be shifted towards greater increase of ventral ‘affective’ activation during emotional distraction, while impairing WM performance. To investigate this, 34 healthy men, randomly assigned to a social stress or control condition, performed a Sternberg WM task with emotional and neutral distracters inside an MRI scanner. Results showed that WM performance after stress tended to be slower during emotional distraction. Brain activations during emotional distraction was enhanced in ventral affective areas, while dorsal executive areas tended to show less deactivation after stress. These results suggest that acute stress shifts priority towards processing of emotionally significant stimuli, at the cost of WM performance.

Keywords: stress, emotional distraction, cortisol, working memory, imaging

INTRODUCTION

Several studies in healthy humans showed that acute stress and stress hormones, catecholamines and glucocorticoids (GC), impair working memory (WM) (Lupien et al., 1999; Oei et al., 2006; Ramos and Arnsten, 2007; Luethi et al., 2008; Schoofs et al., 2008; Arnsten, 2009). WM is the ability to maintain relevant information in mind and to keep irrelevant information out of mind. Stress might be especially detrimental to WM by decreasing one’s ability to keep irrelevant emotional information out of mind, because stress heightens the sensitivity towards potentially threatening stimuli (van Marle et al., 2009), while also compromising the efficiency of conscious effortful information processing by decreasing prefrontal activation during WM performance (Qin et al., 2009). The present study was, therefore, aimed at examining whether acute social stress enhances emotional distraction during WM, and at investigating the stress-induced changes in the underlying neural patterns, using functional magnetic resonance imaging (fMRI).

The preferential processing of emotional cues is considered adaptive, as these are likely to be important for our survival. Accordingly, healthy humans under stress-free circumstances attend to emotional stimuli, even when these are irrelevant to the WM task at hand, and consequently perform poorer at WM (e.g. Kensinger and Corkin, 2003). At the neural level, several studies found an antagonistic relationship between neural activations associated with emotional vs executive processing, revealing that ‘affective processing’ is favoured over ‘executive processing’ (Drevets and Raichle, 1998). When comparing neutral vs emotional distracters in a WM task, ventral ‘affective’ brain areas, such as the inferior frontal gyrus (IFG) and amygdala show increased activation, along with a deactivation of more dorsal ‘executive’ brain areas, such as parietal regions and the right dorsolateral prefrontal cortex (DLPFC) (Perlstein et al., 2002; Dolcos and McCarthy, 2006; Mitchell et al., 2008; Morey et al., 2009; Anticevic et al., 2010).

Attending to emotional stimuli becomes maladaptive when one is biased towards negative cues, and/or unable to disengage from negative information that is unrelated to the task, which is frequently observed in stress-related psychiatric disorders such as post-traumatic stress disorder (PTSD). PTSD, which presumably is precipitated by acute traumatic stress, is associated with an over responsive amygdala and impaired prefrontal function (Elzinga and Bremner, 2002; Shin et al., 2006). Recently, in a task combining emotional and executive processing (Morey et al., 2009) evidence for an imbalance in the interaction between ventral affective and dorsal executive brain areas was found in PTSD patients. PTSD patients showed higher activations in ventral affective brain regions, which was positively related to PTSD symptom severity, and conversely, higher activity in frontoparietal brain regions with lower PTSD symptom severity.

Although the acute stress response in healthy individuals is considered adaptive (De Kloet et al., 1999), its (temporary) effect on the brain shows similarities with PTSD, as even acute mild psychological stress impairs prefrontal cortex (PFC) function (Elzinga and Roelofs, 2005; Oei et al., 2006; Ramos and Arnsten, 2007; Schoofs et al., 2008; Arnsten, 2009; Qin et al., 2009), and heightens the sensitivity of the amygdala towards threatening stimuli (van Marle et al., 2009). We therefore expected that acute social stress would impair WM performance compared with a control condition, especially when distracters are emotional. We further hypothesized that the social stress would lead to an alteration in the reciprocal dorsal–ventral pattern during emotional distraction, with increased activations in ventral ‘affective’ brain areas compared with a non-stressful control condition. To examine our hypothesis, we analysed behavioral performance and dorsal and ventral a priori selected regions of interest (ROIs) implicated in emotional distraction during WM (dorsal system: right DLPFC and bilateral parietal regions, ventral system: bilateral IFG and right amygdala) in previous studies (i.e. Dolcos et al., 2006; Mitchell et al., 2008) We also explored the role of GCs (salivary cortisol) in relation to behavioral performance and neural responses during distraction.

METHODS

Participants

Male volunteers from the general population were recruited by means of advertisements. Eligibility criteria were: no history of disease or chronic disease requiring medical attention, no dyslexia, no colour blindness, no current use of prescribed medication or the use of remedies containing corticosteroids, no use of psychotropic drugs, no current or past psychiatric problems, determined by the Amsterdam Biographical interview (ABV; de Wilde, 1963). The Dutch version of the Symptom checklist (SCL-90) (Arrindell and Ettema, 1986) was used to assess psychoneuroticism (the cut-off score for exclusion was 145, following norm scores for a healthy population), the Dutch version of the Beck Depression Inventory, using a cut-off score for exclusion of >10 (BDI; Bouman et al., 1985). Furthermore, a body mass index (BMI; kg/m2) between 19 and 26, an age between 18 and 35 years, and right-handedness was required. Lastly, participants were required to have a total IQ score of >90, determined by the relevant subtests of the Wechsler Adult intelligence Scale-III (WAIS-III, Wechsler, 1997). Altogether, 40 healthy, male participants were included in the present study and randomly assigned to an experimental and a control group in a randomized two-group design. From this sample two participants with IQs lower than 90 were excluded from analyses in the present study. Four other participants were excluded from the analyses: two participants were outliers because of extreme cortisol levels at baseline, probably reflecting saliva sample contamination or an acute infectious disease (one from stress group, 120 nmol/l; one from the control group, 36 nmol/l). Data from one participant from the stress group could not be collected because of a computer failure. One other participant from the control group was a multivariate outlier with regard to task performance. Each participant gave signed informed consent in which confidentiality, anonymity and the opportunity to withdraw without penalty were assured. The study was approved by the Medical Ethics Committee of the Leiden University Medical Center and carried out according to the standards of the Declaration of Helsinki (2000).

Materials

To ascertain that no pre-stress differences between groups existed on intelligence and WM performance, the subscales Picture Completion, Arithmetic, Information, Block Design, of the WAIS-III (Wechsler 1997) were used to estimate total IQ (TIQ), while Arithmetic, Digit span and Numbers and Letters were used to assess WM Index (WMI). Also state and trait anxiety (State-Trait anxiety inventory, STAI, Spielberger, 1983) was assessed.

Emotional Sternberg task

WM was measured using an adapted version of the Sternberg item-recognition task (Sternberg, 1966), developed and described by Oei et al. (2009). In the present version, the task consisted of a total of 180 trials, which lasted no >25 min. Half of the trials were of low load (i.e. comparison load 4) and the other half of high load (comparison load 16). Comparison load was defined by the number of targets (1 or 4) to hold in WM, multiplied by the number of stimuli (4) in the item-recognition display. Comparison load 16 (4:4; target:recognition display) means that four targets (e.g. RZAS) have to be held in WM while there are four stimuli on the item-recognition display (e.g. CDMA), leading to 16 possible comparisons to perform before answering (i.e. RC-RD-RM-RA-ZC-ZD-ZM-ZA-SC-SD-SA-SM-AC-AD-AM-AA etc.). Each trial started with a blue fixation cross (500 ms), followed by the target presentation (1000 ms), a distracter (1500 ms) and a recognition display (<2000 ms). Random jitter in between trials ranged from 1500 to 4500 ms. Participants were instructed to ignore the distracter pictures, and to fixate their eyes on a red cross centred in each distracter. The target letter then had to be recognized from four letters in a recognition display. Participants pressed a ‘yes’ button indicating they had recognized a target, or a ‘no’ button, when no target letter was present. A target was present (present-target trials) in half of the trials, in the other half the target was absent (absent-target trials). Distracters consisted of validated pictures selected from the International Affective Pictures System (IAPS; Langet al., 2001), of which 60 neutral pictures [rated on 9-points Likert scales (1 very negative, 9 very positive) M ± s.d., valence: 5.09 ± 0.54; arousal (1 not arousing at all, 9 highly arousing): 3.21 ± 0.77] and 60 negatively arousing pictures (M ± s.d., valence: 2.86 ± 0.93; arousal: 6.22 ± 0.52), that matched in background colour, and complexity, e.g. amount of people or animals in the scene. A third category consisted of scrambled versions of both the neutral and emotional pictures (Dolcos and McCarthy 2006). Trial order was pseudorandomized using MATLAB, to optimize independence between regressors (the random generated order was confined by the rule that none of the categories would be presented more than three consecutive times). Task stimuli were back-projected on a screen located at the end of the scanner bore via an LCD projector located outside the scanner room. Subjects viewed stimuli on a screen through a mirror located on the head coil. Stimulus software (e-prime) was used for stimulus presentation and recording of responses.

Subjective ratings

After the experiment participants rated all distracters on a 5-point Likert scale for distractibility (1 not distracting at all, 5 highly distracting), whereas arousal (1 not arousing at all, 5 highly arousing) and valence (1 very positive, 5 very negative) were assessed on 5-points Likert scales using the Self-Assessment Manikin (Bradley and Lang, 1994).

Stress induction

To induce stress, the Trier Social Stress Task (TSST) was employed (Kirschbaumet al., 1993). The TSST protocol has consistently proven to raise cortisol levels (Kirschbaum and Hellhammer, 1994). This laboratory stressor consists of a 10-min period in anticipation of a 5-min free speech, and a 5-min arithmetic task (counting backwards from 1033 to zero, in steps of 13) in front of a selection committee of three psychologists. One committee member responded to incorrect answers by saying out loud ‘incorrect, please start over’, while keeping up participant’s performance by means of a clearly visible scoreboard. In the control condition, participants used the same anticipation period of 10 min to think of a movie to their liking, of which they were informed to having to answer open questions on paper for 5 min, in the same laboratory room, but without audience. Thereafter, they had 5 min to count backwards from 50 to 0 at a slow pace.

Physiological assessments

Salivary cortisol was assessed using Salivettes (Sarstedt, Germany). Saliva sampling is a stress-free method to assess unbound cortisol (Kirschbaum and Hellhammer, 1994). Saliva samples were stored at −20°C until assayed at Proffessor Kirschbaum's laboratory (http://biopsychologie.tu-dresden.de). Cortisol concentrations in saliva were measured using a commercially available chemiluminescence-immuno-assay kit with high sensitivity (IBL, Hamburg, Germany). Inter- and intra-assay coefficients of variation were below 10%. Systolic blood pressure (SBP, mmHg), diastolic blood pressure (DBP, mmHg), and heart rate (HR, bpm) were recorded using an automatic wrist blood pressure monitor (OMRON, R5-I).

Scan protocol

Imaging was carried out on a 3 T Philips Achieva MRI scanner (Philips, Best, The Netherlands), using an 8-channel SENSE head coil. For fMRI, Inline graphic-weighted gradient echo, echo planar images (EPI) sensitive to BOLD contrast were obtained with the following acquisition parameters: repetition time (TR) = 2.2 s, echo time (TE) = 30 ms, flip angle = 80°, SENSE factor = 3, 38 axial slices, FOV = 220 × 220 mm, 2.75 mm isotropic voxels, 0.25 mm slice gap. A high-resolution anatomical image (T1-weighted ultra-fast gradient-echo acquisition; TR = 9.75 ms, TE = 4.59 ms, flip angle = 8°, 140 axial slices, FOV = 224 × 224 mm, in-plane resolution 0.875 × 0.875 mm, slice thickness = 1.2 mm), and a high-resolution Inline graphic-weighted gradient echo EPI scan (TR = 2.2 s, TE = 30 ms, flip angle = 80°, 84 axial slices, FOV = 220 × 220 mm, in-plane resolution 1.96 × 1.96 mm, slice thickness = 2 mm) were acquired for registration purposes. The scan procedure consisted of EPI during the emotional WM task (<25 min), the T1-weighted anatomical scan (6 min) and the high-resolution EPI (1 min). Furthermore, DTI and resting-state fMRI scans were acquired at the end of the procedure (to be reported elsewhere).

Procedure

Participants were invited on two occasions. The first time for further screening purposes (BDI, SCL-90, STAI, WAIS subtests) and the second time for the scan session. Participants were asked to refrain from caffeine or sugar containing drinks, and not to eat 2 h before arrival time. All participants arrived at either 8.30 a.m. or 10.30 a.m. Arrival time was balanced between and within groups, to keep morning cortisol levels as even as possible. After arrival, participants were given instructions regarding the protocol and the emotional WM task. Thirty minutes after arrival, the TSST protocol started. After the TSST, participant got into the scanner, where the emotional Sternberg task, the structural scan, high resolution EPI, DTI and resting states scans were measured. Saliva was sampled at five times: before (‘baseline’) and after the anticipation phase of the TSST (‘pre-speech’), at the end of the TSST (‘post-TSST’), after finishing the emotional WM task while still inside the scanner (‘post-WM’) and after the scan procedure (‘post-scan’). Blood pressure and heart rate were sampled at all the same time points, except for those inside the scanner room. After scanning, participants were seated in front of a PC, to provide subjective ratings of the distracters on arousal, valence and distractibility. Hereafter, an exit-interview and a debriefing regarding the TSST followed. Participants were thanked and paid for their participation.

Data processing and analysis

Physiological data

Cortisol/BP/HR was analysed using repeated measures (RM) ANOVA, and unpaired t-tests.

Task data

Reaction times (RTs) were checked for errors, misses and outliers. Errors and misses were scored and removed. Univariate outliers were replaced by the mean per load by distracter type + 2 s.d. Mahanolobis distance was calculated to check for multivariate outliers [P(D2) < 0.05]. RTs of correct trials were analysed using RM ANOVAs, with as between-subjects factor Group (Stress vs Control), and as within-subjects factors Target (present vs absent), Load (high vs low) and Distracter (emotional vs neutral). Errors were analysed similarly. Follow-up analysis of RM ANOVA effects, if relevant, was done with t-tests. Greenhouse–Geisser corrections were applied when the sphericity assumption was not met. SPSS (version 16) was used for the analyses.

FMRI data

FMRI data processing was carried out using FMRI Expert Analysis Tool (FEAT) Version 4.1, part of [FMRIBs Software Library (FSL), www.fmrib.ox.ac.uk/fsl; Smith et al., 2004]. The following pre-statistics processing was applied: motion correction (Jenkinson et al., 2002); non-brain removal (Smith, 2002); spatial smoothing using a Gaussian kernel of FWHM 8 mm; grand-mean intensity normalization of the entire 4D data set by a single multiplicative factor; high-pass temporal filtering (Gaussian-weighted least-squares straight line fitting, with σ = 50.0 s). Time-series statistical analysis was carried out with local autocorrelation correction (Woolrich et al., 2001). FMRI EPI data were registered to the high resolution EPI scan of each participant, which was registered to the individual T1-weighted structural scan, which was registered to the 2 mm MNI-152 standard space template (Jenkinson and Smith, 2001; Jenkinson et al., 2002). For each participant, eight explanatory variables (EVs) were included in the general linear model: six EVs describing the period between target onset and distracter offset (total length 2.5 s) separate for load (low/high) × distracter type (Neu/Emo/Scr) on correct trials. Target-recognition periods on correct trials were modelled in one EV, independent of load or preceding distracter type, with variable durations depending on the response times of the participants. A last EV was included describing error trials, modelling the entire trial from target onset to target-recognition response.

Each EV was convolved with a double gamma haemodynamic response function to account for the haemodynamic response. The images of contrasts of parameter estimates and corresponding variances were then fed into a higher level mixed effects analysis, carried out with FMRIBs Local Analysis of Mixed Effects (FLAME) (Beckmann et al., 2003; Woolrich et al., 2004). The significance level of the Z- statistic image of the contrast of interest (Emo > Neu) was set to P < 0.001 (Z > 3.1, uncorrected). Before further analysis, the whole-brain activation map, consisting of all participants, was used to select ROIs, defined as clusters of significantly activated contiguous voxels in the four a priori chosen ROIs, involved in coping with emotional distraction, i.e. the right amygdala, the bilateral IFG, right dorsolateral PFC and bilateral parietal lobe (Dolcos and McCarthy, 2006; Dolcos et al., 2006; Mitchell et al., 2008). These activated clusters were further confined within boundaries of preselected atlas-based ROIs (from the anatomical Harvard–Oxford cortical probability atlas, with the exception of the right amygdala, which was confined by boundaries from the Harvard–Oxford subcortical probability atlas). Then, from these ROIs, parameter estimates (PE) were extracted (Emo and Neu at both Low and High Load) with zero determined by each individual’s implicit baseline (Poldrack, 2007). Then, to examine whether stress modulated the specific pattern of more activity in ventral areas, and less activity in dorsal areas during emotional distraction, and the differential (interaction) effects of Load and Distracter, a RM ANOVA was performed on the percentage change of the MR signal (PE/implicit baseline *100) in the regions of interest, with as within-subjects factors neural system (dorsal, ventral), Load (Low vs High), Distracter type (neutral vs emotional), and Group as between-subjects factor.

RESULTS

There were no significant differences in the remaining groups with regard to Age, BMI, BDI, SCL-90, Total IQ, WMI and state anxiety, although trait anxiety showed a trend towards higher anxiety in the stress group (see Table 1 for means and standard deviations).

Table 1.

Means (M) and standard deviations (s.d.) of subject variables in stress and control group

Control (M ± s.d.) Stress (M ± s.d.) F(1, 33) P-value
Age 24.00 ± 2.62 24.47 ± 4.13 0.16 0.69
BMI 22.70 ± 1.55 22.29 ± 2.56 0.32 0.57
BDI 2.71 ± 3.53 3.53 ± 3.61 0.45 0.51
SCL-90 103.24 ± 16.78 104.82 ± 11.51 0.10 0.75
STAI-trait 29.82 ± 6.78 34.06 ± 7.45 3.01 0.09
STAI-state 29.76 ± 6.24 32.47 ± 7.32 1.34 0.26
TIQ 113.35 ± 14.66 114.00 ± 15.30 0.02 0.90
WMI 114.47 ± 13.39 109.41 ± 10.13 1.54 0.22
Open in a new tab

BMI = body mass index; BDI = Beck Depression Inventory; SCL-90 = Symptom Checklist-90; STAI-trait = Trait version of the State-Trait anxiety index: TIQ = Total Intelligence Quotient: WMI = Working memory index.

Stress induction

As expected, the stress induction raised the cortisol levels in the stress group, as evidenced by a Group by Time interaction [F(1.81, 57.83) = 6.95, P = 0.003] (Figure 1). Follow-up t-tests showed that the groups did not differ at baseline [t(32) = 0.59, P = 0.55], while right after the stress induction, cortisol levels were significantly higher in the stress group compared with the control group [t(32) = −2.32, P = 0.027]. After the task, cortisol levels were still higher in the stress group [t(32) = −3.42, P = 0.002). The between-subjects factor Group was not significant, F(1, 32) = 2.19, P = 0.15.

Fig. 1.

Fig. 1

Open in a new tab

Mean levels of cortisol in saliva and standard errors in stress and control group. Note. Significant difference between groups, *P < 0.05, **P < 0.005.

Heart rate. There were no significant differences between groups in heart rate (all P’s > 0.05).

Blood pressure. There were significant within-subjects effects of Time [SBP, F(3, 96) = 9.11, P < 0.0005, DBP, F(3, 96) = 8.64, P < 0.0005] and Condition by Time [SBP, F(3, 96) = 12.52, P < 0.0005; DBP, F(3, 96) = 8.00, P < 0.0005]. After the stress induction, SBP and DBP was significantly higher in the stress group than the control group [respectively, t(32) = −3.09, P = 0.004, t(32) = −4.70, P < 0.0005]. There was also a significant between-groups effect of DBP [F(1, 32) = 6.56, P < 0.02], with a higher mean in the stress group (M ± s.e. = 79.25 ± 1.79) than in the control group (M ± s.e. = 72.75 ± 1.79).

Emotional WM performance

See means and standard deviations of RTs in Table 2. Within subjects, RTs were faster at low load compared with high load, at present vs absent target trials and when the distracter was neutral vs emotional (all P’s < 0.001). Overall, the stress group tended to be slower than the control group [F(1, 32) = 3.66, P = 0.06]. Group, Target and Distracter interacted at trend levels [F(1, 32) = 3.61, P = 0.07]. Post hoc t-tests showed that during present-target trials, the stress group was slower than controls when distracters were emotional [t(32) = −2.03, P = 0.05], but not when they were neutral [t(32) = −1.65, P = 0.11] (Figure 2). In the control group, there was no significant difference in RTs between neutral and emotional trials. There were also no differences during absent-target trials.

Table 2.

Means (M) and standard deviations (s.d.) of RTs and errors on the emotional Sternberg task in the stress and control group.

Control (M ± s.d.)
 Stress (M ± s.d.)
Target Present Absent Present Absent
Load Distracter RTs
    Low     Emo 784.10 ± 180.74 794.50 ± 220.72 949.40 ± 202.67 943.00 ± 183.97
    Neu 736.53 ± 141.68 798.66 ± 222.85 849.29 ± 165.43 973.02 ± 206.98
    High     Emo 1168.38 ± 302.61 1431.22 ± 415.09 1301.25 ± 194.71 1590.8 ± 281.41
    Neu 1138.61 ± 253.51 1357.21 ± 397.44 1240.20 ± 208.66 1537.74 ± 275.57
Errors
    Low     Emo 1.12 ± 1.11 0.18 ± 0.39 0.64 ± 0.86 0.65 ± 0.86
    Neu 0.06 ± 0.68 0.35 ± 0.61 0.35 ± 0.61 0.47 ± 0.72
    High     Emo 3.41 ± 2.48 0.65 ± 0.79 2.94 ± 1.98 1.18 ± 1.19
    Neu 2.82 ± 1.63 0.35 ± 0.99 3.11 ± 2.29 1.06 ± 1.30
Open in a new tab

Fig. 2.

Fig. 2

Open in a new tab

Present-target trials: Mean RTs (and s.e.'s) in emotional and neutral trials of the stress- and control group. *P = 0.05

WM errors

See Table 2 for means and standard deviations of Errors. Within subjects analyses showed that more errors were made at high compared with low load, more during present-target trials vs absent target trials, and also more errors were made when distracters were emotional compared with neutral [F(1, 32) > 5.99, P’s < 0.002]. There were no interactions with group, target or load, and there was no main effect of group [F(1, 32) = 0.70, P = 0.41].

Subjective ratings of neutral and emotional distracters

Participants were subjectively more distracted by emotional pictures (M ± s.d. = 1.78 ± 0.57) than by neutral pictures (M ± s.d. = 1.21 ± 0.22) [t(33) = 6.75, P < 0.0005], and rated emotional distracters (M ± s.d. = 2.07 ± 0.63) as more arousing than neutral distracters (M ± s.d. = 1.18 ± 0.20) [t(33) = 9.99, P < 0.0005)]. The valence of emotional pictures was rated as more negative (M ± s.d. = 3.83 ± 0.46) than the neutral pictures (M ± s.d. = 2.72 ± 0.35) [t(33) = −15.99, P < 0.0005]. There was no difference between stress- and control-group in these ratings (all F’s < 2.34, and P’s > 0.14).

FMRI analyses

The results from the Emo vs Neu contrast in the whole-brain analysis of the combined groups are presented in Table 3. Consistent with previous reports (e.g. Dolcos et al., 2006), the typical pattern of dorsal ‘executive’ deactivations and ventral ‘affective’ activations was found (Figure 3A). The four a priori ROIs (right DLPFC, bilateral LPC, right amygdala, bilateralIFG) were selected from these activations, discarding extended activation in voxels outside these regions (specifically in bilateral orbitofrontal regions) as determined by the probabilistic Harvard–Oxford atlases. Within the right DLPFC, the ROI was selected from the same region as reported by Dolcos et al. (2006).

Table 3.

Peak voxels of significantly activated clusters in brain areas during distraction (Emotional vs Neutral distracters and vice versa), in the whole sample (n = 34).

Contrast Area BA Voxels L/R MNI-coordinates
 Z-value
x y z
Emo > neu
Occipital fusiform gyrus 37 4544 R 42 −62 −12 7.24***
Inferior lateral occipital cortex 19 3924 L −52 −70 12 6.97***
Inferior orbitofrontal cortex 1766 L −36 30 −2 5.20***
IFG, triangularis 1182 R 52 30 4 4.58***
Amygdala 72 R 22 −4 −18 3.98
Anterior temporal fusiform cortex 60 L −30 −10 −36 4.11
Temporal pole 21 24 R 54 8 −32 3.65
Insular cortex 14 R 38 0 −16 3.48
Neu>Emo
Superior temporal gyrus 22 3656 R 62 −4 −4 5.12***
Superior temporal gyrus 22 3391 L −66 −28 8 5.14***
Precentral gyrus 3 1466 R 24 −26 70 4.76***
Pre-/post-central gyrus 777 L −24 −30 66 4.55***
Frontal pole 399 R 42 52 −10 4.23***
Precuneus 224 0 −70 22 3.95
Occipital pole 180 R 30 −94 −10 4.41
Middle frontal gyrus 6 125 L −30 22 54 4.12
Superior frontal gyrus 115 R 24 38 46 4.34
Middle frontal gyrus 9 84 R 50 28 32 4.05
Lateral occipital cortex, superior division 39 79 L −36 −60 38 3.54
Frontal pole (DLPFC) 46 62 R 46 44 16 3.79
Supramarginal gyrus 49 R 54 −38 52 3.55
Post-central gyrus 29 R 52 −22 56 3.52
Pre-/post-central gyrus 25 R 36 −24 48 3.33
Middle frontal gyrus 16 L −24 34 34 3.39
Supramarginal gyrus 40 13 R 46 −42 38 3.39
Open in a new tab

Note. ***cluster corrected (Z > 3.1), P < 0.05. All other areas significant at Z = 3.1, P < 0.001 (uncorrected). No small volume corrections were applied. BA = Brodmann area; L/R = Left/right in the brain; Voxel size is 2 mm isotropic.

Fig. 3.

Fig. 3

Open in a new tab

Brain activation during emotional compared with neutral distraction, and percent signal change in the ROI. (A) Combined group activation showing the typical pattern of dorsal deactivation and ventral activation in the presence of emotional distraction. LPC = lateral parietal cortex; DLPFC = dorsolateral prefrontal cortex; IFG = inferior frontal gyrus. (B) Graphs depict mean percent signal change and standard error in the four regions of interest in control (left) and stress group (right) as a function of distracter.

The RM ANOVA performed on the percentage change of the MR signal in the ROIs showed that there was a Group by Distracter type interaction [F(1, 32) = 5.06, P = 0.03], which indicated more activation during emotional distraction in the stress group than in the control group, but not during neutral distraction. To specifically address our hypothesis that ventral activation would be enhanced, and dorsal activation decreased during emotional distraction, we further inspected this interaction in the dorsal and ventral ROIs. Separate ANOVAs revealed that the stress group compared to control group had a smaller deactivation in the dorsal system during emotional distraction at trend levels [F(1, 33) = 3.09, P = 0.08], and significantly greater activation of the ventral system [F(1, 33) = 4.74, P = 0.04] (see Figure 3b for mean signal change and standard error of the individual ROIs, as a function of group and distracter type).

Finally, Neural system interacted with Load [F(1, 32) = 15.05, P < 0.0001], with at low load, more activation in the ventral system than in the dorsal system [t(33) = −3.29, P = 0.002), and a tendency for less deactivation of the dorsal system at high compared with low load [t(33) = −1.74, P = 0.09].

Correlational analyses

Higher increases in cortisol levels at the time of task performance (mean pre- and post-WM minus baseline) were associated with less interference by emotional distraction (RTs emotional trials minus RTs neutral trials) at trend levels in the stress group (r = −0.37, P = 0.06), but not in the control group (P’s > 0.13). In the stress group, the cortisol response was negatively correlated with neural response in the ventral system during emotional distraction (r = −50, P = 0.04; amygdala, r = −0.45, P = 0.07; IFG, r = −0.30, P = 0.24). There was no significant relation between cortisol response and dorsal activation in stress or control group.

DISCUSSION

In the present study, healthy men were exposed to acute social stress before entering the MRI scanner. Inside the scanner, when cortisol levels were high, participants performed a Sternberg WM task with emotionally negative and neutral distracting pictures, shown during the delay phase of each trial. Emotional distracters evoked more ventral activation after acute social stress, and a tendency towards less deactivation (i.e. a smaller magnitude of below-implicit baseline BOLD signal) in dorsal areas compared to the control group. Furthermore, compared to the control group, WM performance tended to be impaired in the stress group during emotional distraction.

The present study is the first to use a validated stress procedure, the TSST, to test the stress effects on emotional distraction in WM. Our findings lend support to the recent accumulation of ideas on acute stress effects, that—although tackling different memory systems or processes—stress modulates the interaction between ‘higher executive’ and ‘lower emotional’ processes (Luethi et al., 2008; Schwabe and Wolf, 2009; van Marle et al., 2009). Intuitively, the idea that acute effects of stress on memory and cognition have survival value, is attractive as it seems adaptive to prioritize attending to dangerous—instead of neutral stimuli, for later superior recall—and to be more ready to flee than ponder (Joels et al., 2006). For instance, Luethi et al. (2008) showed that stress enhanced implicit memory of negative emotional stimuli, while impairing explicit memory and WM. Stress also induced a shift from goal-directed behaviour towards habits in instrumental stimulus–response processes (Schwabe and Wolf, 2009). Other recent imaging studies reported either enhanced ventral activation after stress, for instance, that stress-induced heightened amygdala and inferior temporal activity towards threat-related stimuli (van Marle et al., 2009), or that stress-reduced dorsal prefrontal activations during WM (Qin et al., 2009). We found comparable effects within one task design, which enhances the convergent validity of the idea that stress facilitates emotional processing at the cost of executive processing. Moreover, consistent with the idea that stress shifts brain activation towards ventral areas during emotional distraction, a recent study (Chuah et al., 2010) reported increased amygdala activation associated with increased emotional distraction during WM after 24 h sleep deprivation, which can be considered as an acute stressor (McEwen, 2006).

The present findings are also consistent with results from other studies showing that stress induces WM impairment (Oei et al., 2006; Schoofs et al., 2008). However, it remains unclear what the specific contribution of GCs is to these stress effects. On the one hand, GCs released during (Elzinga and Roelofs, 2005) and after stress (Oei et al., 2006; Schoofs et al., 2008) have been related to reduced WM performance. On the other hand, GC actions appear to be beneficial in dealing with emotional distraction (Putman et al., 2007; Oei et al., 2009). Here, individuals that responded to stress with high cortisol levels, showed less interference by emotional distraction and a smaller neural response to emotional distracters in the ventral ROIs, especially the amygdala. Although these effects were significant at trend levels, they are consistent with a previous study from our lab, showing that administration of 35 mg hydrocortisone significantly reduced emotional distraction using the same task (Oei et al., 2009). Hydrocortisone administration has also found to reduce selective attention for threat (Putman et al., 2007). Cortisol might act to suppress the first wave stress activity [e.g. noradrenergic (NA) activity] towards emotional stimuli. High NA activity has been shown to increase amygdala responses towards emotional stimuli (Onur et al., 2009), and is also associated with impaired WM performance and PFC function (Arnsten et al., 1999; Birnbaum et al., 1999; Mao et al., 1999; Ramos et al., 2005; Ramos and Arnsten, 2007). Moreover, blocking NA activity has shown to reduce interference by emotional distraction in the present task, which was partially mediated by individual cortisol levels (Oei et al., 2010). Thus, future studies (e.g. using pharmacological manipulations) aimed at further disentangling the specific contributions and interactions of cortisol and NA activity during stress on processing of emotional stimuli should monitor both cortisol and NA.

Given that WM is especially impaired after stress or GCs at high loads (Lupien et al., 1999; Oei et al., 2006), it could be expected that our stressed participants would be particularly distracted by emotional pictures at high load. This was, however, not confirmed. At high load, overall performance speed was quite low and only differentiated between emotional or neutral trials at the descriptive level. This might have been a drawback from having to perform the task inside the scanner, resulting in slightly altered behavioural response patterns compared with similar task data (Oei et al., 2009). At the neural level, more ventral activity was evoked when load was low than when load was high, which is consistent with other reports. Interference by similar emotionally negative distracting pictures was only observed under low- but not high load (Erthal et al., 2005), while amygdala responses to negative distracters under high load were shown to be reduced compared with low load, presumably because high load claims so much attention, that not enough attentional resources were left to be captured by emotional distracters (Pessoa et al., 2005). Furthermore, similar to Dolcos and McCarthy (2006) amygdala activity was higher when contrasting emotional vs neutral distraction. In the control group, however, amygdala activity was not increased when comparing emotional distraction with baseline. As several studies have shown a higher sensitivity to threatening stimuli in women than in men (Canli et al., 2002; Hamann, 2005) the fact that we only tested males, whereas Dolcos and McCarthy tested females, might explain why they found increased amygdala activation during emotional distraction compared to baseline.

Furthermore, only present-target trials appeared sensitive enough to detect effects of distraction in this paradigm, whereas absent-target trials did not differentiate between neutral and emotional distraction (Oei et al., 2009). Present- and absent-target trials usually produce different performances, probably because they elicit/evoke different search strategies (i.e. for present-target trials a self-terminating and for absent-target trials an exhaustive search strategy) (Corbin and Marquer, 2008). Nonetheless, because neural activation during the delay of each trial preceded the participants/knowledge of target presence or absence, we did not analyse the imaging data for present-targets only. Discarding half of the imaging data would also have greatly reduced the power to detect differences.

Together, the present results show greater activation in ventral ‘affective’ areas after stress, and smaller deactivation in dorsal ‘executive’ areas, during emotional distraction. This was related to slower WM performance during emotional distraction. These results might suggest that acute stress shifts priority towards processing of emotionally significant stimuli, at the cost of WM performance. Further research into the effects of stress on cognitive functioning and attention to (distracting) emotional stimuli in the environment should be aimed at elucidating the specific effects of cortisol and other stress hormones on neural and behavioural performance.

Conflict of Interest

None declared.

Acknowledgments

The authors are very grateful to Judith Dekker and Mascha Nuijten for their help with the data collection. The authors also thank Eveline Crone for her helpful advice with regard to the data analysis. The contribution of OTWolf was supported by a grant from the German Research Foundation (DFG WO 733/6-2).

REFERENCES

  1. Anticevic A, Repovs G, Barch DM. Resisting emotional interference: brain regions facilitating working memory performance during negative distraction. Cognitive, Affective and Behavioral Neuroscience. 2010;10:159–73. doi: 10.3758/CABN.10.2.159. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Arnsten AF. Stress signalling pathways that impair prefrontal cortex structure and function. Nature Reviews Neuroscience. 2009;10:410–22. doi: 10.1038/nrn2648. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Arnsten AF, Mathew R, Ubriani R, Taylor JR, Li BM. Alpha-1 noradrenergic receptor stimulation impairs prefrontal cortical cognitive function. Biological Psychiatry. 1999;45:26–31. doi: 10.1016/s0006-3223(98)00296-0. [DOI] [PubMed] [Google Scholar]
  4. Arrindell WA, Ettema JHM. SCL-90. Handleiding bij een multidimensionele psychopathologie-indicator. Lisse: Swets & Zeitlinger B.V; 1986. [Google Scholar]
  5. Beckmann CF, Jenkinson M, Smith SM. General multilevel linear modeling for group analysis in FMRI. NeuroImage. 2003;20:1052–63. doi: 10.1016/S1053-8119(03)00435-X. [DOI] [PubMed] [Google Scholar]
  6. Birnbaum S, Gobeske KT, Auerbach J, Taylor JR, Arnsten AF. A role for norepinephrine in stress-induced cognitive deficits: alpha-1-adrenoceptor mediation in the prefrontal cortex. Biological Psychiatry. 1999;46:1266–74. doi: 10.1016/s0006-3223(99)00138-9. [DOI] [PubMed] [Google Scholar]
  7. Bouman TK, Luteyn F, Albersnagel FA, van der Ploeg FAE. Enige ervaringen met de Beck Depression Inventory (BDI) Gedrag, tijdschrift voor psychologie. 1985;13:13–24. [Google Scholar]
  8. Bradley MM, Lang PJ. Measuring emotion: the Self-Assessment Manikin and the Semantic Differential. Journal of Behavior Therapy and Experimental Psychiatry. 1994;25:49–59. doi: 10.1016/0005-7916(94)90063-9. [DOI] [PubMed] [Google Scholar]
  9. Canli T, Desmond JE, Zhao Z, Gabrieli JD. Sex differences in the neural basis of emotional memories. Proceedings of the National Academy of Sciences USA. 2002;99:10789–94. doi: 10.1073/pnas.162356599. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Chuah LY, Dolcos F, Chen AK, Zheng H, Parimal S, Chee MW. Sleep deprivation and interference by emotional distracters. Sleep. 2010;33:1305–13. doi: 10.1093/sleep/33.10.1305. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Corbin L, Marquer J. Effect of a simple experimental control: the recall constraint in Sternberg's memory scanning task. The European Journal of Cognitive Psychology. 2008;20:913–35. [Google Scholar]
  12. Declaration of Helsinki. 52nd WMA General Assembly, Edinburgh, Scotland, Oct. 2000.
  13. De Kloet ER, Oitzl MS, Joels M. Stress and cognition: are corticosteroids good or bad guys? Trends in Neurosciences. 1999;22:422–6. doi: 10.1016/s0166-2236(99)01438-1. [DOI] [PubMed] [Google Scholar]
  14. de Wilde GJS. Neurotische labiliteit gemeten volgens de vragenlijstmethode. 1963 Amsterdam: Van Rossen. [Google Scholar]
  15. Dolcos F, Kragel P, Wang L, McCarthy G. Role of the inferior frontal cortex in coping with distracting emotions. Neuroreport. 2006;17:1591–94. doi: 10.1097/01.wnr.0000236860.24081.be. [DOI] [PubMed] [Google Scholar]
  16. Dolcos F, McCarthy G. Brain systems mediating cognitive interference by emotional distraction. Journal of Neuroscience. 2006;26:2072–9. doi: 10.1523/JNEUROSCI.5042-05.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Drevets WC, Raichle ME. Suppression of regional cerebral blood during emotional versus higher cognitive implications for interactions between emotion and cognition. Cognition Emotion. 1998;12:353–85. [Google Scholar]
  18. Elzinga BM, Bremner JD. Are the neural substrates of memory the final common pathway in posttraumatic stress disorder (PTSD)? Journal of Affective Disorders. 2002;70:1–17. doi: 10.1016/s0165-0327(01)00351-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Elzinga BM, Roelofs K. Cortisol-induced impairments of working memory require acute sympathetic activation. Behavioral Neuroscience. 2005;119:98–103. doi: 10.1037/0735-7044.119.1.98. [DOI] [PubMed] [Google Scholar]
  20. Erthal FS, de Oliveira, Mocaiber I, Pereira MG, Machado-Pinheiro W, Pessoa L. Load-dependent modulation of affective picture processing. Cognitive, Affective and Behavioral Neuroscience. 2005;5:388–95. doi: 10.3758/cabn.5.4.388. [DOI] [PubMed] [Google Scholar]
  21. Jenkinson M, Smith S. A global optimisation method for robust affine registration of brain images. Medical Image Analysis. 2001;5:143–56. doi: 10.1016/s1361-8415(01)00036-6. [DOI] [PubMed] [Google Scholar]
  22. Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage. 2002;17:825–841. doi: 10.1016/s1053-8119(02)91132-8. [DOI] [PubMed] [Google Scholar]
  23. Joels M, Pu Z, Wiegert O, Oitzl MS, Krugers HJ. Learning under stress: how does it work? Trends in Cognitive Sciences. 2006;10:152–8. doi: 10.1016/j.tics.2006.02.002. [DOI] [PubMed] [Google Scholar]
  24. Hamann SB. Sex Differences in the Responses of the Human Amygdala. The Neuroscientist. 2005;11:288–93. doi: 10.1177/1073858404271981. [DOI] [PubMed] [Google Scholar]
  25. Kensinger EA, Corkin S. Effect of negative emotional content on working memory and long-term memory. Emotion. 2003;3:378–93. doi: 10.1037/1528-3542.3.4.378. [DOI] [PubMed] [Google Scholar]
  26. Kirschbaum C, Hellhammer DH. Salivary cortisol in psychoneuroendocrine research: recent developments and applications. Psychoneuroendocrinology. 1994;19:313–333. doi: 10.1016/0306-4530(94)90013-2. [DOI] [PubMed] [Google Scholar]
  27. Kirschbaum C, Pirke KM, Hellhammer DH. The ‘Trier Social Stress Test’–a tool for investigating psychobiological stress responses in a laboratory setting. Neuropsychobiology. 1993;28:76–81. doi: 10.1159/000119004. [DOI] [PubMed] [Google Scholar]
  28. Kriegeskorte N, Simmons WK, Bellgowan PS, Baker CI. Circular analysis in systems neuroscience: the dangers of double dipping. Nature Neuroscience. 2009;12:535–40. doi: 10.1038/nn.2303. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Lang PJ, Bradley MM, Cuthbert BN. International Affective Picture System (IAPS): Instruction Manual and Affective Ratings. 2001. Technical report A-5. The Center for Research in Psychophysiology, University of Florida. [Google Scholar]
  30. Luethi M, Meier B, Sandi C. Stress effects on working memory, explicit memory, and implicit memory for neutral and emotional stimuli in healthy men. Frontiers in Behavioral Neuroscience. 2008;2:5. doi: 10.3389/neuro.08.005.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Lupien SJ, Gillin CJ, Hauger RL. Working memory is more sensitive than declarative memory to the acute effects of corticosteroids: a dose-response study in humans. Behavioral Neuroscience. 1999;113:420–30. doi: 10.1037//0735-7044.113.3.420. [DOI] [PubMed] [Google Scholar]
  32. Mao ZM, Arnsten AF, Li BM. Local infusion of an alpha-1 adrenergic agonist into the prefrontal cortex impairs spatial working memory performance in monkeys. Biological Psychiatry. 1999;46:1259–65. doi: 10.1016/s0006-3223(99)00139-0. [DOI] [PubMed] [Google Scholar]
  33. McEwen BS. Sleep deprivation as a neurobiologic and physiologic stressor: Allostasis and allostatic load. Metabolism. 2006;55:S20–3. doi: 10.1016/j.metabol.2006.07.008. [DOI] [PubMed] [Google Scholar]
  34. Mitchell DG, Luo Q, Mondillo K, Vythilingam M, Finger EC, Blair RJ. The interference of operant task performance by emotional distracters: an antagonistic relationship between the amygdala and frontoparietal cortices. NeuroImage. 2008;40:859–68. doi: 10.1016/j.neuroimage.2007.08.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Morey RA, Dolcos F, Petty CM, et al. The role of trauma-related distractors on neural systems for working memory and emotion processing in posttraumatic stress disorder. Journal of Psychiatric Research. 2009;43:809–17. doi: 10.1016/j.jpsychires.2008.10.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Oei NY, Everaerd WT, Elzinga BM, van Well S, Bermond B. Psychosocial stress impairs working memory at high loads: an association with cortisol levels and memory retrieval. Stress. 2006;9:133–41. doi: 10.1080/10253890600965773. [DOI] [PubMed] [Google Scholar]
  37. Oei NY, Tollenaar MS, Elzinga BM, Spinhoven P. Propranolol reduces emotional distraction in working memory: a partial mediating role of propranolol-induced cortisol increases? Neurobiology of Learning and Memory. 2010;93:388–95. doi: 10.1016/j.nlm.2009.12.005. [DOI] [PubMed] [Google Scholar]
  38. Oei NY, Tollenaar MS, Spinhoven P, Elzinga BM. Hydrocortisone reduces emotional distracter interference in working memory. Psychoneuroendocrinology. 2009;34:1284–93. doi: 10.1016/j.psyneuen.2009.03.015. [DOI] [PubMed] [Google Scholar]
  39. Onur OA, Walter H, Schlaepfer TE, et al. Noradrenergic enhancement of amygdala responses to fear. Social Cognitive and Affective Neuroscience. 2009;4:119–26. doi: 10.1093/scan/nsn049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Perlstein WM, Elbert T, Stenger VA. Dissociation in human prefrontal cortex of affective influences on working memory-related activity. Proceedings of the National Academy of Sciences USA. 2002;99:1736–41. doi: 10.1073/pnas.241650598. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Pessoa L, Padmala S, Morland T. Fate of unattended fearful faces in the amygdala is determined by both attentional resources and cognitive modulation. NeuroImage. 2005;28:249–55. doi: 10.1016/j.neuroimage.2005.05.048. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Poldrack RA. Region of interest analysis for fMRI. Social Cognitive and Affective. Neuroscience. 2007;2:67–70. doi: 10.1093/scan/nsm006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Putman P, Hermans EJ, Koppeschaar H, van Schijndel A, van Honk J. A single administration of cortisol acutely reduces preconscious attention for fear in anxious young men. Psychoneuroendocrinology. 2007;32:793–802. doi: 10.1016/j.psyneuen.2007.05.009. [DOI] [PubMed] [Google Scholar]
  44. Qin S, Hermans EJ, van Marle HJ, Luo J, Fernandez G. Acute psychological stress reduces working memory-related activity in the dorsolateral prefrontal cortex. Biological Psychiatry. 2009;66:25–32. doi: 10.1016/j.biopsych.2009.03.006. [DOI] [PubMed] [Google Scholar]
  45. Ramos BP, Arnsten AF. Adrenergic pharmacology and cognition: focus on the prefrontal cortex. Pharmacology and Therapeutics. 2007;113:523–36. doi: 10.1016/j.pharmthera.2006.11.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Ramos BP, Colgan L, Nou E, Ovadia S, Wilson SR, Arnsten AF. The beta-1 adrenergic antagonist, betaxolol, improves working memory performance in rats and monkeys. Biological Psychiatry. 2005;58:894–900. doi: 10.1016/j.biopsych.2005.05.022. [DOI] [PubMed] [Google Scholar]
  47. Schoofs D, Preuss D, Wolf OT. Psychosocial stress induces working memory impairments in an n-back paradigm. Psychoneuroendocrinology. 2008;33:643–53. doi: 10.1016/j.psyneuen.2008.02.004. [DOI] [PubMed] [Google Scholar]
  48. Schwabe L, Wolf OT. Stress prompts habit behavior in humans. Journal of Neuroscience. 2009;29:7191–8. doi: 10.1523/JNEUROSCI.0979-09.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Shin LM, Rauch SL, Pitman RK. Amygdala, medial prefrontal cortex, and hippocampal function in PTSD. Annals of the New York Academy of Sciences. 2006;1071:67–79. doi: 10.1196/annals.1364.007. [DOI] [PubMed] [Google Scholar]
  50. Smith SM. Fast robust automated brain extraction. Human Brain Mapping. 2002;17:143–55. doi: 10.1002/hbm.10062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Smith SM, Jenkinson M, Woolrich MW, et al. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage. 2004;23 (Suppl 1):S208–19. doi: 10.1016/j.neuroimage.2004.07.051. [DOI] [PubMed] [Google Scholar]
  52. Spielberger CD. Manual for the State-Trait Anxiety Inventory (STAI) Palo Alto, CA: Consulting Psychologists Press; 1983. [Google Scholar]
  53. Sternberg S. High-speed scanning in human memory. Science. 1966;153:652–4. doi: 10.1126/science.153.3736.652. [DOI] [PubMed] [Google Scholar]
  54. van Marle HJ, Hermans EJ, Qin S, Fernandez G. From specificity to sensitivity: how acute stress affects amygdala processing of biologically salient stimuli. Biological Psychiatry. 2009;66:649–55. doi: 10.1016/j.biopsych.2009.05.014. [DOI] [PubMed] [Google Scholar]
  55. Wechsler D. Wechsler Adult Intelligence Scale. 3rd edn. San Antonio: The Psychological Corporation; 1997. [Google Scholar]
  56. Woolrich MW, Ripley BD, Brady M, Smith SM. Temporal autocorrelation in univariate linear modeling of FMRI data. NeuroImage. 2001;14:1370–86. doi: 10.1006/nimg.2001.0931. [DOI] [PubMed] [Google Scholar]
  57. Woolrich MW, Behrens TE, Beckmann CF, Jenkinson M, Smith SM. Multilevel linear modelling for FMRI group analysis using Bayesian inference. NeuroImage. 2004;21:1732–47. doi: 10.1016/j.neuroimage.2003.12.023. [DOI] [PubMed] [Google Scholar]

Articles from Social Cognitive and Affective Neuroscience are provided here courtesy of Oxford University Press

RESOURCES