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The Influence of Work-Related Chronic Stress on the
Regulation of Emotion and on Functional Connectivity in
the Brain
Armita Golkar
1
, Emilia Johansson
1
, Maki Kasahara
1
, Walter Osika
1,2
, Aleksander Perski
3
, Ivanka Savic
4
*
1Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden, 2Center for Social Sustainability, Department of Neurobiology, Care Sciences and Society,
Karolinska institute, Stockholm, Sweden, 3Stress Research Institute, Stockholm University, Stockholm, Sweden, 4Department of Women’s and children’s health, and
Neurology Clinic, Karolinska Institute and Hospital, Stockholm, Sweden
Abstract
Despite mounting reports about the negative effects of chronic occupational stress on cognitive and emotional functions,
the underlying mechanisms are unknown. Recent findings from structural MRI raise the question whether this condition
could be associated with a functional uncoupling of the limbic networks and an impaired modulation of emotional stress.
To address this, 40 subjects suffering from burnout symptoms attributed to chronic occupational stress and 70 controls
were investigated using resting state functional MRI. The participants’ ability to up- regulate, down-regulate, and maintain
emotion was evaluated by recording their acoustic startle response while viewing neutral and negatively loaded images.
Functional connectivity was calculated from amygdala seed regions, using explorative linear correlation analysis. Stressed
subjects were less capable of down-regulating negative emotion, but had normal acoustic startle responses when asked to
up-regulate or maintain emotion and when no regulation was required. The functional connectivity between the amygdala
and the anterior cingulate cortex correlated with the ability to down-regulate negative emotion. This connectivity was
significantly weaker in the burnout group, as was the amygdala connectivity with the dorsolateral prefrontal cortex and the
motor cortex, whereas connectivity from the amygdala to the cerebellum and the insular cortex were stronger. In subjects
suffering from chronic occupational stress, the functional couplings within the emotion- and stress-processing limbic
networks seem to be altered, and associated with a reduced ability to down-regulate the response to emotional stress,
providing a biological substrate for a further facilitation of the stress condition.
Citation: Golkar A, Johansson E, Kasahara M, Osika W, Perski A, et al. (2014) The Influence of Work-Related Chronic Stress on the Regulation of Emotion and on
Functional Connectivity in the Brain. PLoS ONE 9(9): e104550. doi:10.1371/journal.pone.0104550
Editor: Daniel Margulies, Max Planck Institute for Human Cognitive and Brain Sciences, Germany
Received March 6, 2014; Accepted July 11, 2014; Published September 3, 2014
Copyright: ß2014 Golkar et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. Relevant data are included within the
Supporting Information files.
Funding: The Swedish Council for Working Life and Social Research (FAS), the Swedish Research Council, and VINNOVA are acknowledged for their financial
support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* Email: ivanka.savic-berglund@ki.se
Introduction
Stress is common and hard to avoid. When stress becomes
chronic, it may have negative effects on cognitive functioning and
even lead to psychiatric conditions such as anxiety and depression
[1–2]. In recent years, the mounting reports about occupational
stress and the substantial costs for society that are associated with
it, mainly due to impaired mental health, have been gaining more
attention [3]. These worldwide reports signal the pressing need for
scientific investigations of the underlying pathophysiological
mechanisms.
Cognitive and emotional dysfunctions attributed to
occupational stress – ‘the burnout syndrome’
Occupational ‘burnout’ is characterized by stress-related
symptoms among otherwise healthy and high-performing persons
who report that they have not experienced any major negative life
events [4–8]. The described symptoms are attributed to occupa-
tional stress. They are stereotyped, and include memory and
concentration problems, sleeplessness, diffuse aches, profound
fatigue, irritability, anxiety, and a feeling of being emotionally
drained. The underlying mechanisms are largely unknown.
Measurements of cortisol levels after awakening in these subjects
have hitherto yielded inconclusive results [9], with reports of
normal [10–11], reduced [12–15], and elevated levels [16–18].
Recent data from brain imaging studies, although still limited,
suggest, however, that burnout from occupational stress is
associated with an affection of the limbic structures, the amygdala,
and the mesial prefrontal cortex (mPFC), in particular [19–23].
These initial findings call for further research, considering the
amygdala’s key role in evoking stress responses [24–25] and
considering that the regulation of stress responses during
emotional conflict is processed via functional connectivity between
the amygdala and the mPFC and anterior cingulate cortex (ACC)
[26–30]. During the cognitive reappraisal of emotion, it has, for
example, been demonstrated that the activity of the amygdala is
down-regulated (measured as change in BOLD signal), whereas
the activity in portions of the lateral and medial prefrontal cortex is
upregulated [31–36]. Moreover, it was recently shown that the
ability to cognitively down- regulate negative emotion was severely
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jeopardized after stress exposure [37]. It is, thus, possible that
subjects reporting cognitive and emotional dysfunction due to
chronic occupational stress could have an impaired ability to
modulate emotional stress and emotionally stressful stimuli,
rendering them less apt to cope with psychosocial stress.
Furthermore, in these individuals, the amygdala connectivity with
the mPFC and ACC, and perhaps also to the hippocampus and
the insular cortex, could have undergone alterations. Such changes
could constitute a stress vulnerability factor, or be a consequence
of prolonged occupational stress. Both scenarios would be in line
with our previous observations of structural and neuroreceptor
changes along the limbic circuits in affected subjects [20–23].
These limbic changes, and their apparent overlap with the
networks that are reported to be involved in emotional regulation
led us to design a combined behavioral and MR study to test two
specific hypothesis: (1) That subjects suffering from occupational
stress have an impaired ability to modulate stressful emotions; and
(2) That these subjects show altered amygdala functional
connectivity. To test these, forty subjects with occupational
burnout along with seventy unstressed healthy controls were
investigated using a cognitive emotion regulation task as well as
resting state fMRI.
Emotion regulation and the acoustic startle reflex
In order to assess emotion regulation, we measured the
magnitude of the fear-potentiated startle reflex, which is a highly
conserved, fast defensive reflex that consists of a series of muscular
contractions and is mediated by a well-characterized neural
circuitry [38–39]. In humans, this reflex can be elicited by a
sudden and intense auditory stimulus (acoustic startle probe). The
amplitude of this reflex is measured through facial electromyog-
raphy (EMG), [40], and is potentiated when the individual is in an
aversive or fearful state [41]. The startle reflex is a reliable and
well-validated measure of emotion modulation [40] and has
previously been successfully used as an index of cognitive emotion
regulation in a healthy population [42–43].
In the present study the acoustic startle reflex was measured to
investigate possible group differences in emotional reactions to
negative visual stimuli and in the ability to regulate negative
emotion. We also measured functional resting state connectivity
from the amygdala, paying special attention to the connectivity to
other nodes of the limbic system and to the mPFC and ACC in
particular. In addition, a possible association between the ability to
modulate emotion and the resting state functional connectivity was
tested with linear regression analysis.
Methods
Participants
Forty right-handed [44] subjects (27 females; age 3866 years,
range 19–46 years; education 1763 years), who had been
diagnosed as having a ‘reaction to severe stress and an adjustment
disorder’ according to the International Classification of Diseases
(ICD-10, F43), were recruited from the Stress Research Institute at
Stockholm University. The selection was limited to subjects who
attributed their illness to prolonged work-related stress, after
working 60 to 70 hours per week continuously over several years
prior to the onset of symptoms. Inclusion criteria consisted of a
characteristic symptom course of sleeplessness, diffuse aches,
palpitations and fatigue, a subsequent onset of irritability, anxiety,
memory and concentration problems, feeling of depersonalization,
and reduced work capacity (confirmed by the employers) [8],[19].
All of the subjects attributed their symptoms to chronic stress and
had no other known etiology for their distress.
Subjects were also required to have had a symptom duration of
at least one year (their histories of stress-related burnout symptoms
ranged from 1.5 to 3.5 years), to have been on sick leave ($50%)
for stress-related symptoms for a minimum of 6 months before
entering the study, and to have an average stress-burnout score of
$3.0 on the Maslach Stress-Burnout Inventory – General Survey
(MBI-GS) [45]. This 7-point rating scale, ranging from 0 (never) to
6 (daily), consists of three subscales: exhaustion (five items),
cynicism (five items) and lack of professional efficacy (six items).
When rating perceived stress, subjects were asked to take into
consideration the last six months, and not only the actual time-
point. The average scores for Scandinavian populations are
around 2 for MBI-GS [4],[46].
Subjects were excluded if they had a previous history of
psychosis, personality disorder, major or bipolar depression,
alcohol or substance abuse, chronic fatigue, chronic pain,
fibromyalgia, or neurological or endocrine disease. Those who
had experienced prominent stress factors in their private life or a
major traumatic event at any time in their life, including sexual
abuse, were also excluded. No daily medication was allowed
during the two months prior to the study, except contraceptives.
According to a review of their pharmacological treatment
histories, none of them had taken drugs that are known to affect
brain structure (e.g., psychopharmaca). Subjects who were sleep
deprived the night before the scan/testing procedures were
rescheduled, in order to exclude the acute effects of sleep
deprivation.
Seventy healthy, right-handed, non-smoking volunteers (45
females; age 3366 years, range 24–45 years; education 1763
years) with no history of chronic stress or heredity for neuropsy-
chiatric disorders comprised the control group. The patient and
control groups had similar gender distributions, and both were
predominately female to accord with the female-dominated
epidemiology of the condition studied [4].
The two groups were matched for socioeconomic status assessed
on the basis of years of education, type of occupation, and
organizational position (employee, middle management, supervi-
sor). The study was approved by the Ethics Committee at the
Karolinska Institute and written informed consent was received
from each participant.
Before the interview, participants completed questionnaires in
order to evaluate their stress symptoms and assess their previous
life events [47]. In addition, the occurrence of major life events
among the subjects was assessed through a clinical psychiatric
interview based on the non-work-related items of the Holmes and
Rahe Scale [48]. The participants were asked to answer yes or no
to whether they had experienced any non-work- related stressful
life events (e.g., death of a relative or spouse, recent divorce, forced
family relocation). Subjects were excluded if they answered
positively to having experienced such an event in their lives.
Patients also received a medical screening (physical examination,
test of thyroid and liver function). A structured interview, the
Swedish version of the Mini-International Neuropsychiatric
Interview, MINI [49] was performed, along with a test for
depression using the Montgomery-Asberg Depression Rating
Scale [50]. Although some subjects had high scores in the
MADRS they did not fulfill the MINI criteria for depression, and
were therefore not excluded.
Out of the participants who matched the inclusion criteria, 8
subjects with occupational burnout and 9 controls failed to display
a startle response to the probe. The results from the emotion
regulation experiment and the correlation analyses with fMRI are
therefore based on data from the remaining 32 subjects with
occupational burnout (20 females; mean age = 37.6 years,
Effect of Stress on Emotion Regulation and Brain Connectivity
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SD = 6.5) and 61 controls (33 females; mean age = 30.9 years,
SD = 6.7), whereas the analysis of resting state amygdala
connectivity is based on the entire study group.
Salivary cortisol
Salivary cortisol was sampled according to a previously
established protocol [51]. Saliva sampling was chosen because
the method is simple, non-invasive, and non- stressful; the samples
are shown to readily reflect the levels of the free fraction of cortisol
in plasma [52]. Participants were instructed carefully on how to
collect their own salivary samples. Samples were collected seven
times on an ordinary weekday using Salivette cotton rolls (Sarstedt,
Rommelsdorf, Germany), which participants were instructed to
place in the mouth for 2 minutes. The first sample was collected
immediately upon awakening in the morning, irrespective of time.
The second sample was collected 15 minutes later, before eating
or brushing teeth, and the third sample was collected 15 minutes
after that. The fourth sample was collected around noontime,
before lunch. The fifth sample was collected at about 3 p.m., the
sixth at 8 p.m., and the seventh at bedtime, after having rested in
bed for 15 minutes, before falling asleep. The samples were frozen
(218uC) until analyzed. The levels of salivary cortisol were
measured with radioimmunoassay using the Spectria (
125
I) coated
tubes radioimmunoassay kit (Orion Diagnostica, FIN-02101
Espoo, Finland). The within-assay coefficients of variation ranged
from 0.8 to 0.9, and those between assays never exceeded 10
percent. All samples from each group were analyzed simulta-
neously in duplicate.
Emotion regulation task
Before the experiment, the participants were given written as
well as verbal explanations of the task and instructions. Partici-
pants were informed that they would receive three different
instructions during the experiment and that these instructions
would be symbolically represented by three different arrows: (1) an
upward arrow indicated that the participant should make an effort
to reinforce the feelings that are elicited by the picture, so that he/
she experiences the image as more emotionally charged (‘‘up-
regulate’’); (2) a horizontal arrow indicated that the participant
should focus on the feeling the picture elicits, without trying to
manipulate the emotion (‘‘maintain’’); and (3) a downward arrow
indicated that the participant should make an effort to down-
regulate the feelings that the picture elicits, so that he/she
experiences the image as less emotionally charged, or as neutral as
possible (‘‘down-regulate’’). Participants were thoroughly informed
of the importance of following the instructions during the
experiment and not distracting themselves from their feelings by
thinking of something else or by looking away from the image or
closing their eyes. The subjects were however free to choose the
strategy to regulate their emotion.
The experiment began with a practice session during which the
participants were first subjected to the auditory startle probe six
times to allow for habituation to the sound. This was followed by
twelve practice trials that mirrored the experimental procedure.
After the practice session, the participants were asked to describe
the strategy they had used to regulate emotion. None of the
participants reported that they were confused about how to adopt
a reappraisal strategy for the neutral and negative trials before or
after completing the experimental task.
An example of an experimental trial is shown in Figure 1.
During each trial, the participant was presented with a picture for
5 s, which was then replaced by an instruction cue for 1 s. For
negative pictures, participants were instructed to suppress (down-
regulate), enhance (up-regulate) or maintain their emotional
response. Based on previous work [42] and to avoid confusion
due to ambiguous instructions (e.g., to suppress emotional
reactions to neutral pictures), neutral pictures were only coupled
with the instruction to maintain the emotional response. Imme-
diately following the instruction cue, the same picture was
presented again for 5 s, during which time the participants carried
out the regulation instruction. During each trial, startle probes
were presented 3 s after picture onset during the first (pre-
instruction) and the second (post-instruction) picture-viewing
phases. Lastly, the participants were given 4 s to rate on a scale
of 1–7 how well they had managed to carry out the instructions.
Between each trial, a fixation cross was presented for 4–6 s (mean
5 s). Each trial lasted for 20 s. There were 60 trials, and the entire
testing session lasted approximately twenty minutes, with a 15-
second pause after the first 30 trials. The presentation of pictures
was synchronized with the monitor’s refresh rate and presented
with the software Presentation (Neurobehavioural systems, www.
neurobs.com).
Material
We selected three sets of 15 negative pictures and one set of 15
neutral pictures from the International Affective Picture Set (IAPS)
[53]. Each of the three sets of negative pictures was assigned to one
of the three task instructions (maintain, down-regulate, up-
regulate), and this assignment was counterbalanced between
participants (male and female controls, and patients). Pictures
were selected to match valence and arousal scores of pictures used
in a similar report [54].
Electromyographic recordings: response definition and
data reduction
The eye-blink component of the startle response was measured
through electromyographic (EMG) recordings of the left orbicu-
laris oculi muscle using two miniature Ag/AgCl electrodes
prepared with electrolyte gel. A third ground electrode was placed
behind the left ear over the mastoid. Startle probes were 50-ms
bursts of approximately 95-db[A] white noise with a near
instantaneous rise time (,1 ms), delivered through sound-proof
headphones (Bose AE21, Bose Co. Framingham, Massachusetts).
The raw EMG signal was amplified and filtered through a 28–
50 Hz bandpass filter, rectified and integrated with a time
constant of 20 ms. Startle eye-blink magnitude (microvolts) was
measured as the amplitude from onset to peak, and trials with
excessive baseline activity or recording artifacts were rejected. To
assess initial, unaltered startle responses, pre-instruction (Startle 1)
startle scores for negative and neutral images were normalized
using z-standardization to ensure that all participants contributed
equally to the group means, as has been described previously [55–
56]. The z-score calculation is a within-individual normalization,
resulting in a distribution with an overall mean of 0 and a standard
deviation of 1 for each participant. To assess the regulation of the
startle response according to instruction, for each participant, we
calculated the change in startle response by subtracting the raw
startle 1 response from the raw startle 2 response separately for
each instruction (maintain neutral, maintain negative, down-
regulate negative, up-regulate negative) of the task. This way, we
defined emotion regulation ability as the magnitude during
emotion regulation controlling for baseline levels before the
regulation cues.
Statistical analyses
Initial startle reactions were assessed in a 262 repeated
measures analysis of variance (ANOVA) with Valence (Negative,
Effect of Stress on Emotion Regulation and Brain Connectivity
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Neutral) as a within-subjects variable and Group (Burnout,
Control) as a between subjects variable. To test the hypothesis
that burnout patients would differ from controls in their startle
responses during down-regulation of negative emotion, we ran a
262 repeated measures ANOVA with Instruction (Down-regulate,
Maintain) as the within-subject variable and Group (Burnout,
Control) as the between-subject variable. As a control, we similarly
assessed whether there were any group differences in startle
responses during up-regulation of negative emotions in a 2 (Up-
regulate, Maintain)62 (Burnout, Control) repeated-measures
ANOVA. Possible group difference in salivary cortisol levels was
tested with a repeated measure ANOVA (p,.05).
fMRI data acquisition
MR experiments were carried out on a separate day to avoid
contamination by possible effects of the emotional regulation tasks.
Functional MRI time series data were collected from all of the
participants at rest over 8 minutes in a 3 Tesla MR scanner
Discovery 750 (GE Healthcare), using a 32-channel head coil.
Resting fMRI blood oxygenation-level dependent (BOLD) data
were acquired in a standard gradient echo-planar-imaging (EPI)
acquisition, TR = 2.5 s, TE = 30 ms, flip angle = 90u, resolu-
tion = 36363 mm, whole-head coverage. The participants were
asked to lie with their eyes closed, to think of nothing in particular,
and not to fall asleep. Structural brain images were acquired using
a T1-weighted 3D brain imaging volume imaging sequence with
whole-head coverage, TR = 7.91 s, TE = 3.06 s, flip angle = 12u,
and resolution 16161 mm. These structural images were used to
aid the registration of the functional data into a common standard
brain coordinate system (MNI152).
Seed region analysis
Seed region analysis is based on calculating cross-correlation
coefficients of the time series in a particular seed region-of-interest
(ROI) with all other voxels in the brain, which reveals the strength
of functional connectivity with respect to this seed region [57]. The
seed regions consisted of the right and left amygdala, and were
delineated with the guidance of the WFU-pick atlas, and after
adaptation to the gray matter template of our own population.
The MNI coordinates for the amygdala seeds where (sphere of
5 mm radius, co-ordinate 222, 27219, and 22 27219); the
seed regions covered the amygdala, with the exception of the most
medial 2 mm of the basomedial amygdala, which was excluded to
avoid the susceptibility artifact that was detected in some subjects.
Given the amygdala’s pivotal role in stress perception, we first
evaluated whether and how the functional connectivity from the
amygdala seeds differed between patients and controls. We then
used multiple regression analysis to investigate whether the degree
of perceived stress interacted with the pattern of connectivity from
the amygdala seed. Spatial preprocessing and statistical analysis of
functional images were performed using SPM8 (Welcome
Department of Cognitive Neurology). Functional images were
slice-timed and realigned, and then registered to structural T1
SPGR (spoiled gradient) images for each subject. Next, the
individual T1 SPGR images were segmented into gray matter,
white matter, and cerebrospinal fluid, and the gray matter image
was used to determine the parameters of normalization for the
standard Montreal Neurological Institute gray matter template.
The spatial parameters were then applied to the slice-timed and
realigned functional volumes that were finally resampled to
26262 mm voxels and smoothed with a 6-mm full-width at
half-maximum kernel. Each voxel’s time series was corrected for
noise using standard resting-state low-pass filtering with a cut-off
frequency of 0.1 Hz. In addition, voxel-wise multidimensional
regression analysis was employed in a standardized manner to
remove artifacts due to motion and changes in ventricle and white
matter signals. This was done by adding six movement regressors
obtained from rigid-body head motion correction (SPM 8
statistical package). Segmented WM (white matte) and CSF
(cerebro spinal fluid) were used as ROI for correction of signals
from non-gray matter tissue. To ensure that signals from WM and
CSF ROIs did not contain signals from gray matter, these ROIs
were superimposed on the individual EPIs and, when needed,
adapted to the respective subject, based on intensity differences
between white matter, gray matter, and ventricular regions.
Global signal correction was not employed, as it has been reported
that regression against the global signal may artificially introduce
Figure 1. Overview of one experimental trial with the maintain instruction. Participants were presented with a picture, which was replaced
by an instruction cue. For negative picture trials, this cue indicated whether the participants’ task was to maintain (horizontal arrow), down- regulate
(downward arrow) or enhance (upward arrow) their emotional response. Immediately following the instruction cue, participants implemented the
regulation instruction while being exposed to the same picture again. Lastly, participants rated how well they managed to implement the regulation
instruction on a scale of 1–7.
doi:10.1371/journal.pone.0104550.g001
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anticorrelations into fMRI data sets [58]. For each subject, the
average fMRI time course within the seed region was used as the
regressor of interest. Individual time series in each seed region
were extracted with MarsBar toolbox (http://marsbar.
sourceforge.net/). Each subject’s seed region time course was
then regressed voxel-wise against the subject’s fMRI time course
using the entire brain as search space. The t-values of the
corresponding regression coefficients at each voxel were used as
each subject’s connectivity map.
Statistical analysis
Group comparisons between stressed subjects and healthy
controls were carried out in SPM8 using one-way ANOVA, with
p,.001 voxel threshold, FWE corrected at cluster level, p,.05,
and controlling for age and gender, which were used as nuisance
covariates.
Results
Demographics
No group differences were found with regard to education or
gender distribution. The controls were younger than the stressed
subjects (Table 1). The subjects with occupational burnout scored
significantly higher on the MBI-GS scale (3.860.8 vs. 2.560.7
p = .001; F = 64.3) as well as on the MADRS (16.865.5 vs.
3.863.8; p = .001, F = 206.8) (Table 1). However, no group
difference was detected in cortisol levels (p = .56, F = .08).
Emotion regulation task
To verify that the data could be collapsed across female and
male controls, we first confirmed that there was no significant
difference between female and male controls in their initial startle
response to negative and neutral pictures (Valence6Group
interaction: F(1,30) = .13, p = .72). Furthermore, no sex differences
were found regarding the startle response to negative and neutral
pictures across instructions (Instruction6Group interaction: F
(2,60) = 2.23, p = .12). Because no significant differences were
detected between male and female controls, all of the comparisons
with the subjects with burnout were based on data from the entire
gender-mixed control group.
The burnout group and control group did not differ in their
initial startle response to negative and neutral pictures (Main effect
of Valence: F(1,91) = 39.97, p,.001; Valence6Group interaction:
F,1); both groups showed significantly higher startle responses to
negative images than to neutral images (burnout: t(31) = 3.87,
p = .001; control: t(60) = 5.65, p,.001). However, group differ-
ences emerged in the emotional regulation task (see Figure 2). A
262 repeated measures ANOVA with Instruction (Down-regulate,
Maintain) as the within-subject variable and Group (burnout,
control) as the between-subject variable revealed that the burnout
population showed overall higher startle responses across instruc-
tions (Main effect of Instruction: F(1,91) = 16.32, p,.001 and
Group, F(1,91) = 5.55, p = .02). As predicted, follow-up analysis
revealed that compared to the controls, the startle response among
the burnout patients was significantly higher during negative
down-regulation, [t(91) = 2.38, p = .02], but did not reach signif-
icance during the negative maintain instruction, [t(91) = 1.55,
p = .13]. No significant group difference in startle response was
detected during the up-regulate negative condition,
[F(1,91) = 6.04, p = .02], or during the maintain neutral condition
[t(91) = .06; p = .96]. Lastly, we compared the emotion regulation
success ratings of the burnout patients and the controls (see
Figure 3). The burnout patients differed from the controls
(Instruction6Group: F(2,160) = 4.63, p = .01): the burnout patients
had overall lower success ratings after viewing negative images, an
effect that was particularly pronounced with regard to being
instructed to down-regulate [t(80) = 4.70, p,.001] and maintain
negative emotion [t(80) = 3.12, p = .003] but that did not reach
significance for up-regulation of negative emotion [t(80) = 1.77;
p = .08]. These results parallel those observed with the startle
response. Critically, there were no differences between groups with
respect to rating after viewing neutral images [t(80) = .94, p = .35].
To test for possible effects of stress (MBI-GS) and depression
(MADRS) scores on the ability to down-regulate negative emotion,
two separate correlational analyses were run (Pearsson’s linear
correlation analysis). Bonferroni correction was not employed
Table 1. Demographics.
Stressed subjects (n = 40) Controls (n = 70) P and F values
Age (years) 38.266.8 33.265.8 p = 0.00 F = 17.4
Education (years) 16.963.4 16.862.9 p = 0.88 F = 0.22
MBI- GS (score) 3.860.8 2.560.7 p = 0.00 F = 64.3
Nexhaustion 4.461.1 1.260.8 p = 0.00 F = 269.0
Ncynicism 3.361.3 1.361.0 p = 0.00 F = 75.6
MADRS (score) 16.865.5 3.863.8 p = 0.00 F = 206.8
Cortisol sample 1 15.8612.6 5.763.9 p = 0.86 F = 0.33
Cortisol sample 2 24.2615.7 15.268.5 p = 0.78 F = 0.08
Cortisol sample 3 22.9614.9 20.3612.2 p = 0.17 F = 1.92
Cortisol sample 4 8.8610.0 23.1616.2 p = 0.96 F = 0.00
Cortisol sample 5 5.863.5 9.7613.9 p = 0.73 F = 0.12
Cortisol sample 6 3.664.3 3.764.9 p = 0.92 F = 0.01
Cortisol sample 7 4.2610.8 2.663.9 p = 0.33 F = 0.86
Age and education are expressed in years; MBI-GS is a questionnaire to score perceived work-related stress. Raw 3 indicates the mean total score, raw 4–5 the sub-scores
for the exhaustion and cynicism. MADRS = Montgomery Asberg Depression Scale. There was no overall group difference in cortisol levels (p = 0.56; F = 0.08, repeated
measure ANOVA). Time of the day for cortisol samples: Sample 1: 06.30–07.30; Sample 2: 15 minutes after sample 1; Sample 3: 30 minutes after sample 1; Sample 4:
12.00–13.00; Sample 5: 15.00–16.00; Sample 6: 20.00–21.00. Sample 7: 22.30–23.30.
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because significant correlations were hypothesized for both score
types. Correlation analyses were carried out using both groups,
and also within each separate group. Both higher stress scores
(MGI-GS: r = 22, p = .02) and higher depression scores (MADRS:
r = . 37, p = .02) were related to a decreased ability to down-
regulate negative emotion, as indexed by higher differential startle
responses during the negative down-regulation condition. How-
ever, neither of these scores correlated with the differential startle
responses during down-regulation of negative emotion within the
burnout or control groups (both p’s..1).
Seed region fMRI connectivity
There was a significant difference between stressed subjects and
controls with respect to functional connectivity of the right and left
amygdala. Stressed subjects showed significantly weaker correla-
tions with clusters in the mPFC, the dorsolateral prefrontal cortex
(dlPFC), and the motor cortex, whereas their functional connec-
tivity during resting state with clusters in the cerebellum (vermis
cerebelli and the anterior cerebellum in particular) and the insular
cortex were stronger than in controls (Table 2, Figure 4a and 4b,
clusters calculated at p = .001, cluster level FWE correction at p,
.05). These differences were constitutes by differences in positive
connectivity and not anticorrelations (please see Figure 4c, which
shows within group connectivity patterns).
Post hoc analyses
Because the co-variation pattern from the amygdala differed
between the two groups of participants, we explored if this could
be related to degree of perceived stress or, perhaps, to the
MADRS scores. Each subject’s MGI-GS and MADRS scores
were, therefore, regressed on the individual connectivity maps
from the right and left amygdala seed (voxel threshold corre-
sponded to p = .001, FWE cluster correction at p,.05). In
addition, given the pivotal role of the mPFC and the ACC in
emotional regulation, we tested in the same manner whether the
ability to down-regulate negative emotion could be linked to the
connectivity between the amygdala and these two regions. Because
this analysis was hypothesis based, we employed small volume
correction (FWE corrected peak level at p,.05), using a search
area defined by a box covering both the ACC and the mPFC,
according to Montreal Neurological Institutes (MNI) atlas, the
MNI co-ordinates x = 210 to 10; y = 16 to 66; z= 4 to 24.
Only correlational data from the entire study group (thus,
without subdivision into burnout subjects and controls) are
presented. The subject groups were too limited to allow
explorative calculations of possible group differences in the
interaction between functional connectivity and emotional regu-
lation or to investigate the respective correlations in each group
separately.
Figure 2. Comparison between burnout patients and controls regarding startle reactions across task instructions. The burnout group
displayed overall higher responses when implementing instructions during negative pictures and this pattern was particularly pronounced during
down- regulation of negative emotion. Note that the y-axis represents post-instruction response – pre- instruction response; * = p,.05.
doi:10.1371/journal.pone.0104550.g002
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The MBI-GS scores (total mean scores) were found to be
positively correlated to the functional connectivity between the left
amygdala and the insular cortex, and the thalamus (covering a
portion of the hypothalamus); the more pronounced the stress
perception, the stronger the functional connection was (Table 3,
Figure 5). The corresponding analysis involving the right amyg-
Figure 3. Comparison between burnout patients and controls regarding rated regulation success across task instructions.
The burnout group rated themselves as generally less successful at implementing the task instruction after viewing negative pictures. * = p,.05,
#=p,.1.
doi:10.1371/journal.pone.0104550.g003
Table 2. Group differences in functional resting state connections from the amygdala.
Region Z level Size, cm
3
Coordinates
Controls
.
stressed subjects, R amygdala
RPFC+motor cortex 3.8 3.2 44 6 34
Controls
.
stressed subjects, L amygdala
L mPFC+L dlPFC 4.3 4.8 248 20 10
218 50 22
Stressed subjects
.
controls, R amygdala
R insular cortex 4.2 4.0 44 14 2
L insular cortex 3.9 3.2 228 20 6
Cerebellum 4.1 8.0 222 222 228
26 232 226
Stressed subjects
.
controls, L amygdala
Cerebellum 4.3 3.3 222 244 228
Clusters calculated using voxel threshold at p = 0.001, cluster level FWE correction at p,0.05.
R = right; L = left. The cere bellar clusters covered the anterior cerebellum and the vermis.
doi:10.1371/journal.pone.0104550.t002
Effect of Stress on Emotion Regulation and Brain Connectivity
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dala did not show any significant clusters. There were no negative
correlations with the stress scores, nor any interactions with
MADRS scores. The ability to down-regulate negative emotion
was associated with an increased functional connection between
the right amygdala seed and the ACC (the MNI co-ordinate was 6
26 14, z = 3.6, p = .027, FWE corrected, small volume correction).
Discussion
The present study represents part of a larger effort to
characterize the potential neurobiological underpinnings of
occupational burnout, an increasingly reported condition in
Western societies. The finding that subjects suffering from chronic
occupational stress had an impaired ability to modulate emotion,
and weaker functional connectivity between the amygdala and the
mPFC (two key structures for orchestrating defensive reactions to
environmental threats including stress) supports our previous
notion that we are dealing with a condition affecting the limbic
system.
Notably, stressed subjects showed higher startle responses
specifically during down-regulation of negative emotion, whereas
no group difference was detected in the initial response to negative
images or in the startle response during up-regulation of negative
emotion. Cortisol response during the image presentation was not
specifically measured, and it was not possible to objectively verify
that the images eliciting negative emotions were perceived as
stressful. Such an association has, however, been documented in
several previous studies which showed increased cortisol levels as
well as increased skin conductance responses during the presen-
tation of negatively valenced IAPS images [59–60]. It is, therefore,
reasonable to assume that the higher startle response among the
burnout group during negative down-regulation reflected an
impaired ability to modulate a stressful emotion, although we
cannot exclude that this effect was accompanied by differences in
attentional resources required to perform the tasks Emotion
regulation, as well as stress relies on an intact functional
connection between the amygdala, the mPFC, and the ACC
[24],[35]. The presently detected functional disconnection be-
tween the amygdala and the mPFC in the burnout group as well as
the detected interaction between the ability to down-modulate
negative emotion and the amygdala–ACC connection confirm this
notion. These findings are in line with our previous observation
based on PET measurements of resting state connectivity [22],
although the methodology and participant sample were different.
They are also in accordance with the reduction of gray matter
volume in the dlPFC and ACC and the cortical thinning of the
mPFC observed in subjects suffering from occupational stress
[21],[23]. Taken together, these data support the postulation that
Figure 4. Group difference in resting state functional connectivity from the right amygdala (R amy). Red clusters were calculated from
the burnout group - control-group contrast (A), and blue clusters from the reverse contrast (B), (p,0.05 FWE corrected). Clusters are superimposed
on the grey matter template (in the MNI space) from the entire study group. (C) Within group connectivity (positive) from the right amygdala. Blue
clusters show connectivity clusters in controls, red clusters in the burnout group.
doi:10.1371/journal.pone.0104550.g004
Table 3. Functional resting state connections from the amygdala in relation to stress perception.
Region Z level Size, cm
3
Coordinates
L amygdala connectivity and MBI-GS
L hypothalamus+thalamus 3.9 1.5 28220 6
26266
L insular cortex 4.0 1.0 232 24 4
R amygdala connectivity vs MBI-GS
R insular cortex 3.7 3.0 36 22 0
The interaction with MBI-GS is calculated at voxel threshold corresponding to p = 0.001, cluster level FWE correction at p,0.05. R = right; L = left. There were no negative
covariations from the amygdala seed regions.
doi:10.1371/journal.pone.0104550.t003
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stress-processing limbic networks are affected in subjects suffering
from occupational burnout.
The cluster showing impaired functional connectivity from the
amygdala in the burnout population comprised portions of the
motor cortex, which may be due to the fact that our groups were
gender mixed. In men there are strong connectivity between the
amygdala and motor cortex, while women have strong connec-
tivity between the amygdala and both the mPFC and ACC [61].
Thus, assuming that the amygdala–frontal lobe connectivity were
impaired in both sexes among the burnout population, it is not
surprising that a cluster encompassing both the mPFC and the
motor cortex was observed when comparing the entire control
group with the entire burnout group.
The MGI-GS scores interacted with functional connectivity
between the amygdala, the thalamus, and a minor portion of the
hypothalamus (Figure 5); thus, the more stressed the subject, the
stronger the connectivity was. This finding is congruent with the
well-established finding that stress leads to the activation of the
HPA via amygdala connectivity with the paraventricular hypo-
thalamic nuclei. It also fits well with the notion that the insular
cortex relays stress signals from the amygdala to the autonomous
nervous system. The observance of a stress-related enhancement of
the amygdala–insular cortex connection is in accordance with
previous findings for other stress conditions [62].
The enhanced connectivity observed between the amygdala and
the cerebellum in the stressed group was, on the other hand, not
directly expected. Nevertheless, there are several previous reports
suggesting that cerebellum may have a modulatory role in the
processing of psychosocial stress. The amygdala relays the
emotional salience of incoming signals to the rest of the brain,
and via cholinergic connections to the pontine nuclei and the
cerebellum, the neuronal traffic from the amygdala leads to
increased arousal [24–25]. The cerebellum is part of the
amygdala’s resting state connectivity network [63], and via
inhibitory (GABAergic) output from Purkinje, the excitation of
the amygdala is modulated by the cerebellum. Via this ability to
modulate the excitation of the amygdala the cerebellum is involved
in the processing of emotion, and potentially also the psychosocial
stress. Interestingly, the cerebellum has dense glucocorticoid
binding sites as well as reciprocal monosynaptic connections to
the hypothalamus, that provide a biological substrate for the
regulation of HPA, and the stress response. Animal experiments
show an enlargement of Purkinje cell spines in response to
corticotropin-releasing factor [64]. The involvement of the
cerebellum in stress is also indicated by reports about a reduction
in the cerebellar volume in patients with PTSD [65–67]. Thus,
although there have not been any comparable previous studies
showing stress- related increases in the functional connectivity
between the amygdala and cerebellum, one may speculate that, in
our burnout population, a compensatory enhancement of the
modulatory pathway from the cerebellum could have occurred
due to weakened amygdala–mPFC connectivity.
Methodological limitations and future directions
The amygdala seed covered the entire amygdala except for its
most medial portion, which was excluded because of the signal loss
in the fMRI images; thus, no differentiation could be made
between the basomedial and dorsolateral nuclei. In previous
studies of stress with resting state fMRI, primarily carried out in
patients with PTSD, it has been reported that amygdala–mPFC
(and also the amygdala-ACC) connectivity is decreased when
seeding from the entire amygdala [68–69]. However, when
separating the medial and lateral portions of the amygdala,
Brown et al. found elevated connectivity between the basomedial-
amygdala and the insular and dorsomedial PFC in PTDS patients,
whereas the connection between the lateral amygdala and the
inferior frontal cortex was stronger in controls [70]. It is, thus,
possible that the results with respect to amygdala connectivity
would be slightly different if the two major portions of the
amygdala were separated. In this initial study, our priority was,
however, to minimize the noise in the seed ROI. Also, there was
no primary hypothesis that the mesial and lateral portions of the
amygdala would be affected differently in the burnout population.
The relatively small size of the subject sample did not allow us to
test for possible gender-related differences in our results among the
burnout group. This important issue will be investigated in a
separate study. The groups were, however, matched with respect
to gender distribution.
One important question worth discussing is whether and to
what extent the present findings could reflect depression. For
several reasons we find this to be unlikely. First of all, none of the
stressed subjects reported dysthymia, and none were judged to be
depressed according to the psychiatrist in charge and the SCID-
MINI ratings. Although the depression scores were significantly
higher among the stressed group, for those subjects who had high
MADRS scores, the only items that contributed to these scores
were anxiety and poor sleep, which does not necessarily imply
depression. Higher MADRS scores were related to a decreased
ability to down-regulate negative emotion, but these scores
covaried highly with the stress scores, and did not moderate the
ability to down-regulate negative emotion within the burnout
group. While the MGI-GS scores interacted with the amygdala
connectivity with the insular cortex and the thalamus, no such
interaction was detected with the MADRS scores, not even when
employing small volume correction. Finally, the cortisol levels
were normal in our stressed subjects, whereas they have been
found to be high in a large portion of patients with genuine
depression [71]. We recently also found that women suffering from
chronic occupational stress had an elevated reaction to allopreg-
nanolone [20] which differed from the diminished allopregnano-
lone response that has been observed among depressed women
[72]. Emotional reactions to chronic stress and major depression
may, thus, represent separate constructs. They share, however,
certain symptoms perhaps due to the affection of similar limbic
networks. Indeed, the higher MADRS scores among the stressed
subjects who were not diagnosed as depressed could be an effect of
this comorbidity. Stress may lead to depression, and the impaired
ability to specifically down-regulate negative emotions that was
Figure 5. Yellow clusters denote significant interaction be-
tween the left amygdala connectivity map and the MBI-GS
score merging both groups. Pink clusters denote corresponding
clusters from the right amygdala. Clusters calculated at p,0.05 FWE
corrected, and superimposed on the grey matter template (in the MNI
space) from the entire study group.
doi:10.1371/journal.pone.0104550.g005
Effect of Stress on Emotion Regulation and Brain Connectivity
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demonstrated in the present study may by itself render stressed
individuals more prone to depressive thoughts and explain the
comorbidity between the two conditions. Because the study was
cross-sectional, it is difficult to know whether the detected changes
represent effects of stress or of a pre-existing condition that could
have rendered the brain more vulnerable to the development of
pathological stress responses and reduced the ability to modulate
emotion.
Conclusion
In subjects suffering from chronic emotional stress, there seems
to be a dysregulation of the emotion- and stress-processing
networks, which prevents the restoration of internal homeostasis in
response to negative emotional stress. An impairment of the ability
to down-regulate negative emotions in subjects suffering from
occupational stress may render them more vulnerable to
depressive symptoms. This finding needs to be further explored,
as it may potentially explain the link between stress and
psychological ill health.
Acknowledgments
Tom Perski, Edin Fazlic, and Alexander Berglund are acknowledged for
excellent data collection.
Author Contributions
Conceived and designed the experiments: AG MK WO AP IS. Performed
the experiments: MK EJ. Analyzed the data: MK AG EJ. Wrote the paper:
IS AG.
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