Journal of Behavioral and Brain Science, 2011, 1, 115-123
doi:10.4236/jbbs.2011.13016 Published Online August 2011 (
Copyright © 2011 SciRes. JBBS
Brain Processing of Fearful Facial Expression in Mentally
Disordered Offenders
Katarina Howner1, Håkan Fischer2,3, Thomas Dierks4, Andrea Federspiel4, Lars-Olof Wahlund2,
Tomas Jonsson5, Maria Kristoffersen Wiberg5, Marianne Kristiansson1
1Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
2NVS-Department, Karolinska Institute, Stockholm, Sweden
3Department of Psycholo gy , Stockholm University, Stockholm, Swe den
4Department of Psychiatric Neurophysiology, University Hospital for Psychiatry, Bern, Switzerland
5Department of Clinical Science, Intervent ion and Technology, Karolinska Institute, Stockholm, Sweden
Received June 14, 2011; revised July 19. 2011; accepted July 28, 2011
Emotional facial expressions are important cues for interaction between people. The aim of the present study
was to investigate brain function when processing fearful facial expressions in offenders with two psychiatric
disorders which include impaired emotional facial perception; autism spectrum disorder (ASD) and psycho-
pathy (PSY). Fourteen offenders undergoing forensic psychiatric assessment (7 with ASD, and 7 psycho-
pathic offenders) and 12 healthy controls (HC) viewed fearful and neutral faces while undergoing functional
magnetic resonance imaging (fMRI). Brain activity (fearful versus neutral faces) was compared both be-
tween HC and offenders and between the two offender groups (PSY and ASD). Functional co-activation was
also investigated. The offenders had increased activity bilaterally in amygdala and medial cingulate cortex as
well as the left hippocampus during processing fearful facial expressions compared to HC. The two sub-
groups of offenders differed in five regions compared with each other. Results from functional co-activation
analysis suggested a strong correlation between the amygdala and anterior cingulate cortex (ACC) in the left
hemisphere only in the PSY group. These findings suggest enhanced neural processing of fearful faces in the
amygdala as well as in other facial processing brain areas in offenders compared to HC. Moreover, the co-
activation between amygdala and ACC in the PSY but not the ASD group suggested qualitative differences
in amygdala activity in the two groups. Since the sample size is small the study should be regarded as a pilot
Keywords: Psychopathy, Autism Spectrum Disorder, Offenders, fMRI, Emotional Facial Processing
1. Introduction
Emotional facial expressions are unique cues, crucial for
social interaction [1]. They convey information about
how another individual feels, as well as the motivations
and intentions of others. This increases our ability to pre-
dict the behavior of other persons and also possible threats,
thus facilitating adjustment of our own behavior [2]. Im-
pairment in perceiving emotional facial expressions can
lead to strange and inappropriate behavior and may also
lead to antisocial behavior. A meta analysis of antisocial
populations and emotional facial recognition suggested a
robust link between antisocial behavior and specific
deficits in recognizing fearful expressions [3].
Psychopathy, as defined by Hare [4], and autism spec-
trum disorder (ASD) [5] are two developmental disorders
with impairments in emotional facial expression pro-
cessing [6-9]. Psychopathy has been associated with in-
creased risk of offending behavior [10] and ASD has
been suggested to be overrepresented in forensic psychi-
atric settings [11,12].
ASD includes impairments in mentalizing, emotional
reciprocity, communication, and social interaction [5].
Also impairment in perceiving emotional facial expres-
sions has been suggested. Brain imaging studies have
shown that subjects described as high-functional autism
Copyright © 2011 SciRes. JBBS
(HFA) have showed parallels to subjects with amygdala
damage concerning facial perception [9,13] and in other
studies it have been showed that autistic subjects use
alternative pathways in the brain when processing emo-
tional facial expressions [14,15]. In comparison to
healthy individuals who commonly focus on the eye-re-
gion when looking at human faces, these individuals
seem to focus on other parts of the face, for example on
the mouth [16]. Psychopathic subjects often present a
good, though superficial, ability to understand social
signals [17]. Despite this, it has been shown that these
subjects often have specific impairments in recognizing
sad and fearful facial expressions [18,19], as well as
more global impairment in identifying facial expressions
[6]. Regardless of the fact that both groups (ASD and
PSY) demonstrate impairment in recognizing emotional
facial expressions, the different clinical symptoms shown
in these two groups could possible correspond to re-
cruitment of different brain networks when processing
various facial expressions. Blair has discussed Asperger
syndrome and psychopathy in this respect and suggests
that the amygdala could be the key structure here [20,
A specific neural network for processing human faces
has been suggested [22]. This network consists of brain
regions processing static information, such as the shape
and size of the face (including inferior occipital gyrus,
lateral fusiform gyrus, and superior temporal sulcus), and
areas specific for other aspects of facial perception. In
this network, the amygdala has a specific role in proc-
essing emotional facial expression. It is not clarified
whether there is differential neural processing of fearful
faces in psychopathic offenders as compared to autistic
In the present functional magnetic resonance imaging
(fMRI) study, we contrasted fearful and neutral faces [23]
in a blocked design to study differences in cerebral acti-
vation between offenders with ASD or psychopathy and
a healthy control group. In many previous studies on
criminal offenders the inclusion criteria for subjects stud-
ied have varied substantially [24], so in the present study,
we addressed this specific problem and were very re-
strictive in the inclusion criteria, in order to select well
defined subjects, resulting in small but fairly homogene-
ous study groups. To the best of our knowledge, this is
the first fMRI-study to compare offenders with ASD
with psychopathic offenders in the forensic psychiatric
setting, and the present study should be regarded as a
pilot study.
We hypothesized that the offender group would ex-
hibit a different pattern of neural activity in the network
processing fearful facial expressions, compared to con-
trols. We also hypothesized that the two subgroups of
offenders would differ from each other in this network,
especially in amygdala activation, and in functional coac-
tivation between the amygdala and other regions within
the network.
2. Material and Methods
2.1. Subjects
The sample consisted of 26 right-handed male subjects;
14 offenders (7 with ASD and 7 psychopathic offenders)
undergoing forensic psychiatric assessment, and 12
healthy non-criminal controls. There were no age differ-
ences between the groups (Table 1).
Healthy controls (HC) were recruited from posters
advertised at a nearby hospital. Offenders were recruited
from the Department of Forensic Psychiatry in Stock-
holm. In Sweden major forensic psychiatric assessments
are performed after the court has found evidence for the
crime but before conviction. In this unit, approximately
280 forensic psychiatric assessments of inmates in cus-
tody are performed each year, 10% of inmates are female,
and of the remaining 90%, approximately 5% have
marked psychopathic traits (i.e. Psychopathy Check List
Revised, PCL-R [4] score > 30) and a further 10% are
diagnosed with autism spectrum disorder. The study
subjects were recruited consecutively during, in all, 24
Inclusion criteria for the offenders were either a main
diagnosis of autism spectrum disorder (ASD) or psycho-
pathy (PSY), as defined by Hare with PCL-R scores > 30
[4]. Exclusion criteria were axis I diagnoses, difficulties
in understanding Swedish or acute psychosis at the time
of assessment.
All subjects underwent an interview including the
Structured Clinical Interview for DSM-IV (SCID I)
Screening Interview [25,26], Asperger Syndrome Diag-
nostic Interview, (ASDI) [27], and Psychopathy Check
List Screening Version (PCL-SV) [28]. Age, intelligence
quotient (IQ) according to the Wechsler Adult Intelli-
gence Scale-Revised (WAIS-R) [29] and medication
were collected from the forensic psychiatric reports (Ta-
ble 1). After the MR-scans, all participants performed
State Trait Anxiety Inventory State (STAI-S) [30] in or-
der to measure how stressful the situation was perceived.
One subject in the ASD group was HIV-positive without
clinical symptoms, structural brain damage, and neuro-
psychological dysfunction. All analyses including the
ASD group were performed both with and without this
subject, and the results remained stable.
The study was approved and conducted in accordance
with ethical guidelines established by the Regional Ethi-
cal Committee at the Karolinska Institutet in Stockholm.
Copyright © 2011 SciRes. JBBS
Table 1. Demographic and clinical characteristics. Mean value, SD in parenthesis. Mann-Whitney U-test was used in com-
parisons between groups.
HC Offenders ASD PSY
Age 28.1 (8.2) 28.6 (6.9) 29.9 (4.9) 27.3 (4.9)
IQ - 98.1 (17.7) 100 (22.3) 94.8 (4.3)
PCL-SV* 0.5 (0.5) 15.1 (5.5) 10.6 (3.5) 19.7 (2.1)
STAI-S 32.6 (11.6) 42.4 (16.4) 41.5 (19.1) 43.1 (15.4)
*Significant differences in HC vs Offenders: p < 0.0001, and PSY vs ASD: p < 0.0001; HC = healthy controls; ASD = offenders with autism spectrum disorder;
PSY = psychopathic offenders; IQ = intelligence quotient; PCL-SV = Psychopathy ChecklistScreening Version; STAI-S = State Trait Anxiety Inven-
After description of the study, written informed consent
was obtained.
2.2. Statistical Analysis of Demographic
Age, IQ, PCL-SV scores, and STAI-S scores are pre-
sented as means (SD) and tested with Mann Whitney
U-test. The confidence interval was set at 95%, and the
level of statistical significance of differences was p <
2.3. PCL-SV Scoring
The PCL-SV was performed in all study subjects in order
to make sure that no subjects in the ASD and the HC
group had a high amount of psychopathic traits. The
PCL-SV was used as the HC group consisted of non
criminals. It has high correlation with the PCL-R [31,32]
but is preferred for use in non-criminal settings. The
PCL-SV rating was assessed by two independent raters
and the cut off score for psychopathy in the PCL-SV was
Inter-rater reliability was computed using the intra-
class correlation coefficient (ICC) [33], which was cal-
culated using a two-way mixed effects model. The single
measure ICC was 0.98 (95% CI = 0.95 – 0.99, n = 25).
Two-tailed t-tests showed significant differences be-
tween the HC group and the offenders (t = 9.93, df =
13.3, p < 0.0001). The same analysis was performed be-
tween the two subgroups of offenders (PSY vs AUT) (t =
5.95, df = 9.7, p < 0.0001). For mean scores see Table 1.
2.4. Stimuli
The stimuli comprised photographs of human facial ex-
pressions from the standardized Ekman and Friesen face
set [23]. A blocked design was used which consisted of
alternating blocks of fearful and neutral faces. Each block
consisted of 15 different faces, presented for 2 seconds
each, followed by a fixation cross for 400 ms.
The 36 sec ‘face-blocks’ were interspersed with 18 sec
“rest-blocks” with a white fixation cross on a black screen.
The subjects were asked to identify the sex (male or fe-
male) of the face by pressing buttons with the right index
finger. The pictures were presented with a projector on a
screen and the subjects viewed the pictures through a
mirror on the head coil.
2.5. Behavioral Data
Mean reaction time and accuracy according to the sex
discrimination task were used as a proxy for attention to
the faces. Data are presented as means (SD) and com-
parisons between groups were performed using two-
tailed t-test. Behavioral data was missing for one subject
in the ASD group due to technical problems.
2.6. MRI Acquisition
The MR-scans were acquired with Siemens Avanto 1.5 T
whole body MRI system, with a 12-channel matrix head
coil. The subjects were placed supine in the scanner wear-
ing headphones to reduce noise from the machine, and
their heads were fixated with a vacuum pillow.
Functional imaging was performed using a T2*-
weighted gradient echo planar imaging sequence (EPI)-
mosaic sequence (TR = 3000 ms, TE = 50 ms, slice
thickness = 5 mm, gap between slices = 0.5 mm, FOV =
220 mm, matrix size = 64 × 64, voxel dimension = 3.4
mm × 3.4 mm × 5 mm, 30 coronal slices, covering the
whole brain), 114 volumes were collected. For structural
data we used a 3D magnetization-prepared rapid-acqui-
sition gradient echo (MP-RAGE) sequence, 176 sagittal
slices were acquired with the following parameters:
repetition time (TR) = 2300 ms, inversion time (TI) =
1100 ms, echo time (TE) = 3.93 ms, slice thickness = 1
mm, field of view (FOV) = 256 mm × 256 mm, Matrix =
Copyright © 2011 SciRes. JBBS
256 × 256, isotropic voxel size = 1 mm3.
2.7. fMRI-Analyses
The first three volumes in each run were discarded to
allow for T1 equilibration effects. Image time-series
analysis was performed using Brain voyager, BVQX 1.9.
Preprocessing comprised a correction of slice scan time,
3D motion correction (Trilinear/sinc interpolation) and
temporal filtering removing linear trend. The images of
each subject were co registered to the 3D anatomical
volume, normalized into Talairach space, and herby re-
sample into 3 mm isotropic voxels. The resulting volume-
time course files (VTC) were then spatially smoothed
with a Gaussian filter of 8 mm full-width at half maxi-
mum for the group analyzes.
We chose the following anatomical region of interests
(ROIs), from the model for facial perception by Haxby et
al. [22]; inferior occipital gyrus, superior temporal sulcus,
lateral fusiformis gyrus, insula, hippocampus, parahip-
pocampus, cingulate gyrus and amygdala. Within these
predefined areas, we used a threshold level of p < 0.001
(uncorrected) in line with many other studies in the field.
Because the amygdala has been shown in many studies
to be of major importance for fearful facial processing
[34], we used a threshold of p < 0.05 (uncorrected) in this
specific ROI. We also performed a whole brain analysis,
in which we used a threshold level of p < 0.05 (FDR-
Individual analysis; we investigated blood oxygen
level dependent (BOLD) activation associated specifi-
cally with the processing of the emotional cues in fearful
faces (i.e fearful faces > neutral faces). This was done by
applying a fixed effects model [35], with condition-spe-
cific stimulus boxcar functions, convolved with a gamma-
kernel to model the hemodynamic response behaviour.
Three predictors were entered into the design matrix: fear
faces, neutral faces, and baseline (looking at a white fixa-
tion cross on a black screen). The outputs of the model
are beta values for the different conditions.
Between-group analyses were performed between (1)
the HC and the offenders and (2) between the two sub-
groups of offenders (ASD vs PSY). Random effects mod-
els were used for both within and between group analyses.
The between group analyses were calculated in the fo-
llowing steps: first all individual VTCs were created for
the contrast fearful faces > neutral faces, then a two-
tailed t-test was performed between the HC group and
the offender group and finally the same procedure was
performed between the ASD and the PSY groups.
2.8. Functional Co-Activation
The functional co-activation analysis was performed in
the following steps: first functional ROIs in the right and
the left amygdala in the offender group were defined
based on the group contrast fearful faces > neutral faces,
consisting of 8 voxles located around the peak activation
voxel in each of the two regions (mean TAL: X = 21, Y
= –11, Z = –11; X = –19, Y = –7, Z = –13).
Individual beta values from these specific ROIs were
collected. The difference between the beta values for the
fear condition minus the beta value for the neutral condi-
tion for each subject was used as a measurement of
amygdala reactivity to fearful expressions. From the be-
tween group analyses (ASD vs PSY), we found five re-
gions (Table 3) where the two offender groups differed
from each other within the network for the processing
facial expressions [22]. In all these five regions we de-
fined functional ROIs, as described above for the amyg-
dala, and extracted beta values from these ROIs as well.
We then correlated amygdala reactivity with activity in
these specific ROIs, using Pearsons correlation, on each
side separately (right and left), within each of the two
groups (ASD and PSY). Grubb’s test was used to test for
outliers [36].
3. Results
3.1. Behavioral Responses
There were no significant differences between groups in
any of the behavioral responses (Table 2).
3.2. fMRI BOLD-Responses
3.2.1. Between-Group Comparisons of Fearful Versus
Neutral Faces Contrast
The offender group, collapsed across diagnoses, com-
pared to HC had higher activation in the amygdala bilat-
Table 2. Behavioral responses. Mean values and SD in parenthe sis.
HC Offenders ASD PSY
Accuracy (%) 96.9 (2.9) 96.3 (3.4) 95.7 (3.7) 96.9 (3.3)
Reaction time, neutral (ms) 668.2 (89.7) 725.6 (97.9) 759.2 (130.6) 696.8 (53.5)
Reaction time, fear (ms) 671.7 (111.1) 686.5 (74.9) 703.7 (98.8) 671.8 (50.3)
HC = healthy controls; ASD = offenders with autism spectrum disorder; PSY = psychopathic offenders.
Copyright © 2011 SciRes. JBBS
Table 3. Between-group comparisons. The contrast fear > neutral, p < 0.001 (uncorrected).
Region Brodmann’s Area Hemisphere X Y Z Numbers of voxels t-value
Offenders > HC
Amygdala Amygdala L –19 –7 –13 118 2.22
Amygdala Amygdala R 21 –11 –11 126 2.18
Cingulum 24 R 21 0 34 7 3.85
Cingulate gyrus 23 L –23 23 27 44 3.93
Parahippocampus-Hippocampus Hippocampus L –43 –33 –5 22 3.89
HC > Offenders
No areas
Insula 13 L –39 –7 –5 24 4.36
Anterior cingulate cortex 24 L –4 27 17 19 4.40
Insula 13 R 34 –25 0 258 4.61
Lingual gyrus/fusiform gyrus 18 L –7 –91 –14 26 4.37
Cingulate gyrus 23 L –15 –13 31 7 4.45
HC = healthy controls; PSY = psychopathic offenders; ASD = offenders with autism spectrum disorder.
erally, the left hippocampus as well as in the medial cin-
gulate cortex bilaterally (Table 3).
In a comparison between the two subgroups of of-
fenders (ASD vs PSY), there were two regions where the
PSY group had significantly higher activation than the
ASD group; anterior cingulate cortex (ACC), and insula
on the left side (Table 3, Figure 1). The ASD group, on
the other hand, had higher activation in the right insula
and left cingulate cortex, and left fusiform gyrus (Table
3). In the whole brain analysis we did not find any sig-
nificant differences in any of the between group analy-
3.2.2. Functi o nal Co -Activation
In the PSY group there was a correlation between the
amygdala and the ACC on the left side (rxy = 0.97, p <
0.001), which was not found in the ASD group (rxy =
0.327, p = 0.475) (Figure 2). No other correlations with
amygdala reactivity were significant in any of the two
4. Discussion
The present study investigated the neural underpinnings
of emotional facial perception in offenders with ASD or
psychopathy. The whole offender group had increased
BOLD activity, compared to the HC group, in specific
nodes in the neural network involved in perceiving and
processing facial information [34] namely bilateral amyg-
dala, cingulate gyrus, and left hippocampus. In studies
applying brain imaging techniques to other groups of anti-
social subjects, functional impairments in the frontal lobes
[37] and the limbic system [38,39] have been demon-
strated, and a suggested impairment in the balance be-
tween these two systems has been described [40-42].
These studies have reported both hypoactivity [38,43] and
hyperactivity [40,42] in the amygdala and the limbic sys-
tem compared to healthy controls.
Hyper activation in amygdala in the current offender
group could reflect an imbalance between the limbic sys-
tem and more frontal systems located outside of the net-
work processing facial expressions; it could also be re-
lated to alteration in the way fearful facial expressions
are processed in these specific groups. Since both of
these groups (PSY and ASD) have shown impairments in
recognizing fearful facial expressions before [3,6,9,44],
the enhanced amygdala activity may be related to ambi-
guity in the processing of the emotional face signal [45].
If so, this ambiguity could be related to enhance cogni-
tive elaborative processing associated with exposure to
fearful faces in the offender group, which could explain
the activations also in more “cognitive regions”, such as
the medial cingulate gyrus and the hippocampus.
In the contrast between the two offender groups (ASD
Copyright © 2011 SciRes. JBBS
Figure 1. Between-group analyses. Blue dot illustrates PSY vs ASD in the contrast fearful > neutral faces; PSY > ASD in
ACC (mean TAL-coordinates: –4, 27, 17), p-value < 0.01 (corrected). This region was correlated with amygdala in the
PSY-group. PSY = psychopathic offenders; ASD = offenders wi th autism spectrum disorder syndrome; ACC = anterior cin-
gulate cortex.
Figure 2. Functional co-activation. Correlation between
reactivity in the amygdala (AMY) and in the anterior cin-
gulate cortex (ACC), on the left side in the group of psy-
chopathic offenders, PSY, (rxy = 0.97, p < 0.001), but no
significant correlation in the group of offenders with autism
spectrum disorder, ASD, (rxy = 0.327, p = 0.475).
vs PSY) we observed differential activations in both the
insular cortex (left vs right) and the cingulate gyrus.
Hence, ASD and PSY seem to have differential activa-
tion patterns within these two cortical regions during
perception of fearful faces. The insula cortex has been
connected to visceral representation of autonomic
arousal [46,47]. Because the ASD-group activated the
right insula more than the PSY-group this could reflect
that exposure to fearful facial expressions is associated
with more bodily arousal in the ASD-group compared to
the PSY-group. This reasoning is in line with earlier
studies showing that psychopathic subjects have lower
autonomic responses during exposure to emotionally rele-
vant information [43,48-52]. The PSY-group had higher
activation in the ACC compared to the ASD- group
which could be connected to the possible inhibition of
amygdala reactivity. The ASD-group, on the other hand,
had higher activity in the posterior cingulated gyrus,
Brodmann area 23. The posterior cingulated cortex has
been connected to both emotional processing and mem-
ory-related functions [53-55]. Accordingly, the higher
posterior cingulate activation in the ASD-group could
reflect altered emotional or memory related processing of
fearful facial information compared to the PSY-group.
Our third main result is a strong correlation between
amygdala reactivity and ACC activity in the PSY group
on the left side, which was not found in the ASD group.
This suggests that the amygdala activation in the two of-
fender groups may differ qualitatively, even though there
were no quantitative differences. The ACC influences
emotional processing [56] and is suggested a role in
modulating the amygdala [57]. A possible explanation in
the current study is that the ACC in the PSY-group in-
hibits the amygdala reaction, resulting in impaired emo-
tional information processing. Hence, the amygdala–
ACC correlation could reflect a marked ACC influence
on fearful emotional facial processing in the amygdala
resulting in the disturbed fearful facial processing pattern
often seen in psychopathic subjects [6,7]. An important
note is that it is not possible to tell anything about the
Copyright © 2011 SciRes. JBBS
direction of the co-activation with the current analysis.
Some limitations have to be mentioned. Firstly, the
sample size in the subgroups was small, thus increasing
the risk of type II error, and the present study should be
regarded as a pilot study. Secondly, five of the offenders
and one HC were on medication. It was not possible to
withdraw all medication, as the study was conducted in a
clinical context. Some offenders had a history of drug
and alcohol misuse prior to arrest; as they were re-
manded in custody, all of the offenders had been free
from drugs and alcohol for at least 6 - 10 weeks prior
inclusion. Finally, the use of HC as a comparison group
to the offenders involves some problems; HC consisted
of non criminals who probably have different socioeco-
nomic status than the offenders, they all had completed
high school education and were not tested with WAIS-R.
In summary, our findings indicate altered neural proc-
essing of fearful facial expressions in the offender group
compared to HC within the neural network involved in
processing facial information [22]. Moreover, the two
subgroups of offenders differed from each other in direct
or indirect functional communication between the amyg-
dala and ACC, both located within the face processing
network. The behavioral relevance of these differences is
however unclear. Facial processing most certainly inter-
acts with our decision making in various situations and is
one important factor in the development of empathy [58].
Lack of empathy is a common trait in offenders [58].
Both psychopathy [4] and ASD [5] have been associated
with reduced empathic ability. Empathy is a construct
consisting of many aspects; for example emotional and
cognitive empathy. While cognitive empathy or theory of
mind requires mentalizing, emotional empathy includes
the ability to interpret emotional facial expressions. In
ASD the cognitive empathy is affected, which have not
yet been found in psychopathy. Blair discussed these two
disorders and their differences regarding the empathic
ability. He points out their different dysfunctions, both
regarding empathy deficit and differences in amygdala,
and suggests that a “fine cut” between autism and psy-
chopathy can be made in both amygdala and in the dif-
ferent aspects of empathy, emotional and cognitive em-
pathy [20,21]. In future studies, brain activation patterns
to facial expressions in subjects with autistic and psycho-
pathic traits, with and without offending behavior, ought
to be compared and related to measures of empathy and
its different aspects.
5. Acknowledgements
We are grateful to Kristina Sygel for language revision
and Kerstin Eriksson for assisting during the MRI-scans.
This research has made use of the SMILE medical im-
aging laboratory at Karolinska University Hospital, Stoc-
kholm. Financial support was provided through the re-
gional agreement on medical training and clinical research
between Stockholm County Council and the Karolinska
Institutet (ALF) and grants from the National Board of
Forensic Medicine in Sweden. Dr Fischer was funded by
grants from the Swedish Research Council.
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