Abstract and Figures

Media violence exposure causes increased aggression and decreased prosocial behavior, suggesting that media violence desensitizes people to the emotional experience of others. Alterations in emotional face processing following exposure to media violence may result in desensitization to others' emotional states. This study used scalp electroencephalography (EEG) methods to examine the link between exposure to violence and neural changes associated with emotional face processing. 25 participants were shown a violent or nonviolent film clip and then completed a gender discrimination stop-signal task using emotional faces. Media violence did not affect the early visual P100 component; however, decreased amplitude was observed in the N170 and P200 event-related potentials (ERPs) following the violent film, indicating that exposure to film violence leads to suppression of holistic face processing and implicit emotional processing. Participants who had just seen a violent film showed increased frontal N200/P300 amplitude. These results suggest that media violence exposure may desensitize people to emotional stimuli and thereby require fewer cognitive resources to inhibit behavior. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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Emotionally anesthetized: media violence induces neural
changes during emotional face processing
Laura A. Stockdale, Robert G. Morrison, Matthew J. Kmiecik, James Garbarino, and Rebecca L. Silton
5Loyola University Chicago, Psychology Department, 1032 W. Sheridan Road, Chicago, IL 60660
Media violence exposure causes increased aggression and decreased prosocial behavior, suggesting that media violence desensitizes people to the
emotional experience of others. Alterations in emotional face processing following exposure to media violence may result in desensitization to others
emotional states. This study used scalp electroencephalography methods to examine the link between exposure to violence and neural changes
associated with emotional face processing. Twenty-five participants were shown a violent or nonviolent film clip and then completed a gender discrim-
10 ination stop-signal task using emotional faces. Media violence did not affect the early visual P100 component; however, decreased amplitude was
observed in the N170 and P200 event-related potentials following the violent film, indicating that exposure to film violence leads to suppression of
holistic face processing and implicit emotional processing. Participants who had just seen a violent film showed increased frontal N200/P300
amplitude. These results suggest that media violence exposure may desensitize people to emotional stimuli and thereby require fewer cognitive
resources to inhibit behavior.
15 Keywords: media violence; ERPs; emotion processing; inhibition; desensitization
The media is saturated with violence and aggression and decades of
media violence research has suggested a strong association between
viewing media violence and increased aggressive thoughts and expect-
ations, and decreased prosocial behavior (Anderson et al., 2010).
20 Exposure to media violence also causes increased hostile expectations
(Bushman and Anderson, 2002), decreased sympathy for victims of
real life violence (Fanti et al., 2009), and decreased helping behaviors
towards those in need (Bushman and Anderson, 2009). Taken
together, these findings have led researchers to theorize that desensi-
25 tization to emotion following media violence exposure is a key
mechanism underlying decreases in empathy and prosocial behavior
(Bushman and Anderson, 2009). However, the cognitive changes
associated with emotional processing following media violence
exposure are not well understood.
30 Preliminary research suggests that desensitization to emotion fol-
lowing media violence exposure may result from autonomic and cen-
tral nervous system changes. Carnagey et al. (2007) found that
participants displayed a decrease in heart rate variability and skin con-
ductance when viewing violent images after exposure to violent films,
35 suggesting habituation, or a physiological desensitization to violence.
Likewise, shooting other characters in a violent video game was asso-
ciated with decreased amygdala activity, a part of the brain important
for processing and responding to fear-related emotional information in
an individual’s environment (Weber et al., 2006). Using scalp electro-
40 encephalography (EEG), Bartholow et al. (2006) found that playing a
violent video game resulted in decreased resources allocated to
processing violent emotional images, as indexed by decreased ampli-
tude in the P300 event-related potential (ERP) as compared to playing
a nonviolent video game. While this research suggests that violent
45 media exposure can cause nervous system changes in emotional
processing, it remains unclear how desensitization to emotion interacts
with more top-down cognitive processes, such as inhibitory control, a
capacity likely critical in regulating aggressive behavior. This study
explores how media violence exposure may change bottom-up and
50top-down attentional processes related to emotion processing during
a task that requires inhibitory control.
EMOTIONAL FACE PROCESSING
Humans analyze facial expressions to interpret and respond to the
emotional experiences of others. Interpreting and reacting to
55
emotional facial expressions and nonverbal human gestures is crucial
to effectively negotiate day-to-day life experiences. Processing facial
expressions is one of the first skills that infants learn (McClure,
2000) and it is essential for survival, allowing people to perceive and
interpret potential threat and avoid adverse experiences (Anderson
60et al., 2003). Abnormalities in interpreting facial expressions have
been observed in individuals chronically exposed to violence, abuse,
or neglect (Pollak, 2008). However, we know very little about how
media violence exposure influences emotional face processing.
Preliminary evidence suggests that playing violent video games
65delays identification of happy faces (Kirsh and Mounts, 2007) and
that chronic exposure to violent media was related to more quickly
and accurately identifying angry faces from faces that were mixed
between happy and angry faces (Kirsh et al., 2006). It is possible that
media violence exposure leads to an emotionally anesthetized, habitua-
70
lized response, such that less cognitive resources are needed to process
negatively valenced stimuli, including facial expressions. From this
perspective, emotional anesthetization may contribute to moral disen-
gagement, contributing to feelings of justification in committing
aggressive acts as well as an increasing enjoyment and pleasure
75
during violent video game play (Hartmann and Vorderer, 2010).
Equally disturbing, violent-video gamers show evidence of denying
the humanness of others and report victims of violence as less
human (Greitemeyer and McLatchie, 2011).
In healthy individuals, processing facial emotions is an automatic
80process involving visuospatial and attentional processes relying on sub-
cortical (i.e. thalamus, basal ganglia, amygdala, hippocampus) and
cortical (i.e. dorsolateral prefrontal, anterior cingulate, fusiform
gyrus, occipital) brain regions (Palermo and Rhodes, 2007). Humans
begin processing faces almost immediately after exposure, initially
85engaging the primary and secondary visual cortex (Vuilleumier and
Received 9 July 2014; Revised 14 February 2015; Accepted 4 March 2015
The authors thank Krishna Bharani for assistance in programming the stop-signal task, and Robert Palumbo and
Callie Short for help with data collection and recruitment. American Psychological Association Scott Mesh Honorary
Grant for Research in Psychology and the Provost and The Carroll and Adelaide Johnson Scholarship Funds for their
generous support.
Correspondence should be addressed to Laura Stockdale, Loyola University Chicago, Psychology Department,
1032 W. Sheridan Road, Chicago, IL 60660. E-mail: lstockdale@luc.edu.
doi:10.1093/scan/nsv025 SCAN (2015) 1of 10
ßThe Aut hor (2015). Published by Oxford University Pre ss. For Permissio ns, please email: journals.permissio ns @oup.co m
Driver, 2007). Using event-related potentials (ERPs) derived from EEG
recordings, researchers have argued that fear may be differentially pro-
cessed as early as 100 ms after exposure to emotional faces in the pri-
mary visual cortex (Eimer and Holmes, 2007;Vuilleumier and Driver,
52007). However, this very early processing likely does not involve ex-
plicit emotional processing (Holmes et al., 2006). Instead, explicit pro-
cessing of emotional information is indexed by a right lateralized
frontocentral P200 ERP component that is observed around 200 ms
after exposure to an emotional face (Ashley et al., 2004;Holmes et al.,
10 2006;Eimer and Holmes, 2007). However, existing studies suggest that
this ERP does not distinguish between emotional expressions (Eimer
and Holmes, 2007). Bertsch et al. (2009) found that inducing aggres-
sion in the lab could alter ERP components associated with emotional
face processing. Participants were provoked to behave aggressively and
15 their brain activity was recorded while viewing emotional faces (happy,
angry, fearful, and neutral). Participants who were provoked to behave
aggressively displayed increased P200 amplitude in response to angry
and fearful faces compared to nonprovoked participants, suggesting
that state aggression can alter the neural correlates of emotional
20 facial processing. Yet, it remains unclear how exposure to media vio-
lence interacts with emotional face processing.
INHIBITORY CONTROL PROCESSES
Top-down inhibitory control processes recruit frontocingulate brain
networks, including the dorsolateral prefrontal cortex (DLPFC) and
25 anterior cingulate cortex (ACC) to regulate a dominant response in
favor of a competing response (Morrison et al., 2004;Krawczyk et al.,
2008;Silton et al., 2010). When individuals are asked to inhibit a
dominant response, various midfrontal ERPs are observed, including
the frontocentral N200 and P300 components that are likely generated
30 from the ACC approximately 200 and 300 ms after inhibiting an auto-
matic response, respectively (Kiefer et al., 1998;Badzakova-Trajkov
et al., 2009). This ERP N200/P300 complex is reflective of brain activity
associated with inhibitory control (Enriquez-Geppert et al., 2010).
Intact inhibitory control processes are important for preventing
35 aggression and violent behavior (Raaijmakers et al., 2008). For
example, an individual may experience an impulse to respond to a
social situation with aggression, but intact inhibitory control would
allow this individual to overcome aggressive impulses and engage in
more thoughtful and socially appropriate behaviors.
40 It is not clear from previous research what effect media violence
exposure has on inhibitory control processes. Violent action video
game training studies have found improved inhibitory and motor
control (Ferguson, 2010); while other researchers have argued that
exposure to violent video games is related to both transient and endur-
45
ing patterns of disinhibition (Gentile et al., 2011). Perhaps the con-
flicting literature is a result of decoupling bottom-up emotional
processing from more top-down inhibitory control in the presence
of emotion. Recent research suggests that top-down and bottom-up
cognitive processes are much less distinct than previously thought, and
50particularly in the presence of emotion, they interact (Dennis and
Chen, 2007). Given the unique, but related contributions of top-down
and bottom-up processes during emotion processing, studying how
emotional processing contributes to inhibitory control following
media violence exposure will characterize these phenomena in a
55manner that has previously been neglected. Past behavioral studies
have consistently shown that media violence exposure can desensitize
participants to the emotional experiences of others, this study uses
EEG methods to examine the brain activity associated with neural
processes that occur when completing an implicit emotional
60face-processing task. As such, this study was designed to examine the
influence of short-term exposure to film violence on emotional facial
processing (P100, N170 and P200 ERPs) and inhibitory control (N200/
P300 ERP complex).
METHOD
65
Overview
On separate testing sessions participants viewed either a violent or
nonviolent film clip before performing a gender identification stop-
signal task with emotional faces (see Figure 1). On each trial, partici-
pants saw either a male or female face that exhibited either a fearful or
70
happy face. They were instructed to push one button if the face was
male and another if it was female (go trials). There was no mention in
the instructions about the expression on the faces. On 50% of trials a
striped box appeared around the face indicating that the participant
was to withhold their response (stop trials). The time between face
75onset and stop-signal onset (stop-signal delay) was adjusted on each
trial to adjust task difficulty for each participant. On go trials, we
recorded participant accuracy (whether they correctly identified the
gender of the face) and response time (RT) of this decision on correct
trials. On stop trials, we recorded participant accuracy (whether they
80
were successful in withholding their response) and mean stop-signal
delay. We also recorded EEG throughout the testing session and
calculated stimulus locked ERPs to both face onset on go trials and
stop-signal onset on stop trials.
(a) Go-Trial (b) Stop-Trial
Fig. 1 Stop-Signal Task Paradigm. (a). Go trials begin with a fixation screen followed by the presentation of the face for 1 s while the participants indicate the gender of the face by pressing one of two buttons
on an electronic response box. (b). On stop trials, a stop signal was displayed for 100 ms after a 200500 ms delay. The stop-signal delay was adjusted based on participant performance so that better
withholding of responses on the previous two trials resulted in an increased delay between the presentation of the face and the stop signal, thereby making the task more difficult. On go trials, the ERP epoch
was time-locked to face onset (Face ERP), while for stop trials, the ERP epoch was time-locked to the stop-signal onset (Stop ERP).
2 of10 SCAN (2015) L. Stockdale et al.
Participants
Twenty-eight undergraduate students per paid $40 for their participa-
tion in the study. Four participants were eliminated from further ana-
lysis because of poor task performance (<60% accuracy) resulting in a
5final sample of 25 undergraduate students (M¼21.4 years old, 14
female) for the go trials and 24 for the stop trials. Participants were
recruited from, an urban, midwestern university. All participants
reported that they were right-handed and did not have any known
neurological disorders. The university Institutional Review Board
10 approved all recruiting and experimental methods.
Materials and procedure
Violence manipulation
Participants visited the lab for two experimental sessions. During the
first session each participant was assigned to watch either a violent or
15 nonviolent film clip prior to completing a 30-min implicit emotion
stop-signal task (Sagaspe et al., 2011). Each clip was approximately 10
min in duration. They then watched the other film clip during a
second testing session several weeks later. Coyne et al. (2008) previ-
ously selected the film clips and found them to be equally engaging and
20 arousing. Order of the film presentation was counterbalanced to elim-
inate any potential order effects. In the violent film condition, two
female leads engage in a physical altercation including hitting, kicking,
punching, hitting with objects, shooting and a fatal stabbing. In the
nonviolent film, condition participants watched two female leads
25 engage in a se´ance with a ghost. After the se´ance, one of the female
leads has an interaction with the ghost. Uhlmann and Swanson (2004)
found that behavioral effects from media violence on aggression and
emotional processing lasted at least 30-min in a lab setting. Likewise,
Anderson et al. (2010) found the effects of media violence on aggres-
30 sion, empathy and prosocial behavior to be greatest within 45 min of
exposure. Thus, the emotional state effects that result from exposure to
media violence are expected to last the duration of the stop-signal task
(30 min) used in this study.
Mood measurement
35 Participants completed the Positive and Negative Affect Scale (PANAS;
Watson et al., 1988) before and after watching each film clip. The
PANAS is a 20-item scale that measures the distinct constructs of
positive and negative affect. Participants answer on a five-point
Likert scale how accurately words describe their current mood. For
40 example, negative affect words include ‘afraid, nervous, and guilty’
and positive affect words include ‘active, enthusiastic, and interested.’
Individual items are averaged to create separate positive and negative
affect scores.
Face stimuli
45 Digitalized photographic images of 30 male and 30 female Caucasian
faces displaying either fear or happiness were selected from the
Karolinska Directed Emotional Faces database (Lundqvist et al.,
1998). Face stimuli were converted to grayscale and balanced for
luminance and contrast in Adobe Photoshop. Images were cropped
50 with an oval mask to remove hair to minimize nonfacial gender
cues. Stimuli were adjusted to four degrees of visual angle wide.
Stop-signal task
The stop-signal task was based on the paradigm used by Sagaspe et al.
(2011). Faces exhibited either a fearful or happy expression; however,
55 the task is considered an implicit attention to emotion task since
participants were not asked to attend to or identify the specific facial
emotions. On go trials (see Figure 1a), participants were asked to press
a button to indicate whether they believed the face presented was of
a male or female. Go trials began with a fixation screen followed by a
60face presented for 1 s while participants responded by pressing one of
two buttons on the electronic response box. Participants could respond
any time after the stimulus onset for up to 1 s. A black screen followed
the face stimulus. On stop trials (see Figure 1b), a stop signal
(a stripped box surrounding the face stimulus) was displayed for
65
100 ms shortly after face stimulus onset. When the stop signal
appeared, participants were asked to withhold their gender discrimin-
ation response. The delay between face stimulus presentation and the
stop signal was adjusted (200500 ms) to standardize task difficulty
across participants. Specifically, if a participant was successful in
70
withholding his/her response on the two previous stop trials the next
stop trial would have a 20-ms longer stop delay. This served to make
the task slightly more difficult. The better the participant was at
withholding his/her response the longer the delay became, thus cali-
brating response inhibition effort across participants (Sagaspe et al.,
75
2011). Go and stop trials were randomly intermixed 50/50 within each
block of trials. Donkers and van Boxtel (2004) found that participants
who completed a 50/50 go and stop trial task had higher accuracy rates
in both go and stop conditions than participants who completed a
80/20 or 20/80 task, and importantly for our study the 50/50 task
80mix does not generate a oddball associated P300 ERP (Campanella
et al., 2002).
Participants were seated 100 cm from a 21-inch CRT monitor in a
quiet room. The stimuli were presented and responses recorded using
E-Prime 2.0 (Schneider et al., 2002). Participants received task instruc-
85
tions and then performed two sets of 20 practice trials with trial-
by-trial feedback representative of the various tasks, face valence, and
face genders. During testing participants completed 720 total trials
divided into 12 blocks. They received 180 trials for each task and
valence (go happy, go fearful, stop happy, stop fearful). Half were
90
male and half were female faces. The same 60 face stimuli were used
in each block of trials; however, they varied in their assignment to task
(go, stop) across blocks. Each block was representative of the four
conditions and two genders and trials were presented in random
order across participants. Participants received a 20-s break between
95each block.
EEG recording and data reduction
EEG data were recorded from each participant using a Biosemi Active2
EEG system. Custom-designed Falk Minow caps with 64 equidistant
active electrodes (Ag/AgCl) were used for data collection. CMS/DRL
100
were placed near the vertex. Two electrodes were located on the
mastoid bones. Two electrodes were lateral to each eye to monitor
horizontal eye movements. Two additional electrodes were placed on
the inferior edge of the orbit of each eye to monitor vertical eye
movements. Data were recorded with a band pass of 0104 Hz, and
105sampled at a rate of 512 Hz.
The following EEG data processing steps were performed in EMSE
(Source Signal Imaging). EEG data were re-referenced to common
average reference and then digitally filtered with a 0.01 Hz high-pass
filter and band-stop filter from 59 to 61 Hz. All filters had a cutoff
110
attenuation of 12 dB/octave. A polynomial detrend was applied to the
data to implement a 100 ms pre-stimulus baseline adjustment for ERP
averaging. A spatial PCA filter was applied to remove ocular artifacts.
Muscle and other artifacts were removed via visual inspection of the
raw EEG signal and a 100 mV trial-by-trial rejection criterion during
115
averaging. Participants who were included in ERP analyses had fewer
than 15% rejected trials on every condition.
Mean amplitude and 50% area latency scores (Luck, 2005) were
calculated for the occipital P100 and frontal P200 for go trials and
Emotionally anesthetized SCAN (2015) 3 of10
the frontocentral N200/P300s for stop trials. Electrode sites and scor-
ing windows were selected based on a priori scoring windows derived
from other studies investigating these ERPs in similar contexts and
visual inspection of the data in this study (P100: Herrmann et al.,
52005; P200: Ashley et al., 2004; N200/P300: Enriquez-Geppert et al.,
2010). For go trials, the P100 was measured from 70 to 130 ms post
face stimulus onset, N170 was measured from 120 to 200 ms past
face-stimuli onset, and P200 was measured from 230 to 290 ms
post face-stimulus onset. A cluster of three right posterior electrodes
10 was identified for the P100 analyses (see Figure 3b), the N170 was
measured using multiple sites corresponding to T5, O1, T6 and O2.
Three left lateral posterior electrodes were used for T5, three right
lateral posterior electrodes were used for T6, two left posterior elec-
trodes were used for O1 and two right posterior electrodes were used
15 for O2 (see Figure 4b). A cluster of five frontocentral electrodes,
located near FZ, and a cluster of two posterior electrodes near PZ,
were identified for P200 analyses (see Figure 5b). For stop trials, the
N200/P300 complex was measured from 140 to 400 ms post stop-signal
onset. A cluster of four frontocentral electrodes was identified for
20 N200/P300 analyses (see Figure 6b). On average, participants had
136 correct ‘Go Happy’ trials, 136 correct ‘Go Fearful’ trials, 131
correct ‘Stop Happy’ trials, 134 ‘Stop Fearful’ trials.
Two by two repeated-measure analysis of variance (ANOVAs) were
conducted to examine the influence of face valence (happy and fearful)
25 and film condition (violent and nonviolent) on emotional face
processing and inhibitory control. As an estimate of effect size, partial
eta square was reported for each main effect and interaction (Green
and Salkind, 2008). Behavioral data were analysed by examining the
effect of face valence and film condition on reaction time and accuracy
30 for the go trials and accuracy and stop-signal delay for the stop trials.
In regard to the EEG data, mean amplitude and 50% area latency was
examined for the P100, N170 and P200 ERP components for the go
trials and the N200/P300 component for the stop trials.
RESULTS
35Behavioral results
Mood manipulation (PANAS)
To assess the effect of the two films on mood, we calculated mood
change scores for each participant in both the violent and nonviolent
film conditions by subtracting their self-reported mood score after
40exposure to each film from their self-reported mood score before
exposure to the film. Exposure to both films resulted in an overall
increase in negative mood (t(49) ¼7.22, P< 0.001) and decrease
in positive mood (t(49) ¼5.46, P< 0.001). A one-way ANOVA was
conducted to examine possible differences between groups in overall
45
changes in negative mood. There was no difference between the two
films in regards to overall changes in negative mood (F(2, 48) ¼0.06,
P¼0.94).
Go trials
To assess potential behavioral differences in emotional-face processing
50after exposure to violent and nonviolent films, two repeated measures
ANOVAs were run examining accuracy and RT for happy and fearful
faces for the go trials only. With regard to accuracy, the main effect of
film condition was not significant (F(1, 24) ¼.20, P¼0.67,
2
p¼0.01); although, a main effect of face valence was observed
55(F(1, 24) ¼14.48, P¼0.001,
2
p¼0.38). However, the film condition
by facevalence interaction was not significant (F(1, 24) ¼0.03,
P¼0.85,
2
p¼0.001). Regardless of film condition, people were less
accurate at identifying the gender of fearful faces compared to happy
faces (See Figure 2a).
60
Similar to the accuracy results, RT did not differ across film condi-
tions (F(1, 24) ¼0.10, P¼0.76,
2
p¼0.004); however, there was a
main effect of face valence (F(1, 24) ¼29.06, P< 0.001,
2
p¼0.55). In
contrast to accuracy results, there was a film condition by facevalence
interaction for RT(F(1,24) ¼4.50, P¼0.04,
2
p¼0.16). Regardless of
(b)
(a)
(d)
(c)
0.75
0.80
0.85
0.90
Violent Nonviolent
Proportion Go Correct
Happy
Fearful
740
750
760
770
780
Violent Nonviolent
RT (ms)
Happy
Fearful
0.75
0.80
0.85
0.90
Violent Nonviolent
Proportion Stop Correct
Happy
Fearful
450
460
470
480
490
500
Violent Nonviolent
Stop-Delay (ms)
Fig. 2 (a) Accuracy for go trials. Participants were significantly less accurate at identifying the gender of fearful faces. There was no effect of film condition or interaction. (b) RT for go trials. Consistent with
accuracy results participants were faster to correctly identify happy than fearful faces. Once again there was no main effect of film condition; however, there was a reliable interaction such that people were
slower at identifying the gender of fearful faces and this effect was exacerbated after exposure to a violent film. (c) Rate of success at stopping on stop-trials. Consistent with a longer RT for fearful faces on go
trials, participants were less accurate at stopping on trials with happy than fearful trials. There was no effect of film condition or interaction. (d) There was no difference in stop-delay for participants in the
violent and nonviolent film conditions. Error bars represent 1 SEM.
4 of10 SCAN (2015) L. Stockdale et al.
film condition, people were generally slower at identifying the gender
of fearful faces, and exposure to film violence further slowed RT
(See Figure 2b).
Stop trials
5To assess the impact of violent film exposure on inhibitory control,
we conduced a two (film condition) by two (face valence) repeated
measures analysis of variance (ANOVA) on stop-signal accuracy.
There was no main effect of film condition (F(1, 23) ¼0.06,
P¼0.81,
2
p¼0.002); however there was a main effect of face valence
10 (F(1, 23) ¼5.10, P¼0.03,
2
p¼0.18), but no interaction (F(1, 23) ¼
0.58, P¼0.46,
2
p¼0.02). Regardless of the film viewed, participants
made fewer errors when stopping their response to fearful faces (See
Figure 2c). This is consistent with the go trial results discussed above
where participants were less accurate and slower to respond on trials
15 with fearful faces. The behavioral data from the go trials suggest that it
takes people longer to process features associated with fearful faces and
as a result they may spend more time processing these faces. Threat-
related stimuli captures attention (Vuilleumier and Schwartz, 2001)
and it is difficult to disengage attention from threat stimuli (Koster
20 et al., 2004). Because this task was an implicit measure of emotional
processing, these threat-related stimuli may interfere with the gender
discrimination task. This delay in processing may make it easier to
recognize and withhold responding in stop trials.
In lieu of RT (as a correct response is achieved by withholding a
25response), the average delay (i.e. stop-signal delay) between the pres-
entation of the face and the stop-signal was calculated. We collapsed
across happy and fearful faces because the staircase is adjusted every
two trials and thus a given measurement of stop-signal delay is not
clearly the result of either a happy or fearful face (as they are presented
30
in randomized order). A repeated measures ANOVA showed no effect
of film condition on average stop-signal delay (F(1, 23) ¼1.1,
P¼0.29,
2
p¼0.05; see Figure 2d).
ERP results
Go trials
35P100 amplitude and peak latency. A two (film condition) by two
(face valence) repeated measures ANOVA was conducted to examine
the influence of media violence exposure on the occipital P100 (see
Figure 3). There was no main effect of film condition (F(1, 24) ¼1.94,
P¼0.18,
2
p¼0.08), but a significant effect of face valence (F(1, 24) ¼
40
8.17, P¼0.01,
2
p¼0.25), and no interaction (F(1, 24) ¼2.22,
P¼0.15,
2
p¼0.08). These analyses show that fearful faces resulted
(a)(b)
(c)(d)
Fig. 3 (a) Grand average ERPs (time-locked to the face onset) for correct trials averaged across three posterior electrodes indicated in black on topographic map. (b) Mean amplitude scalp topography for the
average of all four conditions (70130 ms post-face onset). (c) P100 mean amplitude (70130 ms post face onset) for correct go trials across conditions. (d) 50% fractional area latency across conditions. Error
bars represent 1 SEM.
Emotionally anesthetized SCAN (2015) 5 of10
in an increased P100 mean amplitude in comparison to happy faces in
the primary visual cortex, regardless of film condition (see Figure 3a).
A second repeated measures ANOVA was also conducted to exam-
ine the influence of media violence exposure on the right occipital
5P100 latency (50 percent area latency scores; Luck, 2005) in response
to emotional faces. The main effect of film condition was not signifi-
cant (F(1, 24) ¼3.37, P¼0.08,
2
p¼0.12) and no effect of face
valence (F(1, 24) ¼2.0, P¼0.17,
2
p¼0.08) and, there was no inter-
action in P100 latency between film condition and face latency
10 (F(1, 24)¼0.41, P¼0.53,
2
p¼0.02 see Figure 3d). Together, these
analyses show that exposure to film violence did not significantly
alter early visual processing, but that negatively valenced emotional
expressions could potentially modulate early visual processing.
N170 amplitude and peak latency
15 In order to examine the effect of media violence exposure on the N170
amplitude, a 2X2X2 repeated measures ANOVA was run examining
film condition (violent and nonviolent), face valence (happy and
afraid), and lateralization (right or left hemisphere) (see Figure 4).
The N170 was measured bilaterally at four posterior sites (two bilateral
20 clusters of two electrodes each corresponding to T5/O1 and T6/O2) in
order to take into account lateralized differences in holistic facial
processing. There was an effect of film condition (F(1, 47) ¼4.64,
P¼0.04,
2
p¼0.09), no effect of face valence (F(1, 47) ¼0.14,
P> 0.05,
2
p¼0.003), an effect of lateralization (F(1, 47) ¼4.50,
25P¼0.04,
2
p¼0.09), and no interactions (F(1, 47) < 1.12, P>
0.05,
2
p < 0.02). These results indicate that that N170 amplitude is
larger in the right posterior portion of the brain, and that exposure
to media violence is associated with a bilateral reduction in N170
amplitude (see Figure 4c).
30In order to examine the effect of media violence exposure on
facial encoding and processing on N170 latency, a 2 22 repeated
measures ANOVA was run examining film condition (violent and
nonviolent), face valence (happy and fearful) and lateralization
(right or left hemisphere). There was no effect of film condition
35
(F(1, 47) ¼.54, P> 0.05,
2
p < 0.01), face valence (F(1, 47) ¼0.10,
P> 0.05,
2
p¼0.002), no effect of lateralization (F(1, 47) ¼0.02, P>
0.05,
2
p < 0.001), and no significant interactions (F(1, 47) < 2.12, P>
0.05,
2
p < 0.04). These results suggest that exposure to media violence,
face valence, and hemisphere did not alter the time course of holistic
40facial processing (see Figure 4d).
P200 amplitude and peak latency
A two (film condition) by two (face valence) repeated measures
ANOVA was conducted to examine the influence of media violence
exposure on the frontal central P200 (see Figure 5). There was a main
+8.0µV
-4.0µV
600 ms
Violent Fearful
Violent Happy
Nonviolent Fearful
Nonviolent Happy
-
4.6u
V
4.6
uV
147
148
149
150
151
152
153
154
155
Violent Nonviolent
Mean Amplitude (uV)
Happy
Afraid
142
144
146
148
150
152
154
156
158
Violent Nonviolent
Fractional Area Latency (ms)
(a)(b)
(c)(d)
Fig. 4 (a) Grand average ERPs (time-locked to face onset) for correct trials averaged across two right posterior electrodes indicated in black on topographic map. (b) N170 (120200 ms post-face onset) mean
amplitude scalp topography for the average of all four experimental conditions. (c) N170 mean amplitude (120200ms post face onset) across conditions. (d) 50% fractional area latency across conditions. Error
bars represent 1 SEM.
6 of10 SCAN (2015) L. Stockdale et al.
effect of film condition (F(1, 24) ¼6.07, P¼0.02,
2
p¼0.21), but
no effect of face valence (F(1, 24) ¼0.56, P¼0.46,
2
p¼0.02), and
no interaction (F(1, 24) ¼0.68, P¼0.26,
2
p¼0.01; see Figure 5c).
These analyses show that exposure to film violence results in decreased
5frontal central P200 amplitude compared to the nonviolent film
condition regardless of the emotion being displayed on the face.
A two (film condition) by two (face valence) repeated measures
ANOVA was conducted to examine the influence of media
violence exposure on the posterior P200. There was no effect of film
10 condition (F(1, 24) ¼1.24, P¼0.28,
2
p¼0.05), no effect of face
valence (F(1, 24) ¼1.88, P¼0.18,
2
p¼0.08) and no interaction
(F(1, 24) ¼0.07, P¼0.79,
2
p¼0.001). These analyses show that
exposure to film violence did not modulate the posterior P200 amp-
litude compared to the nonviolent film condition regardless of the
15 emotion being displayed on the face.
A third repeated measures ANOVA was also conducted to examine
the influence of media violence exposure on the frontal central P200
latency (50% area latency scores; Luck, 2005) in response to emotional
faces. There was no effect of film violence on the frontal central
20 P200 latency (F(1, 24) ¼0.32, P¼0.58,
2
p¼0.01), no effect of face
valence (F(1, 24) ¼0.001, P¼0.97,
2
p¼0.001), and no interaction
(F(1, 24) ¼0.006, P¼0.71,
2
p¼0.006 see Figure 5d). Together, these
analyses show that exposure to film violence did not modulate the time
course of emotional face processing.
25Finally, a repeated measures ANOVA was also conducted to examine
the influence of media violence exposure on the posterior P200 latency
(50% area latency scores; Luck, 2005) in response to emotional
faces. There was no effect of film condition (F(1, 24) ¼1.85,
P¼.19,
2
p¼0.07), no effect of face valence (F(1, 24) ¼0.01,
30P¼0.99,
2
p¼0.001), and no interaction (F(1, 24) ¼0.03, P¼0.86,
2
p¼0.001). Together, these analyses show that exposure to film
violence did not modulate the posterior P200 amplitude or latency
to emotional faces.
Stop trials
35
N200/P300 amplitude. A two-way repeated measures ANOVA was
conducted to examine the influence of media violence exposure on the
frontocentral N200/P300 mean amplitude in response to emotional
faces (Figure 5). There was a main effect of film condition, with
exposure to film violence resulting in less positive waveforms
40
(F(1, 23) ¼5.54, P¼0.03,
2
p¼0.19), and no effect of face valance
(F(1, 23) ¼0.33, P¼0.57,
2
p¼0.01). The film condition face
valence interaction was not significant (F(1, 23) ¼0.30, P¼0.59,
2
p¼0.01; see Figure 6). These results suggest that exposure to film
600 ms
Violent Fearful
Violent Happy
Nonviolent Fearful
Nonviolent Happy
Face-Onset
-3.5μV
+3.5μV
-2.5
-2
-1.5
-1
-0.5
0
Violent Nonviolent
Mean Amplitude (uV)
Happy
Afraid
254
256
258
260
262
264
266
268
Violent Nonviolent
Fractional Area Latency (ms)
(a)
(d)(e)
(b)
(c)
Fig. 5 (a) Grand average ERPs (time-locked to face onset) for correct trials averaged across five frontal central electrodes indicated in black on topographic map. (b) P200 (230290 ms post-face onset) mean
amplitude scalp topography for the average of all four experimental conditions. (c) P200 (230290 ms post-face onset) subtraction topography for violent and the nonviolent film conditions. (d) P200 mean
amplitude (230290 ms post face onset) across conditions. (e) 50% fractional area latency across conditions. Error bars represent 1 SEM.
Emotionally anesthetized SCAN (2015) 7 of10
violence resulted in decreased cognitive resources being allocated to
inhibitory control processes.
DISCUSSION
Results from this study suggest that short-term exposure to film
5violence can lead to ‘emotional anesthetization’ or a reduction in
cognitive resources allocated to processing emotional face expressions.
The results also suggest that exposure to media violence can lead to
alteration in the way people process human faces. Media violence also
subsequently influenced the neural correlates of inhibitory control
10 processes. The current results also suggest that media violence expos-
ure did not modulate the early visual processing in the primary visual
cortex, but did modulate early holistic processing of faces as well as
processing of emotional information contained in facial expressions
These results build on past research that has consistently shown that
15 exposure to violence in the media is related to desensitization to emo-
tion (Carnagey et al., 2007), decreased prosocial behavior (Bushman
and Anderson, 2009), and increased aggressive behavior (Bushman and
Anderson, 2001). The results from this study elucidate the neural
processes associated with these changes in behavior observed in past
20 media violence research.
Behavioral data demonstrated that participants were less accurate
and slower in gender discrimination when fearful faces were presented
even though the emotion of the faces was irrelevant to the gender
discrimination task (i.e. it was an implicit emotion processing task).
25 Past research has shown threat-related stimuli captures attention rela-
tive to neutral or nonthreat-related stimuli (Pourtois et al., 2004).
Thus, the attentional capture by fearful stimuli may make it more
difficult to disengage in order to adeptly respond to the task at
hand. In this study, slower behavioral responses when fearful stimuli
30
were present likely resulted from difficulties disengaging attention to
threat-related information. Likewise, consistent with earlier studies
(Vuilleumier and Driver, 2007;Eimer and Holmes, 2007) we found
that early visual processing as measured by the P100 ERP was also
sensitive to face valence with fearful faces evoking a larger amplitude
35
than happy faces. In addition, exposure to film violence further slowed
responses on trials that involved fearful faces. This finding is consistent
with past behavioral research that shows that exposure to short-term
media violence results in a bias towards negatively valenced informa-
tion and hostile expectations (Bushman and Anderson, 2002).
40Processing fearful faces may have triggered the vigilance surveillance
system (Nitschke and Heller 2002), thus better preparing participants
to quickly inhibit their response when the stop-signal appeared.
Participants were significantly better at inhibiting their response to
fearful faces as compared to happy faces. While exposure to film
45violence did not alter early visual attention as measured by the P100
ERP component, exposure to film violence was associated with a
bilateral reduction in the N170 ERP component. The N170 ERP
component has been associated with holistic face processing (Sagiv
and Bentin, 2001). Regardless of film condition, the N170 was larger
50in the right posterior region and this finding is consistent with past
research that has demonstrated right lateralization for human face
processing (McCarthy et al., 1997). Previous media violence re-
searchers have found that exposure to violence in the media results
in denying the ‘humanness in others’ (Greitemeyer and McLatchie,
552011). For example, participants who played a violent video game
were more likely to assign less human attributes to people than
people who played a nonviolent video game and were less likely to
view people as unique (Greitemeyer and McLatchie, 2011). Perhaps the
observed reduction in the N170 component after exposure to violence
-2μV
+8μV
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
Violent Nonviolent
Mean Amplitude (μV)
Happy
Afraid
Violent Fearful
Violent Happy
Nonviolent Fearful
Nonviolent Happy
Happy
Fearful
600 ms
Stop-Signal Onset
-.85 +.85µV
-5.8 +5.8µV
(a)(b)
(d)(c)
Fig. 6 (a) Grand average ERPs (time-locked to stop-signal onset) for correct trials averaged across four central electrodes indicated in black on topographic map. (b) N200/P300 (140400 ms post stop-signal
onset) mean amplitude scalp topography for the average of all four experimental conditions. (c) N200/P300 mean amplitude (140400 ms post stop-signal onset) across conditions. (d) N200/P300 mean
amplitude (140400 ms post stop-signal onset) subtraction topography for violent and nonviolent film conditions. Error bars represent 1 SEM.
8 of10 SCAN (2015) L. Stockdale et al.
is reflective of the cognitive processes associated with these changes in
behavior associated with dehumanization of others.
Similarly, previous research that has shown that participants begin
to process emotional aspects of facial expressions around 200 ms in
5frontal brain regions (Holmes et al., 2006). In this study, brief exposure
to film violence resulted in decreased frontal central P200 amplitude in
response to both happy and fearful faces compared to exposure to
these same faces after watching a nonviolent film. Decades of research
on the effects of media violence have found that exposure to media
10 violence results in desensitization to real-life violence (Carnagey et al.,
2007). Bushman and Anderson (2009) stated that exposure to violence
in the media leaves people ‘comfortably numb’ to the pain and suffer-
ing of others. Perhaps this desensitization and numbness to others is a
result of decreased processing and attention to emotional information,
15 even the relatively automatic processing of emotional faces.
With regard to inhibitory control, after exposure to film violence,
participants displayed changes in the N200/P300 complex. Specifically,
participants exposed to a violent film showed decreased N200/P300
amplitude when inhibiting behavior than after exposure to a nonvio-
20 lent film clip. The frontocentral N200/P300 ERP complex is indicative
of motor/behavioral inhibition (Enriquez-Geppert et al., 2010).
This study suggests that exposure to film violence resulted in decreased
cognitive resources needed for inhibiting behavioral responses as
indicated by decreased N200/P300 amplitude. Given the decreased
25 P200 amplitude following film violence exposure, it is possible that
participants who watched the violent film spent less cognitive resources
processing the emotional information contained in faces, and subse-
quently needed less cognitive resources to successfully inhibit motor
behavior. Past research has shown that it is more difficult to inhibit
30 behavior in the presence of emotion (Chan et al., 2008) because it is
more difficult to disengage from emotional information (Schaefer
et al., 2003). The results of this study suggest that exposure to media
violence leads to desensitization and decreased processing of emotional
information and thus less cognitive resources are needed to inhibit
35 behavior.
This study offers a first step towards identifying how violent media
influences the neural correlates of emotional face processing and
subsequent inhibitory control functions. However, the manipulation
was only a short-term experimental manipulation and cannot address
40 the long-term effects of media violence exposure on emotional and
cognitive processes. Future researchers should examine the potential
long-term effects of media violence exposure on emotion processing
and how this may interact with acute exposure to violence. Likewise,
this study compared the processing of happy and fearful faces in order
45 to assure that the facial stimuli were equally engaging (Goeleven et al.,
2008). However, this manipulation did not allow for a neutral condi-
tion. Therefore, it is possible that exposure to film violence modulates
facial processing in general, regardless of the emotional information.
This seems unlikely because early visual attention was not modulated
50 by film condition, but future research should address this limitation
and compare the effects of exposure to violence in the media on
emotional face processing compared to a neutral face condition. This
study focused on emerging adults who are a major consumer of media
violence. Future studies should evaluate the effect on children or ado-
55 lescents who are exposed to large amounts of violence in the media.
Children and adolescents are still developing scripts and schemas re-
garding aggression and violence and thus may be at increased risk from
violent media.
The media is saturated with violence and aggression and people
60 are spending more time with the media today than ever before.
The findings of this study support the idea that exposure to media
violence leads to emotional anesthetization, particularly with regard to
desensitization of the emotional experiences of others as reflected in
their facial emotions. Given the accumulating empirical evidence sup-
65
porting these finding, parents and policy makers should seriously
evaluate the costs and consequences of media violence exposure on
children and society.
CONFLICT OF INTEREST
None declared.
70
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10 o f 10 SC A N ( 2015 ) L. Stockdale et al.
... Participants completed the SST while their EEG data were recorded. The SST was modified from the paradigm used in our previous research (Stockdale et al., 2015(Stockdale et al., , 2017(Stockdale et al., , 2020 to include images of healthy and unhealthy food stimuli from the FoodPics database (Blechert et al., 2014). The FoodPics stimulus set includes detailed metadata about a set of 568 food images, including information about the valence and arousal evoked by each image as well as the nutritional content of the food. ...
... The decision to conceptualize the N200/P300 as a complex instead of two distinct components was based on two factors. First, previous work using a modified version of this paradigm, with a 50/50 presentation of the stop and go-trials, did not justify the separation of these two components, but rather supported the observation of a single ERP component that was theorized to indicate fronto-central neural activity and inhibitory control (Stockdale et al., 2015(Stockdale et al., , 2020. In go/no-go and stop-signal tasks (SST), the N200 ERP component is evoked approximately 200 ms after exposure to a signal to withhold a response, and it is thought to signify conflict detection (Donkers & van Boxtel, 2004;van Boxtel et al., 2001). ...
... However, researchers have argued that there is insufficient evidence to justify the separation of the N200/P300 into two separate ERP components (i.e. N200 and P300; Huster et al., 2013) and this is particularly evident when the trials are split 50/50 instead of the traditional 80/20 split (Stockdale et al., 2015;. Secondly, after visual inspection of the data for the current study, the N200/P300 topography was very similar to the N200/P300 topography observed 0 in previous studies using a version of this task that involved affective face stimuli (Stockdale et al., 2015;. ...
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Developmental changes during adolescence may make youth susceptible to violent media effects. Two studies with male adolescents (N1 = 241; N2 = 161; aged 12–17) examined how habitual and short-term violent video gaming may affect emotion recognition and inhibitory control. We found that not habitual exposure to violent video games, but to antisocial media content predicted worse emotion recognition. Furthermore, higher habitual exposure to violent games predicted better inhibitory control over emotional stimuli in a stop signal task. However, short-term causal effects of violent gameplay on adolescents were not found. While these results do not indicate a negative impact of violent video games on young players, future research may further investigate possible effects of antisocial media content on adolescents.
... Additionally, two studies explored ERP responses to emotional faces in an inhibition task. An experimental study showed a decreased amplitude in early ERP components (N170 and P200) during emotional (happy or fearful) face processing after watching a violent movie (Stockdale et al., 2015). A cross-sectional study showed lower ERP amplitude to happy facial expressions in the frequent violent video game players group as compared to infrequent players; however, no difference was observed for fearful faces (Stockdale et al., 2017). ...
... In sum, research shows that VVGE may be related to or may affect emotion recognition (Kirsh et al., 2006;Kirsh and Mounts, 2007;Bailey and West, 2013;Stockdale et al., 2015Stockdale et al., , 2017Diaz et al., 2016). Most of the previous studies focused on how fast players could identify emotions or how they allocate attention to happy faces. ...
... The findings of our cross-sectional studies are in line with previous experiments showing changes in lower sensitivity to emotional faces in players of violent video games (Bailey and West, 2013) and people who viewed a violent movie (Stockdale et al., 2015). Based on the mechanisms examined in the experimental studies, we suggest that frequent players of violent games in the current studies may be less sensitive to negative emotional expressions. ...
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An ability to accurately recognize negative emotions in others can initiate pro-social behavior and prevent anti-social actions. Thus, it remains of an interest of scholars studying effects of violent video games. While exposure to such games was linked to slower emotion recognition, the evidence regarding accuracy of emotion recognition among players of violent games is weak and inconsistent. The present research investigated the relationship between violent video game exposure (VVGE) and accuracy of negative emotion recognition. We assessed the level of self-reported VVGE in hours per day and the accuracy of the recognition using the Facial Expressions Matching Test. The results, with adolescents (Study 1; N = 67) and with adults (Study 2; N = 151), showed that VVGE was negatively related to accurate recognition of negative emotion expressions, even if controlled for age, gender, and trait empathy, but no causal direction could be assessed. In line with the violent media desensitization model, our findings suggest that higher self-reported VVGE relates to lower recognition of negative emotional expressions of other people. On the one hand, such lower recognition of negative emotions may underlie inaccurate reactions in real-life social situations. On the other hand, lower sensitivity to social cues may help players to better focus on their performance in a violent game.
... Additionally, two studies explored ERP responses to emotional faces in an inhibition task. An experimental study showed a decreased amplitude in early ERP components (N170 INSENSITIVE PLAYERS? 7 and P200) during emotional (happy or fearful) face processing after watching a violent movie (Stockdale, Morrison, Kmiecik, Garbarino, & Silton, 2015). A cross-sectional study showed lower ERP amplitude to happy facial expressions in the frequent violent video games players group as compared to infrequent players; however, no difference was observed for fearful faces (Stockdale, Morrison, Palumbo, Garbarino & Silton, 2017). ...
... In sum, research shows that VVGE may be related to or may affect emotion recognition (Bailey & West, 2013;Diaz et al., 2016;Kirsh et al., 2006, Kirsh & Mounts, 2007Stockdale et al., 2015;Stockdale et al., 2017). Most of the previous studies focused on how fast players could identify emotions or how they allocate attention to happy faces. ...
... Although, we did not measure physiological reactions of participants in the present studies, our interpretation of the current results is consistent with the desensitization model: VVGE may be related to reduced sensitivity to social stimuli, which is visible in worse recognition of negative emotional states. This is in line with previous studies showing changes in lower sensitivity to emotional faces in players of violent video games (Bailey & West, 2013) and people who viewed a violent movie (Stockdale et al., 2015). Based on that we suggest, that frequent players of violent games in the current study may be less sensitive to negative emotional expressions. ...
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An ability to accurately recognize negative emotions in others can initiate pro-social behavior and prevent anti-social actions. Thus, it remains of an interest of scholars studying effects of violent video games. While exposure to such games was linked to slower emotion recognition, the evidence regarding accuracy of emotion recognition among players of violent games is weak and inconsistent. The present research investigated the relationship between violent video game exposure (VVGE) and accuracy of negative emotion recognition. We assessed the level of self-reported VVGE in hours per day and the accuracy of the recognition using the Facial Expressions Matching Test. The results, with adolescents (Study 1; N = 67) and with adults (Study 2; N = 151), showed that VVGE was negatively related to accurate recognition of negative emotion expressions, even if controlled for age, gender, and trait empathy, but no causal direction could be assessed. In line with the violent media desensitization model, our findings suggest that higher self-reported VVGE relates to lower recognition of negative emotional expressions of other people. On the one hand, such lower recognition of negative emotions may underlie inaccurate reactions in real-life social situations. On the other hand, lower sensitivity to social cues may help players to better focus on their performance in a violent game.
... In typically developing preschool aged children, P200 amplitudes are greater for "antisocial" than for "prosocial" actions . In adult population, conditions such as phobic (Sarlo & Munafò, 2010), high-level of callous-unemotional (CU) traits (Brislin et al., 2018) and "emotional desensitization" resulting from exposure to violence (Stockdale, Morrison, Kmiecik, Garbarino, & Silton, 2015) are known to lead to reduced P200 in response to distress cues (e.g., expression of fear), indicating that sustained attention and processing is precluded. LPPs are known to index top-down cognitive reappraisal and regulation of emotion arousal Hajcak, Weinberg, MacNamara, & Foti, 2012). ...
... However, in preschool-aged children, P2 amplitudes are greater when viewing "antisocial" actions than "prosocial" actions . In adult populations, reduced P2 to negative stimuli (e.g., fearful or distressed faces) are associated with CU traits (Brislin et al., 2018) or "emotional desensitization" (Stockdale et al., 2015). Taken together, findings from this study imply that, after engaging with the empathy game, children's attentional resources are more easily mobilized when encountering antisocial or harming actions. ...
Article
There is an emerging concern that modern technology‐saturated environments, particularly computer games, are inhibiting the development of children’s empathic behaviour and social skills. We argue that the solution is embedded in the problem when hybrid learning design blends real‐life social interpersonal interactions with digital representations. We present theory‐informed design principles for creating tablet games with a focus on promoting empathic perception—a building block for the ability to see, sense and understand other’s internal states. Based on these principles, the game Empathy World was developed and trialled in a naturalistic three‐month study in an early childhood education setting. Children learned to perceive empathy‐worthy cues in various scenes and interacted with the tablet game to further their perspective‐taking and to associate emotions with social contexts. The findings from this study show an increase in the selective tendency of children’s in‐game perception of empathy‐worthy stimuli and enhanced empathic concern. We argue that future design for learning can utilise the strengths of hybrid design for social development at a larger scale: integrating theoretically informed and rigorously tested digital tools in existing educational and social environments. Practitioner Notes What is already known about this topic • Research has examined various developmental benefits of empathy and shown that empathy can be learnt. • Digital games can be productive, easy to scale, tools that support learning. • Sound design, based on theory‐informed principles, can improve the effectiveness of digital learning games. What this paper adds • It synthesises theories and research evidence of empathy and its development. • It shows how empathy‐related theoretical ideas and evidence were translated into hybrid design principles for developing empathy games and embedding them into children’s social learning environment. • It illustrates how theory‐ and evidence‐informed design principles were used to create a digital game to enhance empathic learning of young children in a hybrid technology‐mediated environment. • It explores and validates the effectiveness of a hybrid design approach by implementing the digital empathy game in children’s natural learning environment and analysing the data by capturing emerging patterns of development stemming from gameplay. Implications for practice and/or policy • Pre‐schools could enhance children's empathy learning by integrating specially designed empathy games in existing learning environments. • Teachers and parents should be informed about how to create game‐mediated hybrid environments that enhance children’s empathy.
... Our study provided a strict control on the environmental variables, as both groups were selected from the same facilities, and all participants were delinquents. It's very important to control the living environment between groups, for the environment and partnership may largely affect the behavior and cognition of an individual (15,(96)(97)(98)(99)(100)(101)(102)(103)(104)(105)(106)(107)(108). From the scale results, we found that the two groups were not significantly different from each other in CU traits, childhood maltreatment, aggression, self-control and moral disengagement, indicating that the groups were well matched for aspects other than CD. ...
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According to the social-cognitive theory and the social-information-processing theory, individuals with conduct disorder, a persistent and repetitive pattern of problematic behavior, might have cognitive biases toward hostile facial expressions. However, according to the optimal stimulation/arousal theory, the stimulation-seeking theory and the fearlessness theory, individuals with conduct disorder might have less fear and show less response to hostile or threatening facial expressions. To reconcile the discrepancy, we examined the cognitive biases including attentional processing and working memory processing to emotional faces among adolescents with conduct disorder. 35 male adolescent delinquents with conduct disorder and 35 age-matched delinquents without conduct disorder completed a visual search task and a delayed-match-to-sample task to examine their attentional processing and working memory processing for sad, angry, happy, and fearful faces, respectively. It was found that conduct disordered individuals searched angry and fearful faces, rather than sad and happy faces, more slowly than individuals without conduct disorder. However, no difference in mnemonic processing for facial emotions was found between groups. The results indicated that male adolescent delinquents with conduct disorder showed deficits in attentional orientation to hostile and threatening faces, supporting the optimal stimulation/arousal theory, the stimulation-seeking theory and the fearlessness theory, but not the social-cognitive theory.
... Emotion-specific temporal signatures (Costa et al., 2014;Esslen et al., 2004;Styliadis et al., 2015Styliadis et al., , 2018Waugh et al., 2015) are often influenced by a range of individual differences (e.g., Fisher et al., 2014;Sass et al., 2010;Silton et al., 2010;Stockdale et al., 2015Stockdale et al., , 2017. Studying the temporal dynamics of emotional processing is critical due to the distinct aspects of emotional responses (e.g., reactivity, regulation, and repair) that develop across time. ...
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This review paper provides an integrative account regarding neurophysiological correlates of positive emotions and affect that cumulatively contribute to the scaffolding for positive emotions and wellbeing in humans and other animals. This paper reviews the associations among neurotransmitters, hormones, brain networks, and cognitive functions in the context of positive emotions and affect. Consideration of lifespan developmental perspectives are incorporated, and we also examine the impact of healthy social relationships and environmental contexts on the modulation of positive emotions and affect. The neurophysiological processes that implement positive emotions are dynamic and modifiable, and meditative practices as well as flow states change patterns of brain function and ultimately support wellbeing are also discussed. This review is part of “The Human Affectome Project” (http://neuroqualia.org/background.php), and in order to advance a primary aim of the Human Affectome Project, we also reviewed relevant linguistic dimensions and terminology that characterizes positive emotions and wellbeing. These linguistic dimensions are discussed within the context of the neuroscience literature with the overarching goal of generating novel recommendations for advancing neuroscience research on positive emotions and wellbeing.
... Society's increased and continued access and exposure to this content has the potential to alter our emotions, emotion perception, and emotional responses and perhaps become desensitized to its effect (Harper & Hodgins, 2016;Hilton & Watts, 2011;Koukounas & Over, 1993;Kunaharan & Walla, 2014). Several studies have attempted to determine whether increased exposure to violence (Bailey, West, & Anderson, 2011;Bartholow, Bushman, & Sestir, 2006;Carnagey, Anderson, & Bushman, 2007;Elmore, 2014; Englehardt, Bartholow, Kerr, & Bushman, 2011;Stockdale, Morrison, Kmiecik, Garbarino, & Silton, 2015;Wood, Griffiths, Chappell, & Davies, 2004) or pornography (Kühn & Gallinat 2014;Prause, Steele, Staley, & Sabatinelli, 2014;Prause, Steele, Staley, Sabatinelli, & Hajcak, 2015) has any effect on our emotions and whether exposure to either one has any effect on the other (e.g., if viewing excess pornography increases the risk of sexual violence) (Allen, Emmers, Gebhardt, & Giery, 1995;Ferguson & Hartley, 2009;Hald, Malamuth, & Yuen, 2010;Johnson, 2014;Kingston, Fedoroff, Firestone, Curry, & Bradford, 2008;Mancini, Reckdenwald, & Beauregard, 2012;Vega & Malamuth, 2007;Wright, Tokunga, & Kraus, 2015). A common feature of many studies in this field is the use of questionnaire derived data to determine participant affect; few studies make use of alternative methodology required to determine emotional affect beyond conscious thought. ...
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As we are often inundated with images of violence and pornography in modern times with the aid of mobile devices and unrestricted online access and content, the non-conscious effect of such exposure is an area of concern. To date, many clinicians and researchers in behavioral sciences rely on conscious responses from their clients to determine affective content. In doing so, they overlook the effect the non-conscious has on an individual’s emotions. The present study aimed to examine variations in conscious and non-conscious responses to emotion-inducing images following varying amounts of exposure to violent and pornographic images. Eighteen participants who self-reported as being low pornography users were presented with emotion-inducing images after no exposure (Session 1), after one round of exposure to 50 pornographic and 50 violent images (Session 2) and after a further nine rounds of exposure to 50 pornographic and 50 violent images (Session 3). Sessions were temporally separated by at least 2 days while startle reflex modulation (SRM) and scalp-recorded event-related potentials (ERPs) were used to determine non-conscious emotion-related responses to pre-evaluated emotion pictures. Explicit valence and arousal ratings were assessed for each of those emotion pictures to determine conscious emotion effects potentially changing as a function of increasing controlled exposure to pornographic and violent visual material. Conscious explicit ratings and SRM amplitudes revealed no significant difference between the sessions. However, frontal ERP analysis revealed significant changes between processing of “violent” and “unpleasant” images at later ERP time windows, further supporting the growing body of research which shows that relying on self-report data does not result in a full understanding of emotional responses.
... In general, desensitization over prolonged exposure to violence may increase individual enjoyment of violent media through moral disengagement regardless of initial traits [19,34]. There seems to be a positive relationship between moral disengagement and playing violent video games through emotional desensitization [35][36]. ...
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We use an interactive story design in which participants read short stories and make two consecutive plot choices about whether protagonists commit low- or high-violence actions. Our study has four main findings. 1) People who choose high violence report greater satisfaction with the story, while those switching to or staying with no violence show lower satisfaction. 2) However, when participants encounter these stories without choices, they reliably rate higher-violence stories as less satisfying than lower-violence stories. 3) Regret seems to account for the low satisfaction of those who choose or switch to low violence. 4) There is a large segment of people (up to 66%) who can be persuaded by different story contexts (genre, perspective) to choose extreme violence in interactive fiction and as a consequence of their choice feel satisfaction. We hypothesize that people who opt for high violence enjoy the story as a result of their choice. Overall, we suggest that choosing violence serves as a gateway for enjoyment by creating an aesthetic zone of control detached from morality.
... The relationship between frames or consecutive images can give us, for example, the recognition of an important change pattern such as the state of emotion between sequences or a significant change due to an unexpected event [6] [7]. This can be measured by the correlation in contours or landmark [8] [9]. ...
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The perception of faces is sometimes regarded as a specialized task involving discrete brain regions. In an attempt to identi$ face-specific cortex, we used functional magnetic resonance imaging (fMRI) to measure activation evoked by faces presented in a continuously changing montage of common objects or in a similar montage of nonobjects. Bilateral regions of the posterior fusiform gyrus were activated by faces viewed among nonobjects, but when viewed among objects, faces activated only a focal right fusiform region. To determine whether this focal activation would occur for another category of familiar stimuli, subjects viewed flowers presented among nonobjects and objects. While flowers among nonobjects evoked bilateral fusiform activation, flowers among objects evoked no activation. These results demonstrate that both faces and flowers activate large and partially overlapping regions of inferior extrastriate cortex. A smaller region, located primarily in the right lateral fusiform gyrus, is activated specifically by faces.
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Research conducted over several decades has shown that violent media increase aggression. It is now time to move beyond the question of whether violent media increase aggression to answer- ing the question why violent media increase aggression. The pres- ent research tested whether violent video games produce a hostile expectation bias—the tendency to expect others to react to poten- tial conflicts with aggression. Participants (N = 224) played either a violent or nonviolent video game. Next, they read ambig- uous story stems about potential interpersonal conflicts. They were asked what the main character will do, say, think, and feel as the story continues. People who played a violent video game described the main character as behaving more aggressively, thinking more aggressive thoughts, and feeling more angry than did people who played a nonviolent video game. These results are consistent with the General Aggression Model.
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This study aims to advance the media effects debate concerning violent video games. Meta-analytic reviews reveal a small but noticeable association between playing violent video games and aggressive reactions. However, evidence for causal associations is still rare. In a novel, event-related functional magnetic resonance imaging study, 13 male research participants were observed playing a latest-generation violent video game. Each participant's game play was recorded and content analyzed on a frame-by-frame basis. Onscreen activities were coded as either "passive/dead, no interactions"; "active/safe, no imminent danger/no violent interactions"; "active/potential danger occurs, violent interactions expected"; "active/under attack, some violent interactions"; and "active/fighting and killing, many violent interactions." Previous studies in neuroscience on aggressive thoughts and behaviors suggested that virtual violence would suppress affective areas of the anterior cingulate cortex (ACC) and the amygdala subsequent to activity variations at cognitive areas of the ACC. Comparison of game play activities with and without virtual violence in 11 participants confirmed the hypothesis. The rather large observed effects can be considered as caused by the virtual violence. We discuss the applicability of neuroscience methodology in media effects studies, with a special emphasis on the assumption of virtuality prevalent in video game play.
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Although affective facial pictures are widely used in emotion research, standardised affective stimuli sets are rather scarce, and the existing sets have several limitations. We therefore conducted a validation study of 490 pictures of human facial expressions from the Karolinska Directed Emotional Faces database (KDEF). Pictures were evaluated on emotional content and were rated on an intensity and arousal scale. Results indicate that the database contains a valid set of affective facial pictures. Hit rates, intensity, and arousal of the 20 best KDEF pictures for each basic emotion are provided in an appendix.
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In recent studies of the structure of affect, positive and negative affect have consistently emerged as two dominant and relatively independent dimensions. A number of mood scales have been created to measure these factors; however, many existing measures are inadequate, showing low reliability or poor convergent or discriminant validity. To fill the need for reliable and valid Positive Affect and Negative Affect scales that are also brief and easy to administer, we developed two 10-item mood scales that comprise the Positive and Negative Affect Schedule (PANAS). The scales are shown to be highly internally consistent, largely uncorrelated, and stable at appropriate levels over a 2-month time period. Normative data and factorial and external evidence of convergent and discriminant validity for the scales are also presented. (PsycINFO Database Record (c) 2010 APA, all rights reserved)