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I Didn’t Sin—It Was My Brain

10.05.2009

Brain researchers have found the sources of many of our darkest thoughts, from envy to wrath.

by Kathleen McGowan; illustrations by Christopher Buzelli

Why does being bad feel so good? Pride, envy, greed, wrath, lust, gluttony, and sloth: It might sound like just one more
episode of The Real Housewives of New Jersey, but this enduring formulation of the worst of human failures has inspired
great art for thousands of years. In the 14th century Dante depicted ghoulish evildoers suffering for eternity in his
masterpiece, The Divine Comedy. Medieval muralists put the fear of God into churchgoers with lurid scenarios of demons
and devils. More recently George Balanchine choreographed their dance.

Today these transgressions are inspiring great science, too. New research is explaining where these behaviors come from
and helping us understand why we continue to engage in them—and often celebrate them—even as we declare them to
be evil. Techniques such as functional magnetic resonance imaging (fMRI), which highlights metabolically active areas of
the brain, now allow neuroscientists to probe the biology behind bad intentions.

The most enjoyable sins engage the brain’s reward circuitry, including evolutionarily ancient regions such as the nucleus
accumbens and hypothalamus; located deep in the brain, they provide us such fundamental feelings as pain, pleasure,
reward, and punishment. More disagreeable forms of sin such as wrath and envy enlist the dorsal anterior cingulate
cortex (dACC). This area, buried in the front of the brain, is often called the brain’s “conflict detector,” coming online when
you are confronted with contradictory information, or even simply when you feel pain. The more social sins (pride, envy,
lust, wrath) recruit the medial prefrontal cortex (mPFC), brain terrain just behind the forehead, which helps shape the
awareness of self.

No understanding of temptation is complete without considering restraint, and neuroscience has begun to illuminate this
process as well. As we struggle to resist, inhibitory cognitive control networks involving the front of the brain activate to
squelch the impulse by tempering its appeal. Meanwhile, research suggests that regions such as the caudate—partly
responsible for body movement and coordination—suppress the physical impulse. It seems to be the same whether you
feel a spark of lechery, a surge of jealousy, or the sudden desire to pop somebody in the mouth: The two sides battle it
out, the devilish reward system versus the angelic brain regions that hold us in check.

It might be too strong to claim that evolution has wired us for sin, but excessive indulgence in lust or greed could certainly
put you ahead of your competitors. “Many of these sins you could think of as virtues taken to the extreme,” says Adam
Safron, a research consultant at Northwestern University whose neuroimaging studies focus on sexual behavior. “From
the perspective of natural selection, you want the organism to eat, to procreate, so you make them rewarding. But there’s
a potential for that process to go beyond the bounds.”

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There is no sin center in the brain, no single node of fiendishness that we might be able to shut down with drugs or
electrodes. With the advent of modern imaging techniques that peer into the brain as it functions, though, we at least gain
some perspective on our bad habits. At the same time, we can indulge in another gratifying pastime: As other people
misbehave, we can sit back and watch.

LUST
In the annals of sin, weaknesses of the flesh—lust, gluttony, sloth—are considered second-tier offenses, less odious than
the “spiritual” sins of envy and pride. That’s good news for us, since these yearnings are notoriously difficult to suppress.

When it comes to lust, neuroimaging confirms that the prurient urge is all-encompassing. Watching pornography calls
upon brain regions associated with reward, sensory interpretation, and visual processing. It enlists the amygdala and the
hypothalamus, which deal with emotional information; it also stimulates the reward-processing ventral striatum, probably
due to the satisfying nature of watching erotic stimuli. All said, the most notable thing about lust is that it sets nearly the
whole brain buzzing, Safron says.

These responses are so unique and distinctive that, in the context of an experiment, it is possible to determine whether a
man is aroused just by looking at an fMRI brain scan. “These are huge effects,” Safron says. “You’re looking at the
difference between something that elicits intense desire and something that does not.” (Women show a less spectacular
response, Safron says, and it is unclear exactly why.)

If lechery is all-consuming, how do we ever manage to control it? As with other powerful impulses, we try to shut down
arousal by calling upon the right superior frontal gyrus and right anterior cingulate gyrus, according to research led by
Mario Beauregard of the University of Montreal. He and others propose that these brain areas form a conscious
self-regulatory system. This network provides us with the evolutionarily unprecedented ability to control our own neural
processing—a feat achieved by no other creature.

GLUTTONY
Today it is difficult to regard overeating as a sin, considering the overwhelming evidence that physiology plays a more
powerful role than morals in appetite and indulgence.

Physician Gene-Jack Wang of Brookhaven National Laboratory has studied the brains of overeaters since 1999, when he
and colleague Nora Volkow originally observed that obesity and drug addiction alter the same brain circuits. These
pathways, which rely on the neurotransmitter dopamine, are often referred to simplistically as the “reward system” but are
also involved in motivation, attention, decision making, and other complex functions. In their studies, Wang and Volkow
found that both drug addicts and obese people are usually less sensitive to dopamine’s rewarding effects. Being relatively
numb to the pleasure and motivation signal may make them more likely to chase after a stronger thrill: more food or a
bump of cocaine. Excessive stimulation further desensitizes dopaminergic neurons, and the compulsion snowballs.

+++

In some of his experiments, Wang asks his volunteers to come hungry. He then torments them, asking them to describe
their favorite food in loving detail while he heats it up in a nearby microwave so that the aroma wafts through the room.

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The most notable thing about lust is that it sets nearly the whole brain buzzing.

When these miserable souls go into a positron-emission tomography (PET) scanner, Wang sees the motivation regions of
their brains go wild. Parts of the orbital frontal cortex, which is implicated in decision making, also light up.

In the brains of obese people, the regions that regulate sensory information from the mouth and tongue are more active,
suggesting that they may experience the sensations of eating differently. While sensory processing is elevated in many of
these subjects, other research shows that their reward sensitivity is lower. The dorsolateral prefrontal cortex (dlPFC) and
other areas involved in inhibitory control are underactive; the heavier the person, the lower the activity there. “Overeating
downregulates your inhibition control,” Wang says.

For the gluttonous, neuroscience offers moral absolution. After all, Saint Thomas Aquinas asserted that a sin must always
be voluntary, or else it is not really a sin. “Our brain evolved for us to eat in excess, in order to survive,” Wang says. “This
kind of excess is built into the brain.”

SLOTH
Mere laziness does not seem to qualify as a truly deadly sin. It helps to know that this moral failing was originally
conceived of as acedia, an outmoded term that conveys both alienation and tedium, tinged with self-contempt. Acedia
afflicted jaded monks who had grown weary of the cloistered life. Their sin was turning away from their moral obligations
and toward selfish pursuits—a monastic form of ennui.

Today, paralyzing lassitude is often seen as a symptom of disease rather than of turpitude. Apathy is a classic sign of
frontotemporal dementia. In this neurodegenerative disorder, the frontal lobes of the brain are slowly eaten away, causing
social and mood changes as well as cognitive decline. Patients with such dementia often become increasingly withdrawn.

Sadness and listlessness are also hallmarks of major depression. With frontotemporal dementia the symptoms are
caused by dead and dying cells; in depression the root cause is still unknown. Interestingly, the dorsolateral prefrontal
cortex has an unusual pattern of activation in both conditions. Related to its ability to inhibit impulses, this region has a
role in sustaining attention over the long haul, which is necessary for motivation. Abnormal function in the dlPFC might be
connected to the lethargy associated with both conditions. Conversely, activity in this area may keep a lid on negative
emotions; in some studies, depression lifted with stimulation of the dlPFC.

PRIDE
Early theologians saw pride as the fundamental sin—the “queen of them all,” according to Pope Gregory the Great, who
codified the list of seven deadly sins in the sixth century. Indeed, psychologists say that arrogance comes naturally in
Western society. Most of us perceive ourselves as slightly smarter, funnier, more talented, and better-looking than
average. These rose-colored glasses are apparently important to mental health, the psychological immune system that
protects us from despair. “Those who see themselves as they truly are—not so funny, a bad driver, overweight—have a
greater chance of being diagnosed with clinical depression,” says Julian Paul Keenan, director of the cognitive
neuroimaging laboratory and professor of psychology at Montclair State University in New Jersey.

For most of us, it takes less mental energy to puff ourselves up than to think critically about our own abilities. In one recent
neuroimaging study by Hidehiko Takahashi of the National Institute of Radiological Sciences in Japan, volunteers who
imagined themselves winning a prize or trouncing an opponent showed less activation in brain regions associated with
introspection and self-conscious thought than people induced to feel negative emotions such as embarrassment. We
accept positive feedback about ourselves readily, Takahashi says: “Compared with guilt or embarrassment, pride might be
processed more automatically.”

Pride gets its swagger from
the self-related processing
of the mPFC, which Keenan
calls “a very interesting area of the brain, involved in all these wonderful human characteristics, from planning to abstract
thinking to self-awareness.” Using transcranial magnetic stimulation (TMS), in which a magnetic field applied to the scalp
temporarily scrambles the signal in small areas of the brain, he was able to briefly shut off the mPFC in volunteers. With
TMS switched on, his subjects’ normal, healthy arrogance melted away. “They saw themselves as they really were,
without glossing over negative characteristics,” he says.

Righteous humility has traditionally been depicted as the virtue that opposes pride, but the work of Keenan and others
calls that into question. He is using TMS to disrupt deliberate self-deprecation—the type of unctuous, ingratiating behavior
that seems humble but is actually arrogance in disguise. Patterns of brain activation during self-deprecation are
fundamentally the same as those during self-deceptive pride, Keenan is finding. Both are forms of one-upmanship.
“They’re in the same location and seem to serve the same purpose: putting oneself ahead in society,” he says.

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GREED
Despite the enormous pool of potential research subjects, greed has not yet been systematically investigated in brain
research. However, neuroscience does offer insight into a related phenomenon, the indignant outrage of the cheated.

Our hatred of unfairness runs deep, even trumping rational self-interest. In the lab, researchers frequently use the
“ultimatum game” to test our responses to injustice. One of two partners is given a sum of money and told that he must
offer some amount of his own choosing to his partner. If the partner rejects the offer, neither gets to keep any of the
money. On a rational basis, the receiving partner should accept any nonzero offer, since getting some money is always
better than getting none. But people’s sense of violation at unfairness is so strong that they reject offers of 20 percent or
less about half the time.

+++

It makes sense that we are so sensitive to being cheated, notes Matthew Lieberman, a professor of psychology at the
University of California at Los Angeles. “Mammalian survival depends on social bonds, and fairness is a really important
social cue,” he says. Inequitable treatment might be an important sign that we are not valued by the group, he says, so we
had better pay attention.

In response to unfair offers, the brain activates the pain detection process that takes place in the multitasking dACC.
Interestingly, it also engages the bilateral anterior insula, an area implicated in negative emotions such as anger, disgust,
and social rejection. The picture that emerges from fMRI is that of a brain weighing an emotional response (the urge to
punish the guy who cheated you) against a logical response (the appeal of the cash).

The delight in someone else’s downfall can be downright blissful.

When Lieberman increased the money being offered, he found that accepting a share that was larger but still unfair—say,
$8 out of $23—was linked not with reward circuitry but with increased activity in the ventrolateral prefrontal cortex and
downregulation of the anterior insula, changes often seen during the regulation of negative feelings. People seemed to be
suppressing their indignant reaction in order to accept a reward that was inequitable but appealing. Similarly, getting a fair
offer—even if it was small in absolute terms—activated regions in the brain such as the ventral striatum and the
ventromedial prefrontal cortex that are involved in automatic and intuitive reward processing. Justice apparently feels
good.

ENVY
The sin of pride turned on its head, envy is the most social of the moral failures, sparked by the excruciating awareness of
someone else’s supreme talent, stunning looks, or extremely expensive car. For that reason, it is also the least fun of the
deadly sins; feeling jealous provides no dirty thrill.

Only one imaging study (conducted by Takahashi’s group in Japan) has probed the neural basis of envy. Volunteers in
fMRI machines were asked to read three scenarios. In the first, “student A” was portrayed as similar to, but better than,
the volunteer in every respect. “Student B” was depicted as equally successful but very different from the subject, and
“student C” sounded pretty much like a loser. Reading about the awe-inspiring student A activated the volunteers’ conflict-
detecting dACC brain region, perhaps responding to the gap between the default setting of self-aggrandizing pride and
the ugly truth of someone else’s triumphs. This same region is enlisted when feeling pain, suggesting to Takahashi that
envy is a kind of “social pain in the self.”

On the other hand, indulging in schadenfreude—the delight in someone else’s downfall—can be downright blissful.
Aquinas termed this “morose delectation” and condemned it as a failure to resist a passion. Indeed, Takahashi found that
rejoicing in a rival’s defeat brings pleasure just as surely as envy does pain. In the second phase of his study, volunteers
read about student A’s downfall, causing the ventral striatum to light up. The striatum is part of the so-called reward
system, which can be activated by such pleasures as money, food, or sex, Takahashi says. “Schadenfreude is a social
reward.” The stronger the dACC activation in the first study, the stronger the striatum response in the second.

WRATH
It may not have been the original sin, but rage is certainly primordial: You would think that lust and gluttony would predate
any emotion, but much of the brain circuitry active during anger is very basic and very fast. In humans, anger enlists the
conflict-detecting dACC, which immediately alerts other regions of the brain to pay attention. The more upset you get, the
more it activates, found Tom Denson, a psychologist at the University of New South Wales in Australia. In people with
short fuses, this part of the brain seems to be primed to feel provocation and personal slights, Denson says.

Some of us are more easily enraged than others, but few are able to stifle rage completely. Instead we may convert overt

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hostility into angry brooding. To investigate the difference between short fusers and brooders, Denson antagonized his lab
volunteers, insulting them while he scanned their brains. “Within seconds you see differences,” Denson says. The medial
prefrontal cortex, associated with self-awareness and emotional regulation, quickly lit up in angry brooders. So did the
hippocampus, involved in memory. As they fume, people repeatedly relive the event in their minds. Denson found that the
degree of hippocampal activation predicted how much people tended to ruminate.

Probing the underpinnings of vengeful behavior, a German group led by neuropsychologist Ulrike Krämer allowed people
who had been provoked during an experiment to punish their antagonist with a blast of extremely annoying noise. While
the subjects pondered how loud to set the volume, the dorsal striatum, part of the brain’s reward circuitry, lit up at the
prospect of retaliation. “We have this primitive brain that says, ‘Do it! Do it!’” Denson says. Similarly, people asked to
imagine themselves engaging in aggressive behavior actively suppress activity in the prefrontal cortex, where social
information is processed. By deliberately inhibiting our natural social response, we make ourselves detached enough to
strike out.

Historically, moralists have not paid much heed to the findings of science, and it is safe to say that all the brain-scans in
the world probably will not persuade modern theologians to recalculate the wages of sin. But they might want to pay heed
to one recent finding from modern neuroimaging: It turns out that acting virtuously does not really require a hair shirt. In
fact, research suggests it feels pretty good.

Jordan Grafman recently found that virtue literally is its own reward. Altruistic behavior sends reward-related brain
systems into a pleasurable tizzy—even more so than the prospect of self-interested gain. “The big punch line is that all
things being equal, your reward system fires off a lot more when you’re giving than when you’re taking,” says Grafman,
who is chief of the cognitive neuroscience section at the National Institute of Neurological Disorders and Stroke. Call it the
dirty little secret about being good: It might be even more fun than being wicked.

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The Angry Brain: Neural Correlates of Anger, Angry
Rumination, and Aggressive Personality

Thomas F. Denson1, William C. Pedersen2*, Jaclyn Ronquillo3*,
and Anirvan S. Nandy3

Abstract

& Very little is known about the neural circuitry guiding anger,
angry rumination, and aggressive personality. In the present
fMRI experiment, participants were insulted and induced to
ruminate. Activity in the dorsal anterior cingulate cortex was
positively related to self-reported feelings of anger and in-
dividual differences in general aggression. Activity in the me-
dial prefrontal cortex was related to self-reported rumination
and individual differences in displaced aggression. Increased

activation in the hippocampus, insula, and cingulate cortex
following the provocation predicted subsequent self-reported
rumination. These findings increase our understanding of
the neural processes associated with the risk for aggressive
behavior by specifying neural regions that mediate the
subjective experience of anger and angry rumination as well
as the neural pathways linked to different types of aggressive
behavior. &

INTRODUCTION

Despite the enormous costs of anger and aggression,
very little is known about the neural mechanisms guiding
these phenomena (Davidson, Putnam, & Larson, 2000).
Understanding these neural mechanisms is important
because it provides insight into concrete, biological pro-
cesses that predispose individuals for aggression. The
uncovering of these processes has long been a central
concern of neuroscience as well as social, clinical, per-
sonality, and forensic psychology.

For most people, angry feelings dissipate within 10 to
15 min (Tyson, 1998; Fridhandler & Averill, 1982). How-
ever, recent research suggests that dwelling on anger-
inducing experiences (i.e., angry rumination) may be
particularly harmful because it increases aggression over
extended periods of time, even toward the innocent
(Bushman, Bonacci, Pedersen, Vasquez, & Miller, 2005;
Bushman, 2002). Despite its importance, no study has
examined the neural substrate of angry rumination. In
the first fMRI experiment to do so, we provide a broad
view of the neural processes that occur when angered,
when ruminating about an interpersonal insult, and
how these processes vary as a function of aggressive
personality. The present social neuroscience approach
increases our understanding of the neural processes
underlying risk for aggression.

Neural Regions Underlying Anger

Identifying the neural foundations of anger has proven
difficult because prior work has relied on patients with
brain lesions or neuroimaging paradigms that examined
anger indirectly. This latter group of just nine studies
investigated neural responses to angry faces and brain
regions active during the recall of anger-inducing life
experiences. Two recent meta-analyses of these studies
revealed that some of the most prominent areas of brain
activation were the medial prefrontal cortex (mPFC), the
ventromedial PFC (vmPFC), the anterior cingulate cor-
tex (ACC), the posterior cingulate cortex (PCC), the lat-
eral PFC, and the thalamus (Murphy, Nimmo-Smith, &
Lawrence, 2003; Phan, Wager, Taylor, & Liberzon, 2002).1

A social neuroscience approach combines elements of
social psychology and cognitive neuroscience. In a re-
view of the literature on aggressive behavior, Anderson
and Bushman (2002) refer to interpersonal provocation
as ‘‘perhaps the most important single cause of human
aggression’’ (p. 37). In fact, it is such a reliable means of
inducing anger and aggression that it is, by far, the most
common experimental manipulation used in social psy-
chological research. No functional imaging study, to our
knowledge, has specifically examined an anger-inducing
interpersonal insult, despite its ecological validity and
relevance to real-world aggression.

Moreover, no study has examined the neural substrate
that mediates the subjective experience of anger. We
hypothesized a special role for the dorsal ACC (dACC) in
this regard. Activity in the dACC is associated with a
number of negative emotions including the intensity of

1University of New South Wales, Sydney, Australia, 2California
State University, Long Beach, 3University of Southern California
*These authors contributed equally to the research.

D 2008 Massachusetts Institute of Technology Journal of Cognitive Neuroscience 21:4, pp. 734–744

social distress following social rejection (Eisenberger,
Lieberman, & Williams, 2003), and distress associated
with physical pain (Rainville, Duncan, Price, Carrier, &
Bushnell, 1997). The dACC has also been discussed in
terms of a ‘‘neural alarm system’’ because it is active
in response to incongruent stimuli and goals (Kross,
Egner, Ochsner, Hirsch, & Downey, 2007; Eisenberger &
Lieberman, 2004). Interpersonal provocation is likely
just such a stimulus. Thus, in response to the interper-
sonal provocation of the current study, we hypothesized
that the dACC would be positively related to the inten-
sity of self-reported anger.

Neural Regions Underlying Angry Rumination

When upset by a provocation, there are a number of
emotion regulation strategies one may use to cope with
the aversive event. Rumination is one such strategy. Two
types of rumination have been examined in relation to
anger. One is known as provocation-focused rumination,
which involves thinking about and reliving a negative
event or an angering incident (Sukhodolsky, Golub, &
Cromwell, 2001; Caprara, 1986). A second type is self-
focused rumination, which refers to directing attention
inward on the self, particularly on one’s own negative
emotions (Trapnell & Campbell, 1999; Lyubomirsky &
Nolen-Hoeksema, 1995; Nolen-Hoeksema & Morrow,
1993). Following a provocation, both types of rumina-
tion increase anger and aggression (Denson, Pedersen,
& Miller, 2006; Bushman et al., 2005, Experiment 2;
Rusting & Nolen-Hoeksema, 1998).

Because angry rumination contains components of
self-reflection, social cognition, negative affect, and emo-
tion regulation by maintaining or increasing anger after a
provocation, it should involve the recruitment of brain
regions associated with these mental events such as the
mPFC, the lateral PFC, the insula, and the cingulate
cortex (Amodio & Frith, 2006; Lévesque et al., 2003;
Ochsner, Bunge, Gross, & Gabrieli, 2002; Phan et al.,
2002). Although no neuroimaging study has directly
manipulated rumination, Ray et al. (2005) reported that
when participants were asked to decrease their negative
affective responses to aversive photographs, trait rumi-
nation was correlated with ACC and mPFC activity. The
mPFC is associated with the self-awareness of emotions
and self-relevant cognition (Macrae, Moran, Heatherton,
Banfield, & Kelley, 2004; Ochsner et al., 2004; Lane, Fink,
Chau, & Dolan, 1997). The mPFC is active when partic-
ipants are asked to monitor their emotional state, reflect
on their feelings, and when reappraising their responses
to distressing visual stimuli (Amodio & Frith, 2006;
Ochsner et al., 2002, 2004). Moreover, the mPFC also
appears related to the personality trait of self-awareness
(Eisenberger, Lieberman, & Satpute, 2005). Because ru-
mination involves thinking about and regulating one’s
affective state, the mPFC should be especially relevant to
rumination.

As was the case with anger, we also sought to uncover
the neural systems mediating the subjective experience
of rumination. Following the above reasoning, we ex-
pected activity in the mPFC to be positively correlated
with self-reported rumination during the rumination task
(e.g., Ray et al., 2005; Ochsner et al., 2002, 2004; Lane
et al., 1997). We also expected that regions associated
with memory encoding would be especially important
in this regard (Kensinger, Clarke, & Corkin, 2003). Be-
cause real-world provocations are highly salient and self-
relevant, we expected that the hippocampus should be
active in response to the provocation. Because deeper
encoding should increase the accessibility of the provo-
cation in memory, the degree of hippocampus activity
should be a particularly good indicator of the intensity of
self-reported rumination. A second, compatible possibil-
ity concerns the role that the hippocampus is posited
to play in monitoring discrepancies between expected
events and actual situations (Gray & McNaughton, 2000).
This discrepancy-monitoring system is believed to mo-
tivate behavior designed to reduce the problem that
produced the discrepancy. Rumination might be one
such means of mentally resolving the conflict. Thus, in
the context of interpersonal provocation, research and
theory suggest that hippocampus activity in response
to the provocation and mPFC activity during the rumi-
nation task would correlate with self-reported angry
rumination.

Neural Regions Underlying
Aggressive Personality

Why do some people angrily ‘‘fly off the handle’’ in
response to provocation, whereas others ‘‘take it out’’
on innocents such as their romantic partners? Social
psychology has unequivocally demonstrated that even
mentally healthy individuals are capable of consequen-
tial acts of aggression (Anderson & Bushman, 2002), and
some individuals are more prone to aggression than
others (Bettencourt, Talley, Benjamin, & Valentine,
2006). People often respond to identical provocations
very differently. Recent research supports these notions
by providing evidence for the existence of two unique
aggressive personality dimensions (Denson et al., 2006).

The first aggressive personality dimension is general
aggression, which is characterized by frequent anger
and direct retaliation in response to interpersonal prov-
ocation in both laboratory experiments and real-world
settings (Bettencourt et al., 2006; Buss & Perry, 1992).
Because we expected the dACC to be related to the
subjective experience of anger, we also expected general
aggression to be associated with activity in the dACC
because this personality dimension is associated with
intense anger and impulsive aggression. Indirect support
for this hypothesis comes from an fMRI study that ma-
nipulated ostracism. In this study, a composite measure
of trait anger and hostility was moderately positively

Denson et al. 735

correlated with reactivity in the dACC (Eisenberger, Way,
Taylor, Welch, & Lieberman, 2007).

The second aggressive personality dimension is dis-
placed aggression, which is characterized by respond-
ing to insults with rumination instead of immediate
aggression, and eventually ‘‘taking out’’ aggressive urges
on the innocent. When those high in displaced aggres-
sion are provoked, they harm innocents in laboratory
experiments and report increased levels of romantic
partner abuse and driving aggression, whereas those
high in general aggression do not (Denson et al., 2006).
We expected displaced aggression to be primarily as-
sociated with activity in the mPFC and the hippocam-
pus. Because individuals high in displaced aggression
report ruminating when provoked, the mPFC and the
hippocampus should be especially relevant to individu-
al differences in displaced aggression, but not general
aggression.

METHODS

Participants

Twenty right-handed undergraduates (12 women; Mage =
18.68, SDage = 0.75, 70% white) volunteered to partici-
pate in exchange for extra course credit. In order to
reduce suspicion, participants were told that they would
be participating in an experiment on cognitive ability and
mental imagery.

Materials and Procedure

Initial Questionnaire Session

During an initial session, participants completed a safety
screening questionnaire, the 29-item Aggression Ques-
tionnaire (AQ; a = .93, M = 3.28, SD = 1.04; Buss &
Perry, 1992), and the 31-item Displaced Aggression Ques-
tionnaire (DAQ; a = .96, M = 2.80, SD = 1.80; Denson
et al., 2006), which assess individual differences in gen-
eral aggression and displaced aggression, respectively.
The AQ is reliable and has proven useful in predicting
laboratory and real-world aggression (Bushman & Wells,
1998; Buss & Perry, 1992). The DAQ has good internal
consistency, test–retest reliability, convergent validity,
and discriminant validity (Denson et al., 2006). By com-
parison with the AQ, the DAQ is a stronger predictor of
laboratory displaced aggression and real-world indica-
tors of displaced aggression such as domestic abuse and
road rage (Denson et al., 2006). Participants responded
on a scale ranging from 1 (extremely uncharacteristic of
me) to 7 (extremely characteristic of me). These ques-
tionnaires were completed as part of a larger packet of
measures unrelated to anger and aggression. No partic-
ipants reported noticing a suspicious relationship be-
tween the initial questionnaire session and the imaging
experiment.

Provocation Procedure

Approximately 10 to 14 days later, participants returned
to the imaging center for the experiment. Upon arrival,
participants completed baseline measures of mood with
the short version of the Profile of Mood States (POMS;
Shacham, 1983). Of particular interest was the anger/
hostility subscale (a = .70). Two minutes of functional
baseline fixation data were collected while participants
were instructed to stare at a green fixation point in the
center of the screen visible through mirrors. Using a
provocation manipulation adapted from previous re-
search, participants were presented with four easy and
eight difficult anagrams for 15 sec each (e.g., Pedersen,
Gonzales, & Miller, 2000). They were asked to state their
answer out loud or say ‘‘no answer’’ if they did not know
the answer. As part of the provocation manipulation, the
experimenter interrupted participants thrice requesting
that they speak louder. During the third interruption,
which served as the anger induction, the experimenter
stated in a rude, upset, and condescending tone of voice
‘‘Look, this is the third time I have had to say this! Can’t
you follow directions?’’ Immediately following the insult
(<500 msec), an additional 2 min of functional data were collected while participants stared at a fixation point. Because the insinuation was that participants were not intelligent enough to follow simple instructions, the prov- ocation manipulation represented the delivery of an unjustified insult. This provocation manipulation has suc- cessfully angered participants in prior research (Pedersen et al., 2000).

Directed Rumination Manipulation

In a within-participants design, individuals were assigned
to the provocation-focused rumination, self-focused rumi-
nation, and distraction conditions in counterbalanced order
via a Graeco-Latin square design. In the provocation-
focused rumination condition, participants were pre-
sented with a series of statements on the monitor and
asked to think about each statement for 15 sec each
(e.g., ‘‘Think about whom you have interacted with in
the experiment up to this point,’’ ‘‘Think about exactly
what you have done from the start of the study until
now’’). Statements from the self-focused rumination and
distraction conditions were taken from Rusting and Nolen-
Hoeksema (1998; also used in Bushman et al., 2005). In the
self-focused rumination condition, participants were
asked to think about a series of self-referential statements
that did not mention anger or other emotions (e.g., ‘‘Think
about why people treat you the way they do,’’ ‘‘Think
about why you react the way you do’’). In the distraction
condition, participants were asked to think about a series
of affectively neutral statements (e.g., ‘‘Think about the
layout of the local post office,’’ ‘‘Think about a double-
decker bus driving down the street’’). In each of the three
conditions, 12 statements were presented for 15 sec each,

736 Journal of Cognitive Neuroscience Volume 21, Number 4

such that each condition took 3 min to complete. The
conditions were separated by 16-sec rest periods. Func-
tional EPI whole-brain images were taken during the entire
directed rumination period.

Questionnaires

Upon completion of scanning, participants reported
potential emotional responses to the provocation with
the Positive and Negative Affect Schedule (PANAS-X;
Watson & Clark, 1994). Of particular interest was the
hostility subscale which assesses angry affect (a = .81).
We also assessed self-reported rumination during each
of the three blocks of rumination. These were ratings of
how often and how strongly (1 = not at all, 7 = very
often) participants thought about their performance on
the anagram task. All participants were then fully de-
briefed and thanked.

Image Acquisition

Participants viewed the experimental tasks through mir-
rors, which were presented on a high-resolution moni-
tor placed at the end of a Siemens Magnetom 3-T
scanner. Padded foam head constraints controlled par-
ticipant movement. Once participants were situated in
the scanner, a localizer scan was conducted to ensure
proper image acquisition. Next, we acquired 3-D struc-
tural images (MP-RAGE, 192 slices, FOV = 256 mm, thick-
ness = 1 mm, TR = 2070 msec, TE = 4.14 msec). Prior
to beginning the functional scan, we visually inspected a
dummy EPI scan (8 sec) to ensure the quality of the
functional data. Whole-brain functional images were
acquired with interleaved EPI pulse sequence (29 axial
slices, slice thickness = 4 mm, FOV = 24 cm, TE =
68 msec, TR = 2000 msec, 908 flip angle).

Statistical Analysis

All analyses were conducted with Brain Voyager QX
(Brain Innovation). Data were preprocessed using mo-
tion and scan-time corrections, and smoothed with a
Gaussian temporal filter. Brains were normalized via
Talairach transformation (Talairach & Tournoux, 1988),
and regions were identified using the Talairach Daemon
(Lancaster, Summerln, Rainey, Freitas, & Fox, 1997),
which is an electronic database of Talairach coordinates.
Functional images were coregistered with the normal-
ized structural images. All BOLD responses are ex-
pressed in percent signal change. For comparisons
between conditions, whole-brain random-effects general
linear model (GLM) group analyses were conducted
with participant specified as the random factor. The
provocation was modeled as the difference in activation
during the two fixation blocks (i.e., 2 min provocation
fixation > 2 min baseline fixation) adjusted for the he-
modynamic response function. For the rumination data,

because only minor differences were found between
provocation- and self-focused rumination, we averaged
these two conditions and contrasted them against the
distraction condition (rumination > distraction).2 The
rumination scan was modeled as the difference in acti-
vation between the rumination blocks and the distrac-
tion condition (rumination > distraction) adjusted for
the hemodynamic response function. We controlled
Type I error with the false discovery rate (FDR) set at
.05, voxelwise p < .005.

For correlating the self-report data with BOLD re-
sponses, we selected clusters for these analyses based
on the results of our whole-brain main-effects analyses.
The activity in these clusters was averaged such that a
mean percent signal change was calculated for each
participant. We then computed correlations between
our self-report measures and the average activity in
these ROIs.

RESULTS

Manipulation Checks

Participants reported an increase in anger from baseline
as a result of the provocation procedure, thus indicating
a successful anger induction [t(15) = 5.32, p < .001, d = 1.52]. As expected, participants reported thinking more about the provocation during the rumination block than during the distraction block [t(19) = 3.44, p = .003, d = 0.78], thus indicating a successful rumi- nation manipulation. For the personality variables, we computed partial correlations controlling for gender, because men rated themselves higher than women in general aggression [t(18) = 3.48, p = .003, d = 1.75] and displaced aggression [t(18) = 3.39, p = .003, d = 1.71]. Consistent with prior research (Denson et al., 2006), general and displaced aggression were significantly cor- related (r = .68, p = .001).

Anger: Neural Regions, Subjective Experience,
and Personality3

Table 1 displays regions active in response to the prov-
ocation (i.e., provocation > baseline fixation). These
data suggest a substantial degree of consistency with
prior research using autobiographical recall paradigms
and exposure to angry faces (Murphy et al., 2003; Phan
et al., 2002). As expected, activation in the left dACC was
positively correlated with self-reported feelings of anger
(r = .56, p < .05), but no other emotions (see Table 2). This provides the first evidence for a neurophysiological basis underlying the intensity of the subjective anger experience. By contrast, activity in the right dACC was correlated with the Guilt subscale of the PANAS-X. We expand upon this finding in the Discussion section.

As expected, general aggression was associated with
increased activity in the left dACC following provocation

Denson et al. 737

(r = .61, p < .05), but displaced aggression was not (r = .24, ns). Moreover, displaced aggression was sig- nificantly associated with increased activity in the mPFC (r = .57, p < .05), but general aggression was not (r = .37, ns) (see Table 3 and Figure 1). Simultaneously regressing BOLD responses on direct aggression, dis- placed aggression, and gender revealed an identical

pattern of results. Specifically, general aggression pre-
dicted dACC activity (b = .49, t = 2.59, p = .02), but
displaced aggression did not (b = !.14, t = !0.76, ns,
R2 = .42). By contrast, displaced aggression marginally
predicted mPFC activity (b = .21, t = 1.85, p = .09), but
general aggression did not (b = .01, t = 0.10, ns, R2 =
.33). Thus, these different personality dimensions were

Table 1. Brain Regions Active after Exposure to an Interpersonal Provocation Relative to Baseline Fixation

Talairach Coordinates

Region x y z Cluster Size (Voxels) Mean (SE) Percent Signal Change Significance Test

Dorsal Anterior Cingulate

Right 8 24 34 787 0.62 (0.07) t(15) = 9.23, p < .00001

Left !7 22 33 731 0.59 (0.12) t(15) = 4.79, p < .001

Rostral Anterior Cingulate

Rightregion1 5 32 15 446 0.62 (0.13) t(15) = 4.85, p < .001

Rightregion2 4 30 !7 719 1.06 (0.29) t(15) = 3.63, p < .001

Left !3 33 !8 590 1.25 (0.24) t(15) = 5.14, p < .001

Insula

Right 37 !2 7 637 0.50 (0.11) t(15) = 4.66, p < .001

Left !37 4 15 767 0.54 (0.09) t(15) = 6.13, p < .0001

Posterior Cingulate

Right 5 !52 21 796 0.61 (0.08) t(15) = 7.48, p < .0001

Leftregion1 !7 !44 23 240 0.50 (0.07) t(15) = 7.02, p < .00001

Leftregion2 !2 !21 28 276 0.59 (0.12) t(15) = 5.01, p < .001

Medial Frontal Gyrus

Rightregion1 6 47 13 764 0.72 (0.10) t(15) = 7.20, p < .0001

Rightregion2 5 45 19 562 0.59 (0.07) t(15) = 8.65, p < .00001

Medial Frontal Gyrus

Left !5 32 !11 555 1.39 (0.28) t(15) = 4.92, p < .001

Lateral Middle Frontal Gyrus

Right 33 47 7 504 0.76 (0.11) t(15) = 6.68, p < .0001

Left !32 47 9 617 0.78 (0.15) t(15) = 5.10, p < .001

Hippocampus

Right 30 !31 !3 1,013 0.49 (0.07) t(15) = 6.73, p < .00001

Left !30 !31 !3 934 0.60 (0.08) t(15) = 7.22, p < .00001

Thalamus

Left !13 !10 3 675 0.60 (0.12) t(15) = 5.02, p < .001

738 Journal of Cognitive Neuroscience Volume 21, Number 4

associated with the recruitment of separate neural re-
gions when confronted with a provocation. Specifically,
general aggression was more strongly correlated with a
region associated with the intensity of anger, whereas
displaced aggression was more strongly correlated with
a region associated with self-reflection, the monitoring
of negative emotions, and emotion regulation.

Angry Rumination: Neural Regions and
Aggressive Personality

Table 4 displays the regions active during the directed
rumination task relative to distraction (rumination >
distraction). As expected, rumination increased activity
in regions associated with emotion regulation, negative
affect, and social cognition such as the cingulate cortex,
the mPFC, the lateral PFC, and the insula. Also as ex-
pected, displaced aggression was positively associated
with activity in the left mPFC (r = .55, p = .02), but
general aggression was not (r = .22, ns) (Table 3).
Simultaneously regressing mPFC activity on direct ag-
gression, displaced aggression, and gender revealed an
identical pattern of results. Specifically, displaced aggres-
sion predicted mPFC activity (b = .52, t = 2.65, p = .02),
but general aggression did not (b = !.20, t = !1.00, ns,
R2 = .35). These results further support the notion that
individuals who exhibit high levels of displaced aggres-
sion tend to ruminate to a greater extent following

provocations than those who exhibit low levels of dis-
placed aggression.

Angry Rumination: Subjective Experience

We wished to determine whether the degree of neural
activity experienced following the provocation ma-
nipulation (especially in the hippocampus) would be
associated with the degree of self-reported rumination
about the provocation during the directed rumination
task. This was indeed the case. Activity in the hippo-
campus following the provocation was correlated with
self-reported angry rumination (r = .51, p < .05), sug- gesting that those who deeply encoded the provocation in memory and/or were deeply affected by the discrep- ancy between actual and expected events also tended to ruminate about the insult during the subsequent di- rected rumination task (Figure 2).

Because displaced aggression is characterized by ru-
mination in response to provocation, we also expected
individual differences in this trait to correlate with hippo-
campal activity. Displaced aggression was moderately
correlated with hippocampal activation, yet not signifi-
cantly so (r = .40, p = .14). Nonetheless, the magnitude
of the relationship between general aggression and
hippocampal activity was half the size (r = .21, p =
.44). Although not significant, the magnitude and direc-
tion of these results are consistent with our theorizing.

Also of interest was that activity in the right insula was
correlated with the degree of self-reported rumination
(r = .54, p < .05). This region incorporates physiological information from the body, which some have suggested forms the neural substrate for the subjective sense of self and feeling states (Critchley, Wiens, Rotshtein, Öhman, & Dolan, 2004; Damasio, 1994). Two additional regions commonly involved in negative emotional experience, the rACC and the PCC, were correlated with self-reported rumination (rs = .60 and .52, ps < .05). These findings are especially noteworthy given that brain activity following the provocation temporally preceded self-reported rumi- nation. During the directed rumination task, activation in the left mPFC was marginally related to the intensity of self-reported rumination (r = .42, p = .06). In summary, regions associated with memory encoding, conflict mon- itoring, the processing of internal states, and negative affective responses to the provocation correlated with subsequent rumination, whereas increased activity in a region associated with self-reflection, emotion regula- tion, and social cognition (i.e., the mPFC) was correlated with rumination during the task.

DISCUSSION

Our findings provide novel insight into the neural path-
ways underlying anger, angry rumination, and aggressive
personality. Such understanding represents a first step

Table 2. Correlations between BOLD Response in the
dACC and State Mood Measures after Exposure to a Verbal
Interpersonal Provocation (Provocation > Baseline)

PANAS Subscales Left dACC Right dACC

Hostility .56* .40

Guilt .42 .58*

Sadness .19 !.01

Fear .13 .23

Joviality .10 !.08

Self-assurance .28 !.11

Attentiveness .18 .17

Shyness .05 !.03

Fatigue .04 !.26

Serenity !.07 !.17

Surprise .23 !.06

Basic positive affect .26 .01

Basic negative affect .42 .41

Positive emotion .21 !.07

Negative emotion .36 .44

The last four subscales are not independent of the preceding subscales.

*p < .05.

Denson et al. 739

toward forming the basis of successful and enduring,
evidence-based aggression-reduction interventions. The
present research contributes to our knowledge on these
topics in a number of ways. First, we provided evidence
that the dACC is related to the subjective experience of
anger. The emerging picture of the role of the dACC in

social–affective contexts is that it may be involved in
producing feelings associated with the intensity of a
number of emotions that are specific to negative social
situations such as interpersonal provocation and rejec-
tion (e.g., Eisenberger et al., 2003, 2007; Kross et al.,
2007). Our data are also consistent with the conceptu-
alization of the dACC as a ‘‘neural alarm system’’ that is
sensitive to incongruent stimuli and goals (Kross et al.,
2007; Eisenberger & Lieberman, 2004). In our case, the
interpersonal provocation was likely unexpected and
incongruent with participants’ positive self-image. In-
deed, in the absence of prior knowledge about an
individual, people tend to exhibit an initial positivity
bias as a default position (Klar & Giladi, 1997; Sears,
1983). Furthermore, although prior research has exam-
ined regions associated with angry memories and faces,
the current experiment represents a meaningful meth-
odological departure from prior neuroimaging experi-
ments in that previous studies of anger and aggression
have relied on autobiographical episodic recall and angry
faces as stimuli. By using a provocation that modeled a
real-world anger-inducing situation, the current experi-
ment provides a relatively high level of ecological valid-
ity, despite participants being in an MRI scanner.

Table 3. Correlations between BOLD Activation in the Left
dACC and the mPFC and Aggressive Personality Dimensions
following Provocation (Provocation > Baseline) and during
Rumination (Rumination > Distraction)

Brain Region General Aggression Displaced Aggression

Post-provocation

dACC .61* .24

mPFC .37 .57*

During Rumination

dACC .20 .16

mPFC .22 .55*

*p < .05.

Figure 1. Brain activation following provocation. (A) Activity in the left dACC, which was positively associated with self-reported anger and
individual differences in general aggression following the provocation. (B) Activity in the right mPFC, which was positively associated with
individual differences in displaced aggression. The scatterplots below each panel depict these correlations. The y-axes represent BOLD responses,
which are expressed in percent signal change relative to the baseline fixation.

740 Journal of Cognitive Neuroscience Volume 21, Number 4

Table 4. Brain Regions Active during Rumination Relative to Distraction

Talairach Coordinates
Region x y z Cluster Size (Voxels) Mean (SE) Percent Signal Change Significance Test
Dorsal Anterior Cingulate

Right 7 15 35 401 0.71 (0.14) t(19) = 5.13, p < .001

Left !7 15 35 618 0.72 (0.11) t(19) = 6.39, p < .00001

Rostral Anterior Cingulate

Right 3 35 9 736 0.82 (0.15) t(19) = 5.67, p < .0001

Left !9 37 13 402 0.69 (0.13) t(19) = 5.20, p < .0001

Insula

Right 38 !3 7 740 0.68 (0.10) t(19) = 6.50, p < .00001

Left !38 !3 7 827 0.66 (0.11) t(19) = 6.27, p < .00001

Posterior Cingulate

Rightregion1 6 !16 39 422 0.59 (0.10) t(19) = 5.79, p < .0001

Rightregion2 6 !53 25 377 0.60 (0.11) t(19) = 5.34, p < .0001

Leftregion1 !6 !15 35 333 0.64 (0.11) t(19) = 5.84, p < .0001

Leftregion2 !6 !58 22 488 0.57 (0.11) t(19) = 5.00, p < .0001

Medial Frontal Gyrus

Right 9 42 15 451 0.69 (0.12) t(19) = 6.02, p < .00001

Left !9 50 19 339 0.52 (0.13) t(19) = 3.89, p < .001

Superior Frontal Gyrus

Right 7 48 31 509 0.69 (0.14) t(19) = 5.01, p < .0001

Left !9 46 33 601 0.82 (0.11) t(19) = 7.81, p < .000001

Precuneus

Left !9 !53 34 455 0.63 (0.10) t(19) = 6.20, p < .00001

Lateral Middle Frontal Gyrus

Right 36 45 15 684 0.74 (0.13) t(19) = 5.83, p < .0001

Left !37 46 16 368 1.31 (0.27) t(19) = 4.83, p < .001

Lateral Inferior Frontal Gyrus

Left !50 23 15 330 0.75 (0.13) t(19) = 5.80, p < .0001

Thalamus

Left !13 !21 11 160 0.60 (0.11) t(19) = 5.31, p < .0001

Denson et al. 741

Our data also illustrate the neural regions underlying
angry rumination. Activity during angry rumination was
apparent in regions associated with the intensity of
negative affect as well as ‘‘top–down’’ emotion regula-
tion regions such as the lateral PFC and the mPFC.
Indeed, the mPFC appears to be associated with the
awareness and regulation of one’s negative mood
(Macrae et al., 2004; Ochsner et al., 2004; Lane et al.,
1997). Broadly relevant to the current study, the mPFC is
active during impression formation (Mason & Macrae,
2004) and making attributions and determining the
mental states of others (Harris, Todorov, & Fiske,
2005), both of which can occur during rumination. Thus,
the current findings are highly consistent with research
examining rumination as a multifaceted emotion regu-
lation strategy that maintains or increases negative affect
(Denson et al., 2006; Bushman et al., 2005; Ray et al.,
2005; Miller, Pedersen, Earleywine, & Pollock, 2003).

We also identified brain regions associated with the
subjective experience of rumination. Notably, increased
encoding of the provocation in memory as assessed by
hippocampus activation predicted subsequent rumina-
tion. However, the mechanism whereby this occurs
remains unclear. Presumably, increased encoding leads
to greater accessibility in memory, yet it is also likely that
greater encoding may have occurred due to bewilder-
ment regarding the unexpected and unjustified nature
of the provocation. If true, then increased rumination
could be a result of cognitively incorporating the prov-
ocation into existing knowledge structures or mentally
attempting to resolve the conflict. Consistent with this

latter view, the hippocampal activity observed in the
present research can be interpreted in light of Gray and
McNaughton’s (2000) theorizing that the hippocampus
is involved in comparing discrepancies between ex-
pected and actual events. They also propose that this
hippocampal comparator mechanism is highly sensitive
to signals of punishment, which is relevant to the
provocation used in the present research. Furthermore,
hippocampal activity is posited to result in behaviors
designed to solve the problem that produced the dis-
crepancy. In the context of the present study, rumina-
tion may have been just such an attempt at mentally
resolving interpersonal conflict.

The final and perhaps most intriguing contribution of
our findings is that they suggest a neural basis for dif-
ferences in aggressive behavior, such that within seconds
of being insulted, differences emerged in the degree of
activity associated with the dACC and the mPFC as a
function of aggressive personality. Individual differences
in general aggression were more strongly correlated
with exacerbated activity in a region associated with
the intensity of anger, pain, social distress, and cognitive
conflict monitoring (i.e., dACC), whereas individual
differences in displaced aggression were more strongly
correlated with a region associated with self-relevant
cognition, the self-awareness of emotions, and emotion
regulation (i.e., the mPFC). It is highly likely that activity
in these regions is at least partially responsible for the
observed differences in subsequent cognition, affect,
and behavior among those high in general and displaced
aggression (Bettencourt et al., 2006; Denson et al., 2006;
Buss & Perry, 1992).

One unexpected finding was that activity in the right
dACC was correlated with the Guilt subscale of the
PANAS-X. In hindsight, these results appear sensible
given our manipulation, whereby a high status experi-
menter communicated (albeit rudely) that the participant
was not speaking loud enough. Thus, some participants
may have inferred that their actions were invalidating a
quite important and expensive experiment. However, we
do not believe that this measure truly assesses feelings of
guilt as the subscale name implies for two reasons. First,
the subscale combines items assessing both shame and
guilt despite evidence that they are distinct emotions
(e.g., Tangney, 2002). Second, and more importantly, a
post hoc analysis of the six individual items in the Guilt
subscale revealed that the individual items ‘‘guilty’’ and
‘‘ashamed’’ were not significantly correlated with dACC
activity (right or left). However, three of the individual
items from the PANAS-X Guilt subscale demonstrated
strong associations with the right dACC. These were
‘‘dissatisfied with self’’ (r = .70, p < .01), ‘‘disgusted with self’’ (r = .46, p = .07), and ‘‘blameworthy’’ (r = .62, p = .01). In a post hoc analysis, we created an overall ‘‘social distress’’ composite by averaging these three items (a = .80). Consistent with research demonstrating associations between feelings of social distress and the

Figure 2. Hippocampal activation following provocation. Activity in
the left hippocampus was correlated with the intensity of subsequent
self-reported angry rumination during the rumination task. The y-axis
represents BOLD responses, which are expressed in percent signal
change relative to the baseline fixation.

742 Journal of Cognitive Neuroscience Volume 21, Number 4

dACC in the context of social rejection manipulations
(e.g., being left out of a ball-tossing game; Eisenberger
et al., 2003, 2007), this social distress variable was corre-
lated with activity in the right (but not left) dACC follow-
ing the provocation (r = .72, p = .002). These results are
consistent with the notion that, in addition to anger, the
provocation may have elicited feelings of social devalua-
tion and self-reproach rather than true guilt or shame.

There were a number of limitations associated with
the current study. Due to practical considerations, the
directed rumination task was conducted within partic-
ipants rather than between participants. Although our
significant results suggest otherwise, this might have
resulted in carryover effects whereby some individuals
were unable to stop ruminating about the provocation
even in the distraction condition. Another shortcoming
of the current experiment was the temporal placement
of the state mood measures that assessed the reaction to
the provocation at the end of the experiment. Obtaining
self-report data after removing participants from the
scanner rather than immediately following the provoca-
tion might have introduced retrospective memory
biases. However, this was done because we wanted to
assess a wide variety of emotional reactions in the
current study. To do so would have required an exces-
sive burden on participants if they were asked to rate
their mood state on all 65 items in the scanner. We also
felt that an earlier positioning of these measures would
arouse suspicion by inquiring about the participants’
mood immediately following the provocation. Another
unresolved issue in the present research is the nature of
the functional connections between brain regions. Due
to the temporal limitations of fMRI methods, we were
unable to specify a temporal pathway for the processes
underlying anger and aggression. Future research re-
mains to explore the temporal pattern of activation in
response to provocation. Finally, our small sample size
limited statistical power. Although small sample sizes are
common in neuroimaging research, when examining
individual differences and correlations with behavioral
data, larger samples are desired in order to detect
smaller, yet meaningful, differences. Indeed, most effect
sizes in psychology are in the small-to-moderate range
(e.g., r < .30; Hemphill, 2003). Thus, when it is not possible to increase sample size, it is crucial that re- searchers select highly reliable and valid instruments when mixing self-report methods with neuroimaging in order to reduce measurement error. Despite these remaining issues, it is our hope that the data presented here may eventually help eliminate the harm associated with anger, angry rumination, and aggressive personality.

Acknowledgments

This work was supported by grants from California State Uni-
versity, Long Beach, and the David and Dana Dornsife Cognitive
Neuroscience Imaging Center at USC. We thank T. F. D.’s

dissertation committee (in alphabetical order): Brian Lickel,
Zhong-Lin Lu, Norman Miller (chair), and Stephen J. Read. We
also thank Marija Spanovic and Eduardo A. Vasquez for help with
data collection and Jiancheng Zhuang. We thank J. David
Creswell and anonymous reviewers for comments on an earlier
draft of this article.

Reprint requests should be sent to Thomas F. Denson, School
of Psychology, University of New South Wales, Sydney, NSW
2052, Australia, or via e-mail: t.denson@unsw.edu.au.

Notes

1. The amygdala was not associated with anger.
2. Relative to self-focused rumination, provocation-focused
rumination elicited slightly more activity in the right middle
frontal gyrus [M = 0.042, SE = 0.012, t(19) = 3.58, p = .002],
the right PCC [M = 0.036, SE = 0.008, t(19) = 4.35, p < .001], and the left precuneus [M = 0.027, SE = 0.007, t(19) = 3.73, p = .001. These results suggest that, following a provocation, both types of rumination recruit highly similar neural substrates relative to distraction, even though the content of the two types of rumination may differ. 3. Because of an imaging protocol adjustment, provocation data from the first four participants were removed from analyses.

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744 Journal of Cognitive Neuroscience Volume 21, Number 4

Research Article

The Sunny Side of Fairness
Preference for Fairness Activates Reward Circuitry (and
Disregarding Unfairness Activates Self-Control Circuitry)

Golnaz Tabibnia, Ajay B. Satpute, and Matthew D. Lieberman

University of California, Los Angeles

ABSTRACT—Little is known about the positive emotional
impact of fairness or the process of resolving conflict be-
tween fairness and financial interests. In past research,
fairness has covaried with monetary payoff, such that the
mental processes underlying preference for fairness and
those underlying preference for greater monetary outcome
could not be distinguished. We examined self-reported hap-
piness and neural responses to fair and unfair offers while
controlling for monetary payoff. Compared with unfair
offers of equal monetary value, fair offers led to higher
happiness ratings and activation in several reward regions
of the brain. Furthermore, the tendency to accept unfair
proposals was associated with increased activity in right
ventrolateral prefrontal cortex, a region involved in emo-
tion regulation, and with decreased activity in the anterior
insula, which has been implicated in negative affect. This
work provides evidence that fairness is hedonically valued
and that tolerating unfair treatment for material gain
involves a pattern of activation resembling suppression of
negative affect.

Anyone who has watched children negotiate how to share a piece

of cake knows that humans are exquisitely sensitive to fairness.
Although economic models of decision making have tradition-
ally assumed that individuals are motivated solely by material

utility (e.g., financial payouts) and are not directly affected by
social factors such as fairness (Camerer, Loewenstein, & Prelec,

2005; Kahneman, Knetsch, & Thaler, 1986), there is increasing
empirical evidence that fairness does play a role in economic
decision making (Fehr & Schmidt, 1999; Sears & Funk, 1991).

Fairness in economic-exchange tasks is typically defined as
the equitable distribution of an initial stake of money between

two people. Because fair outcomes tend to be more materially

desirable for the recipient than unfair outcomes in everyday life,
it is difficult to distinguish the desire for fairness from the desire
for material gain. Bilateral bargaining games, such as the ulti-

matum game, allow these two potential motives to be examined
separately. The results of studies using the ultimatum game indi-

cate that people are sensitive to fairness over and above its conse-
quences for material gain (Güth, Schmittberger, & Schwarze,
1982). Although there is evidence that receiving an unfair pro-

posal is associated with negative emotional responses (Sanfey,
Rilling, Aronson, Nystrom, & Cohen, 2003), no study on economic

decision making has examined whether a fair proposal produces
positive emotional responses beyond those associated with the

material gain itself.
To examine the emotional response associated with fair

treatment, we conducted two ultimatum-game experiments. In

this game, one player proposes how to split a given sum of money,
the stake, and another player responds. If the responder accepts,

each player keeps the amount allocated by the proposer. If the
responder rejects the offer, neither player receives any money.
Numerous studies using the ultimatum game have shown that

responders do not maximize material utility by accepting every
offer, but rather tend to reject offers below 20% of the stake

(Camerer & Thaler, 1995), even when there will be no future
interactions with the partner (Güth et al., 1982).

In a neuroimaging study of the ultimatum game, Sanfey et al.
(2003) observed that being treated unfairly is associated with
a negative emotional response, inferred from anterior insula

activation. They did not report what regions were more active
during fair than during unfair offers. Furthermore, because fair

offers (i.e., $5 out of $10) were always associated with higher
monetary payoff than unfair offers (e.g., $2 out of $10), it is

difficult to dissociate emotional response to fairness from emo-
tional response to monetary payoff in their study. Hence, it is
unclear from these data whether fair treatment is rewarding, in

addition to unfair treatment being aversive.
Research on social justice suggests that seeking justice is a

basic human impulse (i.e., the justice motive; Tyler, 1991), pos-
sibly rooted in a basic social motivation to be accepted (Bau-

Address correspondence to Golnaz Tabibnia, The Semel Institute for
Neuroscience and Human Behavior, University of California, Los
Angeles, 760 Westwood Plaza, C8-532, Los Angeles, CA 90095-1759,
e-mail: golnaz@ucla.edu.

PSYCHOLOGICAL SCIENCE

Volume 19—Number 4 339Copyright r 2008 Association for Psychological Science

meister & Leary, 1995). Perceived fair treatment from public

institutions (e.g., court, police) has been associated with satis-
faction beyond the effects of the material outcomes, such as

sentencing (Tyler, 1984). Critically, studies examining the im-
pact of fairness on positive and negative emotions separately,

controlling for material outcomes, have found substantial in-
creases in self-rated positive emotions associated with fair treat-
ment (De Cremer & Alberts, 2004; Hegtvedt & Killian, 1999).

If being treated fairly is experienced as rewarding, then
people should be happier with a fair offer than with an unfair

offer of the same monetary value. Similarly, brain regions as-
sociated with reward should be more active during fair than

during unfair treatment, after controlling for material utility.
These reward regions include the ventral striatum, the amygdala,
ventromedial prefrontal cortex (VMPFC), orbitofrontal cor-

tex (OFC), and midbrain dopamine regions (Cardinal, Parkin-
son, Hall, & Everitt, 2002; Trepel, Fox, & Poldrack, 2005).

Although the amygdala has commonly been associated with fear
processes, activity in this structure, particularly on the left, has
also been associated with reward processes (Hommer et al.,

2003; Zalla et al., 2000).
In order to control for material utility, we varied both the offer

amount and the stake size across trials (see Fig. 1). On different
trials, the same offer amount could represent a large percentage

of the total stake (e.g., $7 out of $15), and therefore seem fair, or
a small percentage of the total stake (e.g., $7 out of $23), and
therefore seem unfair. Differences in ratings of happiness or

reward activations observed in the comparison of such trials
cannot be attributed to the magnitude of the monetary reward

and thus are reasonably attributed to fairness.

We also examined neural response during trials in which

fairness and material outcome were at odds—that is, trials
on which the offers were unfair but financially desirable (e.g.,

$8 out of $23). Thus, we examined the neural correlates of
the tendency to accept unfair offers. Two possibilities were in-

vestigated. First, accepted unfair offers may activate reward
circuitry to a greater extent than rejected unfair offers; such a
pattern would reflect enhanced desire to accept the offers. Sec-

ond, emotion regulation may be engaged when unfair offers are
accepted, which would diminish the anterior insula’s response

and decrease the desire to reject the offer. In this case, one would
expect decreased activity in the anterior insula and increased

activity in a prefrontal region that has been associated with
emotion regulation, such as the right ventrolateral prefrontal
cortex (right VLPFC; Hariri, Bookheimer, & Mazziotta, 2000;

Lieberman et al., 2007).
Participants in our studies played the role of responder. In

Experiment 1, we measured emotional responses to each offer by
obtaining self-ratings of happiness and contempt. In Experiment
2, we measured neural responses to fair and unfair offers using

functional magnetic resonance imaging (fMRI). Participants
were told that their decisions regarding four randomly selected

offers in the experiment would actually be implemented, such
that they and the proposers of those offers would be paid or not,

according to the responses.

EXPERIMENT 1

Method

Participants and Task
Twenty-nine undergraduates (average age 5 20.1 years; 18 fe-
males, 11 males) participated after replying to a flyer indicating
that they could earn up to $52 for participation. They were told
that the proposers had submitted their offers already and would

not be present. Actually, there were no real proposers. During
the experiment, each offer was presented as follows (see Fig. 2):

First, participants were shown the purported proposer. Then, the
stake was indicated, followed by the offer. While the offer was

displayed, participants could accept or reject it. After the ex-
periment, all participants were debriefed, paid a total of $27,
and entered in a lottery in which 4 participants were selected to

receive an additional $25. Thus, all participants had a chance of
winning ‘‘up to $52,’’ as advertised. Offers ranged from 5% to

50% of the total stake size, and stakes ranged from $1 to $30. We
selected particular offer values and then matched each with two

stake sizes in order to obtain one low and one high ratio of offer to
stake size.

Measures
After playing the game, participants were asked to rate (1–7)
how much happiness and contempt they felt in response to each

of a preselected subset of 28 offers. This subset consisted of 14

Fig. 1. Illustration of the manipulation of material utility and fairness.
In the analysis of fairness preference, trials of equal material utility were
divided according to fairness (i.e., the ratio of the offer to the stake). In
this example, the offers in the top row are high-fairness offers, and those
in the bottom row are low-fairness offers, and each of two monetary
outcomes is presented in both a high-fairness offer and a low-fairness
offer. Across trials, high- and low-fairness offers had the same average
material utility.

340 Volume 19—Number 4

Fairness Is Rewarding

fair offers (! 40% of the stake) and 14 unfair offers (” 20% of
the stake) that were matched in material utility (e.g., $2 out of $4
matched with $2 out of $10). In this subset of offers, the ratio of

offer to stake size ranged from 5 to 50% (average 5 28%); the
stakes ranged from $1 to $30 (average 5 $12.18).

Results

Fairness Predicts Happiness, Independently of Contempt
Happiness ratings were strongly associated with fairness (i.e.,

percentage of the stake size offered). Participants reported
greater happiness for fair offers (! 40%) than unfair offers
(” 20%) of equal monetary value, t(13) 5 7.73, prep > .99,
d 5 4.29. Similarly, there was a strong correlation between level
of fairness and happiness ratings (r 5 .89, prep > .99). A com-
plementary pattern was observed for contempt ratings. Partici-
pants reported greater contempt for unfair offers than for

fair offers of equal monetary value, t(13) 5 5.51, prep > .99,
d 5 3.06, and there was a strong correlation between level of
fairness and contempt ratings (r 5 #.82, prep > .99).
Given that happiness and contempt were correlated (r 5 #.82,

prep > .99), we examined the effect of fairness on happiness
after partialing out contempt. Happiness controlling for contempt

$HC̄% was still associated with fairness (r 5 .38, prep > .95);
however, contempt controlling for happiness (CH̄), was not (r 5
#.17, prep 5 .80).

Fairness Predicts Happiness, Independently of Material Outcome
Offer amount and emotion ratings were not strongly associated.
Happiness ratings of high-value offers (> $2) did not differ from
those of low-value offers (” $2) of equal fairness, t(13) 5 1.16,
prep 5 .87, d 5 0.64. Although the correlation between offer
amount and happiness was marginally significant (r 5 .32,
prep > .95), offer amount did not predict H!C (r 5 .28, prep > .92).
Similarly, contempt ratings of high-value offers did not differ
from those of low-value offers of equal fairness, t(13) 5 0.39,
prep 5 .60, d 5 0.15. The correlations between offer amount and
contempt (r 5 #.20, prep 5 .85) and between offer amount and
CH̄(r 5 .11, prep 5 .71) were not significant.
After controlling for the effect of offer amount, fairness still

predicted happiness (b 5 .87, prep > .99) and H!C (b 5 .35,
prep > .95), and fairness still predicted contempt (b 5 #.81,
prep > .99), but not C!H (b 5 #.18, prep 5 .82). Together, these
results indicate that fairness, independently of offer amount,

predicts happiness, independently of contempt.

+

$1

0

$0 $5 $10

Blank

0 0.5 2.0 3.0 6.0

Time (seconds)

Portrait Stake Offer

$15
$0 $5 $10 $15 $20 $25 $30

$10

$2

Fig. 2. Diagram illustrating the structure of each 6-s trial: The participant saw a fixation cross for 0.5 s, a picture of the
purported proposer for 1.5 s, a display indicating the size of the stake for 1 s, and finally the offer for 3 s. The participant was
given the final 3 s of each trial to respond, by pressing one button to ‘‘accept’’ and another to ‘‘reject’’ the offer. Then the
next blank screen appeared for 0.5 s, and so forth.

Volume 19—Number 4 341

Golnaz Tabibnia, Ajay B. Satpute, and Matthew D. Lieberman

EXPERIMENT 2

Method

Participants and Task
Twelve undergraduates (average age 5 21.8 years; 9 females, 3
males) participated. The task was similar to that in Experiment
1, except that the stakes ranged from $1 to $23 (average 5
$9.60), and participants underwent fMRI scanning while they
considered the offers. After the scanning session, participants

indicated what they considered a fair offer for each stake size.

fMRI Acquisition and Analysis
Data were acquired on a GE 3-T full-body scanner. Scanning

parameters were identical to those used in our previous studies
(see Lieberman, Jarcho, & Satpute, 2004). Each of four func-

tional scans consisted of thirty-one 6-s trials, as well as five 6-s
jitter trials. The MR data were analyzed using SPM99 (Wellcome
Department of Cognitive Neurology, London). Images for each

participant were realigned, slice-timed, normalized to Montreal
Neurological Institute (MNI) space, and smoothed with an 8-mm

Gaussian kernel, full width at half maximum.
We included in the fairness analysis only matched pairs of

trials in which the same amount was accepted in one case and
rejected in the other. Thus, we analyzed neural activation in re-
sponse to offers that possessed matched financial rewards and

therefore differed primarily in their perceived fairness.
Events were modeled with a canonical hemodynamic re-

sponse function time-locked with the onset of the offer.1 Linear
contrasts were employed to assess comparisons of interest within

individual participants. Random-effects analyses of the group
were computed using the contrast images generated for each
participant. For regions of interest, significance was set using an

uncorrected p value of .005 (5-voxel threshold). Post hoc anal-
yses were carried out at a p value of .001 (20-voxel threshold).
Peristimulus hemodynamic time courses were computed by
identifying clusters of activations from the random-effects
analyses and then applying to these clusters a selective aver-

aging procedure on a participant-by-participant basis (Pold-
rack, 2004). Regression analysis of the tendency to accept unfair

offers was conducted by performing a group analysis in which
each participant’s rate of accepting unfair offers was entered as a

regressor to identify which activations correlated with the rate.

Results

Behavioral Results
On average, participants accepted 56.3% (SD 5 12.3%) of all
the offers in the experiment, a result indicating that they were
not solely motivated by monetary reward, in which case they

would have accepted all offers. This acceptance rate decreased

significantly (prep > .95) as the proportion of the offer relative to
the stake size decreased (see Table 1). Across all trials in the

study, multiple participants rejected offers as financially de-
sirable as $8 out of $23; on average, participants rejected at least

one offer as high as $4.88.

Self-Report Results
Average self-reported estimates of what constituted a fair offer
ranged from 45.2% to 48.3% across stakes. For each partici-

pant, we calculated the percentage of unfair offers (as identified
by the participant’s own responses after the scanning session)

that were accepted. On average, participants accepted 49.0% of
the offers that were below their self-reported fairness thresholds.
These results suggest that although participants were influenced

by fairness, they were sometimes able to overcome or disregard
fairness considerations and make the economically normative

decision when fairness and material considerations were at
odds.

fMRI Results:

Fairness Preference

Several brain regions associated with reward processes were

more active during high-fairness offers than during low-fairness
offers, after controlling for material utility. Brain regions that

showed greater activity for high- than for low-fairness offers
were the ventral striatum, the amygdala, VMPFC, OFC, and a

midbrain region near the substantia nigra (see Table 2 and Fig.
3). A post hoc whole-brain analysis also revealed sensitivity to
increased fairness in lateral temporal cortex (x 5 #44, y 5 18,
z 5 #24), t(11) 5 4.74, prep > .99, d 5 2.86.
In the high- versus low-fairness contrast, participants pro-

ducing greater activity in the ventral striatum, compared with
other participants, tended to produce greater activity in the

amygdala (r 5 .81, prep > .95) and VMPFC (r 5 .65, prep > .95)
as well. This finding is consistent with the hypothesis that the
ventral striatum, the amygdala, and VMPFC function together as

a motivational circuit related to reward (Trepel et al., 2005).
We examined whether the reward activations could be at-

tributed to a continuation of effects occurring during the first
half of each trial, when the face and stake size were presented,
prior to when the offer was presented and a choice was made. We

TABLE 1

Likelihood of an Offer Being Accepted as a Function of the Ratio
of the Offer to the Stake Size

Ratio of offer to stake Acceptance rate

50% 97.9%
40–49% 92.3%
30–39% 75.8%
20–29% 44.7%
10–19% 30.8%
< 10% 1.4%

1These imaging techniques allowed us to determine the blood-oxygenation-
level-dependent signal, an index of neuronal activity, associated with specific
types of offers.

342 Volume 19—Number 4

Fairness Is Rewarding

performed a new fairness analysis targeting the 3-s period prior

to offer onset. No motivational areas active in the fairness analy-
sis were active in this new analysis.

fMRI Results: Accepting Unfair Offers
Our findings for the anterior insula are consistent with those of

Sanfey et al. (2003). Specifically, we observed increased anterior
insula activity (relative to a resting baseline) during idiograph-

ically defined unfair trials that were rejected (x 5 36, y 5 18,
z 5 #8), t(11) 5 4.39, prep > .99, d 5 2.95. We also examined
the neural structures activated when responders overcame fair-

ness concerns and accepted offers they considered unfair. The
hypothesis that accepted unfair offers activate reward circuitry to a

greater extent than rejected unfair offers was not supported by the
data. There was no activity in the ventral striatum, the amygdala, or

VMPFC (at a liberal statistical threshold of p < .01 uncorrected) when accepted unfair offers were compared with resting baseline. However, a large cluster (k 5 834) in right VLPFC was active in this comparison (x 5 50, y 5 44, z 5 8), t(11) 5 5.39, prep > .99,

TABLE 2

A Priori Regions Showing Greater Activation in High-Fairness
Than in Low-Fairness Trials

Region Hemisphere

Coordinates
No. of
voxels tx y z

Ventral striatum Left #6 4 0 7 4.03
VMPFC Left #14 32 #10 10 4.85

Left #16 16 #16 6 3.83
Right 10 60 #4 5 3.82

Orbitofrontal cortex Right 36 36 #20 24 4.32
Amygdala Left #12 #4 #24 10 3.81

Right 20 #12 #12 32 4.32
Midbrain, SN Left #14 #20 #6 9 4.75

Note. No activation was greater in low-fairness than in high-fairness trials.
The coordinates are from the Montreal Neurological Institute (MNI) atlas.
Significance was based on an uncorrected p value of .005, with a 5-voxel
threshold. VMPFC 5 ventromedial prefrontal cortex; SN 5 substantia nigra.

0.3

0.2

0.1

S
ig

n
a
l C

h
a
n
g
e
s

Peristimulus Time

Peristimulus Time Peristimulus Time

Amygdala VMPFC

Ventral Striatum

High Fairness

Low Fairness

High Fairness
Low Fairness
High Fairness
Low Fairness

0.0

6s 12s

6s 12s 6s 12s

!0.1

!0.2

0.2
0.1
0.0
!0.1
!0.2
0.3
0.2
0.1
S
ig
n
a
l C
h
a
n
g
e
s
S
ig
n
a
l C
h
a
n
g
e
s
0
!0.1
!0.2

!0.3

b

c d

a Ventral
Striatum

AmygdalaVMPFC

Fairness Preference

Fig. 3. Ventromedial prefrontal cortex (VMPFC), ventral striatum, and amygdala activation associated with fairness preference. The
illustration (a) shows the location of clusters with significantly greater activation in response to fair compared with unfair offers. The
graphs present the time course of activity for fair and unfair trials, relative to a resting baseline, in (b) the ventral striatum, (c) the
amygdala, and (d) VMPFC. Error bars indicate & 1 SE. Along the abscissa, 0 s indicates the onset of the offer (which was 3 s after the trial
began).

Volume 19—Number 4 343

Golnaz Tabibnia, Ajay B. Satpute, and Matthew D. Lieberman

d 5 3.25, a finding consistent with the hypothesis that accepting
unfair offers may involve emotion regulation.
To further explore the involvement of right VLPFC and the

anterior insula in decisions regarding unfair offers, we specifi-
cally compared trials in which unfair offers were accepted with
trials in which unfair offers were rejected. As expected, the left

anterior insula was less active when unfair offers were accepted
than when they were rejected (x 5 #28, y 5 8, z 5 #6), t(11) 5
4.06, prep > .99, d 5 2.45. Activity in this insula region was
inversely correlated with right VLPFC activity (x 5 58, y 5 34,
z 5 10) during trials in which unfair offers were accepted
(r 5 #.77, prep > .99), a finding consistent with the hypothesis
that right VLPFC reduces insula activity in such cases.

We also examined the rate at which participants accepted
offers they rated unfair in the postscanning questionnaire, re-

gressing this index onto brain activations in the contrast of

accepted versus rejected offers. As Figure 4 shows, participants

who accepted a higher proportion of idiographically defined
unfair offers showed a greater increase in activity in right

VLPFC (x 5 50, y 5 24, z 5 8), t(11) 5 3.68, prep > .99, d 5
2.22, and a greater decrease in activity in the anterior insula on
the left (x 5 #34, y 5 20, z 5 #6), t(11) 5 #7.59, prep > .99,
d 5 4.58, and right (x 5 32, y 5 22, z 5 #10), t(11) 5 #6.01,
prep > .99, d 5 3.62, during trials in which offers were accepted
relative to trials in which offers were rejected. Furthermore,
activity in right VLPFC was again inversely correlated with
activity in the left (r 5 #.68, prep > .99) and right (r 5 #.86,
prep > .99) anterior insula. No activity in the ventral striatum, the
amygdala, or VMPFC was positively correlated with the ten-

dency to accept unfair offers. These findings suggest a prefrontal
down-regulation of negative emotional responses during the

process of accepting unfair offers.

Anterior Insula

a b

dc

VLPFC

1.00

r = !.92

r = .76

0.80

0.60

0.40

0.20

0.00

1.00
0.80
0.60
0.40
0.20
0.00

!1.00 !0.50 0.00 0.50
Activity in Left Anterior Insula [-34 20 -6]

A
cc

e
p

t
U

n
fa

ir
R

a
te

A
cc

e
p
t

U
n
fa

ir
R
a
te
1.00

!1.00 !0.50 0.00 0.50
Activity in Right VLPFC [50 24 8]

1.00

Fig. 4. Brain activation associated with the tendency to accept unfair offers. The illustrations show the location of areas in (a)
left anterior insula and (c) right ventrolateral prefrontal cortex (right VLPFC) whose activation predicted this tendency. The
corresponding scatter plots (b and d) depict the correlation between signal change in these areas during accepted relative to
rejected offers and the rate at which participants accepted offers they later identified as unfair.

344 Volume 19—Number 4

Fairness Is Rewarding

If right VLPFC is involved in the acceptance of unfair offers

by reducing negative affect associated with the anterior insula,
then the relationship between right VLPFC activity and the rate

of accepting unfair offers should be mediated by activity in the
anterior insula. Indeed, the direct path between right VLPFC

activity and the rate of accepting unfair offers (b 5 .76, prep >
.99) was significantly mediated by activity in the left anterior
insula (Sobel test: Z 5 2.51, prep > .99). After we controlled for
activity in this insula region, the remaining path between
VLPFC activity and the rate of accepting unfair offers was no

longer significant (b 5 .25, prep 5 .94).

DISCUSSION

Experiment 1 demonstrated that fairness, but not monetary value,
predicted self-reported happiness independently of contempt

ratings. In Experiment 2, nearly all commonly identified reward
areas, including the ventral striatum, the amygdala, VMPFC, and
OFC, were associated with fairness preference. Together, these

results suggest that individuals react to fairness with a positive
hedonic response, rather than that fairness produces a neutral

state and only unfairness produces an affective response. These
results are consistent with previous reports that reward regions

such as the striatum, VMPFC, and the amygdala are responsive to
cooperative partners and behavior (King-Casas et al., 2005;
Rilling et al., 2002; Singer, Kiebel, Winston, Dolan, & Frith,

2004). Further, these results suggest that fairness processing is
relatively automatic and intuitive, as the ventral striatum, the

amygdala, and VMPFC have all been associated with automatic
and intuitive processes (Lieberman, 2007).

In previous studies of the ultimatum game, fairness and ma-
terial utility have covaried. Typical offers in these studies have
been either completely fair and of highest material utility (e.g.,

$5 out of $10), and therefore easily accepted, or very unfair and
of lowest material utility (e.g., $1 out of $10), and therefore

usually rejected. However, in real life there are situations in
which the choice is less straightforward. In the current study, we
manipulated conflict-ridden choices by presenting offers that

were of considerable material utility but relatively unfair (e.g.,
$8 out of $23).

To the extent that a participant produced increased activity in
right VLPFC and decreased activity in the anterior insula, the

participant was more likely to accept unfair but financially de-
sirable offers. One interpretation of this result is that partici-
pants who accepted unfair offers were better able than others to

down-regulate the negative emotional response to unfair treat-
ment. Alternatively, increased activity in anterior insula could

reflect the ‘‘pain of paying’’ associated with rejecting an offer
(Knutson, Rick, Wimmer, Prelec, & Loewenstein, 2007), rather
than the social pain of unfair treatment. Thus, participants who

were more likely to accept unfair offers may have had lower
insula activity because they experienced little pain of paying.

However, the overall pattern of results involving right VLPFC is

more consistent with the former interpretation. Activity in the

insula mediated the relationship between right VLPFC activity
and tendency to accept unfair offers, and this finding supports

the hypothesis that right VLPFC promotes more normative de-
cision making by down-regulating activity in the anterior insula

when unfair offers are considered. Thus, the ability to swallow
one’s pride, overcome the insult, and take an unfair offer may
involve active down-regulation of emotional responses to unfair

treatment.
Consistent with the idea that right VLPFC activity drove par-

ticipants’ decisions to accept unfair offers, studies using repet-
itive transcranial magnetic stimulation (rTMS) have identified

the right lateral prefrontal cortex as playing a causal role in ra-
tional decision making in the ultimatum game (Knoch, Pascual-
Leone, Meyer, Treyer, & Fehr, 2006; van’t Wout, Kahn, Sanfey, &

Aleman, 2005). Interestingly, in the current study, accepted
unfair offers were not associated with increased activity in re-

ward-related regions, which supports the interpretation that
logical rather than hedonic processes guided these particular
decisions. In the two rTMS studies, transient disruption of

function in right dorsolateral prefrontal cortex (right DLPFC)
interfered with rejection of unfair offers. Although the dorsolat-

eral region identified in these studies is structurally and func-
tionally distinct from the VLPFC region identified in the current

study, these findings together are consistent with the notion (van’t
Wout et al., 2005) that the default response in the ultimatum
game is to reject an unfair offer; DLPFC may be needed

to maintain this default goal, whereas VLPFC may be needed to
override it. An alternative interpretation is that DLPFC may

be needed to override material self-interest (Knoch et al., 2006),
as the role of VLPFC may be to override fairness concerns.
In previous studies, right VLPFC has consistently been as-

sociated with the down-regulation of activity in regions sup-
porting negative affect (Lieberman, in press). Specifically, it has

been associated with the down-regulation of the amygdala’s
response to pictures of disturbing scenes (Hariri, Mattay, Tessi-

tore, Fera, & Weinberger, 2003) and pictures of evocative faces
(Hariri et al., 2000; Lieberman et al., 2007; Lieberman, Hariri,
Jarcho, Eisenberger, & Bookheimer, 2005), as well as the down-

regulation of the anterior cingulate’s response to physical (Lie-
berman, Jarcho, Berman, et al., 2004; Wager et al., 2004) and

social (Eisenberger, Lieberman, & Williams, 2003) pain. Right
VLPFC has also been linked to reduced susceptibility to

amygdala-mediated framing effects and thus to rational decision
making (De Martino, Kumaran, Seymour, & Dolan, 2006). Thus,
it is plausible that in the current study, right VLPFC down-

regulated affect-related activity in the anterior insula to enable
the rational decision of accepting an unfair offer.

The fact that we did not find any region exhibiting greater
activity for low-fairness offers than for high-fairness offers
seems at odds with the results of Sanfey et al. (2003), who re-

ported greater activity in anterior insula and prefrontal areas
during unfair than during fair offers. It is possible that the differ-

Volume 19—Number 4 345

Golnaz Tabibnia, Ajay B. Satpute, and Matthew D. Lieberman

ences in results are due to differences in the experimental de-

signs, such as the use of rapid versus slow event-related designs
or the types of fair and unfair trials used. Nonetheless, in both

investigations, increased insula activity correlated with the ten-
dency to reject unfair offers, so the studies converge on similar

functional interpretations of insula activity.
One may wonder whether the reward activations observed in

the fairness-preference analysis were in response to fairness per

se or were actually due to the perceived higher probability of
receiving the monetary offer in fair trials (which were accepted)

than in unfair trials (which were rejected). Although our data
cannot fully rule out the latter interpretation, it is unlikely. If

greater expectation of monetary payoff was driving reward ac-
tivity during high-fairness trials in Experiment 2, we should
have found reward activity during acceptance of unfair offers,

which had the same perceived probability of payoff as the ac-
cepted fair offers. However, activation during accepted unfair

offers was not greater than baseline activation in any reward-
related regions, which suggests that the increased activity in
these regions during high-fairness trials was not driven by the

perceived probability of monetary payoff.
Finally, the relatively early onset of activity in the amygdala

(see Fig. 3c) suggests that this response may have been both
related to the offer and a continuation of response from the first

half of the trial. However, we did not find significant amygdala
activation in a whole-brain analysis of the first half of the trial,
even at a lenient threshold (prep > .99, uncorrected). The dis-
crepancy between this null result and the apparent time course
of amygdala activation in Figure 3c reflects the fact that whole-

brain analyses examine the correlation between the blood-oxy-
genation-level-dependent response and the canonical hemo-
dynamic response, and do not show effects at any one time point.

Despite the absence of significant amygdala activation in this
analysis, however, it is difficult to infer that the amygdala ac-

tivity reported here reflects reward processing per se, as such
activity has also been observed in numerous studies of nega-

tively valenced information processing. However, when amyg-
dala activity co-occurs with activity in VMPFC and ventral
striatum, it is commonly in the context of reward processing

(Cardinal et al., 2002; Petrovich, Holland, & Gallagher, 2005;
Trepel et al., 2005). Our confidence in the inference that the

amygdala response is related to reward processing is increased
because of (a) the convergence of evidence from self-report and

(b) the fact that this response was observed in the context of
the activation of multiple regions that work together in a net-
work underlying reward processing (Poldrack, 2006). Future

studies are needed to elucidate the role of the amygdala in social
reward.

In conclusion, these findings suggest that people may prefer
fair outcomes at the cost of material utility in part because they
hedonically value fairness itself; this preference may not be

motivated solely by negative emotional responses to unfairness
or by the impersonal application of culture-driven rules.

Moreover, when material utility outweighs social utility, people

may down-regulate their affect-related neural response to unfair
treatment in order to choose the economically desirable option.

These results support the notion that the automatic or default
reaction in economic decision making is to prefer the fair and

refuse the unfair (van’t Wout et al., 2005), not just because fair
options also tend to be materially advantageous or because
unfairness is jarring, but also because fair treatment can be

rewarding in itself.

Acknowledgments—We thank the UCLA Brain Mapping

Medical Organization, the Ahmanson Foundation, the Pierson-

Lovelace Foundation, and the Tamkin Foundation for support

and John Monterosso and Daniel Gilbert for helpful comments

on earlier drafts.

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Volume 19—Number 4 347

Golnaz Tabibnia, Ajay B. Satpute, and Matthew D. Lieberman

Human fronto–mesolimbic networks guide decisions
about charitable donation
Jorge Moll*†, Frank Krueger*, Roland Zahn*, Matteo Pardini*‡, Ricardo de Oliveira-Souza†§, and Jordan Grafman*¶

*Cognitive Neuroscience Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892-1440;
†Cognitive and Behavioral Neuroscience Unit, LABS–D’Or Hospital Network, 2228 – 080, Rio de Janeiro, Brazil; ‡University of Genoa Medical School,
16132 Genoa, Italy; and §Gaffrée and Guinle University Hospital and Philippe Pinel Institute, 20270 – 004 Rio de Janeiro, Brazil

E

dited by Marcus E. Raichle, Washington University School of Medicine, St. Louis, MO, and approved September 7, 2006 (received for review May 31, 2006)

Humans often sacrifice material benefits to endorse or to oppose
societal causes based on moral beliefs. Charitable donation behav-
ior, which has been the target of recent experimental economics
studies, is an outstanding contemporary manifestation of this
ability. Yet the neural bases of this unique aspect of human
altruism, which extends beyond interpersonal interactions, remain
obscure. In this article, we use functional magnetic resonance
imaging while participants anonymously donated to or opposed
real charitable organizations related to major societal causes. We
show that the mesolimbic reward system is engaged by donations
in the same way as when monetary rewards are obtained. Fur-
thermore, medial orbitofrontal–subgenual and lateral orbitofron-
tal areas, which also play key roles in more primitive mechanisms
of social attachment and aversion, specifically mediate decisions to
donate or to oppose societal causes. Remarkably, more anterior
sectors of the prefrontal cortex are distinctively recruited when
altruistic choices prevail over selfish material interests.

altruism ! brain ! moral ! reward ! social

Human altruism far exceeds the immediate bonds of kinship,even when no material or reputation gains are anticipated
(1, 2). Recent studies in experimental economics have started to
explore the neurobiological basis of cooperation in interpersonal
exchanges (3–5). Altruistic choices regularly take place beyond
interpersonal and economic realms, however. People often
sacrifice material interests, time, and even physical integrity on
behalf of societal causes, principles, and ideologies (6 – 8). Anon-
ymous donation to charitable organizations is an outstanding
example of this unique aspect of human altruism (8, 9), which
relies on our ability to directly link motivational significance to
abstract moral beliefs and societal causes. Evolutionary and
neurobiological theories suggest that this ability was critically
shaped during the last major step of human evolution in the
cultural explosion of the Upper Paleolithic period (10, 11).

We investigated the neural mechanisms of charitable dona-
tions using functional magnetic resonance imaging (fMRI; see
Materials and Methods). Nineteen participants chose to endorse
or oppose societal causes by anonymous decisions to donate or
refrain from donating to real charitable organizations (ORGs).
The ORGs’ missions were linked to a wide range of societal
causes, including abortion, children rights, death penalty, eutha-
nasia, gender equality, nuclear power, and war (see Materials and
Methods). Importantly, the experimental design allowed us to
probe the interplay of material interests and altruistic prefer-
ences. Participants were entitled to receive a substantial endow-
ment of U.S.$128, which would be obtained in full if they solely
cared about their self monetary interests when making decisions.
This amount would decrease, depending on how often they made
altruistic choices (see Materials and Methods for an operational
definition of altruistic decisions).

The experimental conditions of interest, defined on the basis
of participants’ ‘‘Yes’’ or ‘‘No’’ decisions to different payoff
types, were: (i) pure monetary reward, (ii) noncostly donation,
(iii) noncostly opposition, (iv) costly donation, and (v) costly

opposition (Fig. 1; see Materials and Methods and Figs. 5– 8,
which are published as supporting information on the PNAS web
site, for details on stimuli and task procedure). Thus, although
some decisions involved pure monetary rewards, and donation or
opposition at no personal costs, other decisions entailed a
conf lict between participants’ personal monetary interests and
their motivations to donate to or to oppose causes. Importantly,
ORGs were paired with randomized payoff types, and all ORGs
were presented to each participant. At the end of the experiment,
all ORGs and their causes were scored according to familiarity
and associated moral emotion (compassion and anger; see
Supporting Methods, which is published as supporting informa-
tion on the PNAS web site). In addition, self-reported ratings of
engagement in real-life voluntary charitable activities were
obtained.

As long as humans can derive utility directly from the act of
alleviating the suffering of another (8, 12), we predicted activa-
tion of the mesolimbic reward system both for decisions leading
to pure monetary rewards and decisions to donate. We also
expected that medial and lateral sectors of the orbitofrontal
cortex, respectively, would mediate decisions to donate or to
oppose causes, in line with the involvement of these regions in
reward and punishment (13). Finally, we predicted that anterior
prefrontal regions that have been implicated in moral judgments
and prospective assessment of outcomes (11, 14 –16) would be
engaged by altruistic decisions that involved sacrificing material
interests for societal causes.

Results
Behavioral analyses showed that all participants consistently
made costly decisions, sacrificing an average of 40% (U.S.$51;
range ! U.S.$21– 80) of their endowment. Participants took
longer to make costly than noncostly decisions (Fig. 2a). Con-
sistent with the role of moral emotions in judgment (11) and in
helping behaviors (17), ratings of experienced compassion were
higher for causes participants chose to donate to, whereas anger
scores were higher for opposed causes (Fig. 2b). For details of
response times and emotion scores across the main experimental
conditions, see Table 1, which is published as supporting infor-
mation on the PNAS web site.

Author contributions: J.M. and J.G. designed research; J.M. and M.P. performed research;
J.M., F.K., and R.Z. analyzed data; and J.M., F.K., R.Z., R.d.O.-S., and J.G. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS direct submission.

Abbreviations: ORGs, charitable organizations; VTA, ventral tegmental area; BA, Brod-
mann’s area; lOFC, lateral orbitofrontal cortex; fMRI, functional magnetic resonance
imaging.

Data deposition: The neuroimaging data have been deposited with the fMRI Data Center,
www.fmridc.org (accession no. 2–2006 –122A7).
¶To whom correspondence should be addressed at: Cognitive Neuroscience Section, Na-
tional Institute of Neurological Disorders and Stroke, National Institutes of Health, Build-
ing 10, Room 5C205, MSC 1440, Bethesda, MD 20892-1440. E-mail: grafmanj@
ninds.nih.gov.

© 2006 by The National Academy of Sciences of the USA

www.pnas.org”cgi”doi”10.1073″pnas.0604475103 PNAS ! October 17, 2006 ! vol. 103 ! no. 42 ! 15623–15628

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The midbrain ventral tegmental area (VTA), the dorsal
striatum, and the ventral striatum were activated by both pure
monetary rewards and decisions to donate (Fig. 3a; see Table 2,
which is published as supporting information on the PNAS web

site), suggesting that donating to societal causes and earning
money share anatomical systems of reward reinforcement and
expectancy (18, 19). This finding is compatible with the putative
role of the ‘‘warm glow’’ (‘‘joy of giving’’) effect, the rewarding
experience associated with anonymous donations (8). But are
the neural correlates of monetary rewards and donations iden-
tical? To address this issue, we directly compared donation
conditions (costly and noncostly) to pure monetary reward. This
contrast revealed that activity in the subgenual area [including
Brodmann’s area (BA) 25] was highly specific for donations (Fig.
3 b and c; see Table 3, which is published as supporting
information on the PNAS web site). Interestingly, the ventral
striatum (together with the adjoining septal region) was also
more active for donations than for pure monetary rewards.
Furthermore, ventral striatum activity was correlated with the
number of decisions to donate that each participant made during
the experiment (Fig. 3d; see Supporting Methods). These findings
indicate that donating to societal causes recruited two types of
reward systems: the VTA–striatum mesolimbic network, which
also was involved in pure monetary rewards, and the subgenual
area, which was specific for donations and plays key roles in
social attachment and affiliative reward mechanisms in humans
(20, 21) and other animals (22).

Although morality often promotes cooperation and helping, it
also can steer hostility among individuals and social groups.
Moral beliefs powerfully incite people to challenge others’ values
and ideologies (6, 7). Previous research consistently implicates
the lateral orbitofrontal cortex (lOFC) in aversive mechanisms
(13), including anger and moral disgust (11, 23). To test the role
of the lOFC in more abstract forms of culturally mediated social
disapproval, brain responses to participants’ decisions to oppose
causes were compared with pure monetary rewards. The lOFC
(BA 11″47), including its transition to the anterior insula and

Fig. 1. Donation task and behavioral results. (a) Task design. The name and mission statement of an ORG was presented, followed by the payoff type (decision
phase), and then by the outcome phase. Depending on the trial, Yes or No decisions to different payoff types had different monetary consequences to the
participant and”or to the ORG (‘‘outcome types’’; see Materials and Methods and Figs. 5– 8). In this example, a (YOU: $0 ORG: $”5) payoff is shown. (b) The
conditions of interest derived from the main outcome types and comprised costly opposition [red; No to (YOU: $”2 ORG: $”5)], noncostly opposition [orange;
No to (YOU: $0 ORG: $”5)], costly donation [dark blue; Yes to (YOU: $#2 ORG: $”5)], noncostly donation [light blue; Yes to (YOU: $0 ORG: $”5)], and pure
monetary reward [green; Yes to (YOU: $”2 ORG: $0)]. Altruistic or costly decisions included costly donation and costly opposition.

Fig. 2. Behavioral results. (a) Response times for main conditions of interest.
Increased response times were associated with altruistic decisions (which
included costly donation and costly opposition) as compared with noncostly
decisions [t(18) ! 3.26, P $ 0.005]. Color code: costly opposition, red; noncostly
opposition, orange; costly donation, dark blue; noncostly donation, light blue;
and pure monetary reward, green. (b) Compassion and anger scores. Societal
causes participants donated to received higher compassion scores [t(16) !
7.84, P $ 0.001], whereas opposed causes scored higher in anger [t(16) ! 5.53,
P $ 0.001]. Color code as the same as in a. Error bars indicate SEM.

15624 ! www.pnas.org”cgi”doi”10.1073″pnas.0604475103 Moll et al.

adjacent dorsolateral cortex, was activated by both costly and
noncostly opposition (Fig. 4 a and c; see Table 4, which is
published as supporting information on the PNAS web site).
Moreover, activity in the lOFC was modulated by how often
participants decided to oppose societal causes (see Supporting
Methods).

Decision making in real social environments requires balanc-
ing immediate motives against the long-term consequences of
one’s choices (11, 24). Previous work implicated anterior regions
of the medial prefrontal cortex in goal representation (13–15,
25), altruistic punishment (5), prediction of future rewards (14,
18, 26), and implicit or explicit moral appraisals (11, 16, 27, 28).
Our results indeed showed that costly decisions (choosing to
costly donate or to costly oppose), which are altruistic in essence,
were associated with activation of the anterior prefrontal cortex,
including the frontopolar cortex and the medial frontal gyrus
(BA 10″11″32; Fig. 4 b and d; see Table 5, which is published as
supporting information on the PNAS web site). Response time
differences between costly and noncostly decisions did not
correlate with anterior prefrontal activity, ruling out the possi-
bility that these effects merely ref lected decision difficulty. In
contrast, the dorsal anterior cingulate cortex response, also
observed for costly decisions, was correlated with response
times, in agreement with its role in conf lict and error monitoring
(16, 29) (Fig. 4b). Finally, we probed the relationships between
individual differences of self-reported engagement in real-life
voluntary activities and brain activation patterns. Anterior pre-
frontal cortex activity to costly donation was highly correlated
with engagement scores (Fig. 4e). This finding indicates that this
region plays a key role in real-life altruistic behaviors, as
suggested by a recent model of moral cognition (11).

Discussion
Our findings extend our knowledge of the neural bases of social
cooperation from interpersonal economic interactions (3–5, 27,

30) to the realm of societal causes that are linked to culturally
shaped moral beliefs. More specifically, they indicate that dis-
tinct neural systems underlie decisions to donate or to oppose
societal causes: the mesolimbic reward system (VTA–striatum)
provides a general reinforcement mechanism, the subgenual
area and the lOFC mediate social attachment and aversion
responses, and the anterior prefrontal cortex is crucial for
representing more complex reinforcement contingencies related
to altruistic decisions.

The importance of these fronto–limbic networks for human
altruism concurs with their key roles in more basic social and
motivational mechanisms. The mesolimbic system regulates
overall reward reinforcement and prediction and is activated by
a host of stimuli, including food, sex, drugs, and money (11, 14,
18). The subgenual area, which specifically was recruited by
donations, comprises a primitive paralimbic, four-layered ar-
chicortex densely interconnected with the mesolimbic dopami-
nergic and dorsal raphe serotonergic pathways (31). This region
plays a key role in controlling septo-hypothalamic function in
social attachment and the release of the neuromodulators oxy-
tocin and vasopressin (22, 32). Interestingly, recent studies
showed that administration of oxytocin to humans increased
trust and cooperation in economic interactions (32, 33). Further,
the subgenual cortex and adjacent septal structures were acti-
vated when humans looked at their own babies and romantic
partners (20, 21). The partially dissociable responses observed in
the mesolimbic system and subgenual area indicate the existence
of interlocking systems for self-serving monetary rewards and
attachment to societal causes. Activity in the lOFC, in turn, was
linked to opposing causes, a finding that converges with the role
of this region in social aversion (3, 11, 23). This pattern is in
general agreement with the medial to lateral functional special-
ization of the orbitofrontal cortex in reward and punishment

Fig. 3. Brain responses for monetary reward and donation. (a) Mesolimbic–striatal reward system, including the VTA and the dorsal and ventral sectors of the
striatum (STR), activation for both pure monetary reward and noncostly donation (conjunction of pure reward vs. baseline and noncostly donation vs. baseline).
(b) Subgenual area (SG) activation for decisions to donate (conjunction of costly and noncostly conditions) as compared with pure monetary reward. The
subgenual area comprised the most posterior sector of the medial orbitofrontal cortex and the ventral cingulate cortex (BA 25) and the adjoining septal region
structures. (c) Hemodynamic responses from the subgenual cortex for donation and pure monetary reward conditions. (d) Positive association between decision
frequency of costly donation (how often each participant made costly donations) and ventral striatum”septal region parameter estimates (VS”SR; x ! #6, y !
11, z ! 4; r ! 0.58; P $ 0.01). BOLD, blood oxygenation level-dependent.

Moll et al. PNAS ! October 17, 2006 ! vol. 103 ! no. 42 ! 15625

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representations (13, 34). We speculate that our capacity to feel
attachment or aversion to societal causes might have emerged
through similar gene-culture coevolution mechanisms as those
proposed by the strong reciprocity theory (35). This premise
would allow primitive reward, social attachment, and aversion
neural systems to operate beyond the immediate spheres of
kinship, thus enabling humans to directly link motivational value
to abstract collective causes, principles, and ideologies (11). The
observation that anterior prefrontal sectors were recruited by
costly decisions indicates that when immediate self-interest and
moral beliefs are at odds, altruistic decisions entail more com-
plex event– outcome associations (11, 13, 34). This finding is
supported by the role of this region in altruistic punishment,
moral judgment, assessment of abstract future rewards, and
long-term goals (5, 11, 13, 25, 36).

Taken together, these lines of evidence indicate that human
altruism draws on general mammalian neural systems of reward,
social attachment, and aversion. In the context of intertwined
social and motivational contingencies, however, altruism tied to
abstract moral beliefs relies on the uniquely developed human
anterior prefrontal cortex.

Materials and Methods
Subjects. Nineteen healthy participants (10 men, 28.2 % 6.2 years of
age, education 17.4 % 2.3 years; mean % SD) took part in the fMRI
study. Before the fMRI experiment, a behavioral study involving 58
healthy volunteers (29 men, 33.3 % 8.0 years of age, educa-
tion 16.7 % 2.2 years; mean % SD) was carried out to design and
assess the stimuli and task procedures and to guide the selection of
ORGs and societal causes for the fMRI experiment (see Supporting
Methods). All participants were right-handed and native English
speakers. Informed consent was obtained according to procedures

approved by the National Institute of Neurological Disorders and
Stroke (NINDS) Internal Review Board. All participants were paid
according to the NINDS standards.

General Task Design. A personal endowment of U.S.$128 was made
available for each participant in the fMRI experiment, which
corresponded to the maximum amount they could obtain for
themselves during the experimental task. Participants were told that
additional experimental funds were available for ORG reimburse-
ments, and they understood that their decisions on each trial would
ultimately affect their personal endowment and the monetary
benefits allocated to ORGs, depending on the payoff type. They
were encouraged to make free choices and were guaranteed
anonymity. Before scanning, participants browsed the full list of
ORGs and mission statements and then were given a supervised
10-min practice session with the actual task (additional ORGs were
used for this purpose). During each trial of the task, the name of an
ORG and a short mission statement were displayed for 6 s. This step
was followed by the combined payoff [i.e., the personal (YOU) and
organizational (ORG)], which could be of four types: (YOU: $”2
ORG: $0), (YOU: $0 ORG: $”5), (YOU: $#2 ORG: $”5), and
(YOU: $”2 ORG: $”5) (see Figs. 1 and 5–8). Next, a decision to
accept (Yes) or reject (No) the combined payoff had to be made
within 3.5 s by a button click with the index or the middle finger of
the right hand. The outcome (e.g., ‘‘YOU will get: $0’’ ‘‘ORG will
get: $”5’’) was then presented for 2.5 s, followed by a jittered
interval time. Each one of the four payoff types appeared 32 times
during the experiment, randomly combined with 64 different
ORGs. Each ORG appeared two times throughout the experiment
(combined with different payoffs), totaling 128 trials (4 payoff
types & 64 ORGs & 2 appearances). To enforce a decision in every
trial, participants were informed that U.S.$1 would be deducted

Fig. 4. Brain responses for opposition and costly decisions. (a) lOFC (BA 11″47) responses to decisions to oppose causes as compared with decisions involving
pure monetary reward (conjunction of costly and noncostly conditions). Activity of the lOFC was modulated by decision frequency of costly opposition (peak:
x ! #27, y ! 35, z ! #5; r ! 0.76; P $ 0.001). (b) Comparison of costly decisions (sacrificing money either to donate or to oppose causes) to pure monetary rewards.
Effects were observed in the anterior prefrontal cortex (aPFC), including the frontopolar cortex and the medial frontal gyrus (BA 10″11″32), and in the dorsal
anterior cingulate cortex (dACC). The differences in response times between costly and noncostly decisions were correlated with parameter estimates from the
dACC (r ! 0.46; P $ 0.05) but not from the frontopolar cortex (r ! #0.15; P ! 0.53) and the medial frontal gyrus (r ! #0.07; P ! 0.75). (c) Hemodynamic responses
from the left lOFC for opposing causes. (d) Hemodynamic responses from the frontopolar cortex for costly decisions. (e) Relationship between self-reported
engagement in real-life voluntary activities and aPFC activity to costly donation (peak: x ! #6, y ! 25, z ! #14; r ! 0.87; P $ 0.0001). BOLD, blood oxygenation
level-dependent.

15626 ! www.pnas.org”cgi”doi”10.1073″pnas.0604475103 Moll et al.

from their endowment if they failed to respond. All decisions were
explicit, with 100% predictability of outcomes. After the fMRI
experiment, participants provided ratings of familiarity and moral
emotion (compassion and anger) for each ORG and respective
mission and of engagement in real-life charitable activities. The
total amount to be received for the task then was calculated and
communicated to participants.

Decision Outcomes and Main Conditions. The task design entailed
an interdependence between the personal (YOU) and organi-
zational (ORG) payoff outcomes, in such a way that securing
one’s personal monetary interest sometimes stood in conf lict
with one’s moral beliefs. More specifically, the interaction of
payoff and decision (Yes or No) types produced eight different
outcome types. Five of these comprised the ‘‘main conditions’’
of the present study: (i) pure monetary reward, (ii) noncostly
donation, (iii) noncostly opposition, (iv) costly donation, and (v)
costly opposition (see Figs. 1b and 5– 8).

The pure monetary reward condition, defined by a Yes choice to
(YOU: $”2 ORG: $0), corresponded to a straightforward decision
aimed at self monetary gain, as it bore no consequences to ORGs
(i.e., ORG would receive nothing regardless of participant’s choice).
Noncostly donation (Yes to YOU: $0 ORG: $”5) and noncostly
opposition (No to YOU: $0 ORG: $”5) did not affect the personal
endowment but did affect ORGs: by choosing Yes, participants
willfully allowed a $5 transfer from the experimental funds to an
ORG (i.e., a donation to the ORG at no personal cost), whereas
choosing No meant avoiding the $5 monetary transfer to the ORG.
Because these decisions did not involve a conflict with self mone-
tary interests, they could have been driven either by slight prefer-
ences or strong beliefs (for or against a given ORG). Costly
opposition and costly donation corresponded to ‘‘altruistic’’ deci-
sions, here defined in the behavioral sense (costly acts that confer
benefits for other individuals). Thus, costly donation corresponded
to a Yes choice to (YOU: $#2 ORG: $”5), leading to a $2 loss to
personal endowment and to a transfer of $5 from experimental
funds to an ORG, whereas costly opposition corresponded to a No
choice to (YOU: $”2 ORG: $”5), leading to a $2 loss to personal
endowment, thus preventing a $5 transfer from experimental funds
to an ORG. Note that costly opposition qualifies as an altruistic act,
once one opts for losing money to avoid contributing to a cause
believed to be unjust. To illustrate these cases, consider a partici-
pant who strongly supports the legalization of euthanasia being
presented with a proeuthanasia ORG and a (YOU: $#2, ORG:
$”5) payoff. A Yes choice means accepting a $2 deduction to one’s
personal endowment to enable a $5 transfer from experimental
funds to the ORG, here defined as a costly donation. In a different
scenario, a participant who strongly opposes euthanasia might
choose No when presented with a (YOU: $”2, ORG: $”5) payoff
paired with a proeuthanasia ORG, denying himself a $2 sum to
prevent a $5 transfer from experimental funds to that ORG, a case
of costly opposition.

Importantly, because participants were paid at the end of the
experiment, costly decisions did not involve out-of-pocket money,
and both a No to a positive personal sum (YOU: $”2) or a Yes to
a negative sum (YOU: $#2) led to an equivalent monetary loss to
the personal endowment at the end of the experiment. This ‘‘status

quo’’ issue was held constant throughout conditions, and the
significantly higher frequency of noncostly vs. costly choices
[t(18) ! 4.6, P $ 0.001 for opposition and t(18) ! 4.3, P $ 0.001
for donation] confirmed that participants were very sensitive to
monetary rewards and cared about their endowment.

Finally, two additional outcomes types, Yes to (YOU: $”2
ORG: $”5) and No to (YOU: $#2 ORG: $”5), also were
modeled but not included as main conditions (see Figs. 7 and 8)
because they did not afford a clear interpretation of the partic-
ipant’s underlying motives. In these cases, participant’s decisions
could have been motivated by self monetary interest and moral
beliefs or by monetary interest alone despite one’s moral beliefs
(i.e., one might simply not care enough about a given societal
cause to accept the monetary sacrifice).

Image Acquisition and Analysis. A 3-tesla GE MRI scanner (Gen-
eral Electric, Milwaukee, WI) equipped with an eight-channel
array receiver head coil was used to acquire high signal-to-noise
single-shot T2*-weighted echoplanar images with blood oxygen-
ation level-dependent contrast (voxel size ! 3.75 & 3.75 & 3
mm). Combining high-field MRI, array coil, and thinner slices
allowed improved fMRI imaging of orbitofrontal cortex, brain-
stem, and limbic structures (see Fig. 9, which is published as
supporting information on the PNAS web site). High-resolution
T1-weighted structural images were acquired for each partici-
pant. Preprocessing steps included correction for slice-timing
and head movement, spatial smoothing (FWHM ! 8 mm) with
Brain Voyager QX version 1.4 (Brain Innovation, Maastrich,
The Netherlands). The general linear model (GLM) included
regressors created on the basis of participants’ decisions on each
payoff type [Yes or No to four payoff types, in addition to the
jitter and null condition (fixation baseline)]. Linear contrasts
were applied to the parameter estimates for each regressor type
to generate contrast images. Results were derived from random
effects analyses by performing one-sample t tests on the first-
level contrast images. Common effects of contrasts of interest
were assessed by performing conjunctions of random effects.
Additional analyses of covariance were used to investigate the
effect of decision frequency (how often participants made costly
donations or costly oppositions) and individual differences of
engagement scores on brain activity to costly donation (see
Supporting Methods). A priori regions of interest were the
orbitofrontal cortex, frontopolar cortex, septo-hypothalamic re-
gion, dorsal and ventral striatum, superior temporal sulcus
region, temporal pole, anterior insula, and dorsal anterior cin-
gulate cortex. Results are reported at P $ 0.005 (uncorrected)
and a cluster threshold of 70 mm3 for a priori regions of interest.

We thank Jerzy Bodurka for helping with optimization of fMRI data
acquisition; Eric Wassermann for performing the neurological exams;
and Marilia Duff les, Mirella Lopez Paiva, Edward Huey, and Walter
Sinnott-Armstrong for their insightful comments on the manuscript. We
are also thankful to Nicolas Lizop, Devon Shook, and Theron Pummer
for their help with data collection. This research was supported by the
Intramural Research Program of the National Institutes of Health,
National Institute of Neurological Disorders and Stroke, Cognitive
Neuroscience Section and by LABS–D’Or Hospital Network and Pro-
grama de Apoio a Núcleos de Excelência–Conselho Nacional de Des-
envolvimento Cientı́fico e Technológico (J.M.).

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The Scientific Method: decoding the primary literature

After you have read the Discovery magazine article
:  “Seven Deadly Sins” by Kathleen McGowan, you can begin this assignment. 

Several different primary literature articles were cited throughout this popular press article.
There are links to the pdfs of three of these scientific journal articles. 
Choose one of these scientific articles (above) and decode it to discuss each part of the scientific method:
1. Observation – what observations are the researchers basing their experiments on, what prior studies do these researchers cite?
2.  What is their hypothesis?
3.  How did they conduct and control their experiments?
4.  What conclusion did they reach?
5.  Did this conclusion help support or reject their hypothesis
6.  What further studies need to be conducted to further the understanding of this phenomenon?