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Neural basis of the undermining effect of monetary
reward on intrinsic motivation
Kou Murayamaa,1, Madoka Matsumotob,c,d, Keise Izumab,c, and Kenji Matsumotob,d,1
aDepartment of Psychology, University of Munich, 80802 Munich, Germany; bBrain Science Institute, Tamagawa University, Tokyo 194-8610, Japan;
Japan Society for the Promotion of Science, Tokyo 102-8471, Japan; and dCognitive Brain Mapping Laboratory, RIKEN Brain Science Institute,
Saitama 351-0198, Japanccrowding-out effect| dopamine | midbrain | neuroeconomicsP

erformance-based incentive systems have long been part ofthe currency of schools and workplaces. This predominanceof incentive systems may reﬂect a widespread cultural belief that
performance-based reward is a reliable and effective way toenhance motivation in students and workers. However, classic
psychological experiments have repeatedly revealed that performance-based reward can also undermine people’s intrinsic
motivation (1–6), that is, motivation to voluntarily engage ina task for the inherent pleasure and satisfaction derived from thetask itself (3–5). In a typical experiment of this “undermining
effect” [also called the “motivation crowding-out effect” (7–9) or“overjustiﬁcation effect” (2)], participants are randomly divided
into a performance-based reward group and a control group, andboth groups work on an interesting task. Participants in theperformance-based reward group obtain (or expect) reward
contingent on their performance, whereas participants in thecontrol group do not. After the session, participants are left toengage in any activity, including more of the target task if theywish, for a brief period when they believe they are no longer
being observed (i.e., “free-choice period”). A number of studies(4–6) found that the performance-based reward group spends
signiﬁcantly less time than the control group engaging in thetarget activity during the free-choice period, providing evidence
that the performance-based reward undermines voluntary engagement in the task (i.e., intrinsic motivation for the task).
The undermining effect challenges normative economic theories, which assume that raising monetary incentives monotonicallyincreases motivation and, more importantly, that increasing andthen removing monetary incentives does not disturb underlying
intrinsic motivation (7–9). It also challenges traditional operant learning theory and reinforcement learning theory, whichcurrently constitutes the fundamental theoretical framework forwww.pnas.org/cgi/doi/10.1073/pnas.1013305107

human decision making (10–12). These theories basically predictthat performance-based rewards increase the likelihood that the
behavior will be voluntarily performed again. It should be noted
that, as thoroughly discussed in the literature (4, 5, 13), the undermining effect cannot be explained by the operant conditioning concept of extinction as a result of the withdrawal of reward (i.e., because
the reward is no longer promised in the free-choice period, thereinforced response is extinguished and this produces the undermining effect) in several respects. Most importantly, the extinction
account predicts that, when rewards are no longer in effect, behavior
should revert to its original rate (the baseline) and never decrease
below that level (14, 15). Studies on the undermining effect, however,showed less voluntary engagement in the target task in the performance-based reward group than in the control group, which serves as
the strict baseline in randomized control design (5, 16). Given that
normative economic theories and standard reinforcement learningtheory have difﬁculty explaining the undermining effect, a better
understanding of this effect has the potential to enrich and give new
insight to these broad research ﬁelds (17). However, the neural basisof this provocative and important phenomenon remains unknown.
A source of intrinsic motivation is the intrinsic value of achieving
success on a given task (3, 5). As such, the undermining effect may
involve the interaction of two different types of subjective values
when one succeeds at a task: the extrinsic value of obtaining a reward and the intrinsic value of achieving success. Many neuroscience studies have revealed that a dopaminergic reward network
plays a pivotal role in representing and updating various types ofsubjective valuation (10–12, 18–24). In particular, recent studies
have suggested that activation in response to feedback in the anterior part of the striatum (caudate head) is modulated by one’s
subjective belief in determining the outcome (23, 25), whichis considered a key psychological factor in the undermining effect(3–5). Previous studies have also suggested that the midbrain,
which has a strong anatomical connection with the anterior striatum (19), is responsive to both monetary reward feedback andcognitive feedback (feedback without monetary reward)—feedbacks that are related to the undermining effect (26, 27). Therefore, we expected that the undermining effect may manifest as
brain activity changes in the reward network, especially in theanterior striatum and midbrain, in response to task feedback.
We expected the lateral prefrontal cortex (LPFC) to be anotherkey structure mediating the undermining effect. When confronting an upcoming task, people tend to be more engaged in mental
preparation for tasks with higher value (28, 29). As the LPFC is

Author contributions: K. Murayama, M.M., and K. Matsumoto designed research; K. Murayama,
M.M., K.I., and K. Matsumoto performed research; M.M. and K.I. contributed new reagents/
analytic tools; K. Murayama analyzed data; and K. Murayama wrote the paper.
The authors declare no conﬂict of interest.
This article is a PNAS Direct Submission.
See Commentary on page 20849.
1

To whom correspondence may be addressed. E-mail: matsumot@lab.tamagawa.ac.jp andmurakou@orion.ocn.ne.jp.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
1073/pnas.1013305107/-/DCSupplemental.

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Contrary to the widespread belief that people are positively motivated by reward incentives, some studies have shown that performance-based extrinsic reward can actually undermine a person’s
intrinsic motivation to engage in a task. This “undermining effect”
has timely practical implications, given the burgeoning of performance-based incentive systems in contemporary society. It also presents a theoretical challenge for economic and reinforcement learningtheories, which tend to assume that monetary incentives monotonically increase motivation. Despite the practical and theoretical importance of this provocative phenomenon, however, little is known
about its neural basis. Herein we induced the behavioral undermining
effect using a newly developed task, and we tracked its neural correlates using functional MRI. Our results show that performance-based
monetary reward indeed undermines intrinsic motivation, as assessedby the number of voluntary engagements in the task. We found that
activity in the anterior striatum and the prefrontal areas decreased
along with this behavioral undermining effect. These ﬁndings suggestthat the corticobasal ganglia valuation system underlies the undermining effect through the integration of extrinsic reward value andintrinsic task value.

PSYCHOLOGICAL AND
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Edited by Edward E. Smith, Columbia University, New York, NY, and approved October 20, 2010 (received for review September 8, 2010)

the center for the preparatory cognitive control to achieve goals(30–34), and this function has been shown to be modulated by task
value (28, 34), the undermining effect may be accompanied by adecrease in LPFC activity upon presentation of the task cue. Here,by using functional MRI (fMRI), we report evidence that theseareas are involved in the undermining effect of monetary reward
on intrinsic motivation.
The undermining effect is applicable only to interesting tasks
that have an intrinsic value of achieving success (3–6). We developed a stopwatch (SW) task in which participants were presented with an SW that starts automatically, and the goal was topress a button with the right thumb so that the button press fellwithin 50 ms of the 5-s time point (Fig. 1A). A point was added
to their score when they succeeded. A series of pilot studies
showed that the SW task is moderately challenging and inherently
interesting to Japanese university students (details provided inMaterials and Methods). The control task was a watch-stop (WS)task, in which participants passively viewed a SW and were asked
to simply press a button when it automatically stopped (Fig. 1A).
Success and failure were not deﬁned in this task; therefore the WS
task was less interesting than the SW task. Both tasks were
pseudorandomly intermixed and preceded by a cue that indicatedwhich task to perform.
Twenty-eight participants were randomly assigned to a control
group or a reward group. Participants were scanned in two separate sessions (Fig. 1B). Before the ﬁrst session, participants in
the reward group were told that they would obtain 200 Japaneseyen (approximately $2.20) for each successful trial of the SW task,
and indeed they received the performance-based reward after thesession. Participants in the control group were told nothing about
the performance-based reward and received money just for task
participation after the ﬁrst session. For each control group participant, the amount of monetary reward for the task was matchedto that received by another participant of the same sex in the reward group; thus, it was unrelated to the control participant’s own
task performance. This allowed us to examine the effect of performance-based reward apart from the amount of monetary reward offered. After being released from the scanner and receiving
the monetary reward, participants were left alone in a quiet roomfor 3 min, where they could freely spend time playing the SW
or WS task on a computer, read several booklets, or anything else
(i.e., free-choice period). The number of times participants played

Results
Behavioral Results. We conducted a 2 × 2 mixed ANOVA on thenumber of times the voluntary SW task was played, with period(ﬁrst or second free-choice period; within-subject) and group(control or reward group; between-subject) as factors. As predicted, the main effect of group was signiﬁcant, (F1,26 = 6.59,
P = 0.016). This result indicates the presence of the undermining
effect: participants in the reward group played the SW task during
the free-choice period signiﬁcantly fewer times than did those in
the control group (Fig. 1C). A signiﬁcant group difference wasobserved in both the ﬁrst and the second free-choice periods (P <0.05; SI Results). To the contrary, neither the main effect of period
nor the session-by-group interaction was signiﬁcant (F < 1, P >0.32). This suggests that no overall increase or decrease in thevoluntary SW task play was observed and that the pattern ofchange in the voluntary SW task play did not differ across thegroups. In fact, we observed no signiﬁcant increase or decrease of
the voluntary SW task play from the ﬁrst to the second free-choiceperiod in either group (P > 0.19).
We also conducted the same 2 × 2 mixed ANOVA on thenumber of times participants played the WS task during the freechoice period. Neither the main effects nor the interaction was
signiﬁcant (F < 1, P > 0.34; Fig. 1C). The numbers were quite
small, suggesting that the WS task was not interesting to
the participants.
fMRI Results. In the fMRI analysis, we were interested in ﬁnding

signiﬁcant session-by-group interactions, which means thatchanges in activation across sessions showed different patterns
between the two groups. Thus, we applied a 2 × 2 mixed ANOVA

Stopwatch (SW) task
Task cue (1.5s)

*

0

0

*

Stop the watch
at 5 sec.

0

*

0.00

button when thewatch stops

5.04

Press button

0

*

0

*

0.00

3.93

0

*
5.04

8

4

0
WS task

SW task

WS task

Press button

Session 1

Free-choiceperiodSession 2

Free-choiceperiod (follow-up)

Controlgroup

No performance-based
rewardIntrinsic motivationassessment

No performance-based
rewardFollow-up
assessment

Rewardgroup

Performance-based
rewardIntrinsic motivationassessment

No performance-based
rewardFollow-up
assessment

Scanning

Second free-choiceperiod**SW task
The stopwatch
stops automatically

B

First free-choiceperiod

12

1

*

3.93

Watch-stop (WS) task

*Press the0C

Feedback (3.0s)

Number of voluntary playA

the SW task during this free-choice period was used as the index of
intrinsic motivation toward the task (1–6).
To track the brain activity associated with the undermining effect, we asked participants in both groups to perform the SW and
WS tasks again after the free-choice period and without performance-based reward inside the scanner (second session; Fig. 1B).
Both groups of participants were explicitly told in advance that no
performance-based rewards would be provided. After being released from the scanner, the second free-choice period followed to
conﬁrm that the undermining effect persisted through the second
scanning session.

Scanning

Fig. 1. Experimental protocol and behavioral results. (A) Illustration of SW and WS tasks. (B) Depiction of the experimental procedure. (C) Means and SEs of thenumber of times participants voluntarily played the SW and WS tasks during the ﬁrst and the second free-choice periods. Performance-based reward
undermined the intrinsic motivation for the SW task for both free-choice periods (Mann–Whitney U = 52.5 and 54.5; P < 0.05).

20912 | www.pnas.org/cgi/doi/10.1073/pnas.1013305107

Murayama et al.

Fig. 2. Bilateral striatum responses elicited bysuccess trials relative to failure trials plotted foreach session/group. Left: Activations superimposed on transaxial sections (P < 0.001, onesample t test for display). Right: Mean contrast
values and SEs of the bilateral striatum (averaged)
activation are plotted. During the ﬁrst session,
signiﬁcant bilateral striatum activation was observed in both groups, although the activation was
signiﬁcantly greater in the reward group than in
the control group (two-sample t26 = 3.30, P < 0.01).
In contrast, during the second session, whereas thecontrol group sustained signiﬁcant activity, theactivation of the bilateral striatum in the reward
group decreased signiﬁcantly below that of thecontrol group (two-sample t26 = 3.75, P < 0.01) andthe activation was no longer signiﬁcant. This
striatal response pattern is in parallel with the
behavioral undermining effect. Asterisks represent the statistical signiﬁcance of one-sample/twosample t tests (**P < 0.01).

Murayama et al.

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midbrain showed a similar pattern of interaction (P < 0.05, smallvolume-corrected; Fig. 3), consistent with the strong anatomical
connection between the midbrain and anterior striatum (19, 26).
We next focused on a task cue period to investigate the brain
activity associated with preparatory cognitive control in the SW
task relative to the WS task. A one-sample t test in the ﬁrst session
revealed that the right LPFC was signiﬁcantly activated regardlessof the group (P < 0.05, small-volume corrected). This result indicates that the participants were cognitively engaged in the SW
task relative to the WS task when the task cue was presented. Thisis consistent both with the observation that participants were more
willing to engage in the SW task in the free-choice periods andwith previous ﬁndings that the LPFC is activated in response toa task cue with high value (28, 34). In other words, this ﬁnding
supports the validity of our experimental task for examining LPFC
activation in response to task cue.
In the 2 × 2 ANOVA, as expected, the right LPFC showeda signiﬁcant session-by-group interaction that is also a parallelwith the behavioral undermining effect (P < 0.05, small-volumecorrected; Fig. 4). During the ﬁrst session, the LPFC in the reward group showed signiﬁcantly larger activation than that in thecontrol group (two-sample t26 = 2.62, P < 0.05), suggesting thatparticipants in the reward group prepared for the SW task more
actively than those in the control group when they saw a task cue.
However, during the second session, although signiﬁcant activity
in the control condition was sustained in the second session (onesample t13 = 2.53, P < 0.05), the activation became signiﬁcantly
smaller in the reward group than in the control group (twosample t26 = 2.27, P < 0.05), and the activation was no longer
signiﬁcant (P = 0.43). This result may indicate that the participants in the reward group were not motivated to prepare for the
SW task during the second session in comparison with the control
group participants. The bilateral striatum also showed a signiﬁcant interaction for the task cue period, but unlike the activation
pattern in the feedback period, no signiﬁcant between-groupdifference in activation was detected during the second session(Fig. S2).
Table S1 (for the feedback period) and Table S2 (for the taskcue period) list all regions displaying a signiﬁcant session-bygroup interaction in a whole-brain analysis (P < 0.001, uncorrected, k > 5). The tables also describe the results of simple
main effect analyses and one-sample t tests that quantify thepattern of interaction as we conducted for the striatum, midbrain,

NEUROSCIENCE

with session (ﬁrst or second session) and group (control or reward
group) as factors. The signiﬁcant interactions reported here werebased on the regions that survived both a whole-brain analysis(P < 0.001, uncorrected) and small-volume correction analysis(P < 0.05; details in Materials and Methods).
We ﬁrst focused on a feedback period to examine the neural
responses to the success feedback versus the failure feedback.
A one-sample t test in the ﬁrst session showed that the bilateralanterior striatum (caudate head) and midbrain were signiﬁcantly
activated, regardless of the group (P values < 0.05, small-volume
corrected). This result indicates that the success feedback in theexperimental task we developed involves reward network activation, regardless of whether the feedback was accompanied with
monetary reward. This is consistent with previous work (21, 23, 25,26) and supports the validity of our experimental task for examining
brain activation in response to task feedback.
In the 2 × 2 ANOVA, as expected, the bilateral striatum activation showed a signiﬁcant interaction between session (ﬁrst or
second session) and group (control or reward group) that is a
striking parallel with the behavioral undermining effect (P < 0.05,
small-volume-corrected; Fig. 2 and Fig. S1). During the ﬁrst session, signiﬁcant anterior striatum activation was observed in bothgroups: one-sample t13 values of 6.61 (control) and 8.43 (reward);
P < 0.01 for both. However, the activation was signiﬁcantly greaterin the reward group than in the control group: two-sample t26 = 3.30
(P < 0.01). Previous studies have implied that the striatum functions as a hub of the human valuation process, by converting andintegrating different types of reward values onto a common scale(11). Our result can be interpreted by this view such that the signiﬁcant positive activation in the control group reﬂects the intrinsic value of achieving success (23, 25) and this activation waselevated by the additional performance-based monetary reward in
the reward group. Importantly, whereas this activity during the second session was sustained in the control group (one-sample t13 =7.33, P < 0.01; no between-session change was observed, P = 0.41),
there was a dramatic decrease in activation of the bilateral anterior striatum in the reward group, and the activation was no longer
signiﬁcant (one-sample t13 = 0.41, P = 0.69; decrease in the activity from the ﬁrst to the second session was signiﬁcant, paired
t13 = 7.35, P < 0.01). As a result, the between-group difference inthe anterior striatal activation was reversed from the ﬁrst session
to the second session and became signiﬁcantly smaller in the reward group compared with the control group during the second
session (two-sample t26 = 3.75, P < 0.01). Also as predicted, theFig. 3. Midbrain activation (peak at −9, −7, −11) detected in the session-bygroup interaction during the feedback period (success trials minus failure trials;
P < 0.05, small-volume-corrected; the image is shown at P < 0.001, uncorrected).
Neural responses are displayed in sagittal and transaxial formats. The midbrain
was activated when performance-based monetary reward was expected (during the ﬁrst session; two-sample t26 = 1.80, P < 0.10), but the activation decreased signiﬁcantly below the control group in the second session (two-sample
t26 = 2.63, P < 0.05). Asterisks represent the statistical signiﬁcance of onesample/two-sample t tests (+P < 0.10, *P < 0.05, **P < 0.01).

Fig. 4. Right LPFC activation (peak at 39, 41, 40) detected in the session-bygroup interaction during the task cue period (P < 0.05, small-volume-corrected; image is shown at P < 0.001, uncorrected for display). Neural responses
are displayed in transaxial and coronal formats. The bar plot represents meancontrast values and SEs for each session/group. During the ﬁrst session, theLPFC in the reward group showed signiﬁcantly larger activation than that in
the control group (two-sample t26 = 2.62, P < 0.05). However, the activation
became signiﬁcantly smaller in the reward group than in the control groupduring the second session (two-sample t26 = 2.27, P < 0.05).

and LPFC (SI Results includes additional analyses focusing on
a possible sex effect).

not signiﬁcant (standardized β = 0.09, P = 0.75). An additional
regression analysis including group, the number of voluntary SW
play trials, and their interaction as independent variables showedsigniﬁcant interaction (P = 0.045), indicating that the aforementioned regression coefﬁcients in the reward and control groups
were signiﬁcantly different.

Brain–Behavior Relation. We conjecture that the observed decreases in activity of the anterior striatum, midbrain, and LPFC arecollectively related to the undermining effect. In fact, the magnitudes of the decreases in activation in these regions were highly
correlated (mean r = 0.65). Accordingly, we calculated a “neural
undermining index”—a composite score representing the betweensession decreases in activity for these regions, and regressed it on
the voluntary SW task play during the free-choice period. Speciﬁcally, we computed the magnitude of a decrease in activation by
subtracting the contrast value in the second session from the contrast value in the ﬁrst session for each region of interest (i.e., thestriatum and the midbrain for feedback period and the LPFC forcue period) and submitted these values to principal component
analysis. Principal component analysis is a statistical technique tocompute optimal and reliable composite scores of a set of variables
that are less susceptible to random noise by taking into accounttheir variance and covariance (35). The ﬁrst principal component
explained a substantial portion (74%) of the total variance, and weused this component score as the neural undermining index.
As expected, regression analysis revealed a signiﬁcant negative
relationship between the amount of voluntary SW play and theneural undermining index in the reward group (standardized
β = −0.49, P = 0.037, one-tailed), indicating that those who did notvoluntarily try the SW task during the free choice period showeda larger decrease in activation of the corticobasal ganglia network(Fig. 5). The regression coefﬁcient remained signiﬁcant even when
the conﬁdence interval was based on a (bias-corrected) bootstrapping method to correct for the potential statistical biases
resulting from nonnormality and outliers (36). The magnitude ofrelationship is large according to the Cohen established effect size
criterion (37). In contrast, the relationship in the control group was
20914 | www.pnas.org/cgi/doi/10.1073/pnas.1013305107

Discussion
Our study provides evidence that the corticobasal ganglia valuation
system plays a central role in the undermining effect. Speciﬁcally,
our neuroimaging results suggest that, when performance-based
reward is no longer promised, (i) people do not feel subjective value
in succeeding in the task, as indicated by the dramatic decreases in
the activation of the striatum and midbrain in response to thesuccess feedback; and (ii) they are not motivated to show cognitive
engagement in facing the task, as indicated by the decrease in the
LPFC activation in response to the task cue. A number of theories
have been proposed to explain the undermining effect from valuebased and cognitive perspectives (5, 6). Our ﬁndings clearly indicatethat value-driven and cognitive processes are involved in theundermining effect, and they are linked. Notably, activation in theanterior part of the striatum, which has been implicated in subjective belief in determining outcomes (23, 25), corresponds particularly well to the pattern observed in the behavioral undermining
effect. This lends support for the recent psychological theory thatthe undermining effect is closely linked to a decreased sense of selfdetermination (3–5).
The precise neural and computational mechanism that accounts
for the striatal signal decrease in the reward group merits future
inquiry. One explanation is that the striatum, in which incommensurable subjective values are aligned on a unidimensional common
scale, integrates the intrinsic value of task success and monetary
reward value through relative comparison and rescaling processes(38). Given the relatively stronger salience of monetary reward, theMurayama et al.

rescaled value of task success could become smaller than theoriginal magnitude. In other words, the strong incentive value ofmonetary reward pushed down the intrinsic value of task success.
As a result, when the monetary reward was no longer promised, theintrinsic task value was underestimated, resulting in decreased
motivation relative to the control group (i.e., less frequent play of
the SW task in the free-choice period). This interpretation underscores the importance for future empirical and theoretical work
addressing the human value integration process (38, 39).
Neuroscience research has made considerable progress by incorporating concepts of motivation (40), yet most research to datehas been conﬁned to extrinsic rewards such as food or money. In
comparison with our knowledge of extrinsic rewards, little lighthas been shed on intrinsic sources of motivation, and much less on
the integration of the two. However, given the burgeoning of
performance-based incentive systems in contemporary society, theinteraction of these motivations is gaining practical importance inguiding human behavior. We believe an expanded understandingof this integration process is a key piece in aligning the undermining effect with leading economic and learning theories, and inreaching a deeper understanding of human behavior in general.
Materials and Methods
Participants. Twenty-eight right-handed healthy participants [mean age, 20.6 ±1.1 y (SD); 10 male and 18 female] recruited from a pool of Tamagawa University (Tokyo, Japan) students took part in the experiment. Participants wererandomly assigned to a control group (n = 14) or a reward group (n = 14). All
participants gave informed consent for the study and the protocol was approvedby the Ethics Committee of Tamagawa University.
Experimental Tasks. The undermining effect can be observed only when a task isinteresting and has intrinsic value of achieving success; with boring tasks, there
is little or no intrinsic motivation to undermine (5). Accordingly, an SW task wasdeveloped (Fig. 1A) to meet this criterion. A series of pilot studies were conducted to determine the time window for success so that participants can
succeed on approximately half the trials on average. Previous literature indicated that people obtain the greatest sense of achievement for the tasks ofintermediate difﬁculty (41, 42). In addition, this rate of success allows a sufﬁcient number of success or failure trials to be obtained for proper fMRI statistical analysis. The participant’s total score was displayed in the upper rightcorner of the display area, and when the participant succeeded in stopping the
SW display between 4.95 s and 5.05 s, a point was added to their score (1,500
ms after the button press) and the updated score panel ﬂashed for 1,500 ms.
Another pilot study using an independent university student sample (n = 37)
revealed that this task is sufﬁciently interesting without any extrinsic incentives (mean enjoyment rating, 4.14; SD, 0.82, on a ﬁve-point Likert scale). We

Murayama et al.

fMRI Data Acquisition. The functional imaging was conducted using a 3-T Trio A
Tim MRI scanner (Siemens) to acquire gradient echo T2*-weighted echo-planar
images (EPI) with blood oxygenation level-dependent contrast. Forty-two
contiguous interleaved transversal slices of EPI images were acquired in eachvolume, with a slice thickness of 3 mm and no gap (repetition time, 2,500 ms;
echo time, 25 ms; ﬂip angle, 90°; ﬁeld of view, 192 mm2; matrix, 64 × 64). Sliceorientation was tilted −30° from the AC–PC line. We discarded the ﬁrst three
images before data processing and used statistical analysis to compensate for
the T1 saturation effects.
fMRI Data Analysis. Image analysis was performed by using Statistical Parametric Mapping software (version 8; http://www.ﬁl.ion.ucl.ac.uk). Images werecorrected for slice acquisition time within each volume, motion-corrected withrealignment to the ﬁrst volume, spatially normalized to the standard Montreal

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Fig. 5. Relationship between behavioral choice during the ﬁrst free-choiceperiod and the neural undermining index. Signiﬁcant negative relationship wasobserved in the reward group (β = −0.49, P = 0.037, one-tailed), indicating thatthose who did not voluntarily try the SW task during the free-choice period
showed a larger decrease in activation of the corticobasal ganglia network. The
relationship in the control group was not signiﬁcant (β = 0.09, P = 0.75). Blue
triangles represent participants in the control group; red squares represent
participants in the reward group.

Experimental Procedure. The experimental sessions were conducted individually. Upon arriving at the experiment room, participants were greeted by
two experimenters. The experiment consisted of two separate sessions, each ofwhich was conducted by one of the experimenters. We decided to use a different experimenter for each session to prevent the participants from being
aware of the relationship between these two sessions. In the postexperimental
interviews, no participant reported noticing the fact that the two experiments
were conducted under a common purpose. Regardless of the experimental
conditions, the payment for the task participation in the second session wasprovided to the participants before the experiment (2,000 Japanese yen, approximately equal to $22). This procedure allowed us to avoid any possible
monetary incentive effects in the second session, the critical session to capture
the brain activity of the undermining effect.
Before the ﬁrst scanning session, participants in the reward group were
informed that they would receive 200 Japanese yen (approximately equal to$2.20) for each point they obtained during the session. In contrast, no mention was made about the performance-based monetary reward in the control
group. The instruction was provided through a computer program to prevent
possible experimenter bias.
On completing the ﬁrst scanning session, participants were released fromthe scanner and led to a small waiting room, where participants in the reward
group were provided with the performance-based monetary reward. Participants in the control group received payment for task participation. For eachparticipant in the control group, the amount of monetary reward for the task
was matched to that of a participant in the reward group (i.e., both groups
received the same amount of reward).
After the participants conﬁrmed the amount of money they received, theexperimenter asked the participants to wait for a couple of minutes because theother experimenter needed a few more minutes to prepare for the next experiment. There was a computer in the room and participants could freely
choose to play the SW or WS task as many times as they wanted with thatcomputer. There were also a few booklets on a desk and participants could freely
read them. During this free-choice period, participants believed they were nolonger observed by the experimenters, but the computer program conﬁdentially recorded the number of SW and WS task trials they voluntarily played. The
number of trials they played on the SW task was used as the index of intrinsic
motivation. This is a standard way of assessing intrinsic motivation and has beenused in many previous experiments on the undermining effect (1–5). After
exactly 3 min, the door of the waiting room was opened and the participants
were led to the scanning room again.
The second session was ostensibly conducted by the second experimenter.
Before the task, participants were instructed that they would do the SW and WS
tasks used in the previous experiment, but it was emphasized that the purpose of
the experiment was completely independent. Both groups of participants werealso explicitly told that no performance-based rewards would be provided in thisexperiment. As such, participants in both groups did not expect any performancebased rewards in the second session. After the scanning session, participants werereleased from the scanner and exposed to a 3-min free-choice period again.

NEUROSCIENCE

also developed a WS task as the control task (Fig. 1A). Because success andfailure were not deﬁned in this task, no point was added on their response.
The experiment was composed of two separate scanning sessions (approximately 18 min each) and each session consists of 30 SW and 30 WS trials,
which were pseudorandomly intermixed with the interstimulus interval alternated between 1,000 and 5,000 ms. Both tasks were preceded by a cue thatindicates which of two tasks is to be performed in the next trial. The cue waspresented for 1,500 ms and the SW starts 3,000 ms after the cue onset. The
timing of the stop for a WS trial is approximately matched (alternating basedon random noise) to the time achieved in a prespeciﬁed SW trial.

Neurological Institute EPI template, and spatially smoothed using a Gaussian
kernel with a full width at half maximum of 8 mm.
For each participant, the blood oxygen-level dependent responses acrossthe scanning run (including both sessions) were modeled with a generallinear model. The model included the following regressors of interest:
presentation of success feedback in the SW task, presentation of failure
feedback in the SW task, presentation of SW task cue, and presentation of
WS task cue. The motion parameters, error trials, and session effects werealso included as regressors of no interest. The regressors (except for the
motion parameters and the session effects) were calculated using a boxcar
function convolved with a hemodynamic-response function. The estimates
were corrected for temporal autocorrelation by using a ﬁrst-order autoregressive model. To investigate the feedback effects and cue effects, ourprimary focus of interest, two contrast values were calculated: (i) contrast
between success feedback and failure feedback effects (i.e., success minus
failure), and (ii ) contrast between SW task cue and WS task cue effects (i.e.,
SW minus WS).
We conducted a second-level, whole-brain 2 × 2 mixed ANOVA with session(ﬁrst or second session; within-subject) and group (control or reward group;
between-subject) as factors, once on the success/failure contrasts and once on
the SW/WS contrasts. A number of regions showed a signiﬁcant session-bygroup interaction (P < 0.001, uncorrected, k > 5 voxels), including anterior
striatum, midbrain (for the feedback period), and LPFC (for the task cue period), our primary region of interest (Tables S1 and S2). To conﬁrm the re-

ACKNOWLEDGMENTS. We thank J. Tanji, C. Camerer, J. O’Doherty, K. Samejima,
H. Kim, A. Przybylski, and R. Pekrun for helpful comments; K. D’Ardenne
and M. J. Tyszka for providing technical information; T. Haji, R. Iseki, S. Bray,and J. Gläscher for technical advice; J. Helen for English prooﬁng; and Y. Otake
for research assistance. This study was supported by Grant-in-Aid for ScientiﬁcResearch C#21530773 (to K. Matsumoto), Grand-in-Aid for Scientiﬁc Researchon Innovative Areas 22120515 (to K. Matsumoto); a Tamagawa University
Global Center of Excellence grant from the Ministry of Education, Culture,
Sports, Science and Technology, Japan; and an Alexander von Humboldt Foundation fellowship (to K. Murayama).

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20916 | www.pnas.org/cgi/doi/10.1073/pnas.1013305107

liability of the signiﬁcant interaction effects obtained in the regions for which
we had an a priori hypothesis (the anterior striatum and midbrain for the
feedback period and the LPFC for the task cue period), we also performeda small-volume correction analysis with a corrected signiﬁcance threshold of
P < 0.05 within a 12-mm sphere centered on the coordinates identiﬁed in theprevious empirical studies or meta-analyses (25, 26, 33, 43). All regions ofinterest survived this analysis.
To quantify the pattern of interaction, we further conducted a series ofpost-hoc analyses. Speciﬁcally, we extracted the contrast values from a 3-mm
sphere centered on the peak voxel of each region using rfxplot (44), andsubjected these extracted values to a series of simple main-effect analyses(i.e., test for the between-group difference within each session) and onesample t tests (i.e., test for the signiﬁcance of the absolute contrast values
for each session/group).

Murayama et al.

Supporting Information
Murayama et al. 10.1073/pnas.1013305107
SI Results
Randomization Test. To conﬁrm that our behavioral results on theundermining effect were not obtained by chance (e.g., preexistingheterogeneity of the groups), we conducted a randomization test
(1) as an additional analysis (using a Monte Carlo simulation; N =10,000). This test allows us to examine the probability of obtaining
the observed between-group difference in the free-choice behavior under the null hypothesis when we use the random assignment
procedure. The obtained P values were less than 0.05 (P = 0.041
for the ﬁrst free-choice period and P = 0.042 for the second freechoice period), indicating that our behavioral results cannot be
attributable to the accidental heterogeneity of the groups.

(r = −0.01, P = 0.98 for the control group; r = −0.09, P = 0.77 forthe reward group), suggesting that the SW task performance does
not reﬂect participants’ intrinsic motivation for the task.
It should also be noted that the skill acquired in motor-responsetasks like the SW task is likely to be resistant to the loss (3, 4). This
could explain why the participants in the reward group continued
to show superior performance (although nonsigniﬁcant) in the
SW task in the second session. In fact, the correlation between
the SW task performance in the ﬁrst and second sessions is very
high (r = 0.78, P < 0.0001), suggesting the high stability of the
SW task performance.

was signiﬁcantly better in the reward group than in the control group(t26 = 2.35, P < 0.05; M = 13.07 and 17.79, SD = 5.28 and 5.34). In
the second session, the difference became weaker and was nolonger signiﬁcant (t26 = 1.72, P = 0.10; M = 13.07 and 16.79, SD =6.53 and 4.74), but there is still a trend that participants in the reward condition showed better performance in the SW task.
A previous meta-analysis has shown that intrinsic motivation
conferred an advantage only for complex, cognitive tasks, but notfor simple, noncognitive tasks (2). Therefore, given that the SW
task is a noncognitive, motor-response task, the results in the SW
task performance are consistent with the previous observations.
Indeed, the correlation between the SW task performance in thesecond session and the number of voluntary plays of the SW task
(after the ﬁrst session) was not signiﬁcant in either of the groups

Sex Difference. In the behavioral analysis, we conducted a 2 (freechoice period: ﬁrst or second time) × 2 (group: control or reward
group) × 2 (sex: male or female) mixed ANOVA to investigate
a possible sex difference in the behavioral undermining effect.
None of the interactions involving sex was signiﬁcant (P values >0.20). In the fMRI analysis, we conducted a 2 (session: ﬁrst or
second session) × 2 (group: control or reward group) × 2 (sex:male or female) ANOVA to examine whether the session-bygroup interaction (our primary effect of interest) was affected bysex (P < 0.001, uncorrected, k > 5 voxels). No signiﬁcant three-way
interaction (i.e., session × group × sex) was detected in the striatum, midbrain, or LPFC for the task cue or feedback period. These
results, taken together, suggest that our behavioral and fMRI
ﬁndings are not dependent on participants’ sex, although ouranalyses may be underpowered as a result of the small sample size.

1. Edgington ES, Onghena P (2004) Randomization Tests (Chapman & Hall/CRC, Boca
Raton, FL), 4th Ed.
2. Utman CH (1997) Performance effects of motivational state: a meta-analysis. Pers Soc
Psychol Rev 1:170–182.

3. Eslinger PJ, Damasio AR (1986) Preserved motor learning in Alzheimer’s disease:
implications for anatomy and behavior. J Neurosci 6:3006–3009.
4. Doyon J, Ungerleider LG (2002) Functional anatomy of motor skill learning. Neuropsychology of Memory, eds Squire LR, Schacter DL (Guilford Press, New York), pp 225–238.

SW Task Performance. During the ﬁrst session, SW task performancez = -1y = 21

5.2

3.9

2.6

1.3
0.0

Fig. S1. Bilateral striatum activation (peaks at 21, 20, −2 and −21, 23, 1) detected in the session-by-group interaction during the feedback period (i.e., successtrials minus failure trials; P < 0.05, small-volume-corrected; image is shown at P < 0.001, uncorrected). Neural responses are displayed in transaxial and coronalformats. Plot for the individual session/group is depicted in Fig. 2.

Murayama et al. www.pnas.org/cgi/content/short/1013305107

1 of 3z = -4

y = 24

4.8

3.6

2.4

1.2

Beta (SW task – WS task)

0.0

2

**

Control group
Reward group

** **

** **

Session 1

Session 2

1.6
1.2
0.8
0.4
0
-0.4

Fig. S2. Bilateral striatum activation (peaks at 15, 8, −11 and −18, 26, 10) showing a signiﬁcant session-by-group interaction in response to the SW cues relative
to the WS cues (image is shown at P < 0.001, uncorrected). Neural responses are displayed in transaxial and coronal formats. The pattern of striatal activation was
different from that during the feedback period. The graph represents the averaged activation across both the right and left striatum. Asterisks represent thestatistical signiﬁcance of one-sample/two-sample t tests (**P < 0.05, *P < 0.01).

Table S1. Patterns of the session-by-group interaction during the
feedback period in response to success (relative to failure) trials
RegionC1 < R1 and C2 > R2
Right anterior striatum
Left anterior striatum
C1 < R1 and C2 ≈ R2
Left inferior frontal gyrus
2
C1 < R1 and C2 > R
Right LPFC
Right inferior frontal gyrus
Midbrain
Left central OFC*
Presupplementary motor area
Right inferior frontal gyrus

Peak MNI coordinates(x, y, z)z value

21
−21

20
23

−2
1

4.04
4.75

−42

29

−2

4.08

57
42
−9
−24
−12
33

32
26
−7
35
20
32

19
−11
−11
−11
52
−2

3.79
3.52
3.40
4.40
3.63
3.38

All regions that showed a signiﬁcant interaction effect (P < 0.001, uncorrected, k > 5 voxels) are categorized based on simple main effect analyses
within each session. C1, control group in the ﬁrst session; R1, reward group in
the ﬁrst session; C2, control group in the second session; R2, reward group in
the second session; MNI, Montreal Neurological Institute; ≈, nonsigniﬁcantdifference. Conditions that showed a signiﬁcant positive activation (activation is signiﬁcantly higher in responses to success trials than to failure trials)
are underlined (e.g., C2). Conditions that showed a signiﬁcant negative activation (activation is signiﬁcantly smaller in responses to success trials than 2 ).
to failure trials) have a bar above them (e.g., R*In the second session, a marginally signiﬁcant positive activation was observed in the control group.

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Table S2. Patterns of the session-by-group interaction during thetask cue period in response to SW (relative to WS) trials
RegionC1 < R1 and C2 > R2
Right LPFC
Cerebellum
C1 < R1 and C2 ≈ R2
Right striatum
Left anterior striatum
Right globus pallidus
Presupplementary motor area
Supplementary motor area
Anterior thalamus
C1 < R1 and C2 ≈ R2
Right premotor cortex
Left premotor cortex*
Right frontal pole
Parietal lobe†
Right temporal lobe†
Left primary motor cortex
C1 < R1 and C2 ≈ R2
Left primary motor cortex
Cerebellum

Peak MNI coordinates(x, y, z)z value

39
−30

41
−79

40
−17

3.77
4.34

15
−18
9
3
6
−3

8
26
−1
11
−7
−4

−11
10
−5
73
79
7

3.55
3.75
3.42
4.23
3.30
3.25

33
−30
36
12
45
−30

−4
−4
62
−73
−31
−40

70
70
16
46
−11
61

3.53
3.87
3.88
3.52
3.92
3.36

−42
−51

−34
−58

61
−20

3.52
3.47

All regions that showed a signiﬁcant interaction effect (P < 0.001, uncorrected, k > 5 voxels) are categorized based on simple main effect analyses
within each session. C1, control group in the ﬁrst session; R1, reward group in
the ﬁrst session; C2, control group in the second session; R2, reward group in
the second session; MNI, Montreal Neurological Institute; ≈, nonsigniﬁcantdifference. Conditions that showed a signiﬁcant positive activation (activation is signiﬁcantly higher in responses to SW trials than to WS trials) are
underlined (e.g., C2).
*In the second session, a signiﬁcant positive activation was observed in the
reward group.
†
In the second session, a signiﬁcant (or a marginally signiﬁcant) positiveeffect was observed in the control group.

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