ORIGINAL RESEARCH ARTICLE
published: 18 September 2014
doi: 10.3389/fnins.2014.00303
The brain correlates of the effects of monetary and verbal
rewards on intrinsic motivation
Konstanze Albrecht 1*, Johannes Abeler 2 , Bernd Weber 3,4 and Armin Falk 3,5
1
2
3
4
5
Department of Education, Cognition, and Communication, Institute of Psychology, RWTH Aachen University, Aachen, Germany
Department of Economics, University of Oxford, Oxford, UK
Center for Economics and Neuroscience, University of Bonn, Bonn, Germany
Department of Epileptology, University Hospital of Bonn, Bonn, Germany
Department of Economics, University of Bonn, Bonn, Germany
Edited by:
Hauke R. Heekeren, Freie
Universität Berlin, Germany
Reviewed by:
Jack Van Honk, Utrecht University,
Netherlands
Mauricio R. Delgado,
Rutgers-Newark: The State
University of New Jersey, USA
*Correspondence:
Konstanze Albrecht, Department of
Education, Cognition, and
Communication, Institute of
Psychology, RWTH Aachen
University, Jaegerstrasse 17-19,
52056 Aachen, Germany
e-mail: albrecht@
psych.rwth-aachen.de
Apart from everyday duties, such as doing the laundry or cleaning the house, there are
tasks we do for pleasure and enjoyment. We do such tasks, like solving crossword puzzles
or reading novels, without any external pressure or force; instead, we are intrinsically
motivated: we do the tasks because we enjoy doing them. Previous studies suggest
that external rewards, i.e., rewards from the outside, affect the intrinsic motivation to
engage in a task: while performance-based monetary rewards are perceived as controlling
and induce a business-contract framing, verbal rewards praising one’s competence can
enhance the perceived self-determination. Accordingly, the former have been shown to
decrease intrinsic motivation, whereas the latter have been shown to increase intrinsic
motivation. The present study investigated the neural processes underlying the effects
of monetary and verbal rewards on intrinsic motivation in a group of 64 subjects
applying functional magnetic resonance imaging (fMRI). We found that, when participants
received positive performance feedback, activation in the anterior striatum and midbrain
was affected by the nature of the reward; compared to a non-rewarded control group,
activation was higher while monetary rewards were administered. However, we did not
find a decrease in activation after reward withdrawal. In contrast, we found an increase
in activation for verbal rewards: after verbal rewards had been withdrawn, participants
showed a higher activation in the aforementioned brain areas when they received success
compared to failure feedback. We further found that, while participants worked on the
task, activation in the lateral prefrontal cortex was enhanced after the verbal rewards were
administered and withdrawn.
Keywords: intrinsic motivation, crowding-out, monetary rewards, verbal rewards, fMRI
INTRODUCTION
In many fields, such as education and the workplace, tangible
incentives are used to motivate individuals to learn or to work.
However, a large body of psychological and economic research
indicates that such incentives do not necessarily enhance, but
can also undermine intrinsic motivation (Deci, 1971; Lepper
et al., 1973; Ryan et al., 1983; Camerer and Hogarth, 1999;
Deci et al., 1999; Irlenbusch and Sliwka, 2005; Mellström and
Johannesson, 2008). Empirical studies showed that individuals who received a tangible performance-based reward—such as
money—exerted lower effort in a task when the reward was
not available anymore (e.g., Deci, 1971; Lepper et al., 1973;
Irlenbusch and Sliwka, 2005). In comparison, in a control group
that never received a performance-based reward, effort did not
decline. The studies further showed that verbal reinforcement can
have the opposite effect on participants’ engagement in a task:
when participants received supportive verbal feedback praising
their competence, engagement in the task increased after reward
withdrawal.
www.frontiersin.org
In their Cognitive Evaluation Theory (CET), Deci and Ryan
(1985) explain these findings as follows: CET asserts that two
psychological needs underlie intrinsic motivation; the need for
self-determination and the need for competence. Accordingly, the
effect of a reward on intrinsic motivation depends on how the
reward affects these needs, i.e., how it affects the perception of
self-determination and the perception of competence. If a reward
has a positive effect on these needs by enhancing perceived selfdetermination and perceived competence, it increases (crowdsin) intrinsic motivation and accordingly the engagement in a task.
In contrast, if the effect is negative, perceived self-determination
and perceived competence are reduced and intrinsic motivation
will be decreased (crowded-out). Whether a reward has a positive or negative effect on these needs depends on its nature: if the
reward is perceived as controlling one’s behavior (such as monetary rewards), it reduces perceived self-determination, leads to a
more external perceived locus of causality and decreases intrinsic motivation. If, on the other hand, the reward is informational
and perceived as indicating one’s competence (such as verbal
September 2014 | Volume 8 | Article 303 | 1
Albrecht et al.
reinforcement), it increases intrinsic motivation. Performancecontingent monetary rewards, i.e., rewards that are expected and
only awarded when a task is performed successfully, are very
likely to be perceived as controlling, since to receive them successful completion of the task is necessary (Deci et al., 1999). In
contrast, informational rewards, such as verbal feedback emphasizing an individual’s competence in a task, are likely enhancing
one’s perceived competence and thus lead to an increased intrinsic
motivation in the task (Deci et al., 1999).
In neuroscientific research, animal studies were used to investigate and model motivation processes (e.g., Dayan and Balleine,
2002; Shiflett and Balleine, 2010; Wassum et al., 2011). To our
knowledge, up to now only one study looked into the effect of tangible rewards on motivation in humans: Murayama et al. (2010)
investigated the neural basis of the first part of Deci’s and Ryan’s
(1985) CET, i.e., the crowding-out of intrinsic motivation with
monetary rewards. They used a stop-watch task which participants performed over two periods. At first, participants in the
monetary reward group received a performance based payment
which was withdrawn in the subsequent period. A control group
did the same task without any performance-based payment over
both periods. They reported an interaction of activation in the
anterior part of the striatum and midbrain when participants
received success vs. failure feedback: whereas activation was higher
in these regions for the reward group compared to the control
group while rewards were administered, it was lower in the reward
group after rewards were withdrawn.
Since these regions were associated with a sense of self-agency
(Tricomi et al., 2004, 2006; Delgado, 2007; Tricomi and Fiez, 2008;
Shohamy, 2011) and responsiveness toward cognitive feedback
and rewards (e.g., Delgado et al., 2000; Shohamy et al., 2004; Aron
et al., 2004; O’Doherty et al., 2006; D’Ardenne et al., 2008; Haber
and Knutson, 2009), respectively, the authors interpreted this as
reduced intrinsic motivation of the reward group to engage in
the task after reward withdrawal. They further observed that activation in the right lateral prefrontal cortex (rLPFC) showed the
same interaction effect during the cue phase, i.e., when participants learned whether an interesting or boring task was coming
next. The rLPFC is assumed to be involved in the cognitive
processes underlying the motivation to achieve goals (Duncan
et al., 1996; Leon and Shadlen, 1999; Miller and Cohen, 2001;
Wager and Smith, 2003; Bunge, 2004), and that this motivation is modulated by reward sensitivity (Jimura et al., 2010). It
could hence signal the motivation to exert effort in an upcoming
task.
In the present functional magnetic resonance study, we, similarly to Murayama et al. (2010), investigated the administration and withdrawal of monetary rewards on brain activation.
We additionally investigated the effect of verbal rewards in a
comparable way.
Like Murayama et al. (2010), we expected the anterior striatum and midbrain to be responsive to reward feedback. Several
studies suggest that the anterior striatum plays a role in the perception of agency (Tricomi et al., 2004, 2006; Delgado, 2007;
Tricomi and Fiez, 2008) and is responsive to both monetary
and social rewards (Izuma et al., 2008). For example, Delgado
(2007) reported that activation to feedback in the striatum was
Frontiers in Neuroscience | Decision Neuroscience
Rewards and intrinsic motivation
higher when rewards were contingent on behavior, suggesting an
association with self-agency. Further, the striatum was found to
be more highly activated when success was not determined randomly (i.e., by luck) but by informed choice (Tricomi and Fiez,
2008). CET claims that monetary and verbal rewards affect the
perception of self-determination (Deci and Ryan, 1985), which
accordingly may be reflected in anterior striatum activation.
Midbrain structures have been shown to be connected to the
striatum (Haber et al., 2000; Kahnt et al., 2009), to be responsive to monetary and non-monetary rewards and are supposed to
be involved in the subjective valuation of rewards (e.g., Shohamy
et al., 2004; Aron et al., 2004; O’Doherty et al., 2006; D’Ardenne
et al., 2008). For example, an increased activation in the midbrain was not only found in the presence of monetary rewards
(Shohamy et al., 2004) but also when cognitive feedback, informing a person that her response was correct, was given (Aron
et al., 2004). Further, O’Doherty et al. (2006) showed that midbrain activation corresponds to reward preferences; the higher a
participant ranked a certain juice stimulus, the higher was the
midbrain’s activation in response to delivery of this stimulus.
Thus, midbrain activation might reflect high valuation of success
feedback.
Specifically, compared to the control group without rewards,
we expected activation in the anterior striatum and midbrain to
be higher while monetary rewards were administered and lower
after rewards were withdrawn. This would be in line with both
performance measures of behavioral studies and the imaging
results by Murayama et al. (2010), suggesting a neural crowdingout effect of monetary rewards.
In the group that received verbal reinforcement, we expected
activation to be higher after reinforcement was withdrawn compared to the control group, which would suggest a crowding-in
effect of verbal rewards. We did not have a hypothesis about
differences in activation in the second period, i.e., while verbal reinforcement was administered, since neither CET (Deci
and Ryan, 1985) predicts any differences here, nor were differences in actual performance in this period between the
verbal reinforcement group and the control group reported
(Deci, 1971).
While participants executed the task (i.e., before they received
task feedback), we expected the rLPFC to be engaged (Duncan
et al., 1996; Miller and Cohen, 2001). We hypothesized that activation in this area would reflect the exerted effort, leading to
a higher activation while monetary rewards were administered,
but to a lower activation after reward withdrawal. In contrast,
we expected effort and hence activation to be higher after verbal rewards were withdrawn. We expected neural activation to
be reflected behaviorally in the number of correctly solved items
during a period, providing a behavioral measure of intrinsic
motivation (Deci, 1971; Lepper et al., 1973).
MATERIALS AND METHODS
PARTICIPANTS
Sixty four participants (38 female, range 18–34 years, mean 24.16
years, SD 3.26 years) without any history of neurological or
psychiatric disease participated in the study. Seven additional participants had to be excluded because of excessive head movement.
September 2014 | Volume 8 | Article 303 | 2
Albrecht et al.
All subjects were right-handed according to the Edinburgh
Handedness Scale.
ETHICS STATEMENT
All participants gave written informed consent before the study.
The experimental procedure of the study was approved by the
local ethics committee of the University hospital of Bonn. Data
were handled anonymously.
MATERIALS
In the before-mentioned behavioral studies, mostly interesting
tasks have been used, such as doing puzzles or drawings (Deci,
1971; Lepper et al., 1973). We used picture puzzles in our study; in
each trial, participants were presented with a relatively unknown
modern art picture that was displayed twice. One was the original version, the other one showed 1–4 small deviations from the
original version (see Figure 1 for an example). Participants had to
find these differences and indicate their number. We consider this
an interesting task since many people do this for fun in everyday
life and hence should be intrinsically motivated to do such puzzles. In total, 120 such pictures (40 in each of three periods) were
presented to each participant.
PROCEDURE
Upon arriving, each participant received written instructions
of the first period of the experiment. Subjects were randomly
assigned to one of three groups: a monetary reward group (22
subjects, 15 female), a verbal reward group (23 subjects, 11
female) and a control group (19 subjects, 12 female). Subjects
were unaware of the existence of different groups. Then subjects entered the scanner and, after five training trials, performed
the first period with 40 picture puzzles (being the same for all
groups). Participants knew that there would be two subsequent
periods, but had no further information about their content.
FIGURE 1 | Example trial. Two picture stimuli are presented
simultaneously. The subjects have to find the number of differences
between the stimuli. There are two differences between the original
picture stimulus (top panel, left) and the manipulated version (top panel,
right) in this example, in which a red and a black bar are missing.
www.frontiersin.org
Rewards and intrinsic motivation
Period 1 (baseline)
In the fMRI scanner, each participant faced the first 40 picture puzzles in a random order. In each trial the pictures were
displayed for 8 s, before they were replaced by a fixation cross
(1–2.5 s) until a response could be entered. Afterwards, a short
response feedback was given (2 s), and after a brief delay (3–5 s),
feedback about the correctness of the response was given (4 s).
Figure 1 displays an overview of the course of one trial. All participants did this first period as a baseline condition, i.e., it was
the same for all participants and could later be used to determine differences in the individual baseline intrinsic motivation
concerning the task. Afterwards, participants were asked via intercom whether they needed a break. All participants wanted to go
on with the second period right away.
Period2 (monetary/verbal/control manipulation)
For the control group, the course of a trial did not differ to that
of period 1. The monetary reward group additionally received
the information that now they would get paid C1 for each puzzle they solved correctly. If the response was correct in the verbal
reward group, “Very well done! Way to go!” was displayed during
feedback presentation.
After the second period ended, participants left the fMRI scanner and took a break of 10 to 15 min before going back in. This
was made to minimize possible effects (e.g., exhaustion) that different effort levels (which might have arisen in period 2 due to
treatment differences) might otherwise have had on performance
in period 3.
Period 3
It was stated clearly to the participants of the monetary reward
group that no monetary rewards would be provided anymore. It
might have been more natural to not announce this reward withdrawal and thus not to direct subjects’ attention to it. Yet, not
Feedback for a correct solution is displayed as given in the control group
and in period 1 and 3 in the reward groups (leftmost bottom panel). The
two alternative feedback panels display the feedback given in the monetary
and verbal reward groups in period 2 (middle and rightmost bottom panels,
respectively).
September 2014 | Volume 8 | Article 303 | 3
Albrecht et al.
Rewards and intrinsic motivation
announcing it might have led to false expectations, i.e., to the
expectation that there still might be a performance-based reward
in the end which was just not announced in each single trial anymore. In the verbal reward group, this was no concern, since
verbal rewards did not lead to any tangible consequences, but
rather were to be “consumed” the moment they appeared. Thus,
the verbal reward group simply did not receive any additional
verbal feedback anymore, without further announcement.
Each period lasted about 17 min. Pictures were presented in
random order and counterbalanced between subjects for periods
1 and 3. Pictures in period 2 were presented in random order but
stayed the same across subjects. After period 3, all subjects indicated how much fun they had solving the picture puzzles on a
7-point Likert scale. See Table 1 for an overview of the procedure.
fMRI DATA ACQUISITION
Scanning was performed on a 1.5-Tesla (T) Avanto
Scanner(Siemens), by using a standard 8-channel head coil. Slices
were in axial orientation and covered all of the brain including
the midbrain but not the entire cerebellum. Scan parameters
were as follows: slice thickness, 2 mm; interslice gap, 1 mm; echo
time (TE), 45 ms; repetition time (TR), 2.83 s. The scanning
was performed in 3 sessions with 40 trials each for ∼17 min
each, resulting in an overall scanning time of ∼ 51 min and ∼1,
180 scans. (Data is available upon request. Please contact the
corresponding author at albrecht@psych.rwth-aachen.de).
fMRI DATA ANALYSIS
fMRI data analysis was performed by using Statistical Parametric
Mapping 5 (SPM5, www.fil.ion.ucl.ac.uk/spm/). For preprocessing, functional images were realigned to the first image of the
first session of each time series and again realigned to the mean
image after first realignment. Images were then normalized to the
canonical EPI template used in SPM5, and smoothed with an 8mm Gaussian kernel. After normalization images were resampled
to a voxel size of 3 × 3× 3 mm.
For modeling the blood oxygen-level dependent (BOLD)
response, five regressors were defined for each period: presentation of correctly solved pictures (PC), presentation of incorrectly
solved pictures (PI), response (R) presentation of success feedback (FBS), and presentation of failure feedback (FBF). The
onsets for our regressors can be inferred from Figure 1 like
this: the onset of PC/PI was when the picture puzzle was presented (top panel). This presentation lasted for 8 s, until the
display of the picture puzzles was replaced by a fixation cross.
R was onset when the fixation cross (1–2.5 s) was replaced
by the display of the possible responses and ended after the
given response (indicated by a button press) was displayed for
2 s (panels 3 + 4 from top). After the display of another fixation cross (3–5 s), the feedback (FBS/FBF) was onset and displayed for 4 s (bottom panels). Parameter images for the contrasts for each single condition were generated for each subject and were then subjected to a second-level random effects
analysis.
We conducted second-level whole-brain ANOVA with withinsubject factor period and between-subject factor group. We tested
interaction effects of feedback [always using contrasts of success minus failure feedback (FBS-FBF)] corrected for individual
baseline differences for period and group separately for the two
reward groups., i.e., we conducted an ANOVA for period (2–1
vs. 3–1) and group (monetary reward vs. control) as well as for
period (2–1 vs. 3–1) and group (verbal reward vs. control). We
further tested whether results would change when not controlling
for baseline activation (i.e., when not subtracting activation in
period 1). Additionally, we ran a period (3–2) × group (monetary
reward vs. control) ANOVA.
Analogously, we conducted the same ANOVAs for picture presentation, i.e., while participants saw the picture puzzles and tried
to find the correct number of differences between the two pictures. Only trials of correctly solved picture puzzles (regressor PC)
were included.
Reported p-values are two-sided, if not stated otherwise.
All reported clusters for uncorrected comparisons consist of a
minimum of 10 voxels.
We conducted small volume corrections and extracted parameter estimates for our regions of interest from a 12 mm sphere centered on the peak voxel of the anterior striatum (21 20 −2, −21 20
1) and midbrain (−9 −7 −11) activation reported by Murayama
et al. (2010), using Marsbar (www.marsbar.sourceforge.net/). We
further conducted the same analyses for the rLPFC [39 41 40
(Murayama et al., 2010)] for picture presentation.
RESULTS
BEHAVIORAL RESULTS
Figure 2 presents an overview of participants’ performance (correctly solved items) over all periods. An ANOVA with the factors
group (monetary, verbal, control) and period (1–3) yielded a significant main effect of period [F(2, 122) = 6.732, p = 0.002]. The
effect of group [F(2, 61) = 1.751, p = 0.184] and the interaction
effect of the two factors [F(4, 122) = 1.004, p = 0.408] were not
significant. Post-hoc analyses (Sidak-corrected for multiple comparisons) revealed a significant increase of performance from
period 1 to 2, irrespective of group (p = 0.003). This suggests
general training effects irrespective of our treatment manipulation. Alternatively, since only the presentation of pictures in
periods 1 and 3 was counterbalanced between subjects, it is
Table 1 | Feedback given in the different periods to the different groups of participants.
Monetary reward group
Verbal reward group
Control group
Period 1
Correct vs. incorrect
Correct vs. incorrect
Correct vs. incorrect
Period 2
Correct “1 Euro” vs. Incorrect “0 Euro”
Correct “Very well done, way to go!” vs. Incorrect
Correct vs. incorrect
Period 3
Correct vs. incorrect
Correct vs. incorrect
Correct vs. incorrect
Frontiers in Neuroscience | Decision Neuroscience
September 2014 | Volume 8 | Article 303 | 4
Albrecht et al.
FIGURE 2 | Performance increased from period 1 to period 2 in all
groups, but from period 1 to 3 in the verbal reward group only.
possible that the picture puzzles in period 2 were slightly easier
to solve than those in the other two periods.
Only in the verbal reward group did performance increase further in period 3 (p = 0.040), whereas in the other two groups
performance did not increase significantly from period 1 to 3
(monetary: p = 0.862; control: p = 0.968). However, a univariate ANOVA with group as independent variable and performance
increase as dependent variable yielded that this increase was not
significantly stronger in the verbal reward group than in the other
two groups (verbal vs. monetary: p = 0.500; verbal vs. control:
p = 0.414).
After the experiment, subjects indicated how much fun they
had solving the picture puzzles on a 7-point Likert scale. On average, subjects in all three groups stated that it was fun (total: 4.92,
monetary: 5.36, verbal: 4.52, control: 4.89). A univariate ANOVA
yielded no significant differences in fun ratings between groups
[F(2, 61) = 1.784, p = 0.177].
A systematic summary of statistics for all post-hoc main
and interaction effects can be found in Tables A1a,b in the
supplementary material.
Rewards and intrinsic motivation
comparing the monetary reward group with the control group
in periods 2 and 3: in line with Murayama et al. (2010), we found
a higher activation in the anterior striatum and midbrain (whole
brain uncorrected, p < 0.001; small volume corrected, pFWE <
0.05) while monetary rewards were administered. Activation differences in these areas stayed significant when baseline activation
of period 1 was subtracted (Figure 3, cf. supplementary material, Table A3). In contrast to Murayama et al. (2010), we did
not find any brain area to be activated more strongly in the control compared to the monetary reward group after rewards were
withdrawn in period 3, even at a lower threshold (uncorrected,
p < 0.005). A group × period ANOVA, testing the interaction
effect of group and activation differences between periods 3 and
2, also yielded no significant activation differences (uncorrected,
p < 0.001; small volume corrected, pFWE < 0.05). Tables A3, A5
in the supplementary material give an overview of results for our
regions of interest and for all regions, respectively.
Task feedback: the verbal reward group
The ANOVA comparing success—failure feedback in the verbal
reward and control groups in period 3 yielded higher activation
in our target areas anterior striatum and midbrain (whole brain
uncorrected, p < 0.001; small volume corrected, pFWE < 0.05) in
the group with verbal rewards after reward withdrawal. Activation
differences in these areas were also significant when baseline activation of period 1 was subtracted (Figure 4, cf. supplementary
material, Table A3). Tables A3, A5 in the supplementary material
give an overview of results for our regions of interest and for all
regions, respectively.
Self-reported ratings of intrinsic motivation (fun) after period
3 correlated significantly with neural activation (success minus
failure feedback) in period 3 only in the verbal reward group
(rho = 0.496, p = 0.016). The correlation did not reach significance when baseline activation from period 1 was subtracted
(rho = 0.294, p = 0.173). See Table A7 in the supplementary
material for statistical values for the other brain areas and in the
other two groups.
IMAGING RESULTS
Baseline period 1
Picture presentation: the monetary reward group
We ran an ANOVA contrasting success and failure feedback in
period 1. Since in period 1, all groups received the same feedback
(success vs. failure) without any monetary or verbal rewards, we
analyzed the data across groups.
In line with previous literature (Daniel and Pollmann, 2010),
we find higher activation in success compared to failure feedback in the ventral striatum and the medial orbitofrontal cortex
(pFWE < 0.05; for coordinates, statistical values and an overview
of all areas with activation differences above threshold, see Table
A2 in the supplementary material).
In our regions of interest, we find a significant activation difference after small volume correction in the midbrain
(pFWE < 0.05). The activation difference does not reach
significance in the left anterior striatum (pFWE = 0.063).
We conducted the same ANOVA as above for picture presentation, comparing activation in the monetary reward and control
group. None of the ANOVA yielded a significant effect in the
rLPFC or elsewhere (whole brain uncorrected, p < 0.001; small
volume corrected; pFWE < 0.05). The interaction contrast of
period 3 and period 2 for the control and monetary reward group
also showed no significant activation (whole brain uncorrected,
p < 0.001; small volume corrected; pFWE < 0.05). The parameter estimates suggest that, if there was an effect in this area at
all, it runs against our hypotheses: whereas activation in period
2 was lower in the monetary reward group than in the control
group, in period 3 it seemed to be higher in the monetary reward
group (Figure 5B). Indeed, activation in period 3 differed significantly between these two groups, also if baseline activation
was subtracted (small volume corrected contrast, pFWE < 0.05;
Figure 5A, cf. supplementary material, Table A4). However, in
period 2 the effect was only significant when baseline activation
was not taken into account (whole brain uncorrected, p < 0.001;
Task feedback: the monetary reward group
To test our hypotheses, we ran ANOVA contrasting success and
failure feedback between the different groups. We start with
www.frontiersin.org
September 2014 | Volume 8 | Article 303 | 5
Albrecht et al.
FIGURE 3 | (A) Activation for success—failure feedback was significantly
higher in the right anterior striatum (left panel) and midbrain (right panel) in
the monetary reward group compared to the control group in period 2 (whole
brain uncorrected, p < 0.001, only clusters with a minimum of 10 activated
small volume corrected, pFWE < 0.05). Further, the interaction
of period 3 with period 2 yielded a significant effect (small volume corrected; pFWE < 0.05). Tables A4, A6 in the supplementary
material give an overview of results for our regions of interest and
for all regions, respectively.
Rewards and intrinsic motivation
voxels are shown; small volume corrected, pFWE < 0.05). Activation clusters
without baseline correction are shown in green, clusters with baseline
correction are shown in red, activation overlaps are shown in yellow. (B)
Parameter estimates are displayed for illustration.
of Murayama et al. (2010) did not yield a significant activation
difference. Tables A4, A6 in the supplementary material give an
overview of results for our regions of interest and for all regions,
respectively.
DISCUSSION
Picture presentation: the verbal reward group
The ANOVA comparing the verbal reward and control groups
in period 3 during picture presentation yielded higher activation
in the rLPFC (whole brain uncorrected, p < 0.001) in the group
with verbal rewards after reward withdrawal. When we subtracted
baseline activation of period 1, we found the activation difference
in the rLPFC to be slightly more posterior (Figure 6, cf. supplementary material, Table A4). Further, a small volume correction
on a 12 mm sphere centered on the peak voxel from the study
Frontiers in Neuroscience | Decision Neuroscience
In the present study, we wanted to investigate the neural correlates of crowding-out and crowding-in of intrinsic motivation. To
this end, our subjects participated in a series of picture puzzles
for three periods receiving feedback about successes and failures in solving the puzzles. In the second period, additionally
to success and failure feedback, either monetary rewards (monetary reward group), verbal reinforcement (verbal reward group)
or no rewards/reinforcement (control group) were administered.
We found that the administration and withdrawal of monetary
September 2014 | Volume 8 | Article 303 | 6
Albrecht et al.
FIGURE 4 | (A) Activation for success—failure feedback was significantly
higher in the right anterior striatum (left panel) and midbrain (right panel) in
the verbal reward group compared to the control group in period 3 (whole
brain uncorrected, p < 0.001, only clusters with a minimum of 10 activated
and verbal rewards influenced brain activation in our regions of
interest.
In order to control for baseline brain activation, we subtracted
the activation of period 1, in which all three groups solved picture
puzzles and received feedback concerning their success in the
task. Since we wanted to compare our results to the results of
Murayama et al. (2010), who did not run such a baseline treatment, we additionally analyzed our data without controlling for
baseline activation. Except for activation in the rLPFC, we could
mostly replicate our own results by finding similar activation
differences between groups irrespective of baseline activation. A
possible explanation for the baseline differences in rLPFC activation could be that cognitive engagement in a task strongly differs
between individuals in general, which could for example be due
to initial individual differences in intrinsic motivation. A baseline
period to control for possible initial variance thus is helpful to
rule out such effects.
www.frontiersin.org
Rewards and intrinsic motivation
voxels are shown; small volume corrected, pFWE < 0.05). Activation clusters
without baseline correction are shown in green, clusters with baseline
correction are shown in red, activation overlaps are shown in yellow. (B)
Parameter estimates are displayed for illustration.
NO CROWDING-OUT EFFECT OF MONETARY REWARDS
With the present study, we could replicate findings from
Murayama et al. (2010) by showing that activation in the anterior striatum and midbrain was higher for success feedback when
monetary rewards were involved. This supports the assumption
that these areas are indeed involved in subjective valuation and
is in line with findings by previous studies that link motivation
to monetary rewards and show that these brain areas are more
highly activated when additionally to success feedback monetary rewards are administered (Engelmann and Pessoa, 2007;
Engelmann et al., 2009; Daniel and Pollmann, 2010; Pessoa and
Engelmann, 2010). However, we could not replicate the finding
that activation in these areas (or any other brain areas) decreased
after monetary rewards were withdrawn. Hence, our data cannot support the crowding-out effect due to monetary rewards.
Further, we even found lower activation for the control compared
to the monetary reward group in the rLPFC while monetary
September 2014 | Volume 8 | Article 303 | 7
Albrecht et al.
FIGURE 5 | (A) Activation for picture presentation was significantly higher
in the right lateral prefrontal cortex in the monetary reward group compared
to the control group in period 3 (whole brain uncorrected, p < 0.001, only
clusters with a minimum of 10 activated voxels are shown; small volume
corrected, pFWE < 0.05). Activation clusters without baseline correction are
shown in green, clusters with baseline correction are shown in red,
activation overlaps are shown in yellow. (B) Parameter estimates are
displayed for illustration.
rewards were administered in period 2, and we found higher activation for the monetary reward compared to the control group
in the rLFPC during task presentation in period 3 (i.e., after
rewards were withdrawn). We expected this activation to reflect
cognitive engagement in the task and hence hypothesized activation to be high when monetary rewards were administered
and, due to crowding-out, lower after reward withdrawal. Yet
our results indicate that, if at all, motivation was decreased while
rewards were administered and increased after their withdrawal. It
is difficult to explain the decrease during reward administration.
However, the activation we found here was only present when we
did not subtract baseline activation, which questions the validity
of this result. Although, the parameter estimates extracted from
the rLPFC were mostly below the baseline, suggesting a rather
weak activation during picture presentation in general. A possible explanation for the finding that activation in the rLPFC was
higher in the monetary reward group after reward withdrawal
is that participants in the reward group were happy about and
grateful for the additional money they just earned and reacted
to this by reciprocating and strongly engaging in the task even
after performance-based rewards were not paid anymore. We can
only speculate about long-term effects, though; it might decline
after some time, even leading to a lower activation than observed
in the control group. Hence, the long-term effects of withdrawn
monetary rewards are still to be investigated in future research.
Frontiers in Neuroscience | Decision Neuroscience
Rewards and intrinsic motivation
FIGURE 6 | (A) Activation for picture presentation was significantly higher
in the right lateral prefrontal cortex in the verbal reward group compared to
the control group in period 3 (whole brain uncorrected, p < 0.001, only
clusters with a minimum of 10 activated voxels are shown). Activation
clusters without baseline correction are shown in green, clusters with
baseline correction are shown in red, activation overlaps are shown in
yellow. (B) Parameter estimates are displayed for illustration.
Although we find activation differences in the same brain
areas as Murayama et al. (2010), who can support their results
with differences in behavioral engagement, it is not clear whether
monetary rewards indeed affected intrinsic motivation in our
paradigm. We did not find behavioral differences and baseline
brain activation in period 1 is not very strong. On the other
hand, subjects’ post-experimental fun ratings indicate that subjects indeed had fun solving the picture puzzles, as the mean
rating was 4.92 (and even 5.36 for the monetary group alone) on
a Likert scale ranging from 1 to 7. Because of these contradicting
findings, it remains unclear whether in our task intrinsic motivation was high enough to be negatively affected by monetary
rewards.
THE CROWDING-IN EFFECT OF VERBAL REWARDS
We found an effect of verbal rewards on brain activation: activation in the anterior striatum and midbrain was higher after
the administration of verbal rewards than in the control group.
Both striatum and midbrain were reported to be involved in
the subjective valuation of situations (Schultz et al., 1997; Bayer
and Glimcher, 2005; Seymour and McClure, 2008); accordingly these activation differences suggest that individuals have
a higher subjective value for succeeding in a task after verbal
reinforcement. The activation in the striatum, which was further reported to be involved in evaluating one’s influence on an
September 2014 | Volume 8 | Article 303 | 8
Albrecht et al.
outcome of a situation (Tricomi et al., 2004, 2006), might reflect
a higher perceived self-determination—a key component of the
crowding-in effect (Deci and Ryan, 1985). Accordingly, verbal
reinforcement might increase subjective valuation and perceived
self-determination of a task. This last inference is supported also
by a significant correlation between striatal activation in period 3
and self-reported fun.
Further, only in this group did performance increase significantly over time, which supports that at least task engagement
grew. However, this increase was not significantly larger than
that in the control and monetary reward groups. Thus, the inferences from neural activation we made in the above paragraph are
only weakly supported by behavioral data and have to be considered with care. Also, although activation in the left striatum
in period 3 correlated significantly with self-reported fun ratings,
this effect was not robust to subtracting baseline activation from
period 1. Taken together with the in general small baseline activation in period 1 and the non-differing post-experimental fun
ratings, it remains unclear whether task engagement and accordingly intrinsic motivation were actually influenced by verbal
rewards.
The neural evidence for higher task engagement of the verbal
reward group during picture presentation is unclear, too; activation in the right rLPFC was higher in the verbal reward compared
to the control group in period 3, but the exact location of this
activation differences was not identical with the region identified
by Murayama et al. (2010). The task used by Murayama and colleagues was different from ours (participants had to press a button
to stop a stop watch after 5.00 s as exactly as possible) and brain
activation was measured not while participants executed the task
but while they were informed that this was the task they were
going to do next (as compared to another more boring task that
was intermixed in the experiment). In the present study, rLPFC
activation was measured while subjects were working on a task.
Likely, these differences between the paradigms could have led to
a difference in the location of LPFC activation between their and
our task.
CONCLUSION
Taken together, we can draw the following conclusions: (1)
While administered, monetary rewards affected brain activation
in response to feedback in the anterior striatum and midbrain. (2)
After their withdrawal, verbal rewards affected brain activation in
response to feedback in the anterior striatum and midbrain. (3)
After their withdrawal, verbal rewards affected rLPFC activation
while subjects worked on a picture puzzle task. Since we found
no strong differences in behavioral task engagement, it is difficult to infer that these activation differences are indeed linked to
intrinsic motivation or even task engagement. Possibly, intrinsic
motivation in our task was not strong enough to be crowdedout by monetary rewards. The slight increase in correctly solved
picture puzzles and the increased activation in our regions of
interest in period 3 in the verbal reward group let us speculate that
(low) intrinsic motivation was increased by verbal reinforcement.
However, these allusions are not very strong and future research
is essential to clarify the role of verbal reinforcement in intrinsic
motivation.
www.frontiersin.org
Rewards and intrinsic motivation
ACKNOWLEDGMENTS
We are grateful for comments from Jan Engelmann, Hannah
Schildberg-Hoerisch and Matthias Wibral. We further thank Anke
Becker, Peter Trautner, Benedikt Vogt, Jana Willrodt, and Ulf
Zoelitz for their assistance.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: http://www.frontiersin.org/journal/10.3389/fnins.2014.
00303/abstract
REFERENCES
Aron, A., Shohamy, D., Clark, J., Myers, C., Gluck, M., and Poldrack, R. (2004).
Human midbrain sensitivity to cognitive feedback and uncertainty during classification learning. J. Neurophysiol. 92, 1144–1152. doi: 10.1152/jn.01209.2003
Bayer, H., and Glimcher, P. (2005). Midbrain dopamine neurons encode
a quantitative reward prediction error signal. Neuron 47, 129–141. doi:
10.1016/j.neuron.2005.05.020
Bunge, S. (2004). How we use rules to select actions: a review of evidence
from cognitive neuroscience. Cogn. Affect. Behav. Neurosci. 4, 564–579. doi:
10.3758/CABN.4.4.564
Camerer, C., and Hogarth, R. (1999). The effects of financial incentives in experiments: a review and capital-labor-production framework. J. Risk Uncertain. 19,
7–42. doi: 10.1023/A:1007850605129
D’Ardenne, K., Allard, S., Nystrom, L., and Cohen, J. (2008). BOLD responses
reflecting dopaminergic signals in the human ventral tegmental area. Science
319, 1264–1267. doi: 10.1126/science.1150605
Daniel, R., and Pollmann, S. (2010). Comparing the neural basis of monetary reward and cognitive feedback during information-integration category
learning. J. Neurosci. 30, 47–55. doi: 10.1523/JNEUROSCI.2205-09.2010
Dayan, P., and Balleine, B. (2002). Reward, motivation, and reinforcement learning.
Neuron 36, 285–298. doi: 10.1016/S0896-6273(02)00963-7
Deci, E. (1971). Effects of externally mediated rewards on intrinsic motivation.
J. Pers. Soc. Psychol. 18, 105–115. doi: 10.1037/h0030644
Deci, E., Koestner, R., and Ryan, R. (1999). A meta-analytic review of experiments
examining the effects of extrinsic rewards on intrinsic motivation. Psychol. Bull.
125, 627–668. doi: 10.1037/0033-2909.125.6.627
Deci, E., and Ryan, R. (1985). Intrinsic Motivation and Self-Determination in
Human Behavior. New York, NY: Plenum Press.
Delgado, M. (2007). Reward-related responses in the human striatum. Ann. N. Y.
Acad. Sci. 1104, 70–88. doi: 10.1196/annals.1390.002
Delgado, M., Nystrom, L., Fissell, C., Noll, D., and Fiez, J. (2000). Tracking
the hemodynamic responses to reward and punishment in the striatum.
J. Neurophysiol. 84, 3072–3077. doi: 10.1006/cogp.1996.0008
Duncan, J., Emslie, H., Williams, P., Johnson, R., and Freer, C. (1996). Intelligence
and the frontal lobe: the organization of goal-directed behavior. Cogn. Psychol.
30, 257–303. doi: 10.3389/neuro.09.004.2009
Engelmann, J., Damaraju, E., Padmala, S., and Pessoa, L. (2009). Combined effects
of attention and motivation on visual task performance: transient and sustained
motivational effects. Front. Hum. Neurosci. 3:4. doi: 10.3389/neuro.09.004.2009
Engelmann, J., and Pessoa, L. (2007). Motivation sharpens exogenous spatial
attention. Emotion 7, 668–674. doi: 10.1037/1528-3542.7.3.668
Haber, S., Fudge, J., and McFarland, N. (2000). Striatonigrostriatal pathways in
primates form an ascending spiral from the shell to the dorsolateral striatum.
J. Neurosci. 20, 2369–2382.
Haber, S., and Knutson, B. (2009). The reward circuit: linking primate
anatomy and human imaging. Neuropsychopharmacology 35, 4–26. doi:
10.1038/npp.2009.129
Irlenbusch, B., and Sliwka, D. (2005). Incentives, Decision Frames, and Motivation
Crowding Out-An Experimental Investigation. Discussion Paper No. 1758. Bonn:
IZA.
Izuma, K., Saito, D., and Sadato, N. (2008). Processing of social and
monetary rewards in the human striatum. Neuron 58, 284–294. doi:
10.1016/j.neuron.2008.03.020
Jimura, K., Locke, H., and Braver, T. (2010). Prefrontal cortex mediation of cognitive enhancement in rewarding motivational contexts. Proc. Natl. Acad. Sci.
U.S.A. 107, 8871–8876. doi: 10.1073/pnas.1002007107
September 2014 | Volume 8 | Article 303 | 9
Albrecht et al.
Kahnt, T., Park, S., Cohen, M., Beck, A., Heinz, A., and Wrase, J. (2009).
Dorsal striatal–midbrain connectivity in humans predicts how reinforcements are used to guide decisions. J. Cogn. Neurosci. 21, 1332–1345. doi:
10.1162/jocn.2009.21092
Leon, M., and Shadlen, M. (1999). Effect of expected reward magnitude on the
response of neurons in the dorsolateral prefrontal cortex of the macaque.
Neuron 24, 415–425. doi: 10.1016/S0896-6273(00)80854-5
Lepper, M., Greene, D., and Nisbett, R. (1973). Undermining children’s intrinsic
interest with extrinsic reward: a test of the “overjustification” hypothesis. J. Pers.
Soc. Psychol. 28, 129–137. doi: 10.1037/h0035519
Mellström, C., and Johannesson, M. (2008). Crowding out in blood donation: was
Titmuss right? J. Eur. Econ. Assoc. 6, 845–863. doi: 10.1162/JEEA.2008.6.4.845
Miller, E., and Cohen, J. (2001). An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24, 167–202. doi: 10.1146/annurev.neuro.
24.1.167
Murayama, K., Matsumoto, M., Izuma, K., and Matsumoto, K. (2010). Neural
basis of the undermining effect of monetary reward on intrinsic motivation. Proc. Natl. Acad. Sci. U.S.A. 107, 20911–20916. doi: 10.1073/pnas.10133
05107
O’Doherty, J. P., Buchanan, T., Seymour, B., and Dolan, R. (2006). Predictive
neural coding of reward preference involves dissociable responses in
human ventral midbrain and ventral striatum. Neuron 49, 157–166. doi:
10.1016/j.neuron.2005.11.014
Pessoa, L., and Engelmann, J. (2010). Embedding reward signals into perception
and cognition. Front. Neurosci. 4:17. doi: 10.3389/fnins.2010.00017
Ryan, R., Mims, V., and Koestner, R. (1983). Relation of reward contingency
and interpersonal context to intrinsic motivation: a review and test using
cognitive evaluation theory. J. Pers. Soc. Psychol. 45, 736–750. doi: 10.1037/00223514.45.4.736
Schultz, W., Dayan, P., and Montague, P. (1997). A neural substrate of prediction
and reward. Science 275, 1593–1599. doi: 10.1126/science.275.5306.1593
Seymour, B., and McClure, S. (2008). Anchors, scales and the relative coding of value in the brain. Curr. Opin. Neurobiol. 18, 173–178. doi:
10.1016/j.conb.2008.07.010
Shiflett, M., and Balleine, B. (2010). At the limbic-motor interface: disconnection
of Basolateral amygdala from nucleus accumbens core and shell reveals dissociable components of incentive motivation. Eur. J. Neurosci. 32, 1735–1743. doi:
10.1111/j.1460-9568.2010.07439.x
Frontiers in Neuroscience | Decision Neuroscience
Rewards and intrinsic motivation
Shohamy, D. (2011). Learning and motivation in the human striatum. Curr. Opin.
Neurobiol. 21, 408–414. doi: 10.1016/j.conb.2011.05.009
Shohamy, D., Myers, C., Grossman, S., Sage, J., Gluck, M., and Poldrack, R.
(2004). Cortico-striatal contributions to feedback-based learning: converging data from neuroimaging and neuropsychology. Brain 127, 851–859. doi:
10.1093/brain/awh100
Tricomi, E., Delgado, M., and Fiez, J. (2004). Modulation of caudate activity by
action contingency. Neuron 41, 281–292. doi: 10.1016/S0896-6273(03)00848-1
Tricomi, E., Delgado, M., McCandliss, B., McClelland, J., and Fiez, J. (2006).
Performance feedback drives caudate activation in a phonological learning task.
J. Cogn. Neurosci. 18, 1029–1043. doi: 10.1162/jocn.2006.18.6.1029
Tricomi, E., and Fiez, J. (2008). Feedback signals in the caudate reflect goal
achievement on a declarative memory task. Neuroimage 41, 1154–1167. doi:
10.1016/j.neuroimage.2008.02.066
Wager, T., and Smith, E. (2003). Neuroimaging studies of working memory. Cogn.
Affect. Behav. Neurosci. 3, 255–274. doi: 10.3758/CABN.3.4.255
Wassum, K., Ostlund, S., Balleine, B., and Maidment, N. (2011). Differential
dependence of Pavlovian incentive motivation and instrumental incentive
learning processes on dopamine signaling. Learn. Mem. 18, 475–483. doi:
10.1101/lm.2229311
Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Received: 20 May 2014; accepted: 04 September 2014; published online: 18 September
2014.
Citation: Albrecht K, Abeler J, Weber B and Falk A (2014) The brain correlates of the
effects of monetary and verbal rewards on intrinsic motivation. Front. Neurosci. 8:303.
doi: 10.3389/fnins.2014.00303
This article was submitted to Decision Neuroscience, a section of the journal Frontiers
in Neuroscience.
Copyright © 2014 Albrecht, Abeler, Weber and Falk. This is an open-access article
distributed under the terms of the Creative Commons Attribution License (CC BY).
The use, distribution or reproduction in other forums is permitted, provided the
original author(s) or licensor are credited and that the original publication in this
journal is cited, in accordance with accepted academic practice. No use, distribution or
reproduction is permitted which does not comply with these terms.
September 2014 | Volume 8 | Article 303 | 10