Different gain/loss sensitivity and social adaptation ability in gifted adolescents during a public goods game.

Abstract

Gifted adolescents are considered to have high IQs with advanced mathematical and logical performances, but are often thought to suffer from social isolation or emotional mal-adaptation to the social group. The underlying mechanisms that cause stereotypic portrayals of gifted adolescents are not well known. We aimed to investigate behavioral performance of gifted adolescents during social decision-making tasks to assess their affective and social/non-social cognitive abilities. We examined cooperation behaviors of 22 gifted and 26 average adolescents during an iterative binary public goods (PG) game, a multi-player social interaction game, and analyzed strategic decision processes that include cooperation and free-riding. We found that the gifted adolescents were more cooperative than average adolescents. Particularly, comparing the strategies for the PG game between the two groups, gifted adolescents were less sensitive to loss, yet were more sensitive to gain. Additionally, the behavioral characteristics of average adolescents, such as low trust of the group and herding behavior, were not found in gifted adolescents. These results imply that gifted adolescents have a high cognitive ability but a low ability to process affective information or to adapt in social groups compared with average adolescents. We conclude that gain/loss sensitivity and the ability to adapt in social groups develop to different degrees in average and gifted adolescents.

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Different Gain/Loss Sensitivity and Social Adaptation
Ability in Gifted Adolescents during a Public Goods
Game
Dongil Chung1, Kyongsik Yun1, Jin Ho Kim2, Bosun Jang3, Jaeseung Jeong1*
1Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, 2Division of Electrical Engineering,
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea, 3Department of Physics, Korea Advanced Institute of Science and Technology
(KAIST), Daejeon, Republic of Korea
Abstract
Gifted adolescents are considered to have high IQs with advanced mathematical and logical performances, but are often
thought to suffer from social isolation or emotional mal-adaptation to the social group. The underlying mechanisms that
cause stereotypic portrayals of gifted adolescents are not well known. We aimed to investigate behavioral performance of
gifted adolescents during social decision-making tasks to assess their affective and social/non-social cognitive abilities. We
examined cooperation behaviors of 22 gifted and 26 average adolescents during an iterative binary public goods (PG)
game, a multi-player social interaction game, and analyzed strategic decision processes that include cooperation and free-
riding. We found that the gifted adolescents were more cooperative than average adolescents. Particularly, comparing the
strategies for the PG game between the two groups, gifted adolescents were less sensitive to loss, yet were more sensitive
to gain. Additionally, the behavioral characteristics of average adolescents, such as low trust of the group and herding
behavior, were not found in gifted adolescents. These results imply that gifted adolescents have a high cognitive ability but
a low ability to process affective information or to adapt in social groups compared with average adolescents. We conclude
that gain/loss sensitivity and the ability to adapt in social groups develop to different degrees in average and gifted
adolescents.
Citation: Chung D, Yun K, Kim JH, Jang B, Jeong J (2011) Different Gain/Loss Sensitivity and Social Adaptation Ability in Gifted Adolescents during a Public Goods
Game. PLoS ONE 6(2): e17044. doi:10.1371/journal.pone.0017044
Editor: Matjaz Perc, University of Maribor, Slovenia
Received October 31, 2010; Accepted January 14, 2011; Published February 16, 2011
Copyright: ? 2011 Chung et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the CHUNG Moon Soul Research Center for Bio Information and Bio Electronics (CMSC) in KAIST and the Korea Science and
Engineering Foundation (KOSEF) grant funded by the Korean government (MOST) (No. R01-2007-000-21094-0 and No. M10644000028-06N4400-02810). The
funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: jsjeong@kaist.ac.kr
Introduction
Gifted adolescents are generally considered to have higher IQs
and better mathematical and logical performances than average
age-matched individuals. Intellectually gifted adolescents show
superior performance (e.g., better memory, faster and more
efficient processing) on various cognitive tasks, including visuo-
spatial tasks (e.g., 3-dimensional mental rotation) that require
creativity and manipulation of mental images [1,2], problem
solving [3,4], memory processing [5,6], and global-local processing
[7]. In contrast to their advanced performances in cognitive tasks,
however, they are often thought to have low sensitivity to social
cues within their age group, or to be socially isolated [8]. Although
the stereotyped view of maladjustment is controversial in other
studies [9–11], little is known about the reasons why gifted
adolescents are often thought to show maladaptive behaviors in
their group, especially in environments in which social interactions
are required.
Social decision-making requires complex information process-
ing, including the integration of cognitive and affective informa-
tion and the prediction of others’ future behavior [12]. Thus,
matured cognitive and affective processing are essential for
strategic decision-making in order to maximize profit he or she
can earn from the group. Gifted adolescents are often judged to be
emotionally maladapted to social groups [13,14]. Thus, gifted
adolescents can be expected to show superior performance in
cognitive tasks, but poor performance in integrative tasks that
include affective information. Investigating choices to cooperate or
not with a participating group is an apt tool for evaluating the
factors, including self-maximizing (to maximize one’s monetary
gain) and emotional reactions (e.g., avoiding the specific option
more than other option irrationally such as loss aversion effect),
that motivate a participant in strategic decision-making. In
reacting to information provided during such a task, participants
who depend less on emotional information processing should show
more (monetary) gain-sensitive behavior than (monetary) loss-
sensitive behavior (i.e., projection of emotional reaction). Since a
participant should weigh affective and cognitive motivations
before making decisions, critical decision differences can be
expected between gifted and average adolescents. However,
potential behavioral and neuro-developmental differences between
gifted and average adolescents during social interactions have
rarely been investigated.
The aim of the current study was first to investigate behavioral
strategies for cooperation and free-riding in mathematically gifted
adolescents with high IQs during a public goods (PG) game, a
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multiple-player social interaction game; and second, to analyze
behaviors to discern the major causes of behavioral differences
between gifted and average adolescents if exists. We hypothesized
that gifted adolescents would show gain-sensitive strategies, that
maximize their mean total earnings with the superior mathemat-
ical abilities that help them to react adaptively to any given
environment. Gifted adolescents were also expected to be less
affected by emotional factors (loss-insensitive) than average
adolescents. These different characteristics of strategic and social
decision-making might cause maladaptations to social groups in
daily life.
A PG game is a useful tool for assessing social interactions,
particularly through cooperative and free-riding behaviors.
Participants are given a certain amount of money at the beginning
of the game and should decide whether to invest their money in
the public account or in a private account (i.e., to keep it). Public
money is generally doubled or tripled and is shared equally
between players regardless of their cooperation. According to
game theory, the dominant strategy to earn the most is to free-ride,
in which a player selfishly keeps his or her own money and also
earns a group share, while investment of the entire money from all
participants in the public account generates the Pareto-efficient
outcome – sharing the most efficient and fair amount of payoff
between the assigned group members [15–18]. However, in
empirical studies, participants showed around 20–40% coopera-
tion (i.e., invested in the public account) in one-shot PG games or
in the first round of repeated PG games [15–22]. Thus, emergence
of non-kin cooperation has been broadly investigated on the point
of view of evolutionary game theory and suggested that
reciprocity, group selection [23,24], and coevolutionary rule
(e.g., environmental evolution) [25] are the possible mechanisms
for the evolution of cooperation. Furthermore, it has been shown
that cooperative behaviors are promoted by social diversity [26]
and institutional designs that implement punishment or reward
[27–31]. Besides modulating the incentives, however, according to
the strategic decisions of the participants, initial cooperation
quickly diminished and converged to nearly 0% cooperation in
later rounds of repeated PG games [15–18,32].
We used an iterative binary PG game, a well-controlled design
for evaluating the behavioral performance of the gifted and
average adolescents during strategic social decision-making. First,
a binary design of a PG game, based on Dawes et al. [19], was
chosen for simplicity. This game provides only two options for
decisions, i.e., cooperate or free-ride, and two alternative results,
i.e., success and failure to earn a bonus. An amount of twice the
promissory note was provided if and only if more than 3 of 5
participants cooperated. Second, three differentiated conditions
were applied in order to distinguish the two major incentives to
free-ride, which are ‘fear of losing money’ and ‘greed for earning
more money than others’ [19]. The first condition (condition I)
included the standard social dilemma problem in the game. Two
other conditions (condition II and III) had the two ‘half social
dilemma problems’ [19], including each of the incentive to free-
ride, respectively. We analyzed the possible behavioral differences
that were induced by each of the modified incentives and
compared gifted with average adolescents in their strategic social
decision-making abilities. Third, we used a 10-round PG game.
Iterative decisions in response to the given information and
individual gain or loss results reflect individual risk-aversive or
risk-taking characteristics.Our
differences in the decision-making processes of gifted and average
adolescents that account for social maladaptation and isolation
problems.
resultsuncover underlying
Materials and Methods
Ethics Statement
Before participating in the experiment, all recruited students
and their teachers were informed about all procedures of the
experiment and written informed consents were obtained. All
protocols utilized in the current study were reviewed and approved
by the KAIST institutional review board (KH2008-01).
Subjects
Twenty four gifted adolescents (age range: 13–15 years,
M:F=18:6) and forty average adolescents (age range: 13–14
years, M:F=24:16) were initially recruited for the current study.
For the gifted adolescent group, students from a private institute
for special education for the gifted were recruited. In order to
obtain a large pool of the gifted, the gifted adolescents were
recruited independently from the average, through local private
academy. All the gifted participants had received awards from
local or national competition which qualifying their advanced
mathematical and logical performances. A teacher additionally
participated in the game to make each group consist of five non-
overlapping players, but data from the teacher was not included in
the data analysis. After recruiting, we tried to make groups of
minimal acquaintance by asking who knows whom and avoiding
them to be in the same group. For the average group, we recruited
first-year middle-school students from the Gapcheon middle
school, Daejeon, South Korea, with the assistance of teachers in
the school. As a control group to be compared with gifted
adolescents, students were randomly recruited regardless of their
academic records. To minimize the influence of participants’
acquaintance with each other, we took average applications from 4
students each from 10 different classes.
All participants in both groups took an IQ test, the Wechsler
Intelligence Scale for Children, Third Edition [33], and a creativity
test, the Khatena-Torrance Creative Perception Inventory (KTCPI
[34]), prior to other procedures. IQ was measured to divide the two
groups with the objective threshold and to rule out the subjects who
have incongruent traits (i.e., adolescent from the gifted population
who has low IQ, or from the average population who has high IQ).
The threshold for the IQ separation was set to 130. Creativity is
another measure that often refers to criteria of the giftedness [35].
Since the correlation between creativity and intelligence is
controversial (negligible vs. modestly related in part) [36–38], the
current study measured KTCPI score and focused on effects of the
sub-components which showed positive correlation with IQ.
We excluded 3 gifted adolescents who had IQs lower than 130,
and 14 average adolescents who had IQs equal to or higher than
130, from analyses to make a further distinction between the gifted
and average groups. The PG game provided a well-preserved
anonymity for individual decisions, and the only information given
to the players was the result of the group in each round (i.e.,
success or failure to earn a bonus) and the supportiveness of the
group (i.e., the number of cooperators in the preceding trial).
Hence, although the excluded students participated in the game,
we assumed that each participant made his or her decisions
independently and that only the given information affected their
decisions. According to the exclusion criteria, we finally analyzed
data from 26 average adolescents (age: 13.9660.20 years, age
range: 13–14 years, M/F: 15/11) and 22 gifted adolescents (age:
14.0560.49 years, age range: 13–15 years, M/F: 16/6).
Experimental Procedures
The experimental procedures were carried out independently
for the gifted and the average groups. We utilized the binary PG
Cooperation Behaviors of Gifted Adolescents
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game based on Dawes et al. [19], which provides only two choices
for the participant: to cooperate, to invest all money in the public;
or to free-ride, to keep all of the money to one’s self. Five
randomly-selected participants were grouped as a team. In each
round, players were provided promissory notes of 1,000 Korean
won (about 1 US dollar), and decided to invest the money in the
public or their private account. Their cooperation determined the
result of the group, i.e., whether everyone earned a bonus or not.
A bonus of twice the first provided endowment, i.e., $2, was given
to all participants regardless of his or her decision only if 3 or more
of 5 participants cooperated during the trial. Otherwise, the
publicly invested money was not paid back. These procedures
were repeated for 10 rounds to investigate strategic behavior
during the game.
Additionally, we provided two more conditions with modified
incentives. In the second condition (condition II), participants were
provided exactly the same environment as the standard game
design (condition I) except that we offered the guarantee that the
participants who invested money into the public would be paid
back if the group failed to satisfy the bonus threshold. The third
condition (condition III) had a different incentive modification
from condition II. The participants were not guaranteed their
money back as in condition I. Instead, they were enforced to
cooperate for a bonus that was unequally provided according to
participants’ decisions. The bonus was adjusted to make fair net
earnings, i.e., $2, in the corresponding successful trial. When the
group succeeded, participants who cooperated were given $2,
twice as much as the amount they invested, whereas the free-riders
were provided with $1. Since the free-riders did not invest their
money (initial promissory note; $1), the extra one dollar for the
free-riders make the net earnings as $2 (equal to the cooperators’
net earnings). We examined these three differentiated conditions
to investigate how average and gifted adolescents performed in
each condition, and to reveal their strategic processes during social
interactions, which required the integration of affective and
cognitive information and the interpretation of others’ actions.
Eight teams of average adolescents and five teams of gifted
adolescents participated in the current study. They were instructed
before the game not to communicate with each other, and
communication was also prevented by the wearing of masks
distributed during the instruction. Written protocols for the PG
game were provided individually and were also orally explained to
each group. A simple questionnaire, including four examples of
each of the three conditions, was given to ensure the students
understood all of the possible cases that could occur during the
game. They were instructed to sit around the table facing each
other and to repeat 10 rounds of the PG game for each condition
(i.e., condition I, II and III). We used two types of cards as
imaginary money for the game, with written numbers that
represented the value of the card: 1,000 and 0 corresponding to
$1 and $0, respectively. Participants were told that they would
receive a gift certificate proportional to the amount of money they
acquired after all three conditions of the game. All participants
were provided with one ‘1,000’ card and one ‘0’ card for each
round, and after some time for decision-making, they were each
instructed to turn in one of the cards to the instructor
simultaneously. They had to hand in the card face-down, to
preserve anonymity of cooperation. After the decision, the
instructor recorded the cooperation of each player, let the
participants know whether the group could earn a bonus or not,
and identified the number of cooperators in the preceding round.
The instructor announced the remaining amount of trials at the
beginning of each round.
Data analysis
We measured cooperation rates, success or failure of the group
in earning a bonus, and total earnings of the participants to
analyze and compare performances. To investigate sequential
effects of the players’ decisions, we calculated cooperation rates
and stay rates for each sub-case, grouped according to success or
failure result, or the number of cooperators in the preceding trial.
For each group, performances among three conditions were
compared using the Kruskal-Wallis one-way analysis of variation.
We used the Mann-Whitney U test for post-hoc tests. The stay-or-
shift strategy was examined through one-sample Wilcoxon signed
rank tests examining whether the participant’s stay ratio was
biased in either direction from a 50% chance of staying. The
Spearman’s correlation analysis was used to examine correlations
between the participants’ performances and their demographic
characteristics. The alpha level was set to 0.05 for all statistical
tests. The commercial statistical package SPSS 13.0 for windows
(SPSS 13.0; SPSS Inc., Chicago, IL, USA) was used for all
statistical analyses.
Results
According to the exclusion criteria, we finally analyzed data
from 26 average adolescents (age: 13.9660.20 years, age range:
13–14 years, M/F: 15/11) and 22 gifted adolescents (age:
14.0560.49 years, age range: 13–15 years, M/F: 16/6). The
average group was not different from the gifted group in terms of
age (x2(1)=0.657, p=0.417) or sex (x2(1)=1.178, p=0.278), but
the average and gifted adolescents were statistically distinguishable
in terms of IQ (x2(1)=35.066, p,0.001). Among KTCPI scores,
the gifted group had significantly higher scores on the section
‘what kind of person are you’ (WKOPAY; x2(1)=3.917, p,0.05),
whereas the average and gifted group had comparable scores on
the section ‘something about myself’ (SAM; x2(1)=0.021,
p=0.885). Furthermore, the two groups were statistically different
in regards to inquisitiveness (x2(1)=4.505, p,0.05) and disci-
plined imagination (x2(1)=7.734, p,0.01) sub-items of the
WKOPAY scores. Demographic data of average and gifted
adolescents are summarized in Table 1. The sub-items of KTCPI
scores are described and summarized in Table 2. These
demographic data of the two groups show that the current study
had a well-controlled set of participant groups, particularly the
gifted adolescents with distinguishable indexes.
Cooperation ratios in the PG game
We first observed the cooperation behavior of the participants
in each condition in the PG game. Through all three conditions,
the adolescents showed rather low cooperation overall, ranging
from around 15% to 50% at maximum (Fig. 1). Particularly in
condition I, the gifted adolescents showed significantly higher
cooperation (about 35%) than the average adolescents (about
20%) (x2(1)=8.994, p,0.01). In condition II, the gifted group still
showed a higher mean cooperation rate (about 35%) than the
average group (about 30%), but the difference was not significant.
The gifted and average adolescents had the largest and most
significant cooperation difference in condition III (x2(1)=14.901,
p,0.001); the gifted group showed about 50% cooperation and
the average group showed about 15% cooperation. This result
indicates that the gifted adolescents were more cooperative than
the average adolescents regardless of the condition design.
To examine whether each group was affected by incentive
modifications, we compared the cooperation ratios between the
conditions. Both groups did not show any significant differences in
cooperationratesamong thethree conditions(gifted:
Cooperation Behaviors of Gifted Adolescents
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x2(2)=3.844, p=0.146; average: x2(2)=3.950, p=0.139). How-
ever, we observed that the gifted adolescents tended to be more
cooperative in condition III, in which cooperation was enforced,
than in the other two conditions. These results demonstrate that
greed possibly affects the gifted adolescents more than the average
adolescents.
Total earnings in the PG game
We found that the gifted adolescents earned more than the
average adolescents in all three conditions (Fig. 2). In condition I,
the gifted group earned about $12 and the average group earned
about $10 on average; this difference was significant (x2(1)=5.951,
p,0.05). In condition II, the gifted adolescents earned significantly
more, about $14, than the average adolescents, about $12
(x2(1)=5.199, p,0.05). The gifted group also showed the superior
performance to the average group in terms of mean total earnings
in condition III, during which the gifted earned about $14 and the
average earned about $12 (x2(1)=13.906, p,0.001). These results
indicate that the gifted adolescents maximized their profit better
than the average adolescents in most circumstance.
Comparing the monetary performances among the three
conditions, the gifted group did not show any significant difference
between different conditions (x2(2)=5.754, p=0.056). However,
the average group earned the most in condition II among the three
conditions (x2(2)=21.822, p,0.001). Their mean total earnings in
condition II were much higher than in condition I (U=104.000,
p,0.001) or condition III (U=159.500, p,0.01). These results
indicate that the average group found the condition that had no
risk of losing much easier than other conditions when maximizing
their profit. In other words, the average adolescents were sensitive
to monetary loss during the game.
Sequential effects on decisions in the PG game
To investigate strategic decision-making of adolescents in social
interactions, we utilized a 10-round repeated design and estimated
the sequential effects (Figure 1 in File S1). Particularly, we
computed the cooperation ratios and stay-or-shift ratios in
reorganized sub-cases that showed whether or not participants
were affected by success or failure and by the number of
cooperators in the preceding trial. The effect of the preceding
trial’s result was examined first. In conditions I, II and III, both
groups showed no significant effects of success or failure in the
preceding trial (Condition I: average, U=117.500, p=0.067;
gifted, U=192.000, p=0.231;
U=253.500, p=0.881; gifted, U=195.000, p=0.934; Condition
III: average, U=99.000, p=0.265; gifted, U=112.000, p=0.111;
Fig. 3). These results show that there is no significant loss
sensitivity difference between groups that revealed in terms of
mean cooperation rates.
We recalculated the cooperation rate in each sub-case according
to the number of cooperators in the preceding trial (0 to 4); this
excludes the decisions of the corresponding participant. Under the
assumption that two repeated, non-consecutive decisions were
independent during the procedure, the effects of the given
information on the behavioral change could be investigated
(Figure 2 in File S1). Gifted adolescents showed comparable
behaviors in all sub-cases during the condition I (x2(3)=6.475,
p=0.091), except that none of the cases had 4 cooperators in the
preceding trial (Fig. 4A). Compared with the gifted group, average
adolescents showed relatively diverse cooperation differences over
the sub-cases (x2(4)=10.558, p,0.05). The average group
exhibited 0% cooperation when there were 3 cooperators in the
last round, in condition I. Interestingly, each of the cooperation
rates following rounds with 0, 2 and 4 cooperators was significantly
higher than the cooperation following trials in which 3 players
cooperated (0: U=42.000, p,0.05; 2: U=24.000, p,0.05; 4:
U=3.000, p,0.05, respectively). The average group’s low
cooperation following trials in which the group had 3 cooperators
might be accounted for by both fear and greed, while the relatively
high cooperation following trials in which 4 participants
cooperated shows an abnormal characteristic of average adoles-
cents. These results indicate that the average adolescents are non-
strategic compared to the gifted adolescents in the sense of
maximizing the total earning.
In condition II, neither gifted nor average adolescents were
affected significantly by the given information about the number of
cooperators in the preceding trial (average:
p=0.260; gifted: x2(4)=4.660, p=0.324). Although cooperation
behaviors of the gifted group were not significantly different
among the sub-cases, their 0% cooperation following the trials
with 4 cooperators indicates relatively strong greed compared with
the average adolescents (Fig. 4B).
In condition III, the gifted adolescents had significantly different
cooperation ratios than the average adolescents in most of the sub-
cases (Fig. 4C). The gifted group showed higher cooperation rates
following trials in which they had 0, 1, and 3 cooperators (0:
x2(1)=5.876, p,0.05; 1: x2(1)=3.935, p,0.05; 3: x2(1)=6.500,
p,0.05, respectively). These results imply that the gifted
adolescents are less sensitive to loss compared to the average
adolescents.
Comparing cooperation within the group in condition III, the
gifted adolescents did not change their cooperation significantly
according to others’ decisions in the preceding trial (x2(4)=5.488,
p=0.241). In contrast, the average adolescents showed signifi-
cantlydifferentcooperation
(x2(3)=9.003, p,0.05); in particular, they cooperated significantly
more following trials in which 2 cooperated, compared with trials
in which all participants free-rode (U=86.500, p,0.05). Although
the condition enforced cooperation, the average group was not
cooperative. The results in the average group (i.e., 0% cooperation
ConditionII: average,
x2(4)=5.276,
ratesbetween thesub-cases
Table 1. Demographic characteristics of average and gifted
adolescents.
Average
(n=26)Gifted (n=22)
VariablesMean SDMean SD Significance level
Age (years)13.960.20 14.050.49
x2(1)=0.657
p=0.417
Sex 15/1116/6
x2(1)=1.178
(male/female)p=0.278
IQ* 111.1113.01142.595.95
x2(1)=35.066
p,0.001
aKTCPI57.9018.38 66.0923.06
x2(1)=1.952
p=0.162
bWKOPAY*50.6525.6966.6827.14
x2(1)=3.917
p,0.05
cSAM65.1529.3365.5030.93
x2(1)=0.021
p=0.885
aKTCPI, Khatena-Torrance Creative Perception Inventory score;
bWKOPAY, What kind of person are you score;
cSAM, Something about myself score;
*, statistically significant differences between groups.
doi:10.1371/journal.pone.0017044.t001
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following 3 previous cooperators and no cases of 4 preceding
cooperators) suggest that average adolescents’ weak mind-reading
abilities prevented them from reaching a collective decision as a
group. On the contrary, the gifted participants’ high cooperation
following trials where more than 3 participants cooperated
suggests that the gifted adolescents have better mind-reading
abilities than average adolescents.
Stay-or-shift strategic choices in the PG game
We analyzed the participants’ strategic drifts by calculating stay-
or-shift ratios in each condition. Cooperators and free-riders were
observed, and each case, followed by a successful or failed trial,
was described (Fig. 5). By using one-sample Wilcoxon signed rank
tests, we defined a stay ratio significantly higher than 50% as a
‘stay’ strategy, a stay ratio lower than 50% as a ‘shift’ strategy, and
all other insignificant cases as ‘random shift’ (see Methods). The
gifted adolescents showed more strategic drifts according to success
or failure than the average adolescents in condition I (Fig. 5A). In
the gifted group, a significant amount of cooperators shifted only if
their group failed to earn a bonus (Z=22.490, p,0.05) and free-
riders stayed regardless of success or failure (Z=2.495, p,0.05;
Z=1.969, p,0.05). However, the gifted adolescents shifted
randomly when they cooperated and succeeded in earning a
bonus. More interestingly, free-riders stayed significantly less when
they failed as compared to the cases in which they succeeded
(U=87.500, p,0.05). These results indicate that the gifted
adolescents are less affected by possible loss, but strongly chase
the strategies that can maximize their profit (i.e., earning a bonus)
or at least not losing their money.
On the other hand, in condition I, the average adolescents who
cooperated in the preceding trial showed significant shifts to free-
riding regardless of the result (success: Z=22.333, p,0.05;
failure: Z=23.227, p,0.001). In contrast, the free-riders chose to
stay in all circumstances (success: 100% stay; failure: Z=4.186,
p,0.001). In particular, the free-riders showed significantly higher
stay ratios when the group succeeded (U=22.500, p,0.05). These
results suggest that the average adolescents prefer to be free-riders,
due to either fear or greed.
In condition II, gifted adolescents chose to shift by random
chance in all cases (Fig. 5B). As the condition guarantees money
back in failed cases, the decisions of the gifted adolescents in
condition II clearly followed rational processes, i.e., no stay-ratio
differences between successful and failed trials. In contrast, among
the average adolescents, the significant stay strategy that the free-
Table 2. Sub-item statistics of the KTCPI scores for average and gifted adolescents.
Average (n=26)Gifted (n=22)
VariablesMean SD Mean SDSignificance level
aWKOPAY*50.6525.69 66.68 27.14
x2(1)=3.917
p,0.05
Acceptance of authority55.96 24.7948.91 29.00
x2(1)=0.882
p=0.348
Self Confidence 55.0032.2958.41 26.84
x2(1)=0.118
p=0.732
Inquisitivness* 70.0826.4553.5929.20
x2(1)=4.505
p,0.05
Awareness of others57.8832.0147.5931.48
x2(1)=1.433
p=0.231
Disciplined Imagination* 65.88 27.1283.64 21.11
x2(1)=7.734
p,0.01
bSAM65.1529.3365.50 30.93
x2(1)=0.021
p=0.885
Environmental sensitivity48.81 33.28 53.2337.18
x2(1)=0.001
p=0.975
Initiative(I) 65.6524.8065.18 27.74
x2(1)=0.007
p=0.933
Self-strength(SS) 70.4227.4868.9125.89
x2(1)=0.013
p=0.909
Intellectuality 61.6930.68 61.4132.34
x2(1)=0.013
p=0.909
Individuality 51.8830.77 66.91 25.13
x2(1)=1.986
p=0.159
Artistry(A) 56.1533.31 45.82 32.46
x2(1)=0.843
p=0.358
aWKOPAY, What kind of person are you score;
bSAM, Something about myself score;
*, statistically significant differences between groups.
doi:10.1371/journal.pone.0017044.t002
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riders used following trials in which they failed (Z=2.407, p,0.05)
implies a non-strategic behavior.
In condition III, the gifted adolescents shifted randomly
regardless of success or failure or the choice they made (cooperate
or free-ride) in the preceding trial (cooperator: U=68.000,
p=0.120; free-rider: U=79.000, p=0.917). However, the
average group exhibited loss-aversive behaviors that were not
revealed by measuring cooperation ratios alone (Fig. 5C). The
cooperators tended to shift after failed trials (Z=22.373, p,0.05),
whereas they did not choose a particular strategy following a
Figure 1. Mean cooperation ratios in each condition. Average and gifted adolescents showed statistically comparable cooperation ratios in all
three conditions. The gifted group was significantly more cooperative in both conditions I and III, whereas the two groups had similar cooperation
rates in condition II. Standard errors of each condition are represented as error bars; *p,0.05; **p,0.01; ***p,0.001.
doi:10.1371/journal.pone.0017044.g001
Figure 2. Mean total earnings in each condition. Gifted adolescents earned comparable amounts in three conditions. Average adolescents
earned the most in condition II among the three conditions. The amount they earned in condition II was significantly higher than in conditions I and
III. Compared with the average group, the gifted group earned significantly larger amounts in each condition. Black asterisk: within-group difference;
Grey asterisk: between-group difference; Standard errors of each condition are represented as error bars; *p,0.05; **p,0.01; ***p,0.001.
doi:10.1371/journal.pone.0017044.g002
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success. The stay ratios between successful and failed cases were
significantly different (U=11.000, p,0.05). The free-riders always
stayed regardless of the result of the preceding trial (success: 100%
stay; failure: Z=4.187, p,0.001), even though they had no
chance of earning more than the cooperator, according to the rule
of the condition. These results indicate that average adolescents
have loss-sensitive behavior, but that gifted adolescents do not.
Correlations between demographic data and
performances
We additionally analyzed correlations between the participants’
demographic data (i.e., IQ and KTCPI scores) and their
performances in the game (i.e., cooperation rates, total earnings,
and stay ratios). For simplicity, we only focused on the
demographic data that were significantly different between the
average and the gifted adolescents: IQ, average WKOPAY score,
WKOPAY score in disciplined imagination, and inquisitiveness.
The significant correlations we found are summarized in Table 1
in File S1.
Among the significant correlations, we found clear clues
supporting the notion that the gifted adolescents were strategically
superior to the average adolescents. First, we found a negative
correlation between IQs and stay ratios in condition III when free-
riders failed in the preceding trial (Spearman’s correlation
coefficient=20.38, p,0.05; Fig. 6A). The significant positive
correlation was detected between IQs and the total earnings in the
corresponding condition (Spearman’s correlation coefficient=
0.43, p,0.01), which may result from the gifted adolescents’
well-suited shift strategies. In condition III, we also found a
significant negative correlation between the stay ratios of free-
riders and disciplined imagination (Spearman’s correlation
coefficient=20.48, p,0.01; Fig. 6B), one of the WKOPAY
scores from the creativity test; this agrees with the correlation we
mentioned above. Furthermore, we observed a positive correlation
between stay ratios in condition II during which cooperators
succeeded, and inquisitiveness, one of the WKOPAY scores from
the creativity test (Spearman’s correlation coefficient=0.41,
p,0.05; Fig. 6C). Based on this correlation observed (i.e., a
Figure 3. Mean cooperation ratios in a successive trial following the preceding successful or failed trials. Both groups had comparable
cooperation rates regardless of the result of the preceding trial in (a) condition I, (b) condition II, and (c) condition III. Particularly in condition III, the
average group exhibited relatively larger differences than the gifted group between successful and failed rounds.
doi:10.1371/journal.pone.0017044.g003
Figure 4. Mean cooperation ratios in a successful trial following trials with the indexed numbers of cooperators. (a) In condition I,
gifted adolescents showed comparable cooperation through all sub-cases. In the gifted group, none of the cases had 4 preceding cooperators.
Average adolescents exhibited significantly low cooperation following trials with 3 cooperators, as compared to those with 0, 2 and 4 cooperators. (b)
In condition II, the gifted group had similar cooperation rates in all sub-cases except for the case with 4 cooperators in the preceding trial. The gifted
group showed 0% cooperation rate in the corresponding case that is relatively lower than in trials with 0, 1 and 2 preceding cooperators. The average
adolescents also showed comparable cooperation rates in all cases except for a relatively higher cooperation following 4 preceding cooperators. (c) In
condition III, the gifted group had statistically comparable cooperation rates for all sub-cases. The average adolescents exhibited significantly higher
cooperation in the trials, with 2 preceding cooperators when compared to those with 0 cooperators in condition III. None of the cases in the average
group had 4 preceding cooperators. Between the two groups, the gifted adolescents showed significantly higher cooperation in which 0, 1 or 3
cooperators existed in the previous round. Black asterisk: within-group difference; Grey asterisk: between-group difference; Standard errors of each
condition are represented as error bars; *p,0.05; **p,0.01; ***p,0.001.
doi:10.1371/journal.pone.0017044.g004
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participant with a higher inquisitiveness score tends to stay with
the previous choice), we suggest that average adolescents, who
showed significantly higher inquisitiveness than the gifted (Table 2),
were not greedy. In other words, gifted adolescents tend to shift to
free-riding, which gives them the opportunity to take advantage of
others’ cooperation.
Discussion
The aim of the current study was to investigate the behavioral
strategies of cooperation and free-riding in gifted adolescents
during the PG game, and to analyze their behaviors to examine
the major causes of behavioral differences between gifted and
average adolescents. Between two groups, gifted adolescents were
more cooperative, as observed in a previous study [39], and
earned more than average adolescents. Gifted adolescents showed
weak loss sensitivity but notable greed. Additionally, they were
more strategic in that their behavior could be straightforwardly
accounted for by economic, emotional or social motivation. In
contrast, average adolescents were rather less cooperative than the
gifted group, more sensitive to loss, non-greedy, and non-strategic
in repeated decisions.
Gain and loss sensitivity in the PG game
The current study found that gifted adolescents show more risk-
taking behavior compared with average adolescents. First, gifted
adolescents’ diminished loss sensitivity seemed to cause their risk-
taking behavior. In the PG game, particularly in condition III
(greed-free environment), the participants might fear losing money
due to the uncertain probability of earning a bonus. In decision
theory, since the probability of earning a bonus remained
Figure 5. Mean strategic stay ratios in the trial following previously successful or failed trials. Each case of trials was tested for whether
the ratios were significantly different from 50% chance of a changing strategy (horizontal blue line). (a) In condition I, the cooperators among the
gifted adolescents shifted randomly after success, but shifted significantly after failure. The free-riders among the gifted adolescents showed a
significant stay strategy following successful and failed trials. Among the average group, the cooperators always chose a shift strategy, whereas the
free-riders always chose a stay strategy, regardless of the group result. The free-riders of the average group showed significantly more cooperation
after success than after failure. (b) In condition II, cooperators and free-riders in both groups chose a random shift strategy in all possible cases except
the following trials in which the free-riders among the average adolescents failed. They showed a significant stay strategy. (c) In condition III, the
gifted group always shifted randomly from their corresponding alternative decision in all cases. In contrast, the cooperators among the average
adolescents exhibited significant differences from the group result in that they randomly shifted after success and shifted after failure. The free-riders
in the group chose a significant stay strategy regardless of the result. The free-riders of the average adolescents showed significantly higher stay
ratios than the gifted adolescents, regardless of the group result. Black asterisk: within-group difference; Grey asterisk: between-group difference;
Standard errors of each condition are represented as error bars; *p,0.05; **p,0.01; ***p,0.001;mp,0.05;mmp,0.01;mmmp,0.001.
doi:10.1371/journal.pone.0017044.g005
Figure 6. Significant correlations between demographic data and performances. A significant negative correlation was found between (a)
IQs and stay ratios and (b) Disciplined imagination score and stay ratios of the free-riders when the group failed to earn a bonus in condition III, which
indicates that participants with higher scores on the corresponding demographic data tended to shift at the corresponding case. (c) Stay ratios in
condition II during which cooperators succeeded showed significant positive correlation with Inquisitiveness score, which represents that the gifted
adolescents with low Inquisitiveness score tended to have higher greediness.
doi:10.1371/journal.pone.0017044.g006
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uncertain through iterations, the participants’ decisions should be
random and not affected by others’ choices [40]. However, in the
empirical study, participants estimated the probability of winning
based on the results of the preceding trials and became either risk-
aversive or risk-taking. Thus, loss sensitivity may lead to emotion-
based phenomena that fear of losing money causes differences in
behavioral differences against risk [41]. Most interestingly, in
strategic drifts of cooperators, the gifted group showed relatively
lower and insignificant levels of loss sensitivity, compared with the
average group. One possible causal brain mechanism that might
underlie the behavioral differences is interactions between brain
regions which encode cognitive and affective process. According to
a neurobiological interpretation from a recent study, gifted
adolescents might show more risk-taking behavior due to
infrequent or weaker interaction between affective and cognitive
control networks in the brain, as compared to average adolescents
[42]. In contrast to gifted adolescents, average adolescents showed
relatively stronger loss sensitivity during the game, which supports
the emotional effects of the preceding results on their decisions. It
can be inferred that average adolescents, regardless of their
mathematical abilities, have more frequent interaction between
affective and cognitive networks in the brain compared with the
gifted. This interpretation of defective loss sensitivity in the gifted
adolescents might account for the stereotypical portrayal of
emotional maladaptation of gifted adolescents as compared to
average adolescents [13,14]. However, further research that
focuses on neural activation differences and functional connectiv-
ity is required to compare with other controversial interpretations
on interaction between brain regions [2,7,43].
Second, compared with gifted adolescents, defective gain
sensitivity seemed to hinder average adolescents from taking risks.
In the PG game, greed can be considered as a profit-maximizing
ability that is related to gain sensitivity. As mentioned above, in
condition II, participants had no risk of losing money, which
eventually leads to greedy incentives for the participants. Hence, a
player has a 50% chance of earning a bonus, and he or she can at
least keep the endowment in the opposite cases. The decision
process is still cognitively demanding, because the participants can
maximize their profit by free-riding in about a third of the cases.
Comparing the expected values for each option, it is a rational
decision to cooperate in the corresponding condition. However, a
greedy participant should free-ride to maximize total earnings. In
our study, the average adolescents showed abnormally cooperative
behavior during a condition without a risk of losing; they were
relatively cooperative following trials in which they faced enough
cooperators to earn a bonus (4 cooperators), but they failed to find
an adequate strategy to maximize their profit during the game. It
could be inferred from these results that mathematically gifted
adolescents are more sensitive to the magnitude of the gain, and
that this is represented as profit-maximizing behavior. Various
previous studies suggested that asymmetrically developed right
hemisphere might underlie the superior mathematical abilities of
the gifted adolescents [11,44]. The current result opens the
possible neurodevelopmental differences between gifted and
average adolescents might exist not only in the hemispheric
dominance but also in the specific functional region, such as the
prefrontal cortex, which is generally related to higher memory,
cognitive performance, and reward process [45].
Social cognition and social strategy in the PG game
During the PG game, we observed several different patterns
between average and gifted adolescents in aspects of social
decision-making. First, the gifted group succeeded more often
than the average group in estimating others’ next moves and in
establishing cooperation rates high enough to earn a bonus.
Average adolescents exhibited evidently abnormal behaviors that
did not reflect the number of cooperators in the preceding trial.
The ability to decide on a next move as an adequate reaction to
others’ decisions is associated with theory-of-mind (TOM) [46–
49]. Recently, Moriguchi et al. [50] examined children and
adolescents ranging from 9 to 16 and found that the activity of the
neural substrates for TOM correlate significantly with age. It was
implied that adolescence might be a critical period for maturation
of the ability to process others’ intentions in a complex social
interaction. Thus, we speculate that gifted adolescents might be
neuro-developmentally more mature than average adolescents in
their ability to estimate others’ intentions.
Another explanation for these behavioral differences is that
average adolescents might have low levels of trust in their group
and that they did not expect preserved high cooperation, as
demonstrated by significantly decreased cooperation following
trials with high rates of cooperation, when they did not benefit
from free-riding (condition III). We also observed the effect of low
trust in condition I, in which average adolescents cooperated
significantly less following 3 cooperators than following 0 or 2
cooperators. We suggest that these distrusting behaviors, often
observed in adolescents [51], might be strongly related not only to
social cognition, but also to hypersensitivity to loss.
Additionally, average adolescents displayed herding behavior
[52]. Especially in conditions I and II, average adolescents showed
abnormally high cooperation in rounds following trials with 4
cooperators when compared with other cases (Fig. 4). Since these
patterns appeared in the conditions that include greedy incentive,
they could be considered as non-strategic but strong social
adaptation within their age group. The current behavioral patterns
support previous studies suggesting that a social affiliation
dominated by peers powerfully motivates adolescents’ decisions
[53].
In aspects of strategic decision-making, average adolescents
failed to find an optimal strategy that fit their group to maximize
their own profit. Multiple factors such as loss sensitivity, herding
behavior, and low trust in their group seemed to induce the results.
In contrast to these social and emotional factors, the greed and
risk-taking behavior that appeared in the gifted adolescents
seemed to assist profit maximizing. A significant positive
correlation in condition III between IQs and shift ratios of free-
riders when they failed to earn a bonus additionally supports the
idea that participants with higher IQs could manage and build
group cooperation when their risk-aversive behaviors did not
satisfy the bonus threshold. Strategic ability is known to be related
to cognitive performance (e.g., working memory) and mathemat-
ical achievement [54,55]. The current study demonstrates that
mathematically gifted adolescents are superior in using economic
strategy. However, at the same time, their strategic decision-
making excludes social and emotional effects (e.g., herding
behavior in the average adolescents); amongst average adolescents
of their own age, this condition might cause social disharmony.
We found underpinnings of differences between average and
gifted adolescents’ behaviors concerning gain or loss sensitivity and
social adaptation strategy during the PG game. Our findings must
be interpreted in light of the limitations of this study. First, we
assessed the relatively small number of subjects for each group.
Thus, there were a few sub-cases that never occurred (e.g., the
gifted group never had an instance of 4 preceding cooperators in
condition I, and the average group never experienced 4 preceding
cooperators in condition III), and some of the comparisons
between groups or amongst sub-cases were restricted only to non-
statistical and heuristic inspection. Second, the group size of the
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game in this study was set to five participants, which is relatively
small compared with previous public goods studies (e.g., N=4, 10,
40, 100) [17,18]. Several studies showed that the level of
cooperation is dependent on the group size [56–59]. Even though
they also showed the increased cooperation in the large-group was
not purely due to the members-in-the-group effect – marginal per
capita return and critical mass is also related to the cooperativeness
of the group, we should note that the behavioral characteristics in
the current study might be limited to the current settings. Third,
due to the complex decision-making processes required for the
game, most of the underlying mechanisms are described
qualitatively and concurrent recording of brain activity during
the game was not possible, which will be our future investigation.
Nevertheless, the current study is the first report of the
differential development of emotional and social or non-social
cognitive abilities between average and gifted adolescents based on
game theory. We estimated that, between the two groups, neuro-
developmental differences in affective and cognitive crosstalk
underlie the behavioral dissimilarity. Additionally, we suggest that
uncovering gifted adolescents’ low dependencies on social and
emotional factors might pave the road for understanding the
causes of their social isolation problem and provide more adequate
educational systems for the gifted.
Supporting Information
File S1
(DOC)
Sequential effects on decisions in the PG game.
Author Contributions
Conceived and designed the experiments: DC JJ. Performed the
experiments: DC KY JHK BJ. Analyzed the data: DC JHK. Wrote the
paper: DC KY JHK BJ JJ.
References
1. Gill H, O’Boyle M, Hathaway J (1998) Cortical distribution of neural activity for
component processes in mental rotation. Cortex 34: 707–718.
2. O’Boyle MW, Cunnington R, Silk TJ, Vaughan D, Jackson G, et al. (2005)
Mathematically gifted male adolescents activate a unique brain network during
mental rotation. Cognitive Brain Research 25: 583–587.
3. Rogers KB (1986) Do the Gifted Think and Learn Differently? A Review of
Recent Research and Its Implications for Instruction. Journal for the Education
of the Gifted 10: 17–39.
4. Geary DC, Brown SC (1991) Cognitive addition: Strategy choice and speed-of-
processing differences in gifted, normal, and mathematically disabled children.
Developmental psychology 27: 398–406.
5. Gaultney JF, Bjorklund DF, Goldstein D (1996) To be young, gifted, and
strategic: Advantages for memory performance. Journal of experimental child
psychology 61: 43–66.
6. Jin SH, Kim SY, Park KH, Lee KJ (2007) Differences in EEG between gifted
and average students: neural complexity and functional cluster analysis.
International Journal of Neuroscience 117: 1167–1184.
7. Singh H, O Boyle MW (2004) Interhemispheric interaction during global-local
processing in mathematically gifted adolescents, average-ability youth, and
college students. NEUROPSYCHOLOGY-NEW YORK- 18: 371–377.
8. Gross MUM (2004) Exceptionally gifted children: Routledge .
9. Janos PM, Robinson NM (1985) Psychosocial development in intellectually
gifted children. The gifted and talented:Developmental perspectives. pp
149–195.
10. Robinson A, Clinkenbeard PR (1998) Giftedness: An exceptionality examined.
Annual Review of Psychology 49: 117–139.
11. O’Boyle MW, Benbow CP, Alexander JE (1995) Sex differences, hemispheric
laterality, and associated brain activity in the intellectually gifted. Developmental
neuropsychology 11: 415–443.
12. Uddin LQ, Iacoboni M, Lange C, Keenan JP (2007) The self and social
cognition: the role of cortical midline structures and mirror neurons. Trends in
Cognitive Sciences 11: 153–157.
13. Lovecky DV (1992) Exploring Social and Emotional Aspects of Giftedness in
Children. Roeper Review 15: 18–25.
14. Neihart M, Reis SM, Robinson NM, Moon SM (2002) The Social and
Emotional Development of Gifted Children: What Do We Know? Prufrock
Press, Inc.
15. Camerer C Behavioral game theory: Experiments in strategic interaction:
Princeton University Press Princeton, NJ.
16. Andreoni J (1988) Why free ride? Strategies and learning in public goods
experiments. Journal of Public Economics 37: 291–304.
17. Isaac RM, Walker JM, Thomas SH (1984) Divergent evidence on free riding: An
experimental examination of possible explanations. Public choice 43: 113–149.
18. Ledyard JO (1995) Public goods: A survey of experimental research. Handbook
of Experimental Economics. pp 111–194.
19. Dawes RM, Orbell JM, Simmons RT, Kragt A (1986) Organizing Groups for
Collective Action. The American Political Science Review 80: 1171–1185.
20. Fischbacher U, Gachter S, Fehr E (2001) Are people conditionally cooperative?
Evidence from a public goods experiment. Economics Letters 71: 397–404.
21. Palfrey TR, Prisbrey JE (1996) Altruism, reputation and noise in linear public
goods experiments. Journal of Public Economics 61: 409–427.
22. Harbaugh WT, Krause K (2000) Children’s altruism in public good and dictator
experiments. Economic Inquiry 38: 95–109.
23. Nowak MA (2006) Five rules for the evolution of cooperation. Science 314:
1560.
24. Szabo G, Fath G (2007) Evolutionary games on graphs. Physics Reports 446:
97–216.
25. Perc M, Szolnoki A (2010) Coevolutionary games–A mini review. BioSystems
99: 109–125.
26. Santos FC, Santos MD, Pacheco JM (2008) Social diversity promotes the
emergence of cooperation in public goods games. Nature 454: 213–216.
27. Fehr E, Gachter S (2000) Cooperation and punishment in public goods
experiments. American Economic Review 90: 980–994.
28. Fehr E, Gachter S (2002) Altruistic punishment in humans. Nature 415:
137–140.
29. Rand DG, Dreber A, Ellingsen T, Fudenberg D, Nowak MA (2009) Positive
interactions promote public cooperation. Science 325: 1272.
30. Helbing D, Szolnoki A, Perc M, Szabo G (2010) Evolutionary establishment of
moral and double moral standards through spatial interactions. PLoS
computational biology 6: 1243–1248.
31. Helbing D, Szolnoki A, Perc M, Szabo G (2010) Punish, but not too hard: How
costly punishment spreads in the spatial public goods game. New Journal of
Physics 12: 083005.
32. Andreoni J (1995) Cooperation in public-goods experiments: kindness or
confusion? The American Economic Review. pp 891–904.
33. Wechsler D (1992) Wechsler Intelligence Scale for Children 3rd UK edn.
London: Psychological Corporation.
34. Khatena J (1977) The Khatena-Torrance Creative Perception Inventory for
Identification Diagnosis Facilitation and Research. Gifted Child Quarterly 21:
517–525.
35. Treffinger DJ (2004) Creativity and giftedness: Corwin Press .
36. Silvia PJ (2008) Creativity and intelligence revisited: A latent variable analysis of
Wallach and Kogan (1965). Creativity Research Journal 20: 34–39.
37. Wallach MA, Kogan N (1965) Modes of thinking in young children: A study of
the creativity-intelligence distinction: Holt, Rinehart and Winston .
38. Kim KH (2005) Can only intelligent people be creative. Journal of Secondary
Gifted Education 16: 57–66.
39. Lupkowski AE (1989) Social Behaviors of Gifted and Typical Preschool Children
in Laboratory School Programs. Roeper Review 11: 124–127.
40. Hsu M, Bhatt M, Adolphs R, Tranel D, Camerer CF (2005) Neural systems
responding to degrees of uncertainty in human decision-making. Science 310:
1680–1683.
41. Yacubian J, Glascher J, Schroeder K, Sommer T, Braus DF, et al. (2006)
Dissociable systems for gain-and loss-related value predictions and errors of
prediction in the human brain. Journal of Neuroscience 26: 9530–9537.
42. Steinberg L (2008) A social neuroscience perspective on adolescent risk-taking.
Developmental Review 28: 78–106.
43. O’Boyle MW (2008) Mathematically Gifted Children: Developmental Brain
Characteristics and Their Prognosis for Well-Being. Roeper Review 30:
181–186.
44. Silverman LK (1997) The construct of asynchronous development. PJE Peabody
Journal of Education 72: 36–58.
45. Pochon JB, Levy R, Fossati P, Lehericy S, Poline JB, et al. (2002) The neural
system that bridges reward and cognition in humans: an fMRI study.
Proceedings of the National Academy of Sciences of the United States of
America 99: 5669–5674.
46. Rilling JK, Sanfey AG, Aronson JA, Nystrom LE, Cohen JD (2004) The neural
correlates of theory of mind within interpersonal interactions. Neuroimage 22:
1694–1703.
47. Frith U, Frith CD (2003) Development and neurophysiology of mentalizing.
Philosophical Transactions of the Royal Society B: Biological Sciences 358:
459–473.
48. Polezzi D, Daum I, Rubaltelli E, Lotto L, Civai C, et al. (2008) Mentalizing in
economic decision-making. Behavioural Brain Research 190: 218–223.
Cooperation Behaviors of Gifted Adolescents
PLoS ONE | www.plosone.org 10 February 2011 | Volume 6 | Issue 2 | e17044

Page 11

49. Premack D, Woodruff G (1978) Does the chimpanzee have a theory of mind.
Behavioral and Brain sciences 1: 515–526.
50. Moriguchi Y, Ohnishi T, Mori T, Hiroshi MD, Komaki G (2007) Changes of
brain activity in the neural substrates for theory of mind during childhood and
adolescence. Psychiatry & Clinical Neurosciences 61: 355–363.
51. Flanagan CA, Gill S, Gallay LS (2005) Social participation and social trust in
adolescence: The importance of heterogeneous encounters. Processes of
community change and social action. pp 149–166.
52. Raafat RM, Chater N, Frith C (2009) Herding in humans. Trends in Cognitive
Sciences 13: 420–428.
53. Guyer AE, McClure-Tone EB, Shiffrin ND, Pine DS, Nelson EE (2009) Probing
the neural correlates of anticipated peer evaluation in adolescence. Child
Development 80: 1000–1015.
54. Keeler ML, Swanson HL (2001) Does strategy knowledge influence working
memory in children with mathematical disabilities? Journal of learning
disabilities 34: 418–434.
55. McNamara DS, Scott JL (2001) Working memory capacity and strategy use.
Memory and Cognition 29: 10–17.
56. Carpenter JP (2007) Punishing free-riders: How group size affects mutual
monitoring and the provision of public goods. Games and Economic Behavior
60: 31–51.
57. Szolnoki A, Perc M (2010) Impact of critical mass on the evolution of
cooperation in spatial public goods games. Physical Review E 81: 057101.
58. Isaac RM, Walker JM, Williams AW (1994) Group size and the voluntary
provision of public goods: Experimental evidence utilizing large groups. Journal
of Public Economics 54: 1–36.
59. Marwell G, Oliver P (1993) The critical mass in collective action: A micro-social
theory: Cambridge Univ Pr .
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PLoS ONE | www.plosone.org 11February 2011 | Volume 6 | Issue 2 | e17044