Social and Nonsocial Relational Reasoning - Am MIT spezialisierte KI-Forschung

Social and Nonsocial Relational Reasoning
in Adolescence and Adulthood

Lucía Magis-Weinberg1, Sarah-Jayne Blakemore1, and Iroise Dumontheil2

Abstrakt

■ Reasoning during social interactions requires the individual
manipulation of mental representations of one’s own traits and
those of other people as well as their joint consideration (rela-
tional integration). Research using nonsocial paradigms has
linked relational integration to activity in the rostrolateral PFC.
Hier, we investigated whether social reasoning is supported by
the same general system or whether it additionally relies on
regions of the social brain network, such as the medial PFC. Wir
further assessed the development of social reasoning. Im
social task, participants evaluated themselves or a friend, or com-
pared themselves with their friend, on a series of traits. In the non-
social task, participants evaluated their hometown or another
town or compared the two. In a behavioral study involving
325 Teilnehmer (11–39 years old), we found that integrating rela-

tionen, compared with performing single relational judgments,
improves during adolescence, both for social and nonsocial infor-
mation. Thirty-nine female participants (10–31 years old) took part
in a neuroimaging study using a similar task. Activation of the
relational integration network, including the rostrolateral PFC,
was observed in the comparison condition of both the social
and nonsocial tasks, whereas the medial PFC showed greater acti-
vation when participants processed social as opposed to non-
social information across conditions. Developmentally, the right
anterior insula showed greater activity in adolescents compared
with adults during the comparison of nonsocial versus social infor-
mation. This study shows parallel recruitment of the social brain
and the relational reasoning network during the relational inte-
gration of social information in adolescence and adulthood. ■

EINFÜHRUNG

Is London more expensive than Cambridge? Answering
this question entails at least two levels of relational rea-
soning. At the first level, one needs to judge the prices
in each city independently (evaluation of single relations,
z.B., how much do houses in London cost?). At the sec-
ond level, one needs to simultaneously consider mental
representations of both cities and to integrate the single
judgments into a higher-order comparison (relational
Integration, in diesem Fall, comparing the house prices in
London and Cambridge). Relational integration has typi-
cally been studied in nonsocial contexts, insbesondere,
using the Raven’s Progressive Matrices (Raven, 1998).
Jedoch, relational integration also occurs in the social
Domain, Zum Beispiel, when comparing people on per-
sonality traits (z.B., are you more patient than your
friend?). The neural processes supporting this kind of
social reasoning and the way it develops are not well
verstanden.

Previous fMRI research has identified the lateral PFC
and lateral parietal cortex as involved in relational integra-
tion (Dumontheil, 2014; Bunge, Helskog, & Wendelken,
2009; Wendelken, Nakhabenko, Donohue, Fuhrmann, &
Bunge, 2008; Schmied, Keramatian, & Christoff, 2007),
whereas medial prefrontal cortex (MPFC) has been asso-

1University College London, 2University of London

ciated with the processing and manipulation of social
Information ( Van Overwalle, 2009; Gilbert et al., 2006;
Holz & Grafman, 2003). The current study aimed to
bring together these separate strands of research to in-
vestigate domain-general and social domain-specific pro-
cesses that support the relational integration of social
Information. Both relational reasoning and social cogni-
tion and their underlying neural substrates undergo sig-
nificant reorganization during adolescence (Kilford,
Garrett, & Blakemore, 2016; Dumontheil, 2014). Dort-
Vordergrund, a second aim of the current study was to compare
social reasoning in adolescents and adults. We employed
a paradigm that allows the investigation and comparison
of relational integration of both social and nonsocial infor-
mation (Raposo, Vicens, Clithero, Dobbins, & Huettel,
2011). In a large behavioral study, we investigated the
development of relational integration of social and non-
social information from late childhood until adulthood.
In a follow-up fMRI study, we studied the neural cor-
relates of these cognitive processes in adolescence and
Erwachsensein.

Neural Bases of Relational Integration and
Social Cognition

Relational reasoning research suggests a central role of
rostrolateral prefrontal cortex (RLPFC), which corresponds

© 2017 Massachusetts Institute of Technology. Published under a
Creative Commons Attribution 3.0 Unportiert (CC BY 3.0) Lizenz.

Zeitschrift für kognitive Neurowissenschaften 29:10, S. 1739–1754
doi:10.1162/jocn_a_01153

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to the lateral aspect of the anterior, or rostral, prefrontal
Kortex (Brodmann’s areas [BAs] 10/46 Und 10/47), In
relational integration compared with processing single
Beziehungen. Imaging studies using the Raven’s Progressive
Matrices in adults have shown RLPFC involvement in
the joint manipulation of visuospatial patterns (Kroger
et al., 2002; Christoff et al., 2001) as well as in the in-
tegration of relations in analogical reasoning tasks
( Wendelken et al., 2008; Bunge, Wendelken, Badre, &
Wagner, 2005) and in the integration of multiple relations
to reach a logical conclusion (Wendelken & Bunge, 2009).
A study comparing visuospatial and semantic variants of a
relational matching task found considerable activation
overlap within the left RLPFC, suggesting a domain-general
role for RLPFC in relational integration ( Wendelken,
Chung, & Bunge, 2012).

Social cognitive research suggests a role of the MPFC,
which corresponds to BA 8/BA 9/BA 10, in the processing
of social information (see Van Overwalle, 2009, for a meta-
Analyse). Studies with adults have shown that this region
is involved in considering one’s thoughts and feelings
(Rameson, Satpute, & Lieberman, 2010; Gusnard, 2005;
Zysset, Huber, Samson, Ferstl, & von Cramon, 2003) Und
in perspective taking (PT; David et al., 2008; D’Argembeau
et al., 2007; Aichhorn, Perner, Kronbichler, Staffen, &
Ladurner, 2006; David et al., 2006; Ruby & Decety, 2001,
2004; Vogeley et al., 2004). The MPFC is also recruited dur-
ing tasks that require mentalizing, das ist, the consideration
of other people’s mental states (Amodio & Frith, 2006;
Decety & Sommerville, 2003; Frith & Frith, 2003).

Development during Adolescence

Both relational integration and social cognition show pro-
tracted development in terms of improved performance
and associated brain activity between adolescence and
Erwachsensein (Blakemore, 2012; Crone & Dahl, 2012;
Dumontheil & Blakemore, 2012; Dumontheil, Hillebrandt,
Apperly, & Blakemore, 2012; Crone et al., 2009;
Dumontheil, Bürger, & Blakemore, 2008). The RLPFC un-
dergoes structural and functional development with age,
with evidence that its activity during relational integra-
tion tasks becomes increasingly specialized during child-
hood and adolescence (Dumontheil, 2014; Wendelken,
O’Hare, Whitaker, Ferrer, & Bunge, 2011; Dumontheil,
Houlton, Christoff, & Blakemore, 2010; Crone et al., 2009;
Ferrer, O’Hare, & Bunge, 2009; Dumontheil et al., 2008).
Zusätzlich, a complex pattern of developmental changes
in functional connectivity related to reasoning ability has
been identified, including changes in connectivity between
the RLPFC and the parietal cortex ( Wendelken, Ferrer,
Whitaker, & Bunge, 2016; Bazargani, Hillebrandt, Christoff,
& Dumontheil, 2014). Bazargani et al. (2014) observed a
decrease in short-range (fronto-insular) connectivity with
stable long-range connectivity (frontoparietal) und ein
increase of modulatory connections with age. Wendelken
et al. (2016) found a pattern of developmental changes

suggestive of increasing communication between pre-
frontal regions and specific targets.

Key regions of the social brain, including the MPFC,
undergo structural and functional changes during adoles-
cence. Cortical thickness and gray matter volume in the
MPFC decrease between late childhood and the early 20s
(Mills, Lalonde, Clasen, Giedd, & Blakemore, 2014). In
parallel, several fMRI studies have shown that MPFC activ-
ity during mentalizing tasks decreases between early
adolescence and adulthood (Blakemore, 2008, 2012). In
a previous study investigating the development of the
neural correlates of mentalizing, Teilnehmer waren
required either to take someone else’s perspective or
to use symbolic cues to select an appropriate action in
a communicative context. We found that adolescents
showed hypoactivation of domain-general cognitive con-
trol regions in the parietal cortex and PFC and hyperacti-
vation of parts of the social brain network (Dumontheil
et al., 2012). This study thus demonstrated the engage-
ment of cognitive control and social brain regions within
a single paradigm and that the engagement of these
regions changes as a function of age.

Relational integration within the social domain has been
investigated in adults using a task that combined both
mentalizing and relational integration (Raposo et al.,
2011). Participants judged how pleasant they found a cer-
tain word, how pleasant a friend would find the word, Und
how their rating of pleasantness would compare with that
of their friend. Behaviorally, RTs were higher when partic-
ipants were comparing themselves with their friend relative
to the two single-relation conditions. MPFC activation was
higher during the friend judgment compared with the
self-judgment, whereas RLPFC activation was higher
when contrasting the relational integration comparison
and self-judgment conditions. The study did not include
a nonsocial relational reasoning condition, preventing
the conclusion that the activation patterns are specific to
relational integration of social information per se or reflec-
tive of relational integration more generally.

This Study

Hier, we adapted the paradigm designed by Raposo et al.
(2011) to investigate behavioral development of social
reasoning (Study 1) and its neural development between
adolescence and adulthood (Study 2). We compared first-
order judgments (1-REL) of traits associated with oneself
or with another individual (z.B., How patient are you?
[Self condition]; How patient is your friend? [Other con-
dition]) with second-order judgments (2-REL) about how
these judgments related to each other (How much more
patient are you than your friend? [Comparison condi-
tion]). Our paradigm also included a control nonsocial
Aufgabe, in which participants were asked to rate character-
istics of towns. Our aim was to assess (1) how perfor-
mance on a task requiring relational integration of social
or nonsocial traits develops between late childhood and

1740

Zeitschrift für kognitive Neurowissenschaften

Volumen 29, Nummer 10

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Erwachsensein, (2) how neural activity underlying these pro-
cesses develops between early adolescence and adult-
hood, Und (3) whether there is domain-specific activation
for the relational integration of social versus nonsocial
Information.

In terms of behavior, we predicted improvements in
relational integration with age, both in terms of RT and
the consistency of participants’ responses between
1-REL and 2-REL judgments. In terms of BOLD signal,
we expected domain-general activations associated with
relational integration in the RLPFC, dorsolateral PFC,
and parietal cortex. We also predicted that there would
be additional domain-specific activations in parts of the
social brain network associated with the people task, spe-
cifically regions involved in processing social information
and mentalizing (Meyer, Taylor, & Lieberman, 2015;
Dumontheil & Blakemore, 2012; Meyer, Spunt, Berkman,
Taylor, & Lieberman, 2012; Raposo et al., 2011). Endlich,
we predicted that the RLPFC would show increased spec-
ificity of activation for 2-REL versus 1-REL judgments in
adults compared with adolescents (Dumontheil, 2014)
and that the MPFC would show greater activation in ad-
olescents than adults in the social versus nonsocial task
(Blakemore & Robbins, 2012; Blakemore, 2008).

STUDY 1: BEHAVIORAL STUDY

Teilnehmer

The data analyzed here are part of a larger project in male
and female children, adolescents, and adults who per-

formed a set of six tasks and provided saliva samples
for genetic analyses (Kilford, Dumontheil, Holz, &
Blakemore, 2015; Dumontheil et al., 2014). The present
analysis focused on the social and nonsocial comparison
task and the Wechsler Abbreviated Scale of Intelligence
( WASI; Wechsler, 1999) assessment. The data presented
here are from 325 participants aged between 11 Und
39 Jahre (n = 160 Erwachsene, n = 165 children and adoles-
cents). From an original sample of 399 Teilnehmer, eins
was excluded because of a diagnosis of Turner syndrome,
one was excluded because of a diagnosis of Asperger
syndrome, four were excluded because of a task program-
ming error, two were excluded because they interrupted
the task early, one participant did not have time to com-
plete this task, and data were lost from 15 Teilnehmer. In
addition, as only four male participants were younger than
11 Jahre (vs. 26 female participants), all participants youn-
ger than 11 years were excluded from further analyses.
Children and adolescents were recruited from schools in
and around London and were tested in their school, Und
adults were recruited from the University College London
(UCL) Psychology Department volunteer database and
word of mouth and tested in the laboratory. Written in-
formed consent was obtained from participants or from
the parent/guardian of participants under 18 Jahre alt.
Adult participants were remunerated for their time. Der
study was approved by the UCL ethics committee.

Child and adolescent participants were divided accord-
ing to age into three groups spanning 2 oder 3 Jahre, Und
there were four adult groups (Tisch 1). Verbal ability

Tisch 1. Demographics of Participants in the Behavioral (Study 1) and fMRI (Study 2) Studien

Age Group

Behavioral study (Study 1)
11–12 years

13–14 years

15–17 years

20–22 years

23–25 years

26–28 years

29–39 years

fMRT-Studie (Study 2)
10–16 years

22–31 years

Sex

F/M

39/27

30/27

20/27

20/22

28/22

20/19

10/18

Alter

Verbal IQ

Range

Mean (SD)

Range

Mean (SD)

11.10–12.98

13.06–14.97

15.01–17.99

20.34–22.97

23.01–25.96

26.06–28.68

29.00–39.39

12.05 (0.51)

13.92 (0.58)

16.18 (0.92)

21.93 (0.69)

24.55 (0.92)

27.30 (0.81)

33.22 (2.80)

87–137

84–140

84–134

97–137

81–137

84–129

94–129

114.4 (12.0)

113.1 (12.7)

114.0 (12.4)

118.1 (9.5)

113.7 (13.7)A

107.6 (12.2)B

115.5 (9.5)

Female only

10.98–16.83

22.22–31.67

14.10 (1.89)

25.89 (2.76)

93–134

107–131

116.8 (11.4)

119.9 (6.7)C

aWASI data were missing for one participant.

bWASI data were missing for three participants.

cWASI data were missing for one participant.

Magis-Weinberg, Blakemore, and Dumontheil

1741

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Figur 1. Example of stimuli for each task and condition. The Vowels condition was only included in Study 2. In the People task, Teilnehmer waren
asked: “How much do you think the following words apply to you/your friend?” (Self/Other) or “How much do you think the following words
apply to you compared with your friend?” (Comparison). On the rating scale, 1 indicated “not at all” and 6 indicated “very much so” in the
Self and Other conditions, wohingegen 1 indicated “much less so” and 6 indicated “much more so” in the Comparison condition. All text was presented
in white on a black background.

was measured using the vocabulary subtest of the WASI
( Wechsler, 1999). A two-way (Age group, Sex) ANOVA
indicated that there was a significant difference in verbal
IQ between age groups (F(1, 307) = 2.91, p = .009).
Paired post hoc comparisons demonstrated that the
age groups of 11–12 and 13–14 years had lower mean
verbal IQ than the age group of 20–22 years ( ps < .05) and that the age group of 26–28 years had lower mean verbal IQ than all other age groups ( ps < .05; Table 1). Only the difference between the age groups of 20–22 and 26–28 years survived Bonferroni correction ( p = .001). There was no main effect of Sex on IQ (F(1, 307) = 2.34, p = .127), but there was a significant Sex × Age group interaction (F(6, 307) = 3.08, p = .006). Post hoc comparisons of male and female participants in each age group indicated that 11- to 12-year-old male participants had lower mean verbal IQ (109.1, SD = 12.2) than female participants (118.1, SD = 10.5, p = .002), whereas 23- to 25-year-old men had higher mean verbal IQ (118.6, SD = 11.1) than women (109.7, SD = 14.5, p = .023). Design and Stimulus Material The task had two within-participant factors (Task: people or town; Condition: self, other, or comparison) and one between-participant factor (Age group: seven levels), re- sulting in a 2 × 3 × 7 mixed factorial design. The task was computer based and adapted from the fMRI study by Raposo et al. (2011). The task was administered as part of a single individual testing session of approximately 45– 50 min. It was the third task administered in the task set, and the WASI was administered as the sixth (and last) task. The experimenter started by asking participants to think of someone whom they knew quite well but who was quite different from them and to give his or her name. If participants did not respond, the experimenter suggested that they consider a close friend or a sibling who was quite different from them. Second, participants were asked to name the town where they lived (typically, London) and then pick a town that they knew quite well but that was quite different from London. Again, if partic- ipants did not respond, the experimenter suggested that they consider a town where they go on a holiday or where their grandparents live. Instructions were then presented on the screen and read aloud to the partici- pants, explaining the different types of judgment they would make during the task and the rating scale. Partici- pants used the index, middle, and ring fingers of both hands to respond. The task was programmed in Cogent (www.vislab.ucl.ac.uk/cogent_graphics.php) running in MATLAB (The MathWorks, Inc., Natick, MA) on a Dell 12-in. laptop or similar. Judgments were blocked according to Task and Condi- tion, and the order of the blocks was counterbalanced within and between participants. Each block started with an instruction screen indicating to participants what type of judgment they should make during that block. On each trial, this information was repeated at the top (e.g., “You”), an adjective was presented in the middle of the screen, and a rating scale from 1 to 6 was provided at the bottom of the scale (Figure 1). Once participants had pressed a key to indicate their response, the corresponding number on the scale (1–6) was highlighted in red for 200 msec, followed by a 200-msec blank screen, and then a new trial started. There were 10 trials per block and 12 blocks in total, with two blocks of each of the six conditions (People or Town × Self, Other, or Comparison), that is, 20 trials in total per 1742 Journal of Cognitive Neuroscience Volume 29, Number 10 condition. A list of 20 adjectives was used for this study (fabulous, weird, loud, charming, romantic, crazy, pleasant, lovely, wild, perfect, busy, unique, friendly, cool, unusual, boring, dull, rich, quiet, and popular). All adjectives were presented once in each condition of each task. Data Analysis Data were analyzed with SPSS 21 (IBM Corp., Armonk, NY ). Median RTs were calculated for each Task and Condition. A 2 (Task) × 3 (Condition) × 7 (Age group) × 2 (Sex) mixed-model repeated-measures ANOVA (rmANOVA) was performed on the median RT data. Because of the nature of the task, a measure for accuracy is not avail- able (we do not know objectively how “friendly” a par- ticipant or their friend is). Instead, we ran Spearman correlations to test whether participants were con- sistent in their response, that is, whether there was a positive correlation between their ratings in the Com- parison judgment and the difference in ratings between the Self and Other judgments, across the set of 20 adjectives. For example, if a participant rated herself as “6” and her friend as “3” for “friendly,” a rating of “5” in the Comparison judgment (“How much more friendly do you think you are compared with your friend?”) would be consistent with the individual judg- ments. Spearman r correlation values obtained for each participant in each task were transformed using Fisher’s z transformation (z = 0.5 × ln ((1 + r)/(1 − r)), resulting in consistency scores. A 2 (Task) × 7 (Age group) × 2 (Sex) mixed-model rmANOVA was performed on the consistency data. Post hoc comparisons investigating pairwise differ- ences between age groups were Bonferroni corrected. Greenhouse–Geisser correction for nonsphericity was applied when necessary. Estimated means and standard errors from the rmANOVAs are reported in the text and in the figures. Results RTs A 2 (Task) × 3 (Condition) × 7 (Age group) × 2 (Sex) mixed rmANOVA showed a main effect of Condition (F(1.4, 435.6) = 500.00, p < .001, ηp 2 = 0.62), whereby partici- pants responded faster in the Self (M = 1944 msec, SD = 36 msec) than the Other (M = 1989 msec, SD = 35 msec) condition ( p = .042) and in both Self and Other conditions than in the Comparison condition (M = 2811 msec, SD = 56 msec; ps < .001); a main effect of Task (F(1, 311) = 12.04, p < .001, ηp 2 = 0.04), with slower RTs in the People (M = 2292 msec, SD = 44 msec) than the Town (M = 2203 msec, SD = 39 msec) task; and a main effect of Age group (F(6, 311) = 2.48, p = .024, ηp 2 = 0.05) but no main effect of Sex (F(1, 311) = 0.05, p = .818). Pairwise post hoc comparisons indicated that the 11- to 12-year age group responded more slowly than the 20- to 22-year age group ( p = .019) and marginally slower than the 26- to 28-year age group ( p = .081). No other pairwise com- parison was significant. The only significant interaction was between Condition and Age group (F(8.4, 435.6) = 3.64, p < .001, ηp 2 = 0.07). This was followed up by first entering the two 1-REL judgments in a 2 (Task) × 7 (Age group) × 2 (Sex) rmANOVA. This analysis showed no main effect of Age group (F(6, 311) = 1.54, p = .165) and no Age group × Condition interaction (F(6, 311) = 1.35, p = .233), in- dicating that the interaction was driven by the 2-REL, Comparison condition. Investigated separately, this con- dition showed a main effect of Age group (F(6, 311) = 3.61, p = .002, ηp 2 = 0.07). Post hoc comparisons indi- cated that the 11- to 12-year age group responded slower on average than the 20- to 22- and 23- to 25-year age groups ( ps < .01; Figure 2A). To further investigate the inter- action, the difference in median RT between the Comparison condition (2-REL, relational integration) and Self and Other conditions (1-REL judgments) was calculated. A 2 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 9 / 1 2 0 9 / 1 1 7 0 3 / 9 1 1 7 9 3 5 9 3 / 0 1 5 4 7 8 o 6 c 7 n 1 _ 1 a / _ j 0 o 1 c 1 n 5 3 _ a p _ d 0 1 b 1 y 5 g 3 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j / . t f u s e r o n 1 7 M a y 2 0 2 1 Figure 2. Mean RT and consistency scores as a function of age group. (A) Study 1: mean RTs as a function of Age group and Condition. (B) Study 1: mean difference in RTs between the Comparison and Self and Other conditions as a function of Age group. (C) Study 1: mean consistency scores as a function of Age group. (D) Study 2: mean consistency scores as a function of Age group. Error bars represent SE. † **p < .01, ***p < .001 (Bonferroni corrected). y = years. p < .1, *p < .05, Magis-Weinberg, Blakemore, and Dumontheil 1743 (Task) × 7 (Age group) × 2 (Sex) rmANOVA with post hoc pairwise comparisons indicated that the 11- to 12-year age group was relatively slower in 2-REL than 1-REL trials than the 13- to 14-, 20- to 22-, 23- to 25-, and 26- to 28-year age groups ( ps < .05; Figure 2B). Consistency A 2 (Task) × 7 (Age group) × 2 (Sex) mixed rmANOVA was performed on consistency, which is the Fisher z- transformed Spearman correlation between participants’ answers in the Comparison condition and the difference between their answers in the Self and Other conditions. The main effect of Task was significant (F(1, 311) = 21.74, p < .001, ηp 2 = 0.07), with greater consistency in the Town (M = 0.713, SD = 0.025) than in the People (M = 0.586, SD = 0.021) task. In both tasks, mean con- sistency was positive, indicating some degree of consis- tency in participants’ responses across conditions. The main effect of Age group was also significant (F(6, 311) = 15.15, p < .001, ηp 2 = 0.23). No other main effect and no interaction were significant. Post hoc comparisons indi- cated that the 11- to 12- and 13- to 14-year age groups did not differ from each other and were less consistent than all older age groups ( ps < .05), which did not differ from each other (Figure 2C). In summary, participants were slightly slower in the Other than in the Self condition and in the People than in the Town task. However, there was a considerable dif- ference in RT between 2-REL and 1-REL judgments, which decreased between 11–12 and 13–14 years old. Consistency was also higher in the Town than in the People task and improved between 13–14 and 15– 17 years old. There was no interaction between Task and Age group, suggesting no evidence of a developmental difference in relational integration between the social and nonsocial tasks. STUDY 2: NEUROIMAGING STUDY Methods Participants Thirty-nine female participants aged between 10 and 31 years (n = 20 adults, n = 19 children and adolescents) took part in the neuroimaging study (Table 1). Seven ad- olescents and two adults had taken part in Study 1, with an interval of between 4 and 10 months between the test- ing sessions. Only female participants were included to reduce variability in the sample due to sex differences in brain development (Herting, Maxwell, Irvine, & Nagel, 2012; Raznahan et al., 2011). Sex differences were not found in Study 1 or in a previous behavioral and neuro- imaging study of visuospatial relational reasoning devel- opment ( Wendelken et al., 2011). However, other behavioral studies have reported sex differences in men- talizing (e.g., Charman, Ruffman, & Clements, 2002) and in relational reasoning (Lynn & Irwing, 2004). Because we were unable to collect a sample large enough to investi- gate sex differences, we chose to maximize the homoge- neity of our sample by only including female participants. Participants were reimbursed £20 and their travel ex- penses for taking part in the study. The study was approved by the UCL research ethics committee. Partici- pants were divided into two groups, adolescents and adults. Adolescents were combined into a single group because of the sample size, with a focus on investigating the development of the neural correlates of relational reasoning, whereas Study 1 had focused on developmen- tal changes in performance. The two groups were matched on estimated IQ (t(36) = 1.02, p = .314), which was assessed using the vocabulary and matrices subtests of the WASI ( Wechsler, 1999). Design and Stimulus Material The fMRI task had two within-participant factors (Task: People or Town; Condition: Self, Other, Comparison, or Vowels) and one between-participant factor (Age group: adults, adolescents), resulting in a 2 × 4 × 2 mixed design. Participants were first trained on the task outside the scanner. After going through the four types of question for each Task, participants performed one block of three trials for each Task and Condition. Partic- ipants then performed four scanning runs as well as a structural scan between the second and third task runs. After scanning, participants completed the Interpersonal Reactivity Index (IRI; Davis, 1980), which provides mea- sures of four components of empathy (empathic concern [EC], fantasy, personal distress, and PT), and were as- sessed on the WASI. The IRI was included as it has been used in previous neuroimaging studies as a measure of individual differences in social cognition in everyday life (Meyer et al., 2012; Raposo et al., 2011). Meyer et al. (2012) found an association between memory load- dependent activity within mentalizing regions and scores on the PT scale. We therefore aimed to relate activity within mentalizing regions in Study 2 with this everyday life measure of PT. The paradigm was similar to the task described in Study 1, adapted from Raposo et al. (2011), with three differences. First, the fMRI task included a Vowels condi- tion in which participants were required to count the number of vowels in the adjective presented on the screen (“Control” condition used by Raposo et al., 2011). This condition matched visual and verbal process- ing and motor execution demands while minimizing rela- tional reasoning demands and, as such, was used as a baseline in the fMRI analyses. Regions of the social brain often show high activation at rest or during fixation phases, as part of the default mode network. Using an active baseline allowed the identification of activation of these brain regions, which was important for the People task. In addition, the words presented in the People and 1744 Journal of Cognitive Neuroscience Volume 29, Number 10 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 9 / 1 2 0 9 / 1 1 7 0 3 / 9 1 1 7 9 3 5 9 3 / 0 1 5 4 7 8 o 6 c 7 n 1 _ 1 a / _ j 0 o 1 c 1 n 5 3 _ a p _ d 0 1 b 1 y 5 g 3 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j f t / . u s e r o n 1 7 M a y 2 0 2 1 Town tasks differed, and using the Vowels condition as a baseline allowed us to control for BOLD signal differ- ences elicited by the presentation of these words. Finally, using a similar baseline to Raposo et al. (2011) facilitates comparison of the results of the two studies. Second, traits were different for the People and Town tasks in an attempt to make them more relevant to each category. Third, a fixed ISI of 100 msec was used. Participants performed two scanning runs of the Peo- ple and Town task, alternating in an ABAB or BABA order, counterbalanced across participants. Each run was com- posed of five blocks of each condition (Self, Other, Com- parison, and Vowels). The order of the conditions was fixed within a run and counterbalanced across runs and participants. After every Vowels block, there was a fixation block. Task blocks were preceded by a 1-sec instruction that specified the condition of the next block (e.g., “You,” “Sam,” “You compared with Sam,” “Vowels,” “London,” “Cambridge,” “London compared with Cambridge”) and was composed of three trials each. Participants had a maximum of 6.05 sec to input their response on each trial, during which time the stimulus remained on the screen. When participants responded, the number they pressed turned red, and the stimulus remained on the screen until 6.1 sec after the onset of the trial presentation. A blank screen was displayed during the ISI. Stimuli consisted of lists of 30 adjectives in each task, which were matched for number of letters, number of vowels, frequency, and familiarity (see Appen- dix). Each adjective was presented once in each of the four conditions. Half of the adjectives were presented in the first scanning run of a task, half in the second run. fMRI Acquisition Multislice T2-weighted echo-planar volumes with BOLD contrast (35 axial slices with a voxel resolution of 3 × 3 × 3 mm covering most of the cerebrum, repetition time = 2.975 sec, echo time = 50 msec, acquisition time = 2.925 sec) were obtained using a 1.5-T MRI scanner (Siemens TIM Avanto, Erlangen, Germany). Functional im- ages were acquired in four scanning runs lasting approxi- mately 8 min 40 sec each in which 174 volumes were obtained. The first four volumes of each run were discarded to allow for T1 equilibrium effects. A 3-D T1- weighted fast-field echo anatomical image lasting 5 min 30 sec was acquired after the first two functional runs for each participant. Data Analysis Behavioral data. A 2 (Task) × 4 (Condition) × 2 (Age group) mixed rmANOVA was performed on median RT data. A 2 (Task) × 2 (Age group) mixed rmANOVA was employed to analyze mean consistency, which was cal- culated in the same way as in Study 1. MRI data. MRI data were preprocessed and analyzed using SPM8 ( Wellcome Trust Centre for Neuroimaging, London, United Kingdom; www.fil.ion.ucl.ac.uk/spm/). Images were realigned to the first analyzed volume with a second-degree B-spline interpolation to correct for movement during the session. The bias-field-corrected structural image was coregistered to the mean, realigned functional image and segmented on the basis of Montreal Neurological Institute (MNI)-registered International Consortium for Brain Mapping tissue probability maps. Resulting spatial normalization parameters were applied to the realigned images to obtain normalized functional images with a voxel size of 3 × 3 × 3 mm, which were smoothed with an 8-mm FWHM Gaussian kernel. Realignment estimates were used to calculated frame- wise displacement (FD) for each volume, which is a com- posite, scalar measure of head motion across the six realignment estimates (Siegel et al., 2014). Volumes with an FD > 0.9 mm were censored and excluded from gen-
eral linear model estimation by including a regressor of
no interest for each censored volume. Scanning sessions
with more than 10% of volumes censored or a root mean
square (RMS) movement over the whole session greater
als 1.5 mm (one session for three participants, two ses-
sions for one participant) were excluded from the analy-
Schwester. Adolescent and adult participants significantly differed
in the number of overall censored volumes (Madolescents =
3.39, SD = 3.61; Madults = 0.19, SD = 0.38; P < .001), mean RMS translational movement (Madolescents = 0.32 mm, SD = 0.11 mm; Madults = 0.24 mm, SD = 0.07 mm; p = .005), and mean FD (Madolescents = 0.18 mm, SD = 0.08 mm; Madults = 0.10 mm, SD = 0.02 mm; p < .001). There was no difference between groups in terms of mean RMS rota- tional movement (Madolescents = 0.23 mm, SD = 0.12 mm; Madults = 0.17 mm, SD = 0.08 mm; p = .088). Scanning runs were treated as separate time series, and each series was modeled by a set of regressors in the general linear model. Runs of the People or Town Task were each modeled by six box-car regressors: four regressors corresponding to each Condition (Self, Other, Comparison, and Vowels), with a duration of 18.6 sec; In- structions, with a duration of 1 sec; and Fixation blocks, with a duration of 18.6 sec except for the last block, which had a duration of 39 sec. All regressors were con- volved with a canonical hemodynamic response function and, together with the separate regressors representing each censored volume and the mean over scans, com- prised the full model for each session. The data and model were high-pass filtered to a cutoff of 1/128 Hz. The second-level whole-brain analysis focused on rela- tional integration, that is, the main effect of Comparison (2-REL) versus Self and Other (1-REL) conditions, and on differences between social and nonsocial tasks. The 1-REL conditions, Self and Other, were thus combined within each task. Four first-level contrasts were calculated using the Vowels condition as a baseline within each task: People (Self, Other) − People Vowels (People SO), Magis-Weinberg, Blakemore, and Dumontheil 1745 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 9 / 1 2 0 9 / 1 1 7 0 3 / 9 1 1 7 9 3 5 9 3 / 0 1 5 4 7 8 o 6 c 7 n 1 _ 1 a / _ j 0 o 1 c 1 n 5 3 _ a p _ d 0 1 b 1 y 5 g 3 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j . t f / u s e r o n 1 7 M a y 2 0 2 1 People Comparison − People Vowels (People Comp), Town (Self, Other) − Town Vowels (Town SO), Town Comparison − Town Vowels (Town Comp). These con- trasts were then entered into a random effects analysis using a Participant × Age group (2) × Block type (4) flex- ible factorial design, modeling Participant as a main effect (to account for the repeated-measure nature of the data) and the Age group × Block type interaction. Main effects of Condition (Comparison > SO) Und
Task (People > Town and Town > People) and the inter-
action between the two factors and with Age group were
determined using the t statistic on a voxel-by-voxel basis.
Statistical contrasts were used to create SPMs thresholded
at p < .001 at the voxel level and at family-wise error (FWE) corrected p < .05 at the cluster level (correspond- ing to a minimum cluster size of 77 voxels determined with SPM8). Activations that survived whole-brain FWE correction at p < .05 at the voxel level are indicated. All coordinates are given in MNI space. Significant inter- actions were followed up by extracting the mean signal across all voxels of significant clusters with MarsBar (Brett, Anton, Valabregue, & Poline, 2002) and analyzing simple effects in SPSS using t tests (with Bonferroni correction for multiple comparisons). We performed exploratory correlation analyses be- tween consistency in ratings and individual differences in activation in the tasks. Relevant task contrasts were entered in a two-sample t test design modeling the two age groups separately, with the behavioral measure as a single covariate of interest. Correlations were run be- tween the contrasts [Comparison > SO] Und [Comparison/
Self/Other > Vowels] and the mean consistency across
tasks, between the contrast [People Comparison > SO]
and consistency in the People task, and between the
Kontrast [Town Comparison > SO] and consistency in the
Town task. In the same manner, we explored correlations
between individual differences in the [People > Town] Und
[People Comparison > SO] contrasts and the PT scale of
the IRI (see Meyer et al., 2015, for a similar approach).

Ergebnisse

Verhaltensergebnisse

RTs. There was a main effect of Task (F(1, 37) = 13.51,
p = .001, ηp
2 = 0.27). In contrast to Study 1, Teilnehmer

were slower in the Town (M = 2419 ms, SE = 69 ms)
relative to the People (M = 2282 ms, SE = 63 ms) Aufgabe.
There was a main effect of Condition (F(1.8, 66.8) = 29.17,
P < .001, ηp 2 = 0.44; Table 2). Pairwise comparisons with Bonferroni correction revealed that participants were slowest in the Comparison condition relative to all other conditions (MComparison = 2638 ± 79 msec, MSelf = 2180 ± 67 msec, MOther = 2196 ± 62 msec, MVowels = 2388 ± 77 msec; all ps < .005). The Vowels condition was the next slowest (all ps < .05). Self and Other conditions did not differ sig- nificantly from one another ( p > .05). In contrast to Study 1,
there was no main effect of Age group (F(1, 37) = 2.21).
There was a significant interaction between Task and
Condition (F(3, 111) = 3.14, p = .028, ηp
2 = 0.08). Das
was followed up by analyzing the data in the People and
Town tasks separately. In both the People and Town
tasks, participants were slower in Comparison than Self
and Other trials (all ps < .001). In the People task, par- ticipants were slower in Vowels than Self and Other trials (all ps < .05). The two-way interaction is driven by a greater difference between Comparison and Vowels trials in the Town task (MComp-Vowels = 342 msec) than in the People task (MComp-Vowels = 157 msec, p = .008), whereas the difference between Comparison and Self and Other trials did not differ between tasks ( ps > .05). Im Gegensatz
to Study 1, there was no significant interaction between
Condition and Age group (F(1.8, 66.8) = 0.58). In line
with Study 1, there were no significant interactions
between Task and Age group (F(1, 37) = 1.43) or among
Condition, Task, and Age group (F(2.7, 98.8) = 1.76).

Consistency. As in Study 1, participants were consistent
overall, with positive correlations between the 1-REL and
2-REL ratings. Similar to the pattern in Study 1, there was
a trend effect of Age group (F(1, 37) = 3.46, p = .071, ηp
2 =
0.09; Figure 2D), with lower consistency in adoles-
cents than adults. There was also a main effect of Task
(F(1, 37) = 18.04, P < .001, ηp 2 = 0.33): Consistency was lower for People than for Town (MPeople = 0.74 ± 0.05, MTown = 0.96 ± 0.07). As in Study 1, the interaction between Task and Age group was not significant (F(1, 37) = 0.18). IRI. Analyses of the subscales of the IRI revealed signif- icantly higher PT and EC scores for adults (MPT = 19.5, SE = 0.91; MEC = 20.9, SE = 1.1) than for adolescents Table 2. Mean RT and SE (msec) for Each Task (People, Town) and Condition (Self, Other, Comparison, Vowels) in Study 2 Self Other Comparison Vowels People Town Adolescents 2215 (110) 2123 (94) 2570 (108) 2503 (112) Adults 2057 (107) 2112 (92) 2460 (106) 2212 (109) Adolescents 2333 (100) 2378 (96) 2904 (136) 2529 (120) Adults 2115 (98) 2171 (94) 2618 (133) 2309 (117) 1746 Journal of Cognitive Neuroscience Volume 29, Number 10 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 9 / 1 2 0 9 / 1 1 7 0 3 / 9 1 1 7 9 3 5 9 3 / 0 1 5 4 7 8 o 6 c 7 n 1 _ 1 a / _ j 0 o 1 c 1 n 5 3 _ a p _ d 0 1 b 1 y 5 g 3 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t f / . u s e r o n 1 7 M a y 2 0 2 1 Table 3. Summary of Neuroimaging Results Main effect of condition (Comparison > SO)

L/R

MNI (X, j, z)

Z Score

Cluster Size

Lingual gyrus

Calcarine gyrus

Lingual gyrus

Precuneus

Middle occipital gyrus

Middle temporal gyrus

Inferior parietal gyrus

Fusiform gyrus

Inferior frontal gyrus

Precentral and middle frontal gyri

Middle cingulate cortex and pre-SMA

Inferior frontal gyrus

Middle frontal gyrus

Inferior frontal gyrus

Middle frontal gyrus

Middle and superior frontal gyri

Precentral gyrus

Inferior and middle frontal gyri

Main effect of task (People > Town)

MPFC

ACC

Anterior insula

Precuneus and posterior cingulate cortex

Main effect of task (Town > People)

Lingual gyrus

Calcarine gyrus

Middle occipital gyrus

Superior occipital gyrus

Fusiform and parahippocampal gyri

Fusiform gyrus

−9, −85, −14

0, −85, 1

−21, −79, −14

18, −79, −14

3, −61, 46

30, −79, 19

−30, −76, 22

−48, −46, 10

−45, −46, 43

27, −64, −5

−48, 14, 25

−39, −1, 55

9, 20, 46

−36, 20, 22

30, 14, 43

48, 26, 31

30, 23, 52

30, 59, 7

30, −4, 46

−39, 47, −2

6, 53, 13

−3, 53, 13

−6, 44, 1

30, 17, −17

6, −52, 28

9, −49, 4

15, −52, 13

−12, −55, 10

−33, −76, 28

36, −70, 37

−21, −64, 28

24, −76, 46

>8a

7.31A

6.53A

6.22A

6.13A

5.90A

6.59A

5.78A

5.77A

5.68A

5.55A

5.32A

5.03A

4.56A

4.44

4.91A

7.22A

7.11A

5.95A

5.74A

5.26A

4,959B

1,351B

819B

95B

1,649B

132B

D
Ö
w
N
l
Ö
A
D
e
D

F
R
Ö
M

/
J

T
T

F
/

ich
T
.

:
/
/

/
J

u
S
e
R

Ö
N

1
7

M
A
j

2
0
2
1

>8a

2,164B

7.65A

7.17A

6.08A

5.90A

5.25A

4.62A

−30, −37, −14

>8a

30, −31, −17

6.97A

192B

302B

Magis-Weinberg, Blakemore, and Dumontheil

1747

MNI (X, j, z)

Z Score

Cluster Size

Tisch 3. (Fortsetzung )

Inferior temporal gyrus

Parahippocampal gyrus

Middle cingulate cortex

Precentral gyrus and inferior frontal operculum

Postcentral and precentral gyri

L/R

54, −46, −11

21, −13, −20

9, −34, 34

−42, 8, 28

60, −10, 31

Interaction adolescents > adults [(Town Comparison > SO) > [People (Comparison > SO)]

Anterior insula

Superior temporal pole

33, 17, −8

39, 26, 4

45, 14, −20

4.13

3.73

4.78A

4.58A

3.93

4.26

3.71

3.59

181B

108B

178B

Coordinates and Z scores are listed for regions showing a significant difference in BOLD signal for the main effect of Condition [Comparison > SO],
the main effect of Task [People > Town] oder [Town > People], and the interaction between Condition, Task, and Age Group [(Adolescents > Adults
[(Town Comparison > SO) > [People (Comparison > SO)]]. Region labeling was done using automatic anatomical labeling (Tzourio-Mazoyer et al.,
2002). BA labeling of peak of activations was done using MRIcron. L/R = left/right hemisphere.

aVoxels where pFWE < .05 at the voxel level. bClusters where pFWE < .05 at the cluster level, with a cluster-defining threshold of p < .001 uncorrected at the voxel level. (MPT = 14.1, SE = 0.94; MEC = 16.8, SE = 1.1; all ps < .05). Pearson correlation coefficients were computed to assess the relationship between PT and performance in the task. There was no correlation between PT and Con- sistency in the People task (r = −.187, p = .255). There was also no correlation between PT and mean median RT for the Self (r = −.021, p = .897), Other (r = .006, p = .973), or Comparison (r = .068, p = .680) conditions in the People task. Relational integration. A broad bilateral network of frontoparietal, temporal, and occipital regions, including bilateral RLPFC, showed increased BOLD signal in Com- parison versus SO conditions (Table 3 and Figure 3A), that is, in 2-REL as opposed to 1-REL processing. In- creases in BOLD signal were observed in a large posterior cluster extending into bilateral occipital and lingual gyri, calcarine sulcus, and inferior parietal lobule and in ante- rior clusters in the precentral gyrus, pre-SMA, and inferior and middle frontal gyri. fMRI Results Whole-brain analyses contrasted the Comparison condi- tion to the combined Self and Other (SO) conditions in the People and Town tasks. The Vowels condition served as an active baseline. Social Information Processing When comparing the People task with the Town task, that is, when the information to be processed was of social (traits of participant or a friend) versus nonsocial Figure 3. fMRI results across age groups. (A) Main effect of Condition. Regions showing increased BOLD signal in Comparison (2-REL) compared with Self and Other (1-REL) conditions are rendered on the SPM8 surface mesh template. From left to right: lateral view of the left hemisphere, medial and lateral views of the right hemisphere. (B) Main effect of Task. Regions showing increased BOLD signal in the People compared with the Town task are rendered on the SPM8 surface mesh template (medial view of the right hemisphere). 1748 Journal of Cognitive Neuroscience Volume 29, Number 10 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 9 / 1 2 0 9 / 1 1 7 0 3 / 9 1 1 7 9 3 5 9 3 / 0 1 5 4 7 8 o 6 c 7 n 1 _ 1 a / _ j 0 o 1 c 1 n 5 3 _ a p _ d 0 1 b 1 y 5 g 3 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j / . f t u s e r o n 1 7 M a y 2 0 2 1 Figure 4. fMRI results of the interaction between Task, Condition, and Age group. On the left, the right anterior insula cluster showing a three-way interaction between Task, Condition, and Age group is shown on an average structural scan of all participants in the study (left: y = 21, right: z = 0). The contrast was thresholded at p < .001 uncorrected at the voxel level, pFWE < .05 at the cluster level. On the right, parameter estimates extracted from this cluster are plotted in a bar chart to illustrate the three-way interaction. Error bars represent SE. † p < .1, *p < .05, **p < .01, ***p < .001. (characteristics of towns) nature, increased BOLD signal was observed in clusters in the MPFC, insula, and precuneus (Table 3 and Figure 3B). The reverse contrast revealed increased BOLD signal in a large cluster extend- ing into bilateral calcarine gyri, middle and superior oc- cipital gyri, and bilateral clusters in the fusiform and parahippocampal gyri extending into the medial tempo- ral gyri, middle cingulate cortex, bilateral precentral and postcentral gyri, and left inferior frontal cortex (Table 3). Age group differences. There was no two-way interac- tion between Task and Age group or between Condition and Age group; however, whole-brain analyses showed a significant three-way interaction between Task, Condi- tion, and Age group in BOLD signal in the right insula (see Table 3 and Figure 4). The mean parameter estimates in this cluster were calculated, and the interac- tion was followed up by running 2 (Condition) × 2 (Age group) mixed rmANOVAs in each Task separately. There was an interaction between Condition and Age group in the People task (F(1, 37) = 7.20, p = .011, ηp 2 = 0.16) and in the Town task (F(1, 37) = 8.64, p = .006, ηp 2 = 0.19). These interactions were further explored by compar- ing SO and Comparison conditions within each age group. In the People task, adolescents showed greater ac- tivation in the SO than the Comparison condition ( p = .026), whereas the conditions did not differ in adults ( p = .132). In the Town task, adolescents reversely showed greater activation in the Comparison than the SO condition ( p = .018), whereas again, there was no difference in adults ( p = .176). Covariate Analyses Whole-brain analyses were performed to investigate cor- relations between the behavioral measure of Consistency and BOLD signal during the task. No correlation between Consistency scores and individual differences in BOLD signal in the contrasts [Comparison > SO], [Comparison/

Self/Other > Vowels], [People Comparison > People SO],
Und [Town Comparison > Town SO]) was observed.
Further whole-brain analyses showed that BOLD signal in
Die [People > Town] Und [People Comparison > People
SO] contrasts was not significantly related to the PT scale
of the IRI.

DISKUSSION

We performed separate behavioral and fMRI studies aim-
ing to disentangle general and specific processes under-
lying relational integration of social information between
late childhood and adulthood. We found behavioral evi-
dence for general development of social and nonsocial
relational reasoning. We discovered similar patterns of
neural activity for adolescents and adults showing do-
main general involvement of the frontoparietal cortex
areas associated with relational integration for both
social and nonsocial relations and domain-specific in-
volvement of the social brain for the manipulation of
social information.

Behavioral Findings

Relational Integration

In Study 1, the large behavioral study, we found earlier
improvements in performance with age for RT and later
improvements in consistency from late childhood to
Erwachsensein. Across age groups, RTs were slower in the
Comparison condition, which required relational integra-
tion, than the Self and Other conditions, which required
processing of a single relation. These results are in line
with the robust processing speed costs observed in par-
adigms comparing relational integration with simpler re-
lational processing (Dumontheil et al., 2010; Crone et al.,
2009). In terms of relational integration performance, Re-
sults show a pattern of early improvement in RT between
ages of 11–12 and 13–14 years, with no further changes at
older ages (Figure 2B), and improvements between ages

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of 13–14 and 15–17 years for the consistency measure,
with no improvements at older ages (Figure 2C). Notiz
that verbal IQ was not matched across age groups;
Jedoch, the differences in verbal IQ did not directly
map onto the observed age effects. Insbesondere, Dort
was no difference in IQ between 11- Zu 12-, 13- Zu 14-,
Und 15- to 17-year age groups, the age range where the
key developmental changes were observed.

Ähnlich, in Study 2, the fMRI study, RTs were slower
in the Comparison than in the Self and Other conditions.
Relational integration was slower in adolescents than
Erwachsene. There was also a trend for poorer consistency in
the adolescents, which fits with the findings of the behav-
ioral study. The less robust behavioral results in Study 2
compared with Study 1 were likely due to the smaller
sample size in the imaging study.

Gesamt, we observed that late childhood and early ad-
olescence are associated with poorer relational integra-
tion performance than adulthood (Figure 2B). Das
pattern fits with previous findings from visuospatial rela-
tional integration tasks, which indicate poorer relational
integration accuracy in 8- to 12-year-olds than in adults
(Crone et al., 2009), improvements in accuracy between
9- and 19-year-olds (Rosso, Jung, Femia, & Yurgelun-
Todd, 2004), and poorer combined accuracy and RT in
7- to 9-year-olds than in 14- to 17-year-olds (Dumontheil
et al., 2010; reanalyzed in Dumontheil, 2014), although
note that Wendelken et al. (2011) did not find age differ-
ences in 7- to 18-year-olds (see Dumontheil, 2014, for a
Rezension). This study is consistent with a previous investi-
gation of the development of the integration of semantic
information using an analogical reasoning task, welche dm-
onstrated poorer performance in 6- to 13-year-olds than
bei Erwachsenen (Wright, Matlen, Baym, Ferrer, & Bunge, 2008).

Social Information Processing

Developmental improvements in RT for relational inte-
gration did not vary as a function of the type of informa-
tion. Jedoch, main effects of task across age were
observed. In Study 1, RTs were faster overall for Town
than People, whereas the opposite pattern was observed
in Study 2 in which RTs were faster overall for the People
task regardless of the level of relational processing,
which is in line with previous findings of benefits in per-
formance when stimuli are social rather than symbolic
(Dumontheil, Hillebrandt, Apperly, & Blakemore, 2012;
den Ouden, Frith, Frith, & Blakemore, 2005).

Both adolescents and adults showed increased speed
for social information. Ähnlich, although consistency
was overall greater in the nonsocial task, domain-general,
not social-specific, developmental changes were ob-
serviert. This is at odds with studies showing increased
sensitivity to social stimuli during adolescence (Foulkes
& Blakemore, 2016). This might be due to the low arousal
and/or affective demands of the current task and should
be explored in further studies. Außerdem, poorer over-

all consistency in the social task may be due to the greater
complexity and variability of people’s traits compared
with towns’ characteristics; this difference would apply
to both adolescents and adults. Zum Beispiel, my friend
Sam may be funny sometimes, but at other times, he is
quite grumpy, while London is always busy.

Slight discrepancies between the findings from Studies
1 Und 2 may be explained by methodological differences.
Study 1 had a larger sample than Study 2, reducing the
power needed to detect developmental changes in per-
Form. In Study 1, the adjectives were the same for
both the People and Town tasks. In Study 2, to maximize
the mentalizing requirements of the People task, we used
different adjectives for each task, which were more di-
rectly applicable to people or towns. The fMRI task was
not self-paced. These factors may have affected the be-
havioral results.

Our behavioral findings provide some evidence for dif-
ferential performance for social information, regardless
of relational level, for both adolescents and adults. Fur-
thermore, we provide evidence for domain-general
development of relational integration of simple relations,
which does not differ as a function of the social or
nonsocial nature of the semantic information being
processed.

Neuroimaging Findings

Relational Integration

Relational integration was associated with greater activa-
tion in a large bilateral frontoparietal network including
the RLPFC in both the People and Town tasks. A similar
pattern of activation was observed by Raposo et al. (2011)
in the Comparison versus Other contrast. These results
further support the involvement of RLPFC and the infe-
rior parietal cortex in relational integration ( Wendelken
et al., 2012; Crone et al., 2009). By adapting the task by
Raposo et al., we are able to directly compare manipula-
tion of social and nonsocial information and provide evi-
dence for domain-general recruitment of the RLPFC
through adolescence and adulthood across social and
nonsocial domains.

Gesamt, we did not find evidence of an interaction be-
tween relational integration and social versus nonsocial
Aufgabe: Both networks were recruited in parallel for rela-
tional integration and social demands. This parallel
recruitment of the two networks is similar to that ob-
served by Meyer et al. (2012, 2015) in their social working
memory task. Jedoch, these studies showed that MPFC
activation associated with social working memory was
modulated by working memory load (Meyer et al.,
2012, 2015), whereas in this study, MPFC activation was
not modulated by the number of relations participants
had to consider. Ähnlich, although Meyer et al. (2012)
found that PT on the IRI scale was positively associated
with social working memory load-dependent activity

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within the MPFC and posterior cingulate cortex in adults,
we found no association between self-reported PT on this
questionnaire and behavior or brain activity in our task. A
possible source of this difference in findings is that social
cognitive load in the Meyer et al. (2012) study was higher
than in this study, with the requirement to compare two,
three, or four individuals, whose names were maintained
in working memory, on given personality traits. In diesem
Studie, our participants only compared two individuals,
and the relevant information remained on the screen
over the duration of the trial. These differences may
have contributed to the lack of observed association be-
tween performance, MPFC activation, and self-reported
real-life PT.

We did not observe developmental differences in acti-
vation in the RLPFC during relational integration across
tasks in whole-brain analyses. Developmental differences
have been reported in this brain region (z.B., Dumontheil
et al., 2010; Crone et al., 2009). Jedoch, in the study by
Crone et al., the age effects were mainly due to differ-
ences in time course of activations evident in their
event-related design, which our block design did not
allow us to test. In our previous study, age group effects
were observed in ROI versus whole-brain analyses only
(Dumontheil et al., 2010). Relational reasoning studies
have traditionally involved demanding visuospatial rea-
soning tasks, such as the Raven Progressive Matrices. Es
might be that semantic reasoning about traits of people
and towns is not demanding enough to tax adolescents
in the same way.

Our results suggest domain-general recruitment of the
RLPFC through adolescence and adulthood, independent
of whether the information being manipulated is social or
nonsocial. These results are therefore in line with the
finding that the integration of visuospatial or semantic re-
lations elicits similar activation of the relational integra-
tion network ( Wendelken et al., 2012).

Social vs. Nonsocial Information Processing

Social information was associated with greater activation
in the precuneus and MPFC in both adolescents and
Erwachsene. These results are in line with a large body of
literature that documents the involvement of these re-
gions when processing social information (z.B., see Van
Overwalle, 2009, for a meta-analysis). Beachten Sie, dass, although
towns can be considered social to some extent, as one
can imagine the population of individuals living there,
characteristics of towns were considered to be less social
than traits of people.

Similar to this study, the investigation of social rela-
tional reasoning in adults by Raposo and colleagues
(2011) reported greater MPFC activation in Self, Other,
and Relational (Comparison) conditions when contrasted
to a Vowel judgment condition. Jedoch, in contrast to
our findings, Raposo et al. (2011) observed activation
across ventral and dorsal MPFC in the Other versus Self

contrast and no activation in the Self > Other contrast.
This difference between the two studies may be due to
the precise question participants were asked to answer.
In this study, participants simply rated how funny (oder
other adjectives) sie waren, or their friend was, wohingegen
in the Raposo et al. (2011) Studie, participants always
rated how pleasant or unpleasant they found a concept
(z.B., tower) or how pleasant or unpleasant they thought
their friend would find this concept. It is possible that
this latter question elicited greater mentalizing by asking
participants to put themselves in their friend’s shoes
rather than asking their own opinion. Gesamt, our results
suggest social-specific recruitment of the MPFC during
adolescence and adulthood for social information for
both simple relations and integration across levels.

Interaction between Task, Condition, and Age Group

One neural difference between age groups was observed.
At the cluster-corrected level, the right anterior insula
showed a significant three-way interaction between Con-
dition, Task, and Age group, driven by differential recruit-
ment according to the domain (social vs. nonsocial) Und
the relational integration requirements with age. Obwohl
these results were not significant with an FWE-corrected
threshold at the voxel level, they replicate the pattern of
decreased activation with age in the anterior insula observed
in a visuospatial relational reasoning task (Dumontheil
et al., 2010). Functional changes in the anterior insula
might reflect the maturation of neurocognitive strategies,
which possibly include changes in task-specific connec-
tivity between brain regions (z.B., see Bazargani et al.,
2014; Dumontheil, 2014; and Dumontheil et al., 2010, für
discussions). This neuroimaging finding does not directly
map onto behavioral differences between the age groups.
In a previous study, we similarly observed that develop-
mental changes in anterior insula activation during rela-
tional reasoning were not accounted for by individual
differences in performance on the task (Dumontheil
et al., 2010). Beyond differences in the sensitivity of be-
havioral and brain imaging measures (z.B., evidenced by
greater sensitivity of neuroimaging data than behavioral
data to genetic differences; Dumontheil et al., 2011), dif-
ferences may be due to the fact that behavior reflects a
large combination of factors beyond the block-related acti-
vations measured in the current fMRI paradigm, wie zum Beispiel
event-related activations, which may have had compen-
satory effects on performance.

Abschluss

We aimed to investigate the development of perfor-
mance in social and nonsocial relational reasoning and
their associated neural substrates. The paradigm required
participants to make first- and second-order relational
judgments about social and nonsocial information. Data
from a behavioral study and an fMRI study demonstrated

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development of social and nonsocial relational reasoning
in adolescence. These behavioral results with semantic
stimuli are in line with previous research using mostly
visuospatial relational reasoning tasks. We did not find
evidence of differential development of relational inte-
gration of social versus nonsocial information in our
behavioral studies. Ähnlich, the fMRI data showed that,
in both adolescents and adults, relational integration
of social and nonsocial information recruited a similar
frontoparietal network. The processing of social informa-
tion additionally engaged the MPFC and precuneus regions
of the social brain, regardless of the order of reasoning.
These findings provide further evidence that relational

integration is a domain-general process ( Wendelken
et al., 2012).

APPENDIX: LIST OF STIMULI FOR EACH TASK
IN STUDY 2
In the People task, participants were asked: “How much
do you think the following words apply to you/your
friend?” or “How much do you think the following words
apply to you compared with your friend?” In the Town
Aufgabe, participants were asked: “How much do you think
the following words apply to your town/other town?” or
“How much do you think the following words apply to

Adjectives

People

Town

arrogant, jealous, timid,
selfish, careless, witty,
cheerful, thoughtful,
stubborn, ambitious,
confident, aggressive,
clever, smart, bold, brave,
generous,helpful, mature,
wise, tough, funny, curious,
honest, sensitive, friendly,
fair, patient, bright, happy

run-down, shabby, boring,

rainy, noisy, sleepy, vibrant,
picturesque, polluted, quaint,
historic, lively, dull, exciting,
romantic, dirty, urban, expensive,
dangerous, ländlich, cultural, safe,
unusual, clean, quiet, traditional,
famous, amazing, flat, ancient

Number of letters

M = 6.7, SD = 1.8

Number of vowels

M = 2.5, SD = 1.1

M = 6.6, SD = 1.9

M = 2.6, SD = 1.1

Familiarity

M = 541.6, SD = 48.6

M = 561.6, SD = 53.6

Brown frequency

M = 9.26, SD = 10.6

M = 7.70, SD = 11.0

Kucera–Francis frequency

M = 32.0, SD = 26.9

M = 35.3, SD = 27.2

T(58) = 0.14, p = .89

T(58) = 0.36, p = .73

T(40) = 1.2, p = .23

T(41) = 0.47, p = .64

T(58) = 0.47, p = .64

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your town compared with the other town?” Familiarity
and frequency measures were included to ensure that
all adjectives were commonly used English words and
that their occurrence was comparable between Tasks.

Danksagungen

Sarah K. G. Jensen assisted with data collection. L. M. W. Ist
funded by the Mexican National Council on Science and Tech-
nology (CONACYT). S. J. B. is funded by a Royal Society Univer-
sity Research Fellowship, the Wellcome Trust, and the Jacobs
Foundation. This research was supported by the Leverhulme
Trust.

Reprint requests should be sent to Dr. Iroise Dumontheil,
Department of Psychological Sciences, Birkbeck, Universität
London, Malet Street, London WC1E 7HX, Großbritannien,
oder per E-Mail: i.dumontheil@bbk.ac.uk.

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