Cooperation in Lovers: An fNIRS-Based Hyperscanning Study

Abstract

This study investigated interactive exchange in lovers and the associated interpersonal brain
synchronization (IBS) using functional near-infrared spectroscopy (fNIRS)-based hyperscanning. Three
types of female-male dyads, lovers, friends, and strangers, performed a cooperation task during which
brain activity was recorded in right frontoparietal regions. We measured better cooperative behavior in
lover dyads compared with friend and stranger dyads. Lover dyads demonstrated increased IBS in
right superior frontal cortex, which also covaried with their task performance. Granger causality analyses
in lover dyads revealed stronger directional synchronization from females to males than from
males to females, suggesting different roles for females and males during cooperation. Our study
refines the theoretical explanation of romantic interaction between lovers.

Full text

Cooperation in Lovers: An fNIRS-Based
Hyperscanning Study
Yafeng Pan,
1
Xiaojun Cheng,
1
Zhenxin Zhang,
2
Xianchun Li,
1
*and Yi Hu
1
*
1
School of Psychology and Cognitive Science, Faculty of Education, East China Normal
University, Shanghai, People’s Republic of China
2
Department of Psychology, Zhejiang Normal University, Jinhua, People’s Republic of China
r r
Abstract: This study investigated interactive exchange in lovers and the associated interpersonal brain
synchronization (IBS) using functional near-infrared spectroscopy (fNIRS)-based hyperscanning. Three
types of female-male dyads, lovers, friends, and strangers, performed a cooperation task during which
brain activity was recorded in right frontoparietal regions. We measured better cooperative behavior in
lover dyads compared with friend and stranger dyads. Lover dyads demonstrated increased IBS in
right superior frontal cortex, which also covaried with their task performance. Granger causality analy-
ses in lover dyads revealed stronger directional synchronization from females to males than from
males to females, suggesting different roles for females and males during cooperation. Our study
refines the theoretical explanation of romantic interaction between lovers. Hum Brain Mapp 38:831–841,
2017.V
C2016 Wiley Periodicals, Inc.
Key words: cooperation; lovers; interpersonal brain synchronization; fNIRS; hyperscanning
r r
INTRODUCTION
Humans have a natural inclination to form bonds with
others, which is more evidenced for romantic relationships
(Acevedo et al., 2012; Fletcher et al., 2015). In this type of
relationship, people of both sexes have a very large
amount of social interactions, such as sharing positive life
events and receiving quality feedback (Gable et al., 2003,
2004). Their interactions, with the same goals in most cases
(Li et al., 2002; Li and Kenrick, 2006), set the stage for
some degree of overlap in their behaviors. In the current
study, we investigate how lovers interact with each other
and any associcated synchronous brain activity between
them.
According to the theory of attachment, individuals
develop mental representations of their relations with
parents, peers, lovers and so on (Furman et al., 2002,
2014). These representations are not fully congruent with
each other. Romantic relationships, compared to other
relationships, involve the integration of sexual, caregiving
and affiliative behavioral systems (Furman et al., 2014).
These behavioral systems provide rich opportunities for
lovers to cooperate (Ackerman and Kenrick, 2009; Schnei-
derman et al., 2012), examples include mutual touch
(Gallace and Spence, 2010), constructive problem-solving
(Assad et al., 2007), and emotion coordination (Randall
et al., 2013). Neurobiological studies have even shown that
when participants view pictures of a loved one, their
Additional Supporting Information may be found in the online
version of this article.
Contract grant sponsor: Peak Discipline Construction Project of Edu-
cation at East China Normal University; National Natural Science
Foundation of China; Contract grant number: 31371052 (to Y.H.)
Y. Pan and X. Cheng contributed equally to this study.
*Correspondence to: Yi Hu, School of Psychology and Cognitive
Science, East China Normal University, Shanghai, 200062, People’s
Republic of China. E-mail: yhu@psy.ecnu.edu.cn and Xianchun Li,
School of Psychology and Cognitive Science, East China Normal
University, Shanghai, 200062, People’s Republic of China. E-mail:
xcli@psy.ecnu.edu.cn
Received for publication 29 April 2016; Revised 30 August 2016;
Accepted 23 September 2016.
DOI: 10.1002/hbm.23421
Published online 4 October 2016 in Wiley Online Library
(wileyonlinelibrary.com)
rHuman Brain Mapping 38:831–841 (2017) r
V
C2016 Wiley Periodicals, Inc.

oxytocin levels surged (de Boer et al., 2012; Zeki, 2007).
Oxytocin is a hormone that plays a pivotal role in trust,
empathy, and cooperation (Kosfeld et al., 2005; Schneider-
man et al., 2012). These findings are suggestive of the
cooperative nature of romantic relationships.
Gender differences in cooperation between lovers can be
explained by established theories from psychology and
evolutionary biology. The self-construal theory suggests
that females are interdependent and males are indepen-
dent (Cross and Madson, 1997). Females are more sharing,
affiliative, and emotionally supportive than males. They
display greater levels of prosociality, such as empathy,
selflessness, and positive emotions (e.g., Cross and Mad-
son, 1997; Eckel and Grossman, 1998; Zakriski et al., 2005).
It seems that, in general, females are more romantically
submissive to males. However, there might be other possi-
bilities. From an evolutionary biology perspective, females
expend more physical and temporal resources in pregnan-
cy and offspring care compared to males. The female
tends to be relatively choosy regarding acceptable qualities
in potential mates and to be actively restricted in their
access to the opposite sex partners (Buss and Schmitt,
1993; Kenrick et al., 1990; Li et al., 2002; Perilloux et al.,
2008). Males, on the other hand, may use more flexible tac-
tics (e.g., flaunting) to demonstrate acceptable mate-value
(Geary et al., 2004; Griskevicius et al., 2006) and thus
might be more capable of humoring females.
We asked two partners in a lover dyad to perform a
cooperative task (Baker et al., 2016; Cheng et al., 2015; Cui
et al., 2012). The lover dyad tried their best to simulta-
neously make quick responses to a stimulus. The quality of
their performance was defined by the difference and vari-
ability between their response times. A small difference
and less variability implied better cooperation (Funane
et al., 2011; Vesper et al., 2011). During the task, we simul-
taneiously recorded brain activities from both partners,
which is known as the “hyperscannning.” Hyperscanning
can be used with fMRI (e.g., Chiu et al., 2008; Li et al.,
2009), EEG (e.g., Lindenberger et al., 2009), and fNIRS (e.g.,
Cheng et al., 2015; Jiang et al., 2015; Tang et al., 2016). Pre-
vious studies using the hyperscanning technique during
studies of cooperation found interpersonal brain synchroni-
zation (IBS) in right centroparietal regions (Dumas et al.,
2010) and prefrontal cortex (McCabe et al., 2001).
Hyperscanning has been used to investigate neural links
between lovers. Specifically, an fMRI study found that
affective facial communication in romantic partners eli-
cited activations in the same cerebral networks, such
as anterior temporal, insular, and somato-motor brain
regions (Anders et al., 2011). A recent EEG study found
that romantic kissing in lovers induced intra- and inter-
brain synchronization in the theta-alpha band (M€
uller
and Lindenberger, 2014). We adopted the fNIRS-based
hyperscanning technique. The fNIRS device is more tol-
erant of motor artifacts and acheives temporal and spa-
tial resolutions that are comparable to fMRI and EEG. A
single fNIRS device can be divided for hyperscanning
experiments by using half of the channels for each par-
ticipant (Cheng et al., 2015; Cui et al., 2012). Therefore,
thefNIRSset-upcanresolvetheissueofvariablesensi-
tivities from different devices.
In sum, this study explored interactive exchange between
lovers through fNIRS-based hyperscanning. Based on the
more interactive experiences and the cooperative nature of
romantic relationships, we expected that lover dyads would
outperform friend and stranger dyads on the cooperative
task. Also, we anticipated that better performance would be
accompanied by increased IBS between the two partners.
Previous studies have found that right frontoparietal cortex
is associated with cooperation and reciprocal interactions
(Decety et al., 2004). Moreover, a right-lateralized frontopar-
ietal mirror-neuron network was shown to be involved
with social understanding (e.g., understand the emotions
and actions of others, Gallese et al., 2004; Iacoboni et al.,
2005) and was considered as the basis for bridging the self-
other gap during interaction (Uddin et al., 2007). Based on
these studies, we defined the region-of-interest for the pre-
sent study to be right frontoparietal area. Meanwhile, we
examined gender differences at the level of behavior and
brain activity, with the goal of providing evidence for either
self-construal theory or the evolutionary biological theory of
heterosextual cooperation.
METHOD
Participants
Ninety-eight adults (49 dyads, age: 21.07 61.85 yrs) par-
ticipated in the study. They were all male–female dyads,
which included 17 lover dyads, 16 friend dyads, and 16
stranger dyads. Lover dyads as well as friend dyads had
been acquainted before the experiment, and these two
types of dyads did not differ in duration of acquaintance
(21.01 65.08 vs. 15.75 63.41 months, t
(31)
51.23, P50.23,
Cohen’s d50.32). The lover dyads reported that they were
intensely in love (duration of “being in love”: M515.15
months, range 52–36 months). Each participant signed
informed consent before the experiment and was paid ¥ 20
for participation. The University Committee on Human
Research Protection of East China Normal University
approved study procedure.
Tasks and Procedures
Two participants in a dyad sat side-by-side, separated
by a board and in front of a shared computer display
(Fig. 1A). The procedure consisted of Rest 1 (30 s), Task
Block 1 (150 s), Rest 2 (30 s), Task Block 2 (150 s), and
Rest 3 (30 s) (Fig. 1B). For each task block, participants
needed to complete 20 trials. Within each trial (Fig. 1C), a
hollow gray circle (0.6 – 1.5 s) was presented first, followed
by a green signal. Upon seeing the signal, participants
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used their right index fingers to press the key simulta-
neously. The participant on the left (participant #1) used
the “1” key on a keyboard, and the participant on the right
(participant #2) used the “2” key on the other keyboard.
To maintain participants’ attention and increase cooper-
ative behaviors, we set a threshold (T) for a trial for which
they would get a winning point:
T51
8RT11RT2ðÞ
where RT1 and RT2 were the response times of participant
#1 and participant #2, respectively. The parameter 1/8 was
chosen to maintain a reasonable difficulty level (Baker
et al., 2016; Cheng et al., 2015; Cui et al., 2012). For each
dyad, if the time difference was smaller than their thresh-
old, both won one point; otherwise, they lost one point.
After key-pressings, a feedback screen (4 s) appeared.
The feedback consisted of the following information: (1)
win or lose; (2) cumulative points; (3) who was faster
(“1”) or slower (“2”). This information aided participants
in adjusting their responses to maximize points. No verbal
or physical communication was allowed. After the feed-
back, there was a blank screen (i.e., the intertrial interval)
lasting 2 s.
Subjective Measurements
We collected each participant’s attitudes towards her/
his partner and the experiment, these information includ-
ed: (1) trustworthiness for others in their daily life (pre-
experiment); (2) satisfaction for her/his own performance
(post-experiment); (3) cooperativeness during the coopera-
tion (post-experiment); (4) pleasantness while cooperating
(post-experiment); (5) concentration during tasks (post-
experiment); (6) favorability for the partner (pre- and post-
experiment). Participants used a 7-point Likert scale,
which ranged from 1 (“not very much”) to 7 (“very
Figure 1.
Experimental design. (A) Experimental setup. (B) Task design. There were two task blocks, each
consisting of 20 trials. (C) Trial design. Events and time flow in a trial. (D) Optode probe set.
The set was placed on the right frontoparietal cortices. [Color figure can be viewed at wileyonli-
nelibrary.com]
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much”), for all ratings. No discussion was allowed while
rating.
Data Acquisition
An ETG-4000 optical topography system (Hitachi Medi-
cal Corporation, Japan) was used to record the oxyhemo-
globin (HbO) and deoxyhemoglobin (HbR) concentrations
for each dyad. The absorption of near infrared light (wave-
lengths: 695 and 830 nm) was measured at a sampling rate
of 10 Hz. The optode probe set was placed over partici-
pants’ right frontoparietal regions (Fig. 1D), based on pre-
vious work showing cooperative exchange involved right
frontal and parietal regions (Decety et al., 2004).
Two 3 35 optode probe sets (eight emitters and seven
detectors, 3 cm optode separation) were used. Each set
consists of 22 measurement channels (CHs). The center of
the middle probe set row was placed at C4, according to
the 10/20 international system. The middle probe set col-
umn was placed along the sagittal reference curve. The
virtual registration method was used to determine the cor-
respondence between the NIRS CHs and the measured
points on the cerebral cortex (Singh et al., 2005; Tsuzuki
et al., 2007).
Data Analysis
Behavior performance
For each participant dyad, response times (RTs), and
winning trials were recorded. Because there were some
outliers in the data, the median and median absolute devi-
ation of response times (median-RT, mad-RT) were calcu-
lated among all trials in each participant. Outliers were
identified by calculating an interval spanning over the
mean 63 SD. We also analyzed the median and median
absolute deviation of the difference of response times
(median-DRT and mad-DRT) between the two participants
in a dyad, similar to procedures used in previous studies
(Funane et al., 2011; Vesper et al., 2011). To quantify par-
ticipant performance and index the quality of cooperation,
we calculated the percentage of winning trials (PWT;
Cheng et al., 2015; Cui et al., 2012).
Nonparametric Wilcoxon tests were used on the
median-RT, mad-RT, median-DRT, and mad-RT, because
the data were not normally distributed. The PWT was dis-
tributed normally, so we applied a two-way ANOVA,
with factors of Group (lover, friend, stranger) by Task
Block (blocks 1, 2). Finally, we used a Bonferroni correc-
tion to account for multiple comparisons.
Interpersonal brain synchronization (IBS)
Because the HbO signal has been demonstrated to be
most sensitive to changes in cerebral blood flow during
fNIRS measurements (Cui et al., 2012; Hoshi, 2007), we
focused on the HbO time series. However, HbR time series
were also analyzed (see Supporting Information).
During preprocessing, the initial and ending periods
(Rest 1 and Rest 3, respectively) of the task were removed.
A line of evidence mentioned that the fNIRS can measure
both global (i.e., systemic components which are not task-
specific activity) and cortical blood oxygen level dependent
(BOLD) activities (Ferrari and Quaresima, 2012; Kirilina
et al., 2012), Therefore, we first used a principal component
spatial filter algorithm (i.e., PCA approach using Gaussian
spatial filtering) to remove the global components (Zhang
et al., 2016). Wavelet transform coherence (WTC) was then
used to assess the relationship between HbO time series for
each dyad (for more details see Grinsted et al., 2004). Based
on WTC analyses of two time series generated by each par-
ticipant dyad, we focused on the frequency band between
3.2 s and 12.8 s (i.e., 0.08 – 0.31 Hz) that was more sensitive
to our task (Fig. 2). Specifically, this frequency band
includes the period of the single trial (7s)inthecoopera-
tion task indicating that this coherence increase is task-
related. The selection of frequency band was also in accor-
dance with previous studies using the same paradigm
(Baker et al., 2016; Cheng et al., 2015; Cui et al., 2012).
Focusing on this frequency band enabled removal of high-
and low-frequency artificial noises, such as those related to
cardiac pulsation (1Hz).
For each pair of CHs between two participants, the aver-
age cross-brain coherence, or IBS, was calculated in task
Figure 2.
Frequency band of interest. Interpersonal brain synchronization
(IBS) indicated by wavelet transform coherence (WTC). The
coherence based on raw HbO signal from channel 20 (CH20) in
a representative pair of lovers. The red border represents the
frequency band of interest (3.2 s – 12.8 s), indicating when the
task was carried out. The color bar denotes the value of WTC
(1 5highest coherence, 0 5lowest coherence). [Color figure
can be viewed at wileyonlinelibrary.com]
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blocks and resting period. We defined IBS as the mean of
coherence in two task blocks minus the coherence during
the inter-block rest period (Rest 2):
IBS51
2IBSblock 11IBSblock 2
ðÞ2IBSrest 2
We converted IBS values to Fisher z-statistics and then cal-
culated a one-sample t-test with false discovery rate (FDR)
correction across all CHs (P<0.05). We generated a t-map
of IBS and smoothed it using the spline method. If a chan-
nel was found with significant IBS, a one-way ANOVA
was conducted on that IBS with the factor of Group. Bon-
ferroni correction was used to account for post hoc multi-
ple comparisons.
Directional coupling
To estimate the direction of synchronization for CHs
that exhibited significant IBS, Granger causality analyses
(GCA) were conducted (see more details in Barnett and
Seth, 2014; Im et al., 2010). GCA uses vector autoregressive
models to measure the causal relationship between time
series in brain data. Our GCA was based on PCA-
corrected signals during the task periods. The pairwise-
conditional Granger-causality (G-causality) of both partici-
pant directions (i.e., from females to males; from males to
females) was calculated. Then, one-sample t-tests were
used to examine whether each direction differed from
zero, and two-sample t-tests were used to compare differ-
ences between two directions.
Subjective measurements
A series of two-way ANOVAs were conducted to
estimate the effects of Group and Gender on participants’
ratings of their (1) trustworthiness, (2) satisfaction, (3)
cooperativeness, (4) pleasantness, and (5) concentration.
One three-way ANOVA was carried out on partner favor-
ability with the factors of Group, Gender, and Time (pre-
vs. post-experiment). We conducted follow-up t-tests with
Bonferroni corrections when necessary.
RESULTS
Behavioral Performance
For individual behavioral data, Wilcoxon tests on
median-RT showed that lover dyads responded faster than
stranger dyads (Bonferroni corrected,P<0.05; see Sup-
porting Information Table S1). Similar analyses on mad-RT
revealed that responses from lover and friend dyads were
less variable than stranger dyads responses (Bonferroni
corrected,Ps<0.05; see Supporting Information Table S2).
Additionally, we explored gender differences on median-
RT and mad-RT between these three groups. Wilcoxon
tests on median-RT showed that males responded slower
than females in the lover dyads (P<0.05), but not in
friend and stranger dyads (Ps>0.05; see Supporting Infor-
mation, Table S1). No other significant effect was found.
We tested for joint cooperation by using Wilcoxon tests
on median-DRT. These tests showed significant group dif-
ferences between lover and friend dyads (P<0.05), and
between lover and stranger dyads (P<0.05; Fig. 3A).
These differences indicate that median-DRT in lover dyads
was smaller than friend and stranger dyads. Similar analy-
ses on mad-DRT confirmed that mad-DRT in lover dyads
was smaller than friend and stranger dyads (Ps<0.05;
Fig. 3B).
The analysis of PWT (ANOVA with factors of Group
and Task Block) yielded statistical significance only for
Figure 3.
Cooperation performance. (A) The median of difference of response time (median-DRT).
(B) The median absolute deviation of difference of response time (mad-DRT). * P<0.05, after
correction. Error bars represent standard errors.
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Task Block (F
(1,46)
524.35, P<0.001, h2
p50.35) with the
higher PWT in block 2 among all groups (Ps<0.05; see
Supporting Information, Table S3 and Fig. S1). These find-
ings confirm that all participants performed the coopera-
tion task as instructed.
Interpersonal Brain Synchronization (IBS)
A series of one-sample t-test analyses of IBS in lover
dyads found significant IBS at CH19 (t
(16)
52.40, P<0.05,
Cohen’s d50.82) and CH20 (t
(16)
54.25, P<0.001,
Cohen’s d51.46). However, only IBS at CH20 survived
after FDR correction (P<0.05; Fig. 4A). CH20 was rough-
ly located in the right superior frontal cortex (r-SFC;
Tzourio-Mazoyer et al., 2002). In contrast, no significant
IBS was found in friend or stranger dyads. A one-way
ANOVA analysis demonstrated that IBS at CH20 was
affected by Group, (F
(2,46)
53.91, P<0.05, h2
p50.14). The
post hoc tests revealed that IBS in lovers was significantly
greater than that in friends and strangers (P<0.05;
Fig. 4B).
The IBS-Behavior Relation
Pearson correlation analyses were conducted on the sig-
nificant IBS at CH20 and behavior indices (e.g., DRT,
PWT). IBS and median-DRT were correlated (Fig. 5A,
r520.50, P<0.05), indicating that the IBS found in lover
dyads was associated with their cooperative performance.
However, similar correlations were not statistically signifi-
cant in friends or strangers (Ps>0.1).
We also calculated the change in IBS between task
blocks by subtracting the coherence value in task block 1
from that in task block 2, IBS
block 2 – block 1
, based on previ-
ous work (Cheng et al., 2015). The correlation between
IBS
block 2 – block 1
and the increase of winning trials from
block 1 to block 2, PWT
block 2 – block 1
, was significant (Fig.
5B, r50.56, P<0.05). In contrast, this relationship was
not significant in friend and stranger dyads (Ps>0.1).
Directional Coupling
To determine the direction of IBS at CH20, we con-
ducted one-sample t-tests on the mean G-causality. For
Figure 4.
Interpersonal brain synchronization (IBS). (A) One-sample t-test
map of IBS. (B) Upper graph: one-way ANOVA results of the
IBS to identify group differences. Lower graph: The amplitude of
synchronization at channel 20 (CH20). Note that only in lover
dyads, a significant IBS at CH20 was found after FDR correction.
Synchronization in lover dyads is higher than that in other dyads.
*P<0.05, after correction. Error bars represent standard
errors. [Color figure can be viewed at wileyonlinelibrary.com]
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lover dyads, both directions demonstrated significant
increases in the mean G-causality relative to zero: from
females to males (t
(16)
57.02, P<0.001, Cohen’s d52.41)
and from male to female (t
(16)
54.23, P<0.001, Cohen’s
d51.45; Fig. 6A). A two-sample t-test revealed that mean
G-causality from females to males was significantly larger
than from males to females (t
(16)
52.97, P<0.01, Cohen’s
d50.91; Fig. 6B). In contrast, no significant G-causality in
either direction or difference between the two directions
was found for the other dyads (Ps>0.05).
Subjective Measurements
The results of two-way ANOVAs showed no significant
effect of Group in evaluations of trustworthiness and con-
centration. However, the effect of Group was significant
on self-rated pleasantness (F
(2,95)
58.62, P<0.001,
h2
p50.08), satisfaction (F
(2,95)
55.71, P<0.01, h2
p50.06),
and cooperativeness (F
(2,95)
510.20, P<0.001, h2
p50.10).
Post hoc tests demonstrated that lover dyads felt more
pleasant and more satisfied than stranger dyads did
(Ps<0.05), but not than the friend dyads did (Ps>0.05).
Lovers felt more cooperative than friend and stranger
dyads (Ps<0.05). To address the potential contribution of
these subjective experiences to IBS, we examined whether
the self-rated pleasantness, satisfaction or cooperativeness
correlated with IBS. None of these correlations survived
(Ps>0.1).
Finally, we conducted a three-way ANOVA on partner
favorability that showed effects of Time (F
(1,95)
546.29, P
<0.001, h2
p50.21) and an interaction between Time and
Group (F
(2,95)
58.11, P<0.001, h2
p50.08). Further analyses
showed that friend and stranger dyads developed more
favorable impressions of their partners from the beginning
to the end of the experiment (Ps<0.01), while lover dyads
did not (P>0.1). The descriptive statistics can be found in
Supporting Information, Table S4.
DISCUSSION
To our knowledge, this is the first fNIRS-based hyper-
scanning study exploring interactive exchange in lovers.
Behavioral results showed that response time differences
between lover dyads were smaller and less variable than
friend and stranger dyads, indicating better cooperation
among lovers. More importantly, fNIRS results showed
interpersonal brain synchronization (IBS) only for lover
dyads. The IBS obtained in lover dyads was also found to
correlate with their task performance.
We found IBS in lover dyads using a task involving
interactive exchange in the form of simultaneously press-
ing keys to maximize joint performance. Our results are
consistent with IBS findings in other interactive activities,
such as game playing (Liu et al., 2016), button pressing
(Funane et al., 2011), and jointly acting (Dommer et al.,
2012). IBS might be accounted for by the familiarity lovers
have with each other or by their emotional involvement
with each other. However, we think these factors are
unlikely based on the following evidence. First, we
observed no significant IBS in friend dyads, who had a
similar duration of acquaintance as lover dyads. Second,
although lover-dyads reported more pleasantness during
the interactive exchange, our analyses suggested that it
might not affect the IBS (see Subjective Measurements in
the Results part). Thus, we argue that IBS found in lover
dyads arises from working together on the task, echoing
Figure 5.
IBS-behavior correlation in lover dyads. Correlations (A) between the IBS at CH20 and median-
DRT, (B) between IBS change at CH20 (IBS
block 2 – block 1
) and percentage of winning trials
change (PWT
block 2 – block 1
).
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the proposal that “significant others” trigger response
facilitation and therefore lead to two interactive partners
“being in tune” (Byrne, 2005). The cooperative task might
also recruit other cognitive processes, such as shared emo-
tions and social intentions, in addition to joint actions.
Whether our findings can generalize to these modalities is
a direction for future research.
We found IBS in the right superior frontal cortex
(r-SFC). Previous functional brain imaging studies reported
the engagement of superior frontal gyrus/intraparietal sul-
cus while viewing a lover’s photograph (Bartels and Zeki,
2000, 2004; Xu et al., 2011) and medial orbitofrontal cortex/
parietal lobes while thinking of their romantic partner (Xu
et al., 2012). A recent study even found that functional
resting-state connectivity in the frontoparietal network was
significantly enhanced for the “in-love” group (Song et al.,
2015). The function of r-SFC has been intensely discussed in
the literature: it has been implicated in implicit understand-
ing of others’ action (Hari and Kujala, 2009), response
inhibition (Dziobek et al., 2012), working memory (du Bois-
gueheneuc et al., 2006), and self-awareness (Goldberg et al.,
2006). The role of r-SFC identified here offers support for
the theory of mind hypothesis (Cui et al., 2012; Yang et al.,
2015), as our cooperation game required understanding,
modeling, and predicting partner behavior. Certainly, the
exact meaning of the IBS at superior frontal cortex (SFC) is
a direction for future research.
We observed similarities and differences between our
findings and two recent studies using fNIRS-based hyper-
scanning. Cui et al. (2012) found IBS at the r-SFC for the
cooperation of 11 participant-dyads, but the gender of the
two partners was not under consideration. In a recent
study that controlled for gender, Cheng et al. (2015)
revealed IBS at the frontopolar cortex, orbitofrontal cortex,
and left dorsolateral prefrontal cortex for female-male
dyads, but not for female-female dyads and male-male
dyads. The fNIRS optode patch was placed mostly over
the prefrontal cortex, and the two partners were unac-
quainted with each other before the experiment. By con-
trast, our study relied on the a priori hypothesis that right
frontoparietal brain areas likely underlay social under-
standing and interactive exchange between partners.
We found gender differences in lover dyads: males
tended to respond more slowly to cues. The slower
response suggests that males needed extra time to adapt
their responses to females’ responses. In agreement with
our finding, a recent study found that when judging the
degree of romance in sentences, males responded more
slowly compared to females. The authors posit that males
may use more cognitive effort to perceive romance (Yin
et al., 2013). These findings support different roles for
females and males in romantic relationships.
Our GCA results for lover dyads further showed that
the direction of IBS from females to males was stronger
than from males to females, implying that the primary
information flow was from females to males. Previous
studies showed IBS directional differences for partners in
relationships as gesturer-guesser (Schippers et al., 2010),
model-imitator (Holper et al., 2012), and leader-follower
(Jiang et al., 2015). Specifically, the brain activity in the
gesturer predicted that of the guesser (Schippers et al.,
2010), the brain activity of the model caused that of the
imitator (Holper et al., 2012), and there was a more impor-
tant role for the leader compared to the follower (Jiang
et al., 2015). In our study, females might “lead” the activi-
ty and “send” information to males, who “receive” the
information and play the “follower” role. Results from
Granger causality analyses highlight the important role of
dynamic social interactions in lovers’ cooperation (Schil-
bach et al., 2013).
Gender differences found for lover dyads tends to sup-
port the evolutionary biological perspective that the male
is more capable of going along with females’ behavior
(Griskevicius et al., 2006; Hyde, 2014). We note that our
participants are mostly undergraduate university students.
Figure 6.
Directional coupling in lover dyads. (A) The G-causality was
analyzed on two directions (from males to females, from females
to males). Significant G-causality was indicated by the solid-lines
(thresholded at P<0.001). (B) Mean G-causalities in both direc-
tions were illustrated in the bar graphs. The mean causality
from females to males (indicated by red color) was significantly
higher than that from male to female (indicated by blue color).
**P<0.01. Error bars represent standard errors. [Color figure
can be viewed at wileyonlinelibrary.com]
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They are in the early stages of the romantic relationship,
during which males exert themselves, display acceptable
attributes, and demonstrate the ability to achieve sexual
access. As such, the examination of gender differences in
lovers should consider more factors, such as relationship
stage (Kenrick et al., 1990), attachment style (Furman
et al., 2002), and affiliation (Furman et al., 2014), to name a
few. In addition, studies have shown that in situations
involving prosocial behaviors, males are expected to
undertake the roles of high status and power, and thus
were more agentic and dominant than females (e.g., Eagly,
2009). Further investigation is needed to elaborate the gen-
der differences in romantic lovers during interactive
exchange.
Investigation of IBS using two-person interactions is a
promising yet nascent field, and it could provide insight
into higher cognitive functions, such as cooperation and
communication. However, fNIRS faces some analytic chal-
lenges. First, the spontaneous oscillations of blood flow
(i.e., Mayer waves, 0.1 Hz), which might contaminate the
task-related brain activities (Lloyd-Fox et al., 2010; Scholk-
mann et al., 2014), were included in our frequency of inter-
est (0.08–0.31 Hz). Consequently, we carried out a parallel
IBS analysis in the frequency band of 0.09–0.11 Hz, but no
significant group difference was detected (see Supporting
Information, Fig. S2). Such physiological process therefore
should have equal impact on fNIRS responses among all
groups and cannot explain our finding of increased IBS
only in the lover dyads. Second, fNIRS signals were con-
taminated with global systemic components, which are not
task-specific, such as the scalp blood flow and changes in
blood pressure. Therefore, we used a PCA approach that
included Gaussian spatial filtering to remove the global
systemic components (Zhang et al., 2016), although such
signals cannot be filtered out completely. Third, we
detected the primary components of IBS based on the
HbO measurement, and we cannot exclude the possibility
of additional useful information in the HbR signal. Previ-
ous studies have shown that HbO is more influenced by
scalp blood flow and HbR is more related to neurovascu-
lar coupling (Ou et al., 2009; Zhang et al., 2016). Therefore,
we also analyzed the HbR time series and found a similar
effect at the r-SFC (see Supporting Information, Fig. S3).
Because fNIRS signals might suffer from various con-
founding contaminants such as physiological processes
and global systemic effects, future studies could (1) collect
physiological responses, and (2) analyze both HbO and
HbR concentrations to get a full picture about measured
brain activity.
Limitations of this study are important to note. First, the
optode probe set of NIRS only covered the right frontopar-
ietal regions of the brain, leaving other regions unex-
plored. In a previous study of cooperative performance,
IBS was also found at the left inferior parietal lobule and
the occipital cortex (Egetemeir et al., 2011). The roles of
these brain regions could be examined by measuring from
the entire brain. Second, close personal relationships are
found to be closely related to motivation and reward brain
systems (Acevedo et al., 2012; Aron et al., 2005), and the
relevant brain structures are mostly subcortical. These sub-
cortical structures could be investigated by using fMRI-
based techniques. Third, we cannot dismiss the potential
effects of motivational state on the establishment of IBS,
since motivation plays an important role during the social
interactions (Canessa et al., 2012). Future studies could
manipulate or control participant’s motivational state and
explore the relationship between motivation and brain
activity.
In summary, we demonstrated that cooperative behavior
between lover dyads was better than friend and stranger
pairs and identified IBS in the right superior frontal cortex.
Our findings support the theory that there are distinctive
mental representations developed for individuals in rela-
tionships with others. Performance differences between
partners and the direction of IBS suggest a leading/affilia-
tive role for females/males in romantic relationships, pri-
marily supporting theories from evolutionary biology. Our
study advances the understanding of the unique brain sig-
nature for lovers’ interactions and potentially provides
insights in the evolution of human love.
ACKNOWLEDGMENTS
Authors thank Dr. Kimberlee D’Ardenne from the Depart-
ment of Psychology at Arizona State University for her
wonderful suggestions and grammar corrections. Authors
thank Yue Yang and Guowei Chen for their technical
assistance with the fNIRS hyperscanning. Authors thank
Qun Ye and Lili Zheng for their assistance in data acquisi-
tion and entry.
REFRENCES
Acevedo BP, Aron A, Fisher HE, Brown LL (2012): Neural corre-
lates of long-term intense romantic love. Soc Cogn Affect Neu-
rosci 7:145–159.
Ackerman JM, Kenrick DT (2009): Cooperative courtship: Helping
friends raise and raze relationship barriers. Pers Soc Psychol B
35:1285–1300.
Anders S, Heinzle J, Weiskopf N, Ethofer T, Haynes JD (2011):
Flow of affective information between communicating brains.
Neuroimage 54:439–446.
Aron A, Fisher H, Mashek DJ, Strong G, Li HF, Brown LL (2005):
Reward, motivation, and emotion systems associated with
early-stage intense romantic love. J Neurophysiol 94:327–337.
Assad KK, Donnellan MB, Conger RD (2007): Optimism: An
enduring resource for romantic relationships. J Pers Soc Psy-
chol 93:285–297.
Baker JM, Liu N, Cui X, Vrticka P, Saggar M, Hosseini SM, Reiss
AL (2016): Sex differences in neural and behavioral signatures
of cooperation revealed by fNIRS hyperscanning. Sci Rep 6:
26492.
rCooperation in Lovers r
r839 r

Barnett L, Seth AK (2014): The MVGC multivariate Granger cau-
sality toolbox: A new approach to Granger-causal inference.
J Neurosci Methods 223:50–68.
Bartels A, Zeki S (2000): The neural basis of romantic love. Neuro-
report 11:3829–3834.
Bartels A, Zeki S (2004): The neural correlates of maternal and
romantic love. Neuroimage 21:1155–1166.
Buss DM, Schmitt DP (1993): Sexual strategies theory—An evolu-
tionary perspective on human mating. Psychol Rev 100:204–232.
Byrne RW (2005): Social cognition: imitation, imitation, imitation.
Curr Biol 15:498–500.
CanessaN,AlemannoF,RivaF,ZaniA,ProverbioAM,MannaraN,
Perani D, Cappa SF (2012): The neural bases of social intention
understanding: The role of interaction goals. PLoS One 7:e42347.
Cheng XJ, Li XC, Hu Y (2015): Synchronous brain activity during
cooperative exchange depends on gender of partner: A fNIRS-
based hyperscanning study. Hum Brain Mapp 36:2039–2048.
Chiu PH, Kayali MA, Kishida KT, Tomlin D, Klinger LG, Klinger
MR, Montague PR (2008): Self responses along cingulate cortex
reveal quantitative neural phenotype for high-functioning
autism. Neuron 57:463–473.
Cross SE, Madson L (1997): Models of the self: Self-construals and
gender. Psychol Bull 122:5–37.
Cui X, Bryant DM, Reiss AL (2012): NIRS-based hyperscanning
reveals increased interpersonal coherence in superior frontal
cortex during cooperation. Neuroimage 59:2430–2437.
de Boer A, van Buel EM, Ter Horst GJ (2012): Love is more than
just a kiss: A neurobiological perspective on love and affection.
Neuroscience 201:114–124.
Decety J, Jackson PL, Sommerville JA, Chaminade T, Meltzoff AN
(2004): The neural bases of cooperation and competition: An
fMRI investigation. Neuroimage 23:744–751.
Dommer L, Jager N, Scholkmann F, Wolf M, Holper L (2012):
Between-brain coherence during joint n-back task performance:
A two-person functional near-infrared spectroscopy study.
Behav Brain Res 234:212–222.
du Boisgueheneuc F, Levy R, Volle E, Seassau M, Duffau H,
Kinkingnehun S, Samson Y, Zhang S, Dubois B (2006): Func-
tions of the left superior frontal gyrus in humans: A lesion
study. Brain 129:3315–3328.
Dumas G, Nadel J, Soussignan R, Martinerie J, Garnero L (2010):
Inter-brain synchronization during social interaction. PLoS
One 5:e12166.
Dziobek I, Preissler S, Grozdanovic Z, Heuser I, Heekeren HR,
Roepke S (2012): Neuronal correlates of altered empathy and
social cognition in borderline personality disorder. Neuro-
image 57:539–548.
Eagly AH (2009): The his and hers of prosocial behavior: An
examination of the social psychology of gender. Am Psychol
64:644–658.
Eckel CC, Grossman PJ (1998): Are women less selfish than men?
Evidence from dictator experiments. Econ J 108:726–735.
Ferrari M, Quaresima V (2012): A brief review on the history of
human functional near-infrared spectroscopy (fNIRS) develop-
ment and fields of application. Neuroimage 63:921–935.
Egetemeir J, Stenneken P, Koehler S, Fallgatter AJ, Herrmann MJ
(2011): Exploring the neural basis of real-life joint action: Mea-
suring brain activation during joint table setting with function-
al near-infrared spectroscopy. Front Hum Neurosci 5:95.
Fletcher GJO, Simpson JA, Campbell L, Overall NC (2015): Pair-
bonding, romantic love, and evolution: The curious case of
homo sapiens. Perspect Psychol Sci 10:20–36.
Funane T, Kiguchi M, Atsumori H, Sato H, Kubota K, Koizumi H
(2011): Synchronous activity of two people’s prefrontal cortices
during a cooperative task measured by simultaneous near-
infrared spectroscopy. J Biomed Opt 16:077011.
Furman W, Simon VA, Shaffer L, Bouchey HA (2002): Adoles-
cents’ working models and styles for relationships with
parents, friends, and romantic partners. Child Dev 73:241–255.
Furman W, Stephenson JC, Rhoades GK (2014): Positive interac-
tions and avoidant and anxious representations in relation-
ships with parents, friends, and romantic partners. J Res
Adolesc 24:615–629.
Gable SL, Reis HT, Elliot AJ (2003): Evidence for bivariate sys-
tems: An empirical test of appetition and aversion across
domains. J Res Pers 37:349–372.
Gable SL, Reis HT, Impett EA, Asher ER (2004): What do you do
when things go right? The intrapersonal and interpersonal
benefits of sharing positive events. J Pers Soc Psychol 87:
228–245.
Gallace A, Spence C (2010): The science of interpersonal touch:
An overview. Neurosci Biobehav Rev 34:246–259.
Gallese V, Keysers C, Rizzolatti G (2004): A unifying view of the
basis of social cognition. Trends Cogn Sci 8:396–403.
Geary DC, Vigil J, Byrd-Craven J (2004): Evolution of human mate
choice. J Sex Res 41:27–42.
Goldberg II, Harel M, Malach R (2006): When the brain loses its
self: Prefrontal inactivation during sensorimotor processing.
Neuron 50:329–339.
Grinsted A, Moore JC, Jevrejeva S (2004): Application of the cross
wavelet transform and wavelet coherence to geophysical time
series. Nonlinear Proc Geoph 11:561–566.
Griskevicius V, Cialdini RB, Kenrick DT (2006): Peacocks, Picasso,
and parental investment: The effects of romantic motives on
creativity. J Pers Soc Psychol 91:63–76.
Hari R, Kujala MV (2009): Brain basis of human social interaction:
From concepts to brain imaging. Physiol Rev 89:453–479.
Holper L, Scholkmann F, Wolf M (2012): Between-brain connectivity
during imitation measured by fNIRS. Neuroimage 63:212–222.
Hoshi Y (2007): Functional near-infrared spectroscopy: Current
status and future prospects. J Biomed Opt 12:062106.
Hyde JS (2014): Gender similarities and differences. Annu Rev
Psychol 65:373–398.
Iacoboni M, Molnar-Szakacs I, Gallese V, Buccino G, Mazziotta JC,
Rizzolatti G (2005): Grasping the intentions of others with
one’s own mirror neuron system. PLoS Biol 3:e109.
Im CH, Jung YJ, Lee S, Koh D, Kim DW, Kim BM (2010): Estima-
tion of directional coupling between cortical areas using near-
infrared spectroscopy (NIRS). Opt Express 18:5730–5739.
Jiang J, Chen CS, Dai BH, Shi G, Ding GS, Liu L, Lu CM (2015):
Leader emergence through interpersonal neural synchroniza-
tion. Proc Natl Acad Sci USA 112:4274–4279.
Kenrick DT, Sadalla EK, Groth G, Trost MR (1990): Evolution,
traits, and the stages of human courtship: Qualifying the
parental investment model. J Pers 58:97–116.
Kirilina E, Jelzow A, Heine A, Niessing M, Wabnitz H, Bruhl R,
Ittermann B, Jacobs AM, Tachtsidis I (2012): The physiological
origin of task-evoked systemic artefacts in functional near
infrared spectroscopy. Neuroimage 61:70–81.
Kosfeld M, Heinrichs M, Zak PJ, Fischbacher U, Fehr E (2005):
Oxytocin increases trust in humans. Nature 435:673–676.
Li J, Xiao E, Houser D, Montague PR (2009): Neural responses to
sanction threats in two-party economic exchange. Proc Natl
Acad Sci USA 106:16835–16840.
rPan et al. r
r840 r

Li NP, Bailey JM, Kenrick DT, Linsenmeier JAW (2002): The
necessities and luxuries of mate preferences: Testing the trade-
offs. J Pers Soc Psychol 82:947–955.
Li NP, Kenrick DT (2006): Sex similarities and differences in pref-
erences for short-term mates: What, whether, and why. J Pers
Soc Psychol 90:468–489.
Liu N, Mok C, Witt E, Pradhan AH, Chen JE, Reiss AL (2016):
NIRS-based hyperscanning reveals inter-brain neural synchro-
nization during cooperative Jenga game with face-to-face com-
munication. Front Hum Neurosci 10:82.
Lindenberger U, Li SC, Gruber W, Muller V (2009): Brains swing-
ing in concert: Cortical phase synchronization while playing
guitar. BMC Neurosci 10:22.
Lloyd-Fox S, Blasi A, Elwell CE (2010): Illuminating the develop-
ing brain: The past, present and future of functional near infra-
red spectroscopy. Neurosci Biobehav Rev 34:269–284.
McCabe K, Houser D, Ryan L, Smith V, Trouard T (2001): A func-
tional imaging study of cooperation in two-person reciprocal
exchange. Proc Natl Acad Sci USA 98:11832–11835.
M€
uller V, Lindenberger U (2014): Hyper-brain networks support
romantic kissing in humans. PLoS One 9:e112080.
Ou W, Nissila I, Radhakrishnan H, Boas DA, Hamalainen MS,
Franceschini MA (2009): Study of neurovascular coupling
in humans via simultaneous magnetoencephalography
and diffuse optical imaging acquisition. Neuroimage 46:
624–632.
Perilloux C, Fleischman DS, Buss DM (2008): The daughter-
guarding hypothesis: Parental influence on, and emotional
reactions to, offspring’s mating behavior. Evol Psychol 6:
217–233.
Randall AK, Post JH, Reed RG, Butler EA (2013): Cooperating
with your romantic partner: Associations with interpersonal
emotion coordination. J Soc Pers Relat 30:1072–1095.
Schilbach L, Timmermans B, Reddy V, Costall A, Bente G,
Schlicht T, Vogeley K (2013): Toward a second-person neuro-
science. Behav Brain Sci 36:393–414.
Schippers MB, Roebroeck A, Renken R, Nanetti L, Keysers C
(2010): Mapping the information flow from one brain to anoth-
er during gestural communication. Proc Natl Acad Sci USA
107:9388–9393.
Schneiderman I, Zagoory-Sharon O, Leckman JF, Feldman R
(2012): Oxytocin during the initial stages of romantic attach-
ment: Relations to couples’ interactive reciprocity. Psychoneur-
oendocrinology 37:1277–1285.
Scholkmann F, Kleiser S, Metz AJ, Zimmermann R, Pavia JM,
Wolf U, Wolf M (2014): A review on continuous wave func-
tional near-infrared spectroscopy and imaging instrumentation
and methodology. Neuroimage 85:6–27.
Singh AK, Okamoto M, Dan H, Jurcak V, Dan I (2005): Spatial
registration of multichannel multi-subject fNIRS data to MNI
space without MRI. Neuroimage 27:842–851.
Song H, Zou Z, Kou J, Liu Y, Yang L, Zilverstand A, d’Oleire
Uquillas F, Zhang X (2015): Love-related changes in the brain:
A resting-state functional magnetic resonance imaging study.
Front Hum Neurosci 9:71.
Tang H, Mai X, Wang S, Zhu C, Krueger F, Liu C (2016): Interper-
sonal brain synchronization in the right temporo-parietal junc-
tion during face-to-face economic exchange. Soc Cogn Affect
Neurosci 11:23–32.
Tsuzuki D, Jurcak V, Singh AK, Okamoto M, Watanabe E, Dan I
(2007): Virtual spatial registration of stand-alone fNIRS data to
MNI space. Neuroimage 34:1506–1518.
Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F,
Etard O, Delcroix N, Mazoyer B, Joliot M (2002): Automated
anatomical labeling of activations in SPM using a macroscopic
anatomical parcellation of the MNI MRI single-subject brain.
Neuroimage 15:273–289.
Uddin LQ, Iacoboni M, Lange C, Keenan JP (2007): The self and
social cognition: The role of cortical midline structures and
mirror neurons. Trends Cogn Sci 11:153–157.
Vesper C, van der Wel RPRD, Knoblich G, Sebanz N (2011): Mak-
ing oneself predictable: Reduced temporal variability facilitates
joint action coordination. Exp Brain Res 211:517–530.
Xu XM, Aron A, Brown L, Cao GK, Feng TY, Weng XC (2011):
Reward and motivation systems: A brain mapping study of
early–stage intense romantic love in Chinese participants.
Hum Brain Mapp 32:249–257.
Xu XM, Brown L, Aron A, Cao GK, Feng TY, Acevedo B, Weng
XC (2012): Regional brain activity during early-stage intense
romantic love predicted relationship outcomes after 40 months:
An fMRI assessment. Neurosci Lett 526:33–38.
Yang DY, Rosenblau G, Keifer C, Pelphrey KA (2015): An integra-
tive neural model of social perception, action observation, and
theory of mind. Neurosci Biobehav Rev 51:263–275.
Yin J, Zhang JX, Xie J, Zou ZL, Huang XT (2013): Gender differ-
ences in perception of romance in Chinese college students.
PLoS One 8:e76294.
Zakriski AL, Wright JC, Underwood MK (2005): Gender similari-
ties and differences in children’s social behavior: Finding per-
sonality in contextualized patterns of adaptation. J Pers Soc
Psychol 88:844–855.
Zeki S (2007): The neurobiology of love. FEBS Lett 581:2575–2579.
Zhang X, Noah JA, Hirsch J (2016): Separation of the global and
local components in functional near-infrared spectroscopy sig-
nals using principal component spatial filtering. Neurophoton-
ics 3:015004-015004.
rCooperation in Lovers r
r841 r