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Two is better than one: The effects of strategic cooperation on intra- and inter-brain connectivity by fNIRS

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Inter-brain synchronization during joint actions is a core question in social neuroscience, and the differential contribution of intra- and inter-brain functional connectivity has yet to be clarified along with the role of psychological variables such as perceived self-efficacy. The cognitive performance and the neural activation underlying the execution of joint actions were recorded by functional Near-Infrared imaging during a synchronicity game. An 8-channel array of optodes was positioned over the frontal and prefrontal regions. During the task, the dyads received reinforcing feedback that was experimentally manipulated to induce adoption of common strategies. Intra- and inter-brain connectivity indices were computed along with an inter-brain/intra-brain connectivity index (ConIndex). Finally, correlation analyses were run to assess the relationship between behavioral and physiological levels. The results showed that the external feedback could modulate participant responses in both behavioral and neural components. After the reinforcing manipulation, there were faster response times and increased inter-brain connectivity, and ConIndex emerged primarily over the dorsolateral prefrontal cortex. Additionally, the presence of significant correlations between response times and inter-brain connectivity revealed that only the “two-players connection” may guarantee an efficient performance. The present study provides a significant contribution to the identification of intra- and inter-brain functional connectivity when social reinforcement is provided.
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RESEARCH ARTICLE
Two is better than one: The effects of strategic
cooperation on intra- and inter-brain
connectivity by fNIRS
Michela Balconi
1,2
*, Laurent Pezard
3
, Jean-Louis Nandrino
4
, Maria Elide Vanutelli
1,2
1Research Unit in Affective and Social Neuroscience, Catholic University of Milan, Milan, Italy,
2Department of Psychology, Catholic University of Milan, Milan, Italy, 3Aix-Marseille Universite
´, CNRS
UMR 7260, LNIA, Marseille, France, 4Laboratoire SCALab UMR CNRS 9193, Cognitive and Affective
Sciences Laboratory E
´quipe Dynamique des E
´motions et Pathologies (DEeP), University of Lille, Lille, France
*michela.balconi@unicatt.it
Abstract
Inter-brain synchronization during joint actions is a core question in social neuroscience,
and the differential contribution of intra- and inter-brain functional connectivity has yet to be
clarified along with the role of psychological variables such as perceived self-efficacy. The
cognitive performance and the neural activation underlying the execution of joint actions
were recorded by functional Near-Infrared imaging during a synchronicity game. An 8-chan-
nel array of optodes was positioned over the frontal and prefrontal regions. During the task,
the dyads received reinforcing feedback that was experimentally manipulated to induce
adoption of common strategies. Intra- and inter-brain connectivity indices were computed
along with an inter-brain/intra-brain connectivity index (ConIndex). Finally, correlation analy-
ses were run to assess the relationship between behavioral and physiological levels. The
results showed that the external feedback could modulate participant responses in both
behavioral and neural components. After the reinforcing manipulation, there were faster
response times and increased inter-brain connectivity, and ConIndex emerged primarily
over the dorsolateral prefrontal cortex. Additionally, the presence of significant correlations
between response times and inter-brain connectivity revealed that only the “two-players
connection” may guarantee an efficient performance. The present study provides a signifi-
cant contribution to the identification of intra- and inter-brain functional connectivity when
social reinforcement is provided.
Introduction
The natural motivation to form bonds with others as well as to cooperate and act prosocially
are fundamental connections between human beings. The so-called “social brain” has become
a pivotal focus of interest in neuroscience research to explore the neurophysiological basis of
interpersonal behavior [1]. In particular, cooperation can be defined as a social interaction
between two or more agents that induces sharing and produces common behavioral actions.
Joint actions are directed towards the achievement of specific objectives or common interests
PLOS ONE | https://doi.org/10.1371/journal.pone.0187652 November 16, 2017 1 / 17
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OPEN ACCESS
Citation: Balconi M, Pezard L, Nandrino J-L,
Vanutelli ME (2017) Two is better than one: The
effects of strategic cooperation on intra- and inter-
brain connectivity by fNIRS. PLoS ONE 12(11):
e0187652. https://doi.org/10.1371/journal.
pone.0187652
Editor: Francesco Di Russo, Universita degli Studi
di Roma La Sapienza, ITALY
Received: March 13, 2017
Accepted: October 22, 2017
Published: November 16, 2017
Copyright: ©2017 Balconi et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: Data access is
restricted by the Ethic Committee of the
Department of the Catholic University of Milan,
which approved the research protocol. The
Committee allowed the access to the data only
after a direct request to access by who is interested
in consulting the data. Requests may be sent to the
Department Director, prof. Paola Di Blasio (paola.
diblasio@unicatt.it).
Funding: The authors received no specific funding
for this work.
that provide an advantage to whomever is involved [2]. A recent study in social neurosciences
indicated that comprehension of such complex behaviors can only be obtained by considering
the interacting actors as a unique system [3]. In fact, interpersonal interactions occur when
somebody’s actions affect the immediate and future outcomes of the other individuals who are
involved [4].
Nonetheless, the majority of research within social neuroscience has explored such con-
structs using single-brain paradigms where a single individual interacts with a computer or
with another subject in turn-taking tasks (using off-line measurements) [57]. However, such
paradigms cannot explain the complexity of such processes in real time. Therefore, starting
with a few pioneering studies, an increased number of researchers have shifted towards a “sec-
ond-person” or “two-person neuroscience” [8] that has led to the hyperscanning paradigm.
This approach involves the simultaneous recording of neural activity from multiple partici-
pants who are interacting [9] and is based on the underlying principle that during joint
actions, people become implicitly coupled [10]. In fact, previous studies have revealed typical
patterns of inter-brain synchronization with correlated cortical responses. For example, Cui
and colleagues [11] simultaneously recorded the brain activity of two subjects while they
played a computer-based game in which they had to cooperate or compete. Inter-brain activity
coherence was performed, and the findings highlighted the presence of increased coherence
between the two brain signals in the right superior frontal cortices during cooperation but
not during competition. Holper and colleagues [12] also analyzed inter-brain connectivity
involved in imitation and found increased coherence compared to the control condition. Fur-
thermore, Nozawa and colleagues [13] explored interpersonal neural synchronization during
cooperative verbal communication and showed an increased synchronization within the fron-
topolar cortex. All these studies were conducted with functional Near-Infrared Spectroscopy
(fNIRS), which imposes low constraints and is relatively tolerant of head/body motion [14].
fNIRS has thus been proven to be a fundamental tool, since it permits an ecological experi-
mental setting in which participants can behave naturally in a realistic environment.
Nonetheless, to the best of our knowledge, no previous study has directly compared the spe-
cific contribution of intra- and inter-brain functional connectivity during cooperation in a
hyperscanning paradigm. Thus, a first aim of this study was to compare these two different
measures during a cooperative joint task. Functional connectivity can be defined as the tempo-
ral correlation between neurophysiological events that are spatially remote. It measures simul-
taneous coupling between two time series [15]. Furthermore, psychological constructs must be
taken into consideration when studying cooperative social performances. For example, when
cooperating, the adoption of common strategies is crucial and can be strongly influenced by
some psychological processes such as mentalization and self-perception. In fact, perceived
self-efficacy during social exchange can influence the motivation to create synergic actions.
Previous experiments already investigated the effects of external feedbacks assessing the behav-
ioral performance during cooperative or competitive tasks [1618]. Results showed that the
perception of positive outcomes can induce a superior cognitive performance and is related to
the activation of prefrontal areas [17,19]. In particular, the Dorsolateral Prefrontal Cortex
(DLPFC) was associated with social exchange, such as perspective taking and theory of mind
[20] but also with the suppression of selfish behavior [21] and commitment in significant rela-
tionships [22], which are extremely important during cooperation.
Although the role of an external feedback was considered in previous research, its effect on
brain (both intra- and inter-) connectivity has yet to be explored. Therefore, the aim of this
study was to investigate the relationship between intra and inter-brain functional connectivity
and behavioral synchronization during cooperation. A hyperscanning paradigm was applied,
and participants were required to synchronize their behavioral performance.
Two is better than one: The effect of strategic cooperation on intra- and inter-brain connectivity
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Competing interests: The authors have declared
that no competing interests exist.
We expected to observe brain and behavioral changes related to the experimental condi-
tions as well as possible correlations. We suppose that based on the social task, the two brains
may function in a synergic way (as shown by functional connectivity). The inter-brain connec-
tivity may show the ability of the two brains (and the two subjects) to function in a more simi-
lar way in terms of hemodynamic activity. At the same time, the behavioral performance may
become more synchronous (similar RTs/ERS performance), since the two subjects should
learn to make their performance more similar due to the motivational factors induced by the
joint task. Additionally, behavioral and neural levels are supposed to be correlated.
Halfway through the task, participants received feedback on their performance, which was
previously manipulated by the experimenter in a manner to induce positive perceived self-effi-
cacy that would influence the construction of joint strategies. We hypothesized that inter-
brain functional connectivity could increase after receiving this positive social feedback start-
ing from the assumption that a higher connectivity may be considered a strategic way to
induce the brains to “work together” [19]. In contrast, before this feedback, we expected higher
intra-brain connectivity as a preliminary intra-personal strategy. Finally, we predicted that
both intra- and interconnectivity should involve prefrontal regions, especially the DLPFC,
which was demonstrated to be relevant in social and cooperative exchanges [23].
Methods
Participants
Thirteen dyads (twenty-six total subjects) were recruited during academic activities (participa-
tion in lab activities). They were undergraduate students (M age = 24.08, SD = 1.78, fourteen
women). Each couple included same-sex individuals matched for age. They did not meet and
were not familiar with each other before the experimental session. The participants were all
right-handed, presented normal or corrected-to-normal visual acuity, and provided informed
written consent to participate in the study. Exclusion criteria included a history of psychopa-
thology (Beck Depression Inventory, BDI-II, [24]; State-Trait-Anxiety-Inventory, STAI, [25])
for the subjects and their immediate families. No neurological or psychiatric pathologies were
revealed, as determined in a preliminary screening phase.
The research was conducted according to the guidelines of the Declaration of Helsinki. It
was preliminarily approved by the local ethics committee of the Department of Psychology,
Catholic University of Milan. The project was approved in its final version. The data files were
stored in the Department repository, as requested by the local ethics committee. The legal
responsibility for the data custody is entrusted to the Department Director, who can be con-
tacted to receive a copy of the data. No payment was provided for the subjects’ performance,
and they provided their consent to participate in the research.
Procedure
Participants paired in dyads were comfortably seated side-by-side in a moderately darkened
room in front of a computer screen located approximately 60 cm from their eyes. They were
asked to perform a simple task for sustained selective attention (modified from the original
task of Balconi and Pagani [26]). To engage dyads in the task, they were told that some cogni-
tive measures would be used to evaluate their subjective performance since they are usually
used to screen future professional career success and teamwork capabilities. The cooperative
and joint nature of the game was stressed by telling dyads that their scorings were based on the
ability to synchronize their responses in terms of both accuracy (error rates, ERs) and response
times (RTs) with the other person. Specifically, they were told that “You have to cooperate
with your partner during the task to obtain a good joint performance. During the task, your
Two is better than one: The effect of strategic cooperation on intra- and inter-brain connectivity
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joined performance will be monitored and specific feedback will be furnished to verify this
cooperation.” Thus, the development of a joint cooperative strategy by the dyad was strongly
suggested. A dark screen separated the two members of the dyad to prevent visual contact and
to avoid any possible effect attributable to nonverbal behavior.
The game included an attentional task that required recognizing target stimuli among non-
targets that were based on four different combinations of shape and color, such as triangles vs
circles, blue vs green. After memorizing the target stimulus that was displayed on the screen,
stimuli were presented one after another. The target stimulus features varied in every experi-
mental block, composed by 25 trials. Each trial was composed of three stimuli. Dyads were
instructed to answer all the stimuli by pressing left/right buttons to decide for targets or non-
targets. Each stimulus remained on the screen for 500 msec with a 300 msec inter-stimulus
interval (ISI). After each trial, subjects received feedback in the form of two up-arrows (high
cooperation score); a dash (mean performance); or two down-arrows (low cooperation score).
This feedback period lasted 5000 msec. (including the arrows display for 500 msec.; and a
dark screen period lasted 4500 msec, the real post-feedback period used for the successive anal-
ysis). Then, an inter-trial interval (ITI) lasted for 5000 msec before the next trial was per-
formed (pre-feedback period).
The task was composed by eight blocks (of 25 trials each) (Fig 1). Thus, participants con-
stantly received a general evaluation of their cooperative performance: both trial feedback
(every three stimuli) and general feedback. Both trial feedback and general feedbacks were
experimentally manipulated a priori, and after each block, subjects were told by the computer
they had good cooperation (“you obtained a good cooperation score, 87% in terms of speed,
and 92% in terms of accuracy”) (general feedback) (Fig 1). They were also encouraged to keep
up their performance level during the experiment. During the task, after an initial medium
Fig 1. Experimental task. Experimental procedure representing the setting and the experimental tasks.
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Two is better than one: The effect of strategic cooperation on intra- and inter-brain connectivity
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performance, subjects were constantly reinforced about their good cooperation by presenting
up-arrows in 70% of cases, while the dash or the down-arrows were presented in 30% of cases
(trial feedback) (it was preliminarily explained to the subjects that these symbols represent a
good or a bad trial feedback on their performance, respectively). In addition, after each block
of 25 trials, subjects were required to assess their performance and cognitive efficacy in terms
of their ranking position on a seven-point Likert scale (“did you improve your performance?”,
from one = most decreased ranking based on how they perceived their performance to seven =
most improved ranking based on how they perceived their performance). Specific analysis
(ANOVA applied to Likert scale) showed significant increased self-ranking after external feed-
back across the eight blocks (F[1, 25] = 10.45, p.001, η
2
= .41) with higher self-ranking for
each block compared to the previous ones (significant differences p.001 for all compari-
sons). Participants were strongly engaged in the cooperative context (93% told to be strongly
engaged, as reported in a post-experimental questionnaire).
Subjects were also required to self-report their degree of trust of the exact feedback of the
performance, which showed high trust (95%), a relevance of the task for social status represen-
tation (96%), and the perception of improved ranking position during the task (94%).
Performance scoring
The RTs (msec) were recorded from the stimulus onset, and ERs were calculated as the total
number of incorrect detections out of the total trial for each category. Therefore, higher values
represented increased incorrect responses.
fNIRS
fNIRS measurements were conducted with NIRScout System (NIRx Medical Technologies,
LLC. Los Angeles, California) using an 8-channel array of optodes (4 light sources/emitters
and 4 detectors) covering the frontal and prefrontal area. Emitters were placed on positions
(FC3-FC4 and F1-F2), while detectors were placed on FC1-FC2 and F3-F4) (Fig 2). Emitter-
detector distance was kept at 30 mm for contiguous optodes and near-infrared light was used
at two wavelengths (760 and 850 nm). NIRS optodes were positioned on the subject’s head
using an NIRS cap according to the international 10/5 system. The following channels were
reported: Ch 1 (FC3-F3) and Ch 3 (FC4-F4) correspond to the left and right (respectively)
DLPFC (Brodmann Area 9). Ch 2 (FC3-FC1) and Ch 4 (FC4-FC2) correspond to the left and
right (respectively) Dorsal Pre-motor Cortex (DPMC, Brodmann Area 6). Ch 5 (F1-F3) and
Ch 7 (F2-F4) corresponding to the left and right (respectively) Frontal Eye Fields (FEF, Brod-
mann Area 8). Ch 6 (F1-FC1) and Ch 8 (F2-FC2) correspond to the left and right (respectively)
Superior Frontal Gyrus (SFG, Brodmann Area 6) [27].
Changes in the concentration of oxygenated (O2Hb) and deoxygenated hemoglobin (HHb)
were recorded continuously throughout the task with NIRStar Acquisition Software that started
from a 120-s resting baseline. Signals obtained from the 8 NIRS channels were acquired with a
sampling rate of 6.25 Hz and analyzed and transformed with nirsLAB software (v2014.05; NIRx
Medical Technologies LLC, 15Cherry Lane, Glen Head, NY, USA) according to their wave-
length and location, which resulted in values for the changes in the concentration of oxy and
deoxygenated hemoglobin for each channel, which was scaled in mmolmm.
The raw O2Hb and HHb data from each channel were digitally bandpass filtered at 0.01–
0.3 Hz. Then, the mean concentration of each channel was calculated by averaging data across
the trials, starting from the feedback onset for the following 4500 msec. The mean concentra-
tion value of 4500 msec before the feedback was used as event-related baseline, where the
brain activity is supposed to be at a minimum. According to the mean concentrations in the
Two is better than one: The effect of strategic cooperation on intra- and inter-brain connectivity
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time series, the effect size in every condition was calculated for each channel and subject. The
effect sizes (Cohen’s d) were calculated as the difference of the means of the baseline and trial
divided by the standard deviation (sd) of the baseline, which is d = (m1-m2)/s, with m1 and
m2 being the mean concentration values during baseline and trial, respectively. The effect sizes
(Cohen’s d) were calculated as the difference of the means of the baseline and trial divided by
the standard deviation (sd) of the baseline: d = (m1-m2)/s, with m1 and m2 being the mean
concentration values during the baseline and trial, respectively, as well as the SD of the base-
line. Then, the effect sizes obtained from the 8 channels were averaged to increase the signal-
to-noise ratio. Although NIRS raw data were originally relative values and could not be directly
Fig 2. fNIRS montage. The location of NIRS channels. The emitters (orange) were placed on positions
FC3-FC4 and F1-F2, while detectors (red) were placed on FC1-FC2 and F3-F4. The resulting channels
(green) were as follows: Ch 1 and Ch 3 correspond to the left and right DLPFC. Ch 2 and Ch 4 correspond to
the left and right DPMC. Ch 5 and Ch 7 correspond to the left and right FEF. Ch 6 and Ch 8 correspond to the
left and right SFG.
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averaged across subjects or channels, effect sizes normalized data could be averaged regardless
of the unit since the effect size is not affected by differential pathlength factors (DPF) [2830].
Finally, the event-related responses to stimuli with respect to each baseline signs have been
inverted.
Functional connectivity analysis
Three sets of analyses were performed with respect to behavioral (ERs; RTs) and neurophysio-
logical (fNIRS: O2Hb measures) measures.
First, a repeated measure ANOVAs with the independent factor set as Condition (Cond:
pre- vs. post-feedback) was applied to ER, and RTs.
Second, a set of analyses were applied to the neurophysiological level, which consisted of
four different steps. First, to obtain intra- and inter-brain connectivity, the partial correlation
coefficient P
ij
was computed to obtain functional connectivity indices. They were obtained by
normalizing the inverse of the covariance matrix Γ=S
1
:
G¼ ðGijÞ ¼ S1:inverse of the covariance matrix
Pij ¼  Gij
ffiffiffiffiffiffiffiffiffiffi
GiiGjj
p:partial correlation matrix
This quantifies the relationship between two signals (i, j) independently from each other
[31].
Then, we applied ANOVAs to intra- and inter-brain measures. A successive phase included
the calculation of a specific ConIndex as the ratio between inter-brain and intra-brain connec-
tivity (Inter
con
/Intra
con
) to directly compare the two connectivity levels. Finally, we applied
ANOVA to a ConIndex dependent measure.
For ANOVA, the independent repeated factors were Condition (Cond), Localization (Loc:
DLPFC, DPMC, FEF, SFG) and Lateralization (Lat: left vs. right). For all the ANOVA tests, the
degrees of freedom were corrected using Greenhouse–Geisser epsilon when appropriate. Post
hoc comparisons (contrast analyses) were applied to the data. A Bonferroni test was applied
for multiple comparisons. In addition, the normality of the data distribution was preliminary
tested (kurtosis and asymmetry tests). The normality assumption of the distribution was sup-
ported by these preliminary tests.
Finally, a third step included a correlation analysis to compare behavioral (RTs and ERs)
and neurophysiological (intra-brain connectivity; inter-brain connectivity; ConIndex) mea-
sures to explore the co-modulation of these different levels with each other.
To exclude a possible learning effect due to pre/post-feedback condition, a preliminary
analysis was conducted, comparing distinctly the first set of four intervals (pre-feedback inter-
vals) and the second set of four intervals (post-feedback) for all the dependent measures (RTs,
ERs, O2Hb). No significant differences among the four intervals (respectively before and after
the feedback) were found. Therefore, we did not include this factor in the remaining analyses.
Results
ERs and RTs
For ERs measurement, ANOVA did not show significant effects for Cond (F[1, 25] = 1.90, p=
.12, η
2
= .17). In contrast, as for RTs, ANOVA indicated a significant main effect for Cond (F
[1, 25] = 9.05, p.001, η
2
= .39) with decreased RTs during post-feedback compared to pre-
feedback conditions (Fig 3).
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Intra-brain connectivity
The statistical analyses were applied to intra-brain indices for O2Hb and HHb-concentrations.
The analysis on HHb did not reveal significant effects, and for this reason we reported only
results for O2Hb-values. As shown by ANOVA, the Loc effect was significant (F[1, 83] =
11.34, p.001, η
2
= .40). As revealed by post hoc analysis, intra-brain connectivity was gener-
ally higher in DLPFC compared to other areas (compared to DPMC F[1, 24] = 7.39, p.001,
η
2
= .35, FEF F[1, 24] = 8.13, p.001, η
2
= .34, SFG F[1, 24] = 9.08, p.001, η
2
= .37) (Fig 4).
No other simple or interaction effect was significant.
Inter-brain connectivity
The ANOVA applied to inter-brain indices for the dyads showed a significant Cond main
effect (F[1, 12] = 10.45, p.001, η
2
= .33) and a Cond ×Localization interaction effect
(F[1, 36] = 9.67, p.001, η
2
= .38). Indeed, for the main effect, increased inter-brain connec-
tivity was observed in the post-feedback condition compared to pre-feedback condition. In
addition, as revealed by a significant interaction (simple effects), inter-brain connectivity
increased in post-feedback compared to pre-feedback in DLPFC (F[1, 12] = 10.45, p.001,
η
2
= .41) (Fig 5).
ConIndex
The ANOVA applied to ConIndex showed a significant Cond x Localization interaction effect
(F[1, 36] = 9.67, p.001, η
2
= .38). Indeed, an increased Index was observed in post-feedback
than the pre-feedback condition within the DLPFC. Therefore, as shown by the Index, we can
conclude there is a general increase in inter-brain connectivity compared to intra-brain con-
nectivity in DLPFC for the post-feedback condition (Fig 6).
Correlation analysis
Correlation analyses were applied to behavioral (ERs; RTs) and neurophysiological measures
(intra- and inter-brain connectivity; ConInd). Corrections for multiple comparisons (Bonfer-
roni corrections) were applied to the analyses. To compare brain connectivity to behavioral
Fig 3. Behavioral results. RTs modulation as a function of Condition (pre vs post). The speed performance
was characterized by faster RTs during the post-feedback condition.
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performance, RTs and ERs, the initial correlational values obtained within each dyad were cal-
culated and taken as measures for successive correlational analysis. As shown by Pearson
Fig 4. Intra-brain connectivity. Bar graph (a) and intra-brain connectivity map (b) of O2Hb correlations as a
function of Localization (averaged for pre- and post-feedback). The results showed that intra-brain
connectivity was generally higher in DLPFC than in other areas, independently from the pre- or post-
feedback.
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correlation coefficients, RTs revealed a significant negative correlation with the inter-brain
connectivity within left and right DLPFC in post-feedback condition (respectively r
2
= —.523,
Fig 5. Inter-brain connectivity. Bar graph (a) and inter-brain connectivity map (b) of O2Hb correlations as a
function of Condition and Localization. The results showed that inter-brain connectivity increased in the post-
feedback stage compared to pre-feedback in DLPFC.
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Fig 6. ConIndex results. Increased Index was observed in post-feedback than pre-feedback condition within
the DLPFC, thus suggesting a general increased inter-brain connectivity compared to intra-brain connectivity
in DLPFC for the post-feedback condition.
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p.001; r
2
= —.565, p.001): indeed, the increased right and left DLPFC connectivity was
related to a reduction of RTs values in the post-feedback condition. No other effect was statisti-
cally significant either (Fig 7A and 7B)
Discussion
The present research study analyzed the behavioral performance and the brain activity (intra-
and inter-brain connectivity) during a joint action task where external feedback was used to
reinforce good cooperative outcomes.
The modulation of different variables before (pre) and after (post) receiving such feedback
has been considered, such as RTs, ERs, and intra- and inter-brain functional connectivity.
Additionally, correlations between behavioral and brain activity have been performed.
First, as predicted, the results showed that the external feedback could modulate partici-
pants’ responses in both behavioral and neural components. In fact, after the reinforcing feed-
back, RTs were faster and inter-brain connectivity indices were higher than in pre-feedback
condition. According to our hypotheses and to results obtained in previous research, the
Fig 7. Correlation results. RTs revealed a significant negative correlation with the inter-brain connectivity
within right (a) and left (b) DLPFC in post-feedback conditions, such that the increased right and left DLPFC
connectivity was related to a reduction of RTs values in post-feedback condition.
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perception of positive feedbacks, and subsequently of self-efficacy, is able to induce improved
behavioral performance in different educational [32,33], sport [34], and work [35] contexts.
Such effects were also related to the activation of prefrontal sites, which are usually triggered by
an increase in cognitive synergy and brain-to-brain coupling [36]. Therefore, we could speak
about a general “gain” due to positive reinforcement. The feedback, in fact, may have generated
a strategic joint trend and boosted optimization of the cognitive performance within the dyad.
However, in the present research, we also explored the contribution of specific frontal areas
in the different experimental conditions more directly. In detail, we found that the increase in
cortical connectivity was mainly localized within the DLPFC for all the neurophysiological
measures. This trend is particularly relevant since both intra-brain and inter-brain indices sup-
ported the recruitment of a brain area involved in social exchange. In fact, previous research
underlined the role of DLPFC not only in perspective and theory of mind [20] but also in the
suppression of selfish behavior [21] and commitment in significant relationships [22], even if
in inter-brain patterns in the DLPFC have emerged only after social reinforcement. The same
results were obtained with ConIndex, which suggests that the extent to which the two indices
contribute to such activation is greater in inter-brain correlation. Therefore, the supplemen-
tary contribution the inter-brain with respect to intra-brain connectivity was substantial in the
second part of the task. Interestingly, intra-brain connectivity was not affected by the feedback
but only showed an increased pattern of connection between the two DLPFC. This finding
suggests that the engagement of DLPFC after social feedback can be referred to as the adoption
of joint strategies, while the increased connectivity between homologous DLPFC in intra-
brain analysis can suggest the general recruitment of a neural network for the joint task. Previ-
ous results already revealed that prefrontal areas are fundamental in social status regulation
and joint actions [3739]. Additionally, using an EEG-based hyperscanning technique, specific
DLPFC activation emerged during reciprocal interactions [40].
Moreover, it has been demonstrated that only the “two-players connection” may guarantee
an efficient performance, as revealed by the presence of significant correlations between RTs
and inter-brain connectivity indices, which confirms a “reinforced trend.” In fact, we may sup-
pose that the external reinforcement could have modulated the effective joint behavior with
increased cognitive performance and inter-brain activity by two inter-agents. In other terms,
we may suggest that the two levels, behavioral and cortical, were effective in signaling the social
effect of the reinforcing feedback. Additionally, they showed similar responsiveness to external
conditions that stress the joint significance of inter-subjective actions.
In addition, compared to other previous research, which included both negative feedback
on cooperative actions [41] or competitive tasks [42,43], the present study could induce differ-
ent and specific effects, including improving cognitive performance and the increased inter-
brain connectivity (but not the intra-brain connectivity), which specifically represents cooper-
ative and positively reinforced cooperative conditions.
Finally, the significance of the correlation between behavioral performance (RTs reduction)
and the inter-brain connectivity, but not between RTs and intra-brain connectivity, may sug-
gest that a brain-to-brain coupling induced by a cooperative task may be directly associated
with a significantly improved performance. However, we do not suppose that the brain affects
behavior, or vice versa, because it falls short of a “causal model.” We only observed brain and
behavioral changes related to the experimental conditions and their possible relations. That is,
we do not suppose that inter-brain functional connectivity may directly affect behavior or, in
the other direction, that behavioral changes affect the strength of inter-brain connectivity. We
can only assume that based on the present social task, two or more brains may function in a
more synergic way (as shown by the connectivity values based on correlation) and that, at the
same time, the behavioral performance may become more synchronous (more coherent RTs).
Two is better than one: The effect of strategic cooperation on intra- and inter-brain connectivity
PLOS ONE | https://doi.org/10.1371/journal.pone.0187652 November 16, 2017 12 / 17
As demonstrated by other experiments and the present results, during social interactions,
people may significantly affect and shape each other’s behaviors [44] through basic resonance
mechanisms. Recent research proposed that during social exchange, such synchronization can
actually occur in the form of an alignment of behavior [45,46], posture [47] as well as neuro-
physiological [3,48] and psychophysiological measures [4953].
Previous hyperscanning approaches have already highlighted some patterns of behavioral
synchronization for their cooperation by EEG [5457] or functional near-infrared spectros-
copy (fNIRS) [6,13,17,58,59].
As shown by previous studies and by our results, the “synergic brain” may support better
social interactions with benefits for all the actors involved. For this reason, a consistent and rel-
evant improvement could be observed between the participants, who may benefit from the
synergy established between the neuroanatomical networks with a significant gain for the
coordination of behavioral activities. In other words, a good synchronization based on a syner-
gic strategy is advantageous for the efficiency of joint behavior, which benefits in turn by the
higher coordination between our brains, which learn to “communicate” to support the behav-
ioral level.
Such results are also crucial from a neuroanatomical point of view, since the involvement of
prefrontal areas have been associated with social exchange. Thus, after receiving a positive
feedback about a dyad’s synchrony, increased connectivity might emerge in areas related to
empathy, bonding, and, importantly, in the suppression of self-centered behaviors in favor of a
common goal.
The present results could also be explained taking into account the “attentional effect” that
was also found to induce a significant increased inter-brain connectivity in the case of a joined
task [19]. However, two main considerations should also be reported. In the present study, the
absence of a significant intra-brain effect may partially require adjunctive explanations, since a
positive feedback (although on a joined-action level) should also have improved the individual
attentional mechanism. Additionally, we may suppose that this attentional effect could not
have been sufficient to support the enduring and constant increased performance (and brain
connectivity) during the entire task, since, as shown by previous research, the attentional effect
appears to decline over time. Therefore, the motivational and social reinforcement may have
acted as a relevant sustained factor to produce both behavioral and brain effects during the
task.
Some limitations should be reported for the present study. First, the limited number of
dyads should be increased in future research. Second, to better evaluate the cortical localization
and the functional meaning of the brain coupling effect, the posterior areas of the brain should
be included. Therefore, in future research, a global analysis on the cortical sites could be
applied. Finally, although the analyses permitted us to isolate the contribution of intra and
inter-brain connectivity, a more systematic comparison could be made with other experimen-
tal conditions consisting, for example, in competitive strategies, cooperation with negative
feedback, or a solitary game.
Acknowledgments
The authors are grateful to Justine Facchini for her help with data preprocessing.
Author Contributions
Conceptualization: Michela Balconi.
Data curation: Michela Balconi, Jean-Louis Nandrino, Maria Elide Vanutelli.
Two is better than one: The effect of strategic cooperation on intra- and inter-brain connectivity
PLOS ONE | https://doi.org/10.1371/journal.pone.0187652 November 16, 2017 13 / 17
Formal analysis: Laurent Pezard, Maria Elide Vanutelli.
Investigation: Michela Balconi, Jean-Louis Nandrino.
Methodology: Michela Balconi, Laurent Pezard.
Project administration: Michela Balconi.
Resources: Michela Balconi, Maria Elide Vanutelli.
Software: Laurent Pezard, Maria Elide Vanutelli.
Supervision: Michela Balconi.
Validation: Michela Balconi, Maria Elide Vanutelli.
Writing – original draft: Michela Balconi, Laurent Pezard, Jean-Louis Nandrino, Maria Elide
Vanutelli.
Writing – review & editing: Michela Balconi.
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... Applications in motor synchronization were relatively common and generally had participants complete synchronous physical motions as an experimental task in the lab e.g., [139]. These tasks included a cooperative button press task [140] where participants interact either side-by-side e.g., [141] or face-to-face e.g., [142], computer games [51,[141][142][143], joint-tapping tasks [32,40,144], and synchronization tasks [145][146][147]. One study utilized a finger-tapping task to record between-brain hemodynamics [40]. ...
... Applications in motor synchronization were relatively common and generally had participants complete synchronous physical motions as an experimental task in the lab e.g., [139]. These tasks included a cooperative button press task [140] where participants interact either side-by-side e.g., [141] or face-to-face e.g., [142], computer games [51,[141][142][143], joint-tapping tasks [32,40,144], and synchronization tasks [145][146][147]. One study utilized a finger-tapping task to record between-brain hemodynamics [40]. ...
... Orientation. Applications in motor synchronization adopted various orientation methods e.g., [32,40,51,[139][140][141][142][143][144][145][146][147]. For example, Six studies had participants oriented side-by-side [51,139,[141][142][143]146], Two studies had participants oriented back-to-back [32,144], and four of the studies had participants interact face-to-face [40,140,145,147]. ...
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... It can be intended as a proxy for functional specialization of an individual's brain activity (e.g., Balconi & Caldiroli, 2011). The second indicator derived from an hyperscanning design (Balconi & Vanutelli, 2017) is inter-brain connectivity, which is identified as that functional connectivity between individuals' brains related to interpersonal coupling mechanisms during social exchanges (e.g., Balconi et al., 2020;Kawasaki et al., 2013). Interestingly, both inter-brain and intra-brain, synchrony showed to be good predictors for collective performance (Reinero et al., 2020). ...
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... The PFC plays a crucial role in promoting interpersonal synchronization [22,25], and here it could have acted as a "soundboard" or an IA amplifier that enhances the effect of IA on linguistic synchronization. Indeed, the activation of the DLPFC has previously been linked to social processes such as partner cooperation [22], mutual collaborative behaviors, and interpersonal tuning [24,25]. However, more confirmative studies are needed to support the interpretations of the results of this pilot study. ...
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... We did not find significant intra-brain differences between conditions in the present study, which is consistent with previous studies (Cui et al., 2012;Simony et al., 2016;Balconi et al., 2017b), implying the significance of adopting an interbrain perspective in the study of cooperation and competition. Nevertheless, as a few other studies have reported intra-brain results related to social interactions (e.g. ...
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... We did not find significant intra-brain differences between conditions in the present study, which is consistent with previous studies (Cui et al., 2012;Simony et al., 2016;Balconi et al., 2017b), implying the significance of adopting an interbrain perspective in the study of cooperation and competition. Nevertheless, as a few other studies have reported intra-brain results related to social interactions (e.g. ...
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Cooperation and competition are two basic modes of human interaction. Their underlying neural mechanisms, especially from an inter-personal perspective, have not been fully explored. Using the EEG-based hyperscanning technique, the present study investigated the neural correlates of both cooperation and competition within the same ecological paradigm using a classic motion-sensing tennis game. Both the inter-brain coupling (the inter-brain amplitude correlation and inter-brain phase-locking) and intra-brain spectral power were analyzed. Only the inter-brain amplitude correlation showed a significant difference between cooperation and competition, with different spatial patterns at the theta, alpha, and beta frequency bands. Further inspection revealed distinct inter-brain coupling patterns for cooperation and competition; cooperation elicited positive inter-brain amplitude correlation at the delta and theta bands in extensive brain regions, while competition was associated with negative occipital inter-brain amplitude correlation at the alpha and beta bands. These findings add to our knowledge of the neural mechanisms of cooperation and competition and suggest the significance of adopting an inter-brain perspective in exploring the neural underpinnings of social interaction in ecological contexts.
... Based on prior research and to avoid large number of multiple comparisons, we choose to use a theory-driven ad-hoc approach and to focus on interbrain synchrony only between homologies areas ( Balconi et al., 2017 ;Kawasaki et al., 2013 ;Koike et al., 2020 ;Kuhlen et al., 2012 ;Liu et al., 2017 ). Consistent with much prior interbrain research ( Dumas et al., 2010 ;Mu et al., 2017 ;Pérez et al., 2017 ), we used phase locking value (PLV) to estimate the amount of synchrony between each electrode two electrodes ( Dumas et al., 2010 ). ...
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Functional connectivity during cooperative actions is an important topic in social neuroscience that has yet to be answered. Here, we examined the effects of administration of (fictitious) negative social feedback in relation to cooperative capabilities. Cognitive performance and neural activation underlying the execution of joint actions was recorded with functional near-infrared spectroscopy (fNIRS) on prefrontal regions during a task where pairs of participants received negative feedback after their joint action. Performance (error rates (ERs) and response times (RTs)) and intra- and inter-brain connectivity indices were computed, along with the ConIndex (inter-brain/intra-brain connectivity). Finally, correlational measures were considered to assess the relation between these different measures. Results showed that the negative feedback was able to modulate participants' responses for both behavioral and neural components. Cognitive performance was decreased after the feedback. Moreover, decreased inter-brain connectivity and increased intra-brain connectivity was induced by the feedback, whereas the cooperative task pre-feedback condition was able to increase the brain-to-brain coupling, mainly localized within the dorsolateral prefrontal cortex (DLPFC). Finally, the presence of significant correlations between RTs and inter-brain connectivity revealed that ineffective joint action produces the worst cognitive performance and a more 'individual strategy' for brain activity, limiting the inter-brain connectivity. The present study provides a significant contribution to the identification of patterns of intra- and inter-brain functional connectivity when negative social reinforcement is provided in relation to cooperative actions.
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Working together feels easier with some people than with others. We asked participants to perform a visual search task either alone or with a partner while simultaneously measuring each participant's EEG. Local phase synchronization and inter-brain phase synchronization were generally higher when subjects jointly attended to a visual search task than when they attended to the same task individually. Some participants searched the visual display more efficiently and made faster decisions when working as a team, whereas other dyads did not benefit from working together. These inter-team differences in behavioral performance gain in the visual search task were reliably associated with inter-team differences in local and inter-brain phase synchronization. Our results suggest that phase synchronization constitutes a neural correlate of social facilitation, and may help to explain why some teams perform better than others.
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The aim of the present study was to investigate the neural bases of cooperative behaviors and social self-perception underlying the execution of joint actions by using a hyperscanning brain paradigm with functional near-infrared spectroscopy (fNIRS). We firstly found that an artificial positive feedback on the cognitive performance was able to affect the self-perception of social position and hierarchy (higher social ranking) for the dyad, as well as the cognitive performance (decreased error rate, ER, and response times, RTs). In addition, the shared cognitive strategy was concurrently improved within the dyad after this social reinforcing. Secondly, fNIRS measures revealed an increased brain activity in the postfeedback condition for the dyad. Moreover, an interbrain similarity was found for the dyads during the task, with higher coherent prefrontal cortex (PFC) activity for the interagents in the postfeedback condition. Finally, a significant prefrontal brain lateralization effect was revealed, with the left hemisphere being more engaged during the postfeedback condition. To summarize, the self-perception, the cognitive performance, and the shared brain activity were all reinforced by the social feedback within the dyad.