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Cooperation is a construct within social cognition that requires both self-perception and the comprehension of others' actions. In the case of synchronized activities the adoption of common strategies is crucial, but this process can be strongly influenced by those variables. In fact, self-perceived efficacy within the social exchange can affect the motivational components toward the creation of synergic actions. Thus, what happens when our performance is efficient or inefficient during cooperation? This question was answered in the present study where we compared behavioral performance and neural activation across different conditions where subjects received an external feedback assessing a good or a poor outcome during a cooperative game. The request was to synchronize responses in a way to achieve good cooperation scorings. Results showed that the behavioral performance was affected by feedback valence, since the negative feedback induced a significant worse performance in contrast to the positive one, which significantly increased performance. For what concerns neural activation, data from functional near-infrared spectroscopy (fNIRS) showed a specific lateralization effect with the right DLPFC recruited in the case of negative feedback, and an opposite left-sided effect in the case of a positive feedback. Findings were interpreted by proposing that the inefficient condition could be similar to a competitive context since the perception of a failed joint action could have frustrated the cooperative attitude and the use of joint strategies.
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ORIGINAL RESEARCH
published: 09 May 2017
doi: 10.3389/fnsys.2017.00026
Frontiers in Systems Neuroscience | www.frontiersin.org 1May 2017 | Volume 11 | Article 26
Edited by:
Agnes Gruart,
Pablo de Olavide University, USA
Reviewed by:
Xunbing Shen,
Jiangxi University of Traditional
Chinese Medicine, China
Raúl G. Paredes,
National Autonomous University of
Mexico, Mexico
*Correspondence:
Michela Balconi
michela.balconi@unicatt.it
Maria E. Vanutelli
mariaelide.vanutelli@unicatt.it
Received: 15 February 2017
Accepted: 21 April 2017
Published: 09 May 2017
Citation:
Balconi M and Vanutelli ME (2017)
When Cooperation Was Efficient or
Inefficient. Functional Near-Infrared
Spectroscopy Evidence.
Front. Syst. Neurosci. 11:26.
doi: 10.3389/fnsys.2017.00026
When Cooperation Was Efficient or
Inefficient. Functional Near-Infrared
Spectroscopy Evidence
Michela Balconi 1, 2*and Maria E. 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
Cooperation is a construct within social cognition that requires both self-perception
and the comprehension of others’ actions. In the case of synchronized activities the
adoption of common strategies is crucial, but this process can be strongly influenced by
those variables. In fact, self-perceived efficacy within the social exchange can affect the
motivational components toward the creation of synergic actions. Thus, what happens
when our performance is efficient or inefficient during cooperation? This question was
answered in the present study where we compared behavioral performance and neural
activation across different conditions where subjects received an external feedback
assessing a good or a poor outcome during a cooperative game. The request was to
synchronize responses in a way to achieve good cooperation scorings. Results showed
that the behavioral performance was affected by feedback valence, since the negative
feedback induced a significant worse performance in contrast to the positive one, which
significantly increased performance. For what concerns neural activation, data from
functional near-infrared spectroscopy (fNIRS) showed a specific lateralization effect with
the right DLPFC recruited in the case of negative feedback, and an opposite left-sided
effect in the case of a positive feedback. Findings were interpreted by proposing that
the inefficient condition could be similar to a competitive context since the perception
of a failed joint action could have frustrated the cooperative attitude and the use of joint
strategies.
Keywords: cooperation, feedback, self-efficacy, interpersonal strategies, emotions, fNIRS
INTRODUCTION
When we speak about cooperation we usually refer to collaborative inter-actions that occur between
two or more actors with the aim to pursue common goals. This kind of behavior is addressed
toward the realization of a definite objective that can provide benefits to all the people involved.
While chasing such targets, a set of cognitive and affective mechanisms arise and support behavior
(Balconi et al., 2012; Balconi and Canavesio, 2013, 2014; Liu et al., 2015, 2016; Balconi and
Vanutelli, 2016a; Vanutelli et al., 2016). Moreover, during cooperation, the behavioral performance
essentially entails the involvement of social cognition processes (Decety et al., 2004; Declerck
et al., 2010). For example, previous research explored the effects of cooperation in relation to self-
perception, self-efficacy, and social cognition within social interactive contexts. Findings revealed
that a cooperative condition may reinforce group membership, social cohesion, self-efficacy and
Balconi and Vanutelli When Cooperation Was Efficient or Inefficient
the perception of a high rank within a social hierarchy (Goldman
et al., 1977; Funane et al., 2011; Cui et al., 2013; Balconi
and Pagani, 2015; Chung et al., 2015). According to recent
studies on brain functioning, social cognition and self-efficacy
are represented within prefrontal areas (Iacoboni et al., 2004;
Mitchell et al., 2005a,b; D’Argembeau et al., 2007; Beer et al.,
2009; Wagner et al., 2012; Jenkins et al., 2014). Indeed, it was
observed that the neural circuits linking the limbic system and
the prefrontal cortex (PFC) may support the emotional and
cognitive components of social interactions during cooperation
(Levitan et al., 2000). Specifically, it was found the Dorsalateral
Prefrontal Cortex (DLPFC), the Orbitofrontal Cortex (OFC) and
some portion of the Frontal Gyrus (FG) are generally recruited
during interpersonal cooperation (Chiao et al., 2009; Balconi
and Pagani, 2014, 2015; Wang et al., 2016). Strong inter-brain
neural synchrony was observed in the posterior region of the
right middle (MFG) and superior frontal gyrus (SFG) during
cooperative joint actions, suggesting that this area could be
involved in goal-oriented social interaction such as complex
dynamics and social decision-making (Baker et al., 2016; Liu
et al., 2016). The same patterns of inter-brain synchrony during
cooperation was also observed in the dorsomedial prefrontal
cortex (dmPFC).
The activation of prefrontal regions during social interactions
that implicate a cooperative action probably reflects the
recruitment of brain networks that can provide top–down
control over cognitive processes and emotional responses
involved during cooperative joint interactions in a way to
prepare the best behavioral response (Marsh et al., 2009).
Indeed, these brain areas are usually recruited during the
regulation of cognitive and socio-emotional responses (Gray
et al., 2002; Ochsner and Gross, 2005; Knyazev, 2007; Ray and
Zald, 2012). Nonetheless, as emerged in many previous studies,
a psychological construct has been considered to mediate the
neural response during the participation in cooperative joint-
actions, that is the evaluation of the behavioral outcome as
efficient or inefficient. In fact, this perception is a powerful
reinforce that can both influence goal-directed behaviors and
train the brain to work jointly. Previous experiment already
investigated the effects of positive outcomes on self-perception,
behavioral performance and neural correlates for cooperative or
competitive tasks based on the effects of an external feedback
(Monterosso et al., 2002; Balconi and Vanutelli, 2016a,b). Results
showed that the perception of positive feedbacks is able to induce
a positive behavioral performance and is related to the activation
of prefrontal sites. In fact, it is associated with an increase
in cognitive synergy and brain-to-brain coupling (Baker et al.,
2016). Nevertheless, although the role of an external feedback
was considered as a key factor in cooperative tasks, no previous
study directly compared the influence of a positive vs. a negative
feedback on performance and neural correlates. In detail, what
kind of neural and behavioral response can we observe when we
observe to be efficient or, on the contrary, inefficient during the
adoption of joint strategies?
Therefore, it is relevant and urgent to distinguish the
perception of our social efficacy or inefficacy and their effects
in different interpersonal conditions—namely in cooperative
situations with a negative feedback or with a positive feedback,
which are qualitatively distinct psychological domains. Different
possible ways are suggested to differentiate unsuccessful from
successful forms of cooperation. Firstly, from a cognitive
point of view, we may suppose that in the case of failure
perception a higher mental effort is required to represent a
sort of “dysfunctional” interaction where the synergic strategy
is disrupted. Indeed, based on the interaction modalities
(positive or negative cooperation), individuals may either
facilitate or obstruct others’ goal achievement (such as in
competition). Concurrently, they can self-represent themselves
as less proficient in relation to the common task. Supplementary
research demonstrated that one’s own actions are facilitated when
others’ actions are at the disposal of common interests (as in
cooperation compared with competition) and when they are
efficient (as in successful cooperation; Knoblich and Jordan,
2003; Sebanz et al., 2003). In contrast, in the case of inefficient
cooperation, the interlocutors’ behavior and the outcomes of
the joint-action are less predictable than in the case of effective
cooperation, where there is a planned expectation for the
other agent’s behavior and the positive outcomes. As found for
competitive tasks, it is plausible that we need to determine
agents’ mental state that is decoupled from reality, and to
handle simultaneously these two competing views (the real one
about inefficacy and the desirable one for a good performance)
on the interactions (Leslie, 1987; Gallagher and Frith, 2003).
As such, this condition may impose an increase in cognitive
load, due the selection of salient information or response to
achieve a new goal internally represented (Humphrey, 1988;
Nigg, 2001). Thus, the strong increase in the prefrontal activity—
mainly the mPFC—observed during competition or in the case
of a failure may in part mirror higher executive processing
demands (Decety et al., 2004). Specifically, it was shown that the
processing load associated with competitive conditions results in
heightened cortical activity across these brain regions. Similarly,
an unsuccessful strategy, although in a cooperative context, may
require an increased demand of cognitive reserves to update and
change the old strategy in favor of a new direction.
Secondly, we may suggest that an inefficient compared with
an efficient cooperation may induce more negative emotions
with a concomitant withdrawal behavior toward their own
partner due the frustrated joint-action. That is, an increased
perception of inefficacy based on joint-strategies may induce a
decreasing in the positive effect produced by the cooperative
task, with a sense of impotence and failure. A further hypothesis
deals with the necessity of a sort of reparative strategy, to
compensate the reciprocal inefficacy and to try to reach a more
proficient common strategy. Here, the second option may be
represented as a sort of a resume in order to strengthen the
common goals and obtain a better result. In this second case
we can assume a sort of renewed cooperation to compensate
a previous failure. This should involve more frontal cortical
portions related to prosocial support and emotional empathic
response, as reported in some studies (Balconi and Canavesio,
2013a,b, 2014). In addition, based on the valence model of
emotions, a lateralized responsiveness should suggest a right-
sided than a left-sided prefrontal activity (Demaree, 2005; Balconi
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Balconi and Vanutelli When Cooperation Was Efficient or Inefficient
et al., 2009, 2015a,b; Harmon-Jones et al., 2010). Indeed the
emotional negative impact of an inefficacy-related feedback
should induce significant lateralized PFC activation as suggested
by the valence and the approach-avoidance model of emotions.
At this regard, we may consider the increased convergence in
the right hemisphere as a possible marker of non-achieved goals.
Indeed, as previously observed, the frontal cortical asymmetry
in favor of the right hemisphere is associated with withdrawal
motivation in opposition to approach motivation (Davidson,
1993; Jackson et al., 2003; Urry et al., 2004; Balconi and Mazza,
2010; Harmon-Jones et al., 2010; Koslow et al., 2013). Therefore,
in the present study we explored the cortical response to two
opposite conditions based on feedback.
Due to their fast temporal evolution, social processes during
interactive contexts should preferably be explored by means
of imaging methods that can provide good resolution in both
temporal and spatial components, that are more ecologically
valid and usable in dynamic and interactive conditions. For these
reasons we used event-related hemodynamic responses thanks
to functional Near-Infrared Spectroscopy (fNIRS; Elwell et al.,
1993). Therefore, we implemented a specific paradigm which
monitored the feedback (for efficient or inefficient performance)
just before (four time intervals) and just after (four time intervals)
the positive/negative feedback. Based on previous hypotheses the
feedback (artificially manipulated) should ingenerate different
PFC responsiveness. Indeed an increased DLPFC activity was
attended in the case of a negative feedback, mainly right
lateralized due to negative emotions and to a more unpredictable
outcome form the relational point of view. As found in previous
research, a specific increased prefrontal activity is attended in
order to manage an unexpected and more complex situation
(failure), since subjects could realize to be inefficient in joining
their strategies and actions. In addition, the increased work
load for the unattended negative outcome should induce a
worse performance in post-feedback, with significant increasing
of response time (RTs) and error rates (ERs). In contrast, the
left DLPFC is expected to be more responsive in the case
of a positive feedback, with a concomitant better cognitive
performance induced by a potentiated sense of self-efficacy and
by the social reinforce.
MATERIALS AND METHODS
Participants
Fifty undergraduate students (M=23.13, SD =2.32; male
=23) took part in the experiment. The participants were
all right-handed and presented normal or corrected-to-normal
visual acuity. Exclusion criteria were history of psychopathology
(Beck Depression Inventory, BDI-II, Beck et al., 1996) for
the subjects and immediate family. Also State-Trait-Anxiety-
Inventory (STAI, Spielberger et al., 1970) was submitted before
the experimental session. Based on the psychometric measures
and the clinical screening, no neurological or psychiatric
pathologies were observed. Subjects gave informed written
consent to participate in the study and no payment was provided
for their participation. Finally, the research was approved by the
local ethics committee of the Department of Psychology, Catholic
University of Milan.
Procedure
Subjects performed a simple task for sustained selective attention
(it was a modified version of (Balconi and Vanutelli, 2016a). They
were seated in a half-darkened room in front of a PC screen CRT
positioned nearby 60 cm in front of their eyes (refresh 60 Hz).
They were seated side-by-side, but separated by a black screen to
prevent visual contact.
Subjects were told that their performance would have used to
evaluate the subjective skills and, to strengthen their motivation,
that these measures are usually applied to screen individuals’
future professional success and teamwork capabilities. In
addition, the cooperative nature of the task was stressed since
they were told to synchronize their responses, in term of accuracy
(number of correct responses) and response times (RTs) with a
second agent to obtain better outcomes. The task consisted in
recognizing target figures from non-targets: after three figures
(a trial) subjects received a feedback signaled by two up-arrows
(good cooperation outcomes); a dash (mean performance); or
two down-arrows (scarce cooperation outcomes). They were
requested to answer by using a mouse. The modified version
of the task was composed by two sessions: the first which
did not include a specific feedback to performance (4 blocks
before the feedback, 100 trials); the second which included a
specific negative feedback to the performance (4 blocks with
the feedback, 100 trials). Halfway, in fact, participants received
a general evaluation of their cooperative performance, either
positive or negative based on the two different conditions. Both
the feedbacks and the evaluation were fixed, and subjects were
told they had a good cooperation (score with 87% in terms of
speed synchrony, and 92% in terms of accuracy synchrony); or a
bad cooperation (score with 26% in terms of speed synchrony,
and 31% in terms of accuracy synchrony). They were also
encouraged to keep (in the case of positive feedback) or modify
(in the case of negative feedback) their performance level during
the second part of the experiment. Across the task, after an initial
mean performance, subjects were constantly informed about
their cooperation by presenting the up-arrows or down-arrows
in 70% of cases, while the other 30% of cases the two other
possibilities (see Figure 1).
Based on a post-experimental questionnaire, participants
reported they were strongly engaged in the cooperative context
(94% told to be strongly engaged), to trust the feedback about the
performance (96%), and to consider the task as relevant for their
social status (93%). About their perception of self-efficacy, the
two groups were requested to consider their efficacy (on Likert
scale 1–7 points, for group 1 M=6.45, SD =0.12; for group 2
M=2.76, SD =0.17). Significant differences were found between
the groups [F(1,49) =7.23, p0.001, η2=0.32].
Performance Scoring
The response times (RTs, ms) were recorded from the stimulus
onset, and the error rates (ERs) were calculated as the total
number of incorrect detections out of the total trial. Therefore,
higher values represented increased incorrect responses.
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Balconi and Vanutelli When Cooperation Was Efficient or Inefficient
FIGURE 1 | Experimental task. Experimental procedure which represents the setting, the experimental tasks and fNIRS recording.
fNIRS
fNIRS recordings were conducted with NIRScout System (NIRx
Medical Technologies, LLC. Los Angeles, California) using a
8-channel array of optodes (4 light sources/emitters and 4
detectors) covering the prefrontal area. Emmiters were placed
on positions (FC3-FC4 and F1-F2) while detectors were placed
on FC1-FC2 and F3-F4; Figure 2. Emitter-detector distance was
kept at 30 mm for contiguous optodes and a near-infrared light of
two wavelengths (760 and 850 nm) was used. NIRS optodes were
placed on the subject’s head by using a NIRS-EEG compatible cup
according to the international 10/5 system. Resulting channels
are 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) Premotor Cortex (PMC, Brodmann Area 6).
Ch 5 (F1-F3) and Ch 7 (F2-F4) correspond to the left and right
(respectively) Frontal Eye Fields (FEF, Brodmann Area 8). Ch 6
(F1-FC1) and Ch 8 (F2-FC2) correspond to the left and right
(respectively) (SFG, Brodmann Area 6; Koessler et al., 2009).
With NIRStar Acquisition Software, changes in the concentration
of oxygenated (O2Hb) and deoxygenated hemoglobin (HHb)
were acquired from a 120 s resting baseline. Signals recorded
from the 8 NIRS channels were acquired with a sampling rate
of 6.25 Hz and analyzed and transformed in values for the
changes in the concentration of oxygenated and deoxygenated
hemoglobin, for each channel, scaled in mmolmm. O2Hb
and HHb changes were calculated by using the optical density
changes of 760- and 850-nm lights in accordance to the modified
Beer-Lambert law. The raw data from each channel were digitally
band-pass 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 trial onset for the following 5 s. According
to the mean concentrations in the time series, the effect size
in every condition was calculated for each channel and subject.
The effect sizes (Cohen’s d) were computed as the difference
of the mean 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 baseline and trial,
respectively, and s the SD of the baseline. In this case, the baseline
was calculated considering the 5 s immediately before the trial.
Then, the effect sizes obtained from the 8 channels were averaged
in order to increase the signal-to-noise ratio. Although NIRS
raw data were originally relative values and could not be directly
averaged across subjects or channels, effect sizes normalized data
could be averaged regardless of the unit (Schroeter et al., 2003;
Matsuda and Hiraki, 2006; Shimada and Hiraki, 2006). In fact, the
effect size is not affected by differential pathlength factor (DPF;
Schroeter et al., 2003).
RESULTS
Three sets of analyses were performed with respect to behavioral
(ERs; RTs) and neurophysiological (fNIRS: O2Hb measures)
measures.
A preliminary repeated measure ANOVA with independent
factor Condition (Cond: pre vs. post feedback) and Feedback
(Fed; positive vs. negative) was applied to ERs and RTs. In the
case of neurophysiological measure (O2Hb) for the ANOVA two
repeated factors were added to Cond and Fed, that is localization
(Loc: DLPFC, SFG, PMC, FEF) and lateralization (Lat: left vs.
right) independent factor. For all of the ANOVA tests, the degrees
of freedom were corrected using Greenhouse–Geisser epsilon
where appropriate. Post-hoc comparisons (contrast analyses)
were applied to the data. Bonferroni test was applied for multiple
comparisons. In addition, the normality of the data distribution
was preliminary tested (tests for kurtosis and asymmetry were
applied). The normality assumption of the distribution was
supported by these preliminary tests.
To exclude a possible learning effect, a further analysis was
applied, comparing separately the first set of four intervals (before
feedback) and the second set of four intervals (post feedback)
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Balconi and Vanutelli When Cooperation Was Efficient or Inefficient
FIGURE 2 | fNIRS montage. The location of NIRS channels. The emitters
(orange) were placed on positions FC3-FC4 and F1-F2, while detectors
(fuchsia) were placed on FC1-FC2 and F3-F4. 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 PMC. Ch 5 and Ch 7 correspond to the
left and right FEF. Ch 6 and Ch 8 correspond to the left and right SFG.
for all the dependent measures (RTs, ERs, O2Hb). Since no
significant differences among the four intervals before and after
the feedback were found for both the positive/negative feedback
condition, we did not include this factor in the successive
analysis.
RTs and ERs
As shown by the ANOVA, significant differences in ERs were
found for Cond ×Fed [F(1,49) =11.07, p0.001, η2=0.43]
(Figures 3A,B). Indeed, a decreased performance (higher ERs)
was found for post-feedback condition compared to pre-feedback
in the case of a negative feedback [F(1,49) =11.07, p0.001, η2=
0.43]. In addition ERs were higher in post-feedback condition in
the case of a negative than a positive feedback [F(1,49) =9.13, p
0.001, η2=0.40]. No other post-hoc comparison was significant.
About RTs, a significant effect was found for Cond ×Fed
[F(1,49) =7.71, p0.001, η2=0.34], with increased RTs in post-
feedback than pre-feedback condition in the case of a negative
feedback [F(1,49) =8.77, p0.001, η2=0.39]. In addition
RTs were increased in post-feedback condition in the case of a
negative than a positive feedback [F(1,49) =9.50, p0.001, η2=
0.40]. No other post-hoc comparison was significant.
FIGURE 3 | Behavioral results. (A) RTs modulation as a function of
Condition (pre vs. post) and Feedback (positive vs. negative). The speed
performance was characterized by longer RTs during post-feedback condition
when a negative reinforce was provided. (B) ERs modulation as a function of
Condition (pre vs. post) and Feedback (positive vs. negative). Accuracy
performance was characterized by decreased performance (higher ERs)
during post-feedback condition in the case of a negative feedback. * 0.01.
fNIRS
The analysis on HHb did not reveal significant effects, and for
this reason we reported only results for O2Hb-values. Indeed, the
main and interaction effects did not reveal relevant differences
based on the independent factors. This effect may be due to the
fact that the increase in O2Hb is larger than the decrease in HHb.
Repeated measure ANOVA showed significant effect for Cond
×Fed [F(1, 49) =8.77, p0.001, η2=0.37] and Cond ×Fed
×Lat ×Loc [F(1, 148) =9.41, p0.001, η2=0.39]. Indeed, a
general increased activity was found in post-feedback condition
than in pre-feedback in the case of negative feedback [F(1, 49)
=8.30, p0.001, η2=0.37]. Secondly, as shown by contrast
analyses applied to the simple effects for the second significant
interaction, the right DLPFC activity was higher in post-feedback
condition more for negative than for positive feedback [F(1, 49) =
8.23, p0.001, η2=0.35]. In addition in the case of negative
feedback right DLPFC activity in post-feedback condition was
increased than right DLPFC in pre-feedback condition [F(1, 49)
=7.11, p0.001, η2=0.35]. Finally, the left DLPFC activity in
post-feedback condition was increased than left DLPFC in pre-
feedback condition in the case of positive feedback [F(1, 49) =
9.40, p0.001, η2=0.40] (Figures 4A,B). No other effect was
statistically significant.
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Balconi and Vanutelli When Cooperation Was Efficient or Inefficient
FIGURE 4 | Optical imaging (fNIRS) results. Histograms (A) and activation maps (B) of O2Hb variations (D-values) for Condition ×Feedback ×Localization ×
Lateralization. The post-feedback condition was characterized by increased D-values over the right DLPFC after the negative feedback and over the left DLPFC after
the positive feedback. * 0.01.
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Balconi and Vanutelli When Cooperation Was Efficient or Inefficient
Correlational Analysis
A series of correlation analyses was applied to cognitive
performance (ERs; RTs) and O2Hb modulation for each cortical
area within the left and right hemisphere, distinctly for each
condition (pre- and post-feedback) and each feedback type
(positive vs. negative). Pearson correlation coefficients were
calculated. We reported only significant correlational results.
RTs revealed significant positive correlation with right DLPFC
activity in post-feedback condition for negative feedback (r2=
0.523, p0.001): the increased right DLPFC was positively
correlated with the increased RTs values in post-feedback
condition. Similarly, RTs decreasing was significantly correlated
with DLPFC increased activity within the left side in the case of
positive feedback (r2= −0.543, p0.001; Figures 5A,B).
DISCUSSION
The present research explored the effects of efficient vs.
inefficient joint-actions in a cooperative task. Indeed the
effect of a positive (artificially induced sense of efficacy) or
a negative (artificially induced sense of inefficacy) feedback
was considered, considering both brain responsiveness and
behavioral performance. Specifically, brain activation was
acquired during a cooperative task which ingenerates a positive
vs. a negative outcome. The following main results were
observed. A first main effect was related to the systematic
impact of the feedback on the frontal sites, mainly for
some specific prefrontal regions (DLPFC). Secondly, a specific
lateralization effect was detected, in relation to the nature of the
feedback. Indeed, the DLPFC showed a significant higher right
activity when the feedback was negative, whereas an increased
left DLPFC activity was revealed in the case of a positive
feedback. Thirdly the cognitive performance was affected by the
feedback, since the negative feedback induced a significant worse
performance in contrast to the positive feedback which induced
a significant improved performance.
The first main effect was related to the general increased PFC
activity after the subjects received their feedback in comparison
FIGURE 5 | Correlational analyses. Scatterplots displaying Pearson’s coefficients between right (A) and left (B) DLPFC with RTs. Results showed that increased
right DLPFC activity was positively correlated with the increased RTs values in post-feedback condition. Similarly, RTs decreasing was significantly correlated with left
DLPFC activity in the case of positive feedback.
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Balconi and Vanutelli When Cooperation Was Efficient or Inefficient
to the absence of a feedback. This effect was mainly distributed
within a specific area that is the DLPFC, whereas other areas
were not implicated by feedback processing. This result may
be coherent with the suggested hypothesis that the feedback on
subjects’ performance has a significant impact on their brain
activity. In fact, as shown by previous research, the DLPFC may
support our social cooperative or competitive interactions with
relevant modulations of the brain responsiveness (Rilling et al.,
2002, 2007; Nihonsugi et al., 2015; Balconi and Vanutelli, 2016a).
As previously shown, the DLPFC has a specific and crucial role
in social contexts, in the self-perception of social hierarchy and in
monitoring within of social task (Balconi and Pagani, 2015; Wang
et al., 2016). In addition, previous results revealed that prefrontal
areas are prominent and relevant in social status regulation and
joint actions (Karafin et al., 2004; Haruno and Kawato, 2009;
De Vico Fallani et al., 2010; Suzuki et al., 2011). This prefrontal
brain area is supposed to have an evolutionary relevance in social
perception especially when hierarchy across species and human
social groups is significant. Therefore, it is plausible to suppose
that this area has specialized mechanisms to perceive and regulate
joint-actions.
However, a relevant result was related to the lateralized effect
we found, that is the specific right lateralization systematically
observed after the negative feedback. A possible interpretation is
that this increased activation is due to higher cognitive efforts and
processing load associated with the representation of a negative
condition, resulted in heightened cortical activity (Gallagher
and Frith, 2003; Decety et al., 2004). An unsuccessful strategy,
although in a cooperative context, may require an increased
demand for cognitive resources to update and modify the joint-
action style. As such, this condition may require an increase
in cognitive load related to the necessity to recalibrate joint
strategies, to implement a more efficient cognitive plan and
to include new behavioral directions. We may explain these
findings also taking into account some previous results related to
competition, where we found that the PFC was mainly activated
within the right side in the case of a competitive task (Decety
et al., 2004; Balconi and Vanutelli, 2016b). Therefore, the present
results seem to suggest that the negative cooperative condition is
more similar to a competitive task and that this fact may be due
to the increasing difficulty in creating a common mental strategy
based on the increased work load.
Nevertheless, a second explanation of the present result, an
emotional one, may bring the increased right responsiveness
back to a significant prevalence of more negative emotions
and avoidance attitudes toward the interlocutor, linked to the
inefficient inter-action. It should be ascribed to the negative
emotional condition that a frustrating feedback may create. In
fact it was observed that the right hemisphere supports aversive
situations where individuals have to regulate the conflictual and
also divergent goals (Balconi et al., 2012). Therefore, a sort of
“negative echo” may be intrinsically related to failure, with a
significant increasing of withdrawal attitudes (Davidson, 1993;
Jackson et al., 2003; Urry et al., 2004; Balconi and Mazza, 2010;
Harmon-Jones et al., 2010; Koslow et al., 2013). In other terms,
the social relevance of the task and the inefficient cooperative
condition may explain this result, together with the decreased
DLPFC response based on the “reduced” cooperation induced
by a failed joint-behavior. Subsequently, activity patterns in the
frontal cortices can be regarded to be crucially involved in
processing emotional conditions which characterize the negative
context. Nevertheless, it has to be noted that few studies have
tried to connect emotional effects of failing cooperation, taking
into account the impact of the emotional behavior on cortical
system when it responds to specific social situations. Therefore,
future research should better explain the role of emotions and
negative feedback to disambiguate their reciprocal relation.
However, a more complete explanation should take into
consideration the second lateralization effect, that is the left-sided
effect we concomitantly found in the case of a positive feedback.
This interesting effect, integrated with the right-negative effect,
may definitely argue in favor of an emotional explanation more
than an increased workload. Indeed this specific lateralization
(negative-right; positive-left) may be hardly explained based
on the cognitive effort perspective. In contrast, considering
the valence model and the withdrawal-approach perspective
on emotions, it may more clearly justify the increased DLPFC
responsiveness as a function of the feedback nature and its effect
on the emotional behavior.
The present interpretation is also supported by the behavioral
results and the significant worse performance (increased RTs
and ERs) after the negative feedback, whereas a better cognitive
performance (decreased RTs) was revealed in the case of a
positive self-represented outcome. Although a cognitive effort
due to the task after the feedback may not be excluded a priori,
we may suppose that the decreased performance in the post-
feedback condition may be due to the negative self-perception
and the representation of an inefficient interaction. This fact
is supported by both higher RTs and increased ERs, which
point out the negative feedback condition as the absolute worst
cognitive factor during cooperation. Moreover, the presence of an
opposite finding in response to a positive feedback (an increased
performance) argues in favor of the emotional impact of the
social feedback. In fact this last result could be hardly explained
only considering a sort of learning effect (which could justify
a better performance). In other words, a simple working load
effect (with decreased performance) or a learning effect (with
improved performance) are not compatible with the present
data. In addition, they are in contrast with our preliminary
analysis which tested the absence of significant effect within each
of the four intervals (no performance variations based on the
comparison between the four time intervals for pre-feedback or
for the post-feedback condition). It should also be noted that,
based on correlational measures, the cortical and behavioral data
showed to be matched, with a similar trend of increased values
for both behavioral performance (higher RTs and ERs) and right
DLPFC, as well as lower RTs and a higher left DLPFC implication.
CONCLUSIONS
In conclusion, in the present research we observed a two-
faced effect in relation to the social outcome representation
when a cooperative task is performed, with significant increased
Frontiers in Systems Neuroscience | www.frontiersin.org 8May 2017 | Volume 11 | Article 26
Balconi and Vanutelli When Cooperation Was Efficient or Inefficient
right/left DLPFC activity in response to negatively or positively
reinforced joint actions. This result may be explained based on
the emotional significance of a positive vs. negative condition,
which underlined the negative or the positive significance of a
feedback in a cooperative situation (Balconi et al., 2012). At this
regard, we may consider the increased right PFC responsiveness
as a possible marker of the reduction of self-perceived efficacy
and good performance. Indeed, as previously observed, the
frontal cortical asymmetry in favor of the right hemisphere
is associated with withdrawal motivations in opposition to
approach motivations, where subjects have to recalibrate their
strategy and to manage negative feelings linked to the inefficient
performance. On the other hand, the reinforced sense of efficacy
and of a better performance may induce a “positive color” on the
existing relationships and the functional strategies adopted.
Some limits may be suggested for the present research.
Firstly, a specific analysis should be conducted to more
extensively explore the whole cortical map of cooperative
behavior, considering also the contribution of posterior areas
in addition to PFC. Secondly, the implementation of other
alternative tasks, which may more directly represent some
ecological conditions of cooperation, is to be considered
for future research. Finally, a connectivity approach, able
to evaluate the brain-to-brain coupling between the two
inter-agents, could be suggested, to better explore the
synergic inter-brain activity during cooperation in different
scenarios.
AUTHOR CONTRIBUTIONS
MB planned the experiment, supervised the data acquisition;
analyzed that data, wrote the paper. MV executed the
experiment, analyzed the data, and partially wrote the
paper.
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Copyright © 2017 Balconi and Vanutelli. This is an open-access article distributed
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author(s) or licensor are credited and that the original publication in this journal
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Frontiers in Systems Neuroscience | www.frontiersin.org 10 May 2017 | Volume 11 | Article 26
... Interestingly, a recent hyperscanning study seems to be in line with such evidence, since it revealed that two cooperative partners show increased behavioral and neural synchrony than competitive ones during a joint task [5]. This result was motivated as a sort of disengagement from the members of the couple, and a similar effect was also observed in the case of inefficient joint interactions [6][7][8][9]. Thus, although it is significant to explore cooperation as a highly gratifying, positive, and rewarding condition, the effects related to disengagement, social exclusion, social differentiation and hierarchic mechanisms deserve greater attention. ...
... Cooperation, instead, creates a bond, an overlapping, between the two inter-agents, which leads to increased connectivity patterns [5,24,25]. Interestingly, a similar effect was also observed in the case of inefficient joint interactions [6][7][8][9]. ...
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... Hyper Tasks -Dual Analysis -BRAIN+BRAIN (B+B). At this regard, two recent studies by Balconi and colleagues [9,10] used a new paradigm to observe the different mental representations during a competitive and cooperative scenario in which the participants coupled in dyads had to compete or cooperate with their partner while carrying out a continuous attention task. Specifically, the game consisted of an attention task that required the recognition of target stimuli among nontargets. ...
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... Moreover, there is a significant increment of activity in beta band in right-temporal-parietal areas and, in general, in parietal area in case of ineffective cooperation. This is coherent with previous knowledge that ineffective cooperation induces higher activation of the right hemisphere due to negative valence (Balconi and Vanutelli, 2017a) because it induces feelings more pertinent to competitive behaviour. Adversely, nor autonomic, Workload or Engagement are affected by cooperation effectiveness. ...
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... Future studies could proceed this line of research by applying more sophisticated paradigms and computation methods, such as the hyperscanning paradigm, which allows assessing the coevolution of neural/psychophysiological indices of 2 or more participants interacting together. 32,52,53 In fact, besides their theoretical implications, similar findings could be applied in organizations to promote employees' wellbeing and better interpersonal social exchange by minimizing dysfunctional reactions and negative emotions. ...
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Organizational research started including neurosciences exploring pivotal phenomena and promoting organizational well-being. Leadership was investigated by assessing psychophysiological responses during performance review characterized by narrative or quantitative assessments and their effects on employees' well-being. As is known, rating could be perceived as threatening for employees' ranking and status perception, leading to avoidant behaviors. Design and methodology: Here, manager-employee dyads were assigned to 2 conditions: in the nonrate scenario, managers were asked to describe the employee's performance; in the rate one, they had to provide a quantitative rating. Skin conductance level and response and heart rate indices were continuously recorded. Findings: Dyads in nonrate condition showed higher arousal-related responses (skin conductance level and skin conductance response), perhaps highlighting an increased engagement triggered by a rewarding exchange. Conversely, in rate condition, employees showed higher heart rate, usually related to negative and stressful conditions, and avoidant behaviors. Originality/value: Results are discussed for their possible applications to employees' well-being.
... Nowadays, the researchers use awide variety of sensorimotor tests in which two or more subjects have to simultaneously perform different tasks in different contexts: individual, competitive or cooperative ones [14,20]. As an example, there are studies on the role of negative and positive feedback in the effectiveness of cooperation between individuals [5,6]. ...
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