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The present study explored the effect of lateralized left-right resting brain activity on prefrontal cortical responsiveness to emotional cues and on the explicit appraisal (stimulus evaluation) of emotions based on their valence. Indeed subjective responses to different emotional stimuli should be predicted by brain resting activity and should be lateralized and valence-related (positive vs. negative valence). A hemodynamic measure was considered (functional Near-Infrared Spectroscopy, fNIRS). Indeed hemodynamic resting activity and brain response to emotional cues were registered when subjects (N = 19) viewed emotional positive vs. negative stimuli (IAPS). LIR (Lateralized Index Response) during resting state, LI (Lateralized Index) during emotional processing and SAM (Self-Assessment Manikin) rating were considered. Regression analysis showed the significant predictive effect of resting activity (more left or right lateralized) on both brain response and appraisal of emotional cues based on stimuli valence. Moreover, significant effects were found as a function of valence (more right response to negative stimuli; more left response to positive stimuli) during emotion processing. Therefore resting state may be considered a predictive marker of the successive cortical responsiveness to emotions. The significance of resting condition for emotional behavior was discussed. © The Author (2015). Published by Oxford University Press. For Permissions, please email:
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Resting lateralized activity predicts the cortical response
and appraisal of emotions: an fNIRS study
Michela Balconi,
Elisabetta Grippa,
and Maria Elide Vanutelli
Research Unit in Affective and Social Neuroscience and
Department of Psychology, Catholic University of the Sacred Heart, Largo Gemelli, 1,
20123, Milan, Italy
This study explored the effect of lateralized leftright resting brain activity on prefrontal cortical responsiveness to emotional cues and on the explicit
appraisal (stimulus evaluation) of emotions based on their valence. Indeed subjective responses to different emotional stimuli should be predictedby
brain resting activity and should be lateralized and valence-related (positive vs negative valence). A hemodynamic measure was considered (functional
near-infrared spectroscopy). Indeed hemodynamic resting activity and brain response to emotional cues were registered when subjects (N¼19) viewed
emotional positive vs negative stimuli (IAPS). Lateralized index response during resting state, LI (lateralized index) during emotional processing and self-
assessment manikin rating were considered. Regression analysis showed the significant predictive effect of resting activity (more left or right later-
alized) on both brain response and appraisal of emotional cues based on stimuli valence. Moreover, significant effects were found as a function of
valence (more right response to negative stimuli; more left response to positive stimuli) during emotion processing. Therefore, resting state may be
considered a predictive marker of the successive cortical responsiveness to emotions. The significance of resting condition for emotional behavior was
Keywords: resting state; emotion; fNIRS; valence; lateralization
Recent research has revealed that the processing of emotional visual
stimuli leads to increased activation of various cortical areas, including
the amygdala, the medial prefrontal cortex (PFC) and the dorsolateral
prefrontal cortex (Davis and Whalen, 2001;Pessoa et al., 2002;Phan
et al., 2002). Although other cortical sites were found to be relevant in
emotional cue processing, in this research we focused on the prefrontal
area to test the direct effect of PFC and resting state in visual emotional
cue comprehension. Indeed more recent studies have identified the
PFC as a key region in the experience and regulation of emotional
responses, based on the lateralization effect (Damasio, 1996;
Davidson, 2002;Ochsner and Gross, 2005;Balconi et al., 2011;
Balconi and Bortolotti, 2012). In addition, recent results suggested a
significant and specific lateralization effect of PFC activation, based on
the positive (more directly processed by the left hemisphere) and the
negative (more directly processed by the right hemisphere) valences of
emotions (Everhart et al., 2003;Balconi and Mazza, 2010). The valence
model supposes that cortical differences between the two hemispheres
are attributable to positive vs negative valence of emotions (Silberman
and Weingartner, 1986;Everhart et al., 2003;Russell, 2003). Based on
the valence model, the right hemisphere is specialized for negative
emotions and the left hemisphere for positive emotions. However,
some other perspectives suggested a dichotomy on approach/avoid-
ance attitude to emotions, the first more frontal left-related and the
second more frontal right-related (Davidson, 1995;Harmon-Jones,
2003;Balconi and Mazza, 2009). Based on the approachwithdrawal
model of emotion regulation, the emotional behavior should be asso-
ciated with a balance of activity in the left and right frontal brain areas
that can be explained in an asymmetry measurement (Harmon-Jones
and Allen, 1997;Sutton and Davidson, 2000). Resting frontal asym-
metry, mainly measured by electroencephalography (EEG), has been
hypothesized to relate to appetitive (approach-related) and positive
and aversive (withdrawal-related) or negative motivation, with
heightened approach tendencies reflected in left-frontal activity and
heightened withdrawal tendencies reflected in relative right-frontal ac-
tivity (Balconi and Pozzoli, 2003;Balconi and Lucchiari, 2007;Stewart
et al., 2014).
In addition, according to the asymmetry hypothesis, the left/right
asymmetry of the PFC activity is correlated with specific emotional
responses to stressors and personality traits (Davidson et al., 2000;
Canli et al., 2001;Fischer et al., 2002). Indeed, EEG has demonstrated
that subjects with greater relative left PFC activity exhibited more
positive and less negative dispositional mood (Tomarken et al.,
1992) than their right-dominant counterparts. In contrast, right front-
ally activated subjects responded more to negative affective challenges
and less to positive affective challenges than their left dominant coun-
terparts (Wheeler et al., 1993). Two main models were adopted to
explain stable subjective asymmetries in brain activity within the fron-
tal areas: the dispositional model of frontal affective style, which pos-
tulates that people possess a general tendency to respond
predominantly with either an approach or withdrawal behavior despite
the situational differences (Davidson, 1998;Balconi and Mazza, 2010);
and the situational model, such as the capability model, which postu-
lates that individual differences are better represented as interactions
between the emotional demands of specific situations and the emo-
tion-monitoring abilities individuals use to respond to those situations
(Wallace, 1966;Lilienfeld et al., 2000;Coan et al., 2006). Moreover,
Harmon-Jones (2004) has argued that we may integrate the valence/
approach models to include both motivational and valence compo-
nents. Through the development and tests of competing hypotheses,
Harmon-Jones et al. (2004) have pursued the goal of specifying more
precisely what the emotional and motivational functions of asymmet-
rical frontal brain activity might be. They have identified a valence
model of brain asymmetry in which high levels of relative left frontal
activity are associated with the expression and experience of positive
emotions and high levels of relative right frontal activity are associated
with the experience and expression of negative emotions. In addition,
they identified a motivational direction model in which high levels of
relative left frontal activity are associated with the expression of ap-
proach-related emotions and high levels of relative right frontal activity
Received 14 December 2014; Revised 25 March 2015; Accepted 7 April 2015
Advance Access publication 9 April 2015
Correspondence should be addressed to Michela Balconi, Department of Psychology, Catholic University of the
Sacred Heart, Largo Gemelli, 1, 20123 Milan, Italy. E-mail:
doi:10.1093/scan/nsv041 S C AN ( 2 015 ) 10, 16 07 ^1614
ßThe Aut hor (2015). Published by Oxford University Pre ss. For Permissio ns, please email: journals.permissio ns m
are associated with the expression of withdrawal-related emotions.
Although positive emotions are typically associated with motivations
to approach and negative emotions are typically associated with mo-
tivations to withdraw, there are notable exceptions (for example anger-
out) (Amodio and Harmon-Jones, 2012;Harmon-Jones and van
Honk, 2012). In fact, whereas some negative emotional expressions,
such as anger and sadness, are generated by negative, aversive situ-
ations, these emotions may introduce some differences in subjective
response as a function of how people appraise their ability to cope with
the aversive situation (Frijda, 1993;Hewig et al., 2004).
Resting activity may contribute to assess the relevance of these
models, defining the role of personality in affective behavior, as a
predictive marker of the left- or right-asymmetry in specific emotion
processing. Indeed, it was observed that spontaneous brain activity
(explored by blood oxygen level dependent) was not just random
noise, but was specifically organized in the resting human brain
(for a review see Fox and Raichle, 2007). However, the role of resting
activity in emotional responsiveness was explored only partially.
Second, the impact of this resting activity for a successive lateralized
response to emotional tasks was scarcely considered. No previous
study has considered the direct relationship between resting activity
within the left and right PFC and the brain response to emotional cues,
also taking into account the explicit subjective evaluation of the sig-
nificance (in term of valence and arousal appraisal) of the emotional
In addition, neither the classical imaging (with fMRI) nor the elec-
trophysiological measure seems to completely describe the depth of
emotional context. Indeed, a methodological issue should be con-
sidered. Although studies have provided functional images of activated
areas of the brain associated with emotional tasks, they have seldom
addressed the temporal course of the activation. Due to its fast tem-
poral evolution and its representation and integration among complex,
widespread neural networks, emotion perception, together with its
neurobiological correlates, should preferably be examined by means
of imaging methods that offer good resolution in both temporal and
spatial domains.
Among the different modalities available for monitoring brain ac-
tivity, near-infrared spectroscopy (NIRS) is non-invasive and particu-
larly well suited for evaluating PFC activity, one of the regions involved
in emotional processing. Temporal resolution of NIRS is high enough
for measuring event-related hemodynamic responses. In addition,
some specific areas more directly related to emotional processing, i.e.
the frontopolar cortex and the anterior lateral PFC are easily accessible
for measurements by NIRS. For the reasons reported above, NIRS is
particularly suited to explore the emotional domain. Interestingly,
recent studies using NIRS investigating the neural correlates of emo-
tion regulation processes also described an activation of the PFC
(Hongyu et al., 2007;Hermann et al., 2008;Balconi et al., 2015).
Moreover, measurement of NIRS and EEG in a resting condition
demonstrated that an increase of oxy-hemoglobin (O2Hb) was asso-
ciated with an increase of neuronal activity whereas a decrease of
O2Hb was associated with a decrease of neuronal activity (Hoshi
et al., 1998;Butti et al., 2006).
In this study, we hypothesized that asymmetry of NIRS-measured
O2Hb changes at rest in the PFC may predict emotional response to an
experimental condition in which the subjects have to detect emotional
cues. Namely, resting activity might have a predictive value for the
successive subject’s activity in response to emotional stimuli. Higher
left activity at rest should be related to increased left activity in the
experimental condition, whereas higher right activity should be related
to increased right activity in the experimental condition.
Moreover, a specific valence effect should be found in the experi-
mental condition. Based on the approach/withdrawal model of
emotions (Russell, 2003), a significant and consistent higher prefrontal
left activation was anticipated for positive emotional stimuli, whereas a
consistent higher prefrontal right activation was expected in response
to negative stimuli (Balconi and Mazza, 2010).
Taking these suppositions together, related to resting and valence
effects, they may support the fact that subjective responsiveness to
different stimulus categories should be predicted by resting activity
and should be valence related. Therefore, we expected that a higher
left resting activity will support a higher cortical responsiveness within
the left hemisphere for the positive stimuli. In contrast, a higher right
resting activity will support a higher responsiveness within the right
hemisphere for the negative stimuli.
These two resting and experimental measures were then related to
the explicit self-report correlates, that is the subjective appraisal in
terms of valence (positive vs negative) by using self-assessment mani-
kin (SAM; Russell, 1980;Bradley and Lang, 1994;Cuthbert et al., 2000;
Balconi and Pozzoli, 2009;Balconi and Mazza, 2010;). Thus, in
addition to the relationship between resting and experimental cortical
responsiveness, brain activity at rest should predict the subjects’
explicit appraisal of the emotional cues that is a specific polarization
of the SAM rating based on the higher left/right resting activity is
Nineteen subjects, 11 females and eight males (M age ¼29.61;
SD ¼5.38; range ¼2347) participated in the experiment. All subjects
were right-handed, with normal or corrected-to-normal visual acuity.
Exclusion criteria were neurological or psychiatric pathologies based
on responses to Beck Depression Inventory (BDI-II; Beck et al., 1996),
for the subjects or immediate family. Also, the absence of documented
head injury was considered based on the subjects’ clinical history. They
provided informed written consent for participating in the study and
the research was approved by the Ethical Committee institution where
the work was carried out. The experiment was conducted in accord-
ance with the Declaration of Helsinki and all the procedures were
carried out with adequate understanding from the subjects, who read
and signed the Research Consent Form before participating in this
research. No payment was provided for their participation.
Stimuli and SAM
One hundred stimuli were chosen from the International Affective
Picture System (IAPS) (Bradley and Lang, 2007), depicting 40 pleasant
and 40 unpleasant pictures (20 low and 20 high arousing, each), and 20
neutral stimuli, previously validated on valence and arousal ratings
(Balconi et al., 2009). IAPS subjective ratings were obtained with the
SAM scale, using an easier adapted 5-point version (Bradley and Lang,
1994,2007). SAM is a non-verbal pictorial assessment technique that
directly (using an analogical scale showing a manikin) measures the
pleasure, arousal and dominance associated with a person’s affective
reaction to a wide variety of emotional stimuli. IAPS-selected stimuli
numbers were chosen from a total of over 900 stimuli: (i) pleasant and
low arousal; (ii) pleasant and high arousal; (iii) unpleasant and low
arousal; (iv) unpleasant and high arousal; (v) neutral (Table 1). Based
on IAPS dataset, the selected positive stimuli were classified as more
positive than the negative stimuli; the high arousal stimuli were clas-
sified as more arousing than low arousal stimuli. However, the positive
high arousal and the negative high arousal stimuli did not differ in
terms of arousal level (high for both of them). Similarly, the positive
low arousal and the negative low arousal did not differ in terms of
arousal level (low for both of them).
16 0 8 S C AN ( 2 015 ) M. Balconi et al.
After the experimental phase, subjects had time to rate their emo-
tional experience on SAM evaluating valence and arousal on a bipolar
scale applied to each picture (Bradley and Lang, 1994).
A total of 180 s resting baseline was registered at the beginning of the
experiment before the picture series. We used this period as baseline
for the successive analysis. Participants performed resting eyes-closed
baseline periods. Each participant was instructed to relax and allow the
mind to disengage during these periods. Participants were seated in a
dimly lit room, facing a computer monitor that was placed 70 cm from
the subject. The stimuli were presented using STIM software (Stim
Compumedics Neuroscan, Charlotte, NC, USA) running on a personal
computer with a 15-in. screen. Participants were required to observe
each stimulus during functional NIRS (fNIRS) recording, and they
were asked to attend to the images during the entire time of exposition.
Pictures were presented in a random order in the center of a computer
monitor for 6 s, with an inter-stimulus interval of 12s. A familiariza-
tion phase was conducted, where subjects saw and rated five pictures
(one for each emotional category), different from those used in the
experimental phase (Figure 1).
Functional near-infrared spectroscopy
fNIRS measurements were conducted with the NIRScout System
(NIRx Medical Technologies, LLC. Los Angeles, CA) using a 6-channel
array of optodes (four light sources/emitters and four detectors) cover-
ing the prefrontal area. Emitters were placed on positions AF3AF4
and F5F6, while detectors were placed on AFF1AFF2 and F3F4.
Emitter-detector distance was 30 mm for contiguous optodes and
near-infrared light of two wavelengths (760 and 850 nm) was used.
NIRS optodes were attached to the subject’s head using a NIRS-EEG
compatible cup, with respect to the international 10/5 system
(Oostenveld and Praamstra, 2001).
With NIRStar Acquisition Software, changes in the concentration of
O2Hb and HHb were recorded from a 180-s starting baseline, using
the modified BeerLambert law. Signals obtained from the six NIRS
channels were measured with a sampling rate of 6.25 Hz, and analyzed
and transformed according to their wavelength and location, resulting
in values for the changes in the concentration of O2Hb and HHb
hemoglobin for each channel (Figure 2). Hemoglobin quantity was
scaled in mmol mm, implying that all concentration changes
depend on the path length of the NIR light in the brain.
The raw data of O2Hb, HHb from individual channels were digitally
band-pass filtered at 0.010.3 Hz. Then, the mean concentration of
each channel within a subject was calculated by averaging data
across the trials from the trial onset for 6 s. Moreover, in order to
analyze left/right asymmetry of PFC activity at rest, we calculated the
Lateralized Index Response (LIR, (right left)/(right þleft)) for the
selected channels for O2Hb (for this procedure see also Ishikawa
et al., 2014). The index provides values in the range of (1, þ1).
A positive LIR indicates that the right PFC is more active at rest
than the left PFC on average, while a negative LIR indicates that the
left PFC is more active at rest than the right PFC on average.
The cerebral blood oxygenation changes in the bilateral PFC were
continuously monitored by NIRS also during the experimental condi-
tion. The mean control values (baseline values) were subtracted from
the mean activation values (measured throughout task performance).
In order to determine left/right asymmetry of PFC activity during the
experimental task, we calculated a laterality index (LI) for the O2Hb
concentration changes ((right left)/(right þleft)). LI > 0 indicates
greater activity of the right PFC compared to left PFC, while LI < 0
indicates greater activity of the left PFC compared to right PFC (for
this procedure see also Ishikawa et al., 2014).
Data analysis
Analyses were conducted on the resting brain activity, the experimental
brain activity and the comparison between these two phases. To ex-
clude a priori gender effects, first a set of repeated measures ANOVAs
was applied to the dependent measures of LIR. A second set of
Fig. 1 Experimental setting during fNIRS recording.
Table 1 IAPS-selected stimuli numbers
Pleasant Unpleasant
Affective Low arousal 1604, 1610, 1620, 1670, 1812, 2206, 2312, 2399, 2490, 2491,
2304, 2360, 2370, 2388, 2501, 2520, 2590, 2722, 6010, 7054,
2530, 5010, 5201, 5551, 5631, 9000, 9001, 9045, 9090, 9110,
5760, 5779, 5811, 7325, 7340 9220, 9330, 9331, 9390, 9472.
High arousal 1650, 1710, 2208, 2216, 4220, 1019, 1120, 1201, 1525, 1932,
5470, 5621, 5628, 8030, 8034, 2683, 2703, 2811, 3022, 3170,
8080, 8185, 8186, 8200, 8251, 3500, 6230, 6313, 6350, 8485,
8341, 8370, 8400, 8490, 8500. 9254, 9300, 9410, 9433, 9910.
Neutral 1112, 1121, 1240, 1313, 1390, 1617, 1675, 1935, 1945, 1947,
2025, 2635, 2770, 2780, 2810, 4004, 5395, 6930, 7484, 9913.
Resting and brain activity during emotions SCAN (2015) 1609
repeated measures ANOVAs with three independent factors (two gen-
der two arousal two valence) was applied separately for the de-
pendent measures of LI and SAM. For all of the ANOVA tests,
degrees of freedom were corrected by Greenhouse-Geisser epsilon
where appropriate. Contrast analyses (paired comparisons) were
applied to significant main or interactions effects.
A successive set of regression analyses was applied to LIR (as pre-
dictor), LI and SAM (as predicted variables), to explore the effect of
resting activity on the experimental response for both brain activation
and appraisal process.
Lateralized index response
Statistical analyses were applied for both 02Hb and HHb concentra-
tions. According to the analysis, HHb was not significant, thus we
reported only results for 02Hb values. One-way ANOVA assessed the
gender effect on the dependent measure 02Hb. As shown by the ana-
lysis, no significant differences were found for gender (F(1,18) ¼1.87,
Laterality index
Three factor (two gender two arousal two valence) repeated meas-
ures ANOVA was applied to LI measure. The main effect of valence
(F(1,18) ¼9.78, P< 0.001) was significant. Indeed LI values were
higher (positive values, more right activity) for negative stimuli, and
lower (negative values, more left activity) for positive stimuli. In con-
trast, gender (F(1,18) ¼1.12, P¼0.38) and arousal (F(1,18) ¼0.87,
P¼0.66) main effects, and valence gender (F(1,18) ¼1.37,
P¼0.11), arousal gender (F(1,18) ¼1.98, P¼0.082) and gen-
der valence arousal (F(1,18) ¼1.03, P¼0.45) interaction effects
were not significant (Figure 3).
SAM ratings
Arousal and valence subjective ratings were analyzed with two separate
three factor (two gender two arousal two valence) repeated meas-
ures ANOVAs. For valence ratings, the valence main effect was signifi-
cant (F(1,18) ¼6.14, P< 0.001). Indeed negative valenced stimuli were
rated as more negative than positive stimuli (Figure 4). In parallel,
regarding arousal ratings, arousal main effect was significant
(F(1,18) ¼6.77, P< 0.001): low arousal stimuli were rated as lower
on arousal than high arousal stimuli. No other effect was statistically
significant (P> 0.481).
Regression analyses
Regression analyses were performed in each condition (positive vs
negative valence) for both LI and SAM variables. Results showed
that LIR accounted for the LI in response to negative stimuli
¼0.58). Moreover, LIR also accounted for LI in response to posi-
tive stimuli (R
¼0.52). As shown by scatterplot (Figure 5a and b), LIR
increased values (higher right resting activity) were related to LI
increasing (higher right-activity), whereas LIR decreased values
(higher left resting activity) were related to LI decreasing (higher left
values). A similar trend was observed for SAM: indeed LIR explained
the SAM rating in response to both positive (R
¼0.57) and negative
¼0.49) stimuli. As reported in the scatterplot, a significant increase
in SAM (more positive value) was related to a decreased LIR value
(more left resting activity), whereas a decrease in SAM (more negative
value) was related to increased LIR value (more right resting activity)
(Figure 6a and b).
This article aimed to explore the direct relationship between the later-
alized resting brain activity and the emotional cue processing within
the PFC. We found that the lateralization in resting state may predict
the successive lateralized brain response to emotional cues. A second
main result was related to the specificity of this relationship in terms of
the valence. Indeed we observed a significant impact of positive vs
negative cues in affecting, respectively, the left and right hemisphere
activations. As a consequence, we found that the higher left vs right
activity at rest was able to predict a specific increased lateralized (left
and right, respectively) brain activation during emotion processing in
response to the specific positive and negative emotions. Third, this
valence-related predictive role of resting brain activity also affected
the successive appraisal of emotional cues: indeed regression analysis
confirmed the impact of the resting state on subjects’ evaluation in
terms of positive vs negative attribution to emotions.
More specifically regarding the first result, in this study we evaluated
the asymmetry of the resting activity in the PFC in terms of LIR. We
found a significant relationship between the lateralized prefrontal ac-
tivity at rest and the lateralized activity of the same brain area in re-
sponse to emotional stimuli. Indeed LIR scores indicated that subjects
with more right-dominant activity at rest (positive values of LIR)
showed higher LI scores (more right activity), while those with left-
dominant O2Hb changes at rest (negative values of LIR) showed lower
LI scores (more left activity). In NIRS activation studies, changes of
Fig. 2 The locations of the measurement channels. The emitters were placed on positions AF3AF4
and F5F6, while detectors were placed on AFF1AFF2 and F3F4. Emitterdetector distance was
30 mm for contiguous optodes and near-infrared light of two wavelengths (760 and 850 nm) was
used. NIRS optodes were attached to the subject’s head using a NIRS-EEG compatible cup, with
respect to the international 10/5 system.
1610 S C AN ( 2 015 ) M. Balconi et al.
O2Hb during activation imply evoked changes of rCBF in response to
neuronal activation, since changes in O2Hb were correlated with
changes in rCBF (Hoshi et al., 2001). In addition, simultaneous meas-
urements of NIRS and EEG at rest demonstrated a relationship be-
tween O2Hb change and mean EEG peak frequency (Hoshi et al.,
1998). These observations indicate that changes of O2Hb concentra-
tion at rest measured by NIRS reflect neuronal activity at rest. We can
also suggest that the relationship we found between resting activity and
experimental response was not random and that the modulation found
at rest is predictive of the successive hemodynamic activity in the
brain. Indeed, as shown by regression analysis, the resting state activity
highly predicted the successive subjects’ responses to the emotional
cues. However, since in this research we used a compound index
(left or right higher activity as a function of the contralateral brain
activity) and no an absolute right vs left hemisphere activation, the
results we obtained should be considered as a measure which expresses
the balance between left or right brain activity and not an absolute
lateralization (absolute left/right prevalent activity) measure. Future
research should test more deeply the separate effect of the left vs
right hemisphere in both resting and experimental condition. In add-
ition it should be noted that the present results were related to 02Hb
modulation. In contrast we did not obtain a significant effect for HHb,
as shown by the statistical analysis. The reason why only one of the two
measures was effective in inducing significant results should be
explored in future research. However, based on the present data, we
may suggest that the two 02Hb/HHb measures which express the local
cerebral blood flow increasing (respectively related to higher and lower
values) may be not exactly two asymmetrical measures, as shown in
some previous research (Ferrari and Quaresima, 2012).
Interestingly, this effect was observed in a strong relationship with
the emotional stimuli category. Namely, regression analysis applied to
LIR and LI revealed that subjects with left (or right) prevalent PFC
activity at rest also exhibited left (or right) prevalent PFC activity
during the emotional processing and that this activity was responsive,
respectively, to the positive vs negative content of the emotional cues.
In other words, the predictive role of resting brain activity was not
indistinct but specifically related to the left vs right activation of the
Fig. 3 O2Hb concentration during resting brain activity: higher LIR values for negative (left figure), and lower values for positive stimuli (right figure).
negave valence
-0.6 -0.4 -0.2 0 0.2 0.4 0.6
-0.6 -0.4 -0.2 0 0.2 0.4 0.6
posive valence
Fig. 5 Scatter plot of LIR and LI while viewing negative (a) vs positive (b) stimuli.
Posi ve N ve low-arousal high-arousal
SAM values
Fig. 4 SAM rating as a function of valence and arousal features of emotional stimuli.
Resting and brain activity during emotions SCAN (2015) 1611
brain when a positive vs a negative emotional stimulus was processed.
Indeed, O2Hb increasing (more right activity) during the resting state
explained the successive greater right hemisphere response to negative
cues during the emotion processing. In contrast O2Hb decreasing
(more left activity) during rest supported greater left activity to posi-
tive cues.
As a direct consequence of these results, the restingactivation rela-
tionship was characterized by two main effects. First, a valence-related
lateralization effect was found. As shown by O2Hb increasing within
the right and the left hemisphere in response to different category
types, a significant difference was found based on valence of the sti-
muli, which was able to activate different cortical sides. PFC was found
to support this valence-related emotional cue processing. This result
confirmed previous research which found that PFC plays a crucial role
in the integration of different aspects of cognition, memory and emo-
tional regulation by managing the cognitive control over emotional
stimuli and emotional behavior (Knight et al., 1999;Hariri et al.,
2000;Miller and Cohen, 2001;Kalish and Robins, 2006;Balconi and
Ferrari, 2012).
Also the appraisal process was affected by this valence effect. Indeed
the explicit level of emotional cue processing (SAM rate) showed a
clear arousal- and valence-related dichotomy. Accordingly, we found a
significant polarization of judgment by the subjects as a function of
valence feature, using positive and negative dichotomy for both low-
and high-arousing categories. To explain this effect, as stated by Lang
et al. (1990), two motive systems may be proposed in the brain to
explain the model of valence. Appetitive and aversive/defensive stable
systems account for the hedonic valence and arousal evaluation in
emotional comprehension. The defensive system should be primarily
activated in negative contexts, with a basic behavioral repertoire built
on withdrawal, escape or attack. Conversely, the appetitive system is
activated in positive contexts that promote survival, sustenance and
nurturance, with a basic behavioral repertoire of ingestion and care-
giving (LeDoux, 1990;Fanselow, 1994;Davis and Lang, 2003;Balconi
et al., 2011).
This resting predictive value on brain response to emotions also
appears to suggest a second main explanation: the contribution of a
possible stable subjective component in emotional behavior and in
emotional responsiveness. Indeed the present results were consistent
with the valence asymmetry hypothesis where the left/right asymmetry
index of PFC activity was correlated with specific emotional responses
to personality traits (Davidson et al., 2000;Canli et al., 2001;Fischer
et al., 2002). Therefore, a main consequence of this ‘lateralization’, as
shown by resting brain activity, is that each subject has a specific ‘at-
titude’ in response to the emotional context. This trait is manifested in
both a main left or right hemispheric activation in the absence of a
specific task or emotional processing; and in sensitivity to more posi-
tive vs negative cues, as reported by the increased lateralized activation
and in the explicit appraisal. We may suppose that this personal atti-
tude successively affects the brain responsiveness (as revealed by LI)
and the conscious process of valence attribution (as revealed by SAM).
Furthermore, the present results were also consistent with the hy-
pothesis of a connection between bilateral frontal cortex activity and
behavioral activation; i.e. the behavioral activation system (BAS) and
the behavioral inhibition system (BIS) may be related to anterior asym-
metry (Hewig et al., 2006). Specifically, induced negative affect in-
creases relative right-sided PFC activation, while induced positive
affect elicits an opposite pattern of asymmetric activation (Tomarken
et al., 1992;Wheeler et al., 1993). Indeed, another main factor affecting
subject’s response to emotional stimuli was the subjective sensitivity to
the environmental emotional cues (Allen and Kline, 2004). The roles
that temperament and personality play in influencing emotional re-
sponses was confirmed by a great number of empirical studies, for both
normal and clinical samples (Heller, 1993;Everhart and Harrison,
2000;Mardaga et al., 2006). A prevalent view suggests that the bases
of the emotional construct correspond to two general systems for
orchestrating adaptive behavior (Gray, 1981;Carver and White,
1994). The first system halts ongoing behavior while processing poten-
tial threat cues and is referred to as BIS (Gray, 1990;Lang et al., 1990).
A second system is believed to govern the engagement of action and
has been referred to as BAS (Fowles, 1980;Gray, 1982). Empirical
evidence suggests that people with highly sensitive BAS may respond
in great measure to positive, approach-related emotions, such as the
expression of happiness and positive effect, that allow the subject to
have favorable behavior toward the environment (Davidson et al.,
1990;Tomarken et al., 1992).
Although the BIS/BAS model concerns behavioral regulation, re-
cently researchers have become interested in how these constructs
are manifested in individual differences and emotional attitudes.
Gray’s model has tried to explain the behavioral motivational re-
sponses in general and, second, the generation of emotions that are
relevant to approach and withdrawal behavior (Gray, 1981;Gray et al.,
1997). In a clinical context, patients with major depressive disorder
exhibited reduced left frontal EEG activity in the resting state com-
pared with normal controls, suggesting that asymmetry in PFC activity
at rest measured by EEG is correlated with the emotional state (Kemp
et al., 2010).
A second consequence is that, also in a clinical condition, the ‘un-
balance effect’ between left vs right activity may be predictive of patho-
logical conditions, as shown in the case of anxiety disorders. Indeed it
was found that an increased level of anxiety might be associated with a
dysfunctional increased activation of the frontal right-hemisphere in
resting condition or a reduced activation of frontal-left-hemisphere
(van Honk et al., 1999;Zwanzger et al., 2009). This model has fur-
nished clear evidence about the different behaviors induced by positive
negave valence
-0.4 -0.2 0 0.2 0.4 0.6
-0.4 -0.2 0 0.2 0.4 0.6
posive valence
Fig. 6 Scatter plot of LIR and SAM while viewing negative (a) vs positive (b) stimuli.
1612 S C A N ( 2 015 ) M. Balconi et al.
vs negative emotional stimuli in specific emotional tasks, supposing a
successively more right frontal hyperactivation for high-anxiety sub-
jects in comparison with the left side, inducing an unbalanced pro-
cessing of the two stimuli categories, with a consistent bias for the
negative one. Specifically, in line with the valence model, hypervigilant
attention was found to interfere with the high-anxiety subjects’ per-
formance, with a specific attentional bias (Eysenck, 1997).
However, future research should better explore the intrinsic rela-
tionship between personality traits, personality components and rest-
ing brain activity to better define the role personality has in affective
behavior. That is, future research may more directly test the relation-
ship between BIS/BAS construct and resting state, from one hand; and
between BIS/BAS and emotional cue processing as predicting by rest-
ing brain activity. Second, the lateralization effect we found for both
resting and activation condition should further be explored by other
cortical measures, such as EEG. Indeed the dynamic modulation of
emotional process could be better analyzed by integrating hemo-
dynamic and electrophysiological indexes. A critical point of the pre-
sent research was the exclusive focus on the prefrontal sites. Indeed we
considered the role of the resting of the PFC as impacting the succes-
sive emotional cue processing. Future research should extend the ana-
lysis to other cortical sites. Finally, a possible limitation of the present
study concerning the baseline period should be mentioned. Our base-
line period (3 min) was relatively short compared with that used in
other studies. However, the stable effect we found related to LIR may
suggest we adopted a significant time-window to compare resting state
with activation response.
Allen, J.J.B., Kline, J.P. (2004). Frontal EEG asymmetry, emotion, and psychopathology: the
first, and the next 25 years. Biological Psychology,67,15.
Amodio, D.M., Harmon-Jones, E. (2012). Neuroscience approaches to social and person-
ality psychology. In: Snyder, M., Deaux, K., editors. Handbook of Social and Personality
Psychology. New York: Oxford University Press, pp. 11150.
Balconi, M., Bortolotti, A. (2012). Detection of the facial expression of emotion and self-
report measures in empathic situations are influenced by sensorimotor circuit inhibition
by low-frequency rTMS. Brain Stimulation,5(3), 306.
Balconi, M., Ferrari, C. (2012). rTMS stimulation on left DLPFC increases the correct
recognition of memories for emotional target and distractor words. Cognitive,
Affective and Behavioral Neuroscience,12(3), 58998.
Balconi, M., Lucchiari, C. (2007). Consciousness and emotional facial expression recogni-
tion: subliminal/supraliminal stimulation effect on N200 and P300 ERPs. Journal of
Psychophysiology,21, 1008.
Balconi, M., Mazza, G. (2009). Brain oscillations and BIS/BAS (behavioral inhibition/
activation system) effects on processing masked emotional cues. ERS/ERD and coher-
ence measures of alpha band. International Journal of Psychophysiology,74(2), 15865.
Balconi, M., Mazza, G. (2010). Lateralisation effect in comprehension of emotional facial
expression: a comparison between EEG alpha band power and behavioural inhibition
(BIS) and activation (BAS) systems. Laterality,15(3), 36184.
Balconi, M., Pozzoli, U. (2003). ERPs (event-related potentials), semantic attribution, and
facial expression of emotions. Consciousness and Emotion,4,6380.
Balconi, M., Pozzoli, U. (2009). Arousal effect on emotional face comprehension: frequency
band changes in different time intervals. Physiology and Behavior,97(34), 45562.
Balconi, M., Bortolotti, A., Gonzaga, L. (2011). Emotional face recognition, EMG response,
and medial prefrontal activity in empathic behavior. Neuroscience Research,71(3),
Balconi, M., Brambilla, E., Falbo, L. (2009). BIS/BAS, cortical oscillations and coherence in
response to emotional cues. Brain Research Bullettin,80(3), 1517.
Balconi, M., Grippa, E., Vanutelli, M.E. (2015). What hemodynamic (fNIRS), electro-
physiological (EEG) and autonomic integrated measures can tell us about emotional
processing. Brain and Cognition,95,6776.
Beck, A.T., Steer, R.A., Brown, G.K. (1996). BDI-II: Beck Depression Inventory Manual 2nd
edn. San Antonio, TX: Psychological Corporation.
Bradley, M.M., Lang, P.J. (1994). Measuring emotion: the self-assessment manikin and the
semantic differential. Journal of Behavior Therapy and Experimental Psychiatry,25(1),
Bradley, M.M., Lang, P.J. (2007). The International Affective Picture System (IAPS) in the
study of emotion and attention. In: Coan, J.A., Allen, J.J.B., editors. Handbook of
Emotion Elicitation and Assessment. New York: Oxford University Press.
Butti, M., Pastori, A., Merzagora, A., et al. (2006). Multimodal analysis of a sustained
attention protocol: continuous performance test assessed with near infrared spectros-
copy and EEG. In: Proceedings of the 28th IEEE Engineering in Medicine and Biology
Society Annual International Conference. New York, NY, vol. 1, 10403.
Canli, T., Zhao, Z., Desmond, J.E., Kang, E., Gross, J., Gabrieli, J.D. (2001). An fMRI study
of personality influences on brain reactivity to emotional stimuli. Behavioral
Neuroscience,115(1), 3342.
Carver, C.S., White, T.L. (1994). Behavioral inhibition, behavioral activation, and affective
responses to impending reward and punishment: The BIS/BAS scales. Journal of
Personality and Social Psychology,67, 31933.
Coan, J.A., Allen, J.J., McKnight, P.E. (2006). A capability model of individual differences
in frontal EEG asymmetry. Biological Psychology,72(2), 198207.
Cuthbert, B.N., Schupp, H.T., Bradley, M.M., Birbaumer, N., Lang, P.J. (2000). Brain
potentials in affective picture processing: covariation with autonomic arousal and af-
fective report. Biological Psychology,52,95111.
Damasio, A.R. (1996). The somatic marker hypothesis and the possible functions of the
prefrontal cortex. Philosophical Transaction of the Royal Society. Series B, Biological
Sciences,351, 141320.
Davidson, R.J. (1995). Cerebral asymmetry, emotion and affective style. In: Davidson, R.J.,
Hughdahl, K., editors. Brain Asymmetry. Cambridge, MA: MIT Press, pp. 36187.
Davidson, R.J. (1998). Anterior electrophysiological asymmetries, emotion, and depression:
conceptual and methodological conundrums. Psychophysiology,35,60714.
Davidson, R.J. (2002). Anxiety and affective style: role of prefrontal cortex and amygdala.
Biological Psychiatry,51,6880.
Davidson, R., Ekman, P., Saron, C.D., Senulis, J.A., Friesen, W.V. (1990). Approach/with-
drawal and cerebral asymmetry: emotional expression and brain physiology. Journal of
Personality and Social Psychology,58, 33041.
Davidson, R.J., Jackson, D.C., Kalin, N.H. (2000). Emotion, plasticity, cortex, and regula-
tion: perspectives from affective neuroscience. Psychological Bulletin,126(6), 890909.
Davis, M., Lang, P.J. (2003). Emotion. In: Gallagher, M., Nelson, R.J., editors. Handbook of
Psychology. New York: Wiley, pp. 40539.
Davis, M., Whalen, P.J. (2001). The amygdala: vigilance and emotion. Molecular Psychiatry,
Everhart, D.E., Harrison, D.W. (2000). Facial affect perception among anxious and non-
anxious men. Psychobiology,28,908.
Everhart, D.E., Carpenter, M.D., Carmona, J.E., Ethridge, A.J., Demaree, H.A. (2003).
Adult sex-related P300 differences during the perception of emotional prosody and
facial affect. Psychophysiology,40(S1), S39.
Eysenck, M.W. (1997). Anxiety and Cognition. A Unified Theory. Hove, UK: Psychology
Fanselow, M.S. (1994). Neural organization of the defensive behavior system responsible
for fear. Psychonomic Bulletin and Review,1, 42938.
Ferrari, M., Quaresima, V. (2012). A brief review on the history of human near-infrared
spectroscopy (fNIRS) development and fields of applications. Neuroimage,63, 92135.
Fischer, H., Andersson, J.L., Furmark, T., Wik, G., Fredrikson, M. (2002). Right-sided
human prefrontal brain activation during acquisition of conditioned fear. Emotion,
2(5), 23341.
Fowles, D.C. (1980). The three arousal model: Implications of Gray’s two-factor learning
theory for heart rate, electrodermal activity, and psychopathy. Psychophysiology,17,
Fox, M.D., Raichle, M.E. (2007). Spontaneous fluctuations in brain activity observed with
functional magnetic resonance imaging. Nature Review of Neuroscience,8,70011.
Frijda, N.H. (1993). The place of appraisal in emotion. Cognition and Emotion,7,35787.
Gray, J.A. (1981). A critique of Eysenck’s theory of personality. In: Eysenck, H.J., editor. A
Model for Personality. Berlin: Springer, pp. 24676.
Gray, J.A. (1982). The Neuropsychology of Anxiety: An Inquiry into the Functions of the
Septo-Hippocampal System. New York: Oxford University Press.
Gray, J.A. (1990). Brain systems that mediate both emotion and cognition. Cognition and
Emotion,4, 26988.
Gray, J.A., Moran, P.M., Grigoryan, G., et al. (1997). Latent inhibition: the nucleus accum-
bens connection revisited. Behavioural Brain Research,88,2735.
Hariri, A., Bookheimer, S., Mazziotta, J. (2000). Modulating emotional responses: effects of
a neocortical network on the limbic system. NeuroReport,11,438.
Harmon-Jones, E. (2003). Clarifying the emotive functions of asymmetrical frontal cortical
activity. Psychophysiology,40, 83848.
Harmon-Jones, E. (2004). Contributions from research on anger and cognitive dissonance
to understanding the motivational functions of asymmetrical frontal brain activity.
Biological Psychology,67(12), 5176.
Harmon-Jones, E., Allen, J.J.B. (1997). Behavioral activation sensitivity and resting frontal
EEG asymmetry: covariation of putative indicators related to risk for mood disorders.
Journal of Abnormal Psychology,106, 15963.
Harmon-Jones, E., van Honk, J. (2012). Introduction to a special issue on the neuroscience
of motivation and emotion. Motivation and Emotion,36,13.
Harmon-Jones, E., Vaughn-Scott, K., Mohr, S., Sigelman, J., Harmon-Jones, C. (2004).
The effect of manipulated sympathy and anger on left and right frontal cortical activity.
Emotion,4(1), 95101.
Resting and brain activity during emotions SCAN (2015) 1613
Heller, W. (1993). Neuropsychological mechanisms of individual differences in emotion,
personality, and arousal. Neuropsychology,7, 47689.
Herrmann, M.J., Huter, T., Plichta, M.M., et al. (2008). Enhancement of activity of the
primary visual cortex during processing of emotional stimuli as measured with event-
related functional Near-Infrared Spectroscopy and Event-Related Potentials. Human
Brain Mapping,29,2835.
Hewig, J., Hagemann, D., Seifert, J., Naumann, E., Bartussek, D. (2004). On the selective
relation of frontal cortical asymmetry and anger-out versus anger-control. Journal of
Personality and Social Psychology,87, 92639.
Hewig, J., Hagemann, D., Seifert, J., Naumann, E., Bartussek, D. (2006). The relation of
cortical activity and BIS/BAS on the trait level. Biological Psychology,71(1), 4253.
Hongyu, Y., Zhenyu, Z., Yun, L., Zongcai, R. (2007). Gender difference in hemodynamic
responses of prefrontal area to emotional stress by near-infrared spectroscopy.
Behavioral Brain Research,178, 1726.
Hoshi, Y., Kobayashi, N., Tamura, M. (2001). Interpretation of near-infrared spectroscopy
signals: a study with a newly developed perfused rat brain model. Journal of Applied
Physiology,90(5), 165762.
Hoshi, Y., Kosaka, S., Xie, Y., Kohri, S., Tamura, M. (1998). Relationship between fluctu-
ations in the cerebral hemoglobin oxygenation state and neuronal activity under resting
conditions in man. Neuroscience Letters,245(3), 14750.
Ishikawa, W., Sato, M., Fukuda, Y., Matsumoto, T., Takemura, N., Sakatani, K. (2014).
Correlation between asymmetry of spontaneous oscillation of hemodynamic changes in
the prefrontal cortex and anxiety levels: a near-infrared spectroscopy study. Journal of
Biomedical Optics,19(2), 027005.
Kalish, Y., Robins, G. (2006). Psychological predispositions and network structure: the
relationship between individual predispositions, structural holes and network closure.
Social Networks,28,5684.
Kemp, A.H., Griffiths, K., Felmingham, K.L., et al. (2010). Disorder specificity des-
pite comorbidity: resting EEG alpha asymmetry in major depressive disorder and
post-traumatic stress disorder. Biological Psychology,85(2), 3504.
Knight, R.T., Staines, W.R., Swick, D., Chao, L.L. (1999). Prefrontal cortex regulates in-
hibition and excitation in distributed neural networks. Acta Psychologica,101, 15978.
Lang, P.J., Bradley, M.M., Cuthbert, B.N. (1990). Emotion, attention, and the startle reflex.
Psychophysiological Review,97, 37798.
LeDoux, J.E. (1990). Information flow from sensation to emotion plasticity in the neural
computation of stimulus values. In: Gabriel, M., Moore, J., editors. Learning and
Computational Neuroscience: Foundations of Adaptive Networks. Cambridge, MA:
Bradford Books/MIT Press, pp. 352.
Lilienfeld, S.O., Wood, J.S., Garb, H.N. (2000). The scientific status of projective tech-
niques. Psychological Science in the Public Interest,1,2766.
Mardaga, S., Laloyaux, O., Hansenne, M. (2006). Personality traits modulate skin conduct-
ance response to emotional pictures: an investigation with Cloninger’s model of
personality. Personality and Individual Differences,40, 160314.
Miller, E.K., Cohen, D.J. (2001). An integrative theory of prefrontal cortex function.
Annual Review of Neuroscience,24, 167202.
Ochsner, K.N., Gross, J.J. (2005). The cognitive control of emotion. Trends in Cognitive
Sciences,9(5), 2429.
Oostenveld, R., Praamstra, P. (2001). The five percent electrode system for high-resolution
EEG and ERP measurements. Clinical Neurophysiology,112, 7139.
Pessoa, L., Kastner, S., Ungerleider, L.G. (2002). Attentional control of the processing of
neural and emotional stimuli. Cognitive Brain Research,15,3145.
Phan, K.L., Wager, T., Taylor, S.F., Liberzon, I. (2002). Functional neuroanatomy of emo-
tion: a meta-analysis of emotion activation studies in PET and fMRI. Neuroimage,16,
Russell, J. (1980). A circumplex model of affect. Journal of Personality and Social Psychology,
39, 116178.
Russell, J.A. (2003). Core affect and the psychological construction of emotion.
Psychological Review,110(1), 14572.
Silberman, E.K., Weingartner, H. (1986). Hemispheric lateralization of functions related to
emotion. Brain and Cognition,5(3), 32253.
Stewart, J.L., Coan, J.A., Towers, D.N., Allen, J.J. (2014). Resting and task-elicited pre-
frontal EEG alpha asymmetry in depression: support for the capability model.
Psychophysiology,51(5), 44655.
Sutton, S.K., Davidson, R.J. (2000). Prefrontal brain electrical asymmetry predicts the
evaluation of affective stimuli. Neuropsychologia,38, 172333.
Tomarken, A.J., Davidson, R.J., Wheeler, R.E., Kinney, L. (1992). Psychometric properties
of resting anterior EEG asymmetry: temporal stability and internal consistency.
Psychophysiology,29(5), 57692.
van Honk, J., Tuiten, A., Verbatern, R., et al. (1999). Correlations among salivary testos-
terone, mood, and selective attention to threat in humans. Hormones and Behavior,36,
Wallace, J. (1966). An abilities conception of personality: some implications for personality
measurement. American Psychologist,21, 1328.
Wheeler, R.E., Davidson, R.J., Tomarken, A.J. (1993). Frontal brain asymmetry and
emotional reactivity: a biological substrate of affective style. Psychophysiology,30(1),
Zwanzger, P., Fallgatter, J., Zavorotnyy, M., Padberg, F. (2009). Anxiolytic effects of tran-
scranial magnetic stimulationan alternative treatment option in anxiety disorders?
Journal of Neural Transmission,116, 76775.
1614 S C AN ( 2 015 ) M. Balconi et al.
... LI is commonly used to describe the asymmetry of brain activation [47]. We calculated the LIS for each session of each group by using the formula LI = (R − L)/(R + L), where R and L are the maximum absolute amplitudes of ∆HbO according to Reference [48]. There are channels on the left (Chs. ...
... However, this type of task might not be adequate for stress-related studies of hemodynamic signal attenuation. During the experiment, the participants only looked at a blank screen and the IAPS image on the screen alternately, while their brain signals were recorded [48]. After looking at the images for several seconds, participants took a break by looking at a blank screen (or with a fixation cross) to allow the hemoglobin levels to return to baseline. ...
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A stress group should be subdivided into eustress (low-stress) and distress (high-stress) groups to better evaluate personal cognitive abilities and mental/physical health. However, it is challenging because of the inconsistent pattern in brain activation. We aimed to ascertain the necessity of subdividing the stress groups. The stress group was screened by salivary alpha-amylase (sAA) and then, the brain’s hemodynamic reactions were measured by functional near-infrared spectroscopy (fNIRS) based on the near-infrared biosensor. We compared the two stress subgroups categorized by sAA using a newly designed emotional stimulus-response paradigm with an international affective picture system (IAPS) to enhance hemodynamic signals induced by the target effect. We calculated the laterality index for stress (LIS) from the measured signals to identify the dominantly activated cortex in both the subgroups. Both the stress groups exhibited brain activity in the right frontal cortex. Specifically, the eustress group exhibited the largest brain activity, whereas the distress group exhibited recessive brain activity, regardless of positive or negative stimuli. LIS values were larger in the order of the eustress, control, and distress groups; this indicates that the stress group can be divided into eustress and distress groups. We built a foundation for subdividing stress groups into eustress and distress groups using fNIRS.
... For the fNIRS data we used Ren, Lu, Liu et al., 2017;Tanida et al., 2007), not only because it is a better indicator of task-related activity (Hoshi et al., 2011), but also because it has better signal-noise ratio (Hoge, Franceschini, Covolan, Huppert, Mandeville & Boas, 2005;Strangman et al., 2002), and correlates well to fMRI BOLD signal (Cui et al., 2011). On the other hand, deoxy-Hb has better spatial resolution (Franceschini, Toronov, Filiaci, Gratton & Fantini, 2000), but is known to suffer from low signalnoise ratio limiting its usability (Balconi, Grippa & Vanutelli, 2015a;Bulgarelli, Blasi, Arridge et al., 2018;Tam & Zouridakis, 2015). Physiological noise (i.e., artifacts from respiration and cardiac pulsation) was removed using two band-stop filters (0.12-0.25 and 0.7-2.0 ...
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Affective processing, including induction and regulation of emotion, activates neural networks, induces physiological responses, and generates subjective experience. Dysregulation of these processes can lead to maladaptive behavior and even psychiatric morbidity. Multimodal studies of emotion thus not only help elucidate the nature of emotion, but also contribute to important clinical insights. In the present study, we compared the induction (EI) and effortful regulation (ER) with reappraisal of fear and disgust in healthy subjects using functional near infrared spectroscopy (fNIRS) in conjunction with electrodermal activity (EDA). During EI, there was significant activation in medial prefrontal cortex (PFC) for fear and more widespread activation for disgust, with right lateral PFC significantly more active during disgust compared to fear. ER was equally effective for fear and disgust reducing subjective emotion rating by roughly 45%. Compared to baseline, there was no increased PFC activity for fear during ER, while for disgust lateral PFC was significantly more active. Significant differences between the two negative emotions were also observed in sympathetic nerve activity as reflected in EDA during EI, but not during ER. Lastly, compared to men, women had higher emotion rating for both fear and disgust without corresponding differences in EDA. In conclusion, in the present study we show that emotion induction was associated with differential activation in both PFC and sympathetic nerve activity for fear and disgust. These differences were however less prominent during emotion regulation. We discuss the potential interpretation of our results and their implications regarding our understanding of negative emotion processing.
... Based on previous evidence, to assess participants' dispositions toward the advertisements that were displayed in the present study, neural activity from PFC was recorded with the functional Near-Infrared Spectroscopy (fNIRS), a solid, non-invasive tool that allows assessing the brain's neural activity by monitoring variations in the cortical hemoglobin concentration with accurate spatial and temporal resolution [40]. The fNIRS can provide accurate esteem of lateralized prefrontal activity [41,42] and has recently proven its potential also in consumer neuroscience research [43][44][45]. ...
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In pandemic times, taking advantage of COVID-19-elicited emotions in commercials has been a popular tactic employed by corporations to build successful consumer engagement and, hopefully, increase sales. The present study investigates whether COVID-19-related emotional communication affects the consumer’s emotional response and the approach/avoidance motivation toward the brand—measured as a function of brain hemodynamic changes—as well as the purchase intentions. The functional Near-Infrared Spectroscopy (fNIRS) was employed to record neural correlates from the prefrontal cortex while the experimental and control groups were observing respectively COVID-19-related and unrelated advertisements (ads). The hemodynamic patterns suggest that COVID-19-related ads may promote deeper emotional elaboration, shifting consumers’ attention from the semantic meaning to the affective features and perhaps supporting a more favorable brand evaluation. Conversely, purchase intentions were only related to the pre-existing level of brand engagement. The findings suggest that leveraging the negative emotional potential of COVID-19 may not shift the explicit purchase intentions but could nonetheless boost emotional engagement, benefitting the final evaluation of the brand at an implicit level.
... Abnormal RSFC of the left PFC with left parietal cortical areas was observed in young depressed patients with suicide attempts in this study. The left hemisphere exhibited particular features with regards to not only general emotion processing but also specific depression pathophysiology (35), and a greater left hemispheric response to positive stimuli was noted during general emotion processing (36). Elsewhere, in our study, we found the RSFC of the frontoparietal circuit was correlated with the SSI and BIS-11 scores in the ATT group. ...
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Suicide is a leading cause of death among youth and is strongly associated with major depressive disorder (MDD). However, the neurobiological underpinnings of suicidal behaviour and the identification of risk for suicide in young depressed patients are not yet well-understood. In this study, we used a seed-based correlation analysis to investigate the differences in resting-state functional connectivity (RSFC) in depressed youth with or without a history of suicide attempts and healthy controls (HCs). Suicidal attempters (ATT group, n = 35), non-suicide attempters (NAT group, n = 18), and HCs exhibited significantly different RSFC patterns with the left superior prefrontal gyrus (L-SFG) and left middle prefrontal gyrus (L-MFG) serving as the regions of interest (ROIs). The ATT group showed decreased RSFC of the left middle frontal gyrus with the left superior parietal gyrus compared to the NAT and HC groups. Decreased RSFC between the left superior frontal gyrus and the right anterior cingulate cortex (rACC) was found in the ATT group compared to the NAT and HC groups. Furthermore, the left prefrontal-parietal connectivity was associated with suicidal ideation and levels of impulsivity, but RSFC of the left prefrontal cortex with the rACC was correlated exclusively with impulsivity levels and was not related to suicidal ideation in the ATT group. Our results demonstrated that altered RSFC of the prefrontal-parietal and prefrontal-rACC regions was associated with suicide attempts in depressed youth, and state-related deficits in their interconnectivity may contribute to traits, such as cognitive impairments and impulsivity to facilitate suicidal acts. Our findings suggest that the neural correlates of suicidal behaviours might be dissociable from those related to the severity of current suicidal ideation. Neural circuits underlying suicide attempts differ from those that underlie suicidal ideation.
... Regarding the mental load, many studies used slow-wave and fast-wave increases/decreases and (α/θ)/β or (α/θ)/(α + β) ratios in the frontal and central brain areas (e.g., Wang et al., 2020) to explore the brain networks contribution in cognitive and emotional planning. In parallel, information about emotion recognition has been collected via frontal asymmetry (Balconi and Mazza, 2010;Balconi et al., 2014), normalized frontal asymmetry (Balconi et al., 2009(Balconi et al., , 2015, theta-beta ratio (Angelidis et al., 2018), and Hjorth parameters for affective state estimation (e.g., Rakibul Mowla et al., 2020). ...
... Studying positive welfare is currently a highly topical issue in animal welfare research (Rault et al., 2020;Webb et al., 2019), which might also benefit from the affective styles approach, specifically, using the BIS/BAS framework. For example, greater involvement of the left hemisphere during positive appraisal has been shown to be predicted by high BAS scores (Balconi and Mazza, 2010) or by greater left hemispheric activity during baseline (Balconi et al., 2015). Combining studies measuring individual hemispheric dominance (Goursot et al., 2019a) with studies testing for differential hemispheric involvement during positive appraisal (Goursot et al., 2019b) would be a first step towards research on affective styles. ...
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The growing recognition of animals as individuals has broader implications for farm animal welfare research. Even under highly standardized on-farm conditions, farm animals show heterogeneous but individually consistent behavioural patterns towards various stimuli, based on how they appraise these stimuli. As a result, animal welfare is likely to be highly individual as well, and studying the proximate mechanisms underlying distinct individual behaviour patterns and appraisal will improve animal welfare research. We propose to extend the framework of affective styles to bridge the gap between existing research fields on animal personality and affective states. Affective styles refer to consistent individual differences in emotional reactivity and regulation and can be predicted by baseline cerebral lateralization. Likewise, animals with consistent left or right motor biases—a proxy measure of individual patterns in cerebral lateralization—have been shown to differ in their personality, emotional reactivity, motivational tendencies or coping styles. In this paper, we present the current knowledge of the links between laterality and stable individual traits in behaviour and affect in light of hypotheses on emotional lateralization. Within our suggested framework, we make recommendations on how to investigate affective styles in non-human animals and give practical examples. This approach has the potential to promote a science of affective styles in nonhuman animals and significantly advance research on animal welfare.
Background An increasing number of neuroimaging studies report alterations of cortical thickness (CT) related to the neuropathology of bipolar disorder (BD). We provide here a whole-brain vertex-wise meta-analysis, which may help improve the spatial precision of these identifications. Methods A comprehensive meta-analysis was performed to investigate the differences in CT between patients with BD and healthy controls (HCs) by using a newly developed mask for CT analysis in seed-based d mapping (SDM) meta-analytic software. We used meta-regression to explore the effects of demographics and clinical characteristics on CT. This meta-review was conducted in accordance with PRISMA guideline. Results We identified 21 studies meeting criteria for the systematic review, of which 11 were eligible for meta-analysis. The meta-analysis comprising 649 BD patients and 818 HCs showed significant cortical thinning in the left insula extending to left Rolandic operculum and Heschl gyrus, the orbital part of left inferior frontal gyrus (IFG), the medial part of left superior frontal gyrus (SFG) as well as bilateral anterior cingulate cortex (ACC) in BD. In meta-regression analyses mean patient age was negatively correlated with reduced CT in the left insula. Limitations All enrolled studies were cross-sectional; we could not explore the potential effects of medication and mood states due to the limited data. Conclusions Our results suggest that BD patients have significantly thinner frontoinsular cortex than HCs, and the results may be helpful in revealing specific neuroimaging biomarkers of BD patients.
The interest of neuroscience has been aimed at the investigation of the neural bases underlying gestural communication. This research explored the intra- and inter-brain connectivity between encoder and decoder. Specifically, adopting a “hyperscanning paradigm” with the functional Near-infrared Spectroscopy (fNIRS) cerebral connectivity in oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin levels were revealed during the reproduction of affective, social, and informative gestures of different valence. Results showed an increase of intra- and inter-brain connectivity in dorsolateral prefrontal cortex for affective gestures, in superior frontal gyrus for social gestures and in frontal eyes field for informative gestures. Moreover, encoder showed a higher intra-brain connectivity in posterior parietal areas more than decoder. Finally, an increasing of inter-brain connectivity more than intra-brain (ConIndex) was observed in left regions for positive gestures. The present research has explored how the individuals neural tuning mechanisms turn out to be strongly influenced by the nature of specific gestures.
Neuroscientific approaches have become increasingly important in understanding how our bodies respond emotionally and physically to experiences. The use (and abuse) of neuroscience and psychological research methodologies for measuring emotional response has become a hot topic in research, particularly in applied sciences such as consumer and market research, often called “applied neuroscience.” Neuro- and psychological science can help researchers better understand unconscious motivators and emotional reactions. However, the application of these tools has been plagued with pseudoscience and “neuro-hype.” Researchers have experienced some disappointments when trying to incorporate these measures into their research. In this chapter we will discuss popular neuro-tools used to assess emotion. We will explore the challenges and discuss real examples of misuses, abuses, and disappointments in the application of these methodologies. Real and thoughtful applied neuroscience is about using the right combination of sensitive measures from psychology and neuroscience in the most appropriate ways.
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Prefrontal cortex provides both inhibitory and excitatory input to distributed neural circuits required to support performance in diverse tasks. Neurological patients with prefrontal damage are impaired in their ability to inhibit task-irrelevant information during behavioral tasks requiring performance over a delay. The observed enhancements of primary auditory and somatosensory cortical responses to task-irrelevant distractors suggest that prefrontal damage disrupts inhibitory modulation of inputs to primary sensory cortex, perhaps through abnormalities in a prefrontal-thalamic sensory gating system. Failure to suppress irrelevant sensory information results in increased neural noise, contributing to the deficits in decision making routinely observed in these patients. In addition to a critical role in inhibitory control of sensory flow to primary cortical regions, and tertiary prefrontal cortex also exerts excitatory input to activity in multiple sub-regions of secondary association cortex. Unilateral prefrontal damage results in multi-modal decreases in neural activity in posterior association cortex in the hemisphere ipsilateral to damage. This excitatory modulation is necessary to sustain neural activity during working memory. Thus, prefrontal cortex is able to sculpt behavior through parallel inhibitory and excitatory regulation of neural activity in distributed neural networks.
At the heart of emotion, mood, and any other emotionally charged event are states experienced as simply feeling good or bad, energized or enervated. These states - called core affect - influence reflexes, perception, cognition, and behavior and are influenced by many causes internal and external, but people have no direct access to these causal connections. Core affect can therefore be experienced as free-floating (mood) or can be attributed to some cause (and thereby begin an emotional episode). These basic processes spawn a broad framework that includes perception of the core-affect-altering properties of stimuli, motives, empathy, emotional meta-experience, and affect versus emotion regulation; it accounts for prototypical emotional episodes, such as fear and anger, as core affect attributed to something plus various nonemotional processes.
Although projective techniques continue to be widely used in clinical and forensic settings, their scientific status remains highly controversial. In this monograph, we review the current state of the literature concerning the psychometric properties (norms, reliability, validity, incremental validity, treatment utility) of three major projective instruments: Rorschach Inkblot Test, Thematic Apperception Test (TAT, and human figure drawings. We conclude that there is empirical support for the validity of a small number of indexes derived from the Rorschach and TAT. However, the substantial majority of Rorschach and TAT indexes are not empirically supported. The validity evidence for human figure drawings is even more limited. With a few exceptions, projective indexes have not consistently demonstrated incremental validity above and beyond other psychometric data. In addition, we summarize the results of a new meta-analysis intended to examine the capacity of these three instruments to detect child sexual abuse. Although some projective instruments were better than chance at detecting child sexual abuse, there were virtually no replicated findings across independent investigative terms. This meta-analysis also provides the first clear evidence of substantial file drawer effects in the projectives literature, as the effect sizes from published studies markedly exceeded those from unpublished studies. We conclude with recommendations regarding the la) construction of projective techniques with adequate validity: lbl forensic and clinical rise of projective techniques, and Ic) education and training of future psychologists regarding projective techniques.
In this article I discuss a hypothesis, known as the somatic marker hypothesis, which I believe is relevant to the understanding of processes of human reasoning and decision making. The ventromedial sector of the prefrontal cortices is critical to the operations postulated here, but the hypothesis does not necessarily apply to prefrontal cortex as a whole and should not be seen as an attempt to unify frontal lobe functions under a single mechanism. The key idea in the hypothesis is that 'marker' signals influence the processes of response to stimuli, at multiple levels of operation, some of which occur overtly (consciously, 'in mind') and some of which occur covertly (non-consciously, in a non-minded manner). The marker signals arise in bioregulatory processes, including those which express themselves in emotions and feelings, but are not necessarily confined to those alone. This is the reason why the markers are termed somatic: they relate to body-state structure and regulation even when they do not arise in the body proper but rather in the brain's representation of the body. Examples of the covert action of 'marker' signals are the undeliberated inhibition of a response learned previously; the introduction of a bias in the selection of an aversive or appetitive mode of behaviour, or in the otherwise deliberate evaluation of varied option-outcome scenarios. Examples of overt action include the conscious 'qualifying' of certain option-outcome scenarios as dangerous or advantageous. The hypothesis rejects attempts to limit human reasoning and decision making to mechanisms relying, in an exclusive and unrelated manner, on either conditioning alone or cognition alone.
Social neuroscience is an interdisciplinary approach to studying the mind and behavior, noted for its appreciation for the dynamic interactions of situational and dispositional processes as they relate to neural and biological mechanisms. In this chapter, we describe the methodological approach of social neuroscience and review research that has applied this approach to address the interplay of the person and situation in the domains of social cognition, attitudes, emotion and motivation, intergroup relations, and personality. We provide critical discussion of how neuroscience may contribute to classic questions in personality and social psychology, and we describe how the social neuroscience approach promotes the integration of dispositional and situational accounts of the mind and behavior.
In two experiments a tachistoscopic paradigm was used to examine hemispheric differences in facial affect perception among anxious and nonanxious men without depression. In Experiment 1, hemispheric processing of Ekman and Friesen's (1978) happy, angry, and neutral emotional faces was tachistoscopically examined, with reaction time as the dependent variable. The following results were obtained: (1) a right-hemisphere (LVF) advantage for the perception of facial affect, consistent with previous reports of the right hemisphere's relative specialization for facial affect perception and (2) slower reaction time to facial affect stimuli for anxious men, regardless of valence and visual field. Similar procedures were used in Experiment 2, but with accuracy rather than reaction time as the dependent measure. Analyses yielded a three-way interaction, with anxious men identifying angry affects in the left versus right visual field more accurately, whereas nonanxious men demonstrated symmetry for the processing of angry affects. Implications for hemispheric asymmetry (i.e., relative right posterior activation) among anxious individuals without depression are discussed.