USF Neural Correlates of Emotional Intelligence in Adolescent Children Essay minimum 350 words for each of the FWS attachments everything is mentioned in t

USF Neural Correlates of Emotional Intelligence in Adolescent Children Essay minimum 350 words for each of the FWS attachments everything is mentioned in the third documnet Format- Research Review
Goal: To help you learn more about the science of emotional Intelligence, to see the relationship
between EI and Brain and nervous system, and to become more critical consumers of information.
Info: For this assignment, you will need to select one article based on Neurobiology of Emotional
Intelligence. Please check ADU database. You only need to select one article corresponding to the
topic, but I encourage you to read as many as you would like. After reading the article, you will
need to fully answer the questions below.
Grading: You may NOT plagiarize from the article or any other source; you may use any other
source to help you complete this report. Only outstanding answers to each question will receive
the full points; this assignment is worth ____ points. Each answer requires multiple, grammatically
correct sentences that should be proofread for clarity and spelling. You are welcome to use
numbered or bullet point lists to help organize your thoughts. Your answers in the form of a
paragraph is also acceptable.
Questions You Will Answer
Question 1 (1 point): List the title of the article you selected and Why did you pick this article to
review for this assignment?
Question 2 (4 points): What did you learn from the article? Clearly explain the main issue(s)
covered in the article and what you specifically learned from the article. You need to fully explain
both the scientific findings covered in the article and what new information you learned from the
You will need multiple, detailed sentences to earn full credit. You will follow the below guideline
to explain the scientific findings:
? Context in which study was run / why this study is important
? Hypothesis/ Research Question
? Methods to conduct reserch (most important, main points, only)
? Results (most important, main points, only)
Cognitive, Affective, & Behavioral Neuroscience
2007, 7 (2), 140-151
Neural correlates of emotional intelligence
in adolescent children
McLean Hospital, Harvard Medical School, Belmont, Massachusetts
The somatic marker hypothesis posits a key role for the ventromedial prefrontal cortex, amygdala, and insula
in the ability to utilize emotions to guide decision making and behavior. However, the relationship between activity in these brain regions and emotional intelligence (EQ) during adolescence, a time of particular importance
for emotional and social development, has not been studied. Using functional magnetic resonance imaging
(f MRI), we correlated scores from the Bar-On Emotional Quotient Inventory, Youth Version (EQ-i:YV) with
brain activity during perception of fearful faces in 16 healthy children and adolescents. Consistent with the neural efficiency hypothesis, higher EQ correlated negatively with activity in the somatic marker circuitry and other
paralimbic regions. Positive correlations were observed between EQ and activity in the cerebellum and visual
association cortex. The findings suggest that the construct of self-reported EQ in adolescents is inversely related
to the efficiency of neural processing within the somatic marker circuitry during emotional provocation.
The transition from childhood to adulthood involves
dramatic changes in physical, cognitive, social, and emotional functioning (Spear, 2000). During this adolescent
period, developing children begin to focus more heavily on
their social relationships, strengthening bonds with peers
while slowly weaning themselves from the emotional support of their parents (Kloep, 1999; Nelson, Leibenluft,
McClure, & Pine, 2005). With the emergence of adolescence, the developing child is confronted with many
new challenges that require a different set of skills and
abilities, particularly in the emotional and social realms.
In order to manage their interpersonal relationships effectively, each adolescent must develop a well-tuned set
of emotional and social capacities: (1) self-awareness and
the ability to communicate emotional needs effectively,
(2) accurate perception of the emotions of others and the
ability to respond appropriately to those emotions, (3) the
ability to regulate emotions in a healthy and productive
way, (4) flexible coping skills and effective interpersonal
problem solving, and (5) a positive affective outlook
when faced with adversity (Bar-On, Tranel, Denburg, &
Bechara, 2003). Persons who possess and effectively utilize these emotional and social capacities have been described as showing emotional intelligence (EQ; Bar-On &
Parker, 2000; Mayer, DiPaolo, & Salovey, 1990). In recent
years, the concept of EQ has gained considerable interest
in the popular media, as well as in academic circles (Goleman, 1995; Mayer, Caruso, & Salovey, 1999). Although a
number of definitions of EQ have emerged, one definition
suggests that it is “an array of noncognitive capabilities,
competencies, and skills that influence one’s ability to
succeed in coping with environmental demands and pres-
sures” (Bar-On, 1997, p. 14). Several authors have made
a strong case for considering EQ to be a standard form of
intelligence (Mayer et al., 1999; Mayer, Salovey, Caruso,
& Sitarenios, 2001), although qualitatively different from
traditional “cognitive” types of intelligence (Bar-On et al.,
An understanding of the neurobiological substrate of
EQ in adults is beginning to emerge (Bar-On et al., 2003).
One influential theory that is particularly relevant to the
neurobiology of emotional intelligence is the somatic
marker hypothesis (Damasio, 1994). According to this
hypothesis, decision making is influenced by previously
learned associations between emotionally evocative
events and the affective response that occurred as a result.
These affective responses are essentially somatic states (or
mental simulations thereof) that are reactivated when one
encounters a biologically relevant situation that is similar to one encountered previously. The activation of these
somatic markers produces an emotional bias that aids in
decision making when circumstances are uncertain or
when there are too many alternatives to compare. In such
situations, somatic markers contribute to decision making by biasing choice selections away from alternatives
that evoke negative somatic states and toward choices that
evoke positive somatic states. Within this framework, an
emotionally intelligent individual may be understood as
one who is effective at utilizing these somatic-emotional
signals to appropriately and advantageously guide decision making and social behavior.
Evidence from neuropsychological studies of patients
with brain damage and from functional neuroimaging
studies of healthy individuals suggests that there are sev-
W. D. S. Killgore,
Copyright 2007 Psychonomic Society, Inc.
eral brain regions that are critical to the process of using
somatic markers to guide decision making toward advantageous outcomes. The most prominent include the amygdala, insular cortex, and ventromedial prefrontal cortex
(Bar-On et al., 2003), although many others, such as the
cerebellum and ventral striatum, are likely to be involved
as well, due to their role in affective processing (Christakou, Robbins, & Everitt, 2004; Exner, Weniger, & Irle,
2004; Lee et al., 2004; Levy & Dubois, 2006; ShamayTsoory et al., 2005). The amygdala is known to be critical for the ability to perceive some classes of emotionally
arousing stimuli and for forming associations between
aversive stimuli and an appropriate negative emotional
response, such as fear (Buchel, Morris, Dolan, & Friston, 1998; Furmark, Fischer, Wik, Larsson, & Fredrikson,
1997). The insula, on the other hand, appears to be important for monitoring ongoing somatic and visceral states
(Dunckley et al., 2005; Reiman, 1997; Reiman et al.,
1997). The ventromedial prefrontal cortex has been shown
to be particularly important for the ability to use somatic
markers to influence decision making toward advantageous outcomes (Bechara, Damasio, & Damasio, 2000;
Bechara, Damasio, Damasio, & Lee, 1999; Bechara, Tranel, & Damasio, 2000). Damage to this somatic marker
circuitry has been shown to lead to deficits in judgment
and decision making, social functioning, and EQ (Bar-On
et al., 2003). Although a large literature is emerging with
regard to EQ in adults, the developmental basis of these
capacities during childhood and adolescence has been virtually unexplored. The accelerated emotional and social
development that is typical of adolescence suggests that
this transitional period may be particularly important for
the emergence of emotionally intelligent behavior.
Although it is clear that there are individual differences in the emotional and social skills that are important
to managing interpersonal relationships and coping successfully with environmental demands and pressures, the
specific manner in which the somatic marker circuitry is
involved in these capacities is currently unknown. Many
studies of learning and development suggest that neural
activity becomes more efficient and focused as individuals
acquire greater skills and experience, a phenomenon that
constitutes the basis of the neural efficiency hypothesis.
For instance, Olson and colleagues (Olson et al., 2006)
found that as performance on a sequence-learning task
improved, there were corresponding decreases in cerebral
blood flow within regions of the brain important for task
completion, suggesting that the brain required less activity
(i.e., developed greater neural efficiency) to perform the
task at the same level of accuracy. Similarly, individuals
who show the greatest improvement on a learned task also
show the greatest reductions in regional cerebral glucose
metabolism during subsequent performance of the task,
suggesting increased neural efficiency (Haier, Siegel,
et al., 1992). Highly trained concert pianists show significantly lower cerebral activity during bimanual sequential
finger movements that mimic piano playing, as compared
with nonmusicians, suggesting that the expert pianists
possess greater efficiency of neural processing when engaged in the same task (Haslinger et al., 2004). Further-
more, traditional measures of cognitive intelligence have
been shown to correlate negatively with rates of cerebral
glucose metabolism following learning, presumably reflecting greater neural efficiency in more intelligent individuals (Haier, Siegel, Tang, Abel, & Buchsbaum, 1992).
A similar general phenomenon appears to emerge as children develop through adolescence and into adulthood.
As adolescents mature, prefrontal activity becomes progressively more focal and specialized, suggesting greater
neural efficiency with development (Brown et al., 2005;
Durston et al., 2006; Tamm, Menon, & Reiss, 2002). At
present, it is not known whether the development of the
emotional and social skills making up EQ is associated
with a similar change in neural efficiency.
To better understand the neurobiology of EQ during
adolescent development, we used functional magnetic
resonance imaging (fMRI) to study whole-brain activity
during a fearful-face perception task known to activate
regions of the brain involved in emotional processing in
adolescents and adults (Baird et al., 1999; Killgore &
Yurgelun-Todd, 2001). Brain activity during this task was
correlated in a voxelwise manner with scores on a wellvalidated and standardized measure of EQ for children
and adolescents (Bar-On & Parker, 2000). On the basis of
the neural efficiency hypothesis, we predicted that higher
EQ scores in adolescents would be negatively correlated
with neural activity within the somatic marker circuitry,
including the ventromedial prefrontal cortex, amygdala,
and insula, during fear perception. We also performed
whole-brain exploratory analysis to determine whether
there were other, nonhypothesized regions that might also
be associated with EQ in adolescents.
Sixteen healthy right-handed children (9 of them male, 7 female)
participated in the present study by completing an EQ scale and undergoing f MRI. The ages of these children ranged from 8 to 15 years
(M 11.6, SD 2.1), in order to capture the period most consistent
with the emergence of adolescent developmental changes. Fifteen of
the subjects were right-handed, according to self-report. Although
we have previously reported data from this sample as it relates to
different behavioral measures (Killgore & Yurgelun-Todd, 2005,
2006), the present EQ findings are novel and have not been reported
elsewhere. The children were free of any history of psychiatric or
neurologic illnesses, on the basis of a structured clinical interview
by a trained psychometric technician, using the Kiddie-Schedule
for Affective Disorders and Schizophrenia (K-SADS). All the subjects had normal visual acuity (or corrected to normal with contact
lenses). The subjects were recruited by advertisements in newspapers within the local community of Belmont, MA. The procedures
and potential risks of the study were explained to all of the children
and their parents, and written informed consent was obtained prior
to participation. Each subject received a small financial compensation for his or her time.
Emotional Intelligence Scale
Several hours prior to the f MRI session, the adolescent children
were administered the Bar-On Emotional Quotient Inventory, Youth
Version (EQ-i:YV; Bar-On & Parker, 2000). The EQ-i:YV is an
easily administered self-report inventory that yields scores on five
primary dimensions derived from the Bar-On model of EQ and a
global total score of EQ (Bar-On & Parker, 2000). These scales and
subscales include intrapersonal, interpersonal, adaptability, stress
management, and general mood, as well as a total EQ score. According to the test manual, the intrapersonal scale measures the child’s
awareness of his or her own feelings and the ability to understand,
express, and communicate effectively about his or her feelings and
needs. On the other hand, the interpersonal scale measures the capacities of the child to engage in satisfying social and interpersonal
relationships, including empathy, social responsibility, and other
social-emotional skills that serve to maintain human relationships.
The adaptability scale measures the ability of the child to respond
flexibly to changing circumstances and situations by engaging in
effective problem solving, emotional adaptation, and effective emotional reality testing. The inventory also includes a stress management scale, which measures the child’s ability to withstand difficult
and stressful situations by using positive coping skills and the ability
to control emotions and impulsive behaviors. The EQ-i:YV also includes a scale that measures general mood, a construct that includes
the tendency to maintain a positive and optimistic perspective, to
enjoy oneself and others, and to generally maintain a happy and satisfied approach to life. Finally, the inventory provides an overall
assessment of EQ, the total EQ score. Total EQ is a global indication of a child’s emotional and social intelligence abilities based on
the domains discussed previously. According to the manual, high
scorers on total EQ are typically happy and highly effective at proactively engaging most of life’s emotional and social demands (Bar-On
& Parker, 2000). The EQ-i:YV consists of 60 self-report questions
(e.g., “I usually know how other people are feeling”), each of which
is answered on a 4-point Likert-type scale with the following response options: very seldom true of me, seldom true of me, often
true of me, and very often true of me. For the present study, raw
scores on each of the six scales were transformed into age-scaled
T scores according to the published normative data provided in the
test manual. The EQ-i:YV was completed on the same day that the
children completed the functional neuroimaging scans.
The EQ-i:YV was normed on a North American sample of 9,172
children and adolescents ranging in age from 7 to 18 years, with a
mean age nearly identical to that of the present sample for males
(M 11.6 years) and females (M 11.7 years; Bar-On & Parker,
2000). According to the normative data presented in the test manual,
the internal consistency of the scales ranges from a low of .65 (interpersonal scale) to a high of .90 (total EQ, stress management, and
general mood), with an average Cronbach’s coefficient of ( .84,
suggesting good-to-high internal consistency reliability (Bar-On &
Parker, 2000). Three-week test–retest reliability estimates are also
provided for a sample of 60 children. These coefficients ranged from
.77 (general mood) to .89 (total EQ). The Bar-On model of EQ has
been validated in a number of studies for both the adolescent and the
adult scales, and these two scales are moderately to highly correlated
in older adolescents. In adults, the EQ-i has shown good convergent
and discriminant validity, assessing a broad range of emotional and
personality constructs (Bar-On, 1997; Dawda & Hart, 2000). For the
adolescent version, the test manual reports that the factorial structure of the inventory in a sample of 9,172 children closely matched
major EQ scales (Bar-On & Parker, 2000). Construct validity was
supported by the expected pattern of convergent and discriminant
correlations with scales of the NEO-Five Factor Inventory (Costa
& McCrae, 1992) in a sample of 102 adolescents, as well as with
several scales of internalizing and externalizing problem behavior
(Bar-On & Parker, 2000). A recent study also demonstrated that the
EQ-i:YV was significantly predictive of parent-reported child behavior problems and other emotional difficulties (Shuler, 2005).
fMRI Stimulation Paradigms
After completion of the EQ-i:YV, the children underwent a series
of f MRI scans. During functional scanning, the adolescents viewed
a series of six photographs of faces expressing the emotion of fear
(Ekman & Friesen, 1976). The face stimuli were back-projected
via a magnetically shielded LCD video projector onto a translucent
screen placed at the foot of the scanning table. The stimuli were
easily viewed from a mirror mounted to the head coil. The stimuli
were presented during five alternating 30-sec stimulus/rest periods,
yielding a 150-sec scanning session. During the baseline and rest intervals, a small white circle appeared in the center of the screen, and
the children were told simply to maintain their gaze on the circle.
During each 30-sec stimulation period, three different photographs
of faces expressing fear were displayed sequentially for 9.5 sec each,
separated by a 0.5-sec interstimulus interval. In order to ensure that
the children attended to the stimuli, they were informed that they
would be quizzed after the end of each scan regarding the types of
emotions they had seen.
Neuroimaging Methods
At the outset of each functional scan, three dummy images were
taken to reduce nonsteady-state effects, followed by acquisition of 50
echoplanar images over 150 sec. Functional images were acquired
using a 1.5 Tesla GE LX MRI scanner equipped with a quadrature
RF head coil (TR 3 sec, TE 40 msec, flip angle 90º). Head
motion was minimized by placing secure but comfortable foam padding around the head. A tape strap across the forehead was also applied as a tactile reminder to the child to remain still. Functional images were acquired over 20 coronal slices (7 mm; 1-mm gap), with a
20-cm field of view and a 64 64 acquisition matrix. This provided
an in-plane resolution of 3.125 7 3.125 mm. We also obtained
matched T1-weighted high-resolution images for every child at the
beginning of each scanning session.
Image Processing
Functional imaging data were preprocessed and statistically analyzed in SPM99 (Friston et al., 1995). Initially, the fun…
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