1) The study examined the relationship between individual variation in emotional responses to visual stimuli and neuropsychological performance and brain structure in 26 older normal subjects.
2) Subjects who experienced negative emotions more intensely performed relatively worse on tests of executive function like the Wisconsin Card Sorting Test. Those who experienced positive emotions more intensely performed relatively worse on the Rey Complex Figure Test assessing visual-spatial skills.
3) Volume of frontal lobe gray matter was not significantly associated with intensity of emotional responses, possibly due to lack of variation in this educated sample. Differences in executive function were associated with variation in emotional experience.
Dr. William Allan Kritsonis earned his BA in 1969 from Central Washington University, Ellensburg, Washington. In 1971, he earned his M.Ed. from Seattle Pacific University. In 1976, he earned his PhD from the University of Iowa. In 1981, he was a Visiting Scholar at Teachers College, Columbia University, New York, and in 1987 was a Visiting Scholar at Stanford University, Palo Alto, California.
Dr. William Allan Kritsonis earned his BA in 1969 from Central Washington University, Ellensburg, Washington. In 1971, he earned his M.Ed. from Seattle Pacific University. In 1976, he earned his PhD from the University of Iowa. In 1981, he was a Visiting Scholar at Teachers College, Columbia University, New York, and in 1987 was a Visiting Scholar at Stanford University, Palo Alto, California.
This study aimed to assess the nature of stress, and
coping styles among rural and urban adolescents. Methods: 200
students in 10+2 and graduation first year of both genders in the
age range of 16-19 years were assessed with the Adolescent Stress
Scale, and a self-report coping scale. Results: The Result of
present study reveals that in both environmental settings male
reported more stress than their counterparts girls, however, to
utilize coping strategies female adolescents are in higher in
number than male adolescents. Conclusions: It is important for
research to examine how adolescents suffering from typical
stressors such as school examination, family conflict and poor
peer relations. Social support is likely one of the most important
resources in their coping process.
This study aimed to assess the nature of stress, and
coping styles among rural and urban adolescents. Methods: 200
students in 10+2 and graduation first year of both genders in the
age range of 16-19 years were assessed with the Adolescent Stress
Scale, and a self-report coping scale. Results: The Result of
present study reveals that in both environmental settings male
reported more stress than their counterparts girls, however, to
utilize coping strategies female adolescents are in higher in
number than male adolescents. Conclusions: It is important for
research to examine how adolescents suffering from typical
stressors such as school examination, family conflict and poor
peer relations. Social support is likely one of the most important
resources in their coping process.
Actividade experimental realizada em 2007 com o objectivo de determinar a qualidade da água do Rio Febros (afluente do Douro) comparando os resultados obtidos com os valores máximos admissíveis e recomendadas para águas superficiais. O estudo analisa amostras recolhidas em dois pontos distintos.
O R I G I N A L P A P E RSelf-Reported Depressive Symptoms.docxhopeaustin33688
O R I G I N A L P A P E R
Self-Reported Depressive Symptoms Have Minimal Effect
on Executive Functioning Performance in Children
and Adolescents
Benjamin D. Hill • Danielle M. Ploetz •
Judith R. O’Jile • Mary Bodzy • Karen A. Holler •
Martin L. Rohling
Published online: 9 May 2012
� Springer Science+Business Media, LLC 2012
Abstract The relation between mood and executive
functioning in children and adolescents has not been previ-
ously reported. This study examined the association between
self-reported depressive symptoms in both clinical outpa-
tient and psychiatric inpatient samples to the following
measures of executive functioning: the Controlled Oral
Word Association Test, Animal Naming, Trail Making Test,
and Wisconsin Card Sorting Test. Records from children and
adolescents aged 7–17 years old with an IQ [ 70 were
examined. Data were gathered at either an outpatient neu-
ropsychology clinic (n = 89) or an inpatient psychiatric
hospital setting (n = 81). Mood was measured with the
Children’s Depression Inventory. Generally, statistical
associations between self-reported depressive symptoms and
executive functioning were small and non-significant. The
variance predicted by mood on measures of executive
functioning was minimal (generally less than 2 %) for the
total sample, the outpatient group, inpatient group, and a
subgroup who endorsed elevated mood symptoms. These
results suggest that impaired performance on measures of
executive functioning in children and adolescents is mini-
mally related to self-reported depressive symptoms.
Keywords Executive functioning � Mood � Depression �
Cognitive ability � Neuropsychological assessment
Introduction
There is a long standing debate that has generated a con-
siderable amount of research in adults concerning the
relationship between levels of emotional disturbance and
their effects on performance on standard neuropsycholog-
ical tests. It appears that when the literature is taken as a
whole, adults diagnosed with psychiatric disorders tend to
perform worse than individuals without diagnoses (Basso
and Bornstein 1999; Cassens et al. 1990; Kindermann and
Brown 1997; Sackeim et al. 1992; Sherman et al. 2000;
Sweet et al. 1992; Tancer et al. 1990; Veiel 1997).
Depression, the most common mood disorder, is generally
associated with dysfunctional memory performance in the
adult literature (Burt et al. 1995; Christensen et al. 1997).
However, adult studies have shown conflicting patterns of
results across other neuropsychological domains. Some
researchers have reported depression to also be associated
with executive dysfunction (McDermott and Ebmeier
2009; Reppermund et al. 2007; Merriam et al. 1999; Martin
et al. 1991). However, others studies have reported no
effect of depression on executive functioning (Castaneda
et al. 2008; Miller et al. 1991; Rohling et al. 2002, Markela-
Lerenc et al. 2006).
While many different adult populations have been
.
Emotions are subjective feelings related to mood and affect. Emotions are biologically basic, present at birth, and universally experi- enced, but can be shaped by culture and learn- ing.
Desires and Decisions - A look into how positive emotions influence decision ...Shiva Kakkar
In the past few years the field of emotions has increasingly attracted the attention of researchers. A major reason for this is the ability of emotions to influence human motivation and actions by influencing the cognitive processes of the brain (Latham, 2007). Research by Kahneman and Tversky (1973) has for long suggested that not all human decisions are rational in nature. A significant part of irrational decision making can be attributed to the play of emotions in human beings. Thus, it is interesting to see how emotions interfere with the thinking process of individuals. The paper specifically attempts to view the effect of positive emotions i.e. feeling of happiness, joy and/or enthusiasm on the decision making process in human beings. In order to achieve this, two opposite scientific views in the form of a critique and a refutation are presented to understand the utility of positive emotions in decision making.
The Reduction of Anxiety on the Ability to Make DecisionsAbbie Frank
A research study I had done in my Cognition psychology class to look at the reduction of anxiety using yoga and animal assisted therapy and the affects they can have on decision making.
Emotion
Unpacking Cognitive Reappraisal: Goals, Tactics, and
Outcomes
Kateri McRae, Bethany Ciesielski, and James J. Gross
Online First Publication, December 12, 2011. doi: 10.1037/a0026351
CITATION
McRae, K., Ciesielski, B., & Gross, J. J. (2011, December 12). Unpacking Cognitive
Reappraisal: Goals, Tactics, and Outcomes. Emotion. Advance online publication. doi:
10.1037/a0026351
Unpacking Cognitive Reappraisal: Goals, Tactics, and Outcomes
Kateri McRae and Bethany Ciesielski
University of Denver
James J. Gross
Stanford University
Studies of emotion regulation typically contrast two or more strategies (e.g., reappraisal vs. suppression)
and ignore variation within each strategy. To address such variation, we focused on cognitive reappraisal
and considered the effects of goals (i.e., what people are trying to achieve) and tactics (i.e., what
people actually do) on outcomes (i.e., how affective responses change). To examine goals, we randomly
assigned participants to either increase positive emotion or decrease negative emotion to a negative
stimulus. To examine tactics, we categorized participants’ reports of how they reappraised. To examine
reappraisal outcomes, we measured experience and electrodermal responding. Findings indicated that (a)
the goal of increasing positive emotion led to greater increases in positive affect and smaller decreases
in skin conductance than the goal of decreasing negative emotion, and (b) use of the reality challenge
tactic was associated with smaller increases in positive affect during reappraisal. These findings suggest
that reappraisal can be implemented in the service of different emotion goals, using different tactics. Such
differences are associated with different outcomes, and they should be considered in future research and
applied attempts to maximize reappraisal success.
Researchers have identified many types of emotion regulation
strategies (e.g., cognitive reappraisal, expressive suppression;
Gross & Thompson, 2007). Contrasting these strategies has led to
important insights about differences among emotion regulatory
processes (Dillon, Ritchey, Johnson, & LaBar, 2007; Goldin,
McRae, Ramel, & Gross, 2008; Gross, 1998; Hayes et al., 2010;
Sheppes & Meiran, 2007) but has deemphasized the variability that
exists within any given strategy, such as those occasioned by
differing goals (i.e., what people are trying to achieve) or tactics
(i.e., what people actually do).
One promising target for examining within-strategy variation is
cognitive reappraisal, which refers to altering emotions by chang-
ing the way one thinks. Successful reappraisal influences many
aspects of emotional responding, including self-reported negative
affect (Gross, 1998), peripheral physiology (Jackson, Malmstadt,
Larson, & Davidson, 2000; Ray, McRae, Ochsner, & Gross, 2010),
and neural indicators of emotional arousal (Hajcak & Nieuwen-
huis, 2006; Ochsner et al., 2004; Urry et al., 2006). However, there
has been notable va ...
Sadder and Less Accurate False Memory for NegativeMaterial .docxrtodd599
Sadder and Less Accurate? False Memory for Negative
Material in Depression
Jutta Joormann
University of Miami
Bethany A. Teachman
University of Virginia
Ian H. Gotlib
Stanford University
Previous research has demonstrated that induced sad mood is associated with increased accuracy of recall
in certain memory tasks; the effects of clinical depression, however, are likely to be quite different. The
authors used the Deese-Roediger-McDermott paradigm to examine the impact of clinical depression on
erroneous recall of neutral and/or emotional stimuli. Specifically, they presented Deese-Roediger-
McDermott lists that were highly associated with negative, neutral, or positive lures and compared
participants diagnosed with major depressive disorder and nondepressed control participants on the
accuracy of their recall of presented material and their false recall of never-presented lures. Compared
with control participants, major depressive disorder participants recalled fewer words that had been
previously presented but were more likely to falsely recall negative lures; there were no differences
between major depressive disorder and control participants in false recall of positive or neutral lures.
These findings indicate that depression is associated with false memories of negative material.
Keywords: depression, memory, cognition, emotion, bias
Mood states and emotions affect memory in various ways.
Mood-induction studies, for example, have demonstrated that neg-
ative affect is associated with increased accuracy in retrieval
(Storbeck & Clore, 2005), whereas positive mood states are asso-
ciated with decreases in processing capacity (Mackie & Worth,
1989) and reduced processing motivation (Wegener & Petty,
1994), resulting in less accurate recall (Ruder & Bless, 2003). At
the same time, research on mood-congruency suggests that affec-
tive states increase the accessibility of mood-congruent material
(Bower, 1981). Understanding this complex interaction of mood
and memory is important, given its critical role in emotion regu-
lation and emotional disorders.
Individual differences in mood-congruent memory and in the
accessibility of mood-incongruent material have been proposed to
predict the ability to regulate negative mood states (Joormann &
Siemer, 2004; Joormann, Siemer, & Gotlib, 2007). Indeed, depres-
sion, by definition a disorder characterized by difficulty regulating
negative mood states, is associated with two distinct but related
memory impairments.
First, difficulties in cognitive control (i.e., focal attention to
relevant stimuli and inhibition of irrelevant material) result in
memory deficits for nonemotional material (Burt, Zembar, &
Niederehe, 1995; Hertel, 2004). In a series of studies, Hertel and
her collaborators (Hertel, 1998; Hertel & Rude, 1991) presented
evidence indicating that depression-related impairments are not
observed in all components of memory but are found primarily in
free-recall tasks and in other unstructu.
The Undoing Effect of Positive Emotions: A Meta-Analytic ReviewMaciej Behnke
The undoing hypothesis proposes that positive emotions serve to undo sympathetic arousal related to negative emotions and stress. However, a recent qualitative review challenged the undoing effect by presenting conflicting results. To address this issue quantitatively, we conducted a meta-analytic review of 16 studies (N=1,220; 72 effect sizes) measuring sympathetic recovery during elicited positive emotions and neutral conditions. Findings indicated that in most cases, positive emotions did not speed sympathetic recovery compared to neutral conditions. However, when a composite index of cardiovascular reactivity was used, undoing effects were evident. Our findings suggest the need for further work on the functions of positive emotions.
Sadder and Less Accurate False Memory for NegativeMaterial .docxlillie234567
Sadder and Less Accurate? False Memory for Negative
Material in Depression
Jutta Joormann
University of Miami
Bethany A. Teachman
University of Virginia
Ian H. Gotlib
Stanford University
Previous research has demonstrated that induced sad mood is associated with increased accuracy of recall
in certain memory tasks; the effects of clinical depression, however, are likely to be quite different. The
authors used the Deese-Roediger-McDermott paradigm to examine the impact of clinical depression on
erroneous recall of neutral and/or emotional stimuli. Specifically, they presented Deese-Roediger-
McDermott lists that were highly associated with negative, neutral, or positive lures and compared
participants diagnosed with major depressive disorder and nondepressed control participants on the
accuracy of their recall of presented material and their false recall of never-presented lures. Compared
with control participants, major depressive disorder participants recalled fewer words that had been
previously presented but were more likely to falsely recall negative lures; there were no differences
between major depressive disorder and control participants in false recall of positive or neutral lures.
These findings indicate that depression is associated with false memories of negative material.
Keywords: depression, memory, cognition, emotion, bias
Mood states and emotions affect memory in various ways.
Mood-induction studies, for example, have demonstrated that neg-
ative affect is associated with increased accuracy in retrieval
(Storbeck & Clore, 2005), whereas positive mood states are asso-
ciated with decreases in processing capacity (Mackie & Worth,
1989) and reduced processing motivation (Wegener & Petty,
1994), resulting in less accurate recall (Ruder & Bless, 2003). At
the same time, research on mood-congruency suggests that affec-
tive states increase the accessibility of mood-congruent material
(Bower, 1981). Understanding this complex interaction of mood
and memory is important, given its critical role in emotion regu-
lation and emotional disorders.
Individual differences in mood-congruent memory and in the
accessibility of mood-incongruent material have been proposed to
predict the ability to regulate negative mood states (Joormann &
Siemer, 2004; Joormann, Siemer, & Gotlib, 2007). Indeed, depres-
sion, by definition a disorder characterized by difficulty regulating
negative mood states, is associated with two distinct but related
memory impairments.
First, difficulties in cognitive control (i.e., focal attention to
relevant stimuli and inhibition of irrelevant material) result in
memory deficits for nonemotional material (Burt, Zembar, &
Niederehe, 1995; Hertel, 2004). In a series of studies, Hertel and
her collaborators (Hertel, 1998; Hertel & Rude, 1991) presented
evidence indicating that depression-related impairments are not
observed in all components of memory but are found primarily in
free-recall tasks and in other unstructu.
Sadder and Less Accurate False Memory for NegativeMaterial .docx
nihms31308
1. Neuropsychological Correlates of Normal Variation in Emotional
Response to Visual Stimuli
Robert G. Robinson, MD, Sergio Paradiso, MD, PhD, Romina Mizrahi, MD, Jess G.
Fiedorowicz, MD, Dimitrios E. Kouzoukas, BS, and David J. Moser, PhD
University of Iowa, Department of Psychiatry, Roy J. and Lucille A. Carver College of Medicine, Iowa
City, Iowa.
Abstract
Although the neural substrates of induced emotion have been the focus of numerous investigations,
the factors related to individual variation in emotional experience have rarely been investigated in
older adults. Twenty-six older normal subjects (mean age, 54) were shown color slides to elicit
emotions of sadness, fear, or happiness and asked to rate the intensity of their emotional responses.
Subjects who experienced negative emotion most intensely showed relative impairment on every
aspect of the Wisconsin Card Sorting Test. Intense positive emotion was associated with relatively
impaired performance on the Rey Complex Figure Test. The volume of frontal brain structures,
however, was not associated with emotion responses. Hemisphere-specific executive dysfunction
was associated with greater intensity of emotional experience in normal older subjects. The role of
these differences in intensity of induced emotion and impairment in executive function in daily social
and vocational activity should be investigated.
Keywords
Emotion; induced mood; neuropsychological tests; Wisconsin Card Sorting test; Rey Complex
Figure Test
Interindividual differences in response to emotion may contribute to the variability of findings
in emotional activation studies, yet have received little attention. Some subjects clearly
experience particular emotions more intensely than others, even when the intensity of
activation is held constant. Study of these individual differences may elucidate the underlying
mechanisms of psychological processes and cognitive function (Canli, 2004).
For instance in late life, two fundamental processes may affect emotion processing and
experience in different and opposite directions: (1) the acquisition of “emotional wisdom”
leading to an ability to manipulate and control extreme emotions (Dougherty et al., 1996;
Magai et al., 2001), and (2) functional and structural changes in areas regulating emotional
processing including the frontal cortex (Cowell et al., 1994; Kemper, 1993, 1994; Raz et al.,
1997, 2000) and medial temporal structures including the hippocampus and amygdala
(Geinisman et al., 1995; Kemper, 1994; West, 1993). The interplay of these phenomena may
lead to greater variability of emotional regulation in older adults. Two block design fMRI
studies exploring differences in perception of facial emotion in older adults confirmed the
reduced functioning in the amygdala, hippocampal, and frontal networks posited in the above
model (Gunning-Dixon et al., 2003; Iidaka et al., 2002).
Send reprint requests to: Robert G. Robinson, MD, Department of Psychiatry, University of Iowa, 200 Hawkins Dr, Iowa City, IA 52242..
NIH Public Access
Author Manuscript
J Nerv Ment Dis. Author manuscript; available in PMC 2007 November 30.
Published in final edited form as:
J Nerv Ment Dis. 2007 February ; 195(2): 112–118.
NIH-PAAuthorManuscriptNIH-PAAuthorManuscriptNIH-PAAuthorManuscript
2. The personality dimensions of neuroticism and extraversion may also influence emotional
reactivity (Mobbs et al., 2005). Neuroticism is associated with a proclivity to experience strong
negative emotions, whereas extraversion reflects an inclination for more positive emotions
(DeNeve and Cooper, 1998). These dimensions may also be influenced by functional and
structural pathology as evidenced by personality changes incurred in patients with
demyelinating disease or surgery (Benedict et al., 2001; Smith et al., 1976).
Understanding the neural basis of interindividual emotional variability has great significance
both heuristically and to help elucidate the specific presentation of emotional disorders. The
present study was undertaken to parse out the complex array of determinants of emotional
reactivity among the elderly by examining neurocognitive and brain structure correlates of
interindividual variation in emotional response to identical stimuli. Specifically, we examined
the extent to which relatively left and right hemisphere–dominant neuropsychological tests of
executive function may be associated with the intensity of emotional response and frontal lobe
structure.
We hypothesized that relatively weaker performance in tests of frontal lobe function, or
differences in gray matter volume of the orbital frontal cortex, would be associated with the
degree of emotional response.
METHODS
Subjects
Subjects were older healthy volunteers (mean age, 54) who were the controls for a larger study
of focal ischemic lesions and emotion induction (Paradiso et al., 2003). A total of 26 normal
subjects provided written informed consented to participate in this study approved by the
Institutional Review Board (see Table 1 for background characteristics). Volunteers were
excluded if they had a history of mental retardation, severe learning disability, dementia, stroke,
head trauma or other brain injury, physical illness that was life-threatening or interfered with
their daily activities, psychiatric disorder, or substance abuse, or were taking any psychotropic
medications. They were recruited using newspaper advertisements and were paid for
participation.
Psychiatric and Neuropsychological Assessment
Depressive symptoms were measured using the 17-item Hamilton Depression Scale, which
ranges from 0 to 55, with higher scores indicating more severe depressive symptoms (Hamilton,
1960). Anxiety symptoms were measured by the Hamilton Anxiety Scale, which ranges from
0 to 25, with higher scores indicating more severe anxiety symptoms (Hamilton, 1959). These
scales were selected to determine whether anxiety or depression may have interfered with
emotion induction. Other instruments administered were the Structured Clinical Interview for
DSM-IV Diagnosis (American Psychiatric Association, 1994; Spitzer et al., 1995) and the
semistructured Present State Examination (Wing et al., 1977) to ensure that the controls did
not have a psychiatric disorder. The structured interview data are reported as total scores
indicating overall severity of psychopathology. Also, the Social Functioning Examination
(Starr et al., 1983) was administered to assess subjects’ satisfaction with their social
functioning, and the Social Ties Checklist (Robinson et al., 1983) to measure subjects’ social
connectedness. These measures were used to document normal levels of social support. The
Toronto Alexithymia Scale (Taylor et al., 1992) was administered to measure subjects’
awareness of their feelings and ability to describe them. A score of ≤60 is considered normal
ability to experience and report emotion.
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3. The neuropsychological assessment included the Wechsler Adult Intelligence Scale—Revised
(Wechsler, 1997) assessing overall intelligence, the Wisconsin Card Sorting Test (Heaton et
al., 1993) assessing subjects’ ability to formulate, test, and alter problem-solving strategies in
response to external feedback, and the Rey Complex Figure Test (Osterrieth, 1944; Rey,
1941, measuring visuospatial ability, visuospatial memory, and executive function.
Additionally, the Controlled Word Association Test (Benton, 1968; Benton et al., 1994)
assessed verbal initiation and maintenance of effort.
The Wisconsin Card Sorting Test, 64-card administration, was selected as a measure of frontal
executive function mediated primarily by the left hemisphere (Berman and Weinberger,
1990); (Deicken et al., 1995). The Rey Complex Figure Test was selected as a measure of
executive visual spatial and organizational strategies as well as executive function mediated
primarily by the right hemisphere (Grossman et al., 1993; Savage et al., 1999.
All psychopathological and neuropsychological tests were administered in a standardized
manner by a trained research assistant several hours before the emotional activation so there
was no interference of induced emotion with cognitive performance or psychopathology.
Emotional Activation
Emotional activation tasks consisted of displaying still pictures on a video screen containing
exclusively nonfamiliar human faces or objects/scenes. These stimuli were chosen from the
International Affective Picture System, a large database of emotionally evocative color pictures
(Lang et al., 1995). Subjects were exposed to seven different sets of stimuli prepared for
inducing neutral emotion (two), happiness (two), sadness (one), or fear/disgust (two). There
were 18 images per stimulus set that were displayed individually for 6 seconds (108 seconds
total per stimulus set). All sets of stimuli were equivalent based on a large normative database
of responses of normal subjects for both mean valence of emotion and mean intensity of
emotion for each picture (Lang et al., 1995). Thus, across each 18 picture stimulus, we were
able to equate both valence and intensity of happiness, sadness, and fear/disgust. The list of
stimuli and the detailed protocol have been described in a prior publication (Paradiso et al.,
2003).
Prior to viewing each set, subjects were told they would be watching pictures with emotional
content and should allow the pictures to influence their emotional state. Subjects had not seen
the images prior to the experiment. Each set of stimuli was shown once in a random order, on
an 11-inch by 8-inch computer monitor positioned 14 inches from the subject. After the
stimulation of each emotion, subjects were asked to rate their feelings, which were assumed
to be dimensional in nature (of happiness and amusement [positive emotions], sadness, fear/
disgust [negative emotions], anger and surprise [other emotions]), using analogue scales
ranging from 0 to 10 (i.e., the analogue scale was a straight line 10 cm long in which subjects
rated intensity by crossing the line, and the score was the number of centimeters from the “not
at all” end). Mean positive and negative emotional responses were calculated. The mean
negative emotion rating consisted of mean scores on sadness and fear following two fear stimuli
(i.e., one with faces, the other without) and one sadness stimulus. The positive responses were
based on mean responses of happiness following the two happy stimuli (i.e., one with and the
other without faces). The responses on anger and surprise were not used in this study because
they did not correspond to the emotion intended to be evoked with the stimuli.
MRI Imaging Acquisition and Processing
T1-weighted and PD and T2-weighted images were acquired using contiguous coronal slices
(1.5 mm thick) from a 1.5 tesla GE Signa Scanner. The brain imaging studies were done before
the emotional activation and neuropsychological assessment. Technical parameters for T1-
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4. weighted images included 1.5-mm slice thickness, SPGR sequence, flip angle = 40°, TE = 5
milliseconds, TR = 24 milliseconds, NEX = 2. The T2-weighted images were 3.0-mm or 4.0-
mm coronal slices with 96 milliseconds TE, 3000 TR, 1 NEX, echo train length 8.
MRI images were analyzed with locally developed software (BRAINS; Andreasen et al.,
1994, 1996; Arndt et al., 1996). All brains were realigned parallel to the anterior-posterior
commissure line and interhemispheric fissure to ensure comparability of head position across
subjects. Alignment also placed the images in standard Talairach space (Talairach and
Tournous, 1988). Images from multiple subjects were coregistered and resliced in three
orthogonal planes to produce a three-dimensional data set that was used for visualization and
measurement of anatomical brain structures. Structural frontal lobe analysis was done for each
individual subject with locally developed parcellation methods (Crespo-Facorro et al., 1999).
This method used a combination of hand-tracing and automated gray-white matter distinction
to calculate the volume of gray matter in the frontal lobe in each hemisphere. The frontal lobe
structures included the superior, middle, and inferior frontal gyrus, the straight gyrus, the orbital
frontal cortex, and the rostral anterior and caudal anterior cingulate.
Data Analysis
Emotional responses obtained from neutral and emotional activation states and neurocognitive
performance were analyzed using Spearman rank correlational analysis. Structural brain
imaging data was analyzed using the volume of gray matter for each frontal lobe structure and
emotional responses.
RESULTS
Background characteristics, psychiatric assessment, and emotion responses are detailed in
Table 1. There were no significant correlations across the 26 total subjects between positive
or negative emotion responses and age, sex, handedness, race, education, or socioeconomic
status (albeit older age showed a modest nonsignificant association with higher emotional
response to positive stimuli; Table 1). Similarly, there was no significant correlation between
emotional reactivity and depression, anxiety, or overall psychopathology (Structured Clinical
Interview for DSM-IV Diagnosis, Present State Examination) and social functioning or
emotional awareness. Positive and negative responses, however, were significantly correlated
with each other. Subjects who experienced negative emotion more intensely also tended to
experience positive emotion more intensely (ρ = 0.603, p = 0.001).
Neuropsychological Test Findings
Correlations between negative emotion responses and Wisconsin Card Sorting Test were
significant for virtually all measures, except nonperseverative errors (Table 2; Figure 1). In
contrast, there were no significant correlations between intensity of positive emotion and
performance on Wisconsin Card Sorting Test. Positive emotion responses, however, were
significantly correlated with Rey Complex Figure Test copying and delayed recall subtests
(Table 2). No other correlations between emotional response and cognitive measures, including
general intelligence and attention, were found to be significant.
Structural Imaging Analysis
The structural magnetic resonance analysis correlating gray matter volumes of the superior,
middle, and inferior frontal gyrus, orbitofrontal cortex and straight gyrus, rostral and caudal
anterior cingulate with positive and negative emotional responses revealed no significant
associations (Table 3). The Spearman rho correlation coefficients ranged from 0.2 to −.03.
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5. DISCUSSION
This study examined the relationship between intensity of emotional experience following
visual stimulation, cognitive function, and frontal lobe gray matter volumes. We hypothesized
that there would be a relationship between intensity of subjective experience of emotion and
executive functioning, and gray matter volume of the frontal gyri. Subjects with relatively
weaker frontal-executive function as evidenced by poorer performance on the Wisconsin Card
Sorting Test showed greater intensity of negative but not positive emotions. Persons with higher
levels of positive emotion showed relative impairment in frontal visual-spatial organizational
strategies and memory as measured by the Rey Complex Figure Test. Surprisingly, no
correlation between emotional responses and gray matter volumes was found to be significant.
Before discussion of these results, we need to acknowledge the limitations of this study. The
population studied was generally of high average intelligence and had a mean of almost 15
years of education. Thus, our findings may not be applicable to less intelligent or less educated
populations. However, it is worth noting that significant emotion/executive function
associations were found despite the relative homogeneity of our sample. We did not examine
whether subjects who experienced more intense emotion manifested any behavioral or
personality characteristics that may have impaired their social or vocational function. However,
we did not find any association between higher emotional reactivity and measures of
psychopathology or self-reported social adjustment and ties. In addition, we only used one
method for stimulating emotion (i.e., visual). However, this method of inducing emotion is the
most highly standardized for both valence and intensity across different types of emotion, and
is a commonly used means of emotional induction (Larson et al., 2005).
The notable finding of this study was that presumably normal variations in the experience of
both positive and negative emotion were significantly correlated with relatively weaker
neurocognitive executive performance subserved by frontal lobe structures. Consistent with
prior studies reporting biological (both biochemical and genetic) influences on normal
variations in personality (Benjamin et al., 1996; Ebstein et al., 1996; Johnson et al., 1999), our
findings support the assumption that normal variation of emotional response is a dimensional
characteristic.
We were unable to find significant associations between frontal lobe gray matter and emotional
response. Age-related changes in prefrontal cortex occur early in some older persons (Raz et
al., 1997) with changes in the ventral aspect observed as early as age 58 (Convit et al., 2001).
Perhaps, in our sample, which showed high mean intelligence and education, there was not
sufficient frontal lobe gray matter variation to detect structural/emotional associations. It is
also possible that other structural brain changes (e.g., white matter hyperintensities) may
correlate more strongly with emotional responses. We are planning to perform these analyses
in future studies.
The major question arising from our findings is why relative left hemisphere–dominant frontal
dysfunction on neuropsychological testing (i.e., Wisconsin Card Sorting Test) was associated
with greater experience of negative emotion, and relative right hemisphere frontal/temporal
visual organizational dysfunction (i.e., Rey Complex Figure Test) with greater experience of
positive emotion. Although the explanation for these phenomena will require further
experimental investigation, there are several possible mechanisms which might be proposed.
The fact that more intense negative emotional induction was associated with relative left frontal
neuropsychological dysfunction and more intense positive emotion with relative right frontal-
parietal-temporal neuropsychological dysfunction suggest that left hemisphere dysfunction
may be related to more intense negative emotion and right hemisphere dysfunction may be
related to more intense positive emotion. Although a topic of scientific controversy, there is a
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6. large literature supporting the hypothesis that limbic or limbic connected structures of the right
hemisphere subserve negative emotions while similar structures of the left hemisphere subserve
positive emotion (Borod, 1992; Davidson and Irwin, 1999). In the present study, impaired
performance on the Wisconsin Card Sorting Test relative to high average general intelligence
might suggest relatively greater left than right frontal dysfunction because the Wisconsin Card
Sorting Test requires left hemisphere–dominant verbal mediation (Berman and Weinberger,
1990). Impaired left frontal function might be manifested by enhanced expression of right
frontal hemisphere activity (i.e., decreased interhemispheric inhibition and therefore increased
sensitivity to negative emotion).
Similarly, relative right hemisphere weakness in executive and visual-spatial function
measured with the Rey Complex Figure Test (Grossman et al., 1993; Savage et al., 1999) may
lead to enhanced expression of the left frontal lobe, and thus greater experience of positive
emotion.
Alternatively, more intense induction of negative emotions may be a marker for neuroticism
(Costa and McCrae, 1980; DeNeve and Cooper, 1998). Neuroticism has been described as
“cognitive noise” associated with executive dysfunction and increased variability in response
and reaction time (Robinson and Tamir, 2005), which may be reflected in the results of the
Wisconsin Card Sorting Test. Furthermore, the induction of positive affect is thought to
improve cognitive flexibility and reduce perseveration (Dreisbach and Goschke, 2004).
Perhaps this occurs in subjects with more active left hemisphere dominance leading to right
hemisphere inhibition and impaired performance on the Rey Complex Figure Test. Further
studies of this phenomenon may elucidate the mechanisms of the interplay between cognitive
performance and intensity of emotion.
Another possible explanation for our findings involves attentional differences. It has been
shown that differences on the Emotional Awareness Scale (i.e., a measure of individual
differences in the capacity to experience emotion) correlate with individual differences in blood
flow in the anterior cingulate cortex (Lane et al., 1998). The anterior cingulate also mediates
subjects’ attention or response selection (Lane et al., 1998). Thus, subjects with less intense
experience of emotion may simply have paid less attention to the emotion inducing pictures.
Although this might be proposed as a possible explanation for our findings, the fact that the
Wisconsin Card Sorting Test and the Rey Complex Figure Test but not the tasks of verbal or
performance IQ were associated with greater intensity of emotion suggests that our findings
may not be due to intersubject attentional differences. This could be tested by correlation of
emotional activation with measures of attention such as digit span.
CONCLUSION
The findings in this study emphasize the need to account for variations in emotional experience
even among normal control populations. These variations may hide or heighten group
differences when compared with patient samples. For instance, control groups containing
unusually large number of patients with “relative” right or left hemisphere dysfunction and
elevated sensitivity to positive or negative emotion might obscure or inflate differences
between controls and patients with clinical mood disorders. These subjects with more intense
emotional responses may additionally experience impairment of social or vocational function
because of these mood changes or the associated underlying relative neuropsychological
impairment.
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10. FIGURE 1.
Ratings of negative emotive stimuli versus Wisconsin Card Sorting Test perseverative errors.
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Robinson et al. Page 11TABLE1
DimensionalAnalysesofBackgroundCharacteristics,PsychiatricAssessmentScores,andEmotionResponses
NegativeEmotionSpearman’sPositiveEmotionSpearman’s
SDor(%)rho/Fprho/Fp
Demographics
Age(mean)5416.30.0420.8380.3780.057
Sex(#)female1765.4%F2.120.163F2.430.137
Handedness(#)right1973.1%F0.800.464F0.250.779
Race(#)Caucasian2492.3%F0.370.550F0.090.771
SES(#)ClassIII–V1869.2%F1.380.281F1.840.176
Education(meany)15.13.4−0.0650.754−0.0620.764
MeanSD
Psychiatricassessment
SCID84.16.3−0.1460.476−0.1100.593
PSE3.22.3−0.0880.6680.0340.870
Ham-A6.34.3−0.1610.4310.0320.878
Ham-D4.33.4−0.1580.442−0.2410.236
SFE0.0660.075−0.0830.688−0.2870.155
STC2.71.20.0610.7670.0940.649
TAS-R46.811.8−0.0290.889−0.2910.149
Emotionresponses
NRstoneutralstimulation0.80.90.6750.00020.6800.0001
NRstonegativestimulation6.12.3——0.6030.001
PRstoneutralstimulation3.92.30.4940.0100.5910.001
PRstopositivestimulation7.41.80.6030.001——
HAM-A,HamiltonAnxietyScale;HAM-D,HamiltonDepressionScale;NR,negativeresponse;PR,positiveresponse;PSE,PresentStateExamination;SCID,StructuredClinicalInterviewforDSM-
IV;SES,socioeconomicstatus;SFE,SocialFunctioningExam;STC,SocialTiesChecklist;TAS-R,TorontoAlexithymiaScale—Revised.
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Robinson et al. Page 12TABLE2
DescriptivesandSpearman'sCorrelationsofEmotionResponsesVersusNeuropsychologicalMeasures
NegativeEmotionSpearman’sPositiveEmotionSpearman’s
NeuropsychologicalTestsbyDomainMeanSDrhoprhop
Handedness
EdinburghHandednessInventory61.855.30.0650.758−0.1800.389
Attention
WAIS-R:DigitSpanACSS10.11.890.0670.7140.0360.868
GeneralIntellectualFunctioning
WAIS-R:VIQ105.213.4−0.2180.2960.0610.772
WAIS-R:PIQ115.615.3−0.0850.687−0.0510.808
WAIS-R:FSIQ110.615.2−0.1830.382−0.0140.949
Visuospatialandperceptual
RCFT:copyrawscore29.75.6−0.2650.200−0.6570.000
RCFT:immediaterecallrawscore15.65.3−0.2160.300−0.3610.077
RCFT:delayedrecallrawscore14.75.8−0.2150.302−0.4460.025
Frontalexecutivefunction
COWAT:totalsum(listgeneration—C/F/L)34.610.9−0.2400.247−0.0370.862
WCST:categories3.51.4−0.5800.002−0.1950.350
WCST:correct48.89.6−0.4680.018−0.1280.543
WCST:errors15.29.60.4510.0240.1220.562
WCST:perseverations8.26.00.5170.0080.1480.480
WCST:perseverativeerrors7.85.20.5150.0080.1460.485
WCST:nonperseverativeerrors7.44.90.3340.1020.0090.965
ACSS,Age-correctedscaledscores;COWAT,ControlledOralWordAssociationTest;FSIQ,Full-ScaleIntelligenceQuotient;PIQ,PerformanceIntelligenceQuotient;RCFT,ReyComplexFigure
Test;VIQ,VerbalIntelligenceQuotient;WAIS-R,WechslerAdultIntelligenceScale—Revised;WCST,WisconsinCardSortingTest.SignificantSpearmanrhopvaluesaredenotedbyboldcase.
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Robinson et al. Page 13TABLE3
RelationshipBetweenEmotionResponsesandFrontalLobeROIGreyMatterVolumes
NegativeEmotionSpearman’sPositiveEmotionSpearman’s
MeanSDrhoprhop
Leftfrontalstructures
SFG21.6024.4550.1970.3340.1120.587
MFG19.6863.7510.0980.6330.1490.468
IFG12.3623.0260.0960.640−0.0100.960
OFC17.4152.182−0.0450.8260.2090.306
rAC6.3662.804−0.2170.288−0.2540.211
cAC6.6821.456−0.2600.199−0.0150.942
SG2.5360.5920.0800.6990.3770.057
Rightfrontalstructures
SFG23.5064.7830.0330.8740.1470.475
MFG20.3624.6640.1090.5960.2220.276
IFG12.5502.636−0.2330.252−0.2750.174
OFC17.1662.2940.1360.5090.1570.445
rAC6.7472.500−0.0330.872−0.3090.125
cAC7.1771.213−0.2310.256−0.1220.551
SG2.6590.7380.1510.4620.2660.189
cAC,Caudal-anteriorcingulate;IFG,inferiorfrontalgyrus;MFG,middlefrontalgyrus;OFC,orbitofrontalcortex;rAC,rostral-anteriorcingulate;ROI,regionofinterest;SFG,superiorfrontalgyrus;
SG,straightgyrus.
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