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Frontal and PosteriorAsymmetry in Female Youth WithBorderline Personality Disorder
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Frontal and Posterior Asymmetry in Female Youth
with Borderline Personality Disorder
Rachana Sachin Agarwal
A Thesis in the Field of Clinical Psychology
for the Degree of Master of Liberal Arts in Extension Studies
Harvard University
November 2017
Abstract Objective: This study aimed to identify pathophysiological markers of borderline
personality disorder (BPD) using electroencephalogram (EEG). More specifically, it
examined whether female youth diagnosed with BPD exhibited more frontal or posterior
alpha asymmetry relative to healthy youth. Presently, there is limited EEG data on alpha
asymmetry in youth with BPD. This study hypothesized that female youth diagnosed
with BPD would exhibit greater frontal asymmetry compared to healthy youth. In
keeping with this initial hypothesis, it was expected that greater frontal alpha asymmetry
in youth with BPD would be associated with greater BPD severity and rumination.
Finally, this study also explored posterior asymmetry in the BPD and healthy samples.
Method: Female youth diagnosed with BPD (n = 33) were recruited from McLean
Hospital’s 3East residential program and healthy controls (n=35) were recruited from the
greater Boston community. Both samples were aged 13 to 23 years. Data regarding
psychiatric conditions were obtained through clinical interviews and self-report measures,
and resting eyes closed EEG data were acquired using a 128-channel high density net.
Analyses focused on total alpha (8-13 Hz), alpha 1 (8.5-10 Hz), and alpha 2 (10.5-12 Hz).
Correlations among all study variables were analyzed, and t-tests comparing differences
among alpha asymmetry between BPD and healthy youth were conducted.
Results: In contrast to the hypothesis, there were no significant frontal alpha asymmetry
differences among healthy and BPD youth. Exploratory analyses, however, found that
posterior asymmetry in the alpha 2 band was greater in the BPD relative to the healthy
adolescents [t(65) = 2.04, p = .046].
iv
Conclusions: These findings suggest that alpha posterior asymmetry may be a potential
pathophysiological marker of BPD.
v
Acknowledgements
This thesis was possible in large part because of Randy Auerbach’s outstanding
mentorship. As Director of the Child and Adolescent Mood Disorders Laboratory at
McLean Hospital-Harvard Medical School, Randy welcomed me into his laboratory as a
student visitor in May 2014. Under his kind guidance, I was introduced to several
members affiliated with his laboratory and from whom I learned different research
methods. First, Randy introduced me to Alexis Whitton, who devotedly taught me how to
administer the Structured Clinical Interview for DSM-IV and greatly expanded my
growing understanding of the discipline of clinical psychology. Randy then graciously
agreed to be my advisor for this master’s thesis and taught me the fundamentals of EEG
as a method for data acquisition. His support never wavered despite the challenges I
faced in learning this new technique. He remained patient and gracious despite my initial
errors. He was always attentive to my needs as a student and I felt tremendously fortunate
in knowing that I could always turn to him for any assistance. I grew to rely on quite a
few of his team members, especially, Erin Bondy, Erika Esposito, Angela Pisoni and
Naomi Tarlow, at different times during my training. Each of them kindly entertained my
many questions and was always approachable and willing to help.
At the Harvard Extension School, I benefitted appreciably from the thoughtful
feedback I received from Dante Spetter on my thesis proposal. Her detailed comments
pushed me to think deeper and improve upon my work. While I learned much from many
faculty members during the coursework stage, two professors in particular, William
Milberg and Shelley Carson, greatly enhanced my knowledge and understanding of
vi
psychology. Milberg’s course on the neuroanatomy of psychological function remains the
most stimulating and engrossing course I have ever taken. His passion and expertize as a
professor in the classroom was rivaled only by his generosity and constant
encouragement to question and think critically. Similarly, Carson’s lectures proved to be
some of the most engaging ones I had the privilege of taking and significantly enhanced
my interest in the field of psychology.
Finally, I would like to acknowledge the role my spouse, Sachin Agarwal, has
played in supporting me tirelessly throughout my academic endeavors. Without him,
none of this would have been possible.
To all of you, thank you.
vii
Table of Contents
Acknowledgements………………………………………………………………………..v
List of Tables……………………………………………………………………………..ix
List of Figures……………………………………………………………………………..x
I. Introduction……………………………………………………………………………..1
Borderline Personality Disorder…………………………………………………..3
Assessment………………………………………………………………………...9
Electroencephalogram……………………………………………………………..9
Frontal and Posterior Asymmetry………………………………………………..12
Study Aims & Hypotheses……………………………………………………….14
Significance………………………………………………………………………15
II. Method………………………………………………………………………………..17
Participants………………………………………………………………………17
Procedure………………………………………………………………………...17
Instruments……………………………………………………………………….20
Electroencephalogram……………………………………………………………21
Data Analytic Overview…………………………………………………………22
III. Results……………………………………………………………………………..…23
Preliminary Analyses………………………………………………………….…23
Frontal Asymmetry………………………………………………………………23
Posterior Asymmetry……………………………………………………….……24
IV. Discussion……………………………………………………………………………29
viii
Limitations……………………………………………………………………….31
Implications and Future Directions………………………………………………31
References………………………………………………………………………………..34
ix
List of Tables
Table 1 Demographic characteristics for the study sample……………..………..18
Table 2 Comorbidity for youth with borderline personality disorder………….....19
Table 3 Correlations among alpha asymmetry, BPD symptoms, and rumination in
healthy adolescents…………………………………………………..…..25
Table 4 Correlations among alpha asymmetries, BPD symptoms and rumination in
youth with BPD………………………………………….………………26
x
List of Figures
Figure 1 Layout illustrating the approximate 10-10 equivalent on the 128-channel
Hydrocel GSN……………………………………………………………10
Figure 2 Mean Frontal Asymmetry…………………..………...……………….....27
Figure 3 Mean Posterior Asymmetry…………………...………………………....28
1
Chapter I
Introduction
Borderline personality disorder (BPD) is a mental disorder characterized by
emotional lability, unstable relationships, impulsivity, and self-destructive behavior. The
prevalence rate within the United States is 1% (Lenzenweger, Lane, Loranger, & Kessler,
2007) with typical onset in late adolescence (Paris, 2014). Approximately 11% of
outpatients (Chanen, Jackson, McGorry, Allot, Clarkson, et al., 2004) and 43-49% of
inpatients (Levy, Becker, Grilo, Mattanah, Garnet, et al., 1999) reported a BPD diagnosis
(Sharp & Fonagy, 2015), and comorbidity with other mental disorders is common
(Zimmerman & Mattia, 1999; Yoshimatsu & Palmer, 2014; Hooley, Cole, & Gironde,
2012).
Research shows a significant correlation between self-injury and BPD (Dulit,
Fyer, Leon, Brodsky, & Frances, 1994; Nock, Joiner, Gordon, Lloyd-Richardson, &
Prinstein, 2006). BPD also has been identified as a major risk factor for suicide, with
patients reporting more than 3 lifetime attempts on average (Soloff, Lis, Kelly, Cornelius,
& Ulrich, 1994). A longitudinal study revealed that a BPD diagnosis prospectively
predicted suicide attempts in adults (Yen, Shea, Pagano, Sanislow, Grilo, et al., 2003).
Compared to other mental disorders, adolescents with BPD report suicide ideation at
earlier ages and with greater frequency (Venta, Ross, Schatte, & Sharp, 2012).
Presently, the pathophysiology of BPD is not well understood, and
electroencephalogram (EEG) offers a non-invasive approach to study neural activity in
2
relation to mental illness. EEG records scalp-recorded brain electrical activity in the form
of wave oscillations. It provides excellent temporal resolution, as data reflect ongoing
neural activity in the milliseconds (ms) range but poor spatial resolution (Luck, 2014).
Temporal resolution means that EEG allows for the recording of neural activity
continuously as it occurs. In contrast, other neural data recording methods, such as
functional magnetic resonance imaging (fMRI), is slower relative to EEG as it depends
on blood flow and may take 3 to 5 seconds to record neural activity (Glover, 2011). On
the other hand, fMRI can tell us what parts of the brain are differentially activated in
response to stimuli, that is, it has better spatial resolution, whereas EEG measures neural
activity across the scalp and so the source of neural activity is poor. However, different
wave patterns may emerge in different disorders so EEG may allow us to objectively
determine whether a particular disorder, such as, BPD, may be characterized by a wave
pattern that is distinct from other mental disorders.
One of the frequency bands recorded by EEG is the alpha band (8-13Hz), a slow
wave usually generated at the back of the head and typically associated with drowsiness,
fatigue, or closed eyes. When greater alpha is observed in one hemisphere in relation to
the other in the frontal region, it is referred to as frontal asymmetry (Davidson, 1993).
Frontal asymmetry is associated with neural deficits related to approach or avoidance
tendencies. Paradoxically, greater alpha activity is believed to reflect reduced neural
activation, such that when generated in the left frontal lobe it indicates reduced positive
affect. Research on frontal asymmetry and emotion shows that positive affect and
approach related behavior is associated with greater activation (i.e. lower alpha power) of
the left frontal lobe (Pizzagalli, Sherwood, Henriques, & Davidson, 2005), whereas
3
negative affect and avoidance related behavior is associated with greater activation of the
right frontal lobe (i.e., higher alpha power) (Davidson, Schwartz, Saron, Bennett, &
Goleman, 1979). Therefore, greater alpha power in the left frontal lobe would be
indicative of reduced cortical activity, and past research has shown that relatively reduced
left frontal asymmetry is present in individuals at-risk for depression, currently depressed
individuals, and adults with remitted depression (Auerbach, Stewart, Stanton, Mueller, &
Pizzagalli, 2015; Schaffer, Davidson, & Saron, 1983; Davidson, 1993; Gotlib,
Ranganath, & Rosenfeld, 1998; Tomarken et al., 2004). Although frontal asymmetry is
well explored in the context of depression, less research has tested whether frontal
asymmetry is observed in people with BPD.
Along with frontal asymmetry, posterior asymmetry has also emerged as a
potential pathophysiological marker of depression, such that subjects with current or
remitted depressive disorder have shown right posterior hypoactivation (indicated by
greater alpha power) (Bruder et al., 1997; Henriques & Davidson, 1990; Kentgen et al.,
2000; Stewart et al., 2011). However, there is lack of research examining posterior
asymmetry in BPD. Therefore, both frontal and posterior asymmetries in BPD remain to
be investigated. Towards addressing this important research gap, this study tests whether
female youth diagnosed with BPD exhibit frontal or posterior alpha asymmetry relative to
healthy youth.
Borderline Personality Disorder (BPD)
In 1980, personality disorder (PD) was formally recognized as a distinct category
of mental illness (Cloninger, 2007). A personality disorder refers to a pervasive,
4
inflexible pattern of behavior that endures over a period of time and causes considerable
distress or functional impairment in cognitive, affective, or interpersonal domains
(Butcher, Hooley, Mineka, 2014). In the DSM-5 (American Psychiatric Association,
2013), personality disorders are divided into three clusters: Cluster A includes three
personality disorders that are characterized by odd or unusual behavior; Cluster B
includes 4 personality disorders that involve emotional, dramatic or erratic behavioral
tendencies; and finally, Cluster C includes 3 personality disorders that are marked by
fearfulness or anxiety. Borderline personality disorder is subsumed in Cluster B.
In comparison to other personality disorders, borderline personality disorder is
more prevalent, however, important questions remain about its etiology and treatment
(Bradley, Conklin & Western, 2007). The term “borderline” was first coined by Adolph
Stern (1938) to denote a state between neurosis and psychosis. Many believe that the
term “borderline” is unclear and problematic because it does not operationalize the
specific “borders” (Hooley, Cole & Gironde, 2012). In contrast, the World Health
Organization’s (WHO) International Classification of Diseases (ICD-10) refers to BPD
as “emotionally unstable disorder”, which, some contend, more accurately conveys the
core features of the disorder (WHO, 1992; Hooley, Cole & Gironde, 2012).
Otto Kernberg has emerged as one of the most influential figures in the
construction of borderline personality (Kernberg, 1967). He held that the behavior of
people with borderline personality organization (BPO) was characterized by impulsivity
and emotional instability. Although this differed from psychosis, people with BPO
displayed more cognitive disorganization, especially when under duress. He suggested
that BPO individuals exhibited unstable views of the self and of others and developed
5
dichotomous perceptions of people as absolutely good or absolutely bad. Similarly,
Gunderson and Singer (1975) identified six features that characterize BPD: intense
negative affect, impulsive behavior, some degree of social adaptation (e.g.,
manipulative), psychotic episodes, odd responses to unstructured tests, and unstable
interpersonal relationships. As the construct of BPD evolved over the decades, diagnostic
criteria were set and BPD was incorporated as an Axis II personality disorder in DSM-III
(American Psychiatric Association, 1980; Bradley, Conklin & Western, 2007).
Presently, the DSM-5 (American Psychiatric Association, 2013) stipulates that
BPD is diagnosed if a person has at least 5 of the following 9 symptoms: (i) frantic
efforts to avoid real or imagined abandonment; (ii) a pattern of unstable and intense
interpersonal relationships characterized by alternating between extremes of idealization
and devaluation; (iii) identity disturbance: markedly and persistently unstable self-image
or sense of self; (iv) impulsivity in at least 2 areas that are potentially self-damaging (e.g.,
spending, sex, substance abuse, reckless driving, binge eating); (v) recurrent suicidal
behavior, gestures, or threats, or self-mutilating behavior; (vi) affective instability due to
a marked reactivity of mood (e.g., intense episodic dysphoria, irritability, or anxiety
usually lasting a few hours and only rarely more than a few days); (vii) chronic feelings
of emptiness; (viii) inappropriate, intense anger or difficulty controlling anger (e.g.,
frequent displays of temper, constant anger, recurrent physical fights); (ix) transient,
stress-related paranoid ideation or severe dissociative symptoms (American Psychiatric
Association, 2013).
The DSM-5 (American Psychiatric Association, 2013) and the proposed
International Classification of Diseases, 11th Revision, recently extended the diagnosis of
6
BPD to adolescent populations (Kaess et al., 2014). Historically, mental health
professionals have been reluctant to diagnose BPD in adolescents for fear of
stigmatization and because of the challenge in distinguishing BPD symptoms from
normal developmental features common to adolescence (Meijer, Goedhart, & Treffers,
1998; Miller, Muehlenkamp, & Jacobson, 2008; Sharp & Tackett, 2014). At the same
time, and perhaps unintentionally, the difficulty of disentangling BPD symptoms from
commonly observed adolescent characteristics has hampered efforts for early detection,
prevention, and timely intervention (Miller, Muehlenkamp, & Jacobson, 2008; Kaess et
al., 2014; Sharp & Tackett, 2014; Chanen, 2015).
Part of the problem in diagnosing adolescents with BPD also emerges from
establishing a stable BPD diagnosis in a population that is experiencing ongoing
developmental changes. For example, within a Dutch sample, a diagnosis of BPD among
adolescents was found not to be stable; in fact, only 2 of the 14 adolescents initially
diagnosed with BPD using the diagnostic interview for borderline patients (DIB) met
BPD criteria again after 3 years (Meijer, Goedhart, & Treffers, 1998). However, studies
also have shown that a diagnosis of BPD can remain stable over time (Miller,
Muehlenkamp, & Jacobson, 2008) and support for the construct validity of BPD in
adolescents is compelling (Bondurant, Greenfield, & Tse, 2004).
Longitudinal studies suggest that BPD emerges in adolescence, peaks in young
adulthood, and diminishes across the lifespan (Kaess et al., 2014). Prevalence rates
among adolescents and adults are comparable. Cumulative data suggest that for young
people, 1.4% will meet diagnostic criteria for BPD by age 16 years, and by age 22, the
prevalence rate will increase to 3.2%. Among adults, between 0.7% and 2.7% will meet
7
diagnostic criteria for BPD (Kaess et al., 2014). In clinical settings, the gender ratio for
females to males with BPD is 3:1, but no significant differences are observed in the
general population (Kaess et al., 2014).
Both genetic and psychosocial environmental factors have been implicated in the
etiology of BPD (Hooley, Cole & Gironde, 2012). Some contend that personality traits,
such as, instability and impulsivity, that are hallmarks of BPD, are heritable themselves,
which may explain to some degree the heritability of BPD (Butcher, Hooley & Mineka,
2014; Hooley, Cole & Gironde, 2012; Paris, 2007). A recent Dutch-based extended twin
study provided strong evidence for genetic rather than cultural transmission of BPD
(Distel, Rebollo-Mesa, Willemsen, Derom, Trull, et al., 2009). A sample of twins
(n=5017) and their parents, siblings and spouses were recruited for the study and BPD
features were measured using a Dutch translation of the Personality Assessment
Inventory-Borderline Features scale (PAI-BOR). Following genetic modeling, strong
evidence for genetic transmission emerged, while no evidence for shared environmental
influences was found. In contrast, retrospective studies have shown that reported adverse
childhood experiences, especially neglect from caregivers, constitute a significant risk
factor for the development of BPD (Zanarini, Williams, Lewis, Reich, Vera, et al., 1997;
Butcher, Hooley & Mineka, 2014).
At present, there is no evidence of effective pharmacological treatment for BPD
(Stoffers, Völlm, Rücker, Timmer, Huband, et al., 2010; Kaess et al., 2014). Randomized
control trials have provided evidence for the effectiveness of four psychosocial
treatments, namely: cognitive analytic therapy (CAT) (Ryle & Kerr, 2002); emotion
regulation training (ERT) (Schuppert, Giesen-Bloo, van Gemert, Wiersema, Minderaa,
8
Emmelkamp, et al., 2009); mentalization-based treatment for adolescents (MBT-A)
(Bateman & Fonagy, 2010); and, dialectical behavior therapy for adolescents (DBT-A)
(Rathus & Miller, 2002). Based on Marsha Linehan’s (1993) DBT for adults, DBT-A is
the most commonly used psychotherapeutic treatment for adolescents with BPD (Kaess
et al., 2014).
Linehan (1993) has conceptualized BPD as a disorder of emotion regulation.
Consistent with the diathesis-stress model (e.g., Monroe & Simons, 1991), this
formulation posits that BPD is a combination of emotional vulnerability and an
invalidating environment that fails to promote the development of emotion regulation
skills. Dialectical behavior therapy (DBT) emphasizes finding a balance between
acceptance and change, and developing validation, problem-solving, and communication
strategies. Suicidal tendencies are understood to be maladaptive ways of coping with
overwhelming emotional distress. Treatment is structured to address a hierarchy of
behaviors: life-threatening behaviors, therapy-interfering behaviors, behaviors that
negatively impact the quality of one’s life, and increasing effective use of behavioral
skills. DBT for adolescents (DBT-A) (Rathus & Miller, 2002) is an adaptation of
Linehan’s proposed treatment for adults with the following modifications: reducing the
number of therapy sessions to 12 weeks to ensure that adolescents perceive therapy
completion as an achievable goal; including family members in therapy sessions for skills
training and family problem solving; limiting the number of skills being taught to set
realistic targets; and, simplifying the language used in sessions. A quasi-experimental
study showed promising results with noteworthy reductions in psychiatric symptoms
(Rathus & Miller, 2002).
9
Assessment
Currently, the most widely accepted diagnostic measure for assessing BPD is the
Structured Clinical Interview for DSM-IV Personality Disorders (SCID-II). Two major
advantages of this diagnostic measure are: first, it directly addresses each DSM criteria
necessary for diagnosis; and second, it has very good psychometric properties (Huprich,
Paggeot & Samuel, 2015; Bradley, Conklin, & Western, 2007). Other diagnostic tools,
such as, the Clinical Diagnostic Interview (CDI), that rely on the clinician’s judgment of
patients’ detailed narratives, have also been developed. The reliance on clinical judgment
is a limitation to any interview-based approach, and thus, developing a
psychophysiological approach to assess BPD may provide a more objective, empirically
verifiable diagnostic measure of BPD. EEG may provide a promising means of
identifying neural markers that underlie BPD. In other words, it may help identify
whether specific wave patterns characterize BPD as well as differentiate it from other
disorders.
Electroencephalogram (EEG)
EEG reflects scalp-recorded electrical brain activity and was first studied by Hans
Berger in 1929 (Luck, 2014). The basic principle of EEG involves measuring brain
electrical activity by placing electrodes on the scalp, securing each electrode connection
using a gel or liquid, and recording the changing voltage over a period by amplifying the
signal received. The naming convention for the electrodes is based on the placement of
each electrode denoted by an alphanumeric code, as shown in the map. The letters signify
11
different lobes of the brain: F=frontal, P=parietal, T=temporal, O=occipital. There are
different electrode placement systems that ensure that electrodes placed across the scalp
are always positioned on the same cranial landmark relative to other electrodes (Jurcak,
Tsuzuki & Dan, 2007). The 10-10 system with 128 electrodes placed across the scalp
(Figure 1) was used for this research. Data are continuously recorded from each
electrode. In the current study, however, data analyses are restricted to F3/F4 and P3/P4,
which is consistent with frontal asymmetry approaches (Beeney, Levy, Gatzke-Kopp, &
Hallquist, 2014).
Compared to other neuroimaging research methods, EEG is non-invasive and less
expensive. One noteworthy advantage of EEG is its temporal sensitivity, as data are
recorded in the milliseconds range. This means that the data gathered will be reflective of
continuous neural activity—particularly important for the study of human emotion. Brain
electrical activity occurs in oscillations, and the alpha wave oscillates approximately 10
times per second (Luck, 2014). This means that each cycle of the alpha wave lasts for
approximately 100 milliseconds. As a recording tool, EEG has the capacity to measure
such a frequency. This is important because it will allow us to determine whether alpha
asymmetry is present in the BPD sample compared to the healthy controls.
Given the time resolution afforded by EEG, it is a valuable tool to probe neural
processes that characterize BPD. Resting EEG activity—probing alpha asymmetry—has
been used to identify potential biomarkers of mental illness (Coan & Allen, 2004). EEG
studies of emotion and cerebral asymmetry suggest that positive affect is associated with
greater activation of the left frontal lobe and approach related behaviors (Pizzagalli,
Sherwood, Henriques, & Davidson, 2005). Conversely, increased negative affect and
12
avoidance behaviors are associated with greater activation of the right frontal lobe
(Davidson, Schwartz, Saron, Bennett, & Goleman, 1979). In other words, research
suggests that emotion is lateralized in the brain. One of the early EEG experiments
examining this pattern involved seventeen right-handed participants who were presented
with emotionally varying stimuli and were asked to press down on a knob when they
disliked what they were shown and let up on the knob when they liked the presented
stimulus. The registered pressure changes on the knob were correlated with
simultaneously gathered frontal and parietal EEG asymmetry scores, and it was found
that positive affect was associated with relatively greater activation of the left frontal
hemisphere as compared with negative affect. In contrast, negative affect was associated
with relatively greater activation of the right frontal hemisphere compared with positive
affect. No emotion related parietal asymmetry was observed (Davidson, Schwartz, Saron,
Bennett, & Goleman, 1979).
Frontal and Posterior Asymmetry
Past research examining hemispheric asymmetry has often measured the alpha
wave band whereby greater alpha power is indicative of less cortical activity (Tomarken,
Dichter, Garber, & Simien, 2004). Therefore, greater alpha power in the left frontal
hemisphere would reflect less neural activity in this region. Left frontal hypoactivity is
considered a neurophysiological marker for vulnerability to depression (Schaffer,
Davidson, & Saron, 1983; Davidson, 1993; Gotlib, Ranganath, & Rosenfeld, 1998), and
adolescents at high risk for depression have demonstrated relative left frontal
hypoactivity on alpha band measures (Tomarken et al., 2004).
13
Building on this research, a recent study (Beeney, Levy, Gatzke-Kopp, &
Hallquist, 2014) compared frontal asymmetry and behavioral tendencies following
rejection in female adults with BPD. No baseline asymmetry differences were reported
between the healthy adults and those with BPD. However, following a rejection mood
induction, adults with BPD showed left frontal asymmetry. While promising, little is
known about pathophysiological markers in youth with BPD. Given profound
neurodevelopmental differences in younger versus older individuals, further research is
warranted.
In addition to frontal asymmetry, links between posterior asymmetry and
depression have also been investigated but findings have been mixed (Schaffer, Davidson
& Saron, 1983; Henriques & Davidson, 1990; Henriques & Davidson, 1991; Bruder,
Fong, Tenke, Leite, et al., 1997; Kentgen, Tenke, Pine, Fong, Klein, et al., 2000;
Debener, Beauducel, Nessler, Brocke, Heilemann & Kayser, 2000; Metzger, Paige,
Carson, Lasko, Paulus, et al., 2004; Stewart, Towers, Coan & Allen, 2011) For instance,
in adult samples, right posterior hypoactivation (i.e. greater alpha power) has been
reported among those with current and remitted depressive disorder (Bruder et al., 1997;
Henriques & Davidson, 1990; Stewart et al., 2011). On the other hand, significant
posterior asymmetry differences have not been found between some samples of
depressed patients and healthy controls (Henriques & Davidson, 1991; Debener et al.,
2000). Furthermore, in cases of depression with comorbid anxiety, posterior asymmetry
findings have shown to be reversed, such that right posterior hyperactivation (as opposed
to hypoactivation in depression alone) has been noted (Metzger et al., 2004)
Similarly, youth focused studies with regard to posterior asymmetry have also
14
demonstrated conflicting results. While alpha asymmetry indicative of right posterior
hypoactivation, as noted among depressed adults, has been found in a sample of female
adolescents with depression (Kentgen et al., 2000), another youth sample revealed no
such posterior asymmetry (Schaffer, Davidson & Saron, 1983). One study examining
alpha asymmetry in high-risk adolescents, who had attempted suicide, suggested that
attempters without a depressive disorder displayed greater alpha power (reduced activity)
in the left posterior hemisphere, whereas attempters with major depressive disorder did
not (Graae, Tenke, Bruder, Rotheram, Piacentini, et al., 1996). This study was the first to
examine EEG alpha asymmetry among high-risk adolescents. The sample consisted of
Hispanic females high school students from lower range socioeconomic status. The study
showed that greater alpha (less activation) in the left posterior hemisphere was related
more to suicidality rather than depression. No significant correlation was found between
alpha asymmetry and depression severity.
At present, there is no EEG research on posterior alpha asymmetry in BPD.
By examining frontal and posterior alpha asymmetry in youth with BPD, this study seeks
to identify potential neural markers of BPD.
Study Aim & Hypotheses
This study examines whether female youth diagnosed with BPD exhibit more
frontal or posterior alpha asymmetry relative to healthy youth. Specifically, three aims
and hypotheses were tested:
15
Aim 1
I hypothesized that female youth diagnosed with BPD will exhibit greater frontal
alpha asymmetry (i.e., less cortical activity in the left compared to the right hemisphere)
than females without BPD. This hypothesis is based on previous studies that have shown
a correlation between left frontal hypoactivation and depression (Schaffer, Davidson, &
Saron, 1983; Davidson, 1993; Gotlib, Ranganath, & Rosenfeld, 1998).
Aim 2
I expected that greater frontal alpha asymmetry in youth with BPD will be
associated with greater BPD severity and rumination. If frontal asymmetry emerges as a
potential correlate of BPD, as it has in the case of depression, then it may be extrapolated
that the degree of asymmetry may be correlated to the severity of BPD.
Aim 3
I also explored posterior alpha asymmetry to determine whether there is greater
asymmetry in BPD relative to healthy youth. Given the mixed findings with regards to
posterior alpha asymmetry and depression in youth (Schaffer, Davidson & Saron, 1983;
Kentgen et al., 2000), this aim was largely exploratory.
Significance
Testing frontal and posterior alpha asymmetry in BPD may reveal important
neurophysiological markers of BPD and help determine if there is a biological basis for
this disorder (Sharp & Tackett, 2014). Identifying promising biological markers may lead
16
to early identification of BPD and could provide promising targets in the development of
new interventions. Examining neural markers in youth is especially important as BPD is
often manifested in adolescence (Kaess et al., 2014). Therefore, testing frontal and
posterior asymmetry in youth is vital. In prior research, adults with BPD exhibited left
frontal asymmetry following a rejection task (Beeney, Levy, Gatzke-Kopp, & Hallquist,
2014); however, no research has tested whether frontal or posterior asymmetry is present
in youth diagnosed with BPD.
17
Chapter II
Method
Participants
The study included female youth (borderline personality disorder [BPD] = 33,
healthy controls [HC] = 35) aged 13 to 23 years. Demographic data are summarized in
Table 1. There were no between-group differences for age or ethnicity; however, BPD
participants reported a higher family income. BPD participants reported a wide range of
comorbid mental illnesses, including mood and anxiety disorders (see Table 2). Inclusion
criteria for youth included English fluency, female, and right-handedness. Exclusion
criteria for healthy participants included history of any psychiatric illness, psychotropic
medication use, organic brain syndrome, neurological disorders, and history of seizures.
BPD participants had the same exclusion criteria with the exception of psychiatric history
and psychotropic medication use.
Procedure
The Partners Institutional Review Board provided approval for the study. Assent
was obtained from female participants aged 13-17 years, and signed consent was
obtained from participants 18 years and older as well as legal guardians of minors. The
BPD sample was recruited from McLean Hospital’s 3East residential program, which
provides intensive dialectical behavioral therapy (DBT). Healthy adolescents were
recruited from the greater Boston community through flyers and online advertisements.
18
Table 1 Demographic characteristics for the study sample
Healthy BPD Statistics
(n = 35) (n = 33) t/x2
p-value
Age (SD) 18.14 (3.44) 17.21 (1.82) 1.38 0.17
BPD symptoms (SD) 0.63 (0.91) 15.36 (7.49) -11.55 <0.001
Ethnicity, n (%)
2.5 0.64
White 24 (68.57) 25 (75.76)
Asian 6 (17.14) 4 (12.12)
Multiple Races 3 (8.57) 4 (12.12)
Black 1 (2.86) 0 (0)
Other 1 (2.86) 0 (0)
Household Income, n (%)
18.09 0.003
≥ $100,000 16 (45.7) 29 (87.9)
$75,000 - $100,000 2 (5.7) 1 (3.0)
$50,000 - $75,000 6 (17.1) 0 (0)
$25,000 - $50,000 3 (8.6) 0 (0)
$10,000 - $25,000 0 (0) 1 (3.0)
<$10,000 4 (11.4) 0 (0)
Unknown/Unreported 4 (11.4) 2 (6.1) Note. BPD = Borderline Personality Disorder
19
Table 2 Comorbidity for youth with borderline personality disorder (n = 33) Comorbidity n (%)
Major Depressive Disorder/Dysthymia 24 (72.7)
Social Phobia 10 (30.3)
Attention Deficit Hyperactivity Disorder 9 (27.3)
Posttraumatic Stress Disorder 7 (21.2)
Bipolar II Disorder/ Bipolar Disorder NOS 7 (21.2)
Generalized Anxiety Disorder 6 (18.2)
Panic Disorder 6 (18.2)
Obsessive Compulsive Disorder 5 (15.2)
Agoraphobia 4 (12.1)
Specific Phobia 2 (6.1)
Psychotic Disorder 1 (3)
20
The study included two visits. On the first study visit, participants were
administered clinical interviews assessing psychiatric diagnoses, and additionally, they
completed self-report measures assessing symptom severity. For the second study visit, 8
minutes of resting EEG data were acquired using a 128-channel HydroCel GSN
Electrical Geodesics, Inc. (EGI) net. Each participant was remunerated $50.
Instruments
Mini International Neuropsychiatric Interview for Children and Adolescents
(MINI-KID; Sheehan, Sheehan, Shytle, Janavs, Bannon, Rogers, et al., 2010).
Participants were administered the MINI-KID to assess Axis I Disorders. The MINI-KID
is a brief, structured diagnostic interview that assesses current Axis I psychopathology in
youth. It has demonstrated good reliability and validity in past research (Sheehan et al.,
2010; Auerbach, Millner, Stewart, Esposito, 2015).
Structured Clinical Interview for DSM-IV Axis II Personality Disorders, BPD
module (SCID-II; First et al., 1994). The SCID-II is a semi-structured clinical interview
assessing personality disorders. For this study, the module assessing borderline
personality psychopathology was administered. Past research has shown that the BPD
module of the SCID-II possesses strong psychometric properties (Huprich, Paggeot &
Samuel, 2015; Bradley, Conklin, & Western, 2007).
Zanarini Rating Scale for Borderline Personality Disorder (ZAN-BPD; Zanarini,
Vujanovic, Parachini, Boulanger, Frankenburg, & Hennen, 2003). The ZAN-BPD is a 9-
item self-report instrument that assesses borderline personality disorder symptom
21
severity. Item scores range from 0 to 4 with greater scores indicating greater BPD
severity. Exemplar items include anger, moodiness, emptiness, identity disturbance, self-
destructive behavior, impulsivity, suspiciousness, fear of abandonment, and unstable
relationships. In the current study, the Cronbach’s alpha was 0.93, indicating strong
internal consistency.
Ruminative Response Scale (RRS; Treynor, Gonzalez, & Nolen-Hoeksema 2003).
The RRS is a 22-item self-report instrument that assesses participants’ response to
depressed mood regarding thoughts about fatigue, difficulty concentrating, motivation,
personal shortcomings, self-analysis and self-criticism, reasons for depressed mood,
preoccupation with recent events, and so on. Item scores range from 1 (almost never) to 4
(almost always). In the current study, the Cronbach’s alpha was 0.97, highlighting
excellent internal consistency.
Electroencephalogram (EEG) EEG data were acquired using a 128-channel HydroCel GSN Electrical
Geodesics, Inc. (EGI) net. Continuous EEG data was sampled at 250 Hz and referenced
online to Cz. Resting EEG data consisted of eight contiguous, 1-min segments (four eyes
open, four eyes closed). These eight segments were randomly sequenced in each
participant and the order of the segments was counterbalanced across participants.
Consistent with past research, this study included only the eyes closed data to ensure that
visual stimuli would not negatively impact findings (Auerbach et al., 2015).
The four 1-minute segments were then concatenated using Matlab 8.1
(MathWorks, Natick, USA). BrainVision Analyzer 2.04 software (Brain Products,
22
Germany) was used to perform independent component analysis to remove eye
movement artifacts and eye blinks. The acquired EEG data was analyzed using SPSS to
assess frontal asymmetry. Frontal asymmetry scores were computed by subtracting the
alpha power of left frontal electrodes (F3) from the alpha power of right frontal
electrodes (F4). Similarly, posterior alpha asymmetry scores were computed by
subtracting alpha power of P3 (left) from P4 (right). Furthermore, the alpha wave band
was divided into two ranges: alpha 1 from 8.5 to 10 Hz and alpha 2 from 10.5 to 12 Hz.
Alpha asymmetry scores were computed for alpha 1, alpha 2 and the total alpha range.
Data Analytic Overview
All data analyses were completed using SPSS. Correlations among all study
variables were tested. Additionally, t-tests compared differences in alpha asymmetry in
BPD and healthy youth. Outliers were removed for each alpha band (alpha 1, alpha 2 and
total alpha) prior to all analysis. Hence, the results reflect different degrees of freedom.
23
Chapter III
Results
Preliminary Analyses Within the BPD group, BPD symptoms were associated with rumination (r = .43, p < .05)
and reflection (r = .36, p < .05). Contrary to my hypothesis, there was no correlation
between frontal or posterior asymmetry and BPD symptoms. Within the healthy group,
there was no correlation between BPD symptoms and rumination or reflection (p > .05),
however, there was a modest correlation between BPD symptoms and depression (r =
.35, p < .05) (see Tables 3 and 4).
Frontal Asymmetry
When comparing HC and BPD participants, there was no significant difference for the
alpha 1, t(66) = -.27, p = .79, alpha 2, t(62) = -.45, p = .65, or total alpha t(64) = -.10, p =
.92 (see Figure 1). Thus, the results obtained did not support our hypothesis on frontal
asymmetry.
24
Posterior Asymmetry BPD participants exhibited greater alpha 2 asymmetry relative to HC youth, t(65) = 2.04,
p = .046 (see Figure 2). At the same time, between group comparisons were non-
significant for alpha 1, t(65) = 1.14, p = .26 and total alpha, t(65) = 1.37, p = .17. This
finding was unexpected as it was not part of my a priori hypothesis.
25
Table 3
Correlations Among Alpha Asymmetry, BPD Symptoms, and Rumination
in Healthy Adolescents (n=35)
Healthy Adolescents
1 2 3 4 5 6 7 8 9 10 11
1. Frontal Alpha 1 --
2. Frontal Alpha 2 .79** --
3. Frontal Alpha Total .95** .91** --
4. Posterior Alpha 1 -0.08 -0.09 -0.1 --
5. Posterior Alpha 2 0.18 -0.02 0.1 .49** -- 6. Posterior Alpha Total 0.09 -0.05 0 .87** .79** --
7. BPD Symptoms -0.01 0.02 0.01 -0.11 0.31 0.05 --
8. Rumination 0.24 0.03 0.18 0.18 0.29 0.31 0.29 --
9. Reflection 0.23 0.02 0.16 0.24 0.24 .36* 0.18 .92** --
10. Brooding 0.19 0.05 0.17 0.21 0.15 0.24 0.18 .86** .82** --
11. Depression 0.22 0.34 0.18 0.1 0.32 0.26 .35* .95** .76** .70** --
Note: *p < 0.05; **p < 0.01
26
Table 4
Correlations Among Alpha Asymmetries, BPD Symptoms and Rumination in Youth with
Borderline Personality Disorder (n=33)
Borderline Personality Disorder
1 2 3 4 5 6 7 8 9 10 11 1. Frontal Alpha 1 -- 2. Frontal Alpha 2 .73** -- 3. Frontal Alpha Total .93** .87** -- 4. Posterior Alpha 1 -0.12 -0.01 -0.16 -- 5. Posterior Alpha 2 -0.04 0.08 -0.06 .83** -- 6. Posterior Alpha Total -0.15 -0.04 -0.19 .96** .93** --
7. BPD Symptoms -0.17 -0.01 -0.13 0.11 0.21 0.12 --
8. Rumination -0.22 -0.31 -0.27 -0.1 -0.13 -0.11 .43* --
9. Reflection 0.05 -0.16 -0.02 -0.22 -0.24 -0.26 .36* .75** --
10. Brooding -0.21 -0.34 -0.28 -0.08 -0.17 -0.12 0.32 .85** .56** --
11. Depression -0.22 -0.24 -0.25 -0.02 -0.01 0.01 .39* .92** .48** .68** --
Note: *p < 0.05; **p < 0.01
27
Figure 2 Mean Frontal Asymmetry
-0.030
-0.020
-0.010
0.000
0.010
0.020
0.030
0.040
0.050
Alpha1 Alpha2 AlphaTotal Mea
n Fr
onta
l Asy
mm
etry
HC
BPD
28
Note. *p < 0.05 Figure 3
Mean Posterior Asymmetry
-0.050
0.000
0.050
0.100
0.150
0.200
Alpha1 Alpha2 AlphaTotal
HC
BPD *
Mea
n Po
ster
ior
Asy
mm
etry
29
Chapter IV
Discussion
Borderline personality disorder is a mental disorder characterized by a pervasive
pattern of instability in emotions, relationships, and self-image (Kaess, Brunner &
Chanen, 2014). Symptoms may include a sense of emptiness, fear of real or imagined
abandonment, impulsive, reckless, self-injurious or suicidal behavior, and psychotic or
dissociative symptoms (DSM-5, American Psychiatric Association, 2013). Onset usually
occurs in late adolescence or early adulthood and may cause significant psychosocial
impairment (Keass et al., 2014; Paris, 2014). The noted correlation between self-injury
and BPD (Dulit, Fyer, Leon, Brodsky, & Frances, 1994; Nock, Joiner, Gordon, Lloyd-
Richardson, & Prinstein, 2006) and the identification of BPD as a risk factor for suicide
(Soloff, Lis, Kelly, Cornelius, & Ulrich, 1994), make it necessary to further investigate
the underlying neural correlates of this disorder.
Towards this end, EEG offers a cost effective and non-invasive method to
examine the neurophysiological markers of BPD. Since current EEG research on BPD is
limited, this study is one of the early attempts to adopt such a methodological approach.
Thus far, one study has shown left frontal asymmetry in adults with BPD following a
rejection mood induction task (Beeney, Levy, Gatzke-Kopp, & Hallquist, 2014). Based
on this finding, as well as previous research on left frontal alpha asymmetry in depression
(Schaffer, Davidson, & Saron, 1983; Davidson, 1993; Gotlib, Ranganath, & Rosenfeld,
1998), I hypothesized that youth with BPD sample will exhibit greater frontal alpha
asymmetry than females without BPD. However, the results obtained in this study do not
30
support this. The lack of significant difference in frontal asymmetry across all alpha
bands between the BPD and healthy group is somewhat surprising. One potential
explanation may be that compared to the frontal asymmetry findings among adults with
BPD (Beeney, Levy, Gatzke-Kopp, & Hallquist, 2014), youth with BPD may not exhibit
similar frontal asymmetry. In other words, differential frontal asymmetry patterns in BPD
may be a result of age related neurodevelopmental differences.
As part of my second hypothesis, I expected to find a positive correlation between
frontal alpha asymmetry and BPD severity and rumination in youth with BPD. However,
no correlation between frontal asymmetry and BPD symptoms was found. An association
between BPD symptoms and rumination and reflection was observed in the BPD sample.
Interestingly, a modest correlation between BPD symptoms and depression was also
found in the healthy group. This finding is somewhat puzzling, as the healthy group was
not expected to display BPD or depressive symptoms, let alone a correlation between
them.
The results with regard to posterior asymmetry were most striking. Of the three
alpha bands, alpha 2 reached significance indicating greater alpha power in the left
compared to the right posterior lobe in the BPD sample. In other words, the BPD group
exhibited left posterior hypoactivation. This finding is consistent with a previous study in
which high-risk adolescents, who had attempted suicide and did not have a depressive
disorder, displayed greater alpha power (reduced activity) in the left posterior
hemisphere, whereas attempters with major depressive disorder did not (Graae, Tenke,
Bruder, Rotheram, Piacentini, et al., 1996).
31
Limitations
This study has a few noteworthy limitations. First, since EEG data was gathered
during rest, that is, when eyes are closed, the EEG asymmetry findings are not applicable
to when responding to specific types of stimuli (e.g., affective-based words, images).
Second, since EEG detects scalp-recorded activity, it cannot provide insight regarding
neural activity in subcortical structures. Third, the generalizability of the study is limited.
As the study focuses only on female youth within a specific age group, the findings may
not apply to males or older populations. Last, comorbidity limits the ability to determine
whether effects are unique to youth with BPD. Since some of the youth in the BPD
sample had comorbid depression, anxiety disorders, and other mental illnesses, it is
difficult to ascertain whether the observed posterior asymmetry is primarily due to BPD.
However, youth with BPD and comorbid depression could not be excluded to maintain
external validity.
Implications and Future Directions
This study is one of the early attempts to identify neural markers of BPD in youth
using EEG. It was based on the premise that the proposed correlation between left frontal
hypoactivation and depression (Schaffer, Davidson, & Saron, 1983; Davidson, 1993;
Gotlib, Ranganath, & Rosenfeld, 1998) may also be displayed in BPD. However, the lack
of significance in frontal alpha asymmetry in the BPD group implies that BPD and
depression may not have similar neural markers with regard to frontal alpha asymmetry.
However, more studies are needed to corroborate or contradict these findings.
The left posterior hypoactivation displayed in the BPD sample in this study poses
32
an interesting point of comparison to the right posterior hypoactivation noted in
depressed samples (Bruder et al., 1997; Henriques & Davidson, 1990). Again, this may
suggest that BPD and depression may actually have different pathophysiology, in contrast
to what was initially hypothesized.
It is striking that left posterior hypoactivation displayed in this BPD sample was
also observed in high-risk female adolescents who had attempted suicide (Graae, Tenke,
Bruder, Rotheram, Piacentini, et al., 1996). As noted earlier, BPD has been identified as a
major risk factor for suicide (Soloff, Lis, Kelly, Cornelius, & Ulrich, 1994; Yen, Shea,
Pagano, Sanislow, Grilo, et al., 2003), and adolescents diagnosed with BPD report
suicide ideation at earlier ages and with greater frequency (Venta, Ross, Schatte, &
Sharp, 2012). This may suggest that suicidal tendencies and BPD have similar
pathophysiology in youth (rather than BPD and depression). Significantly, posterior alpha
asymmetry was observed in those female suicide attempters who did not have depression;
that is, those who had depression and had attempted suicide did not display reduced left
posterior activation. Again, this points to the differences in pathophysiology between
depression, suicide and BPD. That is, BPD and suicide appear to have common neural
markers, rather than BPD and depression as initially hypothesized.
Future studies could further explore the pathophysiology of suicide and BPD to
identify correlations and differences. For instance, they may investigate whether there are
different neural markers for youth with BPD who may or may not have attempted
suicide. In other words, is left posterior hypoactivation more indicative of suicidal
tendencies rather than BPD?
In addition, future studies could also include more varied populations based on
33
gender and age to better understand the pathophysiology of BPD in a more general sense.
For instance, it may be important to test whether boys and older populations with BPD
also exhibit posterior asymmetry. Studies including more varied groups may provide a
more holistic picture of the neural markers of BPD, thereby opening new lines of inquiry
for better intervention methods.
34
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