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

Copyright 2017 Rachana Sachin Agarwal

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

10

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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