Available online at:
https://cc.arcabc.ca/islandora/object/cc%3Apsycjournal

J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.
Submitted Fall 2021; accepted June 2022.

Biological Mechanism of Mental Illness.
Authors: Roget Hall*, Kyle Kubisheski, Julia Ming, Nataly Romero, and Elizabeth Salchert
Supervising Instructor: Michael Pollock, Psyc 215 (“Biological Psychology”)
Department of Psychology, Camosun College, 3100 Foul Bay Road, Victoria, BC, Canada V8P 5J2
*Corresponding author email: Rogetjadehall@hotmail.com

ABSTRACT
In this paper, we sought to understand the biological mechanisms of five common mental
illnesses so that we could learn about the relationship between the mind and body. Previous
research has predicted mental health challenges by variables such as
sympathetic/parasympathetic activity in obsessive-compulsive disorder, prefrontal cortex size in
borderline personality disorder, amygdala activity in depressive rumination and in generalized
anxiety disorder, and cerebellar activity in eating disorders. In our correlational study, we tested
the strength of these relationships by examining naturalistic daily changes in their variables
longitudinally over a one-week period. We measured sympathetic/parasympathetic activity by
measuring heart rate, prefrontal cortex activity by EEG, amygdala activity by increases in heart
rate after watching a scary video clip, cerebellar activity by a balance task, and measured by
questionnaires levels of obsessive-compulsion, rumination, anxiety, borderline personality, and
eating disorder. In contradiction to our predictions, data pooled across our participants showed a
significant positive correlation between heart rate and obsessive compulsive disorder symptoms
and there were no significant results in support of any of our other predicted relationships. These
results could be helpful to understanding the biological mechanisms of obsessive-compulsive
disorder. A possible practical application of these findings shows that having increased
sympathetic/parasympathetic activity indicates higher obsessive-compulsive disorder symptoms.
1. Introduction
1.1 Research Problem
Mental illness causes suffering and
affliction for many individuals worldwide.
This study will center on the relationship
between body and mind and the effects of
those suffering with Obsessive Compulsive
Disorder, Borderline Personality Disorder,
Major Depressive Disorder, Anxiety, and
Eating Disorders. Obsessive Compulsive
Disorder (OCD) causes recurring intrusive
thoughts, ideas, habits and obsessions that

influences and negatively affects different
aspects of an individual’s lives. These
thoughts manifest into actions that prevent
those inflicted from leading normal lives,
maintaining jobs, creating healthy
relationships, and are damaging to their
mental health. Borderline Personality
Disorder (BPD) influences thoughts and
behaviors causing complications in everyday
life, such as mood swings, suicidal
tendencies, fear of abandonment, and
impulsiveness. Major Depressive Disorder
(MDD) is a common mood disorder
characterized by mental and physical
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symptoms, some of which are a depressed
mood most of the day, sleep changes,
feelings of worthlessness, diminished
interest in activities and recurring thoughts
of death. MDD can greatly impair one’s
ability to function in daily life and is
associated with high mortality rates. Anxiety
involves a constant state of worry and fear.
Individuals living with anxiety may avoid
places or situations to escape the feeling,
which can interfere in many aspects of the
individual’s life, such as building and
maintaining relationships, work and school
performance, and social activities. Eating
disorders are repeated disturbances in eating
patterns, which can cause intense emotions
and frustrations as well as bodily harm.
Eating disorders can include restricting,
bingeing, and purging; they often coincide
with other disorders such as mood disorders
and substance abuse. Investigation of the
underlying biological mechanisms of these
particular mental illnesses allows for a
deeper understanding of such complex
ailments and may identify specific areas of
focus for treatment.
1.2 Literature Review
One previously found biological
mechanism of mental illness is the
relationship between the sympathetic and
parasympathetic nervous system’s activity in
OCD. For example, 70 participants
diagnosed with OCD of varying
compulsions (57 washing compulsions, 13
with checking compulsions) along with 72
control participants were part of an
experimental study by Hinds et al. (2012). In
the study participants were hooked up to an
ECG machine in order to record respiratory
sinus arrhythmia at three different intervals.
Respiratory sinus arrhythmia is used as an
objective measurement for the
parasympathetic nervous system by

measuring the variability in heart rate and
spontaneous breathing of patients. First,
participants were asked to close their eyes
for two minutes in order to create a baseline
measurement. Secondly, participants were
asked to place their hands in either a bin
with diapers or Styrofoam beads (this would
initiate the sympathetic nervous system by
making them believe they were
contaminated) for 2 minutes, after which
measurements would then be taken. Lastly
participants were told they would have 30
seconds in order to wash their hands and that
if they continued after the time limit, they
would be asked to stop then another 2minute measurement was taken. The study
concluded that participants significantly
showed no differences in their increase of
sympathetic levels but failed to show a
major decrease in their parasympathetic
nervous system levels during which they
were unable to control the need to stop their
obsessive behavior. It also found that OCD
participants with washing compulsions did
not differ significantly from the control
group with the threat of contamination
regarding their levels of initial activation.
However, the OCD participants had greater
challenges reducing their activation through
handwashing than to the control group.
Based on these results, the researchers
concluded that individuals suffering with
OCD did not have issues with the part of the
brain responsible for flight and fight, but
with the section that switches off the
compulsion after it has been completed
resulting in obsessive behavior.
Another previously found biological
mechanism of mental illness is the prefrontal
cortex in BPD. For example, in an
experimental study by Soloff et al. (2008),
participants were randomly selected with the
criteria that they were clinically diagnosed
with BPD from the DSM-III. MRI scans and
voxel-based imaging analysis were
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conducted to view brain structures of the
participants. Significant findings compared
to healthy controls were that the BPD
sample had decreased grey matter in the
prefrontal cortex (anterior cingulate gyrus),
which is the area that controls impulsivity.
There was no difference for gender when it
came to impulsivity for the BPD sample.
Based on these results, the researchers
suggested that the reduced grey matter in
both the prefrontal cortex and medial
temporal cortex influence the impulsiveness
contributing to the behaviour in BPD
patients for both males and females. The
researchers noted that mediation of
impulsive-aggression and impulsivity could
potentially be explained by reduced
connectivity in prefrontal areas of the brain.
A third previously found biological
mechanism of mental illness is trait
rumination associated with increased
sustained amygdala reactivity. For example,
35 participants with a current diagnosis of
MDD along with 29 never-depressed control
participants were part of an experimental
study by Mandell et al. (2014) aimed at
examining the relationship between trait
rumination and various cortical regions. In
this study, participants completed 17 selfreport measures of rumination and an
alternating emotion-processing and
executive-control task during a functional
Magnetic Resonance Imaging (fMRI)
assessment, as well as a measure of
depression severity. Self-report measures
were used to sample multiple aspects of
persistent negative thought patterns and
included the Emotion Control
Questionnaire-rehearsal (ECQ-REH), Scott
Macintosh Rumination Inventory-motivation
(SMRI-EMOT), etc. A task consisting of 60
emotional valence identification (VID) and
digit-sorting (DS) was conducted in
conjunction with an fMRI screening to
measure emotion-processing and cognitive

control. Through examination of empirically
defined dimensions of trait rumination and
sustained neural responses, the fMRI results
revealed correlations between depressed
participants’ rumination scores and left and
right amygdala activation. Based on these
results, the researchers suggested that
multiple types of depressive rumination are
associated with increased levels of sustained
reactivity in the amygdala.
A fourth previously found biological
mechanism of mental illness is the
relationship between abnormal emotional
and cognitive processing and amygdala
dysfunction in individuals with generalized
anxiety disorder (GAD). For example, Yang
et al. (2021) examined amygdala-based
functional connectivity (FC) in an
experimental study between 38 GAD
patients and 20 healthy individuals to further
explore the association between trait anxiety
and GAD. The study began by performing a
resting-state functional MRI using a 3-Tesla
Siemens MRI system to obtain data on the
participants. Furthermore, a Clinical Global
Impression Severity scale (CGI-S) was used
to test the severity of the relationship
between FC and trait anxiety. The scale
indicated significant differences between the
results of GAD patients and healthy
individuals. In addition, GAD patients
showed more hypoconnectivity in the left
amygdala and the left superior temporal
gyrus than in healthy individuals. The study
found amygdala-rostral anterior cingulate
cortex connectivity for GAD patients was
negatively correlated with symptom severity
and trait anxiety. In contrast, amygdalainferior frontal gyrus connectivity was
positively associated with symptom severity.
Based on these results, the researchers
suggested focusing on amygdala dysfunction
could have important implications in treating
anxiety symptoms.
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The final previously found biological
influence on mental health is the cerebellar
activity found in eating disorders. For
example, 17 patients with either Bulimia
Nervosa or Anorexia Nervosa were part of a
study by Cerasa et al. (2015) looking to see
what biomarkers could contribute to eating
disorders by using MRI scans. The MRI
scans of those with eating disorders were
compared to eighty-one healthy participants
without eating disorders. The differences
were shown mostly in the occipital cortex
and the posterior cerebellar lobule. In
addition, patients with eating disorder had
more damage to the brain regions important
for emotional processing, such as precuneus,
sensorimotor, premotor cortices, agenesis of
corpus callosum, and orbitofrontal cortex.
Based on these results, the researchers
suggested that the cerebellum could be a
contributor to eating disorders because it is
involved with other brain regions that play
an important role in motor, cognitive and
emotional functions.
1.3 Hypotheses
Based on the above literature review, we
predicted the following hypotheses:
Hypothesis #1: If activity of the
parasympathetic nervous system is increased
then the symptoms of OCD will decrease.
Hypothesis #2: If activity in the prefrontal
cortex is decreased then BPD symptoms will
increase.
Hypothesis #3: If activity in the amygdala is
increased then rumination will increase.
Hypothesis #4: If amygdala activity
increases then anxiety symptoms will
increase.
Hypothesis #5: If cerebellum activity
increases then symptoms of eating disorders
will increase.

2.1 Participants
The five authors of this paper served as
the participants in its studies. The
participants ranged in age from 19 to 29
years old college students, with an average
age of 24 years, and included gender
pronouns of he/him and she/her. The
participants were all undergraduate students
at Camosun College who completed the
current studies as an assignment for Psyc
215 (“Biological Psychology”) and were
grouped together due to their mutual interest
in biological mechanisms of mental health.
The participants (authors) all have a mutual
interest or personal experience in the subject
of mental health such as BPD, clinical
depression, substance use disorder, GAD,
OCD, and wished to gain knowledge on the
topics.
2.2 Materials and Procedures
We first performed a correlational study
to test concurrently all of our hypotheses by
examining naturalistic daily changes in their
variables longitudinally. Each participant
kept a study journal with them at all times
over this study’s one-week period in order to
record self-observations of the following 9
variables: (1) sympathetic/parasympathetic
activity, (2) prefrontal cortex activity, (3)
amygdala activity, (4) cerebellum activity,
(5), OCD, (6) BPD, (7) rumination, (8)
anxiety, and (9) eating disorders.
2.2.1 Sympathetic/Parasympathetic Activity
To measure a differential between
symptoms and heart rate, participants
measured their heart rates before taking the
OCD questionnaire each day. Increasing and
decreasing heart rate showed levels of
sympathetic and parasympathetic activity,
respectively.
2.2.2 Prefrontal Cortex Activity

2. Methods
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To measure prefrontal cortex activity
participants used the Muse 2.0 headband to
indicate prefrontal cortex activity (Muse,
2021). The Muse 2.0 Headband uses an
electroencephalography (EEG) system to
scan and record brainwaves (Kovacevic et
al., 2015). Each group member recorded
brain activity for a minute with eyes closed
everyday for a total of seven days. The
brainwaves were recorded and the data
quantified from the Muse using the Mind
Monitor App (Mind Monitor, 2021).
2.2.3 Amygdala Activity
To measure amygdala activity,
participants monitored heart rate before and
after viewing a scary video clip. The video
shown to participants was a short one minute
YouTube video with a pop-up scare at the
end (Jumpscare Zoo, 2019). Participants
measured their initial baseline heart rate by
counting their pulse rate on their wrist
before watching the video and immediately
after viewing. Each group member recorded
amygdala activity each day for a total of
seven days. The measure was completed
each day for a total of seven days to track
longitudinal changes. Longitudinal scores of
heart rate measurements are represented in a
chart (see Appendix 3).
2.2.4 Cerebellum Activity
To measure cerebellum activity,
specifically motor skills and functioning,
participants had their arms out horizontally
with palms up and eyes closed. If there was
upper body weakness relating to the
cerebellum, then the affected side would
drift within 30 seconds. To test lower
extremities, participants laid in the supine
position with knees bent at 30 degrees. The
affected leg would have drifted downward
within 30 seconds. A scale of 0-10 was
given for each participant to use (0 =
extremities drifted before 15 seconds, 5 =
extremities drifted after 30 seconds, and 10
= extremities did not drift within 1 minute /

60 seconds), and a daily total score for seven
days was noted. This method is an
examination used by practitioners at the
London Health Services Centre in the
Critical Care Centre for assessing a
conscious patient's motor skills (Morgan,
2019).
2.2.5 Obsessive-Compulsive Disorder
Each day participants filled out an OCD
symptoms questionnaire (see Appendix 1).
Participants then listed their name, the date,
and the time the questionnaire was taken.
The questionnaire measured seven different
OCD symptoms ranging from excessive
cleanliness to repetition of tasks and
movement. Levels of these symptoms were
rated on a scale from 0-10, with 0 being less
severe and 10 being more severe, and with
an overall score ranging between 0-70, 70
being the maximum score achieved.
2.2.6 Borderline Personality Disorder
To measure impulsivity (a symptom of
BPD), we used a modification of the
Zanarini Rating Scale for Borderline
Personality Disorder (ZAN-BPD), also
known as the McLean Screening for BPD,
which was developed by Dr. Mary Zanarini
at McLean Hospital Harvard Medical School
Affiliate (see Appendix B). The ZAN-BPD
questionnaire was developed to determine
the severity of and changes in BPD
symptoms as well as an indication of BPD
diagnosis (Zanarini et al., 2003). The
questionnaire had items each scored on a
scale of 0 to 10 (0 = not at all and 10 =
extremely severe) and which were summed
to produce an overall score. Questions on
the modified ZAN-BPD were for
impulsivity (spending, binging, mood),
abandonment, identity and reality
questioning.
2.2.7 Rumination
To measure rumination (a popular trait of
depressed individuals), we used the
Ruminative Response Scale (RRS) each day.
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The self-response measure, RRS
(PsyToolkit, 2021), consists of 22 questions
and a 4-point Likert scale to measure
depressive rumination. Rumination scores
were interpreted and quantified through the
psytoolkit.org website, with a possible range
of 22 to 88 points.
2.2.8 Anxiety
To measure anxiety, each participant used
the Generalized Anxiety Disorder 7 Item
Scale (GAD-7). The GAD-7 scale consisted
of seven questions that asked participants
daily to read short statements and rate their
anxiety levels by indicating whether they
felt nervous, anxious, worried, restless, and
annoyed (Psychology Tools, n.d.). The
following responses were available to the
participants: not at all, several days, over
half the days, and nearly everyday. A
numerical value was derived by the score of
the participants, 0-5 = little or no anxiety, 610 = mild anxiety levels, 11-15 = moderate
anxiety levels, and 16-21 = severe anxiety
levels (see Appendix D).
2.2.9 Eating Disorders
To measure eating disorders we used a
20-item questionnaire where each item was
measured on a scale from 0 to 10, where 0 =
not at all and 10 = extreme (See Appendix
E). Participants filled out the questionnaire
and summed their scores daily. The
questionnaire was derived from The Eating
Disorder Foundation (Questionnaire, 2021)
and is a tool used for screening eating
disorders but is not a true diagnosis.

outcome variables (OCD symptoms, BPD
symptoms, MDD symptoms, generalized
anxiety symptoms, and eating disorder
symptoms). For testing Hypothesis #1, we
correlated sympathetic/parasympathetic
activity with OCD symptoms for each of the
participants. For testing Hypothesis #2, we
correlated activity of the prefrontal cortex
with impulsivity (BPD symptoms) for each
of the participants. For testing Hypothesis
#3, we correlated amygdala activity with
MDD symptoms for each of the participants.
For testing Hypothesis #4, we correlated
amygdala activity with GAD symptoms for
each of the participants. For testing
Hypothesis #5, we correlated cerebellum
activity with eating disorder symptoms for
each of the participants. We performed all of
the above correlations separately for each
participant as well as using data pooled
across all of the participants. For the
correlations using pooled data, in addition to
using the raw data, we also performed
correlations after we had first transformed
the data from each participant into z-scores
in order to standardize differences in
averages and variability seen between the
participants in their data and thus make them
more comparable. A correlation coefficient
was considered statistically significant if the
probability of its random occurrence (p) was
< .05 (i.e., less than 5% of the time expected
by chance alone).

2.3 Planned Analyses
To assess the strength and statistical
significance of associations between
variables predicted by our five hypotheses,
we performed Pearson product moment
correlations of their predictor variables
(sympathetic/parasympathetic activity,
prefrontal cortex activity, and amygdala
activity, cerebellum activity) with their

As shown in Table 1, the
parasympathetic/sympathetic activities were
significantly correlated with OCD
symptoms, although not being statistically
significant for any individual participant (all
r ≤ 0.63, all p ≤ 0.81).
Parasympathetic/sympathetic activity was
significantly correlated using the pooled raw
data (r = 0.36, p = 0.04, see Figure 1) but

3. Results

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was not significant for the pooled
standardized raw data (r = 0.19, p = 0.27 see
Figure 2). In contrast, there was no
significant correlation between prefrontal
cortex activity and BPD for any individual
participant (all r ≤ 0.29, all p ≤ 0.97) except
for participant #2 (r = 0.95, p < 0.0003), as
well as no statistical significance for the
pooled raw data (r = -0.15, p = 0.39, see
Figure 3) and pooled standardized data (r =
23, p = 0.20, see Figure 4). There was no
significant correlation between amygdala
activity and rumination for any individual
participant (all r ≤ 0.45, all p ≤ 0.) as well as
no statistical significance for the pooled raw
data (r = 0.23, p = 0.19, see Figure 5) and
pooled standardized data (r = 0.10, p = 0.56,
see Figure 6). There was no significant
correlation between amygdala activity and
anxiety for any individual participant (all r ≤
0.71, all p ≤ 0.95) as well as for the pooled
raw data (r = 0.07, p = 0.69, see Figure 7)
and pooled standardized data (r = 0.31, p =
0.07, see Figure 8). Finally, there was no
significant correlation between cerebellum
activity and eating disorder activity for any
individual participant (all r ≤ 0.75, all p ≤
0.93) as well as for the pooled raw data (r =
0.10, p = 0.56, see Figure 9) and pooled
standardized data (r = 0.32, p = 0.06, see
Figure 10).
4. Discussion
4.1 Summary of Results
Based on previous research, we
hypothesized the biological mechanisms of 5
common mental illnesses: if the
parasympathetic nervous system increases
then obsessive-compulsive disorder
decreases (Hypothesis #1), if prefrontal
cortex activity decreases then borderline
personality symptoms will increase
(Hypothesis #2), if amygdala activity is

increased then rumination will increase
(Hypothesis #3), if amygdala activity
increases then anxiety symptoms will
increase (Hypothesis #4), and if cerebellum
activity increases then eating disorder
symptoms will increase (Hypothesis #5).
The hypotheses were not supported by
significant results.
4.2 Relation of Results to Past Research
The significant relationship found
between sympathetic/parasympathetic
activity and OCD symptoms in our study
differs from previously published work. In
Hinds et al. (2012), it was found that
participants suffering from OCD did not
have any issues with the part of the nervous
system responsible for flight or fight
(sympathetic nervous system) but instead
had a decrease in the division of the nervous
system that switches off arousal
(parasympathetic nervous system) after
compulsions have been completed . In
contrast, we found the opposite: that
increased (not decreased) heart rate was
associated with greater OCD symptoms. The
method of our study differed from that of the
Hinds et al. (2012) study in two major way
that might account for the discrepant results.
Firstly, in the Hinds et al. (2012) study they
had participants perform a task that would
initiate the sympathetic/parasympathetic
nervous system by placing their hands into
“containments” which produced a
significant result using respiratory sinus
arrhythmia measurements. Our study
differed due to measuring
sympathetic/parasympathetic activity by
recording naturalistic heart rates each day.
Secondly, Hinds et al. (2012) used
participants who were diagnosed with two
separate obsessive-compulsive disorders
(washing compulsion and checking) and a
control group. Our study used the five
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authors of this paper suffering from a range
of different mental health disorders with
only one participant who had OCD. These
differences could have affected the results
due to the small sample size and the range of
differences in mental disorders.
Based on previous research (Soloffet al.,
2008) about the biological mechanisms of
BPD, we predicted that prefrontal cortex
activity would be correlated with BPD
symptoms. Whereas the research of Soloff et
al. (2008) was performed with just
diagnosed BPD participants, only one of our
five participants had been diagnosed with
BPD and that participant’s individual results
were significant, in contrast to the rest of our
participants. The current study shows that
the relationship between prefrontal cortex
functioning and BPD symptoms only exists
for those diagnosed with BPD.
The correlational study failed to confirm
the relationship between rumination and
amygdala activity. No significant
relationship was found between participants’
scores on the Ruminative Response Scale
(RRS) and their amygdala activity. Previous
research by Mandell et al (2014) used
multiple questionnaires and an fMRI
machine to examine the relationship
between trait rumination and increased
amygdala activity. Their research was
performed with individuals who were
diagnosed with MDD and used an fMRI to
accurately measure activity levels of the
amygdala and other related cortical regions.
Our correlational study differed from that of
Mandell et al. (2014) in two ways that may
explain the different results. First, our study
used participants with a range of mental
disorders, with only one participant having
MDD. Secondly, amygdala activity was
measured by heart rate after viewing a scary
video instead of using an fMRI technique.
The results of Mandell et al. (2014) study
revealed that increased levels of sustained

reactivity in the amygdala was associated
with multiple types of depressive
rumination. The methodological differences
of measuring clinical levels of depression
and amygdala activity regarding the lack of
MDD participants and relying upon indirect
measures of amygdala activity led to
different results. For future research, other
methods of evaluating amygdala activity that
offer greater internal validity should be
applied.
Our correlational study failed to confirm
the relationship between amygdala activity
and anxiety symptoms reported by previous
research. Yang et al. (2021) found that
amygdala-inferior frontal gyrus connectivity
was associated with anxiety symptom
severity after participants were measured
with a resting-state functional MRI and the
Clinical Global Impression Severity scale
(CGI-S). In contrast, our participants did not
find that amygdala activity, measured by
heart rate activity after viewing a scary
video, was associated with their anxiety
symptoms, and measured by the Generalized
Anxiety 7 Item Scale (GAD-7). The
methodology of our correlational study
differed from that of the Yang et al. (2021)
study in two major ways that might account
for the discrepant results. First, differences
between the studies in how they measured
amygdala activity could have affected the
findings. The self-measurement of amygdala
activity could have produced different
results because it relied on the participants’
judgement to measure their heart rate before
and after watching a scary video clip each
day. Future studies should try to confirm
with functional MRI the results of Yang et
al. (2021) to see if our insignificant results
were due to relying upon indirect measures
of amygdala activity. Second, differences
between the studies in how they measured
anxiety symptoms could have affected their
findings. Our study used the five authors of
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this paper as participants, which could have
affected the results due to the small sample
size. Future experimental studies should
have a bigger sample size and compare
participants with GAD and individuals
without GAD, similar to Yang et al. 2021
study while using the GAD-7 scale.
The study by Cersasa et al. (2015)
regarding the relationship between
cerebellum activity and eating disorders
found that increased cerebellum activity
would lead to a higher likelihood of eating
disorders. Cersasa et al. (2015) used MRI
scans to look for biomarkers which could
lead to eating disorders, but they found that
high cerebellum activity corresponded with
eating disorders in their participants. Our
results were different from the results that
Cersasa et al. (2015) found and one of the
reasons why we did not get the same results
could be because we did not have the same
resources for our study. They used MRI
scans to see cerebellum activity while we
used an arm exercise, and they also had
many more participants in their study than
we did. We tested cerebellum activity
through an exercise which involved keeping
our arms straight out for one minute. The
exercise was rated out of 10 points and
points would be lost if arms waivered or
dropped. The eating disorder data was
collected through a questionnaire with 20
questions with each question being on a
scale of 1-10. Our hypothesis was that high
points on the arm exercise positively
correlated with high scores on the eating
disorder questionnaire, but our study found
that there was no significance between
cerebellum activity and eating disorders. For
future studies, it would be helpful to have a
clearer way to measure cerebellum activity
that possibly involves brain scans.
4.3 Implications of Results

Based on the current study’s findings,
increased sympathetic/parasympathetic
activity indicates higher obsessivecompulsive disorder. These results have
possible practical applications to enhance
the knowledge of the relationship between
the mind and body regarding the biological
mechanisms of individuals diagnosed with
obsessive-compulsive disorder. Since
sympathetic/parasympathetic activity were
found to be significantly correlated with
obsessive-compulsive disorder, other studies
might use these results to improve research
in treatment areas.

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47

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Table 1 - Correlations for Study Variables

Variables

Participant
#1

Participant
#2

r

n

r

n

Sympathetic/
Parasympath
etic Activity
& obsessivecompulsive
disorder

0.16

7

0.42

Prefrontal
cortex
activity &
borderline
personality
disorder

0.17

Amygdala
activity &
major
depressive
disorder

Amygdala
activity &

Participant
#3

r

Participant Participant
#4
#5

Pooled raw
data

Pooled
standardized data

n

r

n

r

n

r

n

r

n

7 -0.12

7

-0.12

7

0.63

7

*0.36

35

0.19

35

7

0.95* 9 -0.37

6

0.02

6

0.29

6

-0.15

33

0.23

33

0.14

7

-0.46

7

0.04

7

0.45

7

0.34

7

0.23

35

0.1

35

0.05

7

0.03

7

0.58

7

0.71

7

0.2

7

0.07

35

0.3

35

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generalized
anxiety
disorder

Cerebellar
activity &
eating
disorder

0.14

7

0.75

7

0.61

7

0.08

7

0.05

7

0.1

35

0.32

* p < .05.

59

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Figure 1

Association Between Sympathetic/Parasympathetic Activity and Obsessive Compulsive Disorder

Obsessive Compulsive Disorder Sypmtoms
(0-70 points)

Symptoms Using Pooled Raw Data

45
40
35
30
25
20
15
10
5
0
0

20
40
60
80
100
Sympathetic/Para Sympathetic Nervous System (BPM)

120

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Hall, Kubisheski, Ming, Romero, & Salchert - J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.

Figure 2

Association Between Sympathetic/Parasympathetic Activity and Obsessive Compulsive Disorder
Symptoms Using Pooled Standardized Data

Obsessive Compulsive Disorder Sypmtoms
(z-score)

2.5

-2.5

2
1.5
1
0.5
0
-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

-0.5

-1
-1.5
Sympathetic/Para Sympathetic Nervous System (z-score)

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Figure 3

Association Between Prefrontal Cortex Activity and Borderline Personality Disorder Symptoms
Using Pooled Raw Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Hall, Kubisheski, Ming, Romero, & Salchert - J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.

Figure 4

Association Between Prefrontal Cortex Activity and Borderline Personality Disorder Using
Pooled Standardized Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Hall, Kubisheski, Ming, Romero, & Salchert - J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.

Figure 5

Association Between Amygdala Activity and Rumination Using Pooled Raw Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Hall, Kubisheski, Ming, Romero, & Salchert - J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.

Figure 6
Association Between Amygdala Activity and Rumination Using Pooled Standardized Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Hall, Kubisheski, Ming, Romero, & Salchert - J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.

Figure 7

Association Between Amygdala Activity and Anxiety Using Pooled Raw Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Hall, Kubisheski, Ming, Romero, & Salchert - J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.

Figure 8

Association Between Amygdala Activity and Rumination Using Pooled Standardized Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Hall, Kubisheski, Ming, Romero, & Salchert - J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.

Figure 9

Association Between Cerebellum Activity and Eating Disorder Symptoms Using Pooled Raw
Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Hall, Kubisheski, Ming, Romero, & Salchert - J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.

Figure 10

Association Between Cerebellum Activity and Eating Disorder Symptoms Using Pooled
Standardized Data

Notes. Marker colour differentiates participants: red = participant #1, orange = participant #2,
yellow = participant #3, light green = participant #4, and dark green = participant #5. Some data
might not be visible in the figure due to overlapping markers.

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Hall, Kubisheski, Ming, Romero, & Salchert - J Camosun Psyc Res. (2022). Vol. 4(1), pp. 48-75.

Appendix A
OCD Symptom Scale

Obsessive Compulsive Disorder (OCD) Levels
Symptom Scale

Name:

Date:

Time:

Below record data regarding emotions and feelings pertaining to OCD symptoms.

How affected are you by these behaviours?

Levels

Excessive Cleanliness/Hygiene

0 – 1 – 2 – 3 – 4 – 5 – 6 – 7 – 8 – 9 - 10

Constant Checking and Worrying

0 – 1 – 2 – 3 – 4 – 5 – 6 – 7 – 8 – 9 - 10

Hoarding Behaviour

0 – 1 – 2 – 3 – 4 – 5 – 6 – 7 – 8 – 9 - 10

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Repetition of Tasks and Movements

0 – 1 – 2 – 3 – 4 – 5 – 6 – 7 – 8 – 9 - 10

Excessive Cleaning

0 – 1 – 2 – 3 – 4 – 5 – 6 – 7 – 8 – 9 - 10

Hard to Control Thoughts or Worry

0 – 1 – 2 – 3 – 4 – 5 – 6 – 7 – 8 – 9 - 10

Depression

0 – 1 – 2 – 3 – 4 – 5 – 6 – 7 – 8 – 9 - 10

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Appendix B
Mclean Screening for BPD

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Appendix C

Rumination Response Scale (RRS)

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Appendix D
Generalized Anxiety Disorder 7 Item Scale (GAD-7)

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Appendix E
Eating Disorder (ED) screening questionnaire

75