1. EFFECTS
OF
DIETARY
PROTEIN
AND
AEROBIC
EXERCISE
ON
FUNCTIONAL
CONNECTIVITY
IN
BRAIN
REWARD
CENTERS:
A
RESTING-‐STATE
fMRI
STUDY
By
Lexie
Buchs
A
Thesis
Submitted
in
Partial
Fulfillment
Of
the
Requirements
for
an
Undergraduate
Degree
with
Honors
(Dietetics)
The
College
of
Health
and
Human
Sciences
Purdue
University
May
2015
West
Lafayette,
Indiana
Approved
by:
Reader:
Richard
Mattes,
Ph.D.
Reader:
Tara
Henagan,
Ph.D.
___________________________________________________________________
Honors
Research
Mentor:
Wayne
Campbell,
PhD
2. 2
ABSTRACT
The
Salience
Network
(SN)
interprets
internal
and
external
stimuli
for
emotion,
homeostatic
regulation,
and
reward.
The
Default
Mode
Network
(DMN)
reflects
resting
state
brain
activity.
Previous
data
have
demonstrated
a
disruption
of
these
networks
in
obesity.
The
purpose
of
this
study
was
to
examine
the
effects
of
dietary
protein
and
aerobic
exercise
on
resting
state
activity
in
the
SN
and
DMN
using
functional
Magnetic
Resonance
Imaging
(fMRI)
in
8
women
ages
18-‐45
years
old
with
a
BMI
of
30
to
40
kg/m2.
On
testing
days,
breakfast
and
lunch
were
identical
while
dinner
meals
varied
in
protein
(Normal
Protein:
15%
vs.
High
Protein:
30%
of
energy
as
protein).
Total
energy
intake
on
testing
days
was
prescribed
at
approximately
80%
of
the
participants’
estimated
daily
energy
requirements
to
stimulate
one
day
of
moderate
energy
restriction.
Participants
completed
a
pre-‐dinner
scan
five
hours
after
lunch.
After
the
pre
dinner
scan,
subjects
either
rested
or
exercised
for
30
minutes
at
60%
of
their
estimated
VO2max.
Dinner
was
consumed
immediately
after
exercise
or
rest.
The
postprandial
fMRI
scan
was
completed
one
hour
after
dinner.
The
independent
component
analysis
did
not
reveal
a
SN
but
did
reveal
a
DMN.
However,
DMN
activity
was
not
influenced
by
meal
consumption,
acute
aerobic
exercise,
or
the
amount
of
protein
at
dinner.
Resting
state
brain
activity
may
not
be
influenced
by
acute
interventions
and
therefore
long
term
inventions
may
be
necessary
for
normalizing
resting-‐state
neural
activity
in
obese
women.
3. 3
ACKNOWLEDGEMENTS
I
would
like
to
thank
Dr.
Campbell
for
his
guidance
and
support
throughout
this
project
and
for
giving
me
many
opportunities
to
learn
about
research.
Thank
you
to
Drew
Sayer
for
patiently
mentoring
me
and
for
all
of
his
help
with
this
project.
Without
your
guidance
and
direction,
I
would
not
have
been
able
to
complete
the
honors
degree.
Thank
you
to
Greg
Tamer
for
completing
the
data
analysis
and
for
providing
his
expertise
throughout
the
study.
I
would
also
like
to
thank
the
study
participants
for
their
dedication
and
compliance
to
this
study.
This
study
was
funded
by
the
Indiana
CTSI.
4. 4
TABLE
OF
CONTENTS
Abstract
…………………………………………………………………………………………………………..…………….2
Acknowledgements
………………………………………………………………………………………..………………3
List
of
Tables
and
Figures
…………………………………………………………………………….………………...5
Introduction
………………..…………………………………………………………………………….………………......6
Subjects
and
Methods
…………………………………………………………………………..…………………..........9
Results
……………………………………………………………………………..............................................................12
Discussion
……………………………………………………………………………......................................................13
References
……………………………………………………………………………......................................................17
Appendix
…………………………………………………………………………….........................................................26
5. 5
LIST
OF
TABLES
AND
FIGURES
Table
1:
Subject
Characteristics.…………………………………………………………………………………….19
Table
2:
Dinner
(High
Protein
or
Normal
Protein)
…………………………………………………………20
Figure
1:
Study
Design
…………………………………………………………………………………….……………22
Figure
2:
Default
Mode
Network
…………………………………………………………………...………………23
Figure
3.
Pre-‐Meal
Default
Mode
Network
Activity………………………………………...……………….24
Figure
4.
1-‐Hour
Post-‐Meal
Default
Mode
Network
Activity……………………………………..……..25
6. 6
INTRODUCTION
Increased
activity
in
a
brain
region
results
in
a
locally
increased
blood
response
in
that
area
and
also
an
increased
ratio
of
oxygenated
to
deoxygenated
blood.
Functional
Magnetic
Resonance
Imaging
(fMRI)
scan
detects
the
difference
of
magnetization
in
oxygen-‐rich
versus
oxygen-‐poor
blood
[1].
The
resultant
blood
flow
response
is
detected
by
the
fMRI
scan
as
an
increase
in
the
blood-‐oxygen-‐level-‐dependent
(BOLD)
contrast,
and
this
is
used
as
a
marker
of
brain
activity.
The
human
brain
is
organized
into
networks
and
the
intrinsic
activity
of
these
networks
can
be
measured
in
the
resting
state
using
fMRI.
These
networks
are
important,
because
it
is
becoming
increasingly
evident
that
they
are
organizational
features
of
the
brain
[2].
The
Salience
Network
(SN)
and
the
Default
Mode
Network
(DMN)
are
two
networks
that
have
been
shown
to
be
associated
with
feeding
behavior.
The
DMN
consists
of
the
posterior
cingulate
cortex,
cuneus/precuneus,
medial
prefrontal
cortex,
medial
temporal
lobe,
and
inferior
parietal
cortices.
The
SN
consists
of
the
anterior
cingulate
cortex
and
insula.
The
DMN
reflects
baseline
brain
function
in
the
resting
state.
The
SN
reflects
feeding
behavior
and
reward
and
involves
assessing
internal
and
external
stimuli.
Previous
studies
have
found
activation
of
the
DMN
and
SN
to
be
increased
in
overweight
and
obese
individuals
in
comparison
to
lean
individuals
[2].
Results
from
previous
studies
have
led
to
the
idea
that
abnormal
or
increased
activation
in
these
networks
may
contribute
to
overeating,
and
there
is
also
a
correlation
between
obesity
and
activation
of
these
networks
[3].
Understanding
these
networks
in
overweight
and
obese
individuals
and
how
acute
and
long-‐term
changes
in
network
activity
are
associated
with
food
intake
7. 7
behavior
would
be
helpful
when
strategizing
how
to
normalize
network
activity
to
reduce
overeating.
Moderate
increases
in
dietary
protein
[4]
and
exercise
[13]
are
common
strategies
for
weight
control
and
therefore
may
represent
potential
interventions
for
normalizing
resting
activity
in
obese
individuals.
For
example,
a
6-‐month
exercise
intervention
decreased
resting
state
activity
in
the
DMN
although
the
intervention
did
not
change
resting
state
activity
in
the
SN
[2].
However,
the
effects
of
acute
exercise
on
the
resting
state
activity
of
the
SN
and
DMN,
or
whether
dietary
protein
modulates
resting
state
activity
of
these
networks,
have
not
been
investigated.
The
purpose
of
this
study
is
to
investigate
the
acute
effects
of
aerobic
exercise
and
dietary
protein
on
the
resting
state
activity
in
the
SN
and
DMN.
The
broad
aim
of
the
study
is
to
determine
the
acute
effects
of
dietary
protein
intake
and
aerobic
exercise
on
resting
state
activity
in
the
SN
and
DMN
of
obese
women.
Our
decision
to
include
only
obese
women
was
guided
by
previous
research
demonstrating
greater
neural
responses
to
visual
food
cues
in
obese
compared
to
healthy-‐weight
individuals
[5-‐10]
and
also
in
women
compared
to
men
[11].
We
hypothesize
that
network
resting
state
activity
will
be
decreased
1-‐hour
after
consuming
dinner
compared
to
the
pre
dinner
assessment.
We
further
hypothesized
that
a
high
protein
dinner
will
elicit
a
greater
reduction
in
resting
state
activity
compared
to
a
normal
protein
dinner.
Acute
aerobic
exercise
will
result
in
a
relatively
greater
resting
state
activity
compared
to
rest.
8. 8
The
rank
order
of
resting
state
SN
and
DMN
activity
under
all
conditions
and
time
points
is
hypothesized
to
be:
NPEx
>
NPR
>
HPEx
>
HPR
NPR:
Normal
Protein/Rest
HPR:
High
Protein/Rest
NPEx:
Normal
Protein/Exercise
HPEx:
High
Protein/Exercise
9. 9
SUBJECTS
AND
METHODS
Subjects
Potential
participants
were
recruited
from
public
advertisements
(flyers).
Study
inclusion
was
based
on
the
following
criteria:
1)
Women
ages
18-‐45
years;
2)
body
mass
index
between
(BMI)
30-‐40
km/m2;
3)
non-‐smoking;
4)
not
diabetic;
5)
not
pregnant
or
lactating;
6)
weight
stable
(±
3kg)
for
3
months;
7)
not
severely
claustrophobic;
8)
and
willing
to
eat
study
food.
Due
to
the
use
of
the
MRI
scanner,
participants
with
implanted
pacemakers
and/or
automated
defibrillators
or
any
ferromagnetic
metal
implanted
in
their
body
were
excluded
from
the
study.
There
were
41
total
contacts,
of
which
11
women
were
screened
for
inclusion
criteria.
Of
these,
9
women
were
approved
and
began
the
study.
Eight
women
completed
all
study
procedures.
The
Purdue
Biomedical
Institutional
Review
Board
approved
all
study
procedures.
All
subjects
provided
written
informed
consent
regarding
purpose,
procedures,
and
potential
risks
of
the
study.
Each
subject
received
monetary
compensation
for
participation.
Baseline
Assessments
BMI
(kg/m2)
was
determined
by
measuring
the
participants
weight
and
height.
These
measurements
were
completed
at
the
Clinical
Research
Center
at
Purdue
University.
The
YMCA
cycle
sub-‐maximal
exercise
test
was
used
to
estimate
each
participant’s
maximal
oxygen
consumption.15
10. 10
Experimental
Design
and
Procedures
The
study
consisted
of
five
testing
days
for
each
participant.
On
the
first
testing
day
the
sub-‐maximal
exercise
test
was
completed.
The
remaining
four
testing
days
were
completed
in
random
order
and
each
testing
day
was
separated
by
at
least
seven
days.
The
following
four
experimental
conditions
were
evaluated:
normal
dietary
protein
with
rest
(NPR),
high
dietary
protein
with
rest
(HPR),
normal
dietary
protein
with
exercise
(NPEx),
and
high
dietary
protein
with
exercise
(HPEx).
On
testing
days,
breakfast
and
lunch
were
consumed
in
the
metabolic
research
kitchen
and
dinner
consumed
at
the
Purdue
MRI
Facility.
Breakfast,
lunch,
and
dinner
provided
approximately
20%,
30%,
and
30%
of
the
participants
estimated
energy
requirement,
respectively.
Total
meals
provided
to
the
participants
included
approximately
80%
of
the
estimated
daily
energy
requirement
to
simulate
one
day
of
moderate
energy
restriction.
Breakfast
and
lunch
were
identical
on
all
testing
days
but
dinner
meals
varied
in
macronutrient
distribution.
The
macronutrient
distribution
of
breakfast
and
lunch
were
15%
protein,
60%
carbohydrate,
and
25%
fat.
The
normal
protein
(NP)
dinners
were
15%
protein,
60%
carbohydrate,
and
25%
fat,
while
the
high
protein
(HP)
dinner
provided
30%
of
energy
as
protein,
45%
carbohydrate,
and
25%
fat.,
(Table
2)
.
Subjects
were
blinded
to
the
protein
level
of
the
dinner
meals.
Dietary
fat
intake
was
held
constant
and
carbohydrate
intakes
adjusted
to
offset
differences
in
protein
intake
for
the
HP
and
NP
dinners.
On
two
of
the
four
testing
days
participants
pedaled
on
a
cycle
ergometer
for
30
minutes
at
60%
of
their
VO2max.
On
the
other
two
testing
days
participants
rested
for
30
minutes
in
a
waiting
room
at
the
MRI
facility.
Participants
arrived
at
the
Purdue
MRI
Facility
on
each
of
the
four
testing
days
at
5
pm.
The
study
design
is
found
in
Figure
1.
11. 11
Appetite
Questionnaire:
On
testing
days,
participants
rated
their
appetite
(hunger
and
fullness)
every
hour
from
8am
until
5pm
as
well
as
immediately
before
and
after
1)
consumption
of
meals,
2)
the
exercise/sedentary
activity,
and
3)
fMRI
scans.
Appetite
was
rated
using
a
100-‐mm
quasilogarithmic
visual
analog
scale,
with
descriptors
ranging
from
“barely
detectable”
to
“strongest
sensation
imaginable
of
any
kind”
[12].
Brain
Scan
using
fMRI:
Participants
lay
in
a
supine
position
and
closed
their
eyes
with
no
external
interaction
but
were
instructed
to
stay
awake.
Participants
were
scanned
in
a
3
Tesla
MRI
scanner
(GE
Signa
HDx).
The
entire
head
was
scanned,
and
the
areas
of
interest
were
the
SN
and
DMN.
Statistical
Analysis:
Independent
Component
Analysis
(ICA)
was
utilized
to
identify
resting
state
networks
(SN
and
DMN).
This
analysis
was
completed
using
the
AFNI
software
(available
from:
http://afni.nimh.nih.gov/).
Repeated
measure
ANOVA
(Mixed
Procedure)
was
used
to
examine
main
effects
of
exercise
(exercise
vs.
rest),
protein
(high
vs.
normal),
time
(before
vs.
60
minutes
after
dinner),
and
all
interactions
on
resting
state
networks.
These
analyses
were
completed
using
SAS
(Version
9.2).
All
data
are
presented
as
mean
±
SEM.
Statistical
significance
was
assigned
when
P
<
0.05
and
Tukey-‐Kramer
adjustment
was
used
for
post-‐hoc
analyses
as
needed.
12. 12
RESULTS
Subject
Characteristics
According
to
our
inclusion
criteria,
the
8
women
who
completed
the
study
procedures
were
29
±
3
years
old
and
had
an
average
BMI
of
35
±
1.1
kg/m2
(Table
1).
Salience
Network
After
analyzing
the
resting
state
scans,
the
ICA
did
not
reveal
a
SN.
Default
Mode
Network
The
DMN
was
revealed
and
is
shown
in
Figure
2.
There
was
no
change
in
DMN
activity
among
interventions
indicating
that
the
high
protein
dinner
versus
normal
protein
dinner,
aerobic
exercise
versus
rest
did
not
have
independent
or
interactive
effects
on
network
activities
(Figure
3
and
Figure
4).
The
ANOVA
model
demonstrated
trend
(unadjusted
p=0.0454,
adjusted
p=0.1134)
for
an
increase
in
DMN
activity
1-‐hour
after
eating
when
subjects
rested
before
dinner.
However,
this
was
not
statistically
confirmed
after
correcting
for
multiple
comparisons.
13. 13
DISCUSSION
The
present
study
evaluated
the
effects
of
protein
consumption
and
aerobic
exercise
on
the
acute
activity
of
two
resting-‐state
reward
networks,
the
SN
and
DMN.
Acute
changes
in
these
two
networks
have
never
been
studied.
We
hypothesized
there
would
be
a
general
meal-‐induced
reduction
in
SN
and
DMN
activity
60
minutes
after
dinner.
We
further
hypothesized
that
a
high
protein
dinner
would
result
in
a
greater
reduction
in
resting
state
activity
compared
to
a
normal
protein
dinner.
Acute
aerobic
exercise
would
result
in
a
relatively
greater
resting
state
activity
compared
to
rest.
These
hypotheses
were
based
on
previous
research
showing
dietary
protein
[4]
and
aerobic
exercise
[5]
influencing
subjective
appetite
sensations.
Previous
research
has
shown
that
acute
higher
protein
diets
increase
satiety
in
comparison
to
lower
protein
diets
and
this
results
in
a
decreased
energy
intake
[4].
A
long-‐term
high
protein
diet
has
been
shown
to
result
in
weight
loss
[16].
The
relationship
between
dietary
induced
thermogenesis
and
satiety
[4],
specifically
because
the
thermic
effect
of
protein
is
greater
then
fat
and
carbohydrate,
may
be
the
reasoning
behind
dietary
protein’s
satiating
effects.
Previous
research
has
also
demonstrated
that
aerobic
exercise
influences
subjective
appetite
and
energy
balance,
though
the
results
are
sometimes
conflicting
[13].
Further,
it
has
been
suggested
that
exercise
effects
on
appetite
may
differ
in
men
versus
women;
specifically
exercise
has
a
tendency
to
increase
hunger
in
women
relative
to
men
[13].
Sensations
of
appetite
may
be
influenced
by
activity
in
DMN
and
SN-‐related
brain
structures
[2,14].
Also,
exercise
training
has
previously
been
shown
to
decrease
DMN
activity
[2].
This
did
not
occur
in
this
study,
but
instead
there
were
no
significant
changes
in
DMN
activity
after
meal
consumption
and
among
interventions.
These
results
suggest
14. 14
that
acute
interventions
may
not
influence
resting
state
brain
activity
and
therefore
long-‐
term
inventions
may
be
necessary
for
normalizing
resting-‐state
neural
activity
in
obese
women.
Another
possibility
is
that
greater
intensity,
duration,
and
caloric
expenditure
of
exercise
may
be
necessary
to
elicit
acute
changes
in
brain
activity.
Looking
at
Figures
3
and
4,
it
seems
that
primarily
the
high
protein
with
rest
condition
drove
the
trend
for
an
increase
of
DMN
activity
on
resting
days.
These
results
are
contrary
to
our
hypothesis
of
a
greater
reduction
of
DMN
activity
with
a
high
protein
meal.
However,
the
increase
in
DMN
activity
was
not
statistically
confirmed
after
correcting
for
multiple
comparisons.
The
independent
component
analysis
did
not
reveal
a
SN,
and
therefore
intervention
effects
on
SN
activity
could
not
be
evaluated.
A
previous
study
assessed
the
effects
of
a
6-‐month
exercise
training
intervention
on
the
DMN
and
SN
in
overweight
and
obese
males
and
females.
DMN
activity
was
decreased
following
the
6-‐month
exercise-‐training
program
relative
to
baseline.
However,
greater
fat
mass
loss
was
associated
with
greater
reductions
in
DMN
activity
[2].
This
correlation
between
fat
loss
and
DMN
activity
cannot
be
used
to
infer
causality.
It
is
possible
that
exercise
training
and
improvements
in
fitness
reduced
DMN
activity.
Conversely,
exercise
training
may
decrease
fat
mass,
which
may
also
decrease
DMN
activity.
Our
results
show
that
acute
aerobic
exercise,
which
did
not
influence
overall
fitness
level
or
fat
mass,
did
not
influence
DMN
activity.
These
results
suggest
that
modulation
of
resting
state
brain
activity
may
be
driven
by
adaptations
to
chronic
exercise
training
rather
than
acute
exercise.
The
resting
state
SN
and
DMN
are
important
because
they
process
homeostatic
information.
The
DMN
is
specifically
associated
with
self-‐monitoring
behavior
[3]
and
is
more
active
during
interoceptive
processing,
which
is
related
to
processing
of
internal
15. 15
stimuli.
The
SN
is
associated
with
the
reward
system
and
shows
greater
activation
when
an
individual
is
anticipating
food
consumption
[3].
We
expected
to
observe
a
SN
because
previous
studies
have
revealed
this
network
using
the
same
standard
techniques
[2,
3,
11].
However
our
analysis
did
not
reveal
this
network.
Strengths
and
Limitations
The
strengths
of
this
study
include
extensive
dietary
controls
and
supervised
exercise
sessions
to
ensure
adherence
to
our
diet
and
exercise
interventions.
All
subjects
were
blinded
to
the
protein
content
of
the
meals,
so
any
cognitive
biases
were
avoided.
Our
small
homogenous
group
of
subjects,
obese
young
women,
is
a
limitation.
A
larger
subject
group
may
provide
greater
statistical
power
to
detect
a
SN
and
changes
in
DMN
activity
among
interventions.
Including
a
more
heterogeneous
group
of
men
and
various
age
groups
would
increase
the
generalizability
of
these
findings.
Inclusion
of
a
normal
weight
group
would
enable
comparisons
of
resting
state
brain
activity
in
normal
weight
versus
obese
women.
Also
this
would
allow
an
investigation
of
whether
weight
status
influences
acute
effects
of
exercise
and
meal
consumption
on
resting
state
brain
activity.
In
this
study,
scanning
was
completed
in
the
evenings,
beginning
at
5pm;
whereas
most
existing
research
completed
resting
state
scanning
in
the
morning.
This
may
have
influenced
our
results,
however
further
research
is
needed
to
confirm
time
of
day
effects.
Further
Research
Since
this
pilot
study
was
the
first
to
test
and
analyze
the
effect
of
protein
consumption
and
aerobic
exercise
on
acute
activity
in
these
reward
networks,
further
research
should
be
done
to
confirm
that
there
is
no
change
in
activity
from
these
interventions.
Further
research
should
especially
be
done
with
a
larger
subject
group,
16. 16
along
with
both
men
and
women
of
varying
BMI’s.
Previous
research
showed
decreased
reward
network
activity
in
a
6-‐month
exercise
training
intervention
[2],
therefore
further
research
should
be
done
to
determine
at
what
time
point
exercise
training
begins
to
decrease
network
activity.
Conclusion
In
conclusion,
neither
high
protein
meals
nor
aerobic
exercise
had
acute
effects
on
DMN
activity
in
obese
women
ages
18-‐45
years
old.
Conclusions
cannot
be
made
regarding
the
effects
of
dietary
protein
or
exercise
on
SN
activity.
Acute
dietary
protein
and
aerobic
exercise
may
not
be
modulators
of
resting-‐state
neural
activity
in
obese
women
and
therefore
may
not
be
effective
strategies
for
decreasing
resting-‐state
neural
activity
in
obese
women.
17. 17
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S.A.,
A.W.
Song,
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McCarthy,
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Mass.:
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xvi,
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2.
McFadden,
K.L.,
et
al.,
Effects
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Neuroreport,
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p.
866-‐71.
3.
Garcia-‐Garcia,
I.,
et
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Alterations
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A
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Hum
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4.
Halton,
T.L.
and
F.B.
Hu,
The
effects
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protein
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on
thermogenesis,
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Am
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5.
Martin,
L.E.,
et
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in
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healthy
weight
adults.
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p.
254-‐60.
6.
Karhunen,
L.J.,
et
al.,
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cerebral
blood
flow
during
food
exposure
in
obese
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weight
women.
Brain,
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1675-‐84.
7.
Rothemund,
Y.,
et
al.,
Differential
activation
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by
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visual
food
stimuli
in
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individuals.
Neuroimage,
2007.
37(2):
p.
410-‐21.
8.
Stice,
E.,
et
al.,
Relation
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reward
from
food
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and
anticipated
food
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J
Abnorm
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2008.
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p.
924-‐35.
9.
Horstmann,
A.,
et
al.,
Obesity-‐Related
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10.
Goldstone,
A.P.,
et
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Fasting
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brain
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11.
Cornier,
M.A.,
et
al.,
Sex-‐based
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538-‐43.
12.
Stubbs,
R.J.,
et
al.,
The
use
of
visual
analogue
scales
to
assess
motivation
to
eat
in
human
subjects:
a
review
of
their
reliability
and
validity
with
an
evaluation
of
new
hand-‐held
computerized
systems
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temporal
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405-‐15.
13.
Stensel,
D.,
Exercise,
appetite
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Tregellas,
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Thompson,
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16.
Wycherley,
T.P.,
L.J.
Moran,
P.M.
Clifton,
M.
Noakes,
and
G.D.
Brinkworth,
Effects
of
18. 18
energy-‐restricted
high-‐protein,
low-‐fat
compared
with
standard-‐protein,
low-‐fat
diets:
a
meta-‐analysis
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randomized
controlled
trials.
Am
J
Clin
Nutr,
2012.
96(6):
p.
1281-‐
98.
19. 19
TABLES
AND
FIGURES
Table
1.
Subject
Characteristics
20. 20
Table
2.
Dinner
(High
Protein
or
Normal
Protein)
Macronutrient
Composition1
Property High Protein Meal Normal Protein Meal
Total Energy (kcals) 811.9 811.9
Protein (g, % Energy) 60.9, 30% 30.4, 15%
Carbohydrate (g, %
Energy)
91.3, 45% 121.8, 60%
Fat (g, % Energy) 22.6 25% 22.6, 25%
1All
values
are
mean
±
SEM.
21. 21
Figure1:
Study
Design.
Schematic
of
testing
day
procedures.
Figure
2:
Default
Mode
Network.
AFNI
was
used
to
create
statistical
parametric
maps
to
depict
resting
state
Default
Mode
Network
activity
with
all
sessions
combined
(n=64
total
sessions).
Figure
3:
Pre-‐Meal
Default
Mode
Network
Activity.
All
values
are
mean
±
SEM.
Repeated
measures
ANOVA
(MIXED
Procedures,
SAS,
version
9.2)
was
used
to
test
for
differences
in
Default
Mode
Network
Activity
on
the
4
testing
days.
Default
Mode
Activity
was
not
different
on
these
testing
days.
Abbreviations:
NPR,
Normal
Protein/Rest;
HPR,
High
Protein/Rest;
NPEx,
Normal
Protein/Exercise;
HPEx,
High
Protein/Exercise
Figure
4:
Post-‐Meal
Default
Mode
Network
Activity.
All
values
are
mean
±
SEM.
Repeated
measures
ANOVA
(MIXED
Procedures,
SAS,
version
9.2)
was
used
to
test
for
differences
in
Default
Mode
Network
Activity
on
the
4
testing
days.
Default
Mode
Activity
was
not
different
on
these
testing
days.
Abbreviations:
NPR,
Normal
Protein/Rest;
HPR,
High
Protein/Rest;
NPEx,
Normal
Protein/Exercise;
HPEx,
High
Protein/Exercise
28. 28
Women Ages 18 to 45
Needed for a Research
Study
Prof. Wayne Campbell
Department of Nutrition Science, Purdue University
We are looking for overweight women who would like to volunteer for
a research study evaluating whether exercise performed before dinner
affects brain activity in response to viewing pictures of food.
Participants will be compensated $200 for completing this study.
INTERESTED VOLUNTEERS SHOULD BE:
ü Female
ü Age: 18 to 45
ü Overweight
ü Not Smoking
ü Not Pregnant
Measurements taken during the study will include brain activity using
functional magnetic resonance imaging, questionnaires about
appetite, and a blood draw.
FOR MORE INFORMATION, contact
Drew @ (765) 494-8313 or Email: sayer@purdue.edu
Department of Nutrition Science, Purdue University; West Lafayette,
IN 47907
Drew
sayer@purdue.edu
765-‐494-‐8313
John
apolzan@purdue.edu
765-496-6480
Drew
sayer@purdue.edu
765-‐494-‐8313
Drew
sayer@purdue.edu
765-‐494-‐8313
John
apolzan@purdue.edu
765-496-6480
Drew
sayer@purdue.edu
765-‐494-‐8313
John
apolzan@purdue.edu
765-496-6480
Drew
sayer@purdue.edu
765-‐494-‐8313
John
Drew
sayer@purdue.edu
765-‐494-‐8313
Drew
sayer@purdue.edu
765-‐494-‐8313
John
apolzan@purdue.edu
765-496-6480
Drew
sayer@purdue.edu
765-‐494-‐8313
John
apolzan@purdue.edu
765-496-6480
Drew
sayer@purdue.edu
765-‐494-‐8313
John
apolzan@purdue.edu
765-496-6480
40. 32
APPETITE LOG Study code:___________
Please place one mark on each scale that best reflects your answer to each of the
following questions at this time.
1. How strong is your feeling of hunger? 1. ____
Not at all Extremely
2. How strong is your feeling of fullness? 2. ____
Not at all Extremely
3. How strong is your desire to eat? 3. ____
Not at all Extremely
4. How strong is your “urge to eat”? 4. ____
Not at all Extremely
5. How strong is your preoccupation with thoughts of food? 5. ____
Not at all Extremely
6. How strong is your feeling of thirst? 6. ____
Not at all Extremely
41. 33
7. How strong is your desire to eat something salty? 7. ____
Not at all Extremely
8. How strong is your desire to eat something fatty? 8. ____
Not at all Extremely
9. How strong is your desire to eat something sweet? 9. ____
Not at all Extremely
10.The shakiness of your hand is… 10. ____
Not at all Extremely
11.How strong is your grip? 11. ____
Not at all Extremely
12.How itchy is your scalp? 12. ____
Not at all Extremely
45. 37
Lexie Buchs
Education
Purdue University – West Lafayette, IN 10/2011 – Present
Bachelor of Science degree with Honors, Major: Dietetics, GPA: 3.40
Study Abroad - Dublin Institute of Technology – Dublin, Ireland 1/2014 – 5/2014
Adult and Child First Aid/CPR/AED Certified
Blood Born Pathogen Certified
Work Experience
Wiley Dining Court – Purdue University 10/2014 – Present
Food Preparation, Food Service, Meal Preparation, Cleaning and Sanitation
Campbell Nutrition Science Lab – Purdue University 5/2014 – Present
MRI Secondary Operator, Data Entry into Microsoft Excel, Miscellaneous Lab Work
Metabolic Kitchen – Purdue University 5/2014 - 8/2014
Data Entry, Food Preparation for scientific research studies
Buffalo Wild Wings – Auburn, IN 5/2012 - 8/2012
Waitress, Cashier, Greeter, Cleaning and Sanitation
Auburn Community Pool – Auburn, IN 5/10 - 8/10 & 5/11 - 8/11
Lifeguard, Swim Lesson Instructor
Brown House Restaurant – Auburn, IN 3/2010 - 7/2010
Cook, Cashier, Food Service, Cleaning and Sanitation
Volunteer Experience
Data Collection for a Pantry Study in a Purdue University Nutrition Lab Fall 2014
Completed 24-hour recalls with study participants and entered data into Microsoft Excel
Lafayette Soup Kitchen Fall 2014
Serve and Prepare Food
Mentor at the Ireland Pre-Departure Meeting 11/20/2014
Assisting students in finding housing, and preparing students to leave for Ireland
Mentor at the Study Abroad Fair 9/10/2014
Advocating to interested students about the perks of studying abroad and answering questions
Ecuador Medical Mission Trip 12/15/2012 - 12/23/2012
Assisted doctors and nurses in hospitals and visited children in orphanages
Delta Zeta Painted Turtle 5K – Benefitting the Starkey Hearing Foundation 4/27/2013
Organized and participated in the race event
Delta Zeta Turtle Tug - Benefitting the Painted Turtle Camp 10/2011 & 10/2012
Organized the competition, Team Leader
Delta Zeta ‘Bowlarama’ - Benefitting the Starkey Hearing Foundation 4/2011
Organized the tournament, facilitated the event
Organizations & Societies Accomplishments & Awards
Academy of Nutrition & Dietetics Honors Society.org
Purdue University Nutrition Society Phi Sigma Theta Honors Society
Purdue University Caduceus Club National Society of Collegiate Scholars
Saint Michael’s Church Parishioner Intel International Science Fair
1st
Place Air force Award 2011, Competitor 2010 & 2011
4546 Cr 16 Waterloo, IN 46793 Ÿ 260 908 1652 Ÿ lbuchs@purdue.edu
