Evaluating Motivation and Reward Mechanisms and Brain Substrates in Adults With Obesity: Further Evidence That Obesity Affects Physical and Mental Health
Conditions: Anhedonia, Obesity
Sponsor: Brain and Cognition Discovery Foundation

 
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Evaluating Motivation and Reward Mechanisms and Brain Substrates in Adults with 
Obesity: Further evidence that obesity affects physical and mental health 
 
 
Roger S. McIntyre 
Professor of Psychiatry and Pharmacology, University of Toronto, Toronto, Canada 
Chairman and Executive Director, Brain and Cognition Discovery Foundation (BCDF), Toronto, 
Canada 
Director, Depression and Bipolar Support Alliance (DBSA), Chicago, USA 
Head, Mood Disorders Psychopharmacology Unit 
http://www.mdpu.ca/ 
Professor and Nanshan Scholar, Guangzhou Medical University, Guangzhou, China 
Adjunct Professor College of Medicine, Korea University, Seoul, Republic of Korea 
 
Mailing Address: 
73 Mathersfield Drive 
Toronto, ON M3W 3W4 
Canada 
Telephone: 416-669-5279 
Fax: 416-603-5368 
Email: roger.mcintyre@uhn.ca 
 

 
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Table of Contents 
STUDY SYNOPSIS ..................................................................................................................................................... 3 
INTRODUCTION ....................................................................................................................................................... 4 
HYPOTHESIS ................................................................................................................................................ 5 
METHODOLOGY  ..................................................................................................................................................... 5 
PARTICIPANTS ....................................................................................................................................................... 5 
INCLUSION/EXCLUSION CRITERIA  ....................................................................................................... 5 
MEASUREMENTS OBTAINED AT SINGLE VISIT ............................................................................................ 6 
PROCEDURES FOR PARTICIPANTS ................................................................................................................... 8 
ADVERSE EVENTS ................................................................................................................................................... 8 
DEFINITIONS ................................................................................................................................................ 8 
RECORDING OF ADVERSE EVENTS ........................................................................................................ 9 
REPORTING OF SERIOUS ADVERSE EVENTS ..................................................................................... 10 
RISKS RELATED TO INVOLVEMENT IN STUDY ........................................................................................... 10 
BENEFITS RELATED TO INVOLVEMENT IN STUDY ................................................................................... 11 
TIMELINE ................................................................................................................................................................. 11 
PRIMARY AND SECONDARY OUTCOME MEASURES ................................................................................. 11 
EEFRT, PRT, MID TASK  ..................................................................................................................................... 12 
STATISTICAL ANALYSIS ..................................................................................................................................... 12 
DATA HANDLING ................................................................................................................................................... 14 
PERSONAL DATA PROTECTION ...................................................................................................................... 14 
DATA RETENTION ................................................................................................................................................. 14 
PARTICIPANT PROTECTION .............................................................................................................................. 14 
IMPLICATIONS ....................................................................................................................................................... 14 
REFERENCES .......................................................................................................................................................... 18 
 
 

 
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Study Synopsis: 
Anhedonia and abnormalities in reward behavior are core features of overweight/obesity 
(OW), a highly prevalent condition within MDD populations and is independently associated with 
reward disturbances. We therefore aimed to investigate the brain substrates subserving reward 
and motivation in adults with overweight/obesity. Herein, we are primarily interested in three 
overlapping, yet distinct aspects, of anhedonia. We are primarily interested in motivation, reward 
valuation, and reward learning towards addressing the measurement of each of these 
respective subdomains, eligible participants will complete validated gold standard measures (i.e. 
the Effort Expenditure for Rewards Task (EEfRT) (reward valuation), Probabilistic Reward Task 
(PRT) (reward learning), and the Monetary Incentive Delay (MID) task (reward anticipation)).  
 
 Twenty adults with overweight/obesity will complete all tasks at a single visit with two of 
the tasks being completed prior to MRI and one of the tasks (i.e. EEfRT) will be completed 
during MRI acquisition. 
  The primary aim of this pilot study is to determine whether associations exist between 
obesity and decreased performance on the respective motivation/reward paradigms. In addition, 
associations between performance on reward tasks and functional connectivity, as measured by 
MRI and DTI, a secondary objective is to ascertain whether associations exist between 
performance on the motivation reward tasks and gold standard measures of food intake (i.e. 
food diary) and energy expenditure (i.e. calorimetry).  
 
 

 
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Introduction 
Anhedonia is a significant complaint and psychopathology in OW. Anhedonia is defined as 
markedly diminished interest or pleasure in all, or almost all, activities for an extended period of 
time. Anhedonia is a core criterion item for the diagnosis of MDD and OW, and is a robust 
predictor 
of 
poor 
longitudinal 
course 
of 
symptoms1-4. 
Existing 
psychological 
and 
pharmacological treatments are relatively ineffective for treating anhedonia, as they have little 
effect, and in some cases may even worsen anhedonic symptoms2,5. As a result, anhedonia is 
one of the most prevalent residual symptoms following treatment with antidepressants in 
individuals with MDD and OW2,6,7. 
Anhedonia includes elements of multiple reward processes8-10. Reward systems are 
primarily responsible for responses to positive motivational situations or contexts, such as 
reward seeking, and reward/habit learning8-10. Evidence indicates that individuals with mood 
disorders exhibit abnormalities in multiple subcomponents of reward13-17. One of the main 
reward sub-constructs of interest in MDD is reward valuation, which includes the measurement 
of value and/or incentive salience of a prospective outcome and the willingness to work for it 
(i.e. effort)11,12. A consistent finding in MDD has been a decrease in the willingness to expend 
effort for rewards13-16,18. Individuals with depression display reduced motivation on effort-based 
decision making14-16, a dissociation between liking a reward and the willingness to exert effort for 
it13, and an increased subjective feeling of having exerted more effort16. 
Replicated evidence indicates that OW is highly prevalent in MDD populations. Meta-
analytical studies have estimated the prevalence of obesity in MDD between 30 and 70%19-22. 
Conversely, OW has been consistently associated with motivational deficits, to both food and 
non-food rewards23. Evidence indicates that in obesity the anticipatory reward response seems 
to be increased24,25, whereas, similar to MDD, the willingness to invest effort is diminished26,27. 

 
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Within MDD populations, obesity, and its metabolic correlates (e.g. insulin resistance), have 
been associated with increased self-reported anhedonia28,29. As a result, anhedonia has been 
proposed as a key clinical mediator between MDD and metabolic comorbidities30,31. 
Nevertheless, few studies have used objective methods to assess reward deficits in 
populations with MDD and obesity. Herein, we aim to explore the role of OW in effort-based 
decision making in overweight/obese adults with varying levels of body mass index (BMI) above 
30kg/m2. We primarily aim to investigate the effects of OW correlation with effort for rewards, as 
measured by the Effort Expenditure for Rewards Task (EEfRT). The secondary aim is to 
examine the associations between effort-based decision-making as measured by EEfRT, with 
MRI/DTI measured alterations in reciprocity between reward and cognitive control circuits.  
We hypothesize that obesity is associated with deficits in each of the reward paradigms we 
have selected.  We also hypothesize that the foregoing disturbances correlate with functional 
disconnectivity within reward/cognitive control networks.   
 
Methodology 
Participants 
Participants will be identified at the Brain and Cognition Discovery Foundation (BCDF). 
Twenty subjects with obesity, will be enrolled. All patients will be assessed for concurrent 
psychiatric disorders (e.g. mood disorders). Eligibility criteria are as follows: inclusion criteria: (a) 
18-65 years of age; (b) meeting DSM-V criteria for: (i) major depressive disorder (symptomatic 
or asymptomatic in any phase of the illness) or (ii) bipolar disorder I/II (symptomatic or 
asymptomatic in any phase of the illness); (c) ability to provide written and informed consent; (d) 
obesity 30 kg/m2; (e ) weight under 440lbs; (f) shoulder-to-shoulder width under 60 cm; 
Exclusion criteria are as follows: (a) age below 18 or above 65; (b) use of benzodiazepines or 
consumption of alcohol within 12 hours of assessments; (c) abuse of marijuana; (d) physical, 

 
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cognitive, or language impairments sufficient to adversely affect data derived from 
assessments; (e) diagnosed  reading disability or dyslexia; (f) clinically significant learning 
disorder by history; (g) history of moderate or severe traumatic brain injury; (h) other 
neurological disorders, or unstable systemic medical diseases; and (i) pregnancy and post-
partum period (j) presence of any contra-indications for MRI; (k) weight above 440lbs; (l) 
shoulder-to-shoulder width greater than 60 cm. All subjects will be consented prior to initiating 
the study; (m) >45 BMI; (n) suicidality as determined by clinical discretion.  
Measurements Obtained at Single Visit 
1. Sociodemographic: 
a. Age 
b. Sex 
c. Education 
d. Employment Status 
e. Education Attainment 
f. Marital Status 
g. Ethnicity and Race 
2. Illness Measurements: 
a. Severity of depression will be assessed with the Quick Inventory of Depressive 
Symptomatology (QUIDS)  
b. Measurement of anhedonia composite (SHAPS)  
c. Self-rated cognitive measurement (PDQ-5) Perceived Deficit Questionnaire 5  
d. Objective cognitive measurement (TMTA/B)  
e. Digit Symbol Substitution Test (DSST)  
f. UCLA Loneliness Scale  

 
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g. Food Diary  
h. Calorimetry  
i. 
Anxiety Measurement (Hamilton Anxiety Scale) (HAMD)  
j. 
Age of onset  
k. Number of episodes 
l. 
Number of hospitalizations 
m. Duration of current episode 
n. Psychiatric comorbidity 
o. Number of treatments  
3. Medical Assessment: 
a. Weight 
b. Height 
c. Waist circumference 
4. Laboratory Measures: 
a. Blood glucose 
b. Cholesterol and fractionation (E.g. HDL, LDL and triglycerides) 
c. Insulin levels 
d. Interleukin 1, interleukin 6, interleukin 10, tumor nercosis factor alpha, c reactive 
peptide, adiponectin, leptin, gherlin, DPP-lV 
e. Oxidative stress markers (e.g. TBARS) 
5. Effort Expenditure for Rewards Task (EEfRT) 
6. Monetary Incentive Delay (MID) task 
7. Probabilistic Reward Task (PRT) 
8. MRI Scan 

 
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All assessments and scan will be done on the same day.  
Procedures for Participants 
Visit 1   
The single visit entails the provision of detailed study information to participant and obtainment 
of informed written consent, as well as completion of all questionnaires, activities, MRI, and 
participant compensation. The psychiatrists will assess participants’ eligibility based on 
inclusion/exclusion criteria and confirm a diagnosis of MDD or BD based on their scheduled 
appointment visit. Demographics including date of birth, sex, and race will be recorded. Years of 
education will be recorded as well. Psychiatric and medical history, number of psychotropic 
medications received according to participant self-report/clinical chart review, as well as 
anthropometrics (including height, weight and waist circumference) will be measured. 
Participants will complete a series of questionnaires to assess their illness. These include: 
Quick Inventory of Depressive Symptomatology (QIDS), Snaith-Hamilton Pleasure Scale 
(SHAPS), Perceived Deficits Questionnaire for Depression (PDQ-5-D), Hamilton Depression 
Rating Scale (HAMD). Participants will also have loneliness assessed by participating in the 
UCLA Loneliness Scale. All self-reports will be administered by a member of the study team. 
Participants will record their food intake via a Food Diary, and will have a Calorimetry test taken. 
Participants will also complete cognitive measures including the Trail Making Test A/B (TMT 
A/B), and the Digit Symbol Substitution Test (DSST). Participants will then complete the 
Monetary Incentive Delay (MID) task, as well as the Probabilistic Reward Task (PRT). All study 
procedures will take place in a quiet setting. Fasting (12-hours) clinical and research bloodwork 
will also be collected. Participants will be escorted by a study member to the MRI facility where 
they will complete the MRI and the Effort Expenditure for Rewards Task (EEfRT). Upon 
completion of the MRI, participants will receive the reimbursement fee for their participation in 
the study.  
 
Adverse Events 
Definitions: 
Adverse event: An adverse event is the development of an undesirable medical condition or the 
deterioration of a pre-existing medical condition following or during exposure to a 
pharmaceutical product, whether or not considered causally related to the product.  An 

 
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undesirable medical condition can be symptoms (e.g., nausea, chest pain), signs (e.g., 
tachycardia, enlarged liver) or the abnormal results of an investigation (e.g., laboratory findings, 
electrocardiogram).  In clinical studies, an AE can include an undesirable medical condition 
occurring at any time, including run-in or washout periods, even if no study treatment has been 
administered. 
Serious adverse event: A serious adverse event is an AE occurring during any study phase (i.e., 
run-in, treatment, washout, follow-up), and at any dose of the investigational product, 
comparator or placebo, that fulfils one or more of the following criteria: 
• 
results in death 
• 
is immediately life-threatening 
• 
requires in-patient hospitalization or prolongation of existing hospitalization 
• 
results in persistent or significant disability or incapacity 
• 
is a congenital abnormality or birth defect 
• 
is an important medical event that may jeopardize the patient or may require medical 
intervention to prevent one of the outcomes listed above. 
The causality of SAEs (i.e., their relationship to study treatment) will be assessed by the 
investigator(s).  Note that SAEs that could be associated with any study procedure should also 
be reported. For such events the casual relationship is implied as "yes". 
Recording of Adverse Events 
AEs will be collected during each visit. At each visit, subjects will be asked if they have had 
any health problems since the previous visit.  All AEs will be recorded appropriately, whether or 
not considered related to the investigational product. This will include AEs spontaneously 
reported by the patient and/or observed by the staff as well as AEs reported in response to a 
direct question e.g. “Have you had any health problems since your last visit?”  
For each AE, the following parameters be described: 
• 
start and stop date 
• 
action taken with regards to investigational product 
• 
outcome 
• 
if the AE caused the patient to discontinue 
• 
a statement if the AE fulfils the criteria for a SAE or not 

 
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• 
the investigator’s assessment of the causal relationship between the event and the 
investigational product 
• 
intensity of the AE 
o mild (awareness of sign or symptom, but easily tolerated) 
o moderate (discomfort sufficient to cause interference with normal activities) 
o severe (incapacitating, with inability to perform normal activities) 
It is important to distinguish between serious and severe AEs.  Severity is a measure of 
intensity whereas seriousness is defined by the criteria in Section.  An AE of severe intensity 
need not necessarily be considered serious.  For example, nausea that persists for several 
hours may be considered severe nausea, but not an SAE.  On the other hand, a stroke that 
results in only a limited degree of disability may be considered a mild stroke but would be an 
SAE.  
Symptoms associated with overdose should be reported as AEs. For further information 
regarding overdose, see section. 
Pregnancy in itself is not regarded as an AE unless there is a suspicion that an 
investigational product may have interfered with the effectiveness of a contraceptive medication.  
Follow-up of adverse events should be based upon the clinical judgement of the 
investigator. 
Reporting of Serious Adverse Events 
Reporting of SAEs to regulatory authorities will be done by the investigator in accordance 
with local regulations. A copy of the report will also be sent to the manufacturer of the 
investigational product. 
 
Risks Related to Being in the Study 
 
This study has risks. Some of these risks we know about. There is also a possibility of risks that 
we do not know about that have not been seen in study participants to date. Some can be 
managed. Please call the study doctor if you have any side effects even if you do not think they 
have anything to do with this study. The risks we know of are: 
  
a) MRI risks: There are few potential risks of having an MRI scan, as it is a non-invasive 
procedure and does not involve any radiation. The main potential risk comes from loose 
metal objects, which, if taken near the scanner, could be dangerous. The combination of 
the noise of the scanner and confined space can also be stressful for people who feel 
uncomfortable in closed spaces. 

 
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b) Blood draw risks: Drawing blood may cause very mild pain, bruising, redness, and rarely 
infection at the needle stick. 
c) Other risks: In addition to medical risks, being in this study may make you feel 
uncomfortable. You will be asked personal questions about your psychiatric and medical 
history. You may refuse to answer questions or stop the interview at any time if there is 
any discomfort. Administering the cognitive testing may sometimes be frustrating 
particularly if you are not performing as well as you think you should, and may also lead 
to mild mental and physical fatigue.   
 
Benefits to Being in the Study 
 
You may or may not receive any direct benefit from being in this study. Information learned from 
this study may help other people with mood disorders in the future. 
 
Timeline 
It is estimated that it will require approximately 3-5 months to recruit. 
 
Primary and Secondary Outcome Measures  
The primary outcome measure in this study will be the association between 
performance on the EEfRT, MID, and PRT. Anthropometric data will be obtained from all 
participants at the day of the EEfRT assessment. Body mass index (BMI) will be measured 
using the formula BMI = weight (Kg) / height (meters)2. The secondary outcome will be the 
association between the EEfRT/ MID/PRT and function reciprocity of the reward circuit/cognitive 
control network as measured by MRI/DTI.  All participants will also have whole blood samples 
collected after a 12 hour fast. Metabolic parameters will be measured immediately in a single 
laboratory with the same assay. Insulin resistance and beta-cell function (i.e. insulin secretion) 
in basal state will be calculated from fasting plasma glucose and fasting insulin using the 
HOMA2 calculator (http://www.dtu.ox.ac.uk)33.  

 
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Effort Expenditure for Rewards Task (EEfRT), Probabilistic Rewards Task (PRT), and Monetary 
Incentive Delay (MID) task 
The EEfRT measures participants’ willingness to make efforts to obtain a monetary 
reward under different conditions of reward probability and magnitude14,18. In each EEfRT trial, 
participants are given an opportunity to choose between two tasks with different levels of 
difficulty: “hard task” and “easy task.” Successful completion of the easy task trials requires 30 
button presses using the dominant index finger within 7 seconds, whereas the hard task trials 
requires 100 button presses using the non-dominant little finger within 21 seconds. Participants 
will be informed that successful trial completion does not guarantee winning the monetary 
reward. Before making a choice, participants are provided with information that varies from trial 
to trial regarding: (1) the probability (12%, 50%, or 88%) of winning the money; and (2) the 
magnitude of reward for successfully completing the hard task. The reward magnitude will be 
set at $1.00 for easy tasks and higher amounts that will vary per trial within a range of $1.24-
$4.30 for hard tasks. Probability levels will always be applied to both the hard task and easy 
task, and there will be equal proportions of each probability level across the experiment. 
Participants are given 20 minutes to perform the task; thus, the number of trials will vary across 
the participants. The Probabilistic Rewards Task (PRT) measures response bias and sensitivity 
to reward under variable conditions. The Monetary Incentive Delay (MID) task assesses the 
basis of anticipation and consumption of reward and punishment. Each test takes approximately 
20 minutes to administer.  
 
Statistical Analysis 
Graph theoretical analysis (GTA) will be used to assess functional connectivity of the 
default mode network, cognitive control network, affect network and reward network. This is a 

 
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preliminary 
exploratory 
analysis, 
descriptive 
statistics 
will 
be 
conducted 
on 
the 
sociodemographic, clinical and metabolic parameters. Associations between obesity and 
alterations in functional connectivity will be the primary outcome of interest and additional 
coprimary outcome is the association between obesity and reward motivation as indexed by the 
EEfRT/MID/PRT task. Laboratory parameters will be used to explore potential mediational 
relationships between obesity and brain connectivity measurements, as well as reward 
performance.  
For each variable, distribution normality will be assessed with one-sample Kolmogorov-
Smirnov tests. Comparisons between groups will be conducted using independent samples t-
tests and Mann-Whitney U (for normally and non-normally distributed variables, respectively). 
Participants are given 20 minutes to complete the EEfRT, and the number of trials completed 
during that time will vary among them (Table 1). Consistently with previous studies, only the first 
50 trials will be used18. Similar to previous studies using the EEfRT, we will use generalized 
estimating equation (GEE) models to test the effects of groups, reward magnitude and 
probability on the willingness to expend effort for rewards (i.e. percentage of trials on which the 
‘hard’ task was selected). We will use an independent matrix, which best fit our data, and a 
binary logistic distribution to model the dichotomous outcome of choosing the hard versus the 
easy task. All GEE models will include reward magnitude, probability, and expected value (EV, 
defined as the interaction between reward probability and magnitude). In addition, each model 
will include a trial number as a covariate to control for possible effects of fatigue over the course 
of the task. Reward magnitude will be categorized in three groups: low (<$2.30), medium 
($2.31-$3.29), and high (>$3.30). To assess associations between EEfRT and clinical and 
metabolic data, we will calculate the mean proportions of hard-task choices for all subjects. 

 
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Stepwise linear regression will then be used to identify significant predictors.  MRI/DTI will be 
attained for all subjects. 
 
Data Handeling 
Personal Data Protection 
All data collection material will be de-identified. Participant records will be distinguished using 
participant identification (PID) numbers. 
 
Data Retention 
Records and documents pertaining to the conduct of the study as well as all data collected as 
part of the study will be retained in a secure place for 25 years in accordance with Health 
Canada regulations. All data collected throughout the study will be kept with membership of the 
BCDF for 25 years. 
 
Participant Protection 
Participants will not be placed at any risk as a result of the study. Information obtained will be 
maintained in a secure and confidential fashion. No participant will be coerced and/or placed 
under duress to complete study procedures. 
 
Implications 
We believe our results will comport with the notion that obesity 31 is subserved by 
disturbances in reward circuits and cognitive control networks. We believe that alterations in 
reward and motivation are fundamental brain disturbances due to obesity34-36,37-39. The 
Research Domain Criteria (RDoC) construct of reward is a core domain for the overlap between 
mood and metabolic disorders. We believe our results will show that obesity moderates and as 
a consequence of disturbance in reward and motivation and functional disconnectivity. 
Mechanistically, a recent genetic study identified multiple genes that are shared between 
mood and metabolic disorders; and revealed an over-representation of genes involved in 

 
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dopamine signaling, which plays a crucial role in anhedonia and reward processing40. In 
addition, obesity and MDD have a shared biosignature, with well-documented involvement of 
inflammatory 
mechanisms, 
hypothalamic–pituitary–adrenal 
(HPA) 
dysregulation, 
and 
oxidative/mitochondrial stress41-43. Replicated neuroimaging studies have reported specific 
morphological alterations of the MDD and obesity comorbidity, implicating mainly medial 
prefrontal areas39,44. Conversely, these areas are an important hub of reward valuation, and are 
known to be affected by, for example, inflammatory and metabolic mediators45-48.   
One of the key subcomponents of metabolic dysfunction in obesity is insulin resistance49. 
Insulin resistance has been associated with depressive symptoms in epidemiological studies50 
and, in clinical populations, with anhedonia specifically28. Indeed, we observed a strong 
correlation between insulin resistance and willingness to expend effort in the MDD subgroup. 
Multiple brain regions that are relevant to reward systems have relatively increased expression 
of insulin receptors51,52. Specifically, midbrain dopamine neurons, one of the main hubs of 
reward neurocircutiry53,54, widely express insulin receptors55. Imaging studies have reported that, 
in healthy individuals, insulin modulates brain activity in the hypothalamus, hippocampus and 
prefrontal cortex56-58. A recent gene expression analysis reported that the differential expression 
of dopamine-related molecules in individuals with mood and psychotic disorders was related to 
altered expression of insulin signaling genes; an effect that was moderated by obesity in a 
region-specific manner (Mansur et al., 2018). As a result, peripheral insulin sensitivity has been 
shown to modulate reward behavior in humans. In obese adults, insulin resistance was 
associated with a stronger preference for immediately receiving a smaller, but certain, monetary 
reward over delaying the receipt of a larger, but less certain one (i.e. greater delay 
discounting)59. 

 
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In humans, insulin resistance is associated with less endogenous dopamine at D2/3 
receptors in the ventral striatum and nucleus accumbens, in both obese and non-obese 
adults60,61. Another study documented that weight loss following bariatric surgery was 
associated with an increase in D2 receptor availability62. In effort-based decision-making, 
evidence indicates that dopamine responsivity, particularly in the striatum and ventromedial 
prefrontal cortex, is strongest for low probability trials63,64. Conversely, we observed a stronger 
effect of overweight/obesity in the low reward trials. If overweight/obesity and the peripheral 
measures of insulin resistance used herein do indeed reflect and/or are associated with brain 
insulin resistance, it could be posited that disturbances in central insulin signaling lead to 
decreased dopamine sensitivity, resulting in an increased likelihood to choose low-effort 
options. This hypothesis, however, has two principle outstanding questions. First, it relies on the 
assumption that peripheral and brain insulin sensitivity are correlated (or that peripheral 
measures are reliable indicators of central processes), which is insufficiently characterized65,66. 
Direct measurements of brain insulin sensitivity, and its relationship to dopamine signaling and 
effort-based decision-making, are necessary. 
Second, it assumes that disturbances in insulin signaling are the principle mediators of the 
changes in dopamine function; an idea that does have support in the literature67,68, but cannot 
be fully ascertained in a cross-sectional study. Moreover, recent evidence has indicated that the 
brain is also as an important regulator of systemic glucose and energy metabolism69,70. For 
example, bromocriptine, a potent dopamine D2 receptor agonist, has been shown to improve 
glucose metabolism in humans71. Dopamine release in the striatum might enhance whole-body 
insulin sensitivity, whereas inhibition of dopamine activity might reduce it70. Therefore, 
individuals predisposed to lower central dopamine activity may be more susceptible to the 
development of obesity and insulin resistance states. Disturbances in reward behavior, 

 
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particularly effort, might also affect peripheral metabolism indirectly, through lower levels of 
physical activity and changes in dietary quality and/or patterns72,73. In addition, other important 
factors might confound and/or mediate the association between obesity and effort in MDD, such 
as the use of psychotropic medications.  There is a need for longitudinal studies, with carefully 
selected and described samples, to answer these questions. 
There is, however, evidence indicating that circadian rhythms can affect reward 
behavior75,76, dopamine signaling77,78 and glucose/insulin metabolism79-81; and are as well a 
prominent component of the overlap between mood and metabolic disorders40,82,83. The 
potential effects of circadian rhythms should be directly explored and/or accounted for in future 
work in the area. 
In conclusion, we believe that obesity is a result of, and induces, disturbances in 
reward/motivation and cognitive control.  There is a need to parse the substrates that subserve 
motivation/reward disturbance in adults with obesity.  There is an additional need to evaluate 
the disturbance in reward/motivation with a rigorous paradigm i.e. EEfRT.  The results of this 
proposal will also reinforce the brain and body consequences of obesity. 
 
This study is supported by an unrestricted research grant from Bausch Health to the Brain and 
Cognition Discovery Foundation, Toronto, ON.  
 
  
 
 

 
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