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Anhedonia (the lack of pleasure in normally pleasurable things) is a common symptom of major depressive disorder (MDD), and it may impact how patients with depression experience reward. Understanding how anhedonia is related to the experience of reward may help improve how depression is treated. Computer tasks can be used to measure how reward is experienced, and these measures might be able to predict things like who is likely to become depressed, or who will respond to antidepressant medication. Studying the relationship between anhedonia and reward in patients with depression might also tell us something about how to improve diagnosis and treatment of other psychiatric disorders.This is an open label controlled treatment study lasting 8 weeks. The brain scans will be used to find changes in brain areas that may be related to how people perform on the tasks. The investigators goal is to use this information to help us find a reliable predictor that can be used to guide MDD treatment.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Treatment | Active Comparator | Patients in this arm will receive treatment with desvenlafaxine for 8 weeks. |
|
| Healthy Control | No Intervention | Patients in this arm are healthy controls and will not receive any medication. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Desvenlafaxine | Drug | Patients will be provided 50mg dose of desvenlafaxine for 1 week titrated up to 100mg dose of desvenlafaxine for 7 weeks. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Measuring Reward association and valuation using the Reward Association Task | Based on signal detection theory, it evaluates response bias as a function of prior reward and permits an objective assessment of disorder-related sensitivity to reward. To evaluate the how the 6 facets of reward are related to each other in unmedicated MDD patients in order to develop a clearer understanding of reward pathways | Change from Baseline at 8 Weeks |
| Measuring Expectation using a prediction error task, to measure learning and choosing, during functional Magnetic Resonance Imaging (fMRI) | This distinction was included in the design in order to dissociate potentially different neural circuits subserving learning reward associations and using them to guide behavior. To evaluate the how the 6 facets of reward are related to each other in unmedicated MDD patients in order to develop a clearer understanding of reward pathways | Change from Baseline at 8 Weeks |
| Anticipation of reward using the monetary incentive delay during fMRI | This task was designed to disentangle anticipatory vs. consummatory phases of reward processing. To evaluate the how the 6 facets of reward are related to each other in unmedicated MDD patients in order to develop a clearer understanding of reward pathways | Change from Baseline at 8 Weeks |
| Motivation/effort using the Cued-Reinforcement Reaction Time Task and the EEfRT task. | The Cued-Reinforcement Reaction Time Task (CRRT) provides an evaluation of reward-based reaction time speed as an index of incentive motivation.The EEfRT task allows analysis of the predictive value of reward probability and magnitude on effort-based decision making. To evaluate the how the 6 facets of reward are related to each other in unmedicated MDD patients in order to develop a clearer understanding of reward pathways | Change from Baseline at 8 Weeks |
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Inclusion/exclusion criteria for MDD patients (n=40) are as follows:
Inclusion Criteria
Exclusion Criteria
Inclusion/exclusion criteria for Healthy Controls (n=20) are as follows:
Inclusion Criteria
Exclusion Criteria
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| Name | Affiliation | Role |
|---|---|---|
| Sakina Rizvi, PhD | Unity Health Toronto | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| St. Michael's Hospital | Toronto | Ontario | M5B 1M8 | Canada |
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| Type | Date | Date Unknown |
|---|---|---|
| Release | Dec 15, 2022 | |
| Reset | Oct 11, 2023 |
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| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Dec 15, 2022 | Oct 11, 2023 |
| ID | Term |
|---|---|
| D003863 | Depression |
| D059445 | Anhedonia |
| ID | Term |
|---|---|
| D001526 | Behavioral Symptoms |
| D001519 | Behavior |
| D019954 | Neurobehavioral Manifestations |
| D009461 | Neurologic Manifestations |
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| ID | Term |
|---|---|
| D000069468 | Desvenlafaxine Succinate |
| ID | Term |
|---|---|
| D003511 | Cyclohexanols |
| D000441 | Hexanols |
| D005233 | Fatty Alcohols |
| D000438 | Alcohols |
| D009930 |
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| Pleasure/Liking using the monetary incentive delay task in an fMRI |
This task was designed to disentangle anticipatory vs. consummatory phases of reward processing. To evaluate the how the 6 facets of reward are related to each other in unmedicated MDD patients in order to develop a clearer understanding of reward pathways. To evaluate the how the 6 facets of reward are related to each other in unmedicated MDD patients in order to develop a clearer understanding of reward pathways |
| Change from Baseline at 8 Weeks |
| Feedback integration using the Probabilistic Reversal Learning task during fMRI | participants are presented with a choice of two stimuli. Based on their first choice, the selected stimulus will be rewarded with a high probability, while the other will be rewarded with a low probability.To evaluate the how the 6 facets of reward are related to each other in unmedicated MDD patients in order to develop a clearer understanding of reward pathways | Change from Baseline at 8 Weeks |
| D009422 |
| Nervous System Diseases |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| Organic Chemicals |
| D003510 | Cyclohexanes |
| D003516 | Cycloparaffins |
| D006840 | Hydrocarbons, Alicyclic |
| D006844 | Hydrocarbons, Cyclic |
| D006838 | Hydrocarbons |
| D010636 | Phenols |
| D001555 | Benzene Derivatives |
| D006841 | Hydrocarbons, Aromatic |
| D008055 | Lipids |