Clinical trial NCT03538535: Set Your Goal: Engaging Go/No-Go Active Learning
Official title: Computational Modeling of Reinforcement Learning in Depression
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Depression
Anxiety
Keywords: reinforcement learning
computational models
neuroimaging
Lead sponsor: Northwestern University
Sponsor class: OTHER
First posted: 2018-05-29
Enrollment: 13
Sex: ALL
Minimum age (years): 21
Maximum age (years): 40
Standard ages: ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Adapted version of Behavioral Activation psychotherapy designed to optimize decision making and learning.
Primary purpose: TREATMENT

Brief summary: This study will test a computational model reinforcement learning in depression and anxiety and test the extent to which the computational model predicts response to an adapted version of behavioral activation psychotherapy. The model will be based on a data from a computer task of reinforcement learning during 3T functional magnetic resonance imaging at baseline.

Detailed description: The dysfunction of reinforcement learning is emerging as a transdiagnostic dimension of mood and anxiety. Computational models of reinforcement learning may expedite our ability to identify predictors of response, thereby improving efficacy rates. We will will, first, examine the neural substrates of reinforcement learning in depression and anxiety, and, second, test a computational model of reinforcement learning as a predictor of response to an adapted version of behavioral activation psychotherapy. Subjects (N=10) will be enrolled in a two week evaluation, followed with a nine week weekly intervention program. Assessments will be conducted at baseline, and during the intervention as the 3-, 6-, 9-week follow-ups. Reinforcement learning will be measured using 3T magnetic resonance imaging during a computer task. All other measures include structured clinical interviews, questionnaires, and computer tasks.

Eligibility criteria: Inclusion Criteria:

* Between the ages of 21 and 40
* Physically healthy
* Right handed
* Normal or corrected to normal vision
* Scores equal or higher of (a) 24 on Inventory of Depressive Symptomatology, Self Report, or (b) 15 on the Generalized Anxiety Disorder Self Report.

Exclusion Criteria:

* Not currently in therapy or taking medications for anxiety or depression
* No contraindications for the magnetic resonance scan (claustrophobic)
* No history of head trauma, seizures, loss of consciousness
* Not taking hormone replacement, not pregnant
* No imminent suicidality
* No report of excessive alcohol or drug use in past three months

Primary outcomes:
measure: Integrated Bayesian Information Criterion (BIC) score based on models using modified Q-learning models with two pairs of action values (go and no-go) for each state.
timeFrame: Baseline (Week 0)
Secondary outcomes:
Other outcomes:
Locations:
city: Chicago
country: United States
facility: Northwestern University
state: Illinois
Study officials:
affiliation: Associate Professor of Psychiatry and Behavioral Science
name: Jackie Gollan, Ph.D.
role: PRINCIPAL_INVESTIGATOR
References: