Set Your Goal: Engaging Go/No-Go Active Learning

Computational Modeling of Reinforcement Learning in Depression

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.

Study Overview

• Status: Completed
• Conditions: Depression; Anxiety
• Intervention / Treatment: Behavioral: Go/No-Go Active Learning (GOAL)

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.

• Study Type: Interventional
• Enrollment (Actual): 13
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Illinois
    • Chicago, Illinois, United States, 60611
      • Northwestern University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 21 years to 40 years (Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Go/No-Go Active Learning (GOAL); Adaptation of Behavioral Activation, focused on reinforcement learning strategies.	Behavioral: Go/No-Go Active Learning (GOAL); Behavioral Activation psychotherapy adapted to engage go/no-go learning

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	Models will include a learning rate, a slope of the softmax rule, noise factor, a bias factor to the action-value for 'go', and a Pavlovian factor.	Baseline (Week 0)

Collaborators and Investigators

• Sponsor: Northwestern University
• Investigators: Principal Investigator: Jackie Gollan, Ph.D., Associate Professor of Psychiatry and Behavioral Science

Study record dates

Study Major Dates

• Study Start (Actual): May 1, 2018
• Primary Completion (Actual): March 1, 2019
• Study Completion (Actual): March 1, 2019

Study Registration Dates

• First Submitted: May 14, 2018
• First Submitted That Met QC Criteria: May 24, 2018
• First Posted (Actual): May 29, 2018

Study Record Updates

• Last Update Posted (Actual): June 13, 2022
• Last Update Submitted That Met QC Criteria: June 9, 2022
• Last Verified: June 1, 2022

More Information

Terms related to this study

• Keywords: neuroimaging; reinforcement learning; computational models
• Additional Relevant MeSH Terms: Behavioral Symptoms; Depression
• Other Study ID Numbers: STU00206862

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No