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

Sponsor

Northwestern University (Other)

Overall Status

Completed

CT.gov ID

NCT03538535

Collaborator

(none)

Enrollment

Location

Arm

Actual Duration (Months)

1.3

Patients Per Site Per Month

Study Details

Study Description

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.

Condition or Disease	Intervention/Treatment	Phase
Depression Anxiety	Behavioral: Go/No-Go Active Learning (GOAL)	N/A

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 Design

Study Type:

Interventional

Actual Enrollment :

13 participants

Allocation:

N/A

Intervention Model:

Single Group Assignment

Intervention Model Description:

Adapted version of Behavioral Activation psychotherapy designed to optimize decision making and learning.Adapted version of Behavioral Activation psychotherapy designed to optimize decision making and learning.

Masking:

None (Open Label)

Primary Purpose:

Treatment

Official Title:

Computational Modeling of Reinforcement Learning in Depression

Actual Study Start Date :

May 1, 2018

Actual Primary Completion Date :

Mar 1, 2019

Actual Study Completion Date :

Mar 1, 2019

Arms and Interventions

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

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

Outcome Measures

Primary Outcome Measures

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. [Baseline (Week 0)]
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.

Eligibility Criteria

Criteria

Ages Eligible for Study:

21 Years to 40 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Northwestern University	Chicago	Illinois	United States	60611

Sponsors and Collaborators

Northwestern University

Investigators

Principal Investigator: Jackie Gollan, Ph.D., Associate Professor of Psychiatry and Behavioral Science

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Northwestern University

ClinicalTrials.gov Identifier:

NCT03538535

Other Study ID Numbers:

STU00206862

First Posted:

May 29, 2018

Last Update Posted:

Jun 13, 2022

Last Verified:

Jun 1, 2022

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Keywords provided by Northwestern University

reinforcement learning

computational models

neuroimaging

Additional relevant MeSH terms:

Depression

Study Results

No Results Posted as of Jun 13, 2022