Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-24 @ 10:35 PM
Ignite Modification Date:
2025-12-24 @ 10:35 PM
NCT ID:
NCT03538535
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.
Study:
NCT03538535
Study Brief:
Protocol Section:
NCT03538535