Computational Modeling of Reinforcement Learning in Depression
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 13
- 试验地点
- 2
- 主要终点
- 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.
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Treatment
- 盲法
- None
入排标准
- 年龄范围
- 21 Years 至 40 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •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
结局指标
主要结局
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.
时间窗: 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.
次要结局
未报告次要终点