Impairment of arbitration between model-based and model-free reinforcement learning in obsessive–compulsive disorder

Author:

Ruan Zhongqiang,Seger Carol A.,Yang Qiong,Kim Dongjae,Lee Sang Wan,Chen Qi,Peng Ziwen

Abstract

IntroductionObsessive–compulsive disorder (OCD) is characterized by an imbalance between goal-directed and habitual learning systems in behavioral control, but it is unclear whether these impairments are due to a single system abnormality of the goal-directed system or due to an impairment in a separate arbitration mechanism that selects which system controls behavior at each point in time.MethodsA total of 30 OCD patients and 120 healthy controls performed a 2-choice, 3-stage Markov decision-making paradigm. Reinforcement learning models were used to estimate goal-directed learning (as model-based reinforcement learning) and habitual learning (as model-free reinforcement learning). In general, 29 high Obsessive–Compulsive Inventory-Revised (OCI-R) score controls, 31 low OCI-R score controls, and all 30 OCD patients were selected for the analysis.ResultsObsessive–compulsive disorder (OCD) patients showed less appropriate strategy choices than controls regardless of whether the OCI-R scores in the control subjects were high (p = 0.012) or low (p < 0.001), specifically showing a greater model-free strategy use in task conditions where the model-based strategy was optimal. Furthermore, OCD patients (p = 0.001) and control subjects with high OCI-R scores (H-OCI-R; p = 0.009) both showed greater system switching rather than consistent strategy use in task conditions where model-free use was optimal.ConclusionThese findings indicated an impaired arbitration mechanism for flexible adaptation to environmental demands in both OCD patients and healthy individuals reporting high OCI-R scores.

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

National Science and Technology Major Project

Publisher

Frontiers Media SA

Subject

Psychiatry and Mental health

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3