Effects of depression on reinforcement learning = 우울증에서의 손상된 강화학습 기제에 관한 연구

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Depression is characterized by deficits in the reinforcement learning (RL) process. Although many computational and neural studies have extended our knowledge of the impact of depression on RL, most focus on habitual control (model-free RL), yielding a relatively poor understanding of goal-directed control (model-based RL) and arbitration control to find a balance between the two. We investigate the effects of depression on goal-directed and habitual control in the prefrontal–striatal circuitry. We find that depression is associated with attenuated state and reward prediction error representation in the insula and caudate, a disruption of arbitration control in the predominantly inferior lateral prefrontal cortex and frontopolar cortex, and suboptimal value–action conversion. These findings fully characterize how depression influences different levels of RL, challenging previous conflicting views that depression simply influences either habitual or goal-directed control. Our study creates possibilities for various clinical applications, such as early diagnosis and behavioral therapy design.
Advisors
Lee, Sang Wanresearcher이상완researcherJeong, Jaeseungresearcher정재승researcher
Description
한국과학기술원 :뇌인지공학프로그램,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 뇌인지공학프로그램, 2019.2,[ii, 35 p. :]

Keywords

Depression▼areinforcement learning▼aarbitration▼acomputational psychiatry▼aprefrontal cortex; 우울증▼a강화학습▼a중재과정▼a계산정신의학▼a전두엽

URI
http://hdl.handle.net/10203/265996
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843068&flag=dissertation
Appears in Collection
BiS-Theses_Master(석사논문)
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