Poster No:
1063
Submission Type:
Abstract Submission
Authors:
Wen-Wei Lin1, Ming-Tsung Tseng2
Institutions:
1Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan, 2Graduate Institute of Brain and Mind Sciences, National Taiwan University, Taipei, Select Region
First Author:
Wen-Wei Lin
Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine
Taipei, Taiwan
Co-Author:
Ming-Tsung Tseng
Graduate Institute of Brain and Mind Sciences, National Taiwan University
Taipei, Select Region
Introduction:
Reinforcement learning requires individuals to balance exploring uncertain options with exploiting predictable ones to link decisions with outcomes. In everyday life, choices often involve both reward and punishment, highlighting the need to understand how these learning processes interact to guide adaptive behavior. When a choice in punishment learning is also associated with reward learning, reward associations may suppress exploration and impair punishment learning, especially in individuals with a strong positivity bias. Conversely, punishment associations may enhance exploration in reward learning, disrupting reward performance in loss-averse individuals. This study aims to characterize the interaction between reward and punishment learning in humans.
Methods:
In three experiments (n = 87), participants completed a probabilistic instrumental learning task with binary choices during 3T functional MRI scanning. Some choices focused on reward or punishment learning, while others involved both. Participants were instructed to maximize rewards (monetary gain) and avoid punishment (monetary loss with painful stimulation). Loss aversion was assessed using a separate risky decision-making task. Computational modeling was applied to examine whether choice behavior reflected loss aversion.
Results:
We found that when choices involved only one type of learning (either reward or punishment), reward learning entailed less exploratory behavior than punishment learning, indicating a more exploitative strategy for reward maximization and a more exploratory approach for minimizing punishment. However, when both types of learning were involved, reward learning performance (but not punishment learning) declined, with the magnitude of the decline depending on the size of potential losses. This decline was further predicted by increased exploration linked to punishment associations in reward-learning choices, as well as enhanced BOLD responses in exploration-related prefrontal regions observed in functional MRI. Additionally, individual loss aversion predicted the extent of increased exploration.
Conclusions:
These findings suggest that when a choice involves both reward and punishment learning histories, increased exploration driven by punishment associations may disrupt the optimal exploration-exploitation balance necessary for effective reward learning, leading to reward maximization failure. In this context, loss aversion plays a key role in shaping choice behavior.
Higher Cognitive Functions:
Decision Making
Learning and Memory:
Learning and Memory Other 2
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 1
Keywords:
Computational Neuroscience
FUNCTIONAL MRI
Learning
Pain
1|2Indicates the priority used for review
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
I accept
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information.
Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
I do not want to participate in the reproducibility challenge.
Please indicate below if your study was a "resting state" or "task-activation” study.
Task-activation
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Not applicable
Please indicate which methods were used in your research:
Functional MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
SPM
Provide references using APA citation style.
not applicable
No