Psychology ETDs
Publication Date
Fall 11-7-2023
Abstract
Reinforcement learning (RL) enables agents to learn through interaction with their environment. This empowers individuals to optimize actions in complex and dynamic settings. The component of event related potential (ERP) termed as the Reward Positivity (RewP) evidently signifies a fundamental reward prediction error (RPE) associated with rewards. This characteristic implies that it represents a fundamental computational process in the assessment of RL. When a reward is particularly pleasurable or liked by an individual, it tends to elicit an amplified RewP signal, reflecting the heightened positive affect. RPE arises from disparities between anticipated and actual rewarding outcomes and is known to strongly impact the RewP. Additionally, the RewP is subject to modulation by both transient emotional states and enduring dispositional traits. This observation suggests a more intricate computational function for the RewP beyond its straightforward signaling of RPE. Theoretical frameworks and empirical investigations postulate that depression encompasses compromised responsiveness to rewards and a deficiency in the processing of rewarding stimuli. This deficiency may arise from diminished neural responsiveness to hedonic rewards, thereby hampering the affective encoding of reward-associated information (EEG-RPE coupling). However, no study till date has directly examined this relationship. The aim of this research could gain insights by investigating the RewP as it has previously shown to be associated with the reduced reward sensitivity in individuals with depression, as well as with EEG-RPE coupling. In the current study, participants, screened as depressed individuals (DEP) and healthy controls (CTL) by Beck Depression Inventory (BDI) Scale, performed both a doors task and an affective RL State task. Through our affective RL State task, we examined “liking” aspect of reward processing by utilizing affective vs. ambivalent categories of images (puppy vs. cow). We first showed that the DEP group had a significantly attenuated RewP compared to CTL in the door task consistent with the findings of existent literature. Next, our results showed that the depression severity did not modulate the RewP to hedonically affective imageries in the DEP group. Subsequently, we found that liking was not associated with the RewP and reward-related delta power to affective stimuli. Lastly, our results showed that the affective information encoding (EEG-RPE) was significantly modulated by depression severity in the DEP group. Investigating the RewP and RPE in clinical cohorts such as individuals with depression is imperative given their direct association with anhedonia, a pivotal symptom characteristic of this disorder.
Degree Name
Psychology
Level of Degree
Doctoral
Department Name
Psychology
First Committee Member (Chair)
James F. Cavanagh, Ph.D., Chairperson
Second Committee Member
Jeremy Hogeveen, Ph.D.
Third Committee Member
Darin R. Brown, Ph.D.
Fourth Committee Member
Davin Quinn, M.D.
Language
English
Keywords
Reward Positivity, Reward Prediction Error, Depression, Reinforcement learning, Affective liking
Document Type
Dissertation
Recommended Citation
Singh, Garima. "Affective Liking Influences Reward Processing in Depression: A Computational EEG Approach." (2023). https://digitalrepository.unm.edu/psy_etds/439