The reward positivity is sensitive to affective liking

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Psychiatry

Background:

• The Reward Positivity (RewP) is an EEG signal linked to reward receipt.
• It is thought to reflect positive prediction errors in reinforcement learning.
• However, RewP is also influenced by affect, suggesting a broader role.

Purpose of the Study:

• To investigate how affect processing influences the RewP.
• To explore the computational role of RewP in integrating reward surprise and hedonic value.

Main Methods:

• Two experiments were conducted using reinforcement learning tasks.
• Experiment 1 varied reward type (points vs. liked images).
• Experiment 2 manipulated reinforcement difficulty and affective image content.

Main Results:

• RewP amplitude correlated with subjective liking of rewards, particularly when reinforcement was difficult.
• No differences in RewP were found for different reward types alone.
• Liking significantly modulated RewP amplitude in the 'hard' reinforcement condition.

Conclusions:

• The RewP reflects both reward prediction errors and hedonic liking.
• It serves as a neural mechanism for computing multidimensional reward value.
• This highlights the integration of surprise and subjective appeal in decision-making.