The Effects of Self-Relevance on Neural Learning Signals Indexing Attention, Perception, and Learning




Rocha Hammerstrom, Mathew

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Humans tend to preferentially process information relevant to themselves. For instance, in experiments where participants learn to manipulate stimuli referenced to themselves or someone else, participants exhibit larger reward processing signals for themselves. Additionally, attention and perception are biased not only towards one’s self but those related to them. However, the aspect of processing information related to known-others has not been addressed in reward learning. Here, I sought to address this issue. Specifically, I recorded electroencephalographic (EEG) data from 15 undergraduate student participants who played a simple two-choice “bandit” gambling game where a photo presented before each gamble indicated whether it benefited either the participant, an individual they knew, or a stranger. EEG data from 64 electrodes on a standard 10-20 layout were analyzed for event-related potentials (ERPs) elicited by target photos and gambling outcomes. Post experiment, I examined the relationship between relatedness and the amplitude reward learning ERPs, namely the reward positivity and the P300, with one-way repeated measures analyses of variance. My results demonstrate that the amplitudes of reward learning ERPs are sensitive to the target of a gamble. A secondary goal of this research was to determine if these differences could be explained by attentional and perceptual responses to cues of who a given gamble was for. Indeed, stepwise linear regression analyses identified the P2, N2, and P3 indexed relevance to self as predictors of resultant reward signals. My findings provide further evidence that a reward learning system within the medial-frontal cortex is sensitive to others with varying self-relevance, which may be a function of biases in attention and perception.



Electroencephalography(EEG), Reward Learning, Self-Relevance