The Characteristics and Neural Substrates of Feedback-based Decision Process in Recognition Memory

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The judgment of prior stimulus occurrence, generally referred to as item recognition, is perhaps the most heavily studied of all memory skills. A skilled recognition observer not only recovers high fidelity memory evidence, he or she is also able to flexibly modify how much evidence is required for affirmative responding (the decision criterion) depending upon whether the context calls for a cautious or liberal task approach. The ability to adaptively adjust the decision criterion is a relatively understudied recognition skill, and the goal of this thesis is to examine reinforcement learning mechanisms contributing to recognition criterion adaptability. In Chapter 1, I review a measurement model whose theoretical framework has been successfully applied to recognition memory research (i.e., Signal Detection Theory). I also review major findings in the recognition literature examining the adaptive flexibility of criteria. Chapter 2 reports behavioral experiments that examine the sensitivity of decision criteria to trial-by-trial feedback by manipulating feedback validity in a potentially covert manner. Chapter 3 presents another series of behavioral experiments that used even subtler feedback manipulations based on predictions from reinforcement learning and category learning literatures. The findings suggested that feedback induced criterion shifts may rely upon procedural learning mechanisms that are largely implicit. The data also revealed that the magnitudes of induced criterion shifts were significantly correlated with personality measures linked to reward seeking outside the laboratory. In Chapter 4 functional magnetic resonance imaging (fMRI) was used to explore possible neurobiological links between brain regions traditionally linked to reinforcement processing, and recognition decisions. Prominent activations in striatum tracked the intrinsic goals of the subjects with greater activation for correct responding to old items compared to correct responding to new items during standard recognition testing. Furthermore, the pattern was amplified and reversed by the addition of extrinsic rewards. Finally, activation in ventral striatum tracked individual differences in personality reward seeking measures. Together, the findings further support the idea that a reinforcement learning system contributes to recognition decision-making. In the final chapter, I review the main implications arising from the research and suggest future research that could bolster the current results and implications.






Han, Sanghoon (2008). The Characteristics and Neural Substrates of Feedback-based Decision Process in Recognition Memory. Dissertation, Duke University. Retrieved from


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