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Title: The organization of experiences and its effects on episodic memory and decision-making
Authors: Shin, Yeon Soon
Advisors: Niv, Yael
Norman, Kenneth A
Contributors: Neuroscience Department
Subjects: Neurosciences
Cognitive psychology
Issue Date: 2020
Publisher: Princeton, NJ : Princeton University
Abstract: Idiosyncratic experiences from the past guide our future predictions and decisions in meaningful ways. We generalize what we learned from the past to similar situations. This dissertation investigates how we group our experiences in a way that supports effective retrieval of relevant experiences and generalization from those experiences. I hypothesize that hidden causal structures that are assumed to have generated a set of observable events, called latent causes, serve as a meaningful basis for generalization. In Chapter 2, I first test whether external environmental contexts that have unique sets of features generated from distinct latent causes organize episodic memories. In this study, subjects learned a list of words while performing context-appropriate tasks and recalled the words either in the same or in a different context. I demonstrate that recalling memories in the original learning environmental context facilitates episodic memory retrieval. This effect is larger when the words were judged to be conceptually more relevant to the context, suggesting that integration to the latent causes is important in organizing memories of experiences. To further this idea, in Chapter 3, I propose a framework for grouping and segmenting events in episodic memory that is based on inferring latent causes. This framework can reconcile seemingly contradictory empirical findings, such as memory biases towards both extreme episodes and the average of episodes, by sampling memories within a latent cause (item-level sampling) or across latent causes (cluster-level sampling). In Chapter 4, I test the predictions of cluster-level sampling in social decision making, in which impressions about a group are biased as experiences with the group members are summarized at the level of inferred latent causes. In the Conclusion, I discuss an ongoing project that aims to directly measure the latent-cause inference process and map cognitive constructs onto model parameters. I propose how this latent-cause inference can provide a framework for social cognition where key features such as current beliefs, mental states, and traits are hidden.
Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog:
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Neuroscience

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