CEU Electronic Theses and Dissertations, 2026
| Author | Magas, David |
|---|---|
| Title | Representation of Uncertainty and Recall Precision in Long-Term Episodic and Semantic Memories |
| Summary | Episodic memory has often been characterized as detailed autonoetic awareness of one’s past events. In my dissertation, I reconceptualize episodic memory as part of a general knowledge structure or long-term semantic memory. I offer a common framework in which the recall precision and the representation of uncertainty in short-term and long-term episodic and semantic memory can be investigated. As a result, my work bridges important gaps between perception, long-term episodic and semantic memory, and provides insights into the detailed form in which items in perception and long-term memory are encoded and recalled. In Chapter 2, I analyze recall precision and the representation of uncertainty in perceptual decision-making and in long-term episodic memories without any semantic regularity imposed on them. I show that items in perception and long-term episodic memory are encoded and recalled in a probabilistic manner. In Chapter 3, I organize episodic elements into simple scenes with both perceptual and semantic connections between the elements. I demonstrate that semantic connections are dominant as opposed to perceptual ones in increasing recall precision. Furthermore, I show that the structure in which scene elements are stored in long-term memory corresponds to the recurring input schema of the scenes. In Chapter 4, I introduce overarching semantic regularity into the input and analyze how it affects recall precision and the representation of uncertainty. I show that semantic regularity improves overall recall precision. In addition, I show that this increase was a result of true semantic learning, where people learnt the structure of the input and used that knowledge exclusively in several responses. Furthermore, I point out major individual differences in episodic and semantic learning ability across participants. Lastly, I show that the fundamentally probabilistic representation of individual items does not change despite learning the overarching semantic regularity. In Chapter 5, I analyze the effect of attention on episodic and semantic learning and show that semantic but not episodic learning remains intact with divided attention. |
| Supervisor | Fiser, Jozsef; Lengyel, Mate |
| Department | Cognitive Science Ps |
| Full text | https://www.etd.ceu.edu/2026/magas_david.pdf |
Visit the CEU Library.
© 2007-2025, Central European University