The Department of Cognitive Science
cordially invites you to the public defense of the PhD thesis
Representation of Uncertainty and Recall Precision in Long-Term Episodic and Semantic Memories
by
Dávid Ádám Magas
THURSDAY, SepteMber
11, 4
P.M. CET
Room C322 (CEU,
Quellenstrasse 51, 1100 Vienna)
Join Zoom Meeting
https://ceu-edu.zoom.us/j/93244559610?pwd=24NXxnQ9bYEv3Pc7f26p70fvX2JoVF.1
Meeting ID: 932 4455 9610 Passcode: 488643
PRIMARY SUPERVISOR: József Fiser (CEU)
SECONDARY SUPERVISOR: Máté Lengyel (CEU)
Members of the Dissertation Committee:
Ernő Téglás, Chair, CEU
Professor
Pernille Hemmer (Rutgers University)
as
External examiner
Professor
Timothy Brady (UC San Diego) as External examiner
*Anyone not affiliated with CEU wishing to attend in-person in Vienna
must RSVP here
to get access to the lecture hall.
ABSTRACT |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, 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.
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