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SARKAE - Modeling the Co-Evolution of Event Memory and Knowledge

SARKAE – Modeling the Co-Evolution of Event Memory and Knowledge Angela B. Nelson (a2nelson@ucsd.edu) Department of Political Science, University of California San Diego, 9500 Gilman Dr. #0521 La Jolla, CA 92093 USA Richard M. Shiffrin (shiffrin@indiana.edu) Department of Psychological & Brain Sciences, Indiana University, 1101 E. Tenth Street Bloomington, IN 47405 USA Abstract the context of the experimental setting, are added to the lexical representation of the word. When the studied word is then presented for perceptual identification, the context tends to be similar to that at study, increasing the match of the probe cues to the lexical trace, predicting a variety of measurable effects that match those observed. In other words, the knowledge that a subject has about a stimulus, and the inclusion in that knowledge of factors like the experimental context, affect the way that a stimulus is perceived. There are many models of the storage and retrieval of event memories, and sometimes the addition to existing knowledge of information from recent events (e.g. - Raaijmakers & Shiffrin, 1981, Shiffrin & Steyvers, 1997, Howard & Kahana, 2002, Anderson, 1983). The temporal context model of Howard & Kahana for example provides an explanation for recency and contiguity effects through the storage of both item information and recent contextual information. Other models, such as the ACT-R model of Anderson (1983) also provide eloquent representations of memory storage and retrieval. A few models attempt to explain aspects of the way events produce knowledge, especially for aspects of the role played by words in language (e.g. McClelland & Rumelhart, 1981). However, most of the prior research has been aimed to explain memory and learning when knowledge has already formed (to various degrees). Previous work by Reder et al. has examined the development of knowledge on a set of pseudowords, and used the dual-process SAC model to explain their findings. Although highly relevant and useful in the development of our research, the training study and modeling by Reder et al. did not explicitly model the growth of new knowledge. Our aim is the development of a model that begins to explain the interacting growth of event memory and knowledge, as they influence both memory storage and retrieval. This co-evolution of the two systems was the focus of the REM-II model, created by Mueller and Shiffrin (2006). In this model, knowledge (or semantic memory) is represented as an accumulation of the co-occurrence of features: Features that are present in an episodic event are coded as occurring together in a matrix representation of semantic memory. REM-II is a quite powerful model, but a simplified version is sufficient to explain the basic concepts We present an overview of a model for the co-evolution of knowledge and event memory. The model, termed SARKAE (Storing and Retrieving Knowledge and Events), describes the development of knowledge and event memories as an interactive process: knowledge is formed through the accrual of individual events, and the storage of an individual episode is dependent on prior knowledge. We reference two experiments which provide data to inform our theory: these studies involve the development of new knowledge, and then testing in transfer tasks involving episodic memory, retrieval from knowledge, and perception. The results of the transfer tasks indicate a substantial role of pure frequency or raw exposure, in opposition to the contextual diversity accounts of frequency suggested by Adelman et al (2006). An overview of the SARKAE model is presented. The model is able to account for the effects of frequency in the absence of contextual diversity. Keywords: episodic memory; semantic memory; learning; perception; Bayesian models. Introduction The processes involved in the accumulation of knowledge and the formation of event memories are interdependent. Almost every study since the 1890s has shown that the way episodic (or event) memories are encoded depends on the knowledge (or semantic memory) of the individual who is encoding them. Conversely, an individual’s knowledge must be formed through the episodes they encounter; this idea was the basis of the REM model’s account of priming (Shiffrin & Steyvers, 1997). These interdependent processes create a feedback loop in which knowledge and episodic memory formation develop together over lifelong learning. Studies of memory and perception in the recent past have provided strong support for the idea that memory processes are robustly influenced by prior experience with the to-be- remembered content. Priming studies, for example, have shown that prior study of a word affects how well that word is identified in a forced choice perceptual identification task (Ratcliff & McKoon, 1997). The REMI model of Schooler, Shiffrin, and Raaijmakers (2001) accounts for these effects through a process in which the lexical representation (or knowledge) of the word is changed through prior study (the “prime”); when a word is studied an event memory is formed, but in addition, novel features of the event, such as