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Episodic Indexing: A Model of Memory for Attention Events
Author(s) -
Altmann Erik M,
John Bonnie E.
Publication year - 1999
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1207/s15516709cog2302_1
Subject(s) - episodic memory , computer science , search engine indexing , trace (psycholinguistics) , recall , event (particle physics) , object (grammar) , encoding (memory) , symbol (formal) , information retrieval , artificial intelligence , cognitive psychology , natural language processing , psychology , cognition , linguistics , programming language , philosophy , physics , quantum mechanics , neuroscience
People often remember what they attend to in the world. Such memory can be cast as a kind of mental catalog or index of attended objects. To investigate how such an index is acquired and used, protocol data were collected from a programmer who scrolled to off‐screen objects from time to time as she worked. These protocol data were modeled using Soar, which constrains how the index is constructed. In the model, an index entry is an episodic trace encoded during attention. The trace associates the attention event with a time symbol denoting the event's occurrence. Later, the model can ask itself whether it saw that object by calling to mind an image of the attention event. If this image retrieves a time symbol, then the model infers that the object exists and can reason about bringing the object back into view. Episodic indexing is a theory of these encoding and retrieval processes. It posits that information about attention events is encoded automatically, but that retrieval requires effort and knowledge. Episodic indexing is congruent with a range of results on episodic and temporal codes and recognition and recall processes. It incorporates source monitoring (Johnson, Hashtroudi, & Lindsay, 1993) and is a simple and pervasive form of long‐term working memory (Ericsson & Kintsch, 1995).