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ERIC Number: EJ945183
Record Type: Journal
Publication Date: 2011-Oct
Pages: 31
Abstractor: As Provided
Reference Count: 104
ISSN: ISSN-0033-295X
A Dynamic Stimulus-Driven Model of Signal Detection
Turner, Brandon M.; Van Zandt, Trisha; Brown, Scott
Psychological Review, v118 n4 p583-613 Oct 2011
Signal detection theory forms the core of many current models of cognition, including memory, choice, and categorization. However, the classic signal detection model presumes the a priori existence of fixed stimulus representations--usually Gaussian distributions--even when the observer has no experience with the task. Furthermore, the classic signal detection model requires the observer to place a response criterion along the axis of stimulus strength, and without theoretical elaboration, this criterion is fixed and independent of the observer's experience. We present a dynamic, adaptive model that addresses these 2 long-standing issues. Our model describes how the stimulus representation can develop from a rough subjective prior and thereby explains changes in signal detection performance over time. The model structure also provides a basis for the signal detection decision that does not require the placement of a criterion along the axis of stimulus strength. We present simulations of the model to examine its behavior and several experiments that provide data to test the model. We also fit the model to recognition memory data and discuss the role that feedback plays in establishing stimulus representations. (Contains 13 figures, 2 tables and 8 footnotes.)
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Ohio