Psychophysical Methods And Signal Detection: Recent Advances In Theory

Abstract

Introduction: A Brief History of SDT Signal detection theory (SDT) represents one of the most prominent scientific developments in psychology of the past 60 years (Dember, 1998; Estes, 2002). Its application to perception began with the use of statistical decision theory for radar detection problems (e.g., Peterson, Birdsall, and Fox, 1954), and efforts to determine the sensitivity of information transmission via a sensitivity measure that was free of response bias (for an early discussion of the historical antecedents of SDT see Swets, 1973). A key insight by the pioneering researchers was that errors of commission in perception tasks are not necessarily the result of guessing, as assumed by threshold theories (Tanner and Swets, 1954). The techniques provided by SDT have found wide application, including domains such as radiology, assessment of memory in clinical populations, and many kinds of monitoring tasks. In general, any categorical decision or diagnostic task can be evaluated using SDT, permitting separate assessment of the capacity of the decision maker to discriminate among categories (defined as perceptual sensitivity, d’) and his or her cognitive bias for selecting one category over another (response criterion or response bias, β). As a statistical model, SDT rests on a set of assumptions. These include the premises that (1) events to be detected (signals) are always embedded in a background of irrelevant sensory information (noise); (2) the distributions of noise and signal-plus-noise are of normal form and equal variance; (3) observers are both sensors and decision makers, and they adopt a criterion of sensory magnitude for deciding whether a given event is a signal or a nonsignal; and (4) measures of perceptual sensitivity (e.g., d’) can be treated as if they were independent of measures of response bias (e.g., β).

Publication Date

1-1-2015

Publication Title

The Cambridge Handbook of Applied Perception Research

Number of Pages

22-38

Document Type

Article; Book Chapter

Personal Identifier

scopus

DOI Link

https://doi.org/10.1017/CBO9780511973017.007

Socpus ID

84954304848 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84954304848

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