Signal detection: applying analysis methods from psychology to animal behaviour

Author:

Sumner Christian J.1ORCID,Sumner Seirian2ORCID

Affiliation:

1. Department of Psychology, Nottingham Trent University, 50 Shakespeare Street, Nottingham NG1 4FQ, UK

2. Centre for Biodiversity and Environmental Research, Department of Genetics Evolution and Environment, Division of Biosciences, University College London, Gower Street, London WC1E 6BT, UK

Abstract

Conspecific acceptance thresholds (Reeve 1989 Am. Nat. 133 , 407–435), which have been widely applied to explain ecological behaviour in animals, proposed how sensory information, prior information and the costs of decisions determine actions. Signal detection theory (Green & Swets 1966 Signal detection theory and psychophysics ; SDT), which forms the basis of CAT models, has been widely used in psychological studies to partition the ability to discriminate sensory information from the action made as a result of it. In this article, we will review the application of SDT in interpreting the behaviour of laboratory animals trained in operant conditioning tasks and then consider its potential in ecological studies of animal behaviour in natural environments. Focusing on the nest-mate recognition systems exhibited by social insects, we show how the quantitative application of SDT has the potential to transform acceptance rate data into independent indices of cue sensitivity and decision criterion (also known as the acceptance threshold). However, further tests of the assumptions underlying SDT analysis are required. Overall, we argue that SDT, as conventionally applied in psychological studies, may provide clearer insights into the mechanistic basis of decision making and information processing in behavioural ecology. This article is part of the theme issue ‘Signal detection theory in recognition systems: from evolving models to experimental tests’.

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology

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