Measuring target detection performance in paradigms with high event rates

Alexandra Bendixen, Søren K Andersen

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

OBJECTIVES: Combining behavioral and neurophysiological measurements inevitably implies mutual constraints, such as when the neurophysiological measurement requires fast-paced stimulus presentation and hence the attribution of a behavioral response to a particular preceding stimulus becomes ambiguous. We develop and test a method for validly assessing behavioral detection performance in spite of this ambiguity. METHODS: We examine four approaches taken in the literature to treat such situations. We analytically derive a new variant of computing the classical parameters of signal detection theory, hit and false alarm rates, adapted to fast-paced paradigms. RESULTS: Each of the previous approaches shows specific shortcomings (susceptibility towards response window choice, biased estimates of behavioral detection performance). Superior performance of our new approach is demonstrated for both simulated and empirical behavioral data. Further evidence is provided by reliable correspondence between behavioral performance and the N2b component as an electrophysiological indicator of target detection. CONCLUSIONS: The appropriateness of our approach is substantiated by both theoretical and empirical arguments. SIGNIFICANCE: We demonstrate an easy-to-implement solution for measuring target detection performance independent of the rate of event presentation. Thus overcoming the measurement bias of previous approaches, our method will help to clarify the behavioral relevance of different measures of cortical activation.
Original languageEnglish
Pages (from-to)928-940
Number of pages13
JournalClinical Neurophysiology
Volume124
Issue number5
Early online date21 Dec 2012
DOIs
Publication statusPublished - May 2013

Keywords

  • signal detection theory (SDT)
  • continuous simulus presentation
  • discrimination
  • sensitivity (d)
  • response bias
  • undefined observation interval

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