Abstract

The Autobiographical Implicit Association Test (aIAT) is a reaction time-based methodology to assess one's recognition of the truth value of propositions about an autobiographical episode. This study introduced pupillometry to examine its utility as an additional measure of aIAT. Participants blindly chose one of two cards and memorized it. They then underwent the aIAT to assess the cards they chose. The pupil diameter was larger in the block in which sentences related to the chosen card shared the same response key with sentences describing false events than the block in which sentences related to the chosen card shared the same response key with true-event sentences. Although preliminary, pupil measurement also yielded high efficiency in discriminating the chosen card. These results indicate that pupillometry can be used as a measure of aIAT.

Highlights

  • The autobiographical Implicit Association Test is a variant of the Implicit Association Test (IAT; Greenwald et al, 1998), which is applied to forensic settings such as crime investigations by law enforcement

  • The present study conducted an Association Test (aIAT) experiment to examine the utility of pupillometry in the IAT

  • AIAT and Pupillometry sensitive to cognitive effort, we predicted that pupil diameter was larger in the incompatible block than in the compatible block, mirroring the conventional reaction time (RT)-based IAT

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Summary

Introduction

The autobiographical Implicit Association Test (aIAT; Sartori et al, 2008) is a variant of the Implicit Association Test (IAT; Greenwald et al, 1998), which is applied to forensic settings such as crime investigations by law enforcement. It examines one’s recognition of the truth value of propositions about an autobiographical episode (Verschuere et al, 2015). In an incompatible block, true sentences share the same response key with sentences about the fictional event. It should be noted that several factors, such as faking, use of negative sentences, and negative labels, could affect the accuracy of aIAT (Verschuere et al, 2009, 2015; Agosta et al, 2011)

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