NDLI: Physiological arousal in processing recognition information

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Physiological arousal in processing recognition information

Content Provider	Open Access Library (OALib)
Author	Guy Hochman Shahar Ayal Andreas Gloeckner
Abstract	The recognition heuristic (RH; Goldstein and Gigerenzer, 2002) suggests that, when applicable, probabilistic inferences are based on a noncompensatory examination of whether an object is recognized or not. The overall findings on the processes that underlie this fast and frugal heuristic are somewhat mixed, and many studies have expressed the need for considering a more compensatory integration of recognition information. Regardless of the mechanism involved, it is clear that recognition has a strong influence on choices, and this finding might be explained by the fact that recognition cues arouse affect and thus receive more attention than cognitive cues. To test this assumption, we investigated whether recognition results in a direct affective signal by measuring physiological arousal (i.e., peripheral arterial tone) in the established city-size task. We found that recognition of cities does not directly result in increased physiological arousal. Moreover, the results show that physiological arousal increased with increasing inconsistency between recognition information and additional cue information. These findings support predictions derived by a compensatory Parallel Constraint Satisfaction model rather than predictions of noncompensatory models. Additional results concerning confidence ratings, response times, and choice proportions further demonstrated that recognition information and other cognitive cues are integrated in a compensatory manner.
ISSN	19302975
Journal	Judgment and Decision Making
Publisher	Society for Judgment and Decision Making
Publisher Date	2010-01-01
Access Restriction	Open
Subject Keyword	Recognition heuristic Physiological arousal Noncompensatory models. Affect Parallel constraint satisfaction
Content Type	Text
Resource Type	Article
Subject	Economics and Econometrics Decision Sciences Applied Psychology

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