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A multinomial modelling approach to face identity recognition during instructed threat
To organise future behaviour, it is important to remember both the central and contextual aspects of a situation. We examined the impact of contextual threat or safety, learned through verbal instructions, on face identity recognition. In two studies (N = 140), 72 face-context compounds were present...
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Published in: | Cognition and emotion 2021-10, Vol.35 (7), p.1302-1319 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | To organise future behaviour, it is important to remember both the central and contextual aspects of a situation. We examined the impact of contextual threat or safety, learned through verbal instructions, on face identity recognition. In two studies (N = 140), 72 face-context compounds were presented each once within an encoding session, and an unexpected item/source recognition task was performed afterwards (including 24 new faces). Hierarchical multinomial processing tree modelling served to estimate individual parameters of item (face identity) and source memory (threat or safety context) as well as guessing behaviour. Results show that language was highly effective in establishing threatening and safe context conditions. In Study 1, a fleeting picture stream (1 s per picture) led to poor item and source recognition. Prolonged presentation times (Study 2 with 6 s per picture) improved face memory but no contextual modulation was observed. Thus, incidental face learning was surprisingly poor and rapidly changing contextual settings might have interfered with the accurate encoding of face identity information and item-source binding. |
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ISSN: | 0269-9931 1464-0600 |
DOI: | 10.1080/02699931.2021.1951175 |