Computerized latency data correspond with Iowa Gambling Task responses in healthy individuals
Peukert, Erika
Mahler, Aniko
Halasz, Jozsef
Petőné Csuka, Ildikó
Simon, Gyula
2026-02-11T09:29:52Z
2026-02-11T09:29:52Z
2022
http://hdl.handle.net/20.500.14044/37422
In recent years, the most important decision making task was the so-called Iowa Gambling Task, to interpret reward sensitivity and the ability to realize long-term consecquences in a card selection game. Surprisingly, the importance in basic and clinical research in relation with the working of the orbitofrontal cortex did not result latency data in this very important, clinically used context. In the present paper, a computerized version of the Iowa Gambling Task was used focusing on latency issues. The aim of the present study was to describe deck-selection-latency and deck-switching data within the Iowa Gambling Task after selecting different blow-like cards throughout the test. General linear model was used to establish statistical differences within 500 responses. High and low blow card selections resulted in higher deck switching responses compared to non-blow card selections. Interestingly, increased latency was only observed in the case of high blow card selections. While the age was accompanied by significantly higher latency data, card number had the opposite effect. Our data indicate the importance of studying latency data in the interpretation of the working of prefrontal cortex via the Iowa Gambling Task.
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pdf
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Computerized latency data correspond with Iowa Gambling Task responses in healthy individuals
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Open access
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Óbudai Egyetem
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2022. November 17.
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Székesfehérvár
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Alba Regia Műszaki Kar
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Óbudai Egyetem
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Műszaki tudományok - informatikai tudományok
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beneficial strategy
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computerized latency data
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decision making
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iowa gambling task
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prefrontal cortex
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Konferenciaközlemény
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AIS 2022 – 17th International Symposium on Applied Informatics and Related Areas
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local.tempfieldCollections
Könyvrészletek
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5.
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Kiadói változat
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5 p.
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PROCEEDINGS of 17th International Symposium on Applied Informatics and Related Areas