Development of Novel Tasks to Assess Outcome-Specific and General Pavlovian-to-Instrumental Transfer in Humans

Introduction: The emergence of Pavlovian-to-instrumental transfer (PIT) research in the human neurobehavioral domain has been met with increased interest over the past two decades. A variety of PIT tasks were developed during this time; while successful in demonstrating transfer phenomena, existing tasks have limitations that should be addressed. Herein, we introduce two PIT paradigms designed to assess outcome-specific and general PIT within the context of addiction. Materials and Methods: The single-lever PIT task, based on an established paradigm, replaced button presses with joystick motion to better assess avoidance behavior. The full transfer task uses alcohol and nonalcohol rewards associated with Pavlovian cues and instrumental responses, along with other gustatory and monetary rewards. We constructed mixed-effects models with the addition of other statistical analyses as needed to interpret various behavioral measures. Results: Single-lever PIT: both versions were successful in eliciting a PIT effect (joystick: p < 0.001, ηp 2 2 2 2 = 0.17). Discussion/Conclusion: Single-lever PIT: PIT was observed in both task versions. We posit that the use of a joystick is more advantageous for the analysis of avoidance behavior. It evenly distributes movement between approach and avoid trials, which is relevant to analyzing fMRI data. Full transfer task: While gustatory conditioning has been used in the past to elicit transfer effects, we present the first paradigm that successfully elicits both specific and general transfers in humans with gustatory alcohol rewards.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Development of Novel Tasks to Assess Outcome-Specific and General Pavlovian-to-Instrumental Transfer in Humans ; volume:81 ; number:5 ; year:2022 ; pages:370-386 ; extent:17
Neuropsychobiology ; 81, Heft 5 (2022), 370-386 (gesamt 17)

Creator
Belanger, Matthew J.
Chen, Hao
Hentschel, Angela
Garbusow, Maria
Ebrahimi, Claudia
Knorr, Felix G.
Zech, Hilmar Gero
Pilhatsch, Maximilian
Heinz, Andreas
Smolka, Michael

DOI
10.1159/000526774
URN
urn:nbn:de:101:1-2022121423312579679608
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:23 AM CEST

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