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Measuring learning in human classical threat conditioning: translational, cognitive and methodological considerations

Ojala, KE; Bach, DR; (2020) Measuring learning in human classical threat conditioning: translational, cognitive and methodological considerations. Neuroscience & Biobehavioral Reviews , 114 pp. 96-112. 10.1016/j.neubiorev.2020.04.019. Green open access

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Abstract

Threat conditioning is a laboratory model of associative learning across species that is often used in research on the etiology and treatment of anxiety disorders. At least 10 different conditioned responses (CR) for quantifying learning in human threat conditioning are found in the literature. In this narrative review, we discuss these CR by considering the following questions: (1) Are the CR indicators of amygdala-dependent threat learning? (2) To what components of formal learning models do the CR relate? (3) How well can threat learning be inferred from the CR? Despite a vast literature, these questions can only be answered for some CR. Among the CR considered, heart period, startle eye-blink and Pavlovian-to-instrumental transfer are most clearly related to amygdala-dependent threat learning. Formal learning models have mostly been studied for skin conductance responses, which are likely to reflect threat prediction and its uncertainty. Startle eye-blink and pupil size appear to best differentiate CS+/CS−, although few direct comparisons between CR exist. We suggest future directions for improving the quantification of threat conditioning.

Type: Article
Title: Measuring learning in human classical threat conditioning: translational, cognitive and methodological considerations
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neubiorev.2020.04.019
Publisher version: https://doi.org/10.1016/j.neubiorev.2020.04.019
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: fear conditioning, associative learning, implicit learning, psychophysiology, inverse inference, conditioned responses retrodictive validity
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10096683
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