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Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies

Luke J. Ney Orcid Logo, Patrick A. F. Laing Orcid Logo, Trevor Steward, Daniel Zuj, Simon Dymond Orcid Logo, Ben Harrison, Bronwyn Graham Orcid Logo, Kim L. Felmingham

PLOS ONE, Volume: 17, Issue: 5, Start page: e0268814

Swansea University Authors: Daniel Zuj, Simon Dymond Orcid Logo

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DOI (Published version): 10.1371/journal.pone.0268814

Abstract

Fear conditioning paradigms are critical to understanding anxiety-related disorders, but studies use an inconsistent array of methods to quantify the same underlying learning process. We previously demonstrated that selection of trials from different stages of experimental phases and inconsistent us...

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ISSN: 1932-6203
Published: Public Library of Science (PLoS) 2022
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spelling v2 60132 2022-06-06 Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies e4ea88775fc5b3764aa6322a2285a582 Daniel Zuj Daniel Zuj true false 8ed0024546f2588fdb0073a7d6fbc075 0000-0003-1319-4492 Simon Dymond Simon Dymond true false 2022-06-06 FGMHL Fear conditioning paradigms are critical to understanding anxiety-related disorders, but studies use an inconsistent array of methods to quantify the same underlying learning process. We previously demonstrated that selection of trials from different stages of experimental phases and inconsistent use of average compared to trial-by-trial analysis can deliver significantly divergent outcomes, regardless of whether the data is analysed with extinction as a single effect, as a learning process over the course of the experiment, or in relation to acquisition learning. Since small sample sizes are attributed as sources of poor replicability in psychological science, in this study we aimed to investigate if changes in sample size influences the divergences that occur when different kinds of fear conditioning analyses are used. We analysed a large data set of fear acquisition and extinction learning (N = 379), measured via skin conductance responses (SCRs), which was resampled with replacement to create a wide range of bootstrapped databases (N = 30, N = 60, N = 120, N = 180, N = 240, N = 360, N = 480, N = 600, N = 720, N = 840, N = 960, N = 1080, N = 1200, N = 1500, N = 1750, N = 2000) and tested whether use of different analyses continued to produce deviating outcomes. We found that sample size did not significantly influence the effects of inconsistent analytic strategy when no group-level effect was included but found strategy-dependent effects when group-level effects were simulated. These findings suggest that confounds incurred by inconsistent analyses remain stable in the face of sample size variation, but only under specific circumstances with overall robustness strongly hinging on the relationship between experimental design and choice of analyses. This supports the view that such variations reflect a more fundamental confound in psychological science—the measurement of a single process by multiple methods. Journal Article PLOS ONE 17 5 e0268814 Public Library of Science (PLoS) 1932-6203 Fear conditioning paradigms, anxiety-related disorders, psychiatric disorders, sample size, replicability, extinction learning 24 5 2022 2022-05-24 10.1371/journal.pone.0268814 COLLEGE NANME Medicine, Health and Life Science - Faculty COLLEGE CODE FGMHL Swansea University SU Library paid the OA fee (TA Institutional Deal) Swansea University 2023-07-26T16:34:14.2858369 2022-06-06T09:53:26.5149128 Faculty of Medicine, Health and Life Sciences School of Psychology Luke J. Ney 0000-0003-0209-8366 1 Patrick A. F. Laing 0000-0001-6890-6827 2 Trevor Steward 3 Daniel Zuj 4 Simon Dymond 0000-0003-1319-4492 5 Ben Harrison 6 Bronwyn Graham 0000-0001-6582-2273 7 Kim L. Felmingham 8 60132__24475__f9a7772dce534b8d93c58832e36c494e.pdf 60132_VoR.pdf 2022-07-07T11:58:01.2885348 Output 1616386 application/pdf Version of Record true © 2022 Ney et al. This is an open access article distributed under the terms of the Creative Commons Attribution License true eng http://creativecommons.org/licenses/by/4.0/
title Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies
spellingShingle Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies
Daniel Zuj
Simon Dymond
title_short Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies
title_full Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies
title_fullStr Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies
title_full_unstemmed Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies
title_sort Methodological implications of sample size and extinction gradient on the robustness of fear conditioning across different analytic strategies
author_id_str_mv e4ea88775fc5b3764aa6322a2285a582
8ed0024546f2588fdb0073a7d6fbc075
author_id_fullname_str_mv e4ea88775fc5b3764aa6322a2285a582_***_Daniel Zuj
8ed0024546f2588fdb0073a7d6fbc075_***_Simon Dymond
author Daniel Zuj
Simon Dymond
author2 Luke J. Ney
Patrick A. F. Laing
Trevor Steward
Daniel Zuj
Simon Dymond
Ben Harrison
Bronwyn Graham
Kim L. Felmingham
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college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_title Faculty of Medicine, Health and Life Sciences
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hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str School of Psychology{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}School of Psychology
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description Fear conditioning paradigms are critical to understanding anxiety-related disorders, but studies use an inconsistent array of methods to quantify the same underlying learning process. We previously demonstrated that selection of trials from different stages of experimental phases and inconsistent use of average compared to trial-by-trial analysis can deliver significantly divergent outcomes, regardless of whether the data is analysed with extinction as a single effect, as a learning process over the course of the experiment, or in relation to acquisition learning. Since small sample sizes are attributed as sources of poor replicability in psychological science, in this study we aimed to investigate if changes in sample size influences the divergences that occur when different kinds of fear conditioning analyses are used. We analysed a large data set of fear acquisition and extinction learning (N = 379), measured via skin conductance responses (SCRs), which was resampled with replacement to create a wide range of bootstrapped databases (N = 30, N = 60, N = 120, N = 180, N = 240, N = 360, N = 480, N = 600, N = 720, N = 840, N = 960, N = 1080, N = 1200, N = 1500, N = 1750, N = 2000) and tested whether use of different analyses continued to produce deviating outcomes. We found that sample size did not significantly influence the effects of inconsistent analytic strategy when no group-level effect was included but found strategy-dependent effects when group-level effects were simulated. These findings suggest that confounds incurred by inconsistent analyses remain stable in the face of sample size variation, but only under specific circumstances with overall robustness strongly hinging on the relationship between experimental design and choice of analyses. This supports the view that such variations reflect a more fundamental confound in psychological science—the measurement of a single process by multiple methods.
published_date 2022-05-24T16:33:28Z
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