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A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting

BACKGROUND: The tendency to devaluate future options as a function of time, known as delay discounting, is associated with various factors such as psychiatric illness and personality. Under identical experimental conditions, individuals may therefore strongly differ in the degree to which they disco...

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Autores principales: Thome, Janine, Pinger, Mathieu, Halli, Patrick, Durstewitz, Daniel, Sommer, Wolfgang H., Kirsch, Peter, Koppe, Georgia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9253427/
https://www.ncbi.nlm.nih.gov/pubmed/35800024
http://dx.doi.org/10.3389/fpsyt.2022.846119
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author Thome, Janine
Pinger, Mathieu
Halli, Patrick
Durstewitz, Daniel
Sommer, Wolfgang H.
Kirsch, Peter
Koppe, Georgia
author_facet Thome, Janine
Pinger, Mathieu
Halli, Patrick
Durstewitz, Daniel
Sommer, Wolfgang H.
Kirsch, Peter
Koppe, Georgia
author_sort Thome, Janine
collection PubMed
description BACKGROUND: The tendency to devaluate future options as a function of time, known as delay discounting, is associated with various factors such as psychiatric illness and personality. Under identical experimental conditions, individuals may therefore strongly differ in the degree to which they discount future options. In delay discounting tasks, this inter-individual variability inevitably results in an unequal number of discounted trials per subject, generating difficulties in linking delay discounting to psychophysiological and neural correlates. Many studies have therefore focused on assessing delay discounting adaptively. Here, we extend these approaches by developing an adaptive paradigm which aims at inducing more comparable and homogeneous discounting frequencies across participants on a dimensional scale. METHOD: The proposed approach probabilistically links a (common) discounting function to behavior to obtain a probabilistic model, and then exploits the model to obtain a formal condition which defines how to construe experimental trials so as to induce any desired discounting probability. We first infer subject-level models on behavior on a non-adaptive delay discounting task and then use these models to generate adaptive trials designed to evoke graded relative discounting frequencies of 0.3, 0.5, and 0.7 in each participant. We further compare and evaluate common models in the field through out-of-sample prediction error estimates, to iteratively improve the trial-generating model and paradigm. RESULTS: The developed paradigm successfully increases discounting behavior during both reward and loss discounting. Moreover, it evokes graded relative choice frequencies in line with model-based expectations (i.e., 0.3, 0.5, and 0.7) suggesting that we can successfully homogenize behavior. Our model comparison analyses indicate that hyperboloid models are superior in predicting unseen discounting behavior to more conventional hyperbolic and exponential models. We report out-of-sample error estimates as well as commonalities and differences between reward and loss discounting, demonstrating for instance lower discounting rates, as well as differences in delay perception in loss discounting. CONCLUSION: The present work proposes a model-based framework to evoke graded responses linked to cognitive function at a single subject level. Such a framework may be used in the future to measure cognitive functions on a dimensional rather than dichotomous scale.
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spelling pubmed-92534272022-07-06 A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting Thome, Janine Pinger, Mathieu Halli, Patrick Durstewitz, Daniel Sommer, Wolfgang H. Kirsch, Peter Koppe, Georgia Front Psychiatry Psychiatry BACKGROUND: The tendency to devaluate future options as a function of time, known as delay discounting, is associated with various factors such as psychiatric illness and personality. Under identical experimental conditions, individuals may therefore strongly differ in the degree to which they discount future options. In delay discounting tasks, this inter-individual variability inevitably results in an unequal number of discounted trials per subject, generating difficulties in linking delay discounting to psychophysiological and neural correlates. Many studies have therefore focused on assessing delay discounting adaptively. Here, we extend these approaches by developing an adaptive paradigm which aims at inducing more comparable and homogeneous discounting frequencies across participants on a dimensional scale. METHOD: The proposed approach probabilistically links a (common) discounting function to behavior to obtain a probabilistic model, and then exploits the model to obtain a formal condition which defines how to construe experimental trials so as to induce any desired discounting probability. We first infer subject-level models on behavior on a non-adaptive delay discounting task and then use these models to generate adaptive trials designed to evoke graded relative discounting frequencies of 0.3, 0.5, and 0.7 in each participant. We further compare and evaluate common models in the field through out-of-sample prediction error estimates, to iteratively improve the trial-generating model and paradigm. RESULTS: The developed paradigm successfully increases discounting behavior during both reward and loss discounting. Moreover, it evokes graded relative choice frequencies in line with model-based expectations (i.e., 0.3, 0.5, and 0.7) suggesting that we can successfully homogenize behavior. Our model comparison analyses indicate that hyperboloid models are superior in predicting unseen discounting behavior to more conventional hyperbolic and exponential models. We report out-of-sample error estimates as well as commonalities and differences between reward and loss discounting, demonstrating for instance lower discounting rates, as well as differences in delay perception in loss discounting. CONCLUSION: The present work proposes a model-based framework to evoke graded responses linked to cognitive function at a single subject level. Such a framework may be used in the future to measure cognitive functions on a dimensional rather than dichotomous scale. Frontiers Media S.A. 2022-06-21 /pmc/articles/PMC9253427/ /pubmed/35800024 http://dx.doi.org/10.3389/fpsyt.2022.846119 Text en Copyright © 2022 Thome, Pinger, Halli, Durstewitz, Sommer, Kirsch and Koppe. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
Thome, Janine
Pinger, Mathieu
Halli, Patrick
Durstewitz, Daniel
Sommer, Wolfgang H.
Kirsch, Peter
Koppe, Georgia
A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting
title A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting
title_full A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting
title_fullStr A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting
title_full_unstemmed A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting
title_short A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting
title_sort model guided approach to evoke homogeneous behavior during temporal reward and loss discounting
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9253427/
https://www.ncbi.nlm.nih.gov/pubmed/35800024
http://dx.doi.org/10.3389/fpsyt.2022.846119
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