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Cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents
Since the first neurodevelopmental models that sought to explain the influx of risky behaviors during adolescence were proposed, there have been a number of revisions, variations and criticisms. Despite providing a strong multi-disciplinary heuristic to explain the development of risk behavior, exta...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262007/ https://www.ncbi.nlm.nih.gov/pubmed/32479377 http://dx.doi.org/10.1016/j.dcn.2020.100798 |
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author | Demidenko, Michael I. Huntley, Edward D. Jahn, Andrew Thomason, Moriah E. Monk, Christopher S. Keating, Daniel P. |
author_facet | Demidenko, Michael I. Huntley, Edward D. Jahn, Andrew Thomason, Moriah E. Monk, Christopher S. Keating, Daniel P. |
author_sort | Demidenko, Michael I. |
collection | PubMed |
description | Since the first neurodevelopmental models that sought to explain the influx of risky behaviors during adolescence were proposed, there have been a number of revisions, variations and criticisms. Despite providing a strong multi-disciplinary heuristic to explain the development of risk behavior, extant models have not yet reliably isolated neural systems that underlie risk behaviors in adolescence. To address this gap, we screened 2017 adolescents from an ongoing longitudinal study that assessed 15-health risk behaviors, targeting 104 adolescents (Age Range: 17-to-21.4), characterized as high-or-average/low risk-taking. Participants completed the Monetary Incentive Delay (MID) fMRI task, examining reward anticipation to “big win” versus “neutral”. We examined neural response variation associated with both baseline and longitudinal (multi-wave) risk classifications. Analyses included examination of a priori regions of interest (ROIs); and exploratory non-parametric, whole-brain analyses. Hypothesis-driven ROI analysis revealed no significant differences between high- and average/low-risk profiles using either baseline or multi-wave classification. Results of whole-brain analyses differed according to whether risk assessment was based on baseline or multi-wave data. Despite significant mean-level task activation, these results do not generalize prior neural substrates implicated in reward anticipation and adolescent risk-taking. Further, these data indicate that whole-brain differences may depend on how risk-behavior profiles are defined. |
format | Online Article Text |
id | pubmed-7262007 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-72620072020-06-01 Cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents Demidenko, Michael I. Huntley, Edward D. Jahn, Andrew Thomason, Moriah E. Monk, Christopher S. Keating, Daniel P. Dev Cogn Neurosci Original Research Since the first neurodevelopmental models that sought to explain the influx of risky behaviors during adolescence were proposed, there have been a number of revisions, variations and criticisms. Despite providing a strong multi-disciplinary heuristic to explain the development of risk behavior, extant models have not yet reliably isolated neural systems that underlie risk behaviors in adolescence. To address this gap, we screened 2017 adolescents from an ongoing longitudinal study that assessed 15-health risk behaviors, targeting 104 adolescents (Age Range: 17-to-21.4), characterized as high-or-average/low risk-taking. Participants completed the Monetary Incentive Delay (MID) fMRI task, examining reward anticipation to “big win” versus “neutral”. We examined neural response variation associated with both baseline and longitudinal (multi-wave) risk classifications. Analyses included examination of a priori regions of interest (ROIs); and exploratory non-parametric, whole-brain analyses. Hypothesis-driven ROI analysis revealed no significant differences between high- and average/low-risk profiles using either baseline or multi-wave classification. Results of whole-brain analyses differed according to whether risk assessment was based on baseline or multi-wave data. Despite significant mean-level task activation, these results do not generalize prior neural substrates implicated in reward anticipation and adolescent risk-taking. Further, these data indicate that whole-brain differences may depend on how risk-behavior profiles are defined. Elsevier 2020-05-21 /pmc/articles/PMC7262007/ /pubmed/32479377 http://dx.doi.org/10.1016/j.dcn.2020.100798 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Research Demidenko, Michael I. Huntley, Edward D. Jahn, Andrew Thomason, Moriah E. Monk, Christopher S. Keating, Daniel P. Cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents |
title | Cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents |
title_full | Cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents |
title_fullStr | Cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents |
title_full_unstemmed | Cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents |
title_short | Cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents |
title_sort | cortical and subcortical response to the anticipation of reward in high and average/low risk-taking adolescents |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262007/ https://www.ncbi.nlm.nih.gov/pubmed/32479377 http://dx.doi.org/10.1016/j.dcn.2020.100798 |
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