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A cognitive process modeling framework for the ABCD study stop-signal task
The Adolescent Brain Cognitive Development (ABCD) Study is a longitudinal neuroimaging study of unprecedented scale that is in the process of following over 11,000 youth from middle childhood though age 20. However, a design feature of the study's stop-signal task violates "context indepen...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9826813/ https://www.ncbi.nlm.nih.gov/pubmed/36603413 http://dx.doi.org/10.1016/j.dcn.2022.101191 |
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author | Weigard, Alexander Matzke, Dora Tanis, Charlotte Heathcote, Andrew |
author_facet | Weigard, Alexander Matzke, Dora Tanis, Charlotte Heathcote, Andrew |
author_sort | Weigard, Alexander |
collection | PubMed |
description | The Adolescent Brain Cognitive Development (ABCD) Study is a longitudinal neuroimaging study of unprecedented scale that is in the process of following over 11,000 youth from middle childhood though age 20. However, a design feature of the study's stop-signal task violates "context independence", an assumption critical to current non-parametric methods for estimating stop-signal reaction time (SSRT), a key measure of inhibitory ability in the study. This has led some experts to call for the task to be changed and for previously collected data to be used with caution. We present a cognitive process modeling framework, the RDEX-ABCD model, that provides a parsimonious explanation for the impact of this design feature on “go” stimulus processing and successfully accounts for key behavioral trends in the ABCD data. Simulation studies using this model suggest that failing to account for the context independence violations in the ABCD design can lead to erroneous inferences in several realistic scenarios. However, we demonstrate that RDEX-ABCD effectively addresses these violations and can be used to accurately measure SSRT along with an array of additional mechanistic parameters of interest (e.g., attention to the stop signal, cognitive efficiency), advancing investigators’ ability to draw valid and nuanced inferences from ABCD data. AVAILABILITY OF DATA AND MATERIALS: Data from the ABCD Study are available through the NIH Data Archive (NDA): nda.nih.gov/abcd. Code for all analyses featured in this study is openly available on the Open Science Framework (OSF): osf.io/2h8a7/. |
format | Online Article Text |
id | pubmed-9826813 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-98268132023-01-10 A cognitive process modeling framework for the ABCD study stop-signal task Weigard, Alexander Matzke, Dora Tanis, Charlotte Heathcote, Andrew Dev Cogn Neurosci Original Research The Adolescent Brain Cognitive Development (ABCD) Study is a longitudinal neuroimaging study of unprecedented scale that is in the process of following over 11,000 youth from middle childhood though age 20. However, a design feature of the study's stop-signal task violates "context independence", an assumption critical to current non-parametric methods for estimating stop-signal reaction time (SSRT), a key measure of inhibitory ability in the study. This has led some experts to call for the task to be changed and for previously collected data to be used with caution. We present a cognitive process modeling framework, the RDEX-ABCD model, that provides a parsimonious explanation for the impact of this design feature on “go” stimulus processing and successfully accounts for key behavioral trends in the ABCD data. Simulation studies using this model suggest that failing to account for the context independence violations in the ABCD design can lead to erroneous inferences in several realistic scenarios. However, we demonstrate that RDEX-ABCD effectively addresses these violations and can be used to accurately measure SSRT along with an array of additional mechanistic parameters of interest (e.g., attention to the stop signal, cognitive efficiency), advancing investigators’ ability to draw valid and nuanced inferences from ABCD data. AVAILABILITY OF DATA AND MATERIALS: Data from the ABCD Study are available through the NIH Data Archive (NDA): nda.nih.gov/abcd. Code for all analyses featured in this study is openly available on the Open Science Framework (OSF): osf.io/2h8a7/. Elsevier 2022-12-22 /pmc/articles/PMC9826813/ /pubmed/36603413 http://dx.doi.org/10.1016/j.dcn.2022.101191 Text en © 2023 The Authors https://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 Weigard, Alexander Matzke, Dora Tanis, Charlotte Heathcote, Andrew A cognitive process modeling framework for the ABCD study stop-signal task |
title | A cognitive process modeling framework for the ABCD study stop-signal task |
title_full | A cognitive process modeling framework for the ABCD study stop-signal task |
title_fullStr | A cognitive process modeling framework for the ABCD study stop-signal task |
title_full_unstemmed | A cognitive process modeling framework for the ABCD study stop-signal task |
title_short | A cognitive process modeling framework for the ABCD study stop-signal task |
title_sort | cognitive process modeling framework for the abcd study stop-signal task |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9826813/ https://www.ncbi.nlm.nih.gov/pubmed/36603413 http://dx.doi.org/10.1016/j.dcn.2022.101191 |
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