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Neuroimaging studies of addiction: The need to incorporate real life data and profile heterogeneity

ABSTRACT: Neuroimaging studies of addiction seek to understand the brain mechanisms that predispose to and support the maintenance of addictive behaviors. Traditional studies are case-control cross-sectional studies, i.e. they conceptualized individuals suffering from addiction as a homogenous group...

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Autor principal: Sescousse, G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417673/
http://dx.doi.org/10.1192/j.eurpsy.2023.37
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author Sescousse, G.
author_facet Sescousse, G.
author_sort Sescousse, G.
collection PubMed
description ABSTRACT: Neuroimaging studies of addiction seek to understand the brain mechanisms that predispose to and support the maintenance of addictive behaviors. Traditional studies are case-control cross-sectional studies, i.e. they conceptualized individuals suffering from addiction as a homogenous group, and report lab-based experiments conducted at one particular point in time. In this talk, I will argue that a refined understanding of addictive behaviors requires the use of dimensional longitudinal studies. Using dimensions will reveal the existence of heterogenous profiles within diagnostic groups, and allow researchers to incorporate individual variability in their models. In turn, using longitudinal follow-up measures should allow researchers to determine whether brain-related abnormalities are predictive of symptoms in real-life. I will illustrate these points using a few example studies from the literature. DISCLOSURE OF INTEREST: None Declared
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spelling pubmed-104176732023-08-12 Neuroimaging studies of addiction: The need to incorporate real life data and profile heterogeneity Sescousse, G. Eur Psychiatry Abstract ABSTRACT: Neuroimaging studies of addiction seek to understand the brain mechanisms that predispose to and support the maintenance of addictive behaviors. Traditional studies are case-control cross-sectional studies, i.e. they conceptualized individuals suffering from addiction as a homogenous group, and report lab-based experiments conducted at one particular point in time. In this talk, I will argue that a refined understanding of addictive behaviors requires the use of dimensional longitudinal studies. Using dimensions will reveal the existence of heterogenous profiles within diagnostic groups, and allow researchers to incorporate individual variability in their models. In turn, using longitudinal follow-up measures should allow researchers to determine whether brain-related abnormalities are predictive of symptoms in real-life. I will illustrate these points using a few example studies from the literature. DISCLOSURE OF INTEREST: None Declared Cambridge University Press 2023-07-19 /pmc/articles/PMC10417673/ http://dx.doi.org/10.1192/j.eurpsy.2023.37 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstract
Sescousse, G.
Neuroimaging studies of addiction: The need to incorporate real life data and profile heterogeneity
title Neuroimaging studies of addiction: The need to incorporate real life data and profile heterogeneity
title_full Neuroimaging studies of addiction: The need to incorporate real life data and profile heterogeneity
title_fullStr Neuroimaging studies of addiction: The need to incorporate real life data and profile heterogeneity
title_full_unstemmed Neuroimaging studies of addiction: The need to incorporate real life data and profile heterogeneity
title_short Neuroimaging studies of addiction: The need to incorporate real life data and profile heterogeneity
title_sort neuroimaging studies of addiction: the need to incorporate real life data and profile heterogeneity
topic Abstract
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417673/
http://dx.doi.org/10.1192/j.eurpsy.2023.37
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