基于连接体的赌博障碍和可卡因使用障碍的渴望预测。

IF 8.3 2区 医学 Q1 Medicine
Stephanie Antons, Sarah W Yip, Cheryl M Lacadie, Javid Dadashkarimi, Dustin Scheinost, Matthias Brand, Marc N Potenza
{"title":"基于连接体的赌博障碍和可卡因使用障碍的渴望预测。","authors":"Stephanie Antons, Sarah W Yip, Cheryl M Lacadie, Javid Dadashkarimi, Dustin Scheinost, Matthias Brand, Marc N Potenza","doi":"10.1080/19585969.2023.2208586","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Craving, involving intense and urgent desires to engage in specific behaviours, is a feature of addictions. Multiple studies implicate regions of salience/limbic networks and basal ganglia, fronto-parietal, medial frontal regions in craving in addictions. However, prior studies have not identified common neural networks that reliably predict craving across substance and behavioural addictions.</p><p><strong>Methods: </strong>Functional magnetic resonance imaging during an audiovisual cue-reactivity task and connectome-based predictive modelling (CPM), a data-driven method for generating brain-behavioural models, were used to study individuals with cocaine-use disorder and gambling disorder. Functions of nodes and networks relevant to craving were identified and interpreted based on meta-analytic data.</p><p><strong>Results: </strong>Craving was predicted by neural connectivity across disorders. The highest degree nodes were mostly located in the prefrontal cortex. Overall, the prediction model included complex networks including motor/sensory, fronto-parietal, and default-mode networks. The decoding revealed high functional associations with components of memory, valence ratings, physiological responses, and finger movement/motor imagery.</p><p><strong>Conclusions: </strong>Craving could be predicted across substance and behavioural addictions. The model may reflect general neural mechanisms of craving despite specificities of individual disorders. Prefrontal regions associated with working memory and autobiographical memory seem important in predicting craving. For further validation, the model should be tested in diverse samples and contexts.</p>","PeriodicalId":54343,"journal":{"name":"Dialogues in Clinical Neuroscience","volume":null,"pages":null},"PeriodicalIF":8.3000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/42/7d/TDCN_25_2208586.PMC10190201.pdf","citationCount":"0","resultStr":"{\"title\":\"Connectome-based prediction of craving in gambling disorder and cocaine use disorder.\",\"authors\":\"Stephanie Antons, Sarah W Yip, Cheryl M Lacadie, Javid Dadashkarimi, Dustin Scheinost, Matthias Brand, Marc N Potenza\",\"doi\":\"10.1080/19585969.2023.2208586\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Craving, involving intense and urgent desires to engage in specific behaviours, is a feature of addictions. Multiple studies implicate regions of salience/limbic networks and basal ganglia, fronto-parietal, medial frontal regions in craving in addictions. However, prior studies have not identified common neural networks that reliably predict craving across substance and behavioural addictions.</p><p><strong>Methods: </strong>Functional magnetic resonance imaging during an audiovisual cue-reactivity task and connectome-based predictive modelling (CPM), a data-driven method for generating brain-behavioural models, were used to study individuals with cocaine-use disorder and gambling disorder. Functions of nodes and networks relevant to craving were identified and interpreted based on meta-analytic data.</p><p><strong>Results: </strong>Craving was predicted by neural connectivity across disorders. The highest degree nodes were mostly located in the prefrontal cortex. Overall, the prediction model included complex networks including motor/sensory, fronto-parietal, and default-mode networks. The decoding revealed high functional associations with components of memory, valence ratings, physiological responses, and finger movement/motor imagery.</p><p><strong>Conclusions: </strong>Craving could be predicted across substance and behavioural addictions. The model may reflect general neural mechanisms of craving despite specificities of individual disorders. Prefrontal regions associated with working memory and autobiographical memory seem important in predicting craving. For further validation, the model should be tested in diverse samples and contexts.</p>\",\"PeriodicalId\":54343,\"journal\":{\"name\":\"Dialogues in Clinical Neuroscience\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/42/7d/TDCN_25_2208586.PMC10190201.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Dialogues in Clinical Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/19585969.2023.2208586\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dialogues in Clinical Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/19585969.2023.2208586","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

摘要

引言:渴望是成瘾的一个特征,包括参与特定行为的强烈而紧迫的欲望。多项研究表明,成瘾性渴求中的突出/边缘网络区域和基底神经节、额顶叶、额内侧区域。然而,先前的研究还没有发现能够可靠预测物质和行为成瘾的渴望的常见神经网络。方法:在视听线索反应任务中使用功能性磁共振成像和基于连接体的预测建模(CPM),这是一种生成大脑行为模型的数据驱动方法,用于研究可卡因使用障碍和赌博障碍的个体。基于元分析数据,识别并解释了与渴望相关的节点和网络的功能。结果:Craving是通过各种疾病的神经连接来预测的。最高程度的淋巴结大多位于前额叶皮层。总体而言,预测模型包括复杂的网络,包括运动/感觉、额顶叶和默认模式网络。解码揭示了与记忆成分、效价、生理反应和手指运动/运动图像的高度功能关联。结论:渴求可以通过物质成瘾和行为成瘾来预测。该模型可能反映了渴望的一般神经机制,尽管个体疾病具有特异性。与工作记忆和自传体记忆相关的额前区域在预测渴望方面似乎很重要。为了进一步验证,模型应该在不同的样本和环境中进行测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Connectome-based prediction of craving in gambling disorder and cocaine use disorder.

Connectome-based prediction of craving in gambling disorder and cocaine use disorder.

Connectome-based prediction of craving in gambling disorder and cocaine use disorder.

Introduction: Craving, involving intense and urgent desires to engage in specific behaviours, is a feature of addictions. Multiple studies implicate regions of salience/limbic networks and basal ganglia, fronto-parietal, medial frontal regions in craving in addictions. However, prior studies have not identified common neural networks that reliably predict craving across substance and behavioural addictions.

Methods: Functional magnetic resonance imaging during an audiovisual cue-reactivity task and connectome-based predictive modelling (CPM), a data-driven method for generating brain-behavioural models, were used to study individuals with cocaine-use disorder and gambling disorder. Functions of nodes and networks relevant to craving were identified and interpreted based on meta-analytic data.

Results: Craving was predicted by neural connectivity across disorders. The highest degree nodes were mostly located in the prefrontal cortex. Overall, the prediction model included complex networks including motor/sensory, fronto-parietal, and default-mode networks. The decoding revealed high functional associations with components of memory, valence ratings, physiological responses, and finger movement/motor imagery.

Conclusions: Craving could be predicted across substance and behavioural addictions. The model may reflect general neural mechanisms of craving despite specificities of individual disorders. Prefrontal regions associated with working memory and autobiographical memory seem important in predicting craving. For further validation, the model should be tested in diverse samples and contexts.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Dialogues in Clinical Neuroscience
Dialogues in Clinical Neuroscience Medicine-Psychiatry and Mental Health
CiteScore
19.30
自引率
1.20%
发文量
1
期刊介绍: Dialogues in Clinical Neuroscience (DCNS) endeavors to bridge the gap between clinical neuropsychiatry and the neurosciences by offering state-of-the-art information and original insights into pertinent clinical, biological, and therapeutic aspects. As an open access journal, DCNS ensures accessibility to its content for all interested parties. Each issue is curated to include expert reviews, original articles, and brief reports, carefully selected to offer a comprehensive understanding of the evolving landscape in clinical neuroscience. Join us in advancing knowledge and fostering dialogue in this dynamic field.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信