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Evaluating Effects of Methylphenidate on Brain Activity in Cocaine Addiction: A Machine-Learning Approach

机译:评估哌醋甲酯对可卡因成瘾者大脑活动的影响:一种机器学习方法

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The objective of this study is to investigate effects of methylphenidate on brain activity in individuals with cocaine use disorder (CUD) using functional MRI (fMRI). Methylphenidate hydrochloride (MPH) is an indirect dopamine agonist commonly used for treating attention deficit/hyperactivity disorders; it was also shown to have some positive effects on CUD subjects, such as improved stop signal reaction times associated with better control/inhibition, as well as normalized task-related brain activity and resting-state functional connectivity in specific areas. While prior fMRI studies of MPH in CUDs have focused on mass-univariate statistical hypothesis testing, this paper evaluates multivariate, whole-brain effects of MPH as captured by the generalization (prediction) accuracy of different classification techniques applied to features extracted from resting-state functional networks (e.g., node degrees). Our multivariate predictive results based on resting-state data from suggest that MPH tends to normalize network properties such as voxel degrees in CUD subjects, thus providing additional evidence for potential benefits of MPH in treating cocaine addiction.
机译:这项研究的目的是使用功能性MRI(fMRI)研究哌醋甲酯对可卡因使用障碍(CUD)患者脑活动的影响。盐酸哌醋甲酯(MPH)是一种间接多巴胺激动剂,通常用于治疗注意力不足/多动症;它也被证明对CUD受试者有一些积极的影响,例如与更好的控制/抑制相关的停止信号反应时间的缩短,以及与任务相关的脑部活动的正常化以及特定区域的静止状态功能连接。虽然先前的CMRI中MPH的fMRI研究集中于质量单变量统计假设检验,但本文评估了MPH的多变量全脑效应,该效应是通过将不同分类技术应用于从静止状态提取的特征的泛化(预测)准确性来捕获的功能网络(例如,节点度)。我们基于静息状态数据得出的多变量预测结果表明,MPH倾向于使CUD受试者的网络属性(如体素度)正常化,从而为MPH在治疗可卡因成瘾方面的潜在益处提供了额外的证据。

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