Delay discounting has been proposed as a behavioral marker of substance use disorders. Innovative analytic approaches that integrate information from multiple neuroimaging modalities can provide new insights into the complex effects of drug use on the brain. This study implemented a supervised multimodal fusion approach to reveal neural networks associated with delay discounting that distinguish persons with and without cocaine use disorder (CUD). Adults with (n = 35) and without (n = 37) CUD completed a magnetic resonance imaging (MRI) scan to acquire high-resolution anatomical, resting-state functional, and diffusion-weighted images. Pre-computed features from each data modality included whole-brain voxel-wise maps for gray matter volume, fractional anisotropy, and regional homogeneity, respectively. With delay discounting as the reference, multimodal canonical component analysis plus joint independent component analysis was used to identify co-alterations in brain structure and function. The sample was 58% male and 78% African–American. As expected, participants with CUD had higher delay discounting compared to those without CUD. One joint component was identified that correlated with delay discounting across all modalities, involving regions in the thalamus, dorsal striatum, frontopolar cortex, occipital lobe, and corpus callosum. The components were negatively correlated with delay discounting, such that weaker loadings were associated with higher discounting. The component loadings were lower in persons with CUD, meaning the component was expressed less strongly. Our findings reveal structural and functional co-alterations linked to delay discounting, particularly in brain regions involved in reward salience, executive control, and visual attention and connecting white matter tracts. Importantly, these multimodal networks were weaker in persons with CUD, indicating less cognitive control that may contribute to impulsive behaviors.

中文翻译：

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与延迟贴现相关的大脑多模态协同改变：对患有和不患有可卡因使用障碍的人进行多模态 MRI 融合分析


延迟折扣已被提议作为物质使用障碍的行为标志。整合多种神经影像模式信息的创新分析方法可以为药物使用对大脑的复杂影响提供新的见解。这项研究采用了一种有监督的多模态融合方法，揭示了与延迟贴现相关的神经网络，可以区分患有和不患有可卡因使用障碍（CUD）的人。患有 (n = 35) 和不患有 (n = 37) CUD 的成年人完成了磁共振成像 (MRI) 扫描，以获取高分辨率解剖、静息态功能和弥散加权图像。每种数据模态的预先计算特征分别包括灰质体积、分数各向异性和区域均匀性的全脑体素图。以延迟贴现为参考，采用多模态典型成分分析加联合独立成分分析来识别大脑结构和功能的共同改变。样本中 58% 是男性，78% 是非裔美国人。正如预期的那样，与没有 CUD 的参与者相比，拥有 CUD 的参与者获得了更高的延迟折扣。确定了一种与所有模式的延迟贴现相关的关节成分，涉及丘脑、背侧纹状体、额极皮层、枕叶和胼胝体区域。这些组成部分与延迟折扣呈负相关，因此较弱的负载与较高的折扣相​​关。患有 CUD 的人的成分负荷较低，这意味着该成分的表达较弱。 我们的研究结果揭示了与延迟贴现相关的结构和功能协同改变，特别是在涉及奖赏显着、执行控制、视觉注意力和连接白质束的大脑区域。重要的是，这些多模式网络在 CUD 患者中较弱，表明认知控制能力较差，这可能会导致冲动行为。