Using Network Parcels and Resting-State Networks to Estimate Correlates of Mood Disorder and Related Research Domain Criteria Constructs of Reward Responsiveness and Inhibitory Control.
Using Network Parcels and Resting-State Networks to Estimate Correlates of Mood Disorder and Related Research Domain Criteria Constructs of Reward Responsiveness and Inhibitory Control.
复制标题
DOI：
10.1016/j.bpsc.2021.06.014
复制
发表时间：
2022-01
期刊：
影响因子：
--
通讯作者：
Welsh RC
中科院分区：
文献类型：
--
作者：
Langenecker SA;Westlund Schreiner M;Thomas LR;Bessette KL;DelDonno SR;Jenkins LM;Easter RE;Stange JP;Pocius SL;Dillahunt A;Love TM;Phan KL;Koppelmans V;Paulus M;Lindquist MA;Caffo B;Mickey BJ;Welsh RC
基于静息状态图的网络边缘可以成为识别情绪障碍的强大工具。我们解决这些边缘是否可以与RDoC结构整合，以准确识别情绪障碍相关的标志物，同时最大限度地减少疾病的活动症状。我们比较了132个人目前缓解或心境正常的情绪障碍与65个健康的对照参与者，18-30岁。较小的大脑包裹的子集，组合成三个突出的网络和一个网络的包裹重叠在这些网络中，被用来比较组之间的边缘差异。与研究领域标准（RDoC）框架一致，我们评估了个体差异与抑制控制和奖励反应的性能测量回归。在一个综合回归模型中，我们预测了与诊断组成员资格、RDoC域内的性能以及相关相互作用相关的边缘。有几个边缘的情绪障碍组，主要是更大的连接网络，不同的个体差异，抑制控制和奖励反应。边缘相关的诊断和抑制控制没有对齐以及与以前的文献，而边缘有关的奖励响应结构表现出更大的对齐与以前的文献。RDoC结构和诊断之间的相互作用的边缘表现出抑制性控制（默认模式下的负相互作用）相对于奖励（与显着性和情感网络的正相互作用）的分歧。总之，有证据表明，先前的简单的网络模型的情绪障碍是目前不够的生物或诊断的清晰度，或基于包裹的边缘可能不够敏感，为这些目的。
Resting-state graph-based network edges can be powerful tools for identification of mood disorders. We address whether these edges can be integrated with RDoC constructs, for accurate identification of mood-disorder related markers, while minimizing active symptoms of disease. We compared 132 individuals with currently remitted or euthymic mood disorder with 65 healthy comparison participants, 18–30 years were included. Subsets of smaller brain parcels, combined into three prominent networks and one network of parcels overlapping across these networks, was used to compare edge differences between groups. Consistent with the research domain criteria (RDoC) framework, we evaluated individual differences with performance measure regressors of inhibitory control and reward responsivity. Within an omnibus regression model, we predicted edges related to diagnostic group membership, performance within both RDoC domains, and relevant interactions. There were several edges of mood disorder group, predominantly of greater connectivity across networks, different than those related to individual differences in inhibitory control and reward responsivity. Edges related to diagnosis and inhibitory control did not align well with prior literature, whereas edges in relation to reward responsivity constructs showed greater alignment with prior literature. Those edges in interaction between RDoC constructs and diagnosis showed a divergence for inhibitory control (negative interactions in default mode) relative to reward (positive interactions with salience and emotion network). In conclusion, there is evidence that prior simple network models of mood disorders are currently of insufficient biological or diagnostic clarity, or that parcel-based edges may be insufficiently sensitive for these purposes.
登录
查看更多内容
影响因子：
2.6
作者：
DelDonno, Sophie R.;Mickey, Brian J.;Pruitt, Patrick J.;Stange, Jonathan P.;Hsu, David T.;Weldon, Anne L.;Zubieta, Jon-Kar;Langenecker, Scott A.
通讯作者：
Langenecker, Scott A.
影响因子：
82.9
作者：
Drysdale AT;Grosenick L;Downar J;Dunlop K;Mansouri F;Meng Y;Fetcho RN;Zebley B;Oathes DJ;Etkin A;Schatzberg AF;Sudheimer K;Keller J;Mayberg HS;Gunning FM;Alexopoulos GS;Fox MD;Pascual-Leone A;Voss HU;Casey BJ;Dubin MJ;Liston C
通讯作者：
Liston C
影响因子：
8.8
作者：
Gordon EM;Lynch CJ;Gratton C;Laumann TO;Gilmore AW;Greene DJ;Ortega M;Nguyen AL;Schlaggar BL;Petersen SE;Dosenbach NUF;Nelson SM
通讯作者：
Nelson SM
影响因子：
4.7
作者：
Bessette KL;Jenkins LM;Skerrett KA;Gowins JR;DelDonno SR;Zubieta JK;McInnis MG;Jacobs RH;Ajilore O;Langenecker SA
通讯作者：
Langenecker SA
DOI：
10.1080/13803395.2019.1585519
发表时间：
2019-03-28
影响因子：
2.2
作者：
DelDonno, Sophie R.;Karstens, Aimee James;Langenecker, Scott A.
通讯作者：
Langenecker, Scott A.