Zhang Aiying, Zhang Gemeng, Cai Biao, Wilson Tony W, Stephen Julia M, Calhoun Vince D, Wang Yu-Ping
School of Data Science, University of Virginia, Charlottesville, VA, USA.
Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA.
Netw Neurosci. 2024 Oct 1;8(3):791-807. doi: 10.1162/netn_a_00384. eCollection 2024.
Emotion perception is essential to affective and cognitive development which involves distributed brain circuits. Emotion identification skills emerge in infancy and continue to develop throughout childhood and adolescence. Understanding the development of the brain's emotion circuitry may help us explain the emotional changes during adolescence. In this work, we aim to deepen our understanding of emotion-related functional connectivity (FC) from association to causation. We proposed a Bayesian incorporated linear non-Gaussian acyclic model (BiLiNGAM), which incorporated association model into the estimation pipeline. Simulation results indicated stable and accurate performance over various settings, especially when the sample size was small. We used fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) to validate the approach. It included 855 individuals aged 8-22 years who were divided into five different adolescent stages. Our network analysis revealed the development of emotion-related intra- and intermodular connectivity and pinpointed several emotion-related hubs. We further categorized the hubs into two types: in-hubs and out-hubs, as the center of receiving and distributing information, respectively. In addition, several unique developmental hub structures and group-specific patterns were discovered. Our findings help provide a directed FC template of brain network organization underlying emotion processing during adolescence.
情绪感知对于涉及分布式脑回路的情感和认知发展至关重要。情绪识别技能在婴儿期出现，并在整个童年和青少年时期持续发展。了解大脑情绪回路的发育可能有助于我们解释青春期的情绪变化。在这项工作中，我们旨在从关联到因果关系加深对与情绪相关的功能连接（FC）的理解。我们提出了一种贝叶斯合并线性非高斯无环模型（BiLiNGAM），该模型将关联模型纳入估计流程。模拟结果表明，在各种设置下该模型性能稳定且准确，尤其是在样本量较小时。我们使用来自费城神经发育队列（PNC）的功能磁共振成像（fMRI）数据来验证该方法。该队列包括855名年龄在8至22岁之间的个体，他们被分为五个不同的青少年阶段。我们的网络分析揭示了与情绪相关的模块内和模块间连接的发展，并确定了几个与情绪相关的枢纽。我们进一步将这些枢纽分为两种类型：内枢纽和外枢纽，分别作为接收和分发信息的中心。此外，还发现了几种独特的发育枢纽结构和特定于组的模式。我们的研究结果有助于提供一个有向的FC模板，用于解释青春期情绪处理背后的脑网络组织。
