用生成模型量化自闭症儿童脑连接差异，提供个性化诊断新工具
Parsing altered brain connectivity in neurodevelopmental disorders by integrating graph-based normative modeling and deep generative networks
- 结合正常发育轨迹与深度生成模型，构建个体化脑连接参考标准
- 全球神经差异得分与自闭症临床评估相关，区域图揭示个体异质性
- 适合研究神经发育障碍机制或开发影像生物标志物的学者使用
许多神经发育障碍的行为和认知症状被认为源于脑连接的异常。量化个体与典型连接模式的偏离，为诊断和干预提供了潜在路径。尽管扩散MRI（dMRI）等先进成像技术已实现脑结构连接组的绘制，但如何准确建模这些复杂网络在发育过程中的动态变化，仍是挑战。本文提出脑表征的个体化深度生成嵌入框架（BRIDGE），将范式建模与生物启发的深度生成模型结合，构建神经典型发育过程中连接转换的参考轨迹，从而通过比较个体与该轨迹来评估神经差异。BRIDGE提供基于连接组脑龄与实际年龄差值的全局神经差异分数，以及突出局部连接差异的区域级神经差异图。在大规模自闭症谱系障碍儿童队列上的应用表明，全局神经差异分数与自闭症临床评估显著相关，区域图则揭示了神经发育障碍在个体层面的异质性。两者共同构成量化连接模式发育偏离的强大工具，推动个性化诊断与干预影像标记物的发展。
原文摘要 · Abstract (English)
Divergent brain connectivity is thought to underlie the behavioral and cognitive symptoms observed in many neurodevelopmental disorders. Quantifying divergence from neurotypical connectivity patterns offers a promising pathway to inform diagnosis and therapeutic interventions. While advanced neuroimaging techniques, such as diffusion MRI (dMRI), have facilitated the mapping of brain's structural connectome, the challenge lies in accurately modeling developmental trajectories within these complex networked structures to create robust neurodivergence markers. In this work, we present the Brain Representation via Individualized Deep Generative Embedding (BRIDGE) framework, which integrates normative modeling with a bio-inspired deep generative model to create a reference trajectory of connectivity transformation as part of neurotypical development. This will enable the assessment of neurodivergence by comparing individuals to the established neurotypical trajectory. BRIDGE provides a global neurodivergence score based on the difference between connectivity-based brain age and chronological age, along with region-wise neurodivergence maps that highlight localized connectivity differences. Application of BRIDGE to a large cohort of children with autism spectrum disorder demonstrates that the global neurodivergence score correlates with clinical assessments in autism, and the regional map offers insights into the heterogeneity at the individual level in neurodevelopmental disorders. Together, the neurodivergence score and map form powerful tools for quantifying developmental divergence in connectivity patterns, advancing the development of imaging markers for personalized diagnosis and intervention in various clinical contexts.
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