Heritability and cognitive implications of structural-functional connectome coupling

人脑是一个由相互连接的神经元组成的难以想象的复杂系统，它能够 思想、情感和行为。通过结构连接体量化的大尺度白质连接 (SC)充当功能激活流的主干，这可以通过功能连接来表示- 蜜环花(Fc)。我们的团队和其他人已经证明，量化大脑的结构和功能的属性-- 神经连接及其关系有助于了解大脑-行为关联和疾病 机制4-9。然而，描述SC-FC关系的模型只达到了适度的一致性 还没有被用来充分探索结构的遗传性和认知含义- 成人和发育中人群的功能耦合。如果我们不能准确地理解大脑是如何- OMY和生理学是贯穿人类寿命的，那么我们将无法量化 疾病或病理性发育轨迹。我们的长期目标是为研究创造计算工具- 大脑的结构和功能，特别是在疾病的背景下。这样做的首要目标是 项目的目的是创建一个模型，准确地(和可解释地)量化结构和结构之间的耦合 这将使我们能够研究遗传性和认知性。 SC-FC偶联在发育中和成年人群中的影响。我们的中心假设是，一个混血儿 从SC预测FC的方法，结合生物物理建模和深度学习，将更加符合实际情况。 比现有的技术更精准。根据以前的文献和我们的初步数据，我们假设SC- FC偶联将因性别而异，是可遗传的，与发育有关，并解释 认知力。我们的假设得到了来自我们团队和其他人的初步数据的支持，这些数据表明SC-FC关系- 船是可遗传的，并随患者的性别和认知而变化7，18。这项工作的基本原理是 健康人群中SC-FC关系的准确模型，目前还不存在，将进一步推动我们的 了解解剖学、生理学、性别、遗传学和认知之间的复杂关系。我们会 通过三个具体目标检验中心假设：1)确定从SC预测FC的最准确模型， 2)量化SC-FC耦合的遗传度及其与认知成绩的关系；3)表征 SC-FC耦合轨迹及其在整个发展过程中的认知影响。我们将使用神经成像技术， 来自人类连接组项目的遗传和认知数据，包括年轻人(约1000人，22- 37岁)和发展中种群(约650个个体，5-21岁)。这种方法是创新的，因为它提出了 使用模型驱动、数据驱动和混合方法来建模SC-FC关系，并提出 更多SC-FC关系的性别效应、遗传力、认知和发展影响。建议数 研究的重要意义在于，理解典型发育过程中的结构-功能关系将使 量化疾病的影响，揭示各种神经疾病的新治疗途径。

The human brain is an unimaginably complicated system of interconnected neurons that is capable of complex thought, emotion and behavior. Macroscale white matter connections quantified via the structural connectome (SC) act as the backbone for the flow of functional activation, which can be represented via the functional con- nectome (FC). Our group and others have shown that quantifying properties of the brain’s structural and func- tional connectomes and their relationship can inform understanding of brain-behavior associations and disease mechanisms4-9. However, models that describe SC-FC relationships have only achieved moderate agreement with observations and have not been used to fully explore the heritability and cognitive implications of structure- function coupling in adult and developing populations. If we do not accurately understand how the brain’s anat- omy and physiology are linked across the human lifespan, then we will not be able to quantify the impact of disease or pathological developmental trajectories. Our long-term goal is to create computational tools for stud- ying the brain’s structure and function, particularly in the context of disease. The overarching objective of this project is to create a model that accurately {and interpretably} quantifies the coupling between the structural and functional connectomes in both sexes, which will in turn allow us to investigate the heritability and cognitive implications of SC-FC coupling across developing and adult populations. Our central hypothesis is that a {hybrid approach to predicting FC from SC, combining both biophysical modeling and deep learning,} will be more ac- curate than existing techniques. Based on the prior literature and our preliminary data, we hypothesize that SC- FC coupling will vary with sex, be heritable, associated with development, and explain inter-subject variability in cognition. Our hypothesis is supported by preliminary data from our group and others that show SC-FC relation- ships are heritable and vary with sex and cognition in patients7,18. The rationale for this work is that having an accurate model of the SC-FC relationship in healthy populations, which currently does not exist, will further our understanding of the complex relationship between anatomy, physiology, sex, genetics and cognition. We will test the central hypothesis via three specific aims: 1) identify the most accurate model for predicting FC from SC, 2) quantify the heritability of SC-FC coupling and its association with cognitive performance and 3) characterize the SC-FC coupling trajectory and its cognitive implications throughout development. We will use neuroimaging, genetic and cognitive data from the Human Connectome Project, including young adult (~1000 individuals, 22- 37 years) and developing populations (~650 individuals, 5-21 years). The approach is innovative, as it proposes to use model-driven, data-driven and hybrid approaches to model SC-FC relationships and that it poses to ex- plore sex effects, heritability, cognitive and developmental implications of SC-FC relationships. The proposed research is significant in that understanding structure-function relationships across typical development will allow quantification of the impact of disease and reveal avenues for novel treatments in various neurological diseases.