An Alignment Framework For Mapping Brain Dynamics and Substrates of Human Cognition Across Species

用于绘制跨物种大脑动态和人类认知基础的对齐框架

• 批准号: 10360863
• 负责人: Ting Xu
• 金额: $ 121.07万
• 依托单位: CHILD MIND INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-13 至 2024-09-12
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10360863
• 关键词: Address; Adopted; Anatomy; Area; BRAIN initiative; Behavioral; Brain; Brain Mapping; Code; Cognition; Cognitive; Data; Data Set; Diffusion; Diffusion Magnetic Resonance Imaging; Dimensions; Fostering; Functional Magnetic Resonance Imaging; Goals; Graph; Human; Image; Individual; Joints; Link; Macaca; Macaca mulatta; Magnetic Resonance Imaging; Maps; Measures; Methods; Modality; Modeling; Monkeys; Motor; Myelin; Ontology; Pattern; Performance; Periodicity; Primates; Publications; Reproducibility; Research; Research Personnel; Resources; Rodent; Sampling; Sensory; Site; Structure; Surface; Testing; Translational Research; Translations; United States National Institutes of Health; Variant; Work; base; cognitive task; connectome; data exchange; experimental study; high dimensionality; human model; improved; in vivo; innovation; insight; markov model; multimodality; neuroimaging; nonhuman primate; novel; open data; response; spatiotemporal; tractography; translational neuroscience; translational study; web page

ABSTRACT The non-human primate (NHP) model is critical to the advancement of translational neuroscience, as it allows researchers to link observations regarding macroscale brain dynamics and cognition in the human to underlying meso- and microscale phenomena that cannot be fully investigated in humans. Importantly, the ultimate value of findings from the NHP for informing human models relies on the adequacy of methods for cross-species anatomical and functional alignment. In this regard, anatomical landmark-based methods for interspecies brain alignment have excelled in lower order sensory and motor areas, but faced limitation in registering heteromodal association areas, which have a paucity of landmarks. In response, we have developed an fMRI-based cross- species alignment framework that leverages recent advances in representation of network organization to generate a common coordinate space (referred to as “joint-embedding”). Our initial application of this function- based method for cortical alignment allowed us to quantify homologies between human and macaque in high detail at all levels of the cortical hierarchy. In this proposal, we will extend the joint-embedding alignment approach to align brain between human and non-human primates using multimodal MRI data (Aim 1). We will make use of the publicly availability of large sample multimodal MRI datasets (Human Connectome Project [HCP], Consortium for Reliability and Reproducibility [CoRR]), as well as recent openly shared non-human primate data (PRIMatE Data Exchange) to incorporate of within- and between species variations. We will assess the alignment performance by comparing to traditional landmark-based registration and unimodal joint- embedding alignments. Using the highest performing alignment to transform brain maps between species, we will quantify spatiotemporal similarities and divergence of brain network between human and macaque monkey based on autoregressive, quasi-periodic pattern, and coactivation pattern analysis (Aim 2). Additionally, we will transform the human cognitive ontology maps to macaque space and assess the similarities of corresponding brain networks for each cognitive component between human and macaque. We will also build an interactive webpage viewer to share the translation human cognition ontology in macaque (Aim 3). All data, data products (e.g. cross-species translation) and code generated will be openly shared through the open science resource - PRIME-DE.

抽象的 非人类灵长类动物（NHP）模型对于转化神经科学的进步至关重要，因为它允许 研究人员将有关人类宏观大脑动力学和认知的观察结果与潜在的联系起来 重要的是，无法在人类身上充分研究的介观和微观现象。 NHP 为人类模型提供信息的发现依赖于跨物种方法的充分性 在这方面，基于解剖学标志的跨种脑方法。 对齐在低阶感觉和运动领域表现出色，但在注册异模态方面面临限制 作为回应，我们开发了一种基于功能磁共振成像的交叉区域。 物种对齐框架利用网络组织表示的最新进展 生成一个公共坐标空间（称为“联合嵌入”）。 基于皮质对齐的方法使我们能够量化人类和猕猴之间的高同源性 在这个提案中，我们将扩展联合嵌入对齐。 使用多模态 MRI 数据来调整人类和非人类灵长类动物大脑的方法（目标 1）。 利用公开的大样本多模态 MRI 数据集（人类连接组项目 [HCP]、可靠性和再现性联盟 [CoRR]），以及最近共享的非人类 我们将评估灵长类动物数据（PRIMatE 数据交换），以纳入物种内和物种间的变异。 通过与传统的基于地标的配准和单峰联合进行比较来确定对齐性能 我们使用最高性能的对齐方式来转换物种之间的大脑图谱。 将量化人类和猕猴之间大脑网络的时空相似性和差异 基于自回归、准周期模式和共激活模式分析（目标 2）。 将人类认知本体图转换到猕猴空间并评估相应的相似性 我们还将为人类和猕猴之间的每个认知组件建立一个互动的大脑网络。 网页浏览器分享猕猴翻译的人类认知本体（目标3）。 （例如跨物种翻译）和生成的代码将通过开放科学资源公开共享 - PRIME-DE。

项目成果

Mapping and comparing fMRI connectivity networks across species.

• DOI: 10.1038/s42003-023-05629-w
• 发表时间: 2023-12-07
• 期刊: COMMUNICATIONS BIOLOGY
• 影响因子: 5.9
• 作者: Pagani, Marco;Gutierrez-Barragan, Daniel;de Guzman, A. Elizabeth;Xu, Ting;Gozzi, Alessandro
• 通讯作者: Gozzi, Alessandro