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发展至关重要，因为它允许 研究人员将有关人类宏观脑动力学和认知的观察结果联系起来 在人类中无法全面研究的中间和微观现象。重要的是，最终价值 NHP的调查结果为人类模型提供信息，取决于跨物种方法的充分性 解剖和功能对准。在这方面，基于地标的大脑的解剖学地标方法 对齐在较低的感觉和运动区域具有出色 协会区，存在着很少的地标。作为回应，我们开发了一个基于fMRI的跨盘 物种对齐框架，利用网络组织代表的最新进展 产生一个共同的坐标空间（称为“联合装饰”）。我们对此功能的初步应用 - 基于皮质比对的方法使我们能够量化人与猕猴之间的同源性 皮质层次结构各个层面的细节。在此提案中，我们将扩展联合对齐方式 使用多模式MRI数据在人与非人类灵长类动物之间对齐大脑的方法（AIM 1）。我们将 利用大型样本多模式MRI数据集的公开供应（人类Connectome Project [HCP]，可靠性和可重复性的财团[corr]），最近公开共享非人类 灵长类动物数据（灵长类动物数据交换），以纳入物种内部和物种变化之间。我们将评估 通过与传统的基于地标的注册和单峰联合 - 嵌入对齐。使用性能最高的对准来改变物种之间的大脑图，我们 将量化人与猕猴之间的时空相似性和大脑网络的差异 基于自回归，准周期模式和共激活模式分析（AIM 2）。此外，我们会的 将人类认知本体图将其转换为猕猴的空间并评估相应的相似性 人与猕猴之间的每个认知成分的大脑网络。我们还将建立一个互动 网页查看器分享猕猴中的翻译人类认知本体（AIM 3）。所有数据，数据产品 （例如，跨物种翻译）和生成的代码将通过开放的科学资源公开共享 - 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