Infrastructure for hyperaligning fMRI data and estimating functional topographies

用于超对齐功能磁共振成像数据和估计功能拓扑的基础设施

• 批准号: 10689268
• 负责人: Maria I Gobbini
• 金额: $ 64.84万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-23 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10689268
• 关键词: Aging; Algorithms; Alzheimer' s Disease; Anatomy; Architecture; Atlases; Brain; Brain imaging; Clinical; Communities; Computer software; Consumption; Data; Data Aggregation; Data Set; Databases; Functional Magnetic Resonance Imaging; Generations; Grain; Hour; Human; Individual; Individual Differences; Infrastructure; Inosine Dialdehyde; Maps; Modeling; Molecular Conformation; Neurosciences; Participant; Personality Tests; Population; Population Analysis; Principal Investigator; Research; Research Infrastructure; Research Personnel; Research Project Grants; Research Support; Resources; Rest; Sampling; Scanning; Software Tools; Space Models; Standardization; Structure; Surface; System; Time; Work; affective neuroscience; aging brain; behavior prediction; cognitive neuroscience; cognitive testing; connectome; cortex mapping; cost effective; data sharing; experimental analysis; flexibility; high dimensionality; information model; movie; neuroimaging; open source; preservation; response; sharing platform; tool

PROJECT SUMMARY Shared information in cortical functional architecture is embedded in topographies that are idiosyncratic, posing a major impediment for functional brain imaging research. Hyperalignment resolves this problem by projecting information from individual brains into a common model information space. The proposed research project will create HyperBase – research infrastructure that will enable the brain imaging research community to leverage hyperalignment to greatly enrich their data, enable analyses of shared information and individual differences embedded in idiosyncratic fine-scale cortical topographies, and create a data sharing platform for data in the hyperaligned common model information space. The infrastructure will be an optimized, standardized template common model space based on a normative database, turnkey software tools for hyperaligning new brains and estimating individual functional topographies, and a framework for sharing hyperaligned data. These data and tools will provide community infrastructural support for research on a broad range of topics in clinical neuroscience, brain aging, and basic cognitive neuroscience. The proposed database will consist of fMRI data in 60 participants collected during movie viewing, story listening, at rest, and during a large set of functional localizers, augmented with demographic information and cognitive and personality test scores. Specific aims 1. Produce an optimized, standardized template for hyperalignment based on a normative database with open-source software that will allow mapping numerous functional topographies, based on standard localizer data in the normative sample, into new participant brains using only fMRI data collected while the new participants watch a movie, listen to a story, or are at rest. 2. Adapt hyperalignment algorithms to work with a standard template and estimate functional topographies via the template and normative localizer data. Develop new hyperalignment algorithms that increase power, precision, and flexibility. 3. Create a system for sharing functional brain imaging data that are projected into the common information space model, allowing accumulation of data in a framework that affords at a fine-grained level of detail. Hyperalign existing public datasets.

项目摘要 皮层功能结构中的共享信息嵌入在 这是脑功能成像研究的一个主要障碍。超排列 通过将来自个体大脑的信息投射到一个共同的模型中来解决这个问题 信息空间 拟议的研究项目将创建HyperBase -研究基础设施， 使大脑成像研究社区能够利用超对齐来极大地丰富他们的 数据，使分析共享的信息和个人差异嵌入 独特的精细尺度皮层地形图，并创建一个数据共享平台， 超对齐公共模型信息空间。基础设施将是优化的， 标准化模板公共模型空间基于规范数据库，交钥匙软件 用于超排列新大脑和估计个体功能地形的工具，以及 共享超对齐数据的框架。这些数据和工具将为社区提供 为临床神经科学、大脑等广泛主题的研究提供基础设施支持 衰老和基础认知神经科学。拟议的数据库将包括60个国家的功能磁共振成像数据。 参与者在看电影，听故事，休息时和在一个大型的 功能定位器，增加人口统计信息和认知和个性 考试成绩 具体目标 1.基于标准化的超比对生成优化的标准化模板 数据库与开源软件，将允许映射许多功能 地形，基于标准样本中的标准定位器数据，进入新的 参与者的大脑只使用新参与者看电影时收集的功能磁共振成像数据， 听一个故事，或在休息。 2.调整超对齐算法以使用标准模板并估计泛函 通过模板和标准定位器数据的地形。开发新的超对齐 算法，提高功率，精度和灵活性。 3.创建一个系统，用于共享投影到 公共信息空间模型，允许在一个框架中积累数据， 提供了精细的细节。Hyperalign现有公共数据集。