Infrastructure for hyperaligning fMRI data and estimating functional topographies

项目总结 皮质功能架构中的共享信息嵌入在 独特性，对脑功能成像研究构成了主要障碍。超对齐 通过将来自个体大脑的信息投射到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，将 使脑成像研究社区能够利用超对齐来极大地丰富其 数据，支持分析共享信息和嵌入在 独特的精细皮质地貌，并创建数据共享平台 超对齐的公共模型信息空间。基础设施将是一个优化的、 基于标准化数据库、交钥匙软件的标准化模板公共模型空间 用于高度调整新大脑和估计个人功能拓扑图的工具，以及 共享超匹配数据的框架。这些数据和工具将提供社区 为临床神经科学、脑科学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。拟议的数据库将由60%的功能磁共振数据组成 参与者在观看电影、听故事、休息和大型活动期间收集 功能定位词，增加了人口统计信息以及认知和个性 考试成绩。 具体目标 1.根据标准化的标准生成用于超对齐的优化、标准化模板 带有开源软件的数据库，将允许绘制许多功能 基于规范样本中的标准定位器数据的地形，转换为新的 参与者的大脑只使用在新参与者观看电影时收集的功能磁共振数据， 听一个故事，或者休息。 2.调整超比对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绘制地形。开发新的超级比对 增强功能、精确度和灵活性的算法。 3.创建一个共享功能脑成像数据的系统，这些数据被投影到 公共信息空间模型，允许在以下框架中积累数据 提供细粒度的细节。HyperAlign现有公共数据集。

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.