CRCNS: Collaborative Research: A Common Model of the Functional Architecture of Human Cortex

CRCNS：协作研究：人类皮质功能架构的通用模型

• 批准号: 1607801
• 负责人: Peter Ramadge
• 金额: $ 30.73万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1607801&HistoricalAwards=false
• 关键词: CRCNS; Collaborative; Research; Common; Model

The human brain is perhaps the most complex known object and is the vessel that contains our thoughts, experiences, knowledge, and, collectively, our culture. Although brains have similar anatomical components, differences in size and shape and in fine structure make it difficult to discern how different brains can contain similar thoughts and knowledge that can be shared and communicated. A major challenge for brain science is to build a common model of the functional architecture of the brain that captures these similarities that are shared across brains at a fine scale. The research in this project is aimed at developing a computational basis for such a common model. The model is based on measurement of patterns of brain activity using functional magnetic resonance imaging (fMRI) while participants engage in everyday cognitive activities like watching a movie, listening to a story, or free-ranging thought while at rest. The model aligns the functional architecture of the brain at multiple scales, from fine to coarse, and captures far more shared structure than is possible with other methods that are based on alignment of brain anatomy. This model will provide infrastructure that can be used by scientists who image the brain in order to study a wide range of brain functions, from perception to social interaction, emotion, and decision making, allowing them to describe the mechanisms underlying these functions in a format that can be communicated across laboratories with a level of detail and precision that will accelerate discovery and application.Alignment of brain imaging data has relied on anatomical features that have a variable correspondence to the underlying functional architecture. Moreover, such alignment methods do not capture the fine structure of brain activity patterns that can be decoded using modern pattern analytic methods. The research in this project is based on aligning representational spaces across brains, rather than anatomical topographies, and will identify the boundaries between patches of cortex with distinct representational spaces. This innovation affords greatly superior alignment of functional architecture across brains and the development of a common model of the human brain. The research will develop computational algorithms for transforming the idiosyncratic organization of individual brains into the common representational spaces and for fine-tuning the description of individual brains by projecting, or shrink-wrapping, the common model based on a large number of individuals onto that individual brain. The development of these computational algorithms and the model will be integral to the training of graduate students and postdoctoral fellows. They will be made available as free and open-source software, with large shared data sets, to be shared and used freely by brain imaging scientists around the world, providing essential research infrastructure to maximize the impact and benefit of this research project.

人脑可能是已知的最复杂的物体，是包含我们的思想、经验、知识以及我们的文化的容器。尽管大脑有相似的解剖成分，但大小、形状和精细结构的差异使得人们很难分辨不同的大脑如何包含相似的思想和知识，这些想法和知识可以共享和交流。脑科学面临的一个主要挑战是建立一个大脑功能结构的通用模型，以捕捉这些在精细尺度上在大脑中共享的相似性。这个项目的研究目的是为这样一个共同的模型开发一个计算基础。该模型基于使用功能磁共振成像(FMRI)测量大脑活动模式的基础上，参与者在休息时参与日常认知活动，如看电影、听故事或自由思考。该模型在多个尺度上对齐大脑的功能架构，从精细到粗略，并捕获了比其他基于大脑解剖学对齐的方法可能捕捉到的更多的共享结构。该模型将提供可供成像大脑的科学家使用的基础设施，以研究从感知到社会互动、情绪和决策的广泛的大脑功能，使他们能够以一种可以跨实验室以详细和精确的形式描述这些功能背后的机制，从而加速发现和应用。大脑成像数据的对齐依赖于与潜在功能架构具有可变对应的解剖特征。此外，这种比对方法没有捕捉到可以使用现代模式分析方法破译的大脑活动模式的精细结构。这个项目的研究是基于对齐整个大脑的表征空间，而不是解剖结构，并将确定具有不同表征空间的皮质斑块之间的边界。这一创新为整个大脑的功能架构提供了极大的优势，并开发了一个人类大脑的通用模型。这项研究将开发计算算法，将个体大脑的特殊组织转换为共同的表征空间，并通过将基于大量个体的共同模型投影或收缩包装到该个体大脑上来微调对个体大脑的描述。这些计算算法和模型的开发将是培养研究生和博士后研究员不可或缺的一部分。它们将以免费和开源软件的形式提供，并带有大量共享数据集，供世界各地的脑成像科学家自由共享和使用，提供必要的研究基础设施，以最大限度地发挥这一研究项目的影响和好处。