The Nature of Brain Networks in Cognitive Neuroimaging

认知神经影像中大脑网络的本质

• 批准号: 2218556
• 负责人: Felipe De Brigard
• 金额: $ 40.19万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2218556&HistoricalAwards=false
• 关键词: Nature; Brain; Networks; Cognitive; Neuroimaging

This project seeks to clarify conceptual challenges in the burgeoning field of network neuroimaging. Network neuroscience uses mathematical tools from graph theory to understand the brain, its relationship to the mind, and the neural basis of neurological and psychiatric illnesses. However, the highly abstract nature of network analysis has produced deep methodological and conceptual disagreements regarding what exactly network methods reveal about the brain and its functions. This project aims to clearly articulate these disagreements and to use tools from philosophy of science to develop the conceptual foundations necessary to resolve them. The project’s findings will be disseminated through both scholarly and public channels and will be of interest to practicing network neuroimagers, philosophers of science, clinical neuroscientists, and members of the general public interested in brain function and malfunction.The central points of disagreement among practicing network neuroscientists concern the extent to which the structures revealed in network neuroimaging are biologically meaningful, as opposed to merely instrumental mathematical abstractions, and relatedly, whether and to what extent functions can be attributed to these networks. The research team will analyze and build on survey results among practicing network neuroscientists that unveil these conceptual disagreements. The project then seeks to use tools from philosophy of science to develop a conceptual framework with two central aims: To show how different modeling commitments affect the extent to which brain networks can be interpreted as biologically real or meaningful, and to articulate the appropriate conditions under which functions can be attributed to brain networks. The results of this project will provide insight into both the strengths and limitations of network methods when employed for different research purposes in neuroscience. These insights will help researchers overcome hurdles that currently threaten progress in the field, will open new avenues of research in philosophy of science, and will facilitate clearer interpretations of results in this cutting-edge area of neuroscience.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目旨在澄清新兴的网络神经成像领域的概念挑战。网络神经科学使用图论的数学工具来理解大脑，它与思维的关系，以及神经和精神疾病的神经基础。然而，网络分析的高度抽象性在方法论和概念上产生了深刻的分歧，即网络方法究竟揭示了大脑及其功能。该项目旨在清楚地阐明这些分歧，并利用科学哲学的工具来发展解决这些分歧所需的概念基础。该项目的研究结果将通过学术和公共渠道传播，并将对网络神经成像师，科学哲学家，临床神经科学家和对大脑功能和故障感兴趣的普通公众感兴趣。网络神经科学家之间的主要分歧点涉及网络神经成像中揭示的结构在生物学上有意义的程度，而不仅仅是工具性的数学抽象，以及相关的，功能是否以及在多大程度上可以归因于这些网络。研究小组将分析并建立在实践网络神经科学家的调查结果基础上，揭示这些概念上的分歧。然后，该项目寻求使用科学哲学的工具来开发一个概念框架，该框架具有两个中心目标：展示不同的建模承诺如何影响大脑网络在生物学上被解释为真实的或有意义的程度，并阐明适当的条件下功能可以归因于大脑网络。这个项目的结果将提供深入了解网络方法的优势和局限性时，在神经科学中用于不同的研究目的。这些见解将帮助研究人员克服目前威胁该领域进展的障碍，将开辟科学哲学研究的新途径，并将促进对神经科学这一前沿领域结果的更清晰解释。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。