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Model-based functional spectroscopy of brain metabolites associated with cognition

基于模型的与认知相关的大脑代谢物的功能光谱

基本信息

批准号：
2883390
负责人：
金额：
--
依托单位：
University of Nottingham
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2023
资助国家：
英国
起止时间：
2023 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2883390
关键词：
Model based functional spectroscopy brain

项目摘要

How can we better understand cognitive impairments in mental health disorders? If we do, we may be able to better target future therapies. This challenge requires the development of new brain imaging techniques. In particular, differences in neurochemicals (such as glutamate or GABA) in the brain may explain the differences we observe in cognitive function. In this project, we will develop new tools using functional MR spectroscopy (fMRS) to non-invasively detect neurochemical changes while participants engage in a cognitive task. This offers a promising technique to investigate cognition. However, sensitivity to detect changes is limited by measurement noise. In addition, neurochemical data is collected separately to the concomitant blood response which occurs during brain activation (fMRI). We will research new data-driven computational approaches to model neurochemical changes. We will also combine fMRS with fMRI scans allowing us to obtain more information simultaneously. The developed techniques will be applied to study neurochemical changes in healthy volunteers during performance monitoring, which is often impaired in individuals with psychosis.The student will engage with interdisciplinary teams of physicists, neuroscientists and engineers. They will gain computational skills (Python, C++) coding their own pipelines and MR sequences to run on the 7 T MR scanner.

我们如何更好地了解心理健康障碍中的认知障碍？如果我们这样做，我们可能能够更好地针对未来的治疗。这一挑战需要开发新的脑成像技术。特别是，大脑中神经化学物质（如谷氨酸或GABA）的差异可以解释我们在认知功能中观察到的差异。在这个项目中，我们将开发新的工具，使用功能磁共振波谱（fMRS），以非侵入性地检测神经化学变化，而参与者从事认知任务。这为研究认知提供了一种很有前途的技术。然而，检测变化的灵敏度受到测量噪声的限制。此外，神经化学数据是单独收集的伴随血液反应，发生在大脑激活（功能磁共振成像）。我们将研究新的数据驱动的计算方法来模拟神经化学变化。我们还将联合收割机与功能磁共振成像扫描相结合，使我们能够同时获得更多的信息。开发的技术将应用于研究健康志愿者在性能监测过程中的神经化学变化，这在精神病患者中通常会受损。学生将与物理学家，神经科学家和工程师的跨学科团队合作。他们将获得计算技能（Python，C++）编码自己的管道和MR序列在7 T MR扫描仪上运行。