Intracranial Electrophysiology and Electrical Stimulation of the Human Default Mode Network

人类默认模式网络的颅内电生理学和电刺激

• 批准号: 1358907
• 负责人: Josef Parvizi
• 金额: $ 57.38万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1358907&HistoricalAwards=false
• 关键词: Intracranial; Electrophysiology; Electrical; Stimulation; Human

Our brains are highly active when we are up and about doing things, such as, cooking, eating, dancing, or when we are sitting quietly solving mathematical equations, or thinking about our past memories and future dreams. Only recently, scientists learned that a set of brain structures, known as the default mode network (DMN), show reduced activity during the performance of many tasks but increased activity when we are at rest or remembering what happened in the past. This is the opposite of what scientists have seen in many other areas of the brain. To date, almost the entire literature about the DMN function is based on neuroimaging methods (e.g. fMRI) that follow the changes of blood flow in the brain, and thus have limited temporal resolution. With support from the National Science Foundation, Drs. Parvizi and Wagner of Stanford University will combine functional imaging (fMRI), direct electrophysiological recordings from the surface of the human cerebral cortex (ECoG), and electrical brain stimulation (EBS) to measure the activity of DMN structures during rest, attention, and recall conditions and determine their interactions with brain areas involved in attention and memory functions. This study will provide unprecedented information about the modes of our brain function when we switch from rest to solving difficult tasks and vice versa. Pathological changes in the DMN are known to hallmark the onset of disorders such as Alzheimer's disease and attention-deficit disorder and autism all of which represent a pervasive public health issue. This project will lead to knowledge about the working of DMN and may one day contribute to development of intervention and treatment methods. Findings from this research will have significant societal impact. This collaborative research will also offer unique training opportunities for students and fellows to learn the multimodal approach with fMRI, ECoG, and EBS.

当我们起床做事时，比如做饭、吃饭、跳舞，或者当我们安静地坐着解数学方程，或者思考过去的记忆和未来的梦想时，我们的大脑是高度活跃的。直到最近，科学家们才了解到，一组被称为默认模式网络（DMN）的大脑结构在执行许多任务时活动减少，但在我们休息或回忆过去发生的事情时活动增加。这与科学家们在大脑的许多其他区域所看到的情况相反。迄今为止，几乎所有关于DMN功能的文献都是基于神经成像方法（如fMRI），这些方法遵循大脑血流的变化，因此时间分辨率有限。在美国国家科学基金会的支持下。斯坦福大学的Parvizi和Wagner将结合功能成像（fMRI）、人类大脑皮层表面的直接电生理记录（ECoG）和脑电刺激（EBS）来测量休息、注意力和回忆条件下DMN结构的活动，并确定它们与大脑中涉及注意力和记忆功能的区域的相互作用。这项研究将为我们从休息转向解决困难任务时的大脑功能模式提供前所未有的信息，反之亦然。DMN的病理变化是阿尔茨海默病、注意力缺陷障碍和自闭症等疾病发病的标志，这些疾病都是普遍存在的公共卫生问题。这个项目将有助于了解DMN的工作原理，并可能有一天有助于开发干预和治疗方法。这项研究的结果将产生重大的社会影响。这项合作研究还将为学生和研究员提供独特的培训机会，以学习fMRI， ECoG和EBS的多模态方法。