Investigating brain network dynamics with simultaneous TMS-fMRI

利用同步 TMS-fMRI 研究大脑网络动态

• 批准号: 8685046
• 负责人: MARK D'ESPOSITO
• 金额: $ 7.83万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-01 至 2016-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8685046
• 关键词: Affect; Alzheimer' s Disease; Area; Attention; Biological Markers; Biological Neural Networks; Brain; Brain region; Clinical; Cognition; Cognitive Therapy; Cognitive deficits; Communication; Conscious; Development; Diagnosis; Diagnostic; Disease; Dorsal; Electroencephalography; Empathy; Functional Magnetic Resonance Imaging; Functional disorder; Future; Health; Health Care Costs; Human; Individual; Intervention; Knowledge; Lead; Link; Literature; Mental Depression; Mental disorders; Methods; Mission; Motivation; Motor; Neurologic; Neurotic Disorders; Occipital lobe; Parietal; Patient Care; Patients; Pattern; Performance; Public Health; Rehabilitation therapy; Research; Research Personnel; Rest; Role; Scanning; Schizophrenia; Signal Transduction; Stroke; Testing; Time; Transcranial magnetic stimulation; Traumatic Brain Injury; United States National Institutes of Health; Work; base; cognitive function; cognitive neuroscience; flexibility; frontal eye fields; insight; nervous system disorder; novel; public health relevance; relating to nervous system; tool; trait; visual search

DESCRIPTION (provided by applicant): A large body of work has demonstrated that human cognition depends on the activity in large-scale brain networks. This network activity has been linked to the emergence of consciousness, to a variety of individual traits as diverse as motivation, empathy, neuroticism, extraversion, and IQ and to clinical conditions such as Alzheimer's, stroke, traumatic brain injury, schizophrenia and depression. Thus, characterizing the pattern and dynamics of brain connectivity is of utmost importance for understanding the workings of the human brain in both health and disease. However, large-scale brain networks are typically studied with correlational methods such as functional MRI (fMRI), EEG or MEG, which cannot detect causal relationships. Consequently, the focus to date has been on characterizing the spatial composition of the brain's networks with less emphasis on the dynamics of intra- and inter-network communication. We propose that the method of simultaneous transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) can fill this gap and provide an invaluable tool for understanding network communication. This method allows researchers to observe the spread of an artificially induced neural signal to the rest of the brain in the context of different tasks. The central hypothesis of this proposal is that the effect of TMS will only extend within the targeted region's network during rest or tasks that engage preferentially the said network, but that regions of other networks will also be affected in tasks that engage the two networks simultaneously. Specifically, we will first test whether brain networks emerge spontaneously as a result of the spread of artificially induced neural signals during rest. Then, we will further explore the role o engagement in a task that either preferentially activates the network of the targeted brain region, or a competing brain network. Finally, we have developed a novel task that activates two separate brain networks in order to test whether the coordination between them will result in a change in the spread of neural signals originating in a region belonging to one of the networks. In this way, the proposed project will pave the way for a wide range of studies on the dynamics of neural networks that can lead to fundamental insights of cognition, as well as a deeper understanding of brain dysfunction. Relevant to the NIH mission, identification of brain networks as proposed in these studies can serve as targets for the development of diagnostic biomarkers as well as cognitive therapy interventions for rehabilitation of patients with cognitive deficits de to neurological or psychiatric disorders.

描述（由申请人提供）：大量工作表明，人类认知取决于大型大脑网络的活性。这种网络活动与意识的出现有关，与动机，移情，神经质，外向性和智商等各种各种特征以及临床状况（如阿尔茨海默氏症，中风，创伤性脑损伤，精神分裂症和抑郁症）相关。因此，表征大脑连通性的模式和动力学对于理解人脑在健康和疾病中的运作至关重要。但是，通常使用相关方法（例如功能性MRI（fMRI），EEG）或MEG进行大规模的大脑网络，该方法无法检测到因果关系。因此，迄今为止的重点一直在表征大脑网络的空间组成，而对内部和网络间交流的动态较少。我们建议同时进行经颅磁刺激（TMS）和功能磁共振成像（fMRI）的方法可以填补这一空白，并为理解网络通信提供了宝贵的工具。这种方法使研究人员可以在不同任务的背景下观察人为诱导的神经信号向其他大脑的传播。中心假设 该建议是，TMS的效果只会在静止期间或优先涉及该网络的任务期间扩展到目标区域的网络内，但是其他网络的区域也会在同时参与两个网络的任务中受到影响。具体而言，我们将首先测试大脑网络是否是由于静止期间人为诱导的神经信号传播而自发出现的。然后，我们将进一步探讨在一个任务中的作用o，要么优先激活目标大脑区域的网络， 或竞争性的大脑网络。最后，我们开发了一项新的任务，该任务激活了两个单独的大脑网络，以测试它们之间的协调是否会导致源自属于一个网络的区域的神经信号的传播变化。通过这种方式，拟议的项目将为有关神经网络动力学的广泛研究铺平道路，这些研究可以导致认知基本的见解，并更深入地了解脑功能障碍。与NIH的任务相关，这些研究中提出的脑网络的鉴定可以作为开发诊断生物标志物的靶标，以及认知障碍患者对神经或精神病患者的康复患者的认知疗法干预措施。