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(申请人提供)：大量研究表明，人类的认知依赖于大规模大脑网络中的活动。这种网络活动与意识的出现有关，与动机、同理心、神经质、外向和智商等各种个人特征有关，与阿尔茨海默氏症、中风、创伤性脑损伤、精神分裂症和抑郁症等临床疾病有关。因此，表征大脑连接的模式和动态对于理解人类大脑在健康和疾病中的工作方式是至关重要的。然而，大规模脑网络的研究通常使用相关方法，如功能磁共振成像(FMRI)、脑电或脑磁图，这些方法无法检测因果关系。因此，到目前为止，重点一直放在表征大脑网络的空间组成上，而较少强调网络内和网络间通信的动态。我们认为，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，并为理解网络交流提供一个宝贵的工具。这种方法使研究人员能够在不同任务的背景下观察人工诱导的神经信号向大脑其余部分的传播。的中心假说 该建议是，TMS的影响将仅在优先占用所述网络的休息或任务期间在目标区域的网络内扩展，但是其他网络的区域也将在同时占用两个网络的任务中受到影响。具体地说，我们将首先测试大脑网络是否由于休息时人工诱导的神经信号的传播而自发出现。然后，我们将进一步探索参与在优先激活目标脑区网络的任务中的作用， 或者是一个相互竞争的大脑网络。最后，我们开发了一项新的任务，激活两个单独的大脑网络，以测试它们之间的协调是否会导致起源于其中一个网络的区域的神经信号传播的变化。通过这种方式，拟议的项目将为对神经网络动力学的广泛研究铺平道路，这些研究可以导致对认知的基本见解，以及对大脑功能障碍的更深入理解。与美国国立卫生研究院的任务相关，这些研究中提出的脑网络识别可以作为开发诊断生物标记物以及认知治疗干预的目标，用于认知缺陷患者的神经或精神障碍的康复。