Correcting Motion and Physiological Noise: key barriers in resting state fMRI

描述（由申请人提供）：静息状态功能连接MRI （rs-fcMRI）已成为绘制大脑功能组织的关键无创技术。这种组织或功能连通性在神经或精神疾病中经常发生改变。Rs-fcMRI有望产生重大的临床影响，因为可以在不需要受试者执行任何特定任务的情况下对大量功能相关的大脑网络进行表征。这很重要，因为许多临床或研究人群要么受到他们在MRI扫描仪中执行任务的能力的限制，要么在任务表现上存在差异。此外，rs-fcMRI在确定许多精神和神经疾病的基础方面具有很大的前景。然而，一个关键的问题是，受试者的运动和生理噪音（特别是呼吸深度和呼吸频率的变化）会导致大脑的各个区域看起来好像它们在功能上是相连的。虽然已经开发了许多技术来纠正运动和生理噪声，但目前还没有就应用哪些处理步骤达成共识。更重要的是，即使有了现有的技术，由运动和生理噪声引起的误报仍然存在。因此，尚不清楚观察到的跨时间或受试者之间的功能连接差异是否真的是神经元起源，还是仅仅是受试者运动差异或生理噪音的结果。这是rs-fcMRI未来应用的一个重大障碍。本研究的目的是减少受试者头部运动和生理噪声的影响，以提高脑功能连接映射的准确性和一致性。为了实现这一目标，提出了两个互补的策略：1)开发一种新的MRI采集方案，该方案对运动和生理波动更具鲁棒性；2)开发新的处理方法，以更好地模拟和解释运动和呼吸引起的伪影。这些新的处理技术包括使用外部获取信息的方法，以及适用于现有数据集的方法，这对于已经获得的大量数据非常重要。这项研究的预期结果是在绘制不同时间和受试者之间大脑功能组织差异的能力上有显著的提高。这一信息将对当前和未来数百项rs- fcMRI研究产生重大影响。这是在临床研究中成功使用静息状态功能连接的关键一步，也是旨在提高我们对大脑发育的理解的研究，精神和神经疾病中大脑组织的破坏，以及导致后来精神病理的发育轨迹的改变（并且是一个风险因素）。

DESCRIPTION (provided by applicant): Resting-state functional connectivity MRI (rs-fcMRI) has emerged as a key noninvasive technique for mapping the functional organization of the brain. This organization, or functional connectivity, is often altered in neurological or mental disorders. Rs-fcMRI is poised to have a significant clinical impact, since a large number of functionally relevant brain networks can be characterized without requiring the subject to perform any specific tasks. This is important, since many clinical or research populations are either limited by their ability to perform tasks in the MRI scanner or have differences in task performance. In addition, rs-fcMRI holds great promise for determining the basis of many mental and neurological disorders. However, a critical problem is that subject motion and physiological noise (from variations in respiration depth and rate in particular) can cause regions of the brain to appear as if they are functionally connected. While a number of techniques have been developed to correct for motion and physiological noise, there is currently no consensus on which processing steps to apply. More importantly, even with available techniques, false positives resulting from motion and physiological noise remain. It is therefore unclear whether observed differences in functional connectivity across time or between subjects are truly neuronal in origin, or merely the result of differences in subject motion or physiological noise. This presents a significant barrier to the future utility of rs-fcMRI. The goal of the proposed research is to reduce the influence of subject head motion and physiological noise in order to improve the accuracy and consistency of mapping functional brain connectivity. Two complementary strategies are proposed to achieve this goal: 1) the development of a novel MRI acquisition scheme that is more robust to motion and physiological fluctuations; and 2) the development of new processing methods to better model and account for motion and respiration induced artifacts. These new processing techniques consist of methods that use externally-acquired information, as well as methods that are applicable to existing datasets, which is important given the wealth of data already acquired. The expected outcome of this study is a significant improvement in the ability to map differences in the functional organization of the brain across time and between subjects. This information will have a significant impact on hundreds of current and future rs- fcMRI studies. It is a critical step towards the successful use of resting-state functional connectivity in clinical investigations, as well as research studies aimed at improving our understanding of brain development, the disrupted brain organization in mental and neurological disorders, and the alterations in developmental trajectories that lead to (and are a risk factor for) later psychopathology.