Functional MRI Method Development

功能性 MRI 方法开发

• 批准号: 9152090
• 负责人: Peter Bandettini
• 金额: $ 168.83万
• 依托单位: NATIONAL INSTITUTE OF MENTAL HEALTH
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9152090
• 关键词: Accounting; Aerobic Exercise; Affect; Agreement; Anterior; Area; Attention; Attention Deficit Disorder; Auditory; Back; Behavioral; Blood flow; Brain; Brain Mapping; Brain Stem; Cardiac; Characteristics; Classification; Clinical; Cognition; Collaborations; Data; Data Quality; Development; Diagnosis; Discrimination; Drops; Education; Electroencephalography; Ensure; Evaluation; Evoked Potentials; Excision; Exercise; Eye; Face; Functional Imaging; Functional Magnetic Resonance Imaging; Future; Goals; Growth; Hand; Hippocampus (Brain); Human; Image; Individual; Inferior Colliculus; Intervention; Letters; Machine Learning; Magnetic Resonance Imaging; Maps; Measures; Medical Imaging; Mental Depression; Mental disorders; Methodology; Methods; Modality; Modeling; Morphologic artifacts; Motion; Nature; Neurologic; Neurons; Neurosciences; Neurosciences Research; Noise; Output; Paper; Parietal; Pattern; Physiological; Pilot Projects; Positioning Attribute; Post-Traumatic Stress Disorders; Process; Protocols documentation; Publishing; Reading; Relative (related person); Reporting; Research; Research Methodology; Rest; Rodent; Running; Scanning; Series; Signal Transduction; Site; Societies; Solutions; Source; Statistical Methods; Stimulus; Structure; Structure of middle temporal gyrus; Structure of superior temporal sulcus; Task Performances; Techniques; Technology; Testing; Time; Transcranial magnetic stimulation; Universities; Work; abstracting; auditory pathway; base; design; gray matter; imaging modality; improved; meetings; mental state; method development; myelination; neurogenesis; neuroimaging; relating to nervous system; response; sustained attention; treatment planning; visual motor

Protocol number 93-M-0170, NCT00001360 The Section on Functional Imaging Methods (SFIM) has advanced functional MRI (fMRI) methodology through development of processing and acquisition methods and research on the underlying mechanisms behind the fMRI signal. The ultimate goals are to gain a deeper understanding of the healthy human brain and to apply fMRI clinically on an individual basis. Moment-to-Moment Classification of Sustained Attention (David Jangraw) Towards developing approaches for fMRI of individuals, we have been developing a new project in which we study the sources and natural fluctuations of sustained attention, the act of focusing on a single task for an extended period of time. This area of study has implications for mental disorders in which sustained attention abilities are affected, such as depression, attention deficit disorder, and post-traumatic stress disorder. We have developed pilot studies in which we record behavioral, eye tracking, and other physiological data as subjects perform a reading task in the presence or absence of distracting stimuli. We use the data to build a machine learning classifier that can distinguish moments when a subject is maintaining attention on the task at hand from moments when their attention wanes. Future work will use the classifier output as an objective moment-to-moment readout of sustained attention in an fMRI scanner, facilitating clearer pictures of the neural processes involved and potentially developing real-time interventions to improve sustained attention in education. Correlations Between EEG and fMRI Activity After ME-ICA Denoising (Jen nifer Evans) The technique of Multi-Echo ICA-based denoising (ME-ICA) has been used to reduce the influence of non-BOLD noise, including slow scanner drifts in the fMRI signal, enhancing the ability to study slow changes in neural activity that overlap with slow drifts, such as engagement and time-on-task effects. The contrast of a checkerboard was very slowly varied to create a slowly changing signal in both BOLD data and EEG evoked potential envelope. We separated the slow induced BOLD changes from slow non-BOLD drifts in the fMRI data using multi-echo fMRI and ME-ICA denoising. We then investigated the correspondence of the denoised data with the neural response. We found strong agreement between modalities, demonstrating the ability of ME-ICA denoising to reveal slow on the order of minutes - neural fluctuations while excluding the effects of scanner drift. Effect of Theta Burst TMS on Resting Connectivity Using Multi-Echo fMRI (Dan iel Handwerker, David Pitcher - LBC) We used multi-echo fMRI and ME-ICA denoising to examine the effect of theta burst transcranial magnetic stimulation (TBS) to the right superior temporal sulcus vs a control region, the right hand knob. When TBS was directed at the right parietal superior temporal sulcus (rpSTS), there was a decrease in connectivity between the rpSTS to the fusiform, middle occipital, and middle temporal gyri. These results show that TBS to the rpSTS selectively decreases functional connections to face-selective regions even without task-evoked responses. The preliminary results will be presented at the Society for Neuroscience Annual Meeting in October 2015. Quantitation of Gains in Contrast to Noise Ratio and Stability of ME-EPI (Ben Gutierrez, Dan Handwerker). We collected 103 five-minute multi-echo runs from two individuals while they performed a visuomotor task with a letter/number discrimination component and then characterized the improvement data quality and spatial reliability of activation maps by ME-EPI relative to standard approaches. We also demonstrated how that more gray matter voxels become reliably activated with considerably less data when using multi-echo EPI acquisition. These results were presented at the Organization for Human Brain Mapping Annual Meeting in June 2015. BOLD Connectivity Dynamics and its Relationship to Mental States (Javier Gonzalez-Castillo) In this study, we demonstrate a direct relationship between ongoing cognition and dynamic changes in whole-brain patterns of connectivity at the scale of tens of seconds. In a recent report we show how it is possible to accurately track on-going cognition (as imposed by task) at the individual level using BOLD connectivity patterns computed from data traces corresponding to time windows as short as 22.5 s econds. Tracking accuracy dropped markedly for subjects with the lowest task performance, confirming the relationship to ongoing cognition. Finally we also demonstrate that restricting connectivity patterns to a select group of ROIs decreases accuracy, emphasizing the distributed nature of cognitively meaning changes in dynamic connectivity. Evaluation of ME-ICA for Removal of T1 Baseline Shifts in Cardiac Gated fMRI (Javier Gonzalez-Castillo, Laura Buchanan) Imaging the brainstem with BOLD fMRI is difficult due to the pulsatile motion of blood flowing through large vasculature surrounding this neuronal structure. One solution is to trigger fMRI acquisitions in synchrony with the cardiac cycle, to ensure the brainstem is imaged always in the same position (cardiac-gated fMRI). Yet, the non-constant TR associated with cardiac-gated fMRI leads to artifactual baseline signal shifts (of a T1 origin) that need to be properly accounted for. ME-ICA has the potential to correct for T1 related artifacts (such as those present in cardiac-gated fMRI) in a completely data driven approach. In this study, we used an auditory block design paradigm to activate inferior colliculus (a small structure in the back of the brainstem part of the ascending auditory pathway). ME-ICA is able to reliably capture and remove signal baseline associated with variable TRs. Results also demonstrate improvements in detectability of BOLD activation in the inferior colliculus as compared with single-echo fMRI combined with model-driven removal. These results highlight the sensitivity of ME-ICA to T1-related artifacts of a different origin to those tested in other studies from our group, and demonstrate its feasibility for improving fMRI-BOLD studies focused in brainstem structures. Change in Hippocampal Myelination with Aerobic Exercise (Adam Thomas) In collaboration with Dr. Heidi Johansen-Berg at Oxford University, we have demonstrated volume growth in the anterior hippocampus after just six weeks of aerobic exercise. Previous rodent studies have shown the hippocampus to be a site of neurogenesis, which is facilitated by exercise. We went on to use nine different neuroimaging measures to characterize the change in anterior hippocampus. Using advanced statistical methods designed by Dr. Thomas Nichols at the University of Warwick, we were able to demonstrate that the change is dominated by myelination and not by grey matter or vasculature as other groups have predicted. This work has just received a favorable review at NeuroImage and will be published shortly.

协议号 93-M-0170，NCT00001360 功能成像方法部分 (SFIM) 通过开发处理和采集方法以及研究 fMRI 信号背后的潜在机制，拥有先进的功能 MRI (fMRI) 方法。最终目标是更深入地了解健康人脑，并将功能磁共振成像应用于个体临床。 持续注意力的时刻分类（David Jangraw） 为了开发个人功能磁共振成像方法，我们一直在开发一个新项目，在该项目中我们研究持续注意力的来源和自然波动，即长时间专注于单一任务的行为。这一领域的研究对于影响持续注意力能力的精神障碍具有重要意义，例如抑郁症、注意力缺陷障碍和创伤后应激障碍。我们开展了试点研究，记录受试者在存在或不存在干扰刺激的情况下执行阅读任务时的行为、眼动追踪和其他生理数据。我们使用这些数据构建一个机器学习分类器，可以区分受试者对手头任务保持注意力的时刻和注意力减弱的时刻。未来的工作将使用分类器输出作为功能磁共振成像扫描仪中持续注意力的客观即时读数，促进更清晰地了解所涉及的神经过程，并有可能开发实时干预措施以提高教育中的持续注意力。 ME-ICA 去噪后 EEG 和 fMRI 活动之间的相关性 (Jen nifer Evans) 基于多回波 ICA 的去噪 (ME-ICA) 技术已用于减少非 BOLD 噪声的影响，包括功能磁共振成像信号中的扫描仪缓慢漂移，从而增强研究与缓慢漂移重叠的神经活动缓慢变化的能力，例如参与度和任务时间效应。棋盘格的对比度非常缓慢地变化，以在 BOLD 数据和 EEG 诱发电位包络中产生缓慢变化的信号。我们使用多回波 fMRI 和 ME-ICA 去噪将 fMRI 数据中缓慢引起的 BOLD 变化与缓慢的非 BOLD 漂移分开。然后我们研究了去噪数据与神经反应的对应关系。我们发现模式之间存在很强的一致性，证明 ME-ICA 去噪能够揭示分钟级的缓慢神经波动，同时排除扫描仪漂移的影响。 使用多回波 fMRI 进行 Theta Burst TMS 对静息连接的影响（Dan iel Handwerker、David Pitcher - LBC） 我们使用多回波功能磁共振成像和 ME-ICA 去噪来检查 theta 突发经颅磁刺激 (TBS) 对右侧颞上沟与控制区域（右手旋钮）的影响。当 TBS 指向右顶叶颞上沟 (rpSTS) 时，rpSTS 与梭状回、枕中回和颞中回之间的连接性降低。这些结果表明，即使没有任务诱发的反应，rpSTS 的 TBS 也会选择性地减少与面部选择性区域的功能连接。初步结果将于 2015 年 10 月在神经科学学会年会上公布。 ME-EPI 的噪声比对比增益和稳定性定量（Ben Gutierrez、Dan Handwerker）。 我们收集了两个人的 103 次五分钟多回波运行，同时他们执行带有字母/数字辨别组件的视觉运动任务，然后表征了 ME-EPI 相对于标准方法改进的数据质量和激活图的空间可靠性。我们还演示了在使用多回波 EPI 采集时如何以相当少的数据可靠地激活更多的灰质体素。这些结果已在 2015 年 6 月的人脑图谱组织年会上公布。 大胆的连接动态及其与心理状态的关系（哈维尔·冈萨雷斯-卡斯蒂略） 在这项研究中，我们证明了持续认知与数十秒范围内全脑连接模式的动态变化之间的直接关系。在最近的一份报告中，我们展示了如何使用从与短至 22.5 秒的时间窗口相对应的数据轨迹计算出的 BOLD 连接模式，在个体层面上准确跟踪正在进行的认知（由任务施加）。对于任务表现最低的受试者，跟踪准确性显着下降，证实了与持续认知的关系。最后，我们还证明，将连接模式限制为选定的一组 ROI 会降低准确性，强调动态连接中认知意义变化的分布式本质。 ME-ICA 去除心脏门控 fMRI 中 T1 基线偏移的评估 (Javier Gonzalez-Castillo, Laura Buchanan) 由于血液流经围绕神经元结构的大血管系统的脉动运动，因此使用 BOLD fMRI 对脑干进行成像很困难。一种解决方案是触发与心动周期同步的功能磁共振成像采集，以确保脑干始终在同一位置成像（心门控功能磁共振成像）。然而，与心脏门控 fMRI 相关的非恒定 TR 会导致（T1 起源的）人为基线信号偏移，需要适当考虑。 ME-ICA 有潜力以完全数据驱动的方法纠正 T1 相关伪影（例如心脏门控 fMRI 中存在的伪影）。在这项研究中，我们使用听觉块设计范例来激活下丘（上行听觉通路脑干部分后部的一个小结构）。 ME-ICA 能够可靠地捕获和删除与可变 TR 相关的信号基线。结果还表明，与单回波功能磁共振成像结合模型驱动去除相比，下丘 BOLD 激活的可检测性有所提高。这些结果强调了 ME-ICA 对与我们小组其他研究中测试的来源不同的 T1 相关伪影的敏感性，并证明了其改进专注于脑干结构的 fMRI-BOLD 研究的可行性。 有氧运动改变海马髓鞘形成（亚当·托马斯） 我们与牛津大学的 Heidi Johansen-Berg 博士合作，证明了经过六周的有氧运动后，前海马体的体积有所增长。先前的啮齿动物研究表明，海马体是神经发生的部位，运动可以促进神经发生。我们继续使用九种不同的神经影像学指标来表征前海马体的变化。使用华威大学托马斯·尼科尔斯博士设计的先进统计方法，我们能够证明这种变化是由髓鞘形成主导的，而不是像其他小组预测的那样由灰质或脉管系统主导。这项工作刚刚在 NeuroImage 上获得了好评，并将很快发表。