Functional MRI Method Development

功能性 MRI 方法开发

• 批准号: 9589754
• 负责人: Peter Bandettini
• 金额: $ 212.43万
• 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/9589754
• 关键词: Algorithms; Arousal; Attention; Automobile Driving; Back; Behavior; Behavioral; Belief; Blood Volume; Brain; Brain Mapping; Brain region; Characteristics; Classification; Clinical; Collaborations; Complex; Cortical Column; Data; Detection; Development; Diagnosis; Early identification; Electroencephalography; Elements; Epilepsy; Etiology; Evaluation; Event; Excision; Feeling; Functional Imaging; Functional Magnetic Resonance Imaging; Goals; Image; Individual; Individual Differences; Intervention; Link; Location; Magnetic Resonance Imaging; Maps; Mathematics; Measures; Medical Imaging; Mental disorders; Methodology; Methods; Mind; Modeling; Neurologic; Neurons; Neurosciences Research; Noise; Paper; Paranoia; Participant; Patients; Pattern; Performance; Physiological; Population; Protocols documentation; Research; Resolution; Rest; Risk; Scanning; Scheme; Series; Signal Transduction; Slice; Specificity; Standardization; Stimulus; Stress Tests; Surface; Techniques; Testing; Time; Visual; Work; association cortex; base; blood oxygen level dependent; cognitive task; cortex mapping; design; experimental study; flexibility; functional MRI scan; hemodynamics; imaging modality; mental imagery; mental state; method development; movie; neuroimaging; novel; psychologic; response; sensorimotor system; social; spatiotemporal; specific biomarkers; sustained attention; trait; treatment planning; ultra high resolution

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 as well as research on the underlying mechanisms behind the fMRI signal. Our work over the past year has focused on methods to extract more information related to tasks, mental state, and individual traits from the fMRI time series. At high resolution we have more accurately mapped cortical layer connectivity and activity. Due to limited space, we decided to highlight here a few projects that are representative of our ongoing work. Multi-Echo Applications Our group has been pioneering the development and use of Multi-echo fMRI (ME fMRI). Because blood oxygen level dependent (BOLD) and non-BOLD signal fluctuations behave differently as a function of echo time, the unique ME fMRI acquisition of at least one echo allows for efficient and robust detection and removal of non-BOLD fluctuations from the time series. Our work developing and utilizing ME fMRI continues. In collaboration with Dr. Caballero-Gaudes, we are working on the detection of individual BOLD events with no information about the task timing or location. Preliminary tests show that the algorithm can reliably detect BOLD events associated with each individual trial in a manner similar to traditional GLM methods, yet without any information on paradigm timing. This new method has important applications including: uncovering hemodynamic events driving dynamic resting functional connectivity, and detecting inter-ictal events in epilepsy patients without the need for concurrent EEG recordings. Dynamic Functional Connectivity Dynamic functional connectivity (FC), understood as patterns of functional brain connectivity that change at the scale of seconds to minutes, has gained great attention in recent years. FC configurations can differ significantly from those obtained from entire time series, and recent studies suggest there is a link between these dynamics and individual behavior and behavioral traits. We previously demonstrated how whole-brain short-term FC patterns could be used to identify cognitive tasks. We are currently investigating how these patterns may provide useful behaviorally-relevant information about individual subjects to be used as a biomarker for specific traits. We are also investigating elements that drive these dynamics and differences in dynamics ranging from changes in arousal and engagement to changes in attention. Lastly, we are exploring the degree to which dynamics of specific networks can predict behavior. Towards the goal of deriving specific individual traits from FC network strengths, we had subjects perform a 2-back task, look for a visual target in a movie, and solve math problems. Performance was recorded on each task. Surprisingly, the sustained attention network (previously found) provided better prediction of performance than the 2-back-specific network. fMRI Connectivity vs. fMRI Magnitude Changes Our work on task-based connectivity change assessment has opened up an entirely new vista in fMRI processing. We have revealed that, for cognitive tasks, task based connectivity changes are more spatially extensive than magnitude changes and more specific or sensitive for a given task. This observation potentially opens a new subfield of brain mapping where connectivity changes are mapped rather than magnitude changes. We are actively exploring the robustness, repeatability, and task specificity of these observations. Naturalistic Tasks Traditional task-based fMRI experiments use tightly controlled paradigms that often lack ecological validity. Resting-state scans, on the other hand, are unconstrained, making it difficult to separate signal from noise. Naturalistic tasks, in which subjects view a movie or listen to a story in the scanner, may provide a happy medium for studying both group-level functional brain organization and individual differences. By imposing a standardized, time-stamped, and engaging stimulus on all subjects, naturalistic tasks evoke rich patterns of brain activity. These patterns lend themselves to flexible, data-driven analyses such as inter-subject correlation (ISC) and inter-subject functional connectivity (ISFC), which are model-free ways to isolate stimulus-dependent brain activity from spontaneous activity and noise. These techniques have several advantages over traditional approaches: 1) they do not requirea priorimodeling of specific task events and/or assumptions about the functional specificity of individual brain regions; 2) there is no need to assume a fixed hemodynamic response function; and 3) they allow for the characterization of the full spatiotemporal richness of both evoked and intrinsic brain activity. In our work, we hypothesize that individual differences in psychological traits - namely suspicion and paranoia - are able to be differentiated by observation of brain activity elicited by a naturalistic task involving a narrative describing a complex social scenario that was deliberately ambiguous regarding characters trustworthiness and intentions. The intent was that some subjects would interpret the story as more suspicious, and others as less so. The narrative did evoke a range of interpretations. We collected data from 23 healthy subjects as they listened to the pre-recorded narrative during fMRI scanning, and characterized their feelings and beliefs about the narrative. We found that pairs of subjects with more similar activity fluctuations in primary visual and visual association cortices--suggesting that they were engaging in more similar mental imagery during listening--were more likely to speak about the story in similar ways afterward. One ultimate goal of this line of work is to develop a neuroimaging-based stress test for use in both clinical and subclinical populations. Such a test would draw out individual differences beyond what can be observed at rest or using more traditional tasks, potentially leading to earlier identification of subjects at risk for mental illness or helping to guide interventions. Continuation of mapping layer-specific brain activity at 7T In the last year, we continued to develop acquisition fMRI methods that can measure brain activity with ultra-high resolution, aiming to distinguish activity across cortical layers. The novel parameter space explored since October 2016 includes: a. The necessity of physiological noise correction with sub-millimeter voxels where thermal noise dominates. b. The capabilities of layer-fMRI at ultra-high field strengths of 9.4T compared to 7T. c. The layer-dependent signal features across different cortical columns in M1 in a participant-specific surface-based signal evaluation scheme. d. The capabilities to image whole slices of the brain beyond the sensory motor system e. The capabilities of alternative contrast mechanisms, including spin-echo BOLD compared to blood-volume sensitive contrast and gradient-echo BOLD fMRI. f. Resting state connectivity from layers to the rest of the brain, in an attempt to arrive at directional input and causality across cortical networks.

协议编号93-M-0170，NCT0000001360 功能成像方法（SFIM）部分通过开发处理和采集方法以及对fMRI信号背后的基本机制的研究具有高级功能MRI（fMRI）方法。过去一年中，我们的工作集中在提取fMRI时间序列中与任务，精神状态和个人特征有关的更多信息的方法上。在高分辨率下，我们具有更准确的映射皮层连接性和活性。由于空间有限，我们决定在这里强调一些代表我们正在进行的工作的项目。 多回波应用 我们的小组一直在开创多echo fMRI（ME fMRI）的开发和使用。由于血氧水平取决于（BOLD）和非折叠信号波动的行为与回声时间的函数不同，因此至少一个回声的唯一ME fMRI获取允许与时间序列相比有效且可靠地检测和去除非折叠波动。 我们的工作正在发展和利用我的fMRI继续。与Caballero-Gaudes博士合作，我们正在研究单个大胆事件的检测，而没有有关任务时间或位置的信息。初步测试表明，该算法可以以类似于传统的GLM方法的方式可靠地检测与每个单独试验相关的大胆事件，但没有任何有关范式时序的信息。这种新方法具有重要的应用，包括：揭示动态静止功能连接性的血液动力学事件，并检测癫痫患者中的互联网事件，而无需同时进行脑电图记录。 动态功能连接 近年来，动态功能连通性（FC）被理解为在几秒钟到几分钟的规模上变化的功能性大脑连接性模式，近年来引起了人们的关注。 FC配置与从整个时间序列中获得的配置可能有很大不同，最近的研究表明，这些动态与个体行为和行为特征之间存在联系。我们以前证明了全脑短期FC模式如何用于识别认知任务。我们目前正在研究这些模式如何提供有关以行为与特定特征的生物标志物相关的与行为相关的信息。我们还正在研究驱动这些动力学和动力学差异的元素，从唤醒和参与度变化到注意力变化。 最后，我们正在探索特定网络的动态可以预测行为的程度。 为了从FC网络优势中得出特定的个人特征，我们让受试者执行了2个背包的任务，在电影中寻找视觉目标并解决数学问题。每个任务都记录了性能。令人惊讶的是，持续的注意力网络（以前发现）比2-back特异性网络提供了更好的性能预测。 fMRI连通性与fMRI幅度变化 我们在基于任务的连接性变更评估上的工作为fMRI处理开辟了全新的远景。我们已经透露，对于认知任务，基于任务的连接性变化在空间上比幅度变化更广泛，并且对给定任务更具体或更敏感。该观察结果可能打开了一个新的大脑映射子字段，其中连通性变化的映射而不是大小变化。我们正在积极探索这些观察结果的鲁棒性，可重复性和任务特异性。 自然主义任务 传统的基于任务的FMRI实验使用经常缺乏生态有效性的严格控制范例。另一方面，静止状态扫描是不受限制的，因此很难将信号与噪声分开。自然主义的任务在扫描仪中观看电影或聆听故事的自然任务可能会为研究小组级功能性脑组织和个体差异提供快乐的媒介。通过对所有受试者施加标准化，时间戳记和引人入胜的刺激，自然主义任务引起了丰富的大脑活动模式。这些模式将自己用于柔性，数据驱动的分析，例如受试者间相关性（ISC）和受试者间功能连接性（ISFC），它们是分离刺激依赖性脑活动与自发活动和噪声的无模型方法。这些技术比传统方法具有多个优点：1）它们不需要对特定任务事件和/或关于单个大脑区域功能特异性的假设进行预先模拟； 2）无需假设固定的血液动力学反应函数； 3）它们允许表征诱发和内在脑活动的全时空丰富度。 在我们的工作中，我们假设心理特征的个体差异（即怀疑和偏执狂）能够通过观察到由自然主义任务引起的大脑活动来区分，涉及一个叙述叙事，该叙述描述了一个复杂的社会场景，这些叙述是故意对角色的信誉和意图有意模棱两可的。目的是，某些主题会将故事解释为更可疑，而其他主题则不太可疑。叙述确实唤起了一系列解释。我们从23个健康受试者那里收集了他们在fMRI扫描过程中听取预先录制的叙述的数据，并描述了他们对叙事的感受和信念。我们发现，在主要视觉和视觉关联性皮层中具有更相似活动波动的受试者对聆听过程中的精神意象更加相似，这是他们的探索者，之后更有可能以类似的方式谈论这个故事。这项工作的最终目标是开发基于神经成像的压力测试，以用于临床和亚临床人群中。这样的测试将带来个体差异，超出了在休息或使用更多传统任务时可以观察到的差异，这可能会导致早期鉴定出患有精神疾病风险或帮助指导干预措施的受试者。 在7T处的映射层特异性大脑活动的延续 在过去的一年中，我们继续开发获取fMRI方法，可以通过超高分辨率测量大脑活动，旨在区分皮质层的活动。自2016年10月以来探索的新型参数空间包括：使用热噪声主导的亚毫米体素校正生理噪声的必要性。 b。超高场强度为9.4t的Flay-FMRI的能力与7T相比。 c。在参与者特定表面的信号评估方案中，M1中不同皮层柱的层依赖性信号具有特征。 d。超出感觉运动系统以外的大脑整个切片的功能e。替代对比机制的功能，包括与血液量敏感的对比度和梯度回波fMRI相比，包括自旋回波大胆。 f。静止状态连接从层到大脑的其余部分，以试图在皮质网络跨性别的输入和因果关系。