NIMH MEG Core Facility

目前，我们有大约40个用户帐户，代表许多NIMH，NINDS和NIDCD协议。正在进行议定书和规划研究的其他团体不断表示兴趣。 MEG核心工作人员一直与这些用户在研究设计、任务编程开发、采集协议以及信号处理和数据分析方面进行互动。已建立数据安全、传输和存储程序。已经制定了一份实质性的政策和程序手册。我们还与科学和统计计算核心合作，将CTF MEG文件传输到AFNI，并开发了工具， 分组统计分析。 技术和科学成果仍然很好。信号分析的发展包括事件相关的SAM（合成孔径磁强计）和275通道伊卡（独立分量分析）。时频分析方法的发展包括Stockwell变换和小波变换以及多锥度技术。特别感兴趣的是虚拟通道的相干性分析作为一种方法来研究相互作用的大脑区域。 工作人员正在与其他MEG小组合作，整合几个信号处理软件包，包括FieldTrip，NUTMEG和BrainStorm。目标是为用户社区提供一个统一的工具包，并提供一个用户友好的界面。SAM软件已成功地在Biowulf集群上运行，从而大大提高了计算能力。受试者眼球运动系统已与任务演示软件集成，允许在视觉刺激期间交互式监测眼球位置。 科学结果是从杏仁核激活的定位与情绪面部任务的初步成功，以及视觉系统调制研究（Jeff Duyn报告说，MEG视觉激活信号的SNR是BOLD的10倍）。对于工作记忆任务，β带的MEG激活模式与同一受试者组的BOLD结果显示出异常一致。用户社区非常富有成效 Qian Lou和James Blair在一项研究中检查了面部威胁处理的神经动力学，他们能够利用MEG的精细时间分辨率来了解杏仁核中的大脑相关反应甚至比视觉皮层更早。这支持了大脑对恐惧表达的快速处理路线的建议。了解这些脑机制对于进一步研究心境和情感障碍具有重要意义。 Brian Cornwell、Christion Griffin及其同事研究了当环境变化导致焦虑时，个体是如何对新刺激敏感的。使用MEG，他们能够勾勒出与没有威胁相比，在受到威胁时大脑对声音的反应增强的途径。这些区域包括杏仁核和杏仁核。了解这些途径以及它们如何变得敏感，对于理解PTSD等疾病的致敏作用可能很重要。 Garolera、Goldberg及其同事也用MEG检查了杏仁核的活动;在这种情况下，在使用积极和消极单词的语言情感启动任务中。杏仁核活动的时间依赖性增加，被认为是对消极的话。他们将继续探索与情绪处理有关的机制。 研究大脑如何将自身组织成功能网络是理解正常人类认知以及精神疾病中认知障碍的关键。为此，Bassett，Meyer-Lindenberg和同事使用MEG的空间和时间能力来研究大脑在运动任务期间与休息时相比如何改变配置。他们发现，功能性网络的特征是小世界特性，表明局部连接和远程连接的混合。这些类型的调查可能有助于了解大脑网络在功能失调状态下如何变化。 正在进行的研究包括检查重度抑郁症患者的海马功能以及氯胺酮治疗后的其他大脑变化。这些研究对于可能阐明氯胺酮输注的抗惊厥作用机制特别有意义。Rich、Leibenluft和Pine正在使用MEG研究行为抑制的神经机制。这些只是MEG如何增强神经成像研究计划的几个例子。 .

At present we have about 40 user accounts representing numerous NIMH, NINDS and NIDCD protocols. There is continual interest from additional groups that are working on protocols and planning studies. The MEG Core staff has been working interactively with these users in terms of study design, task programming development, acquisition protocols, and signal processing and data analysis. Procedures have been setup for data security, transfer and storage. A substantial Policy and Procedures Manual has been established. We have also worked with the Scientific and Statistical Computing Core to enable transfer of CTF MEG files to AFNI and developed tools for group statistical analysis. Technical and scientific results continue to be excellent. Signal analysis development includes event-related SAM (synthetic aperture magnetometry) and 275 channel ICA (independent component analysis). Development of time-frequency analysis methods has included Stockwell and wavelet transforms as well as multi-taper techniques. Of particular interest is coherence analysis of virtual channels as a method to investigate interacting brain regions. Staff are working with other MEG groups to integrate several signal processing packages including FieldTrip, NUTMEG and BrainStorm. The goal is to have a unified tool package with a user-friendly interface available to the user community. The SAM software has been successfully run on the Biowulf Cluster allowing for tremendous increase in computing power. A subject eye movement system has been integrated with task presentation software allowing for interactive monitoring of eye position during visual stimulation. Scientific results follow up from initial successes of localization of amygdala activation with an emotional face task, and a visual system modulation study (Jeff Duyn reports that the MEG visually activated signal has 10 times the SNR compared to BOLD). For a working memory task MEG activation patterns for beta band have shown exceptional agreement with BOLD results in the same subject group. The user community has been very productive Qian Lou and James Blair in a study examining the neural dynamics of facial threat processing have been able to utilize the fine temporal resolution of MEG to learn that there are brian related responses in the amygdale even earlier than in the visual cortex. This supports the suggestion of quick processing route in the brain specific to fear expressions. Understanding these brain mechanisms will be important to further study in mood and affective disorders. Brian Cornwell, Christion Grillion and colleagues have examined how individuals because sensitized to novel stimuli when there are environmental changes that cause anxiety. Using MEG they were able to outline the pathways where brain responses were enhanced to sounds when under threat compared to no threat. These areas included amygdale and insula. Knowledge of these pathways and how they become sensitized may be important for understanding sensitization in disorders such as PTSD. Garolera, Goldberg and colleagues have also examined amygdale activity with MEG; in this case, during a linguistic affective priming task using positive and negative words. A time dependant increase in amygdale activity was seen in response to negative words. They will follow up to explore mechanisms implicated in emotional processing. Studying how the brain organizes itself into functional networks is key to understanding normal human cognition as well as when it becomes disordered in mental illness. To this end Bassett, Meyer-Lindenberg and co-workers used the spatial and temporal ability of MEG to study how the brain changes configuration during a motor task compared to when at rest. They found that functional networks were characterized by small-world properties indicating a mix or both local connections and long range connections. These type of investigations may aid in understanding how brain networks change in dysfunctional states. On going studies include examining hippocampal function in pateients with major depression as well as other brain changes when treated with ketamine. These studies are of particular interest to possibly elucidate the mechanism of the anti-depressant action of ketamine infusion. Rich, Leibenluft and Pine are using MEG to study the neural mechanisms of behavioral inhibition. These are just a few examples of how MEG is augmenting the neuroimaging research program. .