NIMH MEG Core Facility

目前，我们拥有约40个用户帐户，分别代表多种NIMH、NINDS和NIDCD协议。致力于方案和规划研究的更多小组一直对此感兴趣。 MEG核心工作人员一直在研究设计、任务编程开发、采集协议以及信号处理和数据分析方面与这些用户进行互动。已经为数据安全、传输和存储建立了程序。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，使CTF MEG文件能够转移到非洲非政府组织，并开发了用于群体统计分析的工具。 科技成果继续保持优异。信号分析的发展包括与事件相关的SAM(合成孔径磁学)和275通道ICA(独立分量分析)。时频分析方法的发展包括斯托克韦尔变换和小波变换以及多锥度技术。尤其令人感兴趣的是对虚拟通道的一致性分析，作为研究相互作用的大脑区域的一种方法。工作人员正在与其他MEG小组合作，整合包括FieldTrip、Nutmeg和BrainStorm在内的几个信号处理包。目标是为用户社区提供一个具有用户友好界面的统一工具包。SAM软件已经在Biowulf集群上成功运行，从而极大地提高了计算能力。受试者眼球运动系统已经与任务演示软件集成在一起，允许在视觉刺激期间对眼睛位置进行交互式监控。 科学结果是通过情绪面孔任务对杏仁核激活进行定位的初步成功，以及视觉系统调节研究(Jeff Duyn报告，脑磁图视觉激活信号的信噪比是BOLD的10倍)。对于工作记忆任务，β波段的脑磁图激活模式已经显示出与同一受试者组中大胆结果的异常一致。用户社区一直非常高效 Qian Lou和James Blair在一项研究面部威胁处理的神经动力学的研究中，已经能够利用脑磁图的精细时间分辨率来了解到，杏仁核甚至比视觉皮质更早有与大脑相关的反应。这支持了大脑对恐惧表情进行快速处理的建议。了解这些大脑机制将对进一步研究情绪和情感障碍非常重要。 Brian Cornwell、Christion Grillion及其同事研究了当环境变化导致焦虑时，个体是如何对新的刺激敏感的。使用脑磁图，他们能够勾勒出大脑在受到威胁时与没有受到威胁时相比，对声音的反应增强的途径。这些区域包括杏仁核和脑岛。了解这些通路以及它们是如何致敏的，对于理解创伤后应激障碍等疾病的致敏作用可能很重要。 Garolera、Goldberg和他的同事还研究了MEG的杏仁核活动；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。对负面词汇的反应显示杏仁核活动呈时间依赖性增加。他们将跟进探索与情绪处理有关的机制。 研究大脑如何将自己组织成功能网络，是理解正常人类认知以及精神疾病中大脑何时变得混乱的关键。为此，巴西特、迈耶-林登伯格和他的同事利用脑磁图的空间和时间能力，研究了与休息时相比，运动任务期间大脑的形态是如何变化的。他们发现，功能性网络的特征是小世界属性，表明本地连接和远程连接混合或两者兼而有之。这些类型的研究可能有助于理解大脑网络如何在功能失调的状态下发生变化。 正在进行的研究包括检查患有严重抑郁症的患者的海马体功能，以及使用氯胺酮治疗时的其他大脑变化。这些研究对可能阐明氯胺酮输注的抗抑郁作用的机制特别有意义。Rich、Leibenluft和Pine正在使用脑磁图研究行为抑制的神经机制。这些只是MEG如何加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. .