This work was supported by the European Union FP 7 project DECODER and the European Union ODI Project COMAWARE.

本议定书内的所有步骤均符合赫尔辛基宣言的原则。 系统设置<ol><li>使用USB电缆，将放大器连接到运行软件的计算机，然后打开放大器。 </li><li>将硬件加密狗连接到计算机中的空闲USB插槽。 注意:这是运行软件所必需的。 </li><li>将防静电腕带放在被摄体的手腕上，并将其连接到免费的电源插头上。 注意:该乐队的设计旨在帮助地面对准地面，以减少可能影响脑电图质量的噪音。 </li><li>将驱动器盒与USB电缆连接到计算机的空闲插槽。 </li><li>将触发电缆连接到驱动器盒，如下所示: <ol><li>将"g.STIMbox OUT 5"标记的连接器连接到驱动程序框的"OUT 5"。 </li><li>将"g.STIMbox OUT 6"标记的连接器连接到驱动程序b的"OUT 6"牛。 </li><li>将"g.STIMbox OUT 7"标记的连接器连接到驱动程序框的"OUT 7"。 </li><li>将"g.USBamp DIO 1"标记的连接器连接到g.USBamp的"DIG I / O 1"插座。 </li><li>将三个触发器连接到驱动程序框的OUT 1，OUT 2和OUT 3。 </li><li>将"TRIG OUT"标记的连接器连接到音频触发器适配器盒的"TRIG OUT"插口。 </li></ol></li><li>用胶带固定左手腕上的一个反应器，另一个在右手腕上，另一个在右踝上。 </li><li>将公/母音频连接器电缆连接到计算机的音频输出和标有"AUDIO IN"的音频触发器适配器盒的插座。打开音频触发适配器盒，检查电池状态指示灯是否为绿色。 </li><li>启动软件，观察一个名为"添加医师"的窗口。在空白字段中键入标题，名称，机构和部门。社区法网k在"添加"上打开另一个窗口。 </li><li>在窗口中输入病人的姓名，城市，国家，出生日期和入住日期。 </li><li>点击程序右下角的蓝色箭头下面的绿色"+"按钮。在"名称"字段和"熟悉软件"中输入文本"第一个测试"到空的"详细信息"字段。 注意:为了继续进行程序，有必要将信息输入到所有空字段中。 </li><li>最后点击"选择这个病人"按钮。 </li><li>使用电极盖将16个EEG通道连接到被检者的头部。根据扩展的国际10-20系统14 ，使用位置:FC3，FCz，FC4，C5，C3，C1，Cz，C2，C4，C6，CP3，CP1，CPz，CP2，CP4和Pz。将参考电极放在右耳垂和前额上的接地电极上。 </li><li>为了正确地将帽子放置在被摄体的头部上，使用卷尺来衡量入侵和入侵之间的距离，以及左右耳前点之间的距离。确保顶点位置Cz处的电极处于这两个距离的中点。将电极盖放在电极帽上并将其测量位置与电极盖的Cz位置对齐。电极盖现在处于正确的位置。 </li><li>按照步骤1.12中的设置，将电极连接到电极接线盒。将电极接线盒连接到生物信号放大器，并确保放大器和接线盒已打开。 </li><li>将足够的电极凝胶注入电极以在皮肤和电极之间形成连接。 </li></ol>听觉P300评估<ol><li>输入患者信息后，点击屏幕左侧的"听觉P300"按钮。点击底部的"评估"按钮ght开始评估运行。 </li><li>检查脑电图的信号质量。屏幕右侧的大脑的图像为每个电极的信号质量提供了颜色编码指南，红色表示信号质量差，黄色表示可接受的信号质量，绿色表示良好的信号质量。 </li><li>通过设置按钮打开设置菜单，确认听到哔声。将两个不同频率的嘟嘟声呈现给对象，并解释任务，这是对每个高频哔声进行计数。 </li><li>将耳机放入用户的耳朵，然后点击开始按钮。 </li><li>评估运行结束后，检查结果页面和精度图（ 图1和图 2 ）。如果精度水平低于40％，重复运行。 注意:如果受试者的准确度低于40％，那么可靠的通信是不可能的，至少在该范例和记录会话中。然而，与其他的评估方法和/或在不同的时间可能产生不同的结果。 </li></ol> 3.振动触觉P300评估与2个刺激者<ol><li>点击屏幕左侧的"Vibrotactact 2 Tactor "按钮;然后点击右下角的"评估"按钮开始评估运行。重复步骤2.2。 </li><li>通过设置按钮打开设置菜单，确认可以感觉到触觉的振动。指导他/她将在左右手腕上感觉到振动。任务是计算左手腕上的振动刺激次数。在说明之后，点击开始按钮。 </li><li>评估运行结束后，检查结果页面和精度图。如果精度水平低于40％，重复运行。 注意:如果受试者的准确度低于40％，那么可靠的通信是不可能的，至少在该范例和记录会话中。不过，屁股与其他方法和/或在不同的时间可能产生不同的结果。 </li></ol> 4.振动触觉P300评估与3个刺激者<ol><li>单击屏幕左侧的"Vibrotactact 3 Tactor"按钮，然后单击右下角的"评估"按钮开始评估运行。 </li><li>重复步骤2.2。通过设置按钮打开设置菜单，确认可以感觉到触觉的振动。 </li><li>指导他/她将在左右手腕和右脚踝上感觉到振动，并通过耳机听到"左"或"右"的命令。要求受试者对所选手的刺激进行计数，直到出现下一个命令或运行结束。 注意:"左"表示受试者应计算左侧的振动刺激，而"右"则指示受试者计数右手腕上的刺激。 </l我&gt; <li>将耳机插入主体的耳朵，然后单击开始按钮。 </li><li>完成评估运行后，检查结果页面和精度图。如果精度水平低于40％，重复运行。 注意:如果受试者的准确度低于40％，那么可靠的通信是不可能的，至少在该范例和记录会话中。然而，使用其他方法和/或在不同时间的评估可能产生不同的结果。 </li></ol>振动触觉P300与3个刺激器通讯<ol><li>点击屏幕左侧的"Vibrotactact 3 Tactor"按钮。点击底部的"通讯"按钮开始通讯运行。 </li><li>重复步骤2.2。通过设置按钮打开设置菜单，确认可以感觉到触觉的振动。在设置菜单中，选择具有最高精度级别的分类器。这通常是分类器系统确定的最高精度水平。 </li><li>指导他/她将在左右手腕和右脚踝上感觉到振动。指导他/她会听到一个问题，应该回答"是"或"否"。要回答"是"，要求受试者计算左手的刺激;回答"不，"要求受试者对右侧的刺激进行计数。 </li><li>向患者询问可以用"是"或"否"回答的问题。之后，点击"开始新问题"按钮。 注意:序列完成后，软件将显示答案。它可能是"是"，"否"或没有答案（如果软件无法准确检测大脑模式）。 </li></ol> MI评估<ol><li>点击屏幕左侧的"电机图像"按钮。点击"评估"按钮右下角开始评估运行。 </li><li>重复步骤2.2。通过设置按钮打开设置菜单，并确认可以通过耳机听到音频命令。 </li><li>指示他/她将听到哔哔声，然后指示说"左"或"右"。在命令"左"后，用左手挤压一个球，用右手按"右"命令，用右手挤压一个球。一旦主体听到命令"放松"，问题就停止想象挤压。 注意:总共将播放60个随机排列的命令。 </li><li>跑步最后8分钟。约4分钟后点击暂停按钮，等待约1分钟，然后继续运行。 注意:暂停旨在帮助受试者在整个运行中保持集中。 </li><li>评估结束后，检查结果页和精度图（图3和图4）。 不E:如果精度水平低于显着性水平，重复运行。如果精度保持在该显着性水平之下，则至少在该范例和记录会话中，可靠的通信是不可能的。然而，使用其他方法和/或在不同时间的评估可能产生不同的结果。 </li></ol> 7. MI沟通<ol><li>点击屏幕左侧的"电机图像"按钮。点击左下方的"通讯"按钮开始通讯运行。重复步骤2.2。 </li><li>使用设置按钮打开设置菜单，并选择分类精度最高的分类器。 </li><li>指出我的说法，哔哔声后，他/她可以提供以前提出的问题的答案。说"是"，请病人想象用左手挤压一个球。说"不"，病人应该想象用正确的h挤压一个球和。 </li><li>向患者询问可以用"是"或"否"回答的问题。之后，点击"开始新问题"按钮。 注意:当序列完成后，软件将显示答案（ 图5 ）。它可以是"是"或"否"。 </li></ol>

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The author Christoph Guger is CEO of g.tec medical engineering GmbH, which produces the instruments used in this article. The co-author Alexander Heilinger is an employee of g.tec medical engineering GmbH.

许多组的先前研究表明，一些DOC患者可能通过基于功能磁共振成像或基于脑电图的评估来表现出意识的意识，尽管基于行为的评估表明其他方式。因此，显然需要新的系统和范例，可以更准确地评估意识的意识，甚至提供沟通。理想情况下，这些系统应该是廉价的，便携式的，在现实环境中对噪声的鲁棒性，并且易于使用（对于患者和系统操作者）。 这里提出的协议和系统有两个目的:帮助评估DOC的意识水平，并为通过语音，眼睛活动或需要肌肉控制的其他任务来沟通的人建立新的沟通渠道。协议中的范例旨在测试第一步中的基本响应。如果检测到预期的基本大脑反应，则可以进一步进行更复杂的范例，即具有三个触觉和MI的振动触觉P300。这两种模式也可用于建立通信渠道。 EEG信号质量在所有这些协议中至关重要。有时EEG数据不能与噪声区分开来;需要一些EEG分析方面的经验来识别和管理噪声数据。 目前的标准评估方法除了不可靠外，也是耗时的，需要一个专家小组。因此，患者常常只评估一次，即使患者的意识知觉可能在不同时间剧烈波动。这里介绍的协议可以轻松重复几次。不具有意识意识的患者在另一时间可能产生不同的结果。此外，在进行每次通信尝试以确认受试者目前处于有意识状态之前，可以进行单次评估。 Anoth在协议中实施不同范式的原因是因为有些人可能会用一种模式表现不佳，但与另一种模式表现相当。同样，人们可能更喜欢一种范式，因为它们似乎更容易。在用不同的范例探索不同的选择后，患者可以选择他们喜欢的方法。这与"混合"BCI方法一致，它支持提供多种通信选项，以提高通信效率和用户满意度。 精确度图与正确分类的百分比水平相结合，产生了反映模式识别算法在任务期间能够区分不同大脑状态的客观结果。因此，不需要对脑模式或平均反应的主观解释。 与六名慢性锁定器官组进行了三个触觉的振动触觉交流ts 15 。他们在沟通中的平均准确率达到了55.3％，均高于12.5％的机率。 MI通信任务在一组二十个健康用户13中进行了测试，平均精度约为80％。二十人中只有一人的控制精度低于机会级别。 重要的是要提到精确度不佳的跑步或甚至完整的课程并不能完全证明在该主题内没有大脑反应或没有意识。这意味着该系统无法检测到自愿的大脑反应。这可能是由于信号质量差，听力困难或了解任务说明，或仅仅因为尽管执行任务，少数科目不能产生所需的脑电活动。 根据我们集团和其他人的以前的工作，提出的工作表明，建议进行评估用脑成像技术患有DOC的患者的意识水平。 fMRI也是跟踪患者目前大脑活动的有用技术。结果表明，古怪的范式是引起诱发电位，以及运动想象等任务，能产生可以通过功能磁共振成像17,18被跟踪的血流动力学反应。与fMRI相比，EEG具有显着的优势:EEG型工具可以在床边使用，无需昂贵且不可携带的设备，需要相当的专业知识。将患者运送到扫描仪并且来自扫描仪的声音噪声对于患者来说都是紧张的。近红外光谱（NIRS）是便携式的，并且可以具有比EEG略好的空间分辨率，但是它具有较差的时间分辨率19 。 NIRS适合监控MI 20，21，而不是诱发POTEntials。例如，Naseer和Hong 22显示了使用fNIRS的MI-BCI的高分类精度。经过50年的试验，左心梗患者达到77.35％，右心肌梗死达到83％。使用基于EEG的BCI，Guger 等 23次发现，99次会议中约20％达到了80％以上的准确度，99次会议中的70％达到60％以上的准确度。 Ortner 等人使用CSP方法显示出约80％的平均峰值精度。该方法需要比Guger及其同事使用更多的EEG电极，但是它导致更高的精度。使用CSP方法，Ramoser 等 23表明，电极从18 - 56增加并没有显着提高性能;因此，我们得出结论，我们的方法中所选择的16个电极数量是足够的。最近，Coyle 等使用CSP对DOC patie进行MI分类和训练nts 16 。在评估过程中，所有四个受试者都表现出显着和适当的脑激活通过混合NIRS-EEG BCI评估MI可导致高分类准确性，如Khan 等 20显示。这可能是一个有希望的未来发展方向，尽管额外的神经成像工具增加了设备的复杂性和成本。 这里提出的方案提供了一个比较容易的工具，用于评估DOC患者脑电图信号中的脑反应。解释这些分类结果和对药物，治疗或其他医疗方面的任何改变仍然需要医学专家。这种方法的未来方向可能是使用更高数量的自由度的更先进的刺激技术。例如，不是提供只能说"是"或"否"的工具，而是将来的设备可能允许更多的可能的answe一个问题。在另一个步骤中，还可以使用基于上下文的答案。例如，如果患者具有运行的音乐播放器，则可以提供控制声音级别或切换到下一首歌曲的可能性。此外，MI范式需要在DOC患者中进行测试。

营养状态（VS）或最小意识状态（MCS）患者的诊断困难，常常发生错误分类。 2009年的一项研究比较了临床共识与神经行为评估之间的诊断准确性1 。根据医疗团队的临床共识，44例诊断为VS的患者中，18例（41％）被发现在采用Coma恢复量表（CRS-R）进行标准化评估后的MCS中。这一结果与以往的研究，这表明37一致-诊断为VS 43％患者表现出的意识2,3迹象。分类量表基于行为观察或对听觉，视觉，口头和运动功能以及沟通和觉醒水平的评估。可以添加大脑活动数据的新技术是克服beha强加的限制的完美工具vioral评级量表。尽管无法产生评分量表所需的行为变化，患者也许能够调整脑部反应。 Monti 等人 4表明，功能性磁共振成像（fMRI）可以检测5/54名诊断为意识障碍（DOC）的患者的血氧水平依赖性反应的自愿变化，这些变化与想象的运动运动或空间成像任务相关。其中四人以前已被分类为MCS。因此，在少数情况下，满足植物人状态行为标准的患者具有残留认知功能，甚至有意识的意识。 脑电图（EEG）的BCIs还可以检测由想象力或运动运动的尝试引起的大脑活动。还有其他BCI范例可以通过自愿遵循预定义的tas来确定一个人是否能够提供意识ķ。基于脑电图的BCI相对于基于fMRI的评估具有其他优势。例如，EEG系统更具成本效益和便携性，并且可以方便地在患者的床边使用。主要的无创BCI方法包括慢性皮质电位（SCPs），P300s，稳态视觉电位（SSVEP）和电机影像（MI）。 SCPs提供的信息传递率很低，需要大量培训（参见Wolpaw 等人 ） 5 ，而SSVEP需要视觉注意。因此，这两种方法在本协议中不被使用。使用P300拼写器，Ortner 等人 5残疾人的准确率达到70％。这个数字最终可能会增加。例如Turnip et al。 7通过使用自适应神经网络分类器来提高其P300分类精度。对于这个协议，我们选择触觉和听觉P300方法除了MI，因为o它们可以无视觉地使用，每个都有独特的优势。 MI可以提供比非视觉P300 BCI更快的通信，而P300 BCI需要很少的培训。因此，这种混合BCI协议可以为DOC患者实施一整套基于EEG的BCI方法。此外，由于任务相对快速且容易重复，可以与每个患者重复探索不同的方法来减少DOC患者的不正确分类数量。 探讨了四种不同的BCI方法:（i）听觉P300，（ii）具有两个刺激器的振动触觉P300，（iii）具有三个刺激器的振动触觉P300和（iv）MI。 听觉P300方法使用听觉奇怪球模式，其中偏差刺激（1,000Hz哔声）随机分布在更可能的标准刺激（500Hz哔声）的列车内。在范式二中，刺激通过振动触觉刺激器传递放在左右手腕上。左腕上的反应器提供标准刺激，右腕上的反应器传递偏差（目标）刺激。对于范例iii，将额外的刺激器放置在受试者的右踝上，或在另一位置，例如背部的中间。这种刺激器提供了一系列标准刺激，而左右两只刺激器则会产生异常的刺激。为了评估两种振动脉络模型的意识，通过耳机告知受试者，将每个刺激物静音地计数到一只手腕，同时忽略其他刺激。一个随机机制决定是选择左手还是右手，每次跑步都有四组，每组30次，每次试验有一个新的目标手。 对范例i，ii和iii进行以下信号处理:使用256Hz的采样频率获取八个EEG通道。偏差刺激的概率为1/8; HENCe，每个偏差刺激将有七个标准刺激。每次跑步总共有480次刺激。一个范例我需要7分20秒，而每次运行的范例ii和iii需要2分30秒。如果患者默默地计算每个偏差刺激，这些刺激将引发几个事件相关电位（ERP），包括P300，刺激发作后大约300ms的正峰值。每次哔声持续100 ms。对于每个刺激试验，存储100ms之前的窗口和在哔音之后600ms的窗口用于信号处理。然后将数据下采样12倍，导致刺激间期后60 ms的12个采样。最后，将所有采样时间通道特征输入到线性判别分析8中 ，得到12×8 = 96的特征。为了计算精度图（ 图1和图 2 ），重复以下步骤十次，将结果平均为一个图。偏差和标准试验被随机分配到两个相等大小的池中。一个池用于训练分类器，另一个池用于测试分类器。分类器在测试池中越来越多的平均刺激进行测试。起初，它只测试一个偏差和七个标准刺激。如果分类器正确检测到偏差刺激，则得到的精度为100％，否则为0％。对于2个平均偏差刺激和14个平均标准刺激，对于3个偏差刺激和21个标准刺激，同样如此，直到使用完整的测试池。这产生了30个单值（对于测试池中的30个偏差刺激）的图，每个值为100％或0％。平均值为10个单个图形的值在0％到100％之间。如果受试者可以跟随任务，增加平均刺激的数量会增加精度，因为刺激的平均值会降低数据中的随机噪声。准确度超出机会级别（12.5％）显示P300的反应可以在受试者中引发，并且受试者脑部的反应出现.Paradigms i和ii只能用于评估意识。如果在评估过程中达到的准确度高于40％，则可以进一步利用iii或iv模式的沟通。 在范式iii的交流任务中，如果他/她想要回答"是"或右侧回答"否"，则主体选择集中在左侧的刺激。分类器检测用户正在集中的手，并提出答案。 范式iv记录120次试验，每次试验持续8秒，分隔1秒。这导致10秒120分=总时间18分钟。范例iv使用分布在感觉运动皮层上的16个EEG通道。采样频率为256 Hz。每个试验都以提示，通过耳机提示，指示该主题想象一下移动左手或右手。左手和右手指令的顺序是随机的。对于信号预处理中，使用普通的空间格局（CSP）10，12，13中的方法。该方法产生一组空间滤波器，用于最小化一个类的方差，同时最大化另一个类的方差。这导致了四个特征，它们通过线性判别分析8进行分类。整个分类过程被详细描述在最近的出版物中描述，示出了健康的用户13仅60分钟的训练后的80.7％隆重平均分类精度。准确度的计算是通过交叉验证来完成的。这是指将数据样本分解为互补子集，对一个子集进行分析（培训池），并验证其他子集（tes）的分析ing池）。在将数据分离到池之前，包含工件的试验被拒绝。在试验期间的任何时间，如果振幅的绝对值超过100μV，则试验被认为包含人造物。对于测试池中的所有运动的准确性，在1.5秒钟后，在注意哔声至试验结束后，以0.5秒为单位计算。对于每个步骤和每个试验，分类结果为100或0％。然后对每个单一步骤对所有试验池试验的准确性进行平均，从而导致0％至100％之间的准确度水平。最后，十次重复的交叉验证结果的平均值显示在精度图中。实施例可以在图3和图 4中看出。图中分离左手（黄色），右手（蓝色）和所有运动（绿色）中的成像运动。洋红色的水平线代表置信限，取决于它关于用于分析的试验数量。这是总试验的数量减去拒绝试验的次数。它使用Clopper Pearson方法显示95％置信区间9 。精度水平高于该线意味着结果具有统计学意义（α&lt;0.05）。

<table border="0" cellpadding="0" cellspacing="0" width="673">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">g.USBamp</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">Biosignal amplifier</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">Power supply</td>
			<td style="width:133px;">GlobTek Inc.</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">Medical mains power supply for the g.USBamp</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">USB cable</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">Connects the g.USBamp to the computer</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">EEG electrodes gSCARABEO</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">16</td>
			<td style="width:265px;">Active EEG electrodes</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">EEG electrode gSCARABEOgnd</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">passive ground electrode</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">EEG electrode g.GAMMAearclip</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">active reference electrode</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">g.GAMMAbox</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">Connects the amplifier to the EEG electrodes</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">g.USBampGAMMAconnector</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">Connects the g.GAMMAbox to the g.USBamp</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">EEG cap</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">To position electrodes</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:169px;">Computer</td>
			<td style="width:133px;">Hewlett-Packard</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">To run the software. Alternatively computers from other manufacturers could be used.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">g.VIBROstim</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">3</td>
			<td style="width:265px;">Tactors for sensory stimulation</td>
		</tr>
		<tr height="90">
			<td height="90" style="height:90px;width:169px;">Audio trigger adapter box</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">To split up the audio signal into audio commands for the headphones and trigger signals. This box connects to the amplifier.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">Anti static wrist band</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">To suppress noise in the EEG</td>
		</tr>
		<tr height="65">
			<td height="65" style="height:65px;width:169px;">Trigger cable</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">To connect the audio trigger adapter box and the g.STIMbox to the g.USBamp</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">Audio connector cable</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">Audio cable to connect the audio trigger adapter box to the computer</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">Hardlock</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">To run the software</td>
		</tr>
		<tr height="65">
			<td height="65" style="height:65px;width:169px;">SE215-K</td>
			<td style="width:133px;">Shure Europe GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">Noise suppressing earphones. Alternatively other earphones could be used.</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">g.STIMbox</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">Driver box for tactile stimulators</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">mindBEAGLE software</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">software package</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:169px;">g.GAMMAgel</td>
			<td style="width:133px;">g.tec medical engineering GmbH</td>
			<td style="width:107px;">1</td>
			<td style="width:265px;">conductive electrode gel</td>
		</tr>
	</tbody>
</table>

assessment and communication for people with disorders of consciousness

在本实验中，我们演示了一套基于混合脑电脑接口（BCI）的范例，其设计用于两个应用:评估不能提供运动反应的人的意识水平，并在第二阶段建立通信频道对于这些人来说，他们可以用"是"或"否"来回答问题。范例套件旨在测试第一步中的基本响应，并在第一次测试成功时继续进行更全面的任务。后者的任务需要更多的认知功能，但它们可以提供通信，这在基本测试中是不可能的。所有评估测试都会产生精确的图，显示算法是否能够检测患者的大脑对给定任务的响应。如果准确度水平超出了显着水平，我们假设主体了解任务，并能够遵循命令序列p通过耳机向主题反感。这些任务需要用户专注于某些刺激或想象移动左手或右手。所有任务都是围绕着用户不能使用视觉模态的设计而设计的，因此呈现给用户的所有刺激（包括指令，提示和反馈）都是听觉或触觉的。

图1和图 2显示了两个P300评估运行的结果（范例i，ii和iii）。在图1中，精度达到100％;因此，受试者的大脑清楚地表明成功完成任务。在图2中，精度在12.5％的机率水平附近波动。不能检测到任务可靠的大脑反应。当精度差时，我们建议在所有电极和连接器上仔细检查EEG信号质量。如果没有获得脑电，但只是白噪声，则精度水平为12.5％的结果也将被看到。如果准确度水平随着试验次数的增加而增加，但不高于40％，则仅发现脑部反应较弱。在这种情况下，我们建议使用原始数据范围来调查信号中的工件。我们还建议在另一天再次重复这个程序。病人可以在另一时间更灵敏，并产生更好的效果。 图3和图 4显示了范例iv的代表性结果。显着性水平用品红色线标出。红色垂直线标志着命令开始的时间。在命令出现之前（红色垂直线），两个地块的精度约为50％。此时，病人不知道命令是"左"还是"右"，因此不能执行正确的运动想像。在图3中 ，命令呈现后的精度提高到90％以上。这意味着该人自觉意识到，因为他能够遵循随机指令。在图4中，分类精度波动约50％。这意味着系统无法按照提出的命令检测MI。在BCI r中，MI范式可能具有挑战性因为不是所有的用户都能够在没有训练的情况下控制MI BCI，而且少数人也不能通过培训获得控制11 。因此，在这种情况下，错误的准确性可能只是意味着病人无法通过MI控制BCI，至少没有训练。此外，如上所述，我们建议在检查结果不良后检查信号质量。 图5显示了可以用范例iii和iv完成的通信运行的结果。该镜头标记检测到的答案，在该示例中为"是"。如果答案是否定的话，镜头会移动到"NO"。如果系统无法检测到答案，镜头将停留在两个可能的答案的中间。如果镜头停留在答案的中间，可能会选择不好的分类器。我们建议在设置窗口中尝试另一个分类器。 <img alt="图1" src="/files/ftp_upload/53639/53639fig1.jpg" /> 图1.范式的准确度图i，ii，＆iii。 性能良好，精度达到100％。 <a href="http://ecsource.jove.com/files/ftp_upload/53639/53639fig1large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图2" src="/files/ftp_upload/53639/53639fig2.jpg" /> 图2.范例的另一准确性图i，ii，＆iii。 这一次，没有胸罩<html>可以由系统检测到。因此，精度在12.5％的机会水平附近波动。 <a href="http://ecsource.jove.com/files/ftp_upload/53639/53639fig2large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图3" src="/files/ftp_upload/53639/53639fig3.jpg" /> 图3.范式iv（MI）的准确度图。 在这个例子中，精度达到90％以上。 <a href="http://ecsource.jove.com/files/ftp_upload/53639/53639fig3large.jpg" target="_blank">请点击此处查看此图的较大版本。</a> <img alt="图4" src="/files/ftp_upload/53639/53639fig4.jpg" /> 图4.范式iv（MI）的准确度图。 系统无法检测出脑部反应。因此，精度在50％的机会水平附近波动。ttp://ecsource.jove.com/files/ftp_upload/53639/53639fig4large.jpg"target ="_ blank"&gt;请点击此处查看此图的较大版本。 <img alt="图5" src="/files/ftp_upload/53639/53639fig5.jpg" /> 图5.通信任务的结果。 镜头标记检测到的答案，"是"。 <a href="http://ecsource.jove.com/files/ftp_upload/53639/53639fig5large.jpg" target="_blank">请点击此处查看此图的较大版本。</a>

Watch this Scientific Journal Video about Assessment and Communication for People with Disorders of Consciousness at JoVE.com

Assessment and Communication for People with Disorders of Consciousness

With this experiment, one might be able to detect consciousness in people with disorders of consciousness. Furthermore, the approach can create a simple communication channel that enables people to give simple YES/NO answers to questions.

有意识障碍者的评估与沟通

In this experiment, we demonstrate a suite of hybrid Brain-Computer Interface (BCI)-based paradigms that are designed for two applications: assessing the ...

assessment-communication-for-people-with-disorders

Research

JoVE Journal

Neuroscience

8.9K 次观看.  Guger Technologies OG. With this experiment, one might be able to detect consciousness in people with disorders of consciousness. Furthermore, the approach can create a simple communication channel that enables people to give simple YES/NO answers to questions.

视频: Assessment and Communication for People with Disorders of Consciousness

Fluorescence Recovery After Photobleaching (FRAP) of Fluorescence Tagged Proteins in Dendritic Spines of Cultured Hippocampal Neurons

FRAP has been used to quantify the mobility of GFP-tagged proteins. Using a strong excitation laser, the fluorescence of a GFP-tagged protein is bleached in the region of interest. The fluorescence of the region recovers when the unbleached GFP-tagged protein from outside of the region diffuses into the region of interest. The mobility of the protein is then analyzed by measuring the fluorescence recovery rate. This technique could be used to characterize protein mobility and turnover rate.
In this study, we express the (enhanced green fluorescent protein) EGFP vector in cultured hippocampal neurons. Using the Zeiss 710 confocal microscope, we photobleach the fluorescence signal of the GFP protein in a single spine, and then take time lapse images to record the fluorescence recovery after photobleaching. Finally, we estimate the percentage of mobile and immobile fractions of the GFP in spines, by analyzing the imaging data using ImageJ and Graphpad softwares.
This FRAP protocol shows how to perform a basic FRAP experiment as well as how to analyze the data.

Fluorescence Recovery After Photobleaching FRAP of Fluorescence Tagged Proteins in Dendritic Spines of Cultured Hippocampal Neurons

FRAP has been used to quantify the mobility of Green Fluorescence Protein (GFP)-tagged proteins in cultured cells. We examined the mobile/immobile fractions of the GFP by analyzing the fluorescence recovery percentage after photobleaching. In this study, FRAP was performed at spines of hippocampal neurons.

漂白后荧光标记蛋白的荧光恢复（FRAP）在培养海马神经元的树突棘

FRAP has been used to quantify the mobility of GFP-tagged proteins. Using a strong excitation laser, the fluorescence of a GFP-tagged protein is bleached ...

科研

神经科学

Dissection of Adult Mouse Utricle and Adenovirus-mediated Supporting-cell Infection

Hearing loss and balance disturbances are often caused by death of mechanosensory hair cells, which are the receptor cells of the inner ear. Since there is no cell line that satisfactorily represents mammalian hair cells, research on hair cells relies on primary organ cultures. The best-characterized in vitro model system of mature mammalian hair cells utilizes organ cultures of utricles from adult mice (Figure 1) 1-6. The utricle is a vestibular organ, and the hair cells of the utricle are similar in both structure and function to the hair cells in the auditory organ, the organ of Corti. The adult mouse utricle preparation represents a mature sensory epithelium for studies of the molecular signals that regulate the survival, homeostasis, and death of these cells.
Mammalian cochlear hair cells are terminally differentiated and are not regenerated when they are lost. In non-mammalian vertebrates, auditory or vestibular hair cell death is followed by robust regeneration which restores hearing and balance functions 7, 8. Hair cell regeneration is mediated by glia-like supporting cells, which contact the basolateral surfaces of hair cells in the sensory epithelium 9, 10. Supporting cells are also important mediators of hair cell survival and death 11. We have recently developed a technique for infection of supporting cells in cultured utricles using adenovirus. Using adenovirus type 5 (dE1/E3) to deliver a transgene containing GFP under the control of the CMV promoter, we find that adenovirus specifically and efficiently infects supporting cells. Supporting cell infection efficiency is approximately 25-50%, and hair cells are not infected (Figure 2). Importantly, we find that adenoviral infection of supporting cells does not result in toxicity to hair cells or supporting cells, as cell counts in Ad-GFP infected utricles are equivalent to those in non-infected utricles (Figure 3). Thus adenovirus-mediated gene expression in supporting cells of cultured utricles provides a powerful tool to study the roles of supporting cells as mediators of hair cell survival, death, and regeneration.

Mechanosensory hair cells are the receptor cells of the inner ear. The best-characterized in vitro model system of mature mammalian hair cells utilizes organ cultures of utricles from adult mice. We present the dissection of the adult mouse utricle, and we demonstrate adenovirus-mediated infection of supporting cells in cultured utricles.

解剖成年小鼠的椭圆囊和腺病毒介导的支撑细胞的感染

Hearing loss and balance disturbances are often caused by death of mechanosensory hair cells, which are the receptor cells of the inner ear.  Since there ...

Retrograde Loading of Nerves, Tracts, and Spinal Roots with Fluorescent Dyes

Retrograde labeling of neurons is a standard anatomical method1,2 that has also been used to load calcium and voltage-sensitive dyes into neurons3-6. Generally, the dyes are applied as solid crystals or by local pressure injection using glass pipettes. However, this can result in dilution of the dye and reduced labeling intensity, particularly when several hours are required for dye diffusion. Here we demonstrate a simple and low-cost technique for introducing fluorescent and ion-sensitive dyes into neurons using a polyethylene suction pipette filled with the dye solution. This method offers a reliable way for maintaining a high concentration of the dye in contact with axons throughout the loading procedure.

We describe a simple and low cost technique for introducing high concentration of fluorescent and calcium-sensitive dyes into neurons or any neuronal tract using a polyethylene suction pipette.

逆行神经，大港，并用荧光染料的神经根装载

Retrograde labeling of neurons is a standard anatomical method1,2 that has also been used to load calcium and voltage-sensitive dyes into neurons3-6. ...

Direct Visualization of the Murine Dorsal Cochlear Nucleus for Optogenetic Stimulation of the Auditory Pathway

Investigation into the use of virus-mediated gene transfer to arrest or reverse hearing loss has largely been relegated to the peripheral auditory system. Few studies have examined gene transfer to the central auditory system. The dorsal cochlear nucleus (DCN) of the brainstem, which contains second order neurons of the auditory pathway, is a potential site for gene transfer. In this protocol, a technique for direct and maximal exposure of the murine DCN via a posterior fossa approach is demonstrated. This approach allows for either acute or survival surgery. Following direct visualization of the DCN, a host of experiments are possible, including injection of opsins into the cochlear nucleus and subsequent stimulation by an optical fiber coupled to a blue light laser.&#160;Other neurophysiology experiments, such as electrical stimulation and neural injector tracings are also feasible.&#160;The level of visualization and the duration of stimulation achievable make this approach applicable to a wide range of experiments.

The goal of this protocol is to outline a surgical approach to provide direct access to the dorsal cochlear nucleus in a murine model.

在鼠背耳蜗核的听觉通路的光遗传学刺激直接可视化

Investigation into the use of virus-mediated gene transfer to arrest or reverse hearing loss has largely been relegated to the peripheral auditory system. ...

High-Resolution Quantitative Immunogold Analysis of Membrane Receptors at Retinal Ribbon Synapses

Retinal ganglion cells (RGCs) receive excitatory glutamatergic input from bipolar cells. Synaptic excitation of RGCs is mediated postsynaptically by NMDA receptors (NMDARs) and AMPA receptors (AMPARs). Physiological data have indicated that glutamate receptors at RGCs are expressed not only in postsynaptic but also in perisynaptic or extrasynaptic membrane compartments. However, precise anatomical locations for glutamate receptors at RGC synapses have not been determined. Although a high-resolution quantitative analysis of glutamate receptors at central synapses is widely employed, this approach has had only limited success in the retina. We developed a postembedding immunogold method for analysis of membrane receptors, making it possible to estimate the number, density and variability of these receptors at retinal ribbon synapses. Here we describe the tools, reagents, and the practical steps that are needed for: 1) successful preparation of retinal fixation, 2) freeze-substitution, 3) postembedding immunogold electron microscope (EM) immunocytochemistry and, 4) quantitative visualization of glutamate receptors at ribbon synapses.

The postembedding immunogold method is one of the most effective ways to provide high-resolution analyses of the subcellular localization of specific molecules. Here we describe a protocol to quantitatively analyze glutamate receptors at retinal ribbon synapses.

高分辨率定量免疫膜受体在视网膜带状突触分析

Retinal ganglion cells (RGCs) receive excitatory glutamatergic input from bipolar cells. Synaptic excitation of RGCs is mediated postsynaptically by NMDA ...

Somatosensory Event-related Potentials from Orofacial Skin Stretch Stimulation

Cortical processing associated with orofacial somatosensory function in speech has received limited experimental attention due to the difficulty of providing precise and controlled stimulation. This article introduces a technique for recording somatosensory event-related potentials (ERP) that uses a novel mechanical stimulation method involving skin deformation using a robotic device. Controlled deformation of the facial skin is used to modulate kinesthetic inputs through excitation of cutaneous mechanoreceptors. By combining somatosensory stimulation with electroencephalographic recording, somatosensory evoked responses can be successfully measured at the level of the cortex. Somatosensory stimulation can be combined with the stimulation of other sensory modalities to assess multisensory interactions. For speech, orofacial stimulation is combined with speech sound stimulation to assess the contribution of multi-sensory processing including the effects of timing differences. The ability to precisely control orofacial somatosensory stimulation during speech perception and speech production with ERP recording is an important tool that provides new insight into the neural organization and neural representations for speech.

This paper introduces a method for obtaining somatosensory event-related potentials following orofacial skin stretch stimulation. The current method can be used to evaluate the contribution of somatosensory afferents to both speech production and speech perception.

从口面皮肤牵拉刺激体感事件相关电位

Cortical processing associated with orofacial somatosensory function in speech has received limited experimental attention due to the difficulty of ...

Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume three-dimensionally. While MRI is an extremely sensitive tool for detecting tissue abnormalities, association of signal changes with an underlying pathological process is usually not straightforward. In the central nervous system, for example, inflammation, demyelination, axonal damage, gliosis, and neuronal death may all induce similar findings on MRI. As such, interpretation of MRI scans depends on the context, and radiological-histopathological correlation is therefore of the utmost importance. Unfortunately, traditional pathological sectioning of brain tissue is often imprecise and inconsistent, thus complicating the comparison between histology sections and MRI. This article presents novel methodology for accurately sectioning primate brain tissues and thus allowing precise matching between histology and MRI. The detailed protocol described in this article will assist investigators in applying this method, which relies on the creation of 3D printed brain slicers. Slightly modified, it can be easily implemented for brains of other species, including humans.

The overall goal of this protocol is to accurately align magnetic resonance imaging (MRI) image volumes with histology sections via the creation of customized 3D-printed brain holders and slicer boxes.

利用3D打印技术来合并MRI与组织学:一个大脑切片协议

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume ...

Electroencephalographic, Heart Rate, and Galvanic Skin Response Assessment for an Advertising Perception Study: Application to Antismoking Public Service Announcements

The evaluation of advertising, products, and packaging is traditionally performed through methods based on self-reports and focus groups, but these approaches often appear poorly accurate in scientific terms. Neuroscience is increasingly applied to the investigation of the neurophysiological bases of the perception of and reaction to commercial stimuli to support traditional marketing methods. In this context, a particular sector or marketing is represented by public service announcements (PSAs). The objective of this protocol is to apply electroencephalography (EEG) and autonomic signal analysis to study responses to selected antismoking PSAs. Two EEG indices were employed: the frontal alpha band EEG asymmetry (the Approach Withdrawal (AW) index) and the frontal theta (effort index). Furthermore, the autonomic Emotional Index (EI) was calculated, as derived from the Galvanic Skin Response (GSR) and Heart Rate (HR) signals. The present protocol describes a series of operational and computational steps required to properly estimate, through the aforementioned indices, the emotional and cerebral reaction of a group of subjects towards a selected number of antismoking PSAs. In particular, a campaign characterized by a symbolic communication style (classified as "awarded" on the basis of the prizes received by specialized committees) obtained the highest approach values, as estimated by the AW index. A spot and an image belonging to the same PSA campaign based on the "fear arousing appeal" and with a narrative/experiential communication style (classified as "effective" on the basis of the economical/health-related improvements promoted) reported the lowest and highest effort values, respectively. This is probably due to the complexity of the storytelling (spot) and to the immediateness of the image (a lady who underwent a tracheotomy). Finally, the same "effective" campaign showed the highest EI values, possibly because of the empathy induced by the testimonial and the explicitness of the message.

The following protocol describes a series of operational and computational steps required to properly estimate the emotional and cerebral reaction of a group of subjects towards a selected number of Public Service Announcements (PSAs) against smoking, aired in the USA and Europe during the period between 1998 and 2015.

脑电图, 心率和电皮肤反应评估为广告知觉研究: 应用到禁烟公共服务公告

The evaluation of advertising, products, and packaging is traditionally performed through methods based on self-reports and focus groups, but these ...

A Familiarization Protocol Facilitates the Participation of Children with ASD in Electrophysiological Research

This paper includes a detailed description of a familiarization protocol, which is used as an integral component of a larger research protocol to collect electroencephalography (EEG) data and Event-Related Potentials (ERPs). At present, the systems available for the collection of high-quality EEG/ERP data make significant demands on children with developmental disabilities, such as those with an Autism Spectrum Disorder (ASD). Children with ASD may have difficulty adapting to novel situations, tolerating uncomfortable sensory stimuli, and sitting quietly. This familiarization protocol uses Evidence-Based Practices (EBPs) to increase research participants&#39; knowledge and understanding of the specific activities and steps of the research protocol. The tools in this familiarization protocol are a social narrative, a visual schedule, the Premack principle, role-playing, and modeling. The goal of this familiarization protocol is to increase understanding and agency and to potentially reduce anxiety for child participants, resulting in a greater likelihood of the successful completion of the research protocol for the collection of EEG/ERP data.

Electrophysiological research is an important tool for identifying biomarkers of developmental disorders, including Autism Spectrum Disorders (ASD), but data collection in these populations remains challenging. This work presents a familiarization protocol to accompany research that includes electroencephalography (EEG) to improve the likelihood of collecting EEG data from children with ASD.

熟悉方案有助于儿童参与电生理研究

This paper includes a detailed description of a familiarization protocol, which is used as an integral component of a larger research protocol to collect ...

Isolation of Adult Spinal Cord Nuclei for Massively Parallel Single-nucleus RNA Sequencing

Probing an individual cell&#39;s gene expression enables the identification of cell type and cell state. Single-cell RNA sequencing has emerged as a powerful tool for studying transcriptional profiles of cells, particularly in heterogeneous tissues such as the central nervous system. However, dissociation methods required for single cell sequencing can lead to experimental changes in the gene expression and cell death. Furthermore, these methods are generally restricted to fresh tissue, thus limiting studies on archival and bio-bank material. Single nucleus RNA sequencing (snRNA-Seq) is an appealing alternative for transcriptional studies, given that it accurately identifies cell types, permits the study of tissue that is frozen or difficult to dissociate, and reduces dissociation-induced transcription. Here, we present a high-throughput protocol for rapid isolation of nuclei for downstream snRNA-Seq. This method enables isolation of nuclei from fresh or frozen spinal cord samples and can be combined with two massively parallel droplet encapsulation platforms.

Here, we present a protocol to rapidly isolate high-quality nuclei from the fresh or frozen tissue for downstream massively parallel RNA sequencing. We include detergent-mechanical and hypotonic-mechanical tissue disruption and cell lysis options, both of which can be used for isolation of nuclei.

成人脊髓细胞核在大规模平行单核 RNA 测序中的分离

Probing an individual cell&#39;s gene expression enables the identification of cell type and cell state. Single-cell RNA sequencing has emerged as a ...